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Borkhataria CH, Sharma S, Vaja P, Tank C, Mori D, Patel K, Kyada A. Quality management, ethical considerations, and emerging challenges in genomics and biobanking: A comprehensive review. Clin Chim Acta 2025; 569:120161. [PMID: 39864572 DOI: 10.1016/j.cca.2025.120161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2024] [Revised: 01/23/2025] [Accepted: 01/23/2025] [Indexed: 01/28/2025]
Abstract
The integration of genomics into personalized medicine has the potential to transform healthcare by customizing treatments according to individual genetic profiles. This paper examines the diverse applications of genomics, including the identification of disease susceptibility, improvement of diagnostic methods, optimization of drug therapies, and monitoring of treatment responses. It also explores the expanding global market for genetic testing and the increasing implementation of whole-genome sequencing in clinical practice, with a focus on pilot programs that are advancing comprehensive genomic analysis. Despite challenges such as high costs, data interpretation complexities, and ethical concerns, significant efforts are being made to address these issues. Additionally, the creation of biobanks as vital resources for preserving high-quality biosamples and supporting research highlights the critical need for infrastructure development in genomics. By fostering interdisciplinary collaboration and establishing robust ethical and regulatory frameworks, personalized medicine can ensure equitable access to tailored therapies and enhance health outcomes for everyone. This abstract provides an overview of the transformative potential of genomics and personalized medicine in ushering in a new era of precision healthcare.
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Affiliation(s)
| | - Shweta Sharma
- B K Mody Government Pharmacy College Rajkot Gujarat India
| | - Payal Vaja
- School of Pharmacy, Dr. Subhash University Junagadh Gujarat India
| | | | - Dhaval Mori
- B K Mody Government Pharmacy College Rajkot Gujarat India
| | | | - Ashishkumar Kyada
- Department of Pharmaceutical Sciences, Marwadi University Rajkot Gujarat India
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2
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Keogan A, Nguyen TNQ, Bouzy P, Stone N, Jirstrom K, Rahman A, Gallagher WM, Meade AD. Prediction of post-treatment recurrence in early-stage breast cancer using deep-learning with mid-infrared chemical histopathological imaging. NPJ Precis Oncol 2025; 9:18. [PMID: 39825009 PMCID: PMC11748621 DOI: 10.1038/s41698-024-00772-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Accepted: 11/25/2024] [Indexed: 01/20/2025] Open
Abstract
Predicting long-term recurrence of disease in breast cancer (BC) patients remains a significant challenge for patients with early stage disease who are at low to intermediate risk of relapse as determined using current clinical tools. Prognostic assays which utilize bulk transcriptomics ignore the spatial context of the cellular material and are, therefore, of limited value in the development of mechanistic models. In this study, Fourier-transform infrared (FTIR) chemical images of BC tissue were used to train deep learning models to predict future disease recurrence. A number of deep learning models were employed, with champion models employing two-dimensional and two-dimensional-separable convolutional networks found to have predictive performance of a ROC AUC of approximately 0.64, which compares well to other clinically used prognostic assays in this space. All-digital chemical imaging may therefore provide a label-free platform for histopathological prognosis in breast cancer, opening new horizons for future deployment of these technologies.
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Affiliation(s)
- Abigail Keogan
- Radiation and Environmental Science Centre, Physical to Life Sciences Research Hub, Technological University Dublin, Dublin, Ireland
- School of Physics, Clinical and Optometric Sciences, Technological University Dublin, City Campus, Dublin, Ireland
| | | | - Pascaline Bouzy
- Department of Physics and Astronomy, University of Exeter, Exeter, UK
| | - Nicholas Stone
- Department of Physics and Astronomy, University of Exeter, Exeter, UK
| | - Karin Jirstrom
- Division of Oncology and Therapeutic Pathology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Arman Rahman
- UCD School of Biomolecular and Biomedical Science, UCD Conway Institute, University College Dublin, Dublin, Ireland
- UCD School of Medicine, UCD Conway Institute, University College Dublin, Dublin, Ireland
| | - William M Gallagher
- UCD School of Biomolecular and Biomedical Science, UCD Conway Institute, University College Dublin, Dublin, Ireland
| | - Aidan D Meade
- Radiation and Environmental Science Centre, Physical to Life Sciences Research Hub, Technological University Dublin, Dublin, Ireland.
- School of Physics, Clinical and Optometric Sciences, Technological University Dublin, City Campus, Dublin, Ireland.
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3
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Ramamurthy L. Regulatory Perspectives for Gene Expression-Based Diagnostic Devices. Methods Mol Biol 2025; 2880:345-364. [PMID: 39900769 DOI: 10.1007/978-1-0716-4276-4_18] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2025]
Abstract
Genomic methods are a molecular window into the dysregulation of genes and how they may impact human health and disease. They vary widely in how they interrogate the genetic blueprint including epigenetic changes like DNA methylation, or gene expression. They have become variously available and accessible and have become standard methods in oncology or other diseases. This has led to applications of predictive claims for response or progression as companion diagnostics to anti-oncologic therapies or screening for disease whose symptoms are yet to present. The explosion of these technologies has led to renewed efforts by the US Food and Drug Administration to regulate molecular diagnostics. This chapter describes regulation of genomic diagnostics technologies, both for the innovator and the regulator alike.
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Affiliation(s)
- Lakshman Ramamurthy
- Regulatory Affairs, GRAIL, LLC, Washington, DC, USA.
- CDRH/FDA, Washington, DC, USA.
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van 't Veer LJ, Meershoek-Klein Kranenbarg E, Duijm-de Carpentier M, Van de Velde CJH, Kleijn M, Dreezen C, Menicucci AR, Audeh W, Liefers GJ. Selection of Patients With Early-Stage Breast Cancer for Extended Endocrine Therapy: A Secondary Analysis of the IDEAL Randomized Clinical Trial. JAMA Netw Open 2024; 7:e2447530. [PMID: 39602119 DOI: 10.1001/jamanetworkopen.2024.47530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2024] Open
Abstract
Importance There is a need for biomarkers that predict late recurrence risk and extended endocrine therapy (EET) benefit among patients with early-stage breast cancer (EBC). MammaPrint, a 70-gene expression risk-of-recurrence assay, has been found to project significant EET benefit in patients with assay-classified low-risk tumors. Objective To determine the test's utility in identifying which patients with EBC in the IDEAL (Investigation on the Duration of Extended Adjuvant Letrozole) trial could benefit from 5-year vs 2.5-year letrozole treatment. Design, Setting, and Participants This secondary analysis of the IDEAL randomized clinical trial evaluated postmenopausal women with hormone receptor-positive EBC who were assigned to either 2.5 or 5 years of EET, with 10 years of follow-up after randomization. A 70-gene assay was used to classify tumors as high, low, or ultralow risk. Adverse event (AE) frequency and treatment compliance were evaluated. Statistical analyses were performed from April 2022 to September 2024. Interventions After 5 years of endocrine therapy, patients were randomized to 2.5 or 5 years of EET with letrozole. Main Outcomes and Measures Primary end point was distant recurrence (DR). Cox proportional hazard regression models and likelihood ratios tested the interaction between treatment and gene expression assay. Results Among 515 women included (mean [SD] age at randomization, 59.9 [9.5] years), 265 were in the 2.5-year treatment arm and 250 in the 5-year treatment arm. Of these patients, 223 (43.3%) patients with 70-gene assay-classified low-risk tumors had a significant absolute benefit of 10.1% for DR (hazard ratio, 0.32; 95% CI, 0.12-0.87; P = .03). Treatment interaction was not significant for DR. Of patients with either 70-gene assay-classified high-risk tumors (259 [50.3%]) or ultralow risk tumors (33 [6.4%]), 5 years vs 2.5 years of EET was not associated with improved benefit for DR. As expected, rates of AEs and treatment discontinuation were comparable among the different 70-gene assay risk groups in each treatment arm. Conclusions and Relevance This secondary analysis of the IDEAL trial found that the 70-gene assay identified patients with low-risk tumors who could benefit from 5-year vs 2.5-year EET. These findings suggest that this gene expression assay could go beyond guiding neoadjuvant and adjuvant chemotherapy decisions to informing the optimal duration of adjuvant endocrine therapy. Trial Registration EU Clinical Trials Register Eudra CT: 2006-003958-16.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Gerrit-Jan Liefers
- Department of Surgery, Leiden University Medical Center, Leiden, the Netherlands
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5
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Rastogi P, Bandos H, Lucas PC, van ‘t Veer LJ, Wei JPJ, Geyer CE, Fehrenbacher L, Chia SK, Brufsky AM, Walshe JM, Soori GS, Dakhil SR, Paik S, Swain SM, Menicucci AR, Audeh MW, Wolmark N, Mamounas EP. Utility of the 70-Gene MammaPrint Assay for Prediction of Benefit From Extended Letrozole Therapy in the NRG Oncology/NSABP B-42 Trial. J Clin Oncol 2024; 42:3561-3569. [PMID: 39047219 PMCID: PMC11469649 DOI: 10.1200/jco.23.01995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 04/15/2024] [Accepted: 05/20/2024] [Indexed: 07/27/2024] Open
Abstract
PURPOSE MammaPrint (MP) determines distant metastatic risk and may improve patient selection for extended endocrine therapy (EET). This study examined MP in predicting extended letrozole therapy (ELT) benefit in patients with early-stage breast cancer (BC) from the NSABP B-42 trial. PATIENTS AND METHODS MP was tested in 1,866 patients randomly assigned to receive ELT or placebo. The primary end point was distant recurrence (DR). Secondary end points were disease-free survival (DFS) and BC-free interval (BCFI). Tumors were classified as MP high risk (MP-HR) or low risk (MP-LR). MP-LR tumors were further classified as ultralow risk (MP-UL) or low non-ultralow risk (MP-LNUL). RESULTS There was no statistically significant difference in ELT benefit on DR between MP-HR and MP-LR (interaction P = .38). MP-LR tumors (n = 1,160) exhibited a statistically significant 10-year benefit of 3.7% for DR (hazard ratio [HR], 0.43 [95% CI, 0.25 to 0.74]; P = .002), whereas MP-HR tumors (n = 706) exhibited a nonsignificant 2.4% benefit (HR, 0.65 [95% CI, 0.34 to 1.24]; P = .19). The 10-year ELT benefit was significant for DFS (7.8%) and BCFI (7.0%) for MP-LR tumors, whereas MP-HR tumors did not significantly benefit (interaction DFS: P = .015, BCFI: P = .006). In exploratory analysis, the 10-year ELT benefit was significant and more pronounced in MP-LNUL (n = 908) tumors: 4.0% for DR, 9.5% for DFS, and 7.9% for BCFI; the benefit in MP-UL (n = 252) tumors was not significant: 3% for DR, 1.8% for DFS, and 4.1% for BCFI. CONCLUSION The primary hypothesis of predictive ability of MP on DR was not confirmed. However, the secondary outcomes demonstrated MP was predictive of ELT response and identified a subset of patients with early-stage hormone receptor-positive BC (MP-LR) with improved outcomes from ELT. These data could have important clinical implications in patient selection beyond clinical risk assessment for EET.
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Affiliation(s)
- Priya Rastogi
- UPMC Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, PA
- Magee-Women's Hospital, Pittsburgh, PA
| | - Hanna Bandos
- NRG Oncology SDMC, Pittsburgh, PA
- University of Pittsburgh, School of Public Health, Pittsburgh, PA
| | - Peter C. Lucas
- UPMC Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, PA
| | | | | | - Charles E. Geyer
- UPMC Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, PA
| | | | | | - Adam M. Brufsky
- UPMC Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, PA
- Magee-Women's Hospital, Pittsburgh, PA
| | - Janice M. Walshe
- Cancer Trials Ireland, and St Vincent's University Hospital, Dublin, Ireland
| | | | - Shaker R. Dakhil
- Wichita NCORP, Via Christi Regional Medical Center, and Cancer Center of Kansas, Wichita, KS
| | - Soonmyung Paik
- Theragenbio, Inc, Pankyo, Republic of Korea
- Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Sandra M. Swain
- Georgetown Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC
| | | | | | - Norman Wolmark
- UPMC Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, PA
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Nie Q, Cao H, Yang J, Liu T, Wang B. Integration RNA bulk and single cell RNA sequencing to explore the change of glycolysis-related immune microenvironment and construct prognostic signature in head and neck squamous cell carcinoma. Transl Oncol 2024; 46:102021. [PMID: 38850799 PMCID: PMC11220558 DOI: 10.1016/j.tranon.2024.102021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2023] [Revised: 05/26/2024] [Accepted: 06/01/2024] [Indexed: 06/10/2024] Open
Abstract
BACKGROUND Glycolysis is an indispensable process for tumor cell,but the effect of glycolysis on the prognosis and immune cell infiltration of head and neck squamous cell carcinoma is not clear. METHODS Based on RNA bulk and single cell RNA sequencing data of head and neck squamous cell carcinoma from The Cancer Genome Atlas(TCGA) and GSE195832, the effect of glycolysis level on immune cell infiltration was analyzed. Then, we obtained the prognostic genes related to glycolysis through survival analysis to construct prognostic risk signature. Our sample and GSE65858 datasets are used as external verification datasets to verify the validity of the signature. Finally, we used Western blot and cell function assays to determine the relationship between risk genes and glycolysis and the function of prognostic genes. RESULT The level of glycolysis was related to the prognosis of head and neck tumors (P = 0.0044). The results of immune infiltration analysis of TCGA database showed that high level glycolysis subgroup had less infiltration of macrophages, T cells and monocytes. Results of single cell sequencing analysis validates the above results. Additionally, Five risk genes(MUCL1,TRIML2,RAB3B,SPINK6,IGSF11) were selected to construct signature.Risk score was an independent prognostic factor(P < 0.01). The external validation set also shows the same result. In vitro functional and Western blot assays confirmed that the above five genes affect tumor function and related to the process of glycolysis. CONCLUSION Glycolysis-related risk signatures can be used to predict the prognosis and immune infiltration of head and neck squamous cell carcinoma.
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Affiliation(s)
- Qian Nie
- Department of Otorhinolaryngology, The second Hospital of Hebei Medical University, Hebei 050000, China
| | - Huan Cao
- Department of Otorhinolaryngology, The second Hospital of Hebei Medical University, Hebei 050000, China
| | - Jianwang Yang
- Department of Otorhinolaryngology, The second Hospital of Hebei Medical University, Hebei 050000, China
| | - Tao Liu
- Department of Otorhinolaryngology, The second Hospital of Hebei Medical University, Hebei 050000, China
| | - Baoshan Wang
- Department of Otorhinolaryngology, The second Hospital of Hebei Medical University, Hebei 050000, China.
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Pant A, Anjankar AP, Shende S, Dhok A, Jha RK, Manglaram AV. Early detection of breast cancer through the diagnosis of Nipple Aspirate Fluid (NAF). Clin Proteomics 2024; 21:45. [PMID: 38943056 PMCID: PMC11212179 DOI: 10.1186/s12014-024-09495-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Accepted: 06/05/2024] [Indexed: 07/01/2024] Open
Abstract
The development of breast cancer has been mainly reported in women who have reached the post-menopausal stage; therefore, it is the primary factor responsible for death amongst postmenopausal women. However, if treated on time it has shown a survival rate of 20 years in about two-thirds of women. Cases of breast cancer have also been reported in younger women and the leading cause in them is their lifestyle pattern or they may be carriers of high penetrance mutated genes. Premenopausal women who have breast cancer have been diagnosed with aggressive build-up of tumors and are therefore at more risk of loss of life. Mammography is an effective way to test for breast cancer in women after menopause but is not so effective for premenopausal women or younger females. Imaging techniques like contrast-enhanced MRI can up to some extent indicate the presence of a tumor but it cannot adequately differentiate between benign and malignant tumors. Although the 'omics' strategies continuing for the last 20 years have been helpful at the molecular level in enabling the characteristics and proper understanding of such tumors over long-term longitudinal monitoring. Classification, diagnosis, and prediction of the outcomes have been made through tissue and serum biomarkers but these also fail to diagnose the disease at an early stage. Considerably there is no adequate detection technique present globally that can help early detection and provide adequate specificity, safety, sensitivity, and convenience for the younger and premenopausal women, thereby it becomes necessary to take early measures and build efficient tools and techniques for the same. Through biopsies of nipple aspirate fluid (NAF) biomarker profiling can be performed. It is a naturally secreted fluid from the cells of epithelium found in the breast. Nowadays, home-based liquid biopsy collection kits are also available through which a routine check on breast health can be performed with the help of NAF. Herein, we will review the biomarker screening liquid biopsy, and the new emerging technologies for the examination of cancer at an early stage, especially in premenopausal women.
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Affiliation(s)
- Abhishek Pant
- Department of Biochemistry, Datta Meghe Institute of Higher Education and Research, Wardha Sawangi Meghe, India.
| | - Ashish P Anjankar
- Department of Biochemistry, Datta Meghe Institute of Higher Education and Research, Wardha Sawangi Meghe, India
| | - Sandesh Shende
- Department of Biochemistry, Datta Meghe Institute of Higher Education and Research, Wardha Sawangi Meghe, India
| | - Archana Dhok
- Department of Biochemistry, Datta Meghe Institute of Higher Education and Research, Wardha Sawangi Meghe, India
| | - Roshan Kumar Jha
- Department of Biochemistry, Datta Meghe Institute of Higher Education and Research, Wardha Sawangi Meghe, India
| | - Anjali Vagga Manglaram
- Department of Biochemistry, Datta Meghe Institute of Higher Education and Research, Wardha Sawangi Meghe, India
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8
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Koh J, Jeong D, Park SY, Han D, Kim DS, Kim HY, Kim H, Yang S, Kim S, Ryu HS. Identification of VWA5A as a novel biomarker for inhibiting metastasis in breast cancer by machine-learning based protein prioritization. Sci Rep 2024; 14:2459. [PMID: 38291227 PMCID: PMC10828438 DOI: 10.1038/s41598-024-53015-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 01/25/2024] [Indexed: 02/01/2024] Open
Abstract
Distant metastasis is the leading cause of death in breast cancer (BC). The timing of distant metastasis differs according to subtypes of BCs and there is a need for identification of biomarkers for the prediction of early and late metastasis. To identify biomarker candidates whose abundance level can discriminate metastasis types, we performed a high-throughput proteomics assay using tissue samples from BCs with no metastasis, late metastasis, and early metastasis, processed data with machine learning-based feature selection, and found that low VWA5A could be responsible for shorter duration of metastasis-free interval. Low expression of VWA5A gene in METABRIC cohort was associated with poor survival in BCs, especially in hormone receptor (HR)-positive BCs. In-vitro experiments confirmed tumor suppressive effect of VWA5A on BCs in HR+ and triple-negative BC cell lines. We found that expression of VWA5A can be assessed by immunohistochemistry (IHC) on archival tissue samples. Decreasing nuclear expression of VWA5A was significantly associated with advanced T stage and lymphatic invasion in consecutive BCs of all subtypes. We discovered lower expression of VWA5A as the potential biomarker for metastasis-prone BCs, and our results support the clinical utility of VWA5A IHC, as an adjunctive tools for prognostication of BCs.
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Affiliation(s)
- Jiwon Koh
- Department of Pathology, Seoul National University Hospital, Seoul National University College of Medicine, 101 Daehakro, Seoul, 03080, South Korea
- Cancer Research Institute, Seoul National University, Seoul, South Korea
| | - Dabin Jeong
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, South Korea
| | - Soo Young Park
- Department of Pathology, Seoul National University College of Medicine, Seoul, South Korea
| | - Dohyun Han
- Proteomics Core Facility, Biomedical Research Institute, Seoul National University Hospital, Seoul, South Korea
- Transdisciplinary Department of Medicine & Advanced Technology, Seoul National University Hospital, Seoul, South Korea
| | - Da Sol Kim
- Department of Pathology, Seoul National University College of Medicine, Seoul, South Korea
| | - Ha Yeon Kim
- Department of Pathology, Seoul National University College of Medicine, Seoul, South Korea
| | - Hyeyoon Kim
- Proteomics Core Facility, Biomedical Research Institute, Seoul National University Hospital, Seoul, South Korea
| | - Sohyeon Yang
- Department of Pathology, Seoul National University Hospital, Seoul National University College of Medicine, 101 Daehakro, Seoul, 03080, South Korea
| | - Sun Kim
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, South Korea.
- Department of Computer Science and Engineering, Institute of Engineering Research, Seoul National University, Gwanak-ro 1, Seoul, 08826, South Korea.
| | - Han Suk Ryu
- Department of Pathology, Seoul National University Hospital, Seoul National University College of Medicine, 101 Daehakro, Seoul, 03080, South Korea.
- Cancer Research Institute, Seoul National University, Seoul, South Korea.
- Department of Pathology, Seoul National University College of Medicine, Seoul, South Korea.
- Pharmonoid Co., Ltd., Seoul, South Korea.
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Batra H, Mouabbi JA, Ding Q, Sahin AA, Raso MG. Lobular Carcinoma of the Breast: A Comprehensive Review with Translational Insights. Cancers (Basel) 2023; 15:5491. [PMID: 38001750 PMCID: PMC10670219 DOI: 10.3390/cancers15225491] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 11/09/2023] [Accepted: 11/15/2023] [Indexed: 11/26/2023] Open
Abstract
The second most common breast carcinoma, invasive lobular carcinoma, accounts for approximately 15% of tumors of breast origin. Its incidence has increased in recent times due in part to hormone replacement therapy and improvement in diagnostic modalities. Although believed to arise from the same cell type as their ductal counterpart, invasive lobular carcinomas (ILCs) are a distinct entity with different regulating genetic pathways, characteristic histologies, and different biology. The features most unique to lobular carcinomas include loss of E-Cadherin leading to discohesion and formation of a characteristic single file pattern on histology. Because most of these tumors exhibit estrogen receptor positivity and Her2 neu negativity, endocrine therapy has predominated to treat these tumors. However novel treatments like CDK4/6 inhibitors have shown importance and antibody drug conjugates may be instrumental considering newer categories of Her 2 Low breast tumors. In this narrative review, we explore multiple pathological aspects and translational features of this unique entity. In addition, due to advancement in technologies like spatial transcriptomics and other hi-plex technologies, we have tried to enlist upon the characteristics of the tumor microenvironment and the latest associated findings to better understand the new prospective therapeutic options in the current era of personalized treatment.
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Affiliation(s)
- Harsh Batra
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA;
| | - Jason Aboudi Mouabbi
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA;
| | - Qingqing Ding
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (Q.D.); (A.A.S.)
| | - Aysegul A. Sahin
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (Q.D.); (A.A.S.)
| | - Maria Gabriela Raso
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA;
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10
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Gant TW, Auerbach SS, Von Bergen M, Bouhifd M, Botham PA, Caiment F, Currie RA, Harrill J, Johnson K, Li D, Rouquie D, van Ravenzwaay B, Sistare F, Tralau T, Viant MR, van de Laan JW, Yauk C. Applying genomics in regulatory toxicology: a report of the ECETOC workshop on omics threshold on non-adversity. Arch Toxicol 2023; 97:2291-2302. [PMID: 37296313 PMCID: PMC10322787 DOI: 10.1007/s00204-023-03522-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 05/11/2023] [Indexed: 06/12/2023]
Abstract
In a joint effort involving scientists from academia, industry and regulatory agencies, ECETOC's activities in Omics have led to conceptual proposals for: (1) A framework that assures data quality for reporting and inclusion of Omics data in regulatory assessments; and (2) an approach to robustly quantify these data, prior to interpretation for regulatory use. In continuation of these activities this workshop explored and identified areas of need to facilitate robust interpretation of such data in the context of deriving points of departure (POD) for risk assessment and determining an adverse change from normal variation. ECETOC was amongst the first to systematically explore the application of Omics methods, now incorporated into the group of methods known as New Approach Methodologies (NAMs), to regulatory toxicology. This support has been in the form of both projects (primarily with CEFIC/LRI) and workshops. Outputs have led to projects included in the workplan of the Extended Advisory Group on Molecular Screening and Toxicogenomics (EAGMST) group of the Organisation for Economic Co-operation and Development (OECD) and to the drafting of OECD Guidance Documents for Omics data reporting, with potentially more to follow on data transformation and interpretation. The current workshop was the last in a series of technical methods development workshops, with a sub-focus on the derivation of a POD from Omics data. Workshop presentations demonstrated that Omics data developed within robust frameworks for both scientific data generation and analysis can be used to derive a POD. The issue of noise in the data was discussed as an important consideration for identifying robust Omics changes and deriving a POD. Such variability or "noise" can comprise technical or biological variation within a dataset and should clearly be distinguished from homeostatic responses. Adverse outcome pathways (AOPs) were considered a useful framework on which to assemble Omics methods, and a number of case examples were presented in illustration of this point. What is apparent is that high dimension data will always be subject to varying processing pipelines and hence interpretation, depending on the context they are used in. Yet, they can provide valuable input for regulatory toxicology, with the pre-condition being robust methods for the collection and processing of data together with a comprehensive description how the data were interpreted, and conclusions reached.
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Affiliation(s)
- Timothy W Gant
- United Kingdom Health Security Agency, Harwell Science Campus, Didcot, Oxfordshire, United Kingdom.
- Imperial College London School of Public Health, London, United Kingdom.
| | - Scott S Auerbach
- Division of Translational Toxicology, National Institute of Environmental Health Sciences, RTP, Durham, NC, USA
| | - Martin Von Bergen
- Department for Molecular Systems Biology, Helmholtz Centre for Environmental Research, Leipzig, Germany
| | | | | | - Florian Caiment
- Department of Toxicogenomics, Maastricht University, Maastricht, The Netherlands
| | | | - Joshua Harrill
- Cellular and Molecular Toxicologist, Center for Computational Toxicology and Exposure (CCTE), U.S. Environmental Protection Agency, Durham, NC, USA
| | - Kamin Johnson
- Predictive Safety Center, Corteva Agriscience, Indianapolis, IN, USA
| | - Dongying Li
- National Center for Toxicological Research, U.S. Food and Drug Administration (FDA), 3900 NCTR Road, Jefferson, AR, 72079, USA
| | - David Rouquie
- Bayer SAS, Bayer Crop Science, 355 Rue Dostoïevski, CS 90153, 06906, Valbonne Sophia-Antipolis, France
| | | | | | - Tewes Tralau
- Department of Pesticides Safety, German Federal Institute for Risk Assessment (BfR), Berlin, Germany
| | - Mark R Viant
- School of Biosciences, University of Birmingham, Birmingham, UK
| | | | - Carole Yauk
- Department of Biology, University of Ottawa, Ottawa, Canada
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Reddy SP, Alontaga AY, Welsh EA, Haura EB, Boyle TA, Eschrich SA, Koomen JM. Deciphering Phenotypes from Protein Biomarkers for Translational Research with PIPER. J Proteome Res 2023; 22:2055-2066. [PMID: 37171072 PMCID: PMC11636645 DOI: 10.1021/acs.jproteome.3c00137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM) has widespread clinical use for detection of inborn errors of metabolism, therapeutic drug monitoring, and numerous other applications. This technique detects proteolytic peptides as surrogates for protein biomarker expression, mutation, and post-translational modification in individual clinical assays and in cancer research with highly multiplexed quantitation across biological pathways. LC-MRM for protein biomarkers must be translated from multiplexed research-grade panels to clinical use. LC-MRM panels provide the capability to quantify clinical biomarkers and emerging protein markers to establish the context of tumor phenotypes that provide highly relevant supporting information. An application to visualize and communicate targeted proteomics data will empower translational researchers to move protein biomarker panels from discovery to clinical use. Therefore, we have developed a web-based tool for targeted proteomics that provides pathway-level evaluations of key biological drivers (e.g., EGFR signaling), signature scores (representing phenotypes) (e.g., EMT), and the ability to quantify specific drug targets across a sample cohort. This tool represents a framework for integrating summary information, decision algorithms, and risk scores to support Physician-Interpretable Phenotypic Evaluation in R (PIPER) that can be reused or repurposed by other labs to communicate and interpret their own biomarker panels.
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Affiliation(s)
| | | | - Eric A. Welsh
- Bioinformatics and Biostatistics, Moffitt Cancer Center, Tampa, FL, USA
| | - Eric B. Haura
- Thoracic Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | | | | | - John M. Koomen
- Molecular Oncology, Moffitt Cancer Center, Tampa, FL, USA
- Pathology, Moffitt Cancer Center, Tampa, FL, USA
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12
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Xing T, Hu Y, Wang H, Zou Q. A senescence-related signature for predicting the prognosis of breast cancer: A bioinformatics analysis. Medicine (Baltimore) 2023; 102:e33739. [PMID: 37171330 PMCID: PMC10174404 DOI: 10.1097/md.0000000000033739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Revised: 04/18/2023] [Accepted: 04/20/2023] [Indexed: 05/13/2023] Open
Abstract
Breast cancer is a heterogeneous disease with diverse prognosis and treatment outcomes. Current gene signatures for prognostic prediction are limited to specific subtypes of breast cancer. Cellular senescence is a state of irreversible cell cycle arrest that affects various physiological and pathological processes. This study aimed to develop and validate a senescence-related signature for predicting the prognosis of breast cancer patients. We retrieved 744 senescence-associated genes from the SeneQuest database and analyzed their expression profiles in 2 large datasets of breast cancer patients: The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC). We used univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox regression analysis to derive a 29-gene senescence-related risk signature. The risk signature was significantly associated with disease-specific survival (DSS), clinical characteristics, molecular subtypes, and immune checkpoint genes expressions in both datasets. The risk signature also stratified high-risk and low-risk patients within the same clinical stage and molecular subtype. The risk signature was an independent prognostic factor for breast cancer patients. The senescence-related signature may be a useful biomarker for predicting prognosis and immunotherapy response of breast cancer patients. The risk signature may also guide adjuvant chemotherapy decisions, especially in hormone receptor positive (HR+) and human epidermal growth factor receptor type 2 (HER2)- subtypes.
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Affiliation(s)
- Tengfei Xing
- Department of General Surgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Yiyi Hu
- Institute of Antibiotics, Huashan Hospital, Fudan University, Shanghai, China
| | - Hongying Wang
- Department of General Surgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Qiang Zou
- Department of General Surgery, Huashan Hospital, Fudan University, Shanghai, China
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13
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Chitalia R, Miliotis M, Jahani N, Tastsoglou S, McDonald ES, Belenky V, Cohen EA, Newitt D, Van't Veer LJ, Esserman L, Hylton N, DeMichele A, Hatzigeorgiou A, Kontos D. Radiomic tumor phenotypes augment molecular profiling in predicting recurrence free survival after breast neoadjuvant chemotherapy. COMMUNICATIONS MEDICINE 2023; 3:46. [PMID: 36997615 PMCID: PMC10063641 DOI: 10.1038/s43856-023-00273-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 03/10/2023] [Indexed: 04/01/2023] Open
Abstract
BACKGROUND Early changes in breast intratumor heterogeneity during neoadjuvant chemotherapy may reflect the tumor's ability to adapt and evade treatment. We investigated the combination of precision medicine predictors of genomic and MRI data towards improved prediction of recurrence free survival (RFS). METHODS A total of 100 women from the ACRIN 6657/I-SPY 1 trial were retrospectively analyzed. We estimated MammaPrint, PAM50 ROR-S, and p53 mutation scores from publicly available gene expression data and generated four, voxel-wise 3-D radiomic kinetic maps from DCE-MR images at both pre- and early-treatment time points. Within the primary lesion from each kinetic map, features of change in radiomic heterogeneity were summarized into 6 principal components. RESULTS We identify two imaging phenotypes of change in intratumor heterogeneity (p < 0.01) demonstrating significant Kaplan-Meier curve separation (p < 0.001). Adding phenotypes to established prognostic factors, functional tumor volume (FTV), MammaPrint, PAM50, and p53 scores in a Cox regression model improves the concordance statistic for predicting RFS from 0.73 to 0.79 (p = 0.002). CONCLUSIONS These results demonstrate an important step in combining personalized molecular signatures and longitudinal imaging data towards improved prognosis.
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Affiliation(s)
- Rhea Chitalia
- Department of Bioengineering, University of Pennsylvania, Perelman School of Medicine 3400 Spruce Street, Philadelphia, PA, 19104, USA
- Department of Radiology, Division of Hematology/Oncology, University of Pennsylvania, Perelman School of Medicine 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Marios Miliotis
- Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia, Greece
- DIANA-Lab, Hellenic Pasteur Institute, Athens, Greece
| | - Nariman Jahani
- Department of Radiology, Division of Hematology/Oncology, University of Pennsylvania, Perelman School of Medicine 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Spyros Tastsoglou
- Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia, Greece
- DIANA-Lab, Hellenic Pasteur Institute, Athens, Greece
| | - Elizabeth S McDonald
- Department of Radiology, Division of Hematology/Oncology, University of Pennsylvania, Perelman School of Medicine 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Vivian Belenky
- Department of Radiology, Division of Hematology/Oncology, University of Pennsylvania, Perelman School of Medicine 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Eric A Cohen
- Department of Radiology, Division of Hematology/Oncology, University of Pennsylvania, Perelman School of Medicine 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - David Newitt
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA
| | - Laura J Van't Veer
- Department of Surgery and Oncology, University of California, San Francisco, USA
| | - Laura Esserman
- Department of Surgery and Oncology, University of California, San Francisco, USA
| | - Nola Hylton
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA
| | - Angela DeMichele
- Department of Medicine, Division of Hematology/Oncology, University of Pennsylvania, Perelman School of Medicine 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Artemis Hatzigeorgiou
- Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia, Greece
- DIANA-Lab, Hellenic Pasteur Institute, Athens, Greece
| | - Despina Kontos
- Department of Radiology, Division of Hematology/Oncology, University of Pennsylvania, Perelman School of Medicine 3400 Spruce Street, Philadelphia, PA, 19104, USA.
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14
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Park JH, Kim LS. Somatic Mutations in Breast Cancer: The Tip of the Iceberg. J Breast Cancer 2022; 25:523-524. [PMID: 36579452 PMCID: PMC9807321 DOI: 10.4048/jbc.2022.25.e52] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 12/13/2022] [Accepted: 12/13/2022] [Indexed: 12/23/2022] Open
Affiliation(s)
- Jung Ho Park
- Division of Breast and Endocrine Surgery, Hallym University Sacred Heart Hospital, Anyang, Korea
| | - Lee Su Kim
- Department of Surgery, Chung-Ang University Gwangmyeong Hospital, Gwangmyeong, Korea
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15
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Johansson A, Dar H, van ’t Veer LJ, Tobin NP, Perez-Tenorio G, Nordenskjöld A, Johansson U, Hartman J, Skoog L, Yau C, Benz CC, Esserman LJ, Stål O, Nordenskjöld B, Fornander T, Lindström LS. Twenty-Year Benefit From Adjuvant Goserelin and Tamoxifen in Premenopausal Patients With Breast Cancer in a Controlled Randomized Clinical Trial. J Clin Oncol 2022; 40:4071-4082. [PMID: 35862873 PMCID: PMC9746735 DOI: 10.1200/jco.21.02844] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
PURPOSE To assess the long-term (20-year) endocrine therapy benefit in premenopausal patients with breast cancer. METHODS Secondary analysis of the Stockholm trial (STO-5, 1990-1997) randomly assigning 924 premenopausal patients to 2 years of goserelin (3.6 mg subcutaneously once every 28 days), tamoxifen (40 mg orally once daily), combined goserelin and tamoxifen, or no adjuvant endocrine therapy (control) is performed. Random assignment was stratified by lymph node status; lymph node-positive patients (n = 459) were allocated to standard chemotherapy (cyclophosphamide, methotrexate, and fluorouracil). Primary tumor immunohistochemistry (n = 731) and gene expression profiling (n = 586) were conducted in 2020. The 70-gene signature identified genomic low-risk and high-risk patients. Kaplan-Meier analysis, multivariable Cox proportional hazard regression, and multivariable time-varying flexible parametric modeling assessed the long-term distant recurrence-free interval (DRFI). Swedish high-quality registries allowed a complete follow-up of 20 years. RESULTS In estrogen receptor-positive patients (n = 584, median age 47 years), goserelin, tamoxifen, and the combination significantly improved long-term distant recurrence-free interval compared with control (multivariable hazard ratio [HR], 0.49; 95% CI, 0.32 to 0.75, HR, 0.57; 95% CI, 0.38 to 0.87, and HR, 0.63; 95% CI, 0.42 to 0.94, respectively). Significant goserelin-tamoxifen interaction was observed (P = .016). Genomic low-risk patients (n = 305) significantly benefitted from tamoxifen (HR, 0.24; 95% CI, 0.10 to 0.60), and genomic high-risk patients (n = 158) from goserelin (HR, 0.24; 95% CI, 0.10 to 0.54). Increased risk from the addition of tamoxifen to goserelin was seen in genomic high-risk patients (HR, 3.36; 95% CI, 1.39 to 8.07). Moreover, long-lasting 20-year tamoxifen benefit was seen in genomic low-risk patients, whereas genomic high-risk patients had early goserelin benefit. CONCLUSION This study shows 20-year benefit from 2 years of adjuvant endocrine therapy in estrogen receptor-positive premenopausal patients and suggests differential treatment benefit on the basis of tumor genomic characteristics. Combined goserelin and tamoxifen therapy showed no benefit over single treatment. Long-term follow-up to assess treatment benefit is critical.
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Affiliation(s)
- Annelie Johansson
- Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden,Annelie Johansson, MSc, PhD, Department of Oncology and Pathology, Karolinska Institutet and University Hospital, BioClinicum, Visionsgatan 4, 171 64 Stockholm, Sweden; Twitter: @annelieewa; e-mail:
| | - Huma Dar
- Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Laura J. van ’t Veer
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA
| | - Nicholas P. Tobin
- Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Gizeh Perez-Tenorio
- Department of Biomedical and Clinical Sciences and Department of Oncology, Linköping University, Linköping, Sweden
| | - Anna Nordenskjöld
- Institution of Clinical Sciences, Department of Oncology, Sahlgrenska Academy at Gothenburg University, Gothenburg, Sweden
| | - Ulla Johansson
- Oncological Centre, Karolinska University Hospital, Stockholm, Sweden
| | - Johan Hartman
- Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Lambert Skoog
- Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Christina Yau
- Buck Institute for Research on Aging, Novato, CA,Department of Surgery, University of California San Francisco, San Francisco, CA
| | - Christopher C. Benz
- Buck Institute for Research on Aging, Novato, CA,Department of Medicine, University of California San Francisco, San Francisco, CA
| | - Laura J. Esserman
- Department of Surgery, University of California San Francisco, San Francisco, CA
| | - Olle Stål
- Department of Biomedical and Clinical Sciences and Department of Oncology, Linköping University, Linköping, Sweden
| | - Bo Nordenskjöld
- Department of Biomedical and Clinical Sciences and Department of Oncology, Linköping University, Linköping, Sweden
| | - Tommy Fornander
- Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Linda S. Lindström
- Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden
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Sadurní MB, Meves A. Breslow thickness 2.0: Why gene expression profiling is a step toward better patient selection for sentinel lymph node biopsies. Mod Pathol 2022; 35:1509-1514. [PMID: 35654998 PMCID: PMC9162102 DOI: 10.1038/s41379-022-01101-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Revised: 04/23/2022] [Accepted: 05/05/2022] [Indexed: 12/20/2022]
Abstract
Risk-stratification of cutaneous melanoma is important. Patients want to know what to expect after diagnosis, and physicians need to decide on a treatment plan. Historically, melanoma that had spread beyond the skin and regional lymph nodes was largely incurable, and the only approach to preventing a bad outcome was surgery. Through the seminal work of Alexander Breslow and Donald Morton, a system was devised to carefully escalate surgery based on primary tumor thickness and sentinel lymph node status. Today, we know that prophylactic lymph node dissections do not improve survival, but we continue to appreciate the prognostic implications of a positive sentinel node and the benefits of removing nodal metastases, which facilitates locoregional disease control. However, the question arises whether we can better select patients for sentinel lymph node biopsies (SLNB) as, currently, 85% of these procedures are negative and non-therapeutic. Here, we argue that gene expression profiling (GEP) of the diagnostic biopsy is a valuable step toward better patient selection when combined with reliable clinicopathologic (CP) information such as patient age and Breslow thickness. Recently, a CP-GEP-based classifier of nodal metastasis risk, the Merlin Assay, has become commercially available. While CP-GEP is still being validated in prospective studies, preliminary data suggest that it is an independent predictor of nodal metastasis, outperforming clinicopathological variables. The hunt is on for Breslow thickness 2.0.
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Affiliation(s)
- Mariana B Sadurní
- Department of Dermatology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Alexander Meves
- Department of Dermatology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
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17
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Kuilman MM, Ellappalayam A, Barcaru A, Haan JC, Bhaskaran R, Wehkamp D, Menicucci AR, Audeh WM, Mittempergher L, Glas AM. BluePrint breast cancer molecular subtyping recognizes single and dual subtype tumors with implications for therapeutic guidance. Breast Cancer Res Treat 2022; 195:263-274. [PMID: 35984580 PMCID: PMC9464757 DOI: 10.1007/s10549-022-06698-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 07/27/2022] [Indexed: 12/05/2022]
Abstract
PURPOSE BluePrint (BP) is an 80-gene molecular subtyping test that classifies early-stage breast cancer (EBC) into Basal, Luminal, and HER2 subtypes. In most cases, breast tumors have one dominant subtype, representative of a single activated pathway. However, some tumors show a statistically equal representation of more than one subtype, referred to as dual subtype. This study aims to identify and examine dual subtype tumors by BP to understand their biology and possible implications for treatment guidance. METHODS The BP scores of over 15,000 tumor samples from EBC patients were analyzed, and the differences between the highest and the lowest scoring subtypes were calculated. Based upon the distribution of the differences between BP scores, a threshold was determined for each subtype to identify dual versus single subtypes. RESULTS Approximately 97% of samples had one single activated BluePrint molecular subtype, whereas ~ 3% of samples were classified as BP dual subtype. The most frequently occurring dual subtypes were the Luminal-Basal-type and Luminal-HER2-type. Luminal-Basal-type displays a distinct biology from the Luminal single type and Basal single type. Burstein's classification of the single and dual Basal samples showed that the Luminal-Basal-type is mostly classified as 'luminal androgen receptor' and 'mesenchymal' subtypes, supporting molecular evidence of AR activation in the Luminal-Basal-type tumors. Tumors classified as Luminal-HER2-type resemble features of both Luminal-single-type and HER2-single-type. However, patients with dual Luminal-HER2-type have a lower pathological complete response after receiving HER2-targeted therapies in addition to chemotherapy in comparison with patients with a HER2-single-type. CONCLUSION This study demonstrates that BP identifies tumors with two active functional pathways (dual subtype) with specific transcriptional characteristics and highlights the added value of distinguishing BP dual from single subtypes as evidenced by distinct treatment response rates.
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Affiliation(s)
- Midas M Kuilman
- Department of Research and Development, Agendia N.V, Radarweg 60, 1043 NT, Amsterdam, The Netherlands
| | - Architha Ellappalayam
- Department of Research and Development, Agendia N.V, Radarweg 60, 1043 NT, Amsterdam, The Netherlands
| | - Andrei Barcaru
- Department of Research and Development, Agendia N.V, Radarweg 60, 1043 NT, Amsterdam, The Netherlands
| | - Josien C Haan
- Department of Research and Development, Agendia N.V, Radarweg 60, 1043 NT, Amsterdam, The Netherlands
| | - Rajith Bhaskaran
- Department of Research and Development, Agendia N.V, Radarweg 60, 1043 NT, Amsterdam, The Netherlands
| | - Diederik Wehkamp
- Department of Research and Development, Agendia N.V, Radarweg 60, 1043 NT, Amsterdam, The Netherlands
| | - Andrea R Menicucci
- Department of Medical Affairs, Agendia Inc, 22 Morgan, Irvine, CA, 92618, USA
| | - William M Audeh
- Department of Medical Affairs, Agendia Inc, 22 Morgan, Irvine, CA, 92618, USA
| | - Lorenza Mittempergher
- Department of Research and Development, Agendia N.V, Radarweg 60, 1043 NT, Amsterdam, The Netherlands.
| | - Annuska M Glas
- Department of Research and Development, Agendia N.V, Radarweg 60, 1043 NT, Amsterdam, The Netherlands.
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18
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Vliek SB, Hilbers FS, Jager A, Retèl VP, Bueno de Mesquita JM, Drukker CA, Veltkamp SC, Zeillemaker AM, Rutgers EJ, van Tinteren H, van Harten WH, van 't Veer LJ, van de Vijver MJ, Linn SC. Ten-year follow-up of the observational RASTER study, prospective evaluation of the 70-gene signature in ER-positive, HER2-negative, node-negative, early breast cancer. Eur J Cancer 2022; 175:169-179. [PMID: 36126477 DOI: 10.1016/j.ejca.2022.07.036] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 07/13/2022] [Accepted: 07/14/2022] [Indexed: 11/18/2022]
Abstract
INTRODUCTION Prognostic gene expression signatures can be used in combination with classical clinicopathological factors to guide adjuvant chemotherapy decisions in ER-positive, HER2-negative breast cancer. However, long-term outcome data after introduction of genomic testing in the treatment decision-making process are limited. METHODS In the prospective RASTER study, the tumours of 427 patients with cTanyN0M0 breast cancer were tested to assess the 70-gene signature (MammaPrint). The results were provided to their treating physician to be incorporated in the decision-making on adjuvant systemic therapy. Here, we report the long-term outcome of the 310 patients with ER-positive, HER2-negative tumours by clinical and genomic risk categories at a median follow-up of 10.3 years. RESULTS Among the clinically high-risk patients, 45 (49%) were classified as genomically low risk. In this subgroup, at 10 years, distant recurrence free interval (DRFI) was similar between patients treated with (95.7% [95% CI 87.7-100]) and without (95.5% [95% CI 87.1-100]) chemotherapy. Within the group of clinically low-risk patients, 56 (26%) were classified as genomically high risk. Within the clinically low-risk group, beyond 5 years, a difference emerged between the genomically high- and low-risk subgroup resulting in a 10-year DRFI of 84.3% (95% CI 74.8-95.0) and 93.4% (95% CI 89.5-97.5), respectively. Interestingly, genomic ultralow-risk patients have a 10-year DRFI of 96.7% (95% CI 90.5-100), largely (79%) without systemic therapy. CONCLUSIONS These data confirm that clinically high-risk, genomically low-risk tumours have an excellent outcome in the real-world setting of shared decision-making. Together with the updated results of the MINDACT trial, these data support the use of the MammaPrint, in ER-positive, HER2-negative, node-negative, clinically high-risk breast cancer patients. REGISTRY ISRCTN71917916.
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Affiliation(s)
- Sonja B Vliek
- Department of Medical Oncology, University Medical Center Utrecht, Utrecht, the Netherlands; Department of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Florentine S Hilbers
- Department of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Agnes Jager
- Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
| | - Valesca P Retèl
- Departmentment of Psycosocial Research and Epidemiology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Department of Health Technology and Services Research, University of Twente, Enschede, the Netherlands
| | - Jolien M Bueno de Mesquita
- Department of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Department of Addiction Medicin & Psychiatry, Brijder/Parnassia Group, The Hague, the Netherlands
| | - Caroline A Drukker
- Department of Surgical Oncology, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Sanne C Veltkamp
- Department of Surgery, Amstelland Ziekenhuis, Amstelveen, the Netherlands
| | - Anneke M Zeillemaker
- Department of Surgical Oncology, Alrijne Ziekenhuis, Leiderdorp, the Netherlands
| | - Emiel J Rutgers
- Department of Surgical Oncology, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Harm van Tinteren
- Department of Biometrics, The Netherlands Cancer Institute, Amsterdam, Netherlands; Trial and Data Center, Princes Maxima Centrum, Utrecht, the Netherlands
| | - Wim H van Harten
- Departmentment of Psycosocial Research and Epidemiology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Department of Health Technology and Services Research, University of Twente, Enschede, the Netherlands
| | - Laura J van 't Veer
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, USA
| | - Marc J van de Vijver
- Department of Pathology, Amsterdam University Medical Centers, Amsterdam, the Netherlands
| | - Sabine C Linn
- Department of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Department of Medical Oncology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Department of Pathology, University Medical Center Utrecht, Utrecht, the Netherlands.
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19
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Wang D, Gao S, Qian H, Yuan P, Zhang B. Prognostic Value of Copy Number Alteration Burden in Early-Stage Breast Cancer and the Construction of an 11-Gene Copy Number Alteration Model. Cancers (Basel) 2022; 14:4145. [PMID: 36077687 PMCID: PMC9454926 DOI: 10.3390/cancers14174145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Revised: 08/20/2022] [Accepted: 08/23/2022] [Indexed: 11/16/2022] Open
Abstract
The increasing burden of breast cancer has prompted a wide range of researchers to search for new prognostic markers. Considering that tumor mutation burden (TMB) is low and copy number alteration burden (CNAB) is high in breast cancer, we built a CNAB-based model using a public database and validated it with a Chinese population. We collected formalin-fixed, paraffin-embedded (FFPE) tissue samples from 31 breast cancer patients who were treated between 2010 and 2014 at the National Cancer Center (CICAMS). METABRIC and TCGA data were downloaded via cBioPortal. In total, 2295 patients with early-stage breast cancer were enrolled in the study, including 1427 in the METABRIC cohort, 837 in the TCGA cohort, and 31 in the CICAMS cohort. Based on the ROC curve, we consider 2.2 CNA/MBp as the threshold for the CNAB-high and CNAB-low groupings. In both the TCGA cohort and the CICAMS cohort, CNAB-high had a worse prognosis than CNAB-low. We further simplified this model by establishing a prognostic nomogram for early breast cancer patients by 11 core genes, and this nomogram was highly effective in both the TCGA cohort and the CICAMS cohort. We hope that this model will subsequently help clinicians with prognostic assessments.
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Affiliation(s)
- Dingyuan Wang
- Department of Breast Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Songlin Gao
- Department of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Haili Qian
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Peng Yuan
- Department of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Bailin Zhang
- Department of Breast Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
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Butelmann T, Gu Y, Li A, Tribukait-Riemenschneider F, Hoffmann J, Molazem A, Jaeger E, Pellegrini D, Forget A, Shastri VP. 3D Printed Solutions for Spheroid Engineering and Cancer Research. Int J Mol Sci 2022; 23:ijms23158188. [PMID: 35897762 PMCID: PMC9331260 DOI: 10.3390/ijms23158188] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 07/13/2022] [Accepted: 07/20/2022] [Indexed: 01/03/2023] Open
Abstract
In multicellular organisms, cells are organized in a 3-dimensional framework and this is essential for organogenesis and tissue morphogenesis. Systems to recapitulate 3D cell growth are therefore vital for understanding development and cancer biology. Cells organized in 3D environments can evolve certain phenotypic traits valuable to physiologically relevant models that cannot be accessed in 2D culture. Cellular spheroids constitute an important aspect of in vitro tumor biology and they are usually prepared using the hanging drop method. Here a 3D printed approach is demonstrated to fabricate bespoke hanging drop devices for the culture of tumor cells. The design attributes of the hanging drop device take into account the need for high-throughput, high efficacy in spheroid formation, and automation. Specifically, in this study, custom-fit, modularized hanging drop devices comprising of inserts (Q-serts) were designed and fabricated using fused filament deposition (FFD). The utility of the Q-serts in the engineering of unicellular and multicellular spheroids-synthetic tumor microenvironment mimics (STEMs)—was established using human (cancer) cells. The culture of spheroids was automated using a pipetting robot and bioprinted using a custom bioink based on carboxylated agarose to simulate a tumor microenvironment (TME). The spheroids were characterized using light microscopy and histology. They showed good morphological and structural integrity and had high viability throughout the entire workflow. The systems and workflow presented here represent a user-focused 3D printing-driven spheroid culture platform which can be reliably reproduced in any research environment and scaled to- and on-demand. The standardization of spheroid preparation, handling, and culture should eliminate user-dependent variables, and have a positive impact on translational research to enable direct comparison of scientific findings.
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Affiliation(s)
- Tobias Butelmann
- Institute for Macromolecular Chemistry, University of Freiburg, 79104 Freiburg, Germany; (T.B.); (Y.G.); (A.L.); (F.T.-R.); (J.H.); (A.M.); (E.J.); (D.P.); (A.F.)
| | - Yawei Gu
- Institute for Macromolecular Chemistry, University of Freiburg, 79104 Freiburg, Germany; (T.B.); (Y.G.); (A.L.); (F.T.-R.); (J.H.); (A.M.); (E.J.); (D.P.); (A.F.)
| | - Aijun Li
- Institute for Macromolecular Chemistry, University of Freiburg, 79104 Freiburg, Germany; (T.B.); (Y.G.); (A.L.); (F.T.-R.); (J.H.); (A.M.); (E.J.); (D.P.); (A.F.)
| | - Fabian Tribukait-Riemenschneider
- Institute for Macromolecular Chemistry, University of Freiburg, 79104 Freiburg, Germany; (T.B.); (Y.G.); (A.L.); (F.T.-R.); (J.H.); (A.M.); (E.J.); (D.P.); (A.F.)
| | - Julius Hoffmann
- Institute for Macromolecular Chemistry, University of Freiburg, 79104 Freiburg, Germany; (T.B.); (Y.G.); (A.L.); (F.T.-R.); (J.H.); (A.M.); (E.J.); (D.P.); (A.F.)
| | - Amin Molazem
- Institute for Macromolecular Chemistry, University of Freiburg, 79104 Freiburg, Germany; (T.B.); (Y.G.); (A.L.); (F.T.-R.); (J.H.); (A.M.); (E.J.); (D.P.); (A.F.)
| | - Ellen Jaeger
- Institute for Macromolecular Chemistry, University of Freiburg, 79104 Freiburg, Germany; (T.B.); (Y.G.); (A.L.); (F.T.-R.); (J.H.); (A.M.); (E.J.); (D.P.); (A.F.)
| | - Diana Pellegrini
- Institute for Macromolecular Chemistry, University of Freiburg, 79104 Freiburg, Germany; (T.B.); (Y.G.); (A.L.); (F.T.-R.); (J.H.); (A.M.); (E.J.); (D.P.); (A.F.)
| | - Aurelien Forget
- Institute for Macromolecular Chemistry, University of Freiburg, 79104 Freiburg, Germany; (T.B.); (Y.G.); (A.L.); (F.T.-R.); (J.H.); (A.M.); (E.J.); (D.P.); (A.F.)
| | - V. Prasad Shastri
- Institute for Macromolecular Chemistry, University of Freiburg, 79104 Freiburg, Germany; (T.B.); (Y.G.); (A.L.); (F.T.-R.); (J.H.); (A.M.); (E.J.); (D.P.); (A.F.)
- BIOSS Centre for Biological Signalling Studies, University of Freiburg, 79104 Freiburg, Germany
- Correspondence: or
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21
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Limiting systemic endocrine overtreatment in postmenopausal breast cancer patients with an ultralow classification of the 70-gene signature. Breast Cancer Res Treat 2022; 194:265-278. [PMID: 35587322 PMCID: PMC9239940 DOI: 10.1007/s10549-022-06618-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 04/30/2022] [Indexed: 11/13/2022]
Abstract
Purpose Guidelines recommend endocrine treatment for estrogen receptor-positive (ER+) breast cancers for up to 10 years. Earlier data suggest that the 70-gene signature (MammaPrint) has potential to select patients that have an excellent survival without chemotherapy and limited or no tamoxifen treatment. The aim was to validate the 70-gene signature ultralow-risk classification for endocrine therapy decision making. Methods In the IKA trial, postmenopausal patients with non-metastatic breast cancer had been randomized between no or limited adjuvant tamoxifen treatment without receiving chemotherapy. For this secondary analysis, FFPE tumor material was obtained of ER+HER2− patients with 0–3 positive lymph nodes and tested for the 70-gene signature. Distant recurrence-free interval (DRFI) long-term follow-up data were collected. Kaplan–Meier curves were used to estimate DRFI, stratified by lymph node status, for the three predefined 70-gene signature risk groups. Results A reliable 70-gene signature could be obtained for 135 patients. Of the node-negative and node-positive patients, respectively, 20% and 13% had an ultralow-risk classification. No DRFI events were observed for node-negative patients with an ultralow-risk score in the first 10 years. The 10-year DRFI was 90% and 66% in the low-risk (but not ultralow) and high-risk classified node-negative patients, respectively. Conclusion These survival analyses indicate that the postmenopausal node-negative ER+HER2− patients with an ultralow-risk 70-gene signature score have an excellent 10-year DRFI after surgery with a median of 1 year of endocrine treatment. This is in line with published results of the STO-3-randomized clinical trial and supports the concept that it is possible to reduce the duration of endocrine treatment in selected patients. Supplementary Information The online version contains supplementary material available at 10.1007/s10549-022-06618-z.
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22
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Distinct Gene Expression Profiles of Matched Primary and Metastatic Triple-Negative Breast Cancers. Cancers (Basel) 2022; 14:cancers14102447. [PMID: 35626050 PMCID: PMC9139196 DOI: 10.3390/cancers14102447] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 05/13/2022] [Indexed: 02/05/2023] Open
Abstract
Background: Although triple-negative breast cancer (TNBC) is associated with an increased risk of recurrence and metastasis, the molecular mechanisms underlying metastasis in TNBC remain unknown. To identify transcriptional changes and genes regulating metastatic progression in TNBC, we compared the transcriptomic profiles of primary and matched metastatic tumors using massively parallel RNA sequencing. Methods: We performed gene expression profiling using formalin-fixed paraffin-embedded (FFPE) TNBC tissues of patients from two cohorts: the Zurich cohort (n = 31) and the Stavanger cohort (n = 5). Among the 31 patients in the Zurich cohort, 18 had primary TNBC tumors that did not metastasize, and 13 had primary tumors that metastasized (11 paired primary and locoregional recurrences). The Stavanger cohort included five matched primary and metastatic TNBC tumors. Significantly differentially expressed genes (DEGs; absolute fold change ≥2, p < 0.05) were identified and subjected to functional analyses. We investigated if there was any overlap between DEGs from both the cohorts with epithelial-to-mesenchymal-to-amoeboid transition (EMAT) gene signature. xCell was used to estimate relative fractions of 64 immune and stromal cell types in each RNA-seq sample. Results: In the Zurich cohort, we identified 1624 DEGs between primary TNBC tumors and matched metastatic lesions. xCell analysis revealed a significantly higher immune scores for metastatic lesions compared to paired primary tumors in the Zurich cohort. We also found significant upregulation of three MammaPrint signature genes (HRASLS, TGFB3 and RASSF7) in primary tumors that metastasized compared to primary tumors that remained metastasis-free. In the Stavanger cohort, we identified 818 DEGs between primary tumors and matched metastatic lesions. No significant differences in xCell immune scores were observed. We found that 21 and 14 DEGs from Zurich and Stavanger cohort, respectively, overlapped with the EMAT gene signature. In both cohorts, genes belonging to the MMP, FGF, and PDGFR families were upregulated in primary tumors compared to matched metastatic lesions. Conclusions: Our results suggest that distinct gene expression patterns exist between primary TNBCs and matched metastatic tumors. Further studies are warranted to explore whether these discrete expression profiles underlie or result from disease status.
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23
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Whitworth P, Beitsch PD, Pellicane JV, Baron PL, Lee LA, Dul CL, Nash CH, Murray MK, Richards PD, Gittleman M, Budway R, Rahman RL, Kelemen P, Dooley WC, Rock DT, Cowan K, Lesnikoski BA, Barone JL, Ashikari AY, Dupree B, Wang S, Menicucci AR, Yoder EB, Finn C, Corcoran K, Blumencranz LE, Audeh W. Age-Independent Preoperative Chemosensitivity and 5-Year Outcome Determined by Combined 70- and 80-Gene Signature in a Prospective Trial in Early-Stage Breast Cancer. Ann Surg Oncol 2022; 29:4141-4152. [PMID: 35378634 PMCID: PMC9174138 DOI: 10.1245/s10434-022-11666-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 03/07/2022] [Indexed: 11/18/2022]
Abstract
BACKGROUND The Neoadjuvant Breast Symphony Trial (NBRST) demonstrated the 70-gene risk of distant recurrence signature, MammaPrint, and the 80-gene molecular subtyping signature, BluePrint, precisely determined preoperative pathological complete response (pCR) in breast cancer patients. We report 5-year follow-up results in addition to an exploratory analysis by age and menopausal status. METHODS The observational, prospective NBRST (NCT01479101) included 954 early-stage breast cancer patients aged 18-90 years who received neoadjuvant chemotherapy and had clinical and genomic data available. Chemosensitivity and 5-year distant metastasis-free survival (DMFS) and overall survival (OS) were assessed. In a post hoc subanalysis, results were stratified by age (≤ 50 vs. > 50 years) and menopausal status in patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2-) tumors. RESULTS MammaPrint and BluePrint further classified 23% of tumors to a different subtype compared with immunohistochemistry, with more precise correspondence to pCR rates. Five-year DMFS and OS were highest in MammaPrint Low Risk, Luminal A-type and HER2-type tumors, and lowest in MammaPrint High Risk, Luminal B-type and Basal-type tumors. There was no significant difference in chemosensitivity between younger and older patients with Low-Risk (2.2% vs. 3.8%; p = 0.64) or High-Risk tumors (14.5% vs. 11.5%; p = 0.42), or within each BluePrint subtype; this was similar when stratifying by menopausal status. The 5-year outcomes were comparable by age or menopausal status for each molecular subtype. CONCLUSION Intrinsic preoperative chemosensitivity and long-term outcomes were precisely determined by BluePrint and MammaPrint regardless of patient age, supporting the utility of these assays to inform treatment and surgical decisions in early-stage breast cancer.
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Affiliation(s)
- Pat Whitworth
- Nashville Breast Center, Nashville, TN, USA
- Targeted Medical Education, Cupertino, CA, USA
| | - Peter D Beitsch
- Targeted Medical Education, Cupertino, CA, USA
- Dallas Surgical Group, Dallas, TX, USA
| | | | - Paul L Baron
- Breast and Melanoma Specialist of Charleston, Charleston, SC, USA
- Lenox Hill Hospital/Northwell Health, New York, NY, USA
| | - Laura A Lee
- Comprehensive Cancer Center, Palm Springs, CA, USA
| | - Carrie L Dul
- Ascension St. John Hospital Great Lakes Cancer Management Specialists, Grosse Pointe Woods, MI, USA
| | | | - Mary K Murray
- Akron General Medical Center, Akron, OH, USA
- Cleveland Clinic Akron General, Akron, OH, USA
| | | | | | | | | | - Pond Kelemen
- Ashikari Breast Center, Sleepy Hollow, NY, USA
- Zucker School of Medicine, Hofstra University, Hempstead, NY, USA
| | - William C Dooley
- Breast Institute, University of Oklahoma Health Sciences, Oklahoma City, OK, USA
- Stephenson Cancer Center, Oklahoma City, OK, USA
| | - David T Rock
- Regional Breast Care, Fort Myers, FL, USA
- Genesis Care, Fort Myers, FL, USA
| | - Ken Cowan
- University of Nebraska Medical Center, Omaha, NE, USA
| | - Beth-Ann Lesnikoski
- The Breast Institute at JFK Medical Center, Atlantis, FL, USA
- Baptist MD Anderson Cancer Center, Jacksonville, FL, USA
| | - Julie L Barone
- Exempla Saint Joseph Hospital, Denver, CO, USA
- Vail Health, Vail, CO, USA
| | - Andrew Y Ashikari
- Ashikari Breast Center, Sleepy Hollow, NY, USA
- New York Medical College, Valhalla, NY, USA
- Northwell Health Physician Partners, Mount Kisco, NY, USA
- Phelps and Northern Westchester Hospitals, Westchester, NY, USA
| | - Beth Dupree
- St. Mary Medical Alliance Cancer Specialists, Langhorne, PA, USA
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24
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Ko ER, Henao R, Frankey K, Petzold EA, Isner PD, Jaehne AK, Allen N, Gardner-Gray J, Hurst G, Pflaum-Carlson J, Jayaprakash N, Rivers EP, Wang H, Ugalde I, Amanullah S, Mercurio L, Chun TH, May L, Hickey RW, Lazarus JE, Gunaratne SH, Pallin DJ, Jambaulikar G, Huckins DS, Ampofo K, Jhaveri R, Jiang Y, Komarow L, Evans SR, Ginsburg GS, Tillekeratne LG, McClain MT, Burke TW, Woods CW, Tsalik EL. Prospective Validation of a Rapid Host Gene Expression Test to Discriminate Bacterial From Viral Respiratory Infection. JAMA Netw Open 2022; 5:e227299. [PMID: 35420659 PMCID: PMC9011121 DOI: 10.1001/jamanetworkopen.2022.7299] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 02/24/2022] [Indexed: 12/24/2022] Open
Abstract
Importance Bacterial and viral causes of acute respiratory illness (ARI) are difficult to clinically distinguish, resulting in the inappropriate use of antibacterial therapy. The use of a host gene expression-based test that is able to discriminate bacterial from viral infection in less than 1 hour may improve care and antimicrobial stewardship. Objective To validate the host response bacterial/viral (HR-B/V) test and assess its ability to accurately differentiate bacterial from viral infection among patients with ARI. Design, Setting, and Participants This prospective multicenter diagnostic study enrolled 755 children and adults with febrile ARI of 7 or fewer days' duration from 10 US emergency departments. Participants were enrolled from October 3, 2014, to September 1, 2019, followed by additional enrollment of patients with COVID-19 from March 20 to December 3, 2020. Clinical adjudication of enrolled participants identified 616 individuals as having bacterial or viral infection. The primary analysis cohort included 334 participants with high-confidence reference adjudications (based on adjudicator concordance and the presence of an identified pathogen confirmed by microbiological testing). A secondary analysis of the entire cohort of 616 participants included cases with low-confidence reference adjudications (based on adjudicator discordance or the absence of an identified pathogen in microbiological testing). Thirty-three participants with COVID-19 were included post hoc. Interventions The HR-B/V test quantified the expression of 45 host messenger RNAs in approximately 45 minutes to derive a probability of bacterial infection. Main Outcomes and Measures Performance characteristics for the HR-B/V test compared with clinical adjudication were reported as either bacterial or viral infection or categorized into 4 likelihood groups (viral very likely [probability score <0.19], viral likely [probability score of 0.19-0.40], bacterial likely [probability score of 0.41-0.73], and bacterial very likely [probability score >0.73]) and compared with procalcitonin measurement. Results Among 755 enrolled participants, the median age was 26 years (IQR, 16-52 years); 360 participants (47.7%) were female, and 395 (52.3%) were male. A total of 13 participants (1.7%) were American Indian, 13 (1.7%) were Asian, 368 (48.7%) were Black, 131 (17.4%) were Hispanic, 3 (0.4%) were Native Hawaiian or Pacific Islander, 297 (39.3%) were White, and 60 (7.9%) were of unspecified race and/or ethnicity. In the primary analysis involving 334 participants, the HR-B/V test had sensitivity of 89.8% (95% CI, 77.8%-96.2%), specificity of 82.1% (95% CI, 77.4%-86.6%), and a negative predictive value (NPV) of 97.9% (95% CI, 95.3%-99.1%) for bacterial infection. In comparison, the sensitivity of procalcitonin measurement was 28.6% (95% CI, 16.2%-40.9%; P < .001), the specificity was 87.0% (95% CI, 82.7%-90.7%; P = .006), and the NPV was 87.6% (95% CI, 85.5%-89.5%; P < .001). When stratified into likelihood groups, the HR-B/V test had an NPV of 98.9% (95% CI, 96.1%-100%) for bacterial infection in the viral very likely group and a positive predictive value of 63.4% (95% CI, 47.2%-77.9%) for bacterial infection in the bacterial very likely group. The HR-B/V test correctly identified 30 of 33 participants (90.9%) with acute COVID-19 as having a viral infection. Conclusions and Relevance In this study, the HR-B/V test accurately discriminated bacterial from viral infection among patients with febrile ARI and was superior to procalcitonin measurement. The findings suggest that an accurate point-of-need host response test with high NPV may offer an opportunity to improve antibiotic stewardship and patient outcomes.
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Affiliation(s)
- Emily R. Ko
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
- Hospital Medicine, Division of General Internal Medicine, Duke University School of Medicine, Durham, North Carolina
| | - Ricardo Henao
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
- Department of Biostatistics and Informatics, Duke University, Durham, North Carolina
- Duke Clinical Research Institute, Durham, North Carolina
| | - Katherine Frankey
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
| | - Elizabeth A. Petzold
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
| | - Pamela D. Isner
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
| | - Anja K. Jaehne
- Department of Emergency Medicine, Henry Ford Hospital System, Detroit, Michigan
| | - Nakia Allen
- Department of Pediatrics, Henry Ford Hospital System, Detroit, Michigan
| | - Jayna Gardner-Gray
- Department of Emergency Medicine, Henry Ford Hospital System, Detroit, Michigan
- Department of Medicine, Henry Ford Hospital System, Detroit, Michigan
- Division of Pulmonary and Critical Care Medicine, Henry Ford Hospital System, Detroit, Michigan
| | - Gina Hurst
- Department of Emergency Medicine, Henry Ford Hospital System, Detroit, Michigan
- Department of Medicine, Henry Ford Hospital System, Detroit, Michigan
- Division of Pulmonary and Critical Care Medicine, Henry Ford Hospital System, Detroit, Michigan
| | - Jacqueline Pflaum-Carlson
- Department of Emergency Medicine, Henry Ford Hospital System, Detroit, Michigan
- Department of Medicine, Henry Ford Hospital System, Detroit, Michigan
- Division of Pulmonary and Critical Care Medicine, Henry Ford Hospital System, Detroit, Michigan
| | - Namita Jayaprakash
- Department of Emergency Medicine, Henry Ford Hospital System, Detroit, Michigan
- Division of Pulmonary and Critical Care Medicine, Henry Ford Hospital System, Detroit, Michigan
| | - Emanuel P. Rivers
- Department of Emergency Medicine, Henry Ford Hospital System, Detroit, Michigan
- Department of Surgery, Henry Ford Hospital System, Detroit, Michigan
| | - Henry Wang
- McGovern Medical University of Texas Health, Houston
- Department of Emergency Medicine, The Ohio State University, Columbus
| | - Irma Ugalde
- McGovern Medical University of Texas Health, Houston
| | - Siraj Amanullah
- Department of Emergency Medicine, Alpert Medical School of Brown University, Hasbro Children’s Hospital, Providence, Rhode Island
- Department of Pediatrics, Alpert Medical School of Brown University, Hasbro Children’s Hospital, Providence, Rhode Island
| | - Laura Mercurio
- Department of Emergency Medicine, Alpert Medical School of Brown University, Hasbro Children’s Hospital, Providence, Rhode Island
- Department of Pediatrics, Alpert Medical School of Brown University, Hasbro Children’s Hospital, Providence, Rhode Island
| | - Thomas H. Chun
- Department of Emergency Medicine, Alpert Medical School of Brown University, Hasbro Children’s Hospital, Providence, Rhode Island
- Department of Pediatrics, Alpert Medical School of Brown University, Hasbro Children’s Hospital, Providence, Rhode Island
| | - Larissa May
- Department of Emergency Medicine, University of California, Davis
| | - Robert W. Hickey
- Division of Pediatric Emergency Medicine, UPMC Children’s Hospital of Pittsburgh, Pittsburgh, Pennsylvania
| | - Jacob E. Lazarus
- Division of Infectious Diseases, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Shauna H. Gunaratne
- Division of Infectious Diseases, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Infectious Diseases, Department of Medicine, Columbia University Irving Medical Center, New York, New York
| | - Daniel J. Pallin
- Department of Emergency Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | | | - David S. Huckins
- Department of Emergency Medicine, Newton-Wellesley Hospital, Boston, Massachusetts
| | - Krow Ampofo
- Department of Pediatrics, University of Utah, Salt Lake City
| | - Ravi Jhaveri
- Department of Pediatrics, University of North Carolina at Chapel Hill
- Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Yunyun Jiang
- The Biostatistics Center, George Washington University, Rockville, Maryland
| | - Lauren Komarow
- The Biostatistics Center, George Washington University, Rockville, Maryland
| | - Scott R. Evans
- The Biostatistics Center, George Washington University, Rockville, Maryland
| | - Geoffrey S. Ginsburg
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
| | - L. Gayani Tillekeratne
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, North Carolina
- Medical Service, Durham Veterans Affairs Health Care System, Durham, North Carolina
| | - Micah T. McClain
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, North Carolina
- Medical Service, Durham Veterans Affairs Health Care System, Durham, North Carolina
| | - Thomas W. Burke
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
| | - Christopher W. Woods
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, North Carolina
- Medical Service, Durham Veterans Affairs Health Care System, Durham, North Carolina
| | - Ephraim L. Tsalik
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, North Carolina
- Emergency Medicine Service, Durham Veterans Affairs Health Care System, Durham, North Carolina
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25
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Johansson A, Yiu-Lin Yu N, Iftimi A, Tobin NP, Van't Veer L, Nordenskjöld B, Benz CC, Fornander T, Perez-Tenorio G, Stål O, Esserman LJ, Yau C, Lindström LS. Clinical and Molecular Characteristics of ER-Positive Ultralow Risk Breast Cancer Tumors Identified by the 70-Gene Signature. Int J Cancer 2022; 150:2072-2082. [PMID: 35179782 PMCID: PMC9083187 DOI: 10.1002/ijc.33969] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 01/14/2022] [Accepted: 01/20/2022] [Indexed: 11/09/2022]
Abstract
The metastatic potential of estrogen receptor (ER)-positive breast cancers is heterogenous and distant recurrences occur months to decades after primary diagnosis. We have previously shown that patients with tumors classified as ultralow risk by the 70-gene signature have a minimal long-term risk of fatal breast cancer. Here, we evaluate the previously unexplored underlying clinical and molecular characteristics of ultralow risk tumors in 538 ER-positive patients from the Stockholm tamoxifen randomized trial (STO-3). Out of the 98 ultralow risk tumors, 89% were luminal A molecular subtype, whereas 26% of luminal A tumors were of ultralow risk. Compared with other ER-positive tumors, ultralow risk tumors were significantly (Fisher's test, P<0.05) more likely to be of smaller tumor size, lower grade, progesterone receptor (PR)-positive, human epidermal growth factor 2 (HER2)-negative and have low Ki-67 levels (proliferation-marker). Moreover, ultralow risk tumors showed significantly lower expression scores of multi-gene modules associated with the AKT/mTOR-pathway, proliferation (AURKA), HER2/ERBB2-signaling, IGF1-pathway, PTEN-loss, and immune response (IMMUNE1 and IMMUNE2), and higher expression scores of the PIK3CA-mutation-associated module. Furthermore, 706 genes were significantly (FDR<0.001) differentially expressed in ultralow risk tumors, including lower expression of genes involved in immune response, PI3K/Akt/mTOR-pathway, histones, cell cycle, DNA repair, apoptosis, and higher expression of genes coding for epithelial-to-mesenchymal transition, and homeobox proteins, among others. In conclusion, ultralow risk tumors, associated with minimal long-term risk of fatal disease, differ from other ER-positive tumors, including luminal A molecular subtype tumors. Identification of these characteristics is important to improve our prediction of non-fatal versus fatal breast cancer. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Annelie Johansson
- Department of Oncology and Pathology, Karolinska Institutet and University Hospital, Stockholm, Sweden
| | - Nancy Yiu-Lin Yu
- Department of Biosciences and Nutrition, Karolinska Institutet, Stockholm, Sweden
| | - Adina Iftimi
- Department of Biosciences and Nutrition, Karolinska Institutet, Stockholm, Sweden
| | - Nicholas P Tobin
- Department of Oncology and Pathology, Karolinska Institutet and University Hospital, Stockholm, Sweden
| | - Laura Van't Veer
- Department of Laboratory Medicine, University of California San Francisco, 94115, San Francisco, California, United States.,Department of Pathology, University of California San Francisco, 94115, San Francisco, California, United States
| | - Bo Nordenskjöld
- Department of Biomedical and Clinical Sciences and Department of Oncology, Linköping University, Linköping
| | - Christopher C Benz
- Department of Medicine, University of California San Francisco, 94115, San Francisco, California, United States.,Buck Institute for Research on Aging, 94945, Novato, California, United States
| | - Tommy Fornander
- Department of Oncology and Pathology, Karolinska Institutet and University Hospital, Stockholm, Sweden
| | - Gizeh Perez-Tenorio
- Department of Biomedical and Clinical Sciences and Department of Oncology, Linköping University, Linköping
| | - Olle Stål
- Department of Biomedical and Clinical Sciences and Department of Oncology, Linköping University, Linköping
| | - Laura J Esserman
- Department of Surgery, University of California San Francisco, 94115, San Francisco, California, United States
| | - Christina Yau
- Buck Institute for Research on Aging, 94945, Novato, California, United States.,Department of Surgery, University of California San Francisco, 94115, San Francisco, California, United States
| | - Linda S Lindström
- Department of Oncology and Pathology, Karolinska Institutet and University Hospital, Stockholm, Sweden
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26
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Crozier JA, Barone J, Whitworth P, Cheong A, Maganini R, Tamayo JP, Dauer P, Wang S, Audeh W, Glas AM. High concordance of 70-gene recurrence risk signature and 80-gene molecular subtyping signature between core needle biopsy and surgical resection specimens in early-stage breast cancer. J Surg Oncol 2021; 125:596-602. [PMID: 34964996 PMCID: PMC9305900 DOI: 10.1002/jso.26780] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 12/13/2021] [Accepted: 12/19/2021] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND OBJECTIVES With increased neoadjuvant therapy recommendations for early-stage breast cancer patients due to the COVID-19 pandemic, it is imperative that molecular diagnostic assays provide reliable results from preoperative core needle biopsies (CNB). The study objective was to determine the concordance of MammaPrint and BluePrint results between matched CNB and surgical resection (SR) specimens. METHODS Matched tumor specimens (n = 121) were prospectively collected from women enrolled in the FLEX trial (NCT03053193). Concordance is reported using overall percentage agreement and Cohen's kappa coefficient. Correlation is reported using Pearson correlation coefficient. RESULTS We found good concordance for MammaPrint results between matched tumor samples (90.9%, κ = 0.817), and a very strong correlation of MammaPrint indices (r = 0.94). The concordance of BluePrint subtyping in matched samples was also excellent (98.3%). CONCLUSIONS CNB samples demonstrated high concordance with paired SR samples for MammaPrint risk classification and BluePrint molecular subtyping, suggesting that physicians are provided with accurate prognostic information that can be used to guide therapy decisions.
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Affiliation(s)
- Jennifer A Crozier
- Division of Hematology & Oncology, Baptist MD Anderson, Jacksonville, Florida, USA
| | - Julie Barone
- SCL Health, St. Joseph's Hospital, Denver, Colorado, USA
| | - Pat Whitworth
- Department of Surgery, Nashville Breast Center, Nashville, Tennessee, USA
| | - Abraham Cheong
- Division of Hematology & Oncology, Southeast Georgia Health System, Brunswick, Georgia, USA
| | - Robert Maganini
- Division of Oncology, AMITA Health Alexian Brothers, Elk Grove Village, Illinois, USA
| | - Jose Perez Tamayo
- Department of Radiology, Ogden Regional Medical Center, Ogden, Utah, USA
| | - Patricia Dauer
- Division of Medical Affairs, Agendia Inc., Irvine, California, USA
| | - Shiyu Wang
- Division of Medical Affairs, Agendia Inc., Irvine, California, USA
| | - William Audeh
- Division of Medical Affairs, Agendia Inc., Irvine, California, USA
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Lau R, Du L, Chen E, Fu C, Gould R, Marczyk M, Sinn BV, Layman R, Bedrosian I, Valero V, Symmans WF. Technical Validity of a Customized Assay of Sensitivity to Endocrine Therapy Using Sections from Fixed Breast Cancer Tissue. Clin Chem 2021; 66:934-945. [PMID: 32613237 DOI: 10.1093/clinchem/hvaa105] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2020] [Accepted: 04/20/2020] [Indexed: 12/24/2022]
Abstract
BACKGROUND We translated a multigene expression index to predict sensitivity to endocrine therapy for Stage II-III breast cancer (SET2,3) to hybridization-based expression assays of formalin-fixed paraffin-embedded (FFPE) tissue sections. Here we report the technical validity with FFPE samples, including preanalytical and analytical performance. METHODS We calibrated SET2,3 from microarrays (Affymetrix U133A) of frozen samples to hybridization-based assays of FFPE tissue, using bead-based QuantiGene Plex (QGP) and slide-based NanoString (NS). The following preanalytical and analytical conditions were tested in controlled studies: replicates within and between frozen and fixed samples, age of paraffin blocks, homogenization of fixed sections versus extracted RNA, core biopsy versus surgically resected tumor, technical replicates, precision over 20 weeks, limiting dilution, linear range, and analytical sensitivity. Lin's concordance correlation coefficient (CCC) was used to measure concordance between measurements. RESULTS SET2,3 index was calibrated to use with QGP (CCC 0.94) and NS (CCC 0.93) technical platforms, and was validated in two cohorts of older fixed samples using QGP (CCC 0.72, 0.85) and NS (CCC 0.78, 0.78). QGP assay was concordant using direct homogenization of fixed sections versus purified RNA (CCC 0.97) and between core and surgical sample types (CCC 0.90), with 100% accuracy in technical replicates, 1-9% coefficient of variation over 20 weekly tests, linear range 3.0-11.5 (log2 counts), and analytical sensitivity ≥2.0 (log2 counts). CONCLUSIONS Measurement of the novel SET2,3 assay was technically valid from fixed tumor sections of biopsy or resection samples using simple, inexpensive, hybridization methods, without the need for RNA purification.
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Affiliation(s)
- Rosanna Lau
- Department of Translational Molecular Pathology, UT MD Anderson Cancer Center, Houston, TX
| | - Lili Du
- Department of Translational Molecular Pathology, UT MD Anderson Cancer Center, Houston, TX
| | - Eveline Chen
- Department of Translational Molecular Pathology, UT MD Anderson Cancer Center, Houston, TX
| | - Chunxiao Fu
- Department of Translational Molecular Pathology, UT MD Anderson Cancer Center, Houston, TX
| | - Rebekah Gould
- Department of Translational Molecular Pathology, UT MD Anderson Cancer Center, Houston, TX
| | - Michal Marczyk
- Department of Medicine, Yale University School of Medicine, New Haven, CT.,Data Mining Division, Silesian University of Technology, Gliwice, Poland
| | - Bruno V Sinn
- Department of Pathology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institut of Health, Berlin, Germany
| | - Rachel Layman
- Department of Breast Medical Oncology, UT MD Anderson Cancer Center, Houston, TX
| | - Isabelle Bedrosian
- Department of Breast Surgical Oncology, UT MD Anderson Cancer Center, Houston, TX
| | - Vicente Valero
- Department of Breast Medical Oncology, UT MD Anderson Cancer Center, Houston, TX
| | - W Fraser Symmans
- Department of Translational Molecular Pathology, UT MD Anderson Cancer Center, Houston, TX.,Department of Pathology, UT MD Anderson Cancer Center, Houston, TX
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28
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Kathad U, Kulkarni A, McDermott JR, Wegner J, Carr P, Biyani N, Modali R, Richard JP, Sharma P, Bhatia K. A machine learning-based gene signature of response to the novel alkylating agent LP-184 distinguishes its potential tumor indications. BMC Bioinformatics 2021; 22:102. [PMID: 33653269 PMCID: PMC7923321 DOI: 10.1186/s12859-021-04040-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 02/15/2021] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Non-targeted cytotoxics with anticancer activity are often developed through preclinical stages using response criteria observed in cell lines and xenografts. A panel of the NCI-60 cell lines is frequently the first line to define tumor types that are optimally responsive. Open data on the gene expression of the NCI-60 cell lines, provides a unique opportunity to add another dimension to the preclinical development of such drugs by interrogating correlations with gene expression patterns. Machine learning can be used to reduce the complexity of whole genome gene expression patterns to derive manageable signatures of response. Application of machine learning in early phases of preclinical development is likely to allow a better positioning and ultimate clinical success of molecules. LP-184 is a highly potent novel alkylating agent where the preclinical development is being guided by a dedicated machine learning-derived response signature. We show the feasibility and the accuracy of such a signature of response by accurately predicting the response to LP-184 validated using wet lab derived IC50s on a panel of cell lines. RESULTS We applied our proprietary RADR® platform to an NCI-60 discovery dataset encompassing LP-184 IC50s and publicly available gene expression data. We used multiple feature selection layers followed by the XGBoost regression model and reduced the complexity of 20,000 gene expression values to generate a 16-gene signature leading to the identification of a set of predictive candidate biomarkers which form an LP-184 response gene signature. We further validated this signature and predicted response to an additional panel of cell lines. Considering fold change differences and correlation between actual and predicted LP-184 IC50 values as validation performance measures, we obtained 86% accuracy at four-fold cut-off, and a strong (r = 0.70) and significant (p value 1.36e-06) correlation between actual and predicted LP-184 sensitivity. In agreement with the perceived mechanism of action of LP-184, PTGR1 emerged as the top weighted gene. CONCLUSION Integration of a machine learning-derived signature of response with in vitro assessment of LP-184 efficacy facilitated the derivation of manageable yet robust biomarkers which can be used to predict drug sensitivity with high accuracy and clinical value.
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Affiliation(s)
- Umesh Kathad
- Lantern Pharma, Inc., 1920 McKinney Ave, 7th floor, Dallas, TX, 75201, USA.
| | - Aditya Kulkarni
- Lantern Pharma, Inc., 1920 McKinney Ave, 7th floor, Dallas, TX, 75201, USA
| | | | - Jordan Wegner
- Lantern Pharma, Inc., 1920 McKinney Ave, 7th floor, Dallas, TX, 75201, USA
| | - Peter Carr
- Lantern Pharma, Inc., 1920 McKinney Ave, 7th floor, Dallas, TX, 75201, USA
| | - Neha Biyani
- Lantern Pharma, Inc., 1920 McKinney Ave, 7th floor, Dallas, TX, 75201, USA
| | - Rama Modali
- REPROCELL USA Inc., 9000 Virginia Manor Rd, Ste 207, Beltsville, MD, 20705, USA
| | | | - Panna Sharma
- Lantern Pharma, Inc., 1920 McKinney Ave, 7th floor, Dallas, TX, 75201, USA
| | - Kishor Bhatia
- Lantern Pharma, Inc., 1920 McKinney Ave, 7th floor, Dallas, TX, 75201, USA
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29
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Wu HJ, Chu PY. Recent Discoveries of Macromolecule- and Cell-Based Biomarkers and Therapeutic Implications in Breast Cancer. Int J Mol Sci 2021; 22:ijms22020636. [PMID: 33435254 PMCID: PMC7827149 DOI: 10.3390/ijms22020636] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 12/31/2020] [Accepted: 01/08/2021] [Indexed: 12/13/2022] Open
Abstract
Breast cancer is the most commonly diagnosed cancer type and the leading cause of cancer-related mortality in women worldwide. Breast cancer is fairly heterogeneous and reveals six molecular subtypes: luminal A, luminal B, HER2+, basal-like subtype (ER−, PR−, and HER2−), normal breast-like, and claudin-low. Breast cancer screening and early diagnosis play critical roles in improving therapeutic outcomes and prognosis. Mammography is currently the main commercially available detection method for breast cancer; however, it has numerous limitations. Therefore, reliable noninvasive diagnostic and prognostic biomarkers are required. Biomarkers used in cancer range from macromolecules, such as DNA, RNA, and proteins, to whole cells. Biomarkers for cancer risk, diagnosis, proliferation, metastasis, drug resistance, and prognosis have been identified in breast cancer. In addition, there is currently a greater demand for personalized or precise treatments; moreover, the identification of novel biomarkers to further the development of new drugs is urgently needed. In this review, we summarize and focus on the recent discoveries of promising macromolecules and cell-based biomarkers for the diagnosis and prognosis of breast cancer and provide implications for therapeutic strategies.
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Affiliation(s)
- Hsing-Ju Wu
- Department of Biology, National Changhua University of Education, Changhua 500, Taiwan;
- Research Assistant Center, Show Chwan Memorial Hospital, Changhua 500, Taiwan
- Department of Medical Research, Chang Bing Show Chwan Memorial Hospital, Lukang Town, Changhua County 505, Taiwan
| | - Pei-Yi Chu
- School of Medicine, College of Medicine, Fu Jen Catholic University, New Taipei City 231, Taiwan
- Department of Pathology, Show Chwan Memorial Hospital, No. 542, Sec. 1 Chung-Shan Rd., Changhua 500, Taiwan
- Department of Health Food, Chung Chou University of Science and Technology, Changhua 510, Taiwan
- National Institute of Cancer Research, National Health Research Institutes, Tainan 704, Taiwan
- Correspondence: ; Tel.: +886-975-611-855; Fax: +886-4-7227-116
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30
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Lu Y, Wu S, Cui C, Yu M, Wang S, Yue Y, Liu M, Sun Z. Gene Expression Along with Genomic Copy Number Variation and Mutational Analysis Were Used to Develop a 9-Gene Signature for Estimating Prognosis of COAD. Onco Targets Ther 2020; 13:10393-10408. [PMID: 33116619 PMCID: PMC7569059 DOI: 10.2147/ott.s255590] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 08/19/2020] [Indexed: 12/13/2022] Open
Abstract
PURPOSE This study aims to systematically analyze multi-omics data to explore new prognosis biomarkers in colon adenocarcinoma (COAD). MATERIALS AND METHODS Multi-omics data of COAD and clinical information were obtained from The Cancer Genome Atlas (TCGA). Univariate Cox analysis was used to select genes which significantly related to the overall survival. GISTIC 2.0 software was used to identify significant amplification or deletion. Mutsig 2.0 software was used to identify significant mutation genes. The 9-gene signature was screened by random forest algorithm and Cox regression analysis. GSE17538 dataset was used as an external dataset to verify the predictive ability of 9-gene signature. qPCR was used to detect the expression of 9 genes in clinical specimens. RESULTS A total of 71 candidate genes are obtained by integrating genomic variation, mutation and prognostic data. Then, 9-gene signature was established, which includes HOXD12, RNF25, CBLN3, DOCK3, DNAJB13, PYGO2, CTNNA1, PTPRK, and NAT1. The 9-gene signature is an independent prognostic risk factor for COAD patients. In addition, the signature shows good predicting performance and clinical practicality in training set, testing set and external verification set. The results of qPCR based on clinical samples showed that the expression of HOXD12, RNF25, CBLN3, DOCK3, DNAJB13, and PYGO2 was increased in colon cancer tissues and the expression of CTNNA1, PTPRK, NAT1 was decreased in colon cancer tissues. CONCLUSION In this study, 9-gene signature is constructed as a new prognostic marker to predict the survival of COAD patients.
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Affiliation(s)
- Yiping Lu
- BioBank, The Affiliated Shengjing Hospital, China Medical University, Shenyang, Liaoning 110004, People's Republic of China
| | - Si Wu
- BioBank, The Affiliated Shengjing Hospital, China Medical University, Shenyang, Liaoning 110004, People's Republic of China
| | - Changwan Cui
- BioBank, The Affiliated Shengjing Hospital, China Medical University, Shenyang, Liaoning 110004, People's Republic of China
| | - Miao Yu
- BioBank, The Affiliated Shengjing Hospital, China Medical University, Shenyang, Liaoning 110004, People's Republic of China
| | - Shuang Wang
- BioBank, The Affiliated Shengjing Hospital, China Medical University, Shenyang, Liaoning 110004, People's Republic of China
| | - Yuanyi Yue
- BioBank, The Affiliated Shengjing Hospital, China Medical University, Shenyang, Liaoning 110004, People's Republic of China
| | - Miao Liu
- BioBank, The Affiliated Shengjing Hospital, China Medical University, Shenyang, Liaoning 110004, People's Republic of China
| | - Zhengrong Sun
- BioBank, The Affiliated Shengjing Hospital, China Medical University, Shenyang, Liaoning 110004, People's Republic of China
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31
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Yu F, Quan F, Xu J, Zhang Y, Xie Y, Zhang J, Lan Y, Yuan H, Zhang H, Cheng S, Xiao Y, Li X. Breast cancer prognosis signature: linking risk stratification to disease subtypes. Brief Bioinform 2020; 20:2130-2140. [PMID: 30184043 DOI: 10.1093/bib/bby073] [Citation(s) in RCA: 72] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2017] [Revised: 07/14/2018] [Accepted: 07/28/2018] [Indexed: 01/29/2023] Open
Abstract
Breast cancer is a very complex and heterogeneous disease with variable molecular mechanisms of carcinogenesis and clinical behaviors. The identification of prognostic risk factors may enable effective diagnosis and treatment of breast cancer. In particular, numerous gene-expression-based prognostic signatures were developed and some of them have already been applied into clinical trials and practice. In this study, we summarized several representative gene-expression-based signatures with significant prognostic value and separately assessed their ability of prognosis prediction in their originally targeted populations of breast cancer. Notably, many of the collected signatures were originally designed to predict the outcomes of estrogen receptor positive (ER+) patients or the whole breast cancer cohort; there are no typical signatures used for the prognostic prediction in a specific population of patients with the intrinsic subtype. We thus attempted to identify subtype-specific prognostic signatures via a computational framework for analyzing multi-omics profiles and patient survival. For both the discovery and an independent data set, we confirmed that subtype-specific signature is a strong and significant independent prognostic factor in the corresponding cohort. These results indicate that the subtype-specific prognostic signature has a much higher resolution in the risk stratification, which may lead to improved therapies and precision medicine for patients with breast cancer.
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Affiliation(s)
- Fulong Yu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Fei Quan
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Jinyuan Xu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Yan Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Yi Xie
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Jingyu Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Yujia Lan
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Huating Yuan
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Hongyi Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Shujun Cheng
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.,State Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, Cancer Institute and Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100021, China
| | - Yun Xiao
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Xia Li
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
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32
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Jacob L, Witteveen A, Beumer I, Delahaye L, Wehkamp D, van den Akker J, Snel M, Chan B, Floore A, Bakx N, Brink G, Poncet C, Bogaerts J, Delorenzi M, Piccart M, Rutgers E, Cardoso F, Speed T, van 't Veer L, Glas A. Controlling technical variation amongst 6693 patient microarrays of the randomized MINDACT trial. Commun Biol 2020; 3:397. [PMID: 32719399 PMCID: PMC7385160 DOI: 10.1038/s42003-020-1111-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Accepted: 06/23/2020] [Indexed: 12/12/2022] Open
Abstract
Gene expression data obtained in large studies hold great promises for discovering disease signatures or subtypes through data analysis. It is also prone to technical variation, whose removal is essential to avoid spurious discoveries. Because this variation is not always known and can be confounded with biological signals, its removal is a challenging task. Here we provide a step-wise procedure and comprehensive analysis of the MINDACT microarray dataset. The MINDACT trial enrolled 6693 breast cancer patients and prospectively validated the gene expression signature MammaPrint for outcome prediction. The study also yielded a full-transcriptome microarray for each tumor. We show for the first time in such a large dataset how technical variation can be removed while retaining expected biological signals. Because of its unprecedented size, we hope the resulting adjusted dataset will be an invaluable tool to discover or test gene expression signatures and to advance our understanding of breast cancer.
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Affiliation(s)
- Laurent Jacob
- Université de Lyon, Université Lyon 1, CNRS, Laboratoire de Biométrie et Biologie Évolutive UMR 5558, Villeurbanne, France
| | | | - Inès Beumer
- Agendia NV/Agendia Inc, Amsterdam, The Netherlands
| | | | | | | | | | - Bob Chan
- Agendia NV/Agendia Inc, Amsterdam, The Netherlands
| | - Arno Floore
- Agendia NV/Agendia Inc, Amsterdam, The Netherlands
| | - Niels Bakx
- Agendia NV/Agendia Inc, Amsterdam, The Netherlands
| | - Guido Brink
- Agendia NV/Agendia Inc, Amsterdam, The Netherlands
| | | | | | - Mauro Delorenzi
- University Lausanne, Lausanne, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | | | - Emiel Rutgers
- Netherlands Cancer Institute, Amsterdam, The Netherlands
| | | | - Terence Speed
- Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
| | - Laura van 't Veer
- Agendia NV/Agendia Inc, Amsterdam, The Netherlands.
- Helen Diller Family Comprehensive Cancer Center, University California San Francisco, San Francisco, CA, USA.
| | - Annuska Glas
- Agendia NV/Agendia Inc, Amsterdam, The Netherlands.
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33
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Robinson JE, Greiner TC, Bouska AC, Iqbal J, Cutucache CE. Identification of a Splenic Marginal Zone Lymphoma Signature: Preliminary Findings With Diagnostic Potential. Front Oncol 2020; 10:640. [PMID: 32457837 PMCID: PMC7225304 DOI: 10.3389/fonc.2020.00640] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Accepted: 04/06/2020] [Indexed: 12/12/2022] Open
Abstract
Splenic marginal zone lymphoma (SMZL) is a rare, indolent non-Hodgkin's lymphoma that affects 0. 13 per 100,000 persons annually. Overall survival of SMZL is estimated to reach 8-11 years in most cases, but up to 30% of SMZL cases develop aggressive presentations resulting in greatly diminished time of survival. SMZL presents with a very heterogeneous molecular profile, making diagnosis problematic, and accurate prognosis even less likely. The study herein has identified a potential diagnostic gene expression signature with highly specific predictive utility, coined the SMZL-specific Gene Expression Signature (SSGES). Additionally, five of the most impactful markers identified within the SSGES were selected for a five-protein panel, for further evaluation among control and SMZL patient samples. These markers included EME2, ERCC5, SETBP1, USP24, and ZBTB32. When compared with control spleen and other B-cell lymphoma subtypes, significantly higher expression was noticed in SMZL samples when stained for EME2 and USP24. Additionally, ERCC5, SETBP1, USP24, and ZBTB32 staining displayed indications of prognostic value for SMZL patients. Delineation of the SSGES offers a unique SMZL signature that could provide diagnostic utility for a malignancy that has historically been difficult to identify, and the five-marker protein panel provides additional support for such findings. These results should be further investigated and validated in subsequent molecular investigations of SMZL so it may be potentially incorporated into standard oncology practice for improving the understanding and outlook for SMZL patients.
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Affiliation(s)
- Jacob E Robinson
- Department of Biology, University of Nebraska Omaha, Omaha, NE, United States
| | - Timothy C Greiner
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE, United States
| | - Alyssa C Bouska
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE, United States
| | - Javeed Iqbal
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE, United States
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34
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Nanda R, Liu MC, Yau C, Shatsky R, Pusztai L, Wallace A, Chien AJ, Forero-Torres A, Ellis E, Han H, Clark A, Albain K, Boughey JC, Jaskowiak NT, Elias A, Isaacs C, Kemmer K, Helsten T, Majure M, Stringer-Reasor E, Parker C, Lee MC, Haddad T, Cohen RN, Asare S, Wilson A, Hirst GL, Singhrao R, Steeg K, Asare A, Matthews JB, Berry S, Sanil A, Schwab R, Symmans WF, van ‘t Veer L, Yee D, DeMichele A, Hylton NM, Melisko M, Perlmutter J, Rugo HS, Berry DA, Esserman LJ. Effect of Pembrolizumab Plus Neoadjuvant Chemotherapy on Pathologic Complete Response in Women With Early-Stage Breast Cancer: An Analysis of the Ongoing Phase 2 Adaptively Randomized I-SPY2 Trial. JAMA Oncol 2020; 6:676-684. [PMID: 32053137 PMCID: PMC7058271 DOI: 10.1001/jamaoncol.2019.6650] [Citation(s) in RCA: 491] [Impact Index Per Article: 98.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2019] [Accepted: 12/03/2019] [Indexed: 02/01/2023]
Abstract
Importance Approximately 25% of patients with early-stage breast cancer who receive (neo)adjuvant chemotherapy experience a recurrence within 5 years. Improvements in therapy are greatly needed. Objective To determine if pembrolizumab plus neoadjuvant chemotherapy (NACT) in early-stage breast cancer is likely to be successful in a 300-patient, confirmatory randomized phase 3 neoadjuvant clinical trial. Design, Setting, and Participants The I-SPY2 study is an ongoing open-label, multicenter, adaptively randomized phase 2 platform trial for high-risk, stage II/III breast cancer, evaluating multiple investigational arms in parallel. Standard NACT serves as the common control arm; investigational agent(s) are added to this backbone. Patients with ERBB2 (formerly HER2)-negative breast cancer were eligible for randomization to pembrolizumab between November 2015 and November 2016. Interventions Participants were randomized to receive taxane- and anthracycline-based NACT with or without pembrolizumab, followed by definitive surgery. Main Outcomes and Measures The primary end point was pathologic complete response (pCR). Secondary end points were residual cancer burden (RCB) and 3-year event-free and distant recurrence-free survival. Investigational arms graduated when demonstrating an 85% predictive probability of success in a hypothetical confirmatory phase 3 trial. Results Of the 250 women included in the final analysis, 181 were randomized to the standard NACT control group (median [range] age, 47 [24.77] years). Sixty-nine women (median [range] age, 50 [27-71] years) were randomized to 4 cycles of pembrolizumab in combination with weekly paclitaxel followed by AC; 40 hormone receptor (HR)-positive and 29 triple-negative. Pembrolizumab graduated in all 3 biomarker signatures studied. Final estimated pCR rates, evaluated in March 2017, were 44% vs 17%, 30% vs 13%, and 60% vs 22% for pembrolizumab vs control in the ERBB2-negative, HR-positive/ERBB2-negative, and triple-negative cohorts, respectively. Pembrolizumab shifted the RCB distribution to a lower disease burden for each cohort evaluated. Adverse events included immune-related endocrinopathies, notably thyroid abnormalities (13.0%) and adrenal insufficiency (8.7%). Achieving a pCR appeared predictive of long-term outcome, where patients with pCR following pembrolizumab plus chemotherapy had high event-free survival rates (93% at 3 years with 2.8 years' median follow-up). Conclusions and Relevance When added to standard neoadjuvant chemotherapy, pembrolizumab more than doubled the estimated pCR rates for both HR-positive/ERBB2-negative and triple-negative breast cancer, indicating that checkpoint blockade in women with early-stage, high-risk, ERBB2-negative breast cancer is highly likely to succeed in a phase 3 trial. Pembrolizumab was the first of 10 agents to graduate in the HR-positive/ERBB2-negative signature. Trial Registration ClinicalTrials.gov Identifier: NCT01042379.
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Affiliation(s)
- Rita Nanda
- The University of Chicago, Chicago, Illinois
| | | | | | | | | | | | | | | | | | | | - Amy Clark
- University of Pennsylvania, Philadelphia
| | - Kathy Albain
- Loyola University Chicago Stritch School of Medicine, Maywood, Illinois
| | | | | | | | | | | | | | | | | | | | | | | | | | - Smita Asare
- Quantum Leap Healthcare Collaborative, San Francisco, California
| | - Amy Wilson
- Quantum Leap Healthcare Collaborative, San Francisco, California
| | | | | | | | - Adam Asare
- Quantum Leap Healthcare Collaborative, San Francisco, California
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35
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Mittempergher L, Delahaye LJ, Witteveen AT, Snel MH, Mee S, Chan BY, Dreezen C, Besseling N, Luiten EJ. Performance Characteristics of the BluePrint® Breast Cancer Diagnostic Test. Transl Oncol 2020; 13:100756. [PMID: 32208353 PMCID: PMC7097521 DOI: 10.1016/j.tranon.2020.100756] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Accepted: 02/29/2020] [Indexed: 12/31/2022] Open
Abstract
The analytical performance of a multi-gene diagnostic signature depends on many parameters, including precision, repeatability, reproducibility and intra-tumor heterogeneity. Here we study the analytical performance of the BluePrint 80-gene breast cancer molecular subtyping test through determination of these performance characteristics. BluePrint measures the expression of 80 genes that assess functional pathways which determine the intrinsic breast cancer molecular subtypes (i.e. Luminal-type, HER2-type, Basal-type). Knowing a tumor's dominant functional pathway can help allocate effective treatment to appropriate patients. Here we show that BluePrint is a highly precise and highly reproducible test with correlations above 98% based on the generated index and subtype concordance above 99%. Therefore, BluePrint can be used as a robust and reliable tool to identify breast cancer molecular subtypes.
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Affiliation(s)
- Lorenza Mittempergher
- Research and Development, Agendia N.V., Science Park 406, 1098 XH Amsterdam, The Netherlands
| | - Leonie Jmj Delahaye
- Research and Development, Agendia N.V., Science Park 406, 1098 XH Amsterdam, The Netherlands
| | - Anke T Witteveen
- Research and Development, Agendia N.V., Science Park 406, 1098 XH Amsterdam, The Netherlands
| | - Mireille Hj Snel
- Research and Development, Agendia N.V., Science Park 406, 1098 XH Amsterdam, The Netherlands
| | - Sammy Mee
- Product Support, Agendia Inc., 22 Morgan, Irvine, CA 92780, USA
| | - Bob Y Chan
- Product Support, Agendia Inc., 22 Morgan, Irvine, CA 92780, USA
| | - Christa Dreezen
- Research and Development, Agendia N.V., Science Park 406, 1098 XH Amsterdam, The Netherlands
| | - Naomi Besseling
- Research and Development, Agendia N.V., Science Park 406, 1098 XH Amsterdam, The Netherlands
| | - Ernest Jt Luiten
- Department of Surgery, Amphia Hospital, Molengracht 21, 4818 CK, Breda, The Netherlands
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Goebel C, Louden CL, Mckenna R, Onugha O, Wachtel A, Long T. Blood test shows high accuracy in detecting stage I non-small cell lung cancer. BMC Cancer 2020; 20:137. [PMID: 32085733 PMCID: PMC7035746 DOI: 10.1186/s12885-020-6625-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Accepted: 02/11/2020] [Indexed: 12/18/2022] Open
Abstract
Background In a previous study (Goebel et. al, Cancer Genomics Proteomics 16:229-244, 2019), we identified 33 biomarkers for an early stage (I-II) Non-Small Cell Lung Cancer (NSCLC) test with 90% accuracy, 80.3% sensitivity, and 95.4% specificity. For the current study, we used a narrowed ensemble of 21 biomarkers while retaining similar accuracy in detecting early stage lung cancer. Methods A multiplex platform, 486 human plasma samples, and 21 biomarkers were used to develop and validate our algorithm which detects early stage NSCLC. The training set consisted of 258 human plasma with 79 Stage I-II NSCLC samples. The 21 biomarkers with the statistical model (Lung Cancer Detector Test 1, LCDT1) was then validated using 228 novel samples which included 55 Stage I NSCLC. Results The LCDT1 exhibited 95.6% accuracy, 89.1% sensitivity, and 97.7% specificity in detecting Stage I NSCLC on the blind set. When only NSCLC cancers were analyzed, the specificity increased to 99.1%. Conclusions Compared to current approved clinical methods for diagnosing NSCLC, the LCDT1 greatly improves accuracy while being non-invasive; a simple, cost-effective, early diagnostic blood test should result in expanding access and increase survival rate.
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Affiliation(s)
- Cherylle Goebel
- Goebel Consulting Inc., Mountain View, 780 Montague Expressway, Suite 703, San Jose, CA, 95131, USA.
| | | | - Robert Mckenna
- Providence Saint John's Health Center/John Wayne Cancer Institute, Santa Monica, CA, USA
| | - Osita Onugha
- Providence Saint John's Health Center/John Wayne Cancer Institute, Santa Monica, CA, USA
| | - Andrew Wachtel
- Southern California Institute for Respiratory Diseases, Los Angeles, CA, USA
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Soliman H, Shah V, Srkalovic G, Mahtani R, Levine E, Mavromatis B, Srinivasiah J, Kassar M, Gabordi R, Qamar R, Untch S, Kling HM, Treece T, Audeh W. MammaPrint guides treatment decisions in breast Cancer: results of the IMPACt trial. BMC Cancer 2020; 20:81. [PMID: 32005181 PMCID: PMC6995096 DOI: 10.1186/s12885-020-6534-z] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Accepted: 01/13/2020] [Indexed: 01/06/2023] Open
Abstract
Background Increased usage of genomic risk assessment assays suggests increased reliance on data provided by these assays to guide therapy decisions. The current study aimed to assess the change in treatment decision and physician confidence based on the 70-gene risk of recurrence signature (70-GS, MammaPrint) and the 80-gene molecular subtype signature (80-GS, BluePrint) in early stage breast cancer patients. Methods IMPACt, a prospective, case-only study, enrolled 452 patients between November 2015 and August 2017. The primary objective population included 358 patients with stage I-II, hormone receptor-positive, HER2-negative breast cancer. The recommended treatment plan and physician confidence were captured before and after receiving results for 70-GS and 80-GS. Treatment was started after obtaining results. The distribution of 70-GS High Risk (HR) and Low Risk (LR) patients was evaluated, in addition to the distribution of 80-GS compared to IHC status. Results The 70-GS classified 62.5% (n = 224/358) of patients as LR and 37.5% (n = 134/358) as HR. Treatment decisions were changed for 24.0% (n = 86/358) of patients after receiving 70-GS and 80-GS results. Of the LR patients initially prescribed CT, 71.0% (44/62) had CT removed from their treatment recommendation. Of the HR patients not initially prescribed CT, 65.1% (41/63) had CT added. After receiving 70-GS results, CT was included in 83.6% (n = 112/134) of 70-GS HR patient treatment plans, and 91.5% (n = 205/224) of 70-GS LR patient treatment plans did not include CT. For patients who disagreed with the treatment recommended by their physicians, most (94.1%, n = 16/17) elected not to receive CT when it was recommended. For patients whose physician-recommended treatment plan was discordant with 70-GS results, discordance was significantly associated with age and lymph node status. Conclusions The IMPACt trial showed that treatment plans were 88.5% (n = 317/358) in agreement with 70-GS results, indicating that physicians make treatment decisions in clinical practice based on the 70-GS result. In clinically high risk, 70-GS Low Risk patients, there was a 60.0% reduction in treatment recommendations that include CT. Additionally, physicians reported having greater confidence in treatment decisions for their patients in 72% (n = 258/358) of cases after receiving 70-GS results. Trial registration “Measuring the Impact of MammaPrint on Adjuvant and Neoadjuvant Treatment in Breast Cancer Patients: A Prospective Registry” (NCT02670577) retrospectively registered on Jan 27, 2016.
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Affiliation(s)
| | - Varsha Shah
- Ascension Columbia St. Mary's Hospital, Milwaukee, WI, USA
| | - Gordan Srkalovic
- Herbert-Herman Cancer Center, Sparrow Hospital, Lansing, MI, USA
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Alexandre M, Maran-Gonzalez A, Viala M, Firmin N, D'Hondt V, Gutowski M, Bourgier C, Jacot W, Guiu S. Decision of Adjuvant Systemic Treatment in HR+ HER2- Early Invasive Breast Cancer: Which Biomarkers Could Help? Cancer Manag Res 2019; 11:10353-10373. [PMID: 31849525 PMCID: PMC6912012 DOI: 10.2147/cmar.s221676] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Accepted: 09/21/2019] [Indexed: 11/23/2022] Open
Abstract
The decision to administer adjuvant chemotherapy in treatment of early invasive breast cancer (EBC) is often complex, particularly for hormone receptor-positive (HR+) diseases, and current guidelines often classify these patients in an intermediate-risk group. Several biomarkers are currently available in this indication, in order to obtain additional and more accurate prognostic information compared to classic clinicopathological characteristics and guide the indication of adjuvant chemotherapy, optimizing the efficacy/toxicity ratio. We conducted a systematic review to evaluate the clinical validity and clinical utility of five biomarkers (uPA/PAI-1, OncotypeDX®, MammaPrint®, PAM50, and EndoPredict®) in HR+/HER2- EBC, whatever the nodal status. A total of 89 studies met the inclusion criteria. Even though data currently available confirm the clinical validity of these biomarkers, there is a lack of data regarding clinical utility for most of them. Prospective studies in well-defined populations are needed to integrate these biomarkers in a decision strategy.
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Affiliation(s)
- Marie Alexandre
- Department of Medical Oncology, Institut Régional du Cancer de Montpellier, Montpellier Cedex 5 34298, France
| | - Aurélie Maran-Gonzalez
- Department of Pathology, Institut Régional du Cancer de Montpellier, Montpellier Cedex 5 34298, France
| | - Marie Viala
- Department of Medical Oncology, Institut Régional du Cancer de Montpellier, Montpellier Cedex 5 34298, France
| | - Nelly Firmin
- Department of Medical Oncology, Institut Régional du Cancer de Montpellier, Montpellier Cedex 5 34298, France
| | - Véronique D'Hondt
- Department of Medical Oncology, Institut Régional du Cancer de Montpellier, Montpellier Cedex 5 34298, France.,INSERM U1194 - Institut de Recherche en Cancérologie de Montpellier (IRCM), Montpellier, France.,University of Montpellier, Montpellier,France
| | - Marian Gutowski
- Department of Surgery, Institut Régional du Cancer de Montpellier, Montpellier Cedex 5 34298, France
| | - Céline Bourgier
- INSERM U1194 - Institut de Recherche en Cancérologie de Montpellier (IRCM), Montpellier, France.,Department of Radiation Oncology, Institut Régional du Cancer de Montpellier, Montpellier Cedex 5 34298, France
| | - William Jacot
- Department of Medical Oncology, Institut Régional du Cancer de Montpellier, Montpellier Cedex 5 34298, France.,INSERM U1194 - Institut de Recherche en Cancérologie de Montpellier (IRCM), Montpellier, France.,University of Montpellier, Montpellier,France
| | - Séverine Guiu
- Department of Medical Oncology, Institut Régional du Cancer de Montpellier, Montpellier Cedex 5 34298, France.,INSERM U1194 - Institut de Recherche en Cancérologie de Montpellier (IRCM), Montpellier, France.,University of Montpellier, Montpellier,France
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Rashid NU, Li Q, Yeh JJ, Ibrahim JG. Modeling Between-Study Heterogeneity for Improved Replicability in Gene Signature Selection and Clinical Prediction. J Am Stat Assoc 2019; 115:1125-1138. [PMID: 33012902 DOI: 10.1080/01621459.2019.1671197] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
In the genomic era, the identification of gene signatures associated with disease is of significant interest. Such signatures are often used to predict clinical outcomes in new patients and aid clinical decision-making. However, recent studies have shown that gene signatures are often not replicable. This occurrence has practical implications regarding the generalizability and clinical applicability of such signatures. To improve replicability, we introduce a novel approach to select gene signatures from multiple datasets whose effects are consistently non-zero and account for between-study heterogeneity. We build our model upon some rank-based quantities, facilitating integration over different genomic datasets. A high dimensional penalized Generalized Linear Mixed Model (pGLMM) is used to select gene signatures and address data heterogeneity. We compare our method to some commonly used strategies that select gene signatures ignoring between-study heterogeneity. We provide asymptotic results justifying the performance of our method and demonstrate its advantage in the presence of heterogeneity through thorough simulation studies. Lastly, we motivate our method through a case study subtyping pancreatic cancer patients from four gene expression studies.
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Affiliation(s)
- Naim U Rashid
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, U.S.A.,Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, U.S.A
| | - Quefeng Li
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, U.S.A
| | - Jen Jen Yeh
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, U.S.A.,Department of Surgery, University of North Carolina at Chapel Hill, Chapel Hill, NC, U.S.A.,Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, U.S.A
| | - Joseph G Ibrahim
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, U.S.A
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Slembrouck L, Darrigues L, Laurent C, Mittempergher L, Delahaye LJ, Vanden Bempt I, Vander Borght S, Vliegen L, Sintubin P, Raynal V, Bohec M, Reyes C, Rapinat A, Helsmoortel C, Jongen L, Hoste G, Neven P, Wildiers H, Smeets A, Nevelsteen I, Punie K, Van Nieuwenhuysen E, Han S, Vincent Salomon A, Laas Faron E, Cynober T, Gentien D, Baulande S, Snel MH, Witteveen AT, Neijenhuis S, Glas AM, Reyal F, Floris G. Decentralization of Next-Generation RNA Sequencing-Based MammaPrint® and BluePrint® Kit at University Hospitals Leuven and Curie Institute Paris. Transl Oncol 2019; 12:1557-1565. [PMID: 31513983 PMCID: PMC6742807 DOI: 10.1016/j.tranon.2019.08.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Revised: 08/14/2019] [Accepted: 08/15/2019] [Indexed: 12/17/2022] Open
Abstract
A previously developed and centrally validated MammaPrint® (MP) and BluePrint® (BP) targeted RNA next-generation sequencing (NGS) kit was implemented and validated in two large academic European hospitals. Additionally, breast cancer molecular subtypes by MP and BP RNA sequencing were compared with immunohistochemistry (IHC). Patients with early breast cancer diagnosed at University Hospitals Leuven and Curie Institute Paris were prospectively included between September 2017 and January 2018. Formalin-fixed paraffin-embedded tissue sections were analyzed with MP and BP NGS technology at the beta sites and with both NGS and microarray technology at Agendia. Raw NGS data generated on Illumina MiSeq instruments at the beta sites were interpreted and compared with NGS and microarray data at Agendia. MP and BP NGS molecular subtypes were compared to surrogate IHC breast cancer subtypes. Equivalence of MP and BP indices was determined by Pearson's correlation coefficient. Acceptable limits were defined a priori, based on microarray data generated at Agendia between 2012 and 2016. The concordance, the Negative Percent Agreement and the Positive Percent Agreement were calculated based on the contingency tables and had to be equal to or higher than 90%. Out of 124 included samples, 48% were MP Low and 52% High Risk with microarray. Molecular subtypes were BP luminal, HER2 or basal in 82%, 8% and 10% respectively. Concordance between MP microarray at Agendia and MP NGS at the beta sites was 91.1%. Concordance of MP High and Low Risk classification between NGS at the beta sites and NGS at Agendia was 93.9%. Concordance of MP and BP molecular subtyping using NGS at the beta sites and microarray at Agendia was 89.5%. Concordance between MP and BP NGS subtyping, and IHC was 71.8% and 76.6%, for two IHC surrogate models. The MP/BP NGS kit was successfully validated in a decentralized setting.
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Affiliation(s)
- Laurence Slembrouck
- KU Leuven - University of Leuven, Department of Oncology, B-3000 Leuven, Belgium.
| | - Lauren Darrigues
- Curie Institute, Department of Surgery, Paris Descartes University, F-75248, France
| | - Cecile Laurent
- Curie Institute, Residual Tumor & Response to Treatment Laboratory, RT2Lab, Paris Descartes University, INSERM, U932 Immunity and Cancer, Paris, F-75248, France
| | - Lorenza Mittempergher
- Agendia, Department of Research and Development, Medical Affairs, Amsterdam, The Netherlands
| | - Leonie Jmj Delahaye
- Agendia, Department of Research and Development, Medical Affairs, Amsterdam, The Netherlands
| | - Isabelle Vanden Bempt
- KU Leuven - University of Leuven, University Hospitals Leuven, Department of Human Genetics, B-3000 Leuven, Belgium
| | - Sara Vander Borght
- KU Leuven - University of Leuven, University Hospitals Leuven, Department of Human Genetics, B-3000 Leuven, Belgium; KU Leuven - University Hospitals Leuven, Department of Pathology, B-3000 Leuven, Belgium
| | - Liesbet Vliegen
- KU Leuven - University of Leuven, University Hospitals Leuven, Department of Human Genetics, B-3000 Leuven, Belgium
| | - Petra Sintubin
- KU Leuven - University of Leuven, University Hospitals Leuven, Department of Human Genetics, B-3000 Leuven, Belgium
| | - Virginie Raynal
- Curie Institute, PSL Research University, Genomics of Excellence (ICGex) Platform, Paris, F-75248, France
| | - Mylene Bohec
- Curie Institute, PSL Research University, Genomics of Excellence (ICGex) Platform, Paris, F-75248, France
| | - Cécile Reyes
- Curie Institute, PSL Research University, Translational Research Department, Genomics Platform, Paris, F-75248, France
| | - Audrey Rapinat
- Curie Institute, PSL Research University, Translational Research Department, Genomics Platform, Paris, F-75248, France
| | - Céline Helsmoortel
- KU Leuven - University of Leuven, University Hospitals Leuven, Genomics Core, B-3000 Leuven, Belgium
| | - Lynn Jongen
- KU Leuven - University of Leuven, Department of Oncology, B-3000 Leuven, Belgium
| | - Griet Hoste
- KU Leuven - University of Leuven, University Hospitals Leuven, Department of Gynaecology and Obstetrics, B-3000 Leuven, Belgium
| | - Patrick Neven
- KU Leuven - University of Leuven, Department of Oncology, B-3000 Leuven, Belgium; KU Leuven - University of Leuven, University Hospitals Leuven, Department of Gynaecology and Obstetrics, B-3000 Leuven, Belgium
| | - Hans Wildiers
- KU Leuven - University of Leuven, Department of Oncology, B-3000 Leuven, Belgium; KU Leuven - University of Leuven, University Hospitals Leuven, Department of General Medical Oncology, B-3000 Leuven, Belgium
| | - Ann Smeets
- KU Leuven - University of Leuven, Department of Oncology, B-3000 Leuven, Belgium; KU Leuven - University of Leuven, University Hospitals Leuven, Department of Surgical Oncology, B-3000 Leuven, Belgium
| | - Ines Nevelsteen
- KU Leuven - University of Leuven, Department of Oncology, B-3000 Leuven, Belgium; KU Leuven - University of Leuven, University Hospitals Leuven, Department of Surgical Oncology, B-3000 Leuven, Belgium
| | - Kevin Punie
- KU Leuven - University of Leuven, Department of Oncology, B-3000 Leuven, Belgium; KU Leuven - University of Leuven, University Hospitals Leuven, Department of General Medical Oncology, B-3000 Leuven, Belgium
| | - Els Van Nieuwenhuysen
- KU Leuven - University of Leuven, Department of Oncology, B-3000 Leuven, Belgium; KU Leuven - University of Leuven, University Hospitals Leuven, Department of Gynaecology and Obstetrics, B-3000 Leuven, Belgium
| | - Sileny Han
- KU Leuven - University of Leuven, Department of Oncology, B-3000 Leuven, Belgium; KU Leuven - University of Leuven, University Hospitals Leuven, Department of Gynaecology and Obstetrics, B-3000 Leuven, Belgium
| | | | - Enora Laas Faron
- Curie Institute, Department of Surgery, Paris Descartes University, F-75248, France
| | - Timothé Cynober
- Curie Institute, Administration and General Services, Paris, F-75248, France
| | - David Gentien
- Curie Institute, PSL Research University, Translational Research Department, Genomics Platform, Paris, F-75248, France
| | - Sylvain Baulande
- Curie Institute, PSL Research University, Genomics of Excellence (ICGex) Platform, Paris, F-75248, France
| | - Mireille Hj Snel
- Agendia, Department of Research and Development, Medical Affairs, Amsterdam, The Netherlands
| | - Anke T Witteveen
- Agendia, Department of Research and Development, Medical Affairs, Amsterdam, The Netherlands
| | - Sari Neijenhuis
- Agendia, Department of Research and Development, Medical Affairs, Amsterdam, The Netherlands
| | - Annuska M Glas
- Agendia, Department of Research and Development, Medical Affairs, Amsterdam, The Netherlands
| | - Fabien Reyal
- Curie Institute, Department of Surgery, Paris Descartes University, F-75248, France; Curie Institute, Residual Tumor & Response to Treatment Laboratory, RT2Lab, Paris Descartes University, INSERM, U932 Immunity and Cancer, Paris, F-75248, France
| | - Giuseppe Floris
- KU Leuven - University Hospitals Leuven, Department of Pathology, B-3000 Leuven, Belgium; KU Leuven - University of Leuven, Department of Imaging and Pathology, Laboratory of Translational Cell & Tissue Research
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Panoptic View of Prognostic Models for Personalized Breast Cancer Management. Cancers (Basel) 2019; 11:cancers11091325. [PMID: 31500225 PMCID: PMC6770520 DOI: 10.3390/cancers11091325] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Revised: 09/03/2019] [Accepted: 09/05/2019] [Indexed: 12/12/2022] Open
Abstract
The efforts to personalize treatment for patients with breast cancer have led to a focus on the deeper characterization of genotypic and phenotypic heterogeneity among breast cancers. Traditional pathology utilizes microscopy to profile the morphologic features and organizational architecture of tumor tissue for predicting the course of disease, and is the first-line set of guiding tools for customizing treatment decision-making. Currently, clinicians use this information, combined with the disease stage, to predict patient prognosis to some extent. However, tumoral heterogeneity stubbornly persists among patient subgroups delineated by these clinicopathologic characteristics, as currently used methodologies in diagnostic pathology lack the capability to discern deeper genotypic and subtler phenotypic differences among individual patients. Recent advancements in molecular pathology, however, are poised to change this by joining forces with multiple-omics technologies (genomics, transcriptomics, epigenomics, proteomics, and metabolomics) that provide a wealth of data about the precise molecular complement of each patient's tumor. In addition, these technologies inform the drivers of disease aggressiveness, the determinants of therapeutic response, and new treatment targets in the individual patient. The tumor architecture information can be integrated with the knowledge of the detailed mutational, transcriptional, and proteomic phenotypes of cancer cells within individual tumors to derive a new level of biologic insight that enables powerful, data-driven patient stratification and customization of treatment for each patient, at each stage of the disease. This review summarizes the prognostic and predictive insights provided by commercially available gene expression-based tests and other multivariate or clinical -omics-based prognostic/predictive models currently under development, and proposes a more inclusive multiplatform approach to tackling the challenging heterogeneity of breast cancer to individualize its management. "The future is already here-it's just not very evenly distributed."-William Ford Gibson.
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42
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A plasma microRNA biomarker of melanoma as a personalised assessment of treatment response. Melanoma Res 2019; 29:19-22. [PMID: 30320629 DOI: 10.1097/cmr.0000000000000492] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
New tools for monitoring response to primary melanoma treatment are needed to reduce recurrence rates and patient anxiety. A previously developed plasma-based microRNA signature (MEL38) was measured in four melanoma patient samples obtained before and 12-14 days after treatment (i.e. surgical excision), as well as in two nonmelanoma controls. The value of the MEL38 score and selected individual genes were compared between the time points. The MEL38 scores of the four patients with melanoma became more 'normal like' after tumour excision, with a statistically significant 15% mean reduction. MicroRNAs involved in tumour suppression were upregulated in the postexcision samples and those involved in facilitating treatment resistance and tumour invasion were downregulated. Based on these limited preliminary data, the MEL38 signature may have clinical utility in assessing an individual patient's response to the most common form of melanoma treatment. Additional studies are needed on larger, clinically diverse patient cohorts, sampled over longer periods of time.
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Natarajan L, Pu M, Davies SR, Vickery TL, Nelson SH, Pittman E, Parker BA, Ellis MJ, Flatt SW, Mardis ER, Marinac CR, Pierce JP, Messer K. miRNAs and Long-term Breast Cancer Survival: Evidence from the WHEL Study. Cancer Epidemiol Biomarkers Prev 2019; 28:1525-1533. [PMID: 31186261 DOI: 10.1158/1055-9965.epi-18-1322] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Revised: 02/22/2019] [Accepted: 06/06/2019] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND There is substantial variation in breast cancer survival rates, even among patients with similar clinical and genomic profiles. New biomarkers are needed to improve risk stratification and inform treatment options. Our aim was to identify novel miRNAs associated with breast cancer survival and quantify their prognostic value after adjusting for established clinical factors and genomic markers. METHODS Using the Women's Healthy Eating and Living (WHEL) breast cancer cohort with >15 years of follow-up and archived tumor specimens, we assayed PAM50 mRNAs and 25 miRNAs using the Nanostring nCounter platform. RESULTS We obtained high-quality reads on 1,253 samples (75% of available specimens) and used an existing research-use algorithm to ascertain PAM50 subtypes and risk scores (ROR-PT). We identified miRNAs significantly associated with breast cancer outcomes and then tested these in independent TCGA samples. miRNAs that were also prognostic in TCGA samples were further evaluated in multiple regression Cox models. We also used penalized regression for unbiased discovery. CONCLUSIONS Two miRNAs, 210 and 29c, were associated with breast cancer outcomes in the WHEL and TCGA studies and further improved risk stratification within PAM50 risk groups: 10-year survival was 62% in the node-negative high miR-210-high ROR-PT group versus 75% in the low miR-210- high ROR-PT group. Similar results were obtained for miR-29c. We identified three additional miRNAs, 187-3p, 143-3p, and 205-5p, via penalized regression. IMPACT Our findings suggest that miRNAs might be prognostic for long-term breast cancer survival and might improve risk stratification. Further research to incorporate miRNAs into existing clinicogenomic signatures is needed.
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Affiliation(s)
- Loki Natarajan
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, California. .,Moores Cancer Center, University of California, San Diego, La Jolla, California
| | - Minya Pu
- Moores Cancer Center, University of California, San Diego, La Jolla, California
| | - Sherri R Davies
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri
| | - Tammi L Vickery
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, Missouri
| | - Sandahl H Nelson
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, California
| | - Emily Pittman
- Moores Cancer Center, University of California, San Diego, La Jolla, California
| | - Barbara A Parker
- Moores Cancer Center, University of California, San Diego, La Jolla, California.,Department of Medicine, University of California, San Diego, La Jolla, California
| | - Matthew J Ellis
- Baylor College of Medicine, Lester and Sue Smith Breast Center, Houston, Texas
| | - Shirley W Flatt
- Moores Cancer Center, University of California, San Diego, La Jolla, California
| | - Elaine R Mardis
- Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, Ohio
| | - Catherine R Marinac
- Division of Population Sciences, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.,Department of Epidemiology, T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts
| | - John P Pierce
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, California.,Moores Cancer Center, University of California, San Diego, La Jolla, California
| | - Karen Messer
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, California.,Moores Cancer Center, University of California, San Diego, La Jolla, California
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44
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Mittempergher L, Delahaye LJMJ, Witteveen AT, Spangler JB, Hassenmahomed F, Mee S, Mahmoudi S, Chen J, Bao S, Snel MHJ, Leidelmeijer S, Besseling N, Bergstrom Lucas A, Pabón-Peña C, Linn SC, Dreezen C, Wehkamp D, Chan BY, Bernards R, van 't Veer LJ, Glas AM. MammaPrint and BluePrint Molecular Diagnostics Using Targeted RNA Next-Generation Sequencing Technology. J Mol Diagn 2019; 21:808-823. [PMID: 31173928 DOI: 10.1016/j.jmoldx.2019.04.007] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2018] [Revised: 03/21/2019] [Accepted: 04/16/2019] [Indexed: 01/31/2023] Open
Abstract
Next-generation DNA sequencing is rapidly becoming an indispensable tool for genome-directed cancer diagnostics, but next-generation RNA sequencing (RNA-seq) is currently not standardly used in clinical diagnostics for expression assessment. However, multigene RNA diagnostic assays are used increasingly in the routine diagnosis of early-stage breast cancer. Two of the most widely used tests are currently available only as a central laboratory service, which limits their clinical use. We evaluated the use of RNA-seq as a decentralized method to perform such tests. The MammaPrint and BluePrint RNA-seq tests were found to be equivalent to the clinically validated microarray tests. The RNA-seq tests were highly reproducible when performed in different locations and were stable over time. The MammaPrint RNA-seq test was clinically validated. Our data demonstrate that RNA-seq can be used as a decentralized platform, yielding results substantially equivalent to results derived from the predicate diagnostic device.
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Affiliation(s)
| | | | - Anke T Witteveen
- Research and Development, Agendia NV, Amsterdam, the Netherlands
| | | | | | - Sammy Mee
- Product Support, Agendia Inc., Irvine, California
| | | | - Jiang Chen
- Product Support, Agendia Inc., Irvine, California
| | - Simon Bao
- Product Support, Agendia Inc., Irvine, California
| | | | | | - Naomi Besseling
- Research and Development, Agendia NV, Amsterdam, the Netherlands
| | | | - Carlos Pabón-Peña
- Diagnostics and Genomics Group, Agilent Technologies, Santa Clara, California
| | - Sabine C Linn
- Division of Molecular Pathology and Medical Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Christa Dreezen
- Research and Development, Agendia NV, Amsterdam, the Netherlands
| | - Diederik Wehkamp
- Research and Development, Agendia NV, Amsterdam, the Netherlands
| | - Bob Y Chan
- Product Support, Agendia Inc., Irvine, California
| | - René Bernards
- Research and Development, Agendia NV, Amsterdam, the Netherlands; Division of Molecular Carcinogenesis, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Laura J van 't Veer
- Research and Development, Agendia NV, Amsterdam, the Netherlands; Department of Laboratory Medicine, University of California, San Francisco, San Francisco, California
| | - Annuska M Glas
- Research and Development, Agendia NV, Amsterdam, the Netherlands.
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45
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Estrogen receptor variants in ER-positive basal-type breast cancers responding to therapy like ER-negative breast cancers. NPJ Breast Cancer 2019; 5:15. [PMID: 31016233 PMCID: PMC6472385 DOI: 10.1038/s41523-019-0109-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Accepted: 03/22/2019] [Indexed: 01/05/2023] Open
Abstract
Immunohistochemically ER-positive HER2-negative (ER+HER2−) breast cancers are classified clinically as Luminal-type. We showed previously that molecular subtyping using the 80-gene signature (80-GS) reclassified a subset of ER+HER2− tumors to molecular Basal-type. We report here that molecular reclassification is associated with expression of dominant-negative ER variants and evaluate response to neoadjuvant therapy and outcome in the prospective neoadjuvant NBRST study (NCT01479101). The 80-GS reclassified 91 of 694 (13.1%) immunohistochemically Luminal-type tumors to molecular Basal-type. Importantly, all 91 discordant tumors were classified as high-risk, whereas only 66.9% of ER+/Luminal-type tumors were classified at high-risk for disease recurrence (i.e., Luminal B) (P < 0.001). ER variant mRNA (ER∆3, ER∆7, and ERα-36) analysis performed on 84 ER+/Basal tumors and 48 ER+/Luminal B control tumors revealed that total ER mRNA was significantly lower in ER+/Basal tumors. The relative expression of ER∆7/total ER was significantly higher in ER+/Basal tumors compared to ER+/Luminal B tumors (P < 0.001). ER+/Basal patients had similar pathological complete response (pCR) rates following neoadjuvant chemotherapy as ER−/Basal patients (34.3 vs. 37.6%), and much higher than ER+/Luminal A or B patients (2.3 and 5.8%, respectively). Furthermore, 3-year distant metastasis-free interval (DMFI) for ER+/Basal patients was 65.8%, significantly lower than 96.3 and 88.9% for ER+/Luminal A and B patients, respectively, (log-rank P < 0.001). Significantly lower total ER mRNA and increased relative ER∆7 dominant-negative variant expression provides a rationale why ER+/Basal breast cancers are molecularly ER-negative. Identification of this substantial subset of patients is clinically relevant because of the higher pCR rate to neoadjuvant chemotherapy and correlation with clinical outcome.
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46
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Chen L, Luo Y, Wang G, Qian K, Qian G, Wu CL, Dan HC, Wang X, Xiao Y. Prognostic value of a gene signature in clear cell renal cell carcinoma. J Cell Physiol 2018; 234:10324-10335. [PMID: 30417359 DOI: 10.1002/jcp.27700] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Accepted: 10/15/2018] [Indexed: 12/29/2022]
Abstract
Renal cancer is a common urogenital system malignance. Novel biomarkers could provide more and more critical information on tumor features and patients' prognosis. Here, we performed an integrated analysis on the discovery set and established a three-gene signature to predict the prognosis for clear cell renal cell carcinoma (ccRCC). By constructing a LASSO Cox regression model, a 3-messenger RNA (3-mRNA) signature was identified. Based on the 3-mRNA signature, we divided patients into high- and low-risk groups, and validated this by using three other data sets. In the discovery set, this signature could successfully distinguish between the high- and low-risk patients (hazard ratio (HR), 2.152; 95% confidence interval (CI),1.509-3.069; p < 0.0001). Analysis of internal and two external validation sets yielded consistent results (internal: HR, 2.824; 95% CI, 1.601-4.98; p < 0.001; GSE29609: HR, 3.002; 95% CI, 1.113-8.094; p = 0.031; E-MTAB-3267: HR, 2.357; 95% CI, 1.243-4.468; p = 0.006). Time-dependent receiver operating characteristic (ROC) analysis indicated that the area under the ROC curve at 5 years was 0.66 both in the discovery and internal validation set, while the two external validation sets also suggested good performance of the 3-mRNA signature. Besides that, a nomogram was built and the calibration plots and decision curve analysis indicated the good performance and clinical utility of the nomogram. In conclusion, this 3-mRNA classifier proved to be a useful tool for prognostic evaluation and could facilitate personalized management of ccRCC patients.
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Affiliation(s)
- Liang Chen
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Yongwen Luo
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Gang Wang
- Department of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China.,Laboratory of Precision Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Kaiyu Qian
- Department of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China.,Laboratory of Precision Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Guofeng Qian
- Department of Endocrinology, The First Affiliated Hospital of Zhejiang University, Hangzhou, China
| | - Chin-Lee Wu
- Department of Urology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Han C Dan
- Greenebaum Cancer Center, School of Medicine, University of Maryland, Baltimore, Maryland
| | - Xinghuan Wang
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Yu Xiao
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.,Department of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China.,Laboratory of Precision Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
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47
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Jing A, Vizeacoumar FS, Parameswaran S, Haave B, Cunningham CE, Wu Y, Arnold R, Bonham K, Freywald A, Han J, Vizeacoumar FJ. Expression-based analyses indicate a central role for hypoxia in driving tumor plasticity through microenvironment remodeling and chromosomal instability. NPJ Syst Biol Appl 2018; 4:38. [PMID: 30374409 PMCID: PMC6200725 DOI: 10.1038/s41540-018-0074-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2018] [Revised: 09/25/2018] [Accepted: 09/27/2018] [Indexed: 12/27/2022] Open
Abstract
Can transcriptomic alterations drive the evolution of tumors? We asked if changes in gene expression found in all patients arise earlier in tumor development and can be relevant to tumor progression. Our analyses of non-mutated genes from the non-amplified regions of the genome of 158 triple-negative breast cancer (TNBC) cases identified 219 exclusively expression-altered (EEA) genes that may play important role in TNBC. Phylogenetic analyses of these genes predict a "punctuated burst" of multiple gene upregulation events occurring at early stages of tumor development, followed by minimal subsequent changes later in tumor progression. Remarkably, this punctuated burst of expressional changes is instigated by hypoxia-related molecular events, predominantly in two groups of genes that control chromosomal instability (CIN) and those that remodel tumor microenvironment (TME). We conclude that alterations in the transcriptome are not stochastic and that early-stage hypoxia induces CIN and TME remodeling to permit further tumor evolution.
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Affiliation(s)
- Anqi Jing
- Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB T6G2R3 Canada
| | - Frederick S. Vizeacoumar
- Department of Pathology and Laboratory Medicine, College of Medicine, University of Saskatchewan, Saskatoon, SK S7N 5E5 Canada
| | - Sreejit Parameswaran
- Department of Pathology and Laboratory Medicine, College of Medicine, University of Saskatchewan, Saskatoon, SK S7N 5E5 Canada
| | - Bjorn Haave
- Department of Pathology and Laboratory Medicine, College of Medicine, University of Saskatchewan, Saskatoon, SK S7N 5E5 Canada
| | - Chelsea E. Cunningham
- Department of Biochemistry, Cancer Cluster, College of Medicine, University of Saskatchewan, Saskatoon, SK S7N 5E5 Canada
| | - Yuliang Wu
- Department of Biochemistry, Cancer Cluster, College of Medicine, University of Saskatchewan, Saskatoon, SK S7N 5E5 Canada
| | - Roland Arnold
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Keith Bonham
- Department of Biochemistry, Cancer Cluster, College of Medicine, University of Saskatchewan, Saskatoon, SK S7N 5E5 Canada
- Cancer Research, Saskatchewan Cancer Agency, Saskatoon, SK S7N 5E5 Canada
| | - Andrew Freywald
- Department of Pathology and Laboratory Medicine, College of Medicine, University of Saskatchewan, Saskatoon, SK S7N 5E5 Canada
- Department of Biochemistry, Cancer Cluster, College of Medicine, University of Saskatchewan, Saskatoon, SK S7N 5E5 Canada
| | - Jie Han
- Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB T6G2R3 Canada
| | - Franco J. Vizeacoumar
- Department of Pathology and Laboratory Medicine, College of Medicine, University of Saskatchewan, Saskatoon, SK S7N 5E5 Canada
- Department of Biochemistry, Cancer Cluster, College of Medicine, University of Saskatchewan, Saskatoon, SK S7N 5E5 Canada
- Cancer Research, Saskatchewan Cancer Agency, Saskatoon, SK S7N 5E5 Canada
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48
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A Survey of Data Mining and Deep Learning in Bioinformatics. J Med Syst 2018; 42:139. [DOI: 10.1007/s10916-018-1003-9] [Citation(s) in RCA: 81] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Accepted: 06/21/2018] [Indexed: 12/13/2022]
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49
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Narrandes S, Xu W. Gene Expression Detection Assay for Cancer Clinical Use. J Cancer 2018; 9:2249-2265. [PMID: 30026820 PMCID: PMC6036716 DOI: 10.7150/jca.24744] [Citation(s) in RCA: 77] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2018] [Accepted: 05/15/2018] [Indexed: 12/23/2022] Open
Abstract
Cancer is a genetic disease where genetic variations cause abnormally functioning genes that appear to alter expression. Proteins, the final products of gene expression, determine the phenotypes and biological processes. Therefore, detecting gene expression levels can be used for cancer diagnosis, prognosis, and treatment prediction in a clinical setting. In this review, we investigated six gene expression assay systems (qRT-PCR, DNA microarray, nCounter, RNA-Seq, FISH, and tissue microarray) that are currently being used in clinical cancer studies. Some of these methods are also commonly used in a modified way; for example, detection of DNA content or protein expression. Herein, we discuss their principles, sample preparation, design, quantification and sensitivity, data analysis, time for sample preparation and processing, and cost. We also compared these methods according to their sample selection, particularly for the feasibility of using formalin-fixed paraffin-embedded (FFPE) samples, which are routinely archived for clinical cancer studies. We intend to provide a guideline for choosing an assay method with respect to its oncological applications in a clinical setting.
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Affiliation(s)
- Shavira Narrandes
- Departments of Biochemistry and Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada.,Research Institute of Oncology and Hematology, CancerCare Manitoba, Winnipeg, Canada
| | - Wayne Xu
- Departments of Biochemistry and Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada.,Research Institute of Oncology and Hematology, CancerCare Manitoba, Winnipeg, Canada.,College of Pharmacy, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada
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50
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Tsai M, Lo S, Audeh W, Qamar R, Budway R, Levine E, Whitworth P, Mavromatis B, Zon R, Oldham D, Untch S, Treece T, Blumencranz L, Soliman H. Association of 70-Gene Signature Assay Findings With Physicians' Treatment Guidance for Patients With Early Breast Cancer Classified as Intermediate Risk by the 21-Gene Assay. JAMA Oncol 2018; 4:e173470. [PMID: 29075751 DOI: 10.1001/jamaoncol.2017.3470] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Importance Among patients who undergo the 21-gene assay (21-GA), 39% to 67% receive an intermediate risk result and may receive ambiguous treatment guidance. The 70-gene signature assay (70-GS) may be associated with physicians' treatment decisions in this population with early breast cancer. Objective To determine whether 70-GS findings are associated with physicians' decisions about adjuvant treatment and confidence in their recommendations and to evaluate the dichotomous (high- vs low-risk) and continuous distribution of 70-GS indices among this group of patients with intermediate risk. Design, Setting, and Participants The Prospective Study of MammaPrint in Breast Cancer Patients With an Intermediate Recurrence Score (PROMIS trial) was an impact study conducted from May 20, 2012, through December 31, 2015, that enrolled 840 patients with early-stage breast cancer and a 21-gene assay recurrence score of 18 to 30. Patients were treated in 58 US institutions. Interventions The 70-GS result was given to physicians before adjuvant treatment. Main Outcomes and Measures Change in physician treatment decision before vs after receiving the 70-GS result. With a treatment change of greater than 20%, the odds ratio (OR) was applied. Results Among the 840 patients who underwent 70-GS classification (mean age, 59 years; range, 27-93 years), 374 (44.5%) had a low-risk and 466 (55.5%) had a high-risk result. The distribution of 70-GS indices did not correlate with recurrence score within the 21-GA intermediate range, with 70-GS low- and high-risk patients observed at every recurrence score. A significant change in adjuvant treatment was associated with receiving the 70-GS classifications with an OR of 0.64 (95% CI, 0.50-0.82; McNemar test, P < .001) for all patients. Among the low-risk patients, 108 of 374 (28.9%) had chemotherapy removed from their treatment recommendation; among the high-risk patients, 171 of 466 (36.7%) had chemotherapy added. Results of the 70-GS were associated with the physician's adjuvant treatment recommendation; 409 high-risk patients (87.8%) were recommended to receive adjuvant chemotherapy, and 339 low-risk patients (90.6%) were recommended no chemotherapy. Physicians reported having greater confidence in their treatment recommendation in 660 cases (78.6%) based on 70-GS results. Conclusions and Relevance The 70-GS provides clinically actionable information regarding patients classified as intermediate risk by the 21-GA and was associated with a change in treatment decision in 282 of these patients (33.6%). Chemotherapy was added or withheld by the treating physician based on the results of the 70-GS test. Physicians reported more confidence with their treatment recommendation after receiving 70-GS results.
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Affiliation(s)
- Michaela Tsai
- Virginia Piper Cancer Center, Minneapolis, Minnesota
| | - Shelly Lo
- Cardinal Bernardin Cancer Center, Loyola University Stritch School of Medicine, Maywood, Illinois
| | | | - Rubina Qamar
- Aurora Advanced Healthcare, Milwaukee, Wisconsin
| | - Raye Budway
- St Clair Hospital, Bethel Park, Pennsylvania
| | - Ellis Levine
- Roswell Park Cancer Institute, Buffalo, New York
| | | | - Blanche Mavromatis
- Western Maryland Health System Schwab Family Cancer Center, Cumberland, Maryland
| | - Robin Zon
- Northern Indiana Cancer Research Consortium, South Bend, Indiana
| | | | | | | | - Lisa Blumencranz
- Agendia, Inc, Irvine, California.,Department of Biochemistry and Molecular Biology, Miller School of Medicine, University of Miami, Miami, Florida
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