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Grindrod N, Cecchini M, Brackstone M. Concurrent Neoadjuvant Chemotherapy and Radiation in Locally Advanced Breast Cancer: Impact on Locoregional Recurrence Rates. Curr Oncol 2025; 32:85. [PMID: 39996885 PMCID: PMC11854545 DOI: 10.3390/curroncol32020085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2024] [Revised: 01/22/2025] [Accepted: 01/27/2025] [Indexed: 02/26/2025] Open
Abstract
Neoadjuvant chemoradiation therapy (NCRT) is an underutilized treatment in breast cancer but may improve outcomes by impacting the tumor immune microenvironment. The aim of this study was to evaluate NCRT's impact on recurrence and the role of tumor-infiltrating lymphocytes (TILs) in treatment response. We hypothesized that NCRT reduces recurrence by upregulating TILs. Patients with locally advanced breast cancer (LABC) were treated with NCRT. Stage IIB to III patients with any molecular subtypes were eligible. The patients were matched for age, stage, and molecular subtype by a propensity score to a concurrent cohort receiving standard neoadjuvant chemotherapy (NCT) followed by adjuvant radiation. The objective of this study was to assess the patients in terms of the pathological complete response (pCR), TIL counts prior to and following treatment, and locoregional recurrence. The median follow-up was 7.2 years. Thirty NCRT patients were successfully matched 1:3 to ninety NCT patients. The NCRT cohort had no regional and locoregional recurrences (p = 0.036, (hazard ratio) HR [0.25], 95% confidence interval (CI) [0.06-0.94] and p = 0.013, HR [0.25], 95% CI [0.08-0.76], respectively), compared to 17.8% of the NCT cohort. The NCRT group had significantly more pCRs, and TILs were increased in the post-treatment pCR specimens. NCRT can improve outcomes in LABC patients, with a higher pCR and significantly lower locoregional recurrence/higher recurrence-free survival. Further trials are needed to evaluate the role of NCRT in all breast cancer patients.
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Affiliation(s)
- Natalie Grindrod
- Schulich Faculty of Medicine & Dentistry, Western University, London, ON N6A 3K7, Canada; (N.G.); (M.C.)
- Department of Pathology, London Health Sciences Centre, London, ON N6A 5A5, Canada
| | - Matthew Cecchini
- Schulich Faculty of Medicine & Dentistry, Western University, London, ON N6A 3K7, Canada; (N.G.); (M.C.)
- Department of Pathology, London Health Sciences Centre, London, ON N6A 5A5, Canada
| | - Muriel Brackstone
- Schulich Faculty of Medicine & Dentistry, Western University, London, ON N6A 3K7, Canada; (N.G.); (M.C.)
- Department of Surgery, London Health Sciences Centre, London, ON N6A 5W9, Canada
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Dikoglu E, Pareja F. Molecular Basis of Breast Tumor Heterogeneity. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2025; 1464:237-257. [PMID: 39821029 DOI: 10.1007/978-3-031-70875-6_13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2025]
Abstract
Breast cancer (BC) is a profoundly heterogenous disease, with diverse molecular, histological, and clinical variations. The intricate molecular landscape of BC is evident even at early stages, illustrated by the complexity of the evolution from precursor lesions to invasive carcinoma. The key for therapeutic decision-making is the dynamic assessment of BC receptor status and clinical subtyping. Hereditary BC adds an additional layer of complexity to the disease, given that different cancer susceptibility genes contribute to distinct phenotypes and genomic features. Furthermore, the various BC subtypes display distinct metabolic demands and immune microenvironments. Finally, genotypic-phenotypic correlations in special histologic subtypes of BC inform diagnostic and therapeutic approaches, highlighting the significance of thoroughly comprehending BC heterogeneity.
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Affiliation(s)
- Esra Dikoglu
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Fresia Pareja
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
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Janssen LM, de Vries BBLP, Janse MHA, van der Wall E, Elias SG, Salgado R, van Diest PJ, Gilhuijs KGA. Tumor infiltrating lymphocytes and change in tumor load on MRI to assess response and prognosis after neoadjuvant chemotherapy in breast cancer. Breast Cancer Res Treat 2025; 209:167-175. [PMID: 39285068 PMCID: PMC11785616 DOI: 10.1007/s10549-024-07484-7] [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: 03/16/2024] [Accepted: 08/28/2024] [Indexed: 02/02/2025]
Abstract
PURPOSE In this study, we aimed to explore if the combination of tumor infiltrating lymphocytes (TILs) and change in tumor load on dynamic contrast-enhanced magnetic resonance imaging leads to better assessment of response to neoadjuvant chemotherapy (NAC) in patients with breast cancer, compared to either alone. METHODS In 190 NAC treated patients, MRI scans were performed before and at the end of treatment. The percentage of stromal TILs (%TILs) was assessed in pre-NAC biopsies according to established criteria. Prediction models were developed with linear regression by least absolute shrinkage and selection operator and cross validation (CV), with residual cancer burden as the dependent variable. Discrimination for pathological complete response (pCR) was evaluated using area under the receiver operating characteristic curves (AUC). We used Cox regression analysis for exploring the association between %TILs and recurrence-free survival (RFS). RESULTS Fifty-one patients reached pCR. In all patients, the %TILs model and change in MRI tumor load model had an estimated CV AUC of 0.69 (95% confidence interval (CI) 0.53-0.78) and 0.69 (95% CI 0.61-0.79), respectively, whereas a model combining the variables resulted in an estimated CV AUC of 0.75 (95% CI 0.66-0.83). In the group with tumors that were ER positive and HER2 negative (ER+/HER2-) and in the group with tumors that were either triple negative or HER2 positive (TN&HER2+) separately, the combined model reached an estimated CV AUC of 0.72 (95% CI 0.60-0.88) and 0.70(95% CI 0.59-0.82), respectively. A significant association was observed between pre-treatment %TILS and RFS (hazard ratio (HR) 0.72 (95% CI 0.53-0.98), for every standard deviation increase in %TILS, p = 0.038). CONCLUSION The combination of TILs and MRI is informative of response to NAC in patients with both ER+/HER2- and TN&HER2+ tumors.
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Affiliation(s)
- L M Janssen
- Image Sciences Institute, University Medical Centre Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - B B L Penning de Vries
- Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands
| | - M H A Janse
- Image Sciences Institute, University Medical Centre Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - E van der Wall
- Department of Medical Oncology, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands
| | - S G Elias
- Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands
| | - R Salgado
- Department of Pathology, ZAS Hospitals, Antwerp, Belgium
- Division of Research, Peter Mac Callum Cancer Centre, Melbourne, Australia
| | - P J van Diest
- Department of Pathology, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands
| | - K G A Gilhuijs
- Image Sciences Institute, University Medical Centre Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands.
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Rahadian RE, Tan HQ, Ho BS, Kumaran A, Villanueva A, Sng J, Tan RSYC, Tan TJY, Tan VKM, Tan BKT, Lim GH, Cai Y, Nei WL, Wong FY. Using Machine Learning Models to Predict Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer. JCO Clin Cancer Inform 2024; 8:e2400071. [PMID: 39576956 DOI: 10.1200/cci.24.00071] [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: 03/27/2024] [Revised: 08/15/2024] [Accepted: 10/11/2024] [Indexed: 11/24/2024] Open
Abstract
PURPOSE Neoadjuvant chemotherapy (NAC) is increasingly used in breast cancer. Predictive modeling is useful in predicting pathologic complete response (pCR) to NAC. We test machine learning (ML) models to predict pCR in breast cancer and explore methods of handling missing data. METHODS Four hundred and ninety-nine patients with breast cancer treated with NAC in two centers in Singapore (National Cancer Centre Singapore [NCCS] and KK Hospital) between January 2014 and December 2017 were included. Eleven clinical features were used to train five different ML models. Listwise deletion and imputation were evaluated on handling missing data. Model performance was evaluated by AUC and calibration (Brier score). Feature importance from the best performing model in the external testing data set was calculated using Shapley additive explanations. RESULTS Seventy-two (24.6%), 18 (24.7%), and 31 (24.8%) patients attained pCR in NCCS training, NCCS testing, and KK Women's and Children's Hospital (KKH) testing data sets, respectively. The random forest (RF) base and imputed models have the highest AUCs in the KKH cohort of 0.794 (95% CI, 0.709 to 0.873) and 0.795 (95% CI, 0.706 to 0.871), respectively, and were the best calibrated with the lowest Brier score. No statistically significant difference was noted between AUCs of the base and imputed models in all data sets. The imputed model had a larger positive predictive value (PPV; 98.2% v 95.1%) and negative predictive value (NPV; 96.7% v 90.0%) than the base model in the KKH data set. Estrogen receptor intensity, human epidermal growth factor 2 intensity, and age at diagnosis were the three most important predictors. CONCLUSION ML, particularly RF, demonstrates reasonable accuracy in pCR prediction after NAC. Imputing missing fields in the data can improve the PPV and NPV of the pCR prediction model.
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Affiliation(s)
| | - Hong Qi Tan
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore Health Services, Singapore, Singapore
| | - Bryan Shihan Ho
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore Health Services, Singapore, Singapore
| | - Arjunan Kumaran
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore Health Services, Singapore, Singapore
| | - Andre Villanueva
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore Health Services, Singapore, Singapore
| | - Joy Sng
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore Health Services, Singapore, Singapore
| | - Ryan Shea Ying Cong Tan
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore Health Services, Singapore, Singapore
| | - Tira Jing Ying Tan
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore Health Services, Singapore, Singapore
| | - Veronique Kiak Mien Tan
- Division of Breast Surgery, Singapore General Hospital, Singapore Health Services, Singapore, Singapore
| | - Benita Kiat Tee Tan
- Division of Breast Surgery, Sengkang General Hospital, Singapore Health Services, Singapore, Singapore
| | - Geok Hoon Lim
- Breast Department, KK Women's and Children's Hospital, Singapore, Singapore
| | - Yiyu Cai
- School of Mechanical & Aerospace Engineering, Nanyang Technological University, Singapore, Singapore
| | - Wen Long Nei
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore Health Services, Singapore, Singapore
| | - Fuh Yong Wong
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore Health Services, Singapore, Singapore
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Sun HK, Jiang WL, Zhang SL, Xu PC, Wei LM, Liu JB. Predictive value of tumor-infiltrating lymphocytes for neoadjuvant therapy response in triple-negative breast cancer: A systematic review and meta-analysis. World J Clin Oncol 2024; 15:920-935. [PMID: 39071463 PMCID: PMC11271722 DOI: 10.5306/wjco.v15.i7.920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2024] [Revised: 05/21/2024] [Accepted: 06/06/2024] [Indexed: 07/16/2024] Open
Abstract
BACKGROUND The association between tumor-infiltrating lymphocyte (TIL) levels and the response to neoadjuvant therapy (NAT) in patients with triple-negative breast cancer (TNBC) remains unclear. AIM To investigate the predictive potential of TIL levels for the response to NAT in TNBC patients. METHODS A systematic search of the National Center for Biotechnology Information PubMed database was performed to collect relevant published literature prior to August 31, 2023. The correlation between TIL levels and the NAT pathologic complete response (pCR) in TNBC patients was assessed using a systematic review and meta-analysis. Subgroup analysis, sensitivity analysis, and publication bias analysis were also conducted. RESULTS A total of 32 studies were included in this meta-analysis. The overall meta-analysis results indicated that the pCR rate after NAT treatment in TNBC patients in the high TIL subgroup was significantly greater than that in patients in the low TIL subgroup (48.0% vs 27.7%) (risk ratio 2.01; 95% confidence interval 1.77-2.29; P < 0.001, I 2 = 56%). Subgroup analysis revealed that the between-study heterogeneity originated from differences in study design, TIL level cutoffs, and study populations. Publication bias could have existed in the included studies. The meta-analysis based on different NAT protocols revealed that all TNBC patients with high levels of TILs had a greater rate of pCR after NAT treatment in all protocols (all P ≤ 0.01), and there was no significant between-protocol difference in the statistics among the different NAT protocols (P = 0.29). Additionally, sensitivity analysis demonstrated that the overall results of the meta-analysis remained consistent when the included studies were individually excluded. CONCLUSION TILs can serve as a predictor of the response to NAT treatment in TNBC patients. TNBC patients with high levels of TILs exhibit a greater NAT pCR rate than those with low levels of TILs, and this predictive capability is consistent across different NAT regimens.
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Affiliation(s)
- Hai-Kuan Sun
- Department of Thyroid and Breast Surgery, The First Affiliated Hospital, College of Clinical Medicine, Henan University of Science and Technology, Luoyang 471000, Henan Province, China
| | - Wen-Long Jiang
- Department of Thyroid and Breast Surgery, The First Affiliated Hospital, College of Clinical Medicine, Henan University of Science and Technology, Luoyang 471000, Henan Province, China
| | - Shi-Lei Zhang
- Department of Thyroid and Breast Surgery, The First Affiliated Hospital, College of Clinical Medicine, Henan University of Science and Technology, Luoyang 471000, Henan Province, China
| | - Peng-Cheng Xu
- Department of Thyroid and Breast Surgery, The First Affiliated Hospital, College of Clinical Medicine, Henan University of Science and Technology, Luoyang 471000, Henan Province, China
| | - Li-Min Wei
- Department of Thyroid and Breast Surgery, The First Affiliated Hospital, College of Clinical Medicine, Henan University of Science and Technology, Luoyang 471000, Henan Province, China
| | - Jiang-Bo Liu
- Department of Thyroid and Breast Surgery, The First Affiliated Hospital, College of Clinical Medicine, Henan University of Science and Technology, Luoyang 471000, Henan Province, China
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Wei LJ, Fu J, Yang HX, Yang X, Liang HY, Luo RZ, Liu LL. Evaluation of pathological response to neoadjuvant chemotherapy in locally advanced cervical cancer. J Transl Med 2024; 22:655. [PMID: 39004706 PMCID: PMC11247755 DOI: 10.1186/s12967-024-05482-3] [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: 04/12/2024] [Accepted: 07/03/2024] [Indexed: 07/16/2024] Open
Abstract
Neoadjuvant chemotherapy (NACT) is a viable therapeutic option for women diagnosed locally advanced cervical cancer (LACC). However, the factors influencing pathological response are still controversial. We collected pair specimens of 185 LACC patients before and after receiving NACT and conducted histological evaluation. 8 fresh tissues pre-treatment were selected from the entire cohort to conducted immune gene expression profiling. A novel pathological grading system was established by comprehensively assessing the percentages of viable tumor, inflammatory stroma, fibrotic stroma, and necrosis in the tumor bed. Then, 185 patients were categorized into either the good pathological response (GPR) group or the poor pathological response (PPR) group post-NACT, with 134 patients (72.4%, 134/185) achieving GPR. Increasing tumor-infiltrating lymphocytes (TILs) and tumor-infiltrating lymphocytes volume (TILV) pre-treatment were correlated with GPR, with TILV emerging as an independent predictive factor for GPR. Additionally, CIBERSORT analysis revealed noteworthy differences in the expression of immune makers between cPR and non-cPR group. Furthermore, a significantly heightened density of CD8 + T cells and a reduced density of FOXP3 + T cells were observed in GPR than PPR. Importantly, patients exhibiting GPR or inflammatory type demonstrated improved overall survival and disease-free survival. Notably, stromal type was an independent prognostic factor in multivariate analysis. Our study indicates the elevated TILV in pre-treatment specimens may predict a favorable response to NACT, while identifying stromal type in post-treatment specimens as an independent prognostic factor. Moreover, we proposed this pathological grading system in NACT patients, which may offer a more comprehensive understanding of treatment response and prognosis.
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Affiliation(s)
- Li-Jun Wei
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China
- Department of Pathology, Sun Yat-sen University Cancer Center, 651# Dong Feng Road East, Guangzhou, 510060, Guangdong, China
| | - Jia Fu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China
- Department of Pathology, Sun Yat-sen University Cancer Center, 651# Dong Feng Road East, Guangzhou, 510060, Guangdong, China
| | - Hai-Xia Yang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China
- Department of Pathology, The Second Affiliated Hospital of Shenzhen University, Shenzhen, 518101, China
| | - Xia Yang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China
- Department of Pathology, Sun Yat-sen University Cancer Center, 651# Dong Feng Road East, Guangzhou, 510060, Guangdong, China
| | - Hao-Yu Liang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China
- Department of Pathology, Sun Yat-sen University Cancer Center, 651# Dong Feng Road East, Guangzhou, 510060, Guangdong, China
| | - Rong-Zhen Luo
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China.
- Department of Pathology, Sun Yat-sen University Cancer Center, 651# Dong Feng Road East, Guangzhou, 510060, Guangdong, China.
| | - Li-Li Liu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China.
- Department of Pathology, Sun Yat-sen University Cancer Center, 651# Dong Feng Road East, Guangzhou, 510060, Guangdong, China.
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Kusama H, Kittaka N, Soma A, Taniguchi A, Kanaoka H, Nakajima S, Oyama Y, Seto Y, Okuno J, Watanabe N, Matsui S, Nishio M, Fujisawa F, Honma K, Tamaki Y, Nakayama T. Predictive factors for response to neoadjuvant chemotherapy: inflammatory and immune markers in triple-negative breast cancer. Breast Cancer 2023; 30:1085-1093. [PMID: 37782377 DOI: 10.1007/s12282-023-01504-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 09/09/2023] [Indexed: 10/03/2023]
Abstract
BACKGROUND Tumor-infiltrating lymphocytes (TILs) predict response to neoadjuvant chemotherapy (NAC) in triple-negative breast cancer (TNBC) patients. However, the TIL level can be determined at a few facilities. By contrast, neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are easily and objectively determined from the results of full blood counts. We conducted a retrospective study to investigate whether TILs, NLR, and PLR predict NAC efficacy and whether NLR and PLR could be surrogate markers for TILs in TNBC. METHODS Of the 266 patients diagnosed with TNBC between 2013 and 2019, 66 who underwent radical surgery after sequential administration of anthracycline and taxane as NAC were included in the study. TILs, NLR, and PLR were evaluated as predictors of pathologic complete response (pCR) using cutoff values determined from receiver operating characteristic curves. RESULTS The cutoff values of TILs, NLR, and PLR were 20%, 2.6, and 180, respectively. High TIL level was associated with low NLR (P = 0.01) and low PLR (P = 0.01). High TIL level (odds ratio [OR] 4.28 [95% CI 1.40-13.1]; P = 0.01), low NLR (OR 5.51 [95% CI 1.60-18.9]; P = 0.01), and low PLR (OR 3.29 [95% CI 1.13-9.57]; P = 0.03) were associated with pCR. Low NLR predicted pCR independently (OR 6.59 [95% CI 1.45-30.0]; P = 0.01). CONCLUSIONS TILs, NLR, and PLR predicted NAC efficacy against TNBC. TIL level was associated with NLR and PLR. NLR was an independent predictive factor and may be a useful surrogate marker for TILs when predicting pCR.
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Affiliation(s)
- Hiroki Kusama
- Department of Breast and Endocrine Surgery, Osaka International Cancer Institute, 3-1-69 Otemae Chuo-Ku, Osaka, 541-8567, Japan
| | - Nobuyoshi Kittaka
- Department of Breast Surgery, Osaka Rosai Hospital, 1179-3 Nagasone-Cho Kita-Ku Sakai-Shi, Osaka, 541-8567, Japan
| | - Ai Soma
- Department of Breast and Endocrine Surgery, Osaka International Cancer Institute, 3-1-69 Otemae Chuo-Ku, Osaka, 541-8567, Japan
| | - Azusa Taniguchi
- Department of Breast and Endocrine Surgery, Osaka International Cancer Institute, 3-1-69 Otemae Chuo-Ku, Osaka, 541-8567, Japan
| | - Haruka Kanaoka
- Department of Breast and Endocrine Surgery, Osaka International Cancer Institute, 3-1-69 Otemae Chuo-Ku, Osaka, 541-8567, Japan
| | - Satomi Nakajima
- Department of Breast and Endocrine Surgery, Osaka International Cancer Institute, 3-1-69 Otemae Chuo-Ku, Osaka, 541-8567, Japan
| | - Yuri Oyama
- Department of Breast and Endocrine Surgery, Osaka International Cancer Institute, 3-1-69 Otemae Chuo-Ku, Osaka, 541-8567, Japan
| | - Yukiko Seto
- Department of Breast and Endocrine Surgery, Osaka International Cancer Institute, 3-1-69 Otemae Chuo-Ku, Osaka, 541-8567, Japan
| | - Jun Okuno
- Department of Breast and Endocrine Surgery, Osaka International Cancer Institute, 3-1-69 Otemae Chuo-Ku, Osaka, 541-8567, Japan
| | - Noriyuki Watanabe
- Department of Breast and Endocrine Surgery, Osaka International Cancer Institute, 3-1-69 Otemae Chuo-Ku, Osaka, 541-8567, Japan
| | - Saki Matsui
- Department of Breast and Endocrine Surgery, Osaka International Cancer Institute, 3-1-69 Otemae Chuo-Ku, Osaka, 541-8567, Japan
| | - Minako Nishio
- Department of Medical Oncology, Osaka International Cancer Institute, Osaka, Japan
| | - Fumie Fujisawa
- Department of Medical Oncology, Osaka International Cancer Institute, Osaka, Japan
| | - Keiichiro Honma
- Department of Pathology, Osaka International Cancer Institute, Osaka, Japan
| | - Yasuhiro Tamaki
- Department of Breast and Endocrine Surgery, Kaizuka City Hospital, 3-10-20 Hori Kaizuka-Shi, Osaka, 597-0015, Japan
| | - Takahiro Nakayama
- Department of Breast and Endocrine Surgery, Osaka International Cancer Institute, 3-1-69 Otemae Chuo-Ku, Osaka, 541-8567, Japan.
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Erol VB, Goktas Aydin S, Bilici A, Cakir A, Acikgoz O, Olmez OF, Basim P. Relationship between the change in tumour-infiltrating lymphocyte level and residual tumour after neoadjuvant chemotherapy in patients with locally advanced breast cancer. J Chemother 2023; 35:662-670. [PMID: 37599454 DOI: 10.1080/1120009x.2023.2247207] [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] [Received: 03/13/2023] [Revised: 07/01/2023] [Accepted: 07/20/2023] [Indexed: 08/22/2023]
Abstract
To evaluate the tumour-infiltrating lymphocyte (TIL) rates in breast tissue before and after neoadjuvant chemotherapy (NAC) and their impact on survival, eighty-four patients with locally advanced breast cancer (LABC) were assessed. Pre- and post-NAC TIL levels were determined using biopsy and surgical specimens, respectively. The median TIL rate was significantly different before (17.5%) and after (5%) NAC. Pre- and postoperative Ki-67 index, molecular subtype, pre- and post-NAC TIL concentration, and preoperative residual-cancer-burden TIL were significantly associated with pathological complete response (pCR). Specifically, higher pre-NAC TIL levels were associated with higher pCR rates. Postoperative Ki-67 index and pCR, and postoperative Ki-67 index were significant predictors of disease-free (DFS) and overall survival, respectively. The independent prognostic factors for DFS were postoperative Ki-67 score (hazard ratio [HR]: 6.16; p = 0.012), post-NAC TIL score (HR: 0.42; P = 0.041), and pCR (HR: 0.10; P = 0.038). Our study confirms that higher pre-NAC and lower postoperative TIL levels may be surrogate factors for longer DFS, and postoperative TIL rate may predict post-NAC pCR in patients with LABC.
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Affiliation(s)
- Vedat Bugra Erol
- Department of Medical Oncology, Medical Faculty, Istanbul Medipol University, Istanbul, Turkey
| | - Sabin Goktas Aydin
- Department of Medical Oncology, Medical Faculty, Istanbul Medipol University, Istanbul, Turkey
| | - Ahmet Bilici
- Department of Medical Oncology, Medical Faculty, Istanbul Medipol University, Istanbul, Turkey
| | - Asli Cakir
- Department of Pathology, Medical Faculty, Istanbul Medipol University, Istanbul, Turkey
| | - Ozgur Acikgoz
- Department of Medical Oncology, Medical Faculty, Istanbul Medipol University, Istanbul, Turkey
| | - Omer Fatih Olmez
- Department of Medical Oncology, Medical Faculty, Istanbul Medipol University, Istanbul, Turkey
| | - Pelin Basim
- Department of Surgery, Medical Faculty, Istanbul Medipol University, Istanbul, Turkey
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Malhaire C, Selhane F, Saint-Martin MJ, Cockenpot V, Akl P, Laas E, Bellesoeur A, Ala Eddine C, Bereby-Kahane M, Manceau J, Sebbag-Sfez D, Pierga JY, Reyal F, Vincent-Salomon A, Brisse H, Frouin F. Exploring the added value of pretherapeutic MR descriptors in predicting breast cancer pathologic complete response to neoadjuvant chemotherapy. Eur Radiol 2023; 33:8142-8154. [PMID: 37318605 DOI: 10.1007/s00330-023-09797-5] [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] [Received: 12/15/2022] [Revised: 04/14/2023] [Accepted: 05/13/2023] [Indexed: 06/16/2023]
Abstract
OBJECTIVES To evaluate the association between pretreatment MRI descriptors and breast cancer (BC) pathological complete response (pCR) to neoadjuvant chemotherapy (NAC). MATERIALS AND METHODS Patients with BC treated by NAC with a breast MRI between 2016 and 2020 were included in this retrospective observational single-center study. MR studies were described using the standardized BI-RADS and breast edema score on T2-weighted MRI. Univariable and multivariable logistic regression analyses were performed to assess variables association with pCR according to residual cancer burden. Random forest classifiers were trained to predict pCR on a random split including 70% of the database and were validated on the remaining cases. RESULTS Among 129 BC, 59 (46%) achieved pCR after NAC (luminal (n = 7/37, 19%), triple negative (n = 30/55, 55%), HER2 + (n = 22/37, 59%)). Clinical and biological items associated with pCR were BC subtype (p < 0.001), T stage 0/I/II (p = 0.008), higher Ki67 (p = 0.005), and higher tumor-infiltrating lymphocytes levels (p = 0.016). Univariate analysis showed that the following MRI features, oval or round shape (p = 0.047), unifocality (p = 0.026), non-spiculated margins (p = 0.018), no associated non-mass enhancement (p = 0.024), and a lower MRI size (p = 0.031), were significantly associated with pCR. Unifocality and non-spiculated margins remained independently associated with pCR at multivariable analysis. Adding significant MRI features to clinicobiological variables in random forest classifiers significantly increased sensitivity (0.67 versus 0.62), specificity (0.69 versus 0.67), and precision (0.71 versus 0.67) for pCR prediction. CONCLUSION Non-spiculated margins and unifocality are independently associated with pCR and can increase models performance to predict BC response to NAC. CLINICAL RELEVANCE STATEMENT A multimodal approach integrating pretreatment MRI features with clinicobiological predictors, including tumor-infiltrating lymphocytes, could be employed to develop machine learning models for identifying patients at risk of non-response. This may enable consideration of alternative therapeutic strategies to optimize treatment outcomes. KEY POINTS • Unifocality and non-spiculated margins are independently associated with pCR at multivariable logistic regression analysis. • Breast edema score is associated with MR tumor size and TIL expression, not only in TN BC as previously reported, but also in luminal BC. • Adding significant MRI features to clinicobiological variables in machine learning classifiers significantly increased sensitivity, specificity, and precision for pCR prediction.
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Affiliation(s)
- Caroline Malhaire
- Department of Medical Imaging, Institut Curie, PSL Research University, 26 Rue d'Ulm, 75005, Paris, France.
- Institut Curie, Research Center, U1288-LITO, Inserm, Paris-Saclay University, 91401, Orsay, France.
| | - Fatine Selhane
- Gustave Roussy, Department of Imaging, Paris-Saclay University, 94805, Villejuif, France
| | | | - Vincent Cockenpot
- Pathology Unit, Centre Léon Bérard, 28 Rue Laennec, 69008, Lyon, France
| | - Pia Akl
- Women Imaging Unit, HCL, Radiologie du Groupement Hospitalier Est, 3 Quai Des Célestins, 69002, Lyon, France
| | - Enora Laas
- Department of Surgical Oncology, Institut Curie, 26 Rue d'Ulm, 75005, Paris, France
| | - Audrey Bellesoeur
- Department of Medical Oncology, Institut Curie, 26 Rue d'Ulm, 75005, Paris, France
| | - Catherine Ala Eddine
- Department of Medical Imaging, Institut Curie, PSL Research University, 26 Rue d'Ulm, 75005, Paris, France
| | - Melodie Bereby-Kahane
- Department of Medical Imaging, Institut Curie, PSL Research University, 26 Rue d'Ulm, 75005, Paris, France
| | - Julie Manceau
- Department of Medical Imaging, Institut Curie, PSL Research University, 26 Rue d'Ulm, 75005, Paris, France
| | - Delphine Sebbag-Sfez
- Department of Medical Imaging, Institut Curie, PSL Research University, 26 Rue d'Ulm, 75005, Paris, France
| | - Jean-Yves Pierga
- Department of Medical Oncology, Institut Curie, 26 Rue d'Ulm, 75005, Paris, France
| | - Fabien Reyal
- Department of Surgical Oncology, Institut Curie, 26 Rue d'Ulm, 75005, Paris, France
| | | | - Herve Brisse
- Department of Medical Imaging, Institut Curie, PSL Research University, 26 Rue d'Ulm, 75005, Paris, France
| | - Frederique Frouin
- Institut Curie, Research Center, U1288-LITO, Inserm, Paris-Saclay University, 91401, Orsay, France
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Thagaard J, Broeckx G, Page DB, Jahangir CA, Verbandt S, Kos Z, Gupta R, Khiroya R, Abduljabbar K, Acosta Haab G, Acs B, Akturk G, Almeida JS, Alvarado‐Cabrero I, Amgad M, Azmoudeh‐Ardalan F, Badve S, Baharun NB, Balslev E, Bellolio ER, Bheemaraju V, Blenman KRM, Botinelly Mendonça Fujimoto L, Bouchmaa N, Burgues O, Chardas A, Chon U Cheang M, Ciompi F, Cooper LAD, Coosemans A, Corredor G, Dahl AB, Dantas Portela FL, Deman F, Demaria S, Doré Hansen J, Dudgeon SN, Ebstrup T, Elghazawy M, Fernandez‐Martín C, Fox SB, Gallagher WM, Giltnane JM, Gnjatic S, Gonzalez‐Ericsson PI, Grigoriadis A, Halama N, Hanna MG, Harbhajanka A, Hart SN, Hartman J, Hauberg S, Hewitt S, Hida AI, Horlings HM, Husain Z, Hytopoulos E, Irshad S, Janssen EAM, Kahila M, Kataoka TR, Kawaguchi K, Kharidehal D, Khramtsov AI, Kiraz U, Kirtani P, Kodach LL, Korski K, Kovács A, Laenkholm A, Lang‐Schwarz C, Larsimont D, Lennerz JK, Lerousseau M, Li X, Ly A, Madabhushi A, Maley SK, Manur Narasimhamurthy V, Marks DK, McDonald ES, Mehrotra R, Michiels S, Minhas FUAA, Mittal S, Moore DA, Mushtaq S, Nighat H, Papathomas T, Penault‐Llorca F, Perera RD, Pinard CJ, Pinto‐Cardenas JC, Pruneri G, Pusztai L, Rahman A, Rajpoot NM, Rapoport BL, Rau TT, Reis‐Filho JS, et alThagaard J, Broeckx G, Page DB, Jahangir CA, Verbandt S, Kos Z, Gupta R, Khiroya R, Abduljabbar K, Acosta Haab G, Acs B, Akturk G, Almeida JS, Alvarado‐Cabrero I, Amgad M, Azmoudeh‐Ardalan F, Badve S, Baharun NB, Balslev E, Bellolio ER, Bheemaraju V, Blenman KRM, Botinelly Mendonça Fujimoto L, Bouchmaa N, Burgues O, Chardas A, Chon U Cheang M, Ciompi F, Cooper LAD, Coosemans A, Corredor G, Dahl AB, Dantas Portela FL, Deman F, Demaria S, Doré Hansen J, Dudgeon SN, Ebstrup T, Elghazawy M, Fernandez‐Martín C, Fox SB, Gallagher WM, Giltnane JM, Gnjatic S, Gonzalez‐Ericsson PI, Grigoriadis A, Halama N, Hanna MG, Harbhajanka A, Hart SN, Hartman J, Hauberg S, Hewitt S, Hida AI, Horlings HM, Husain Z, Hytopoulos E, Irshad S, Janssen EAM, Kahila M, Kataoka TR, Kawaguchi K, Kharidehal D, Khramtsov AI, Kiraz U, Kirtani P, Kodach LL, Korski K, Kovács A, Laenkholm A, Lang‐Schwarz C, Larsimont D, Lennerz JK, Lerousseau M, Li X, Ly A, Madabhushi A, Maley SK, Manur Narasimhamurthy V, Marks DK, McDonald ES, Mehrotra R, Michiels S, Minhas FUAA, Mittal S, Moore DA, Mushtaq S, Nighat H, Papathomas T, Penault‐Llorca F, Perera RD, Pinard CJ, Pinto‐Cardenas JC, Pruneri G, Pusztai L, Rahman A, Rajpoot NM, Rapoport BL, Rau TT, Reis‐Filho JS, Ribeiro JM, Rimm D, Roslind A, Vincent‐Salomon A, Salto‐Tellez M, Saltz J, Sayed S, Scott E, Siziopikou KP, Sotiriou C, Stenzinger A, Sughayer MA, Sur D, Fineberg S, Symmans F, Tanaka S, Taxter T, Tejpar S, Teuwen J, Thompson EA, Tramm T, Tran WT, van der Laak J, van Diest PJ, Verghese GE, Viale G, Vieth M, Wahab N, Walter T, Waumans Y, Wen HY, Yang W, Yuan Y, Zin RM, Adams S, Bartlett J, Loibl S, Denkert C, Savas P, Loi S, Salgado R, Specht Stovgaard E. Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer. J Pathol 2023; 260:498-513. [PMID: 37608772 PMCID: PMC10518802 DOI: 10.1002/path.6155] [Show More Authors] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 06/07/2023] [Indexed: 08/24/2023]
Abstract
The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
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Affiliation(s)
- Jeppe Thagaard
- Technical University of DenmarkKongens LyngbyDenmark
- Visiopharm A/SHørsholmDenmark
| | - Glenn Broeckx
- Department of PathologyGZA‐ZNA HospitalsAntwerpBelgium
- Centre for Oncological Research (CORE), MIPPRO, Faculty of MedicineAntwerp UniversityAntwerpBelgium
| | - David B Page
- Earle A Chiles Research InstituteProvidence Cancer InstitutePortlandORUSA
| | - Chowdhury Arif Jahangir
- UCD School of Biomolecular and Biomedical Science, UCD Conway InstituteUniversity College DublinDublinIreland
| | - Sara Verbandt
- Digestive Oncology, Department of OncologyKU LeuvenLeuvenBelgium
| | - Zuzana Kos
- Department of Pathology and Laboratory MedicineBC Cancer Vancouver Centre, University of British ColumbiaVancouverBritish ColumbiaCanada
| | - Rajarsi Gupta
- Department of Biomedical InformaticsStony Brook UniversityStony BrookNYUSA
| | - Reena Khiroya
- Department of Cellular PathologyUniversity College Hospital LondonLondonUK
| | | | | | - Balazs Acs
- Department of Oncology and PathologyKarolinska InstitutetStockholmSweden
- Department of Clinical Pathology and Cancer DiagnosticsKarolinska University HospitalStockholmSweden
| | - Guray Akturk
- Translational Molecular Biomarkers, Merck & Co IncRahwayNJUSA
| | - Jonas S Almeida
- Division of Cancer Epidemiology and Genetics (DCEG)National Cancer Institute (NCI)Rockville, MDUSA
| | | | - Mohamed Amgad
- Department of PathologyNorthwestern University Feinberg School of MedicineChicagoILUSA
| | | | - Sunil Badve
- Department of Pathology and Laboratory Medicine, Emory University School of MedicineEmory University Winship Cancer InstituteAtlantaGAUSA
| | | | - Eva Balslev
- Department of PathologyHerlev and Gentofte HospitalHerlevDenmark
| | - Enrique R Bellolio
- Departamento de Anatomía Patológica, Facultad de MedicinaUniversidad de La FronteraTemucoChile
| | | | - Kim RM Blenman
- Department of Internal Medicine Section of Medical Oncology and Yale Cancer CenterYale School of MedicineNew HavenCTUSA
- Department of Computer ScienceYale School of Engineering and Applied ScienceNew HavenCTUSA
| | | | - Najat Bouchmaa
- Institute of Biological Sciences, Faculty of Medical SciencesMohammed VI Polytechnic University (UM6P)Ben‐GuerirMorocco
| | - Octavio Burgues
- Pathology DepartmentHospital Cliníco Universitario de Valencia/InclivaValenciaSpain
| | - Alexandros Chardas
- Department of Pathobiology & Population SciencesThe Royal Veterinary CollegeLondonUK
| | - Maggie Chon U Cheang
- Head of Integrative Genomics Analysis in Clinical Trials, ICR‐CTSU, Division of Clinical StudiesThe Institute of Cancer ResearchLondonUK
| | - Francesco Ciompi
- Radboud University Medical CenterDepartment of PathologyNijmegenThe Netherlands
| | - Lee AD Cooper
- Department of PathologyNorthwestern Feinberg School of MedicineChicagoILUSA
| | - An Coosemans
- Department of Oncology, Laboratory of Tumor Immunology and ImmunotherapyKU LeuvenLeuvenBelgium
| | - Germán Corredor
- Biomedical Engineering DepartmentEmory UniversityAtlantaGAUSA
| | - Anders B Dahl
- Technical University of DenmarkKongens LyngbyDenmark
| | | | | | - Sandra Demaria
- Department of Radiation OncologyWeill Cornell MedicineNew YorkNYUSA
- Department of Pathology and Laboratory MedicineWeill Cornell MedicineNew YorkNYUSA
| | | | - Sarah N Dudgeon
- Conputational Biology and BioinformaticsYale UniversityNew HavenCTUSA
| | | | | | - Claudio Fernandez‐Martín
- Instituto Universitario de Investigación en Tecnología Centrada en el Ser Humano, HUMAN‐techUniversitat Politècnica de ValènciaValenciaSpain
| | - Stephen B Fox
- Pathology, Peter MacCallum Cancer Centre and Sir Peter MacCallum Department of OncologyUniversity of MelbourneMelbourneVictoriaAustralia
| | - William M Gallagher
- UCD School of Biomolecular and Biomedical Science, UCD Conway InstituteUniversity College DublinDublinIreland
| | | | - Sacha Gnjatic
- Department of Oncological Sciences, Medicine Hem/Onc, and Pathology, Tisch Cancer Institute – Precision Immunology InstituteIcahn School of Medicine at Mount SinaiNew YorkNYUSA
| | | | - Anita Grigoriadis
- Cancer Bioinformatics, School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences and MedicineKing's College LondonLondonUK
- The Breast Cancer Now Research Unit, School of Cancer and Pharmaceutical Sciences, Faculty of Life Sciences and MedicineKing's College LondonLondonUK
| | - Niels Halama
- Department of Translational ImmunotherapyGerman Cancer Research CenterHeidelbergGermany
| | - Matthew G Hanna
- Department of PathologyMemorial Sloan Kettering Cancer CenterNew YorkUSA
| | | | - Steven N Hart
- Department of Laboratory Medicine and PathologyMayo ClinicRochester, MNUSA
| | - Johan Hartman
- Department of Oncology and PathologyKarolinska InstitutetStockholmSweden
- Department of Clinical Pathology and Cancer DiagnosticsKarolinska University HospitalStockholmSweden
| | - Søren Hauberg
- Technical University of DenmarkKongens LyngbyDenmark
| | - Stephen Hewitt
- Laboratory of Pathology, Center for Cancer Research, National Cancer InstituteNational Institutes of HealthBethesdaMDUSA
| | - Akira I Hida
- Department of PathologyMatsuyama Shimin HospitalMatsuyamaJapan
| | - Hugo M Horlings
- Division of PathologyNetherlands Cancer Institute (NKI)AmsterdamThe Netherlands
| | | | | | - Sheeba Irshad
- King's College London & Guy's & St Thomas’ NHS TrustLondonUK
| | - Emiel AM Janssen
- Department of PathologyStavanger University HospitalStavangerNorway
- Department of Chemistry, Bioscience and Environmental TechnologyUniversity of StavangerStavangerNorway
| | | | | | - Kosuke Kawaguchi
- Department of Breast SurgeryKyoto University Graduate School of MedicineKyotoJapan
| | | | - Andrey I Khramtsov
- Department of Pathology and Laboratory MedicineAnn & Robert H. Lurie Children's Hospital of ChicagoChicagoILUSA
| | - Umay Kiraz
- Department of PathologyStavanger University HospitalStavangerNorway
- Department of Chemistry, Bioscience and Environmental TechnologyUniversity of StavangerStavangerNorway
| | - Pawan Kirtani
- Department of HistopathologyAakash Healthcare Super Speciality HospitalNew DelhiIndia
| | - Liudmila L Kodach
- Department of PathologyNetherlands Cancer Institute – Antoni van Leeuwenhoek HospitalAmsterdamThe Netherlands
| | - Konstanty Korski
- Data, Analytics and Imaging, Product DevelopmentF. Hoffmann‐La Roche AGBaselSwitzerland
| | - Anikó Kovács
- Department of Clinical PathologySahlgrenska University HospitalGothenburgSweden
- Institute of Biomedicine, Sahlgrenska AcademyUniversity of GothenburgGothenburgSweden
| | - Anne‐Vibeke Laenkholm
- Department of Surgical PathologyZealand University HospitalRoskildeDenmark
- Department of Surgical PathologyUniversity of CopenhagenCopenhagenDenmark
| | - Corinna Lang‐Schwarz
- Institute of Pathology, Klinikum Bayreuth GmbHFriedrich‐Alexander‐University Erlangen‐NurembergBayreuthGermany
| | - Denis Larsimont
- Institut Jules BordetUniversité Libre de BruxellesBrusselsBelgium
| | - Jochen K Lennerz
- Center for Integrated DiagnosticsMassachusetts General Hospital/Harvard Medical SchoolBostonMAUSA
| | - Marvin Lerousseau
- Centre for Computational Biology (CBIO)Mines Paris, PSL UniversityParisFrance
- Institut CuriePSL UniversityParisFrance
- INSERMParisFrance
| | - Xiaoxian Li
- Department of Pathology and Laboratory MedicineEmory UniversityAtlantaGAUSA
| | - Amy Ly
- Department of PathologyMassachusetts General HospitalBostonMAUSA
| | - Anant Madabhushi
- Department of Biomedical Engineering, Radiology and Imaging Sciences, Biomedical Informatics, PathologyGeorgia Institute of Technology and Emory UniversityAtlantaGAUSA
| | - Sai K Maley
- NRG Oncology/NSABP FoundationPittsburghPAUSA
| | | | | | - Elizabeth S McDonald
- Breast Cancer Translational Research GroupUniversity of PennsylvaniaPhiladelphiaPAUSA
| | - Ravi Mehrotra
- Indian Cancer Genomic AtlasPuneIndia
- Centre for Health, Innovation and Policy FoundationNoidaIndia
| | - Stefan Michiels
- Office of Biostatistics and Epidemiology, Gustave Roussy, Oncostat U1018, InsermUniversity Paris‐Saclay, Ligue Contre le Cancer labeled TeamVillejuifFrance
| | - Fayyaz ul Amir Afsar Minhas
- Tissue Image Analytics Centre, Warwick Cancer Research Centre, PathLAKE Consortium, Department of Computer ScienceUniversity of WarwickCoventryUK
| | - Shachi Mittal
- Department of Chemical Engineering, Department of Laboratory Medicine and PathologyUniversity of WashingtonSeattle, WAUSA
| | - David A Moore
- CRUK Lung Cancer Centre of Excellence, UCL and Cellular Pathology DepartmentUCLHLondonUK
| | - Shamim Mushtaq
- Department of BiochemistryZiauddin UniversityKarachiPakistan
| | - Hussain Nighat
- Pathology and Laboratory MedicineAll India Institute of Medical sciencesRaipurIndia
| | - Thomas Papathomas
- Institute of Metabolism and Systems ResearchUniversity of BirminghamBirminghamUK
- Department of Clinical PathologyDrammen Sykehus, Vestre Viken HFDrammenNorway
| | - Frederique Penault‐Llorca
- Centre Jean Perrin, Université Clermont Auvergne, INSERM, U1240 Imagerie Moléculaire et Stratégies ThéranostiquesClermont FerrandFrance
| | - Rashindrie D Perera
- School of Electrical, Mechanical and Infrastructure EngineeringUniversity of MelbourneMelbourneVictoriaAustralia
- Division of Cancer ResearchPeter MacCallum Cancer CentreMelbourneVictoriaAustralia
| | - Christopher J Pinard
- Radiogenomics LaboratorySunnybrook Health Sciences CentreTorontoOntarioCanada
- Department of Clinical Studies, Ontario Veterinary CollegeUniversity of GuelphGuelphOntarioCanada
- Department of OncologyLakeshore Animal Health PartnersMississaugaOntarioCanada
- Centre for Advancing Responsible and Ethical Artificial Intelligence (CARE‐AI)University of GuelphGuelphOntarioCanada
| | | | - Giancarlo Pruneri
- Department of Pathology and Laboratory MedicineFondazione IRCCS Istituto Nazionale dei TumoriMilanItaly
- Faculty of Medicine and SurgeryUniversity of MilanMilanItaly
| | - Lajos Pusztai
- Yale Cancer CenterYale UniversityNew HavenCTUSA
- Department of Medical Oncology, Yale School of MedicineYale UniversityNew HavenCTUSA
| | - Arman Rahman
- UCD School of Biomolecular and Biomedical Science, UCD Conway InstituteUniversity College DublinDublinIreland
| | | | - Bernardo Leon Rapoport
- The Medical Oncology Centre of RosebankJohannesburgSouth Africa
- Department of Immunology, Faculty of Health SciencesUniversity of PretoriaPretoriaSouth Africa
| | - Tilman T Rau
- Institute of PathologyUniversity Hospital Düsseldorf and Heinrich‐Heine‐University DüsseldorfDüsseldorfGermany
| | - Jorge S Reis‐Filho
- Department of Pathology and Laboratory MedicineMemorial Sloan Kettering Cancer CenterNew YorkNYUSA
| | - Joana M Ribeiro
- Département de Médecine OncologiqueGustave RoussyVillejuifFrance
| | - David Rimm
- Department of PathologyYale University School of MedicineNew HavenCTUSA
- Department of MedicineYale University School of MedicineNew HavenCTUSA
| | - Anne Roslind
- Department of PathologyHerlev and Gentofte HospitalHerlevDenmark
| | - Anne Vincent‐Salomon
- Department of Diagnostic and Theranostic Medicine, Institut CurieUniversity Paris‐Sciences et LettresParisFrance
| | - Manuel Salto‐Tellez
- Integrated Pathology UnitThe Institute of Cancer ResearchLondonUK
- Precision Medicine CentreQueen's University BelfastBelfastUK
| | - Joel Saltz
- Department of Biomedical InformaticsStony Brook UniversityStony BrookNYUSA
| | - Shahin Sayed
- Department of PathologyAga Khan UniversityNairobiKenya
| | - Ely Scott
- Translational PathologyTranslational Sciences and Diagnostics/Translational Medicine/R&D, Bristol Myers SquibbPrincetonNJUSA
| | - Kalliopi P Siziopikou
- Department of Pathology, Section of Breast PathologyNorthwestern University Feinberg School of MedicineChicagoILUSA
| | - Christos Sotiriou
- Breast Cancer Translational Research Laboratory J.‐C. Heuson, Institut Jules Bordet, Hôpital Universitaire de Bruxelles (HUB)Université Libre de Bruxelles (ULB)BrusselsBelgium
- Medical Oncology Department, Institut Jules Bordet, Hôpital Universitaire de Bruxelles (HUB)Université Libre de Bruxelles (ULB)BrusselsBelgium
| | - Albrecht Stenzinger
- Institute of PathologyUniversity Hospital HeidelbergHeidelbergGermany
- Centers for Personalized Medicine (ZPM)HeidelbergGermany
| | | | - Daniel Sur
- Department of Medical OncologyUniversity of Medicine and Pharmacy “Iuliu Hatieganu”Cluj‐NapocaRomania
| | - Susan Fineberg
- Montefiore Medical CenterBronxNYUSA
- Albert Einstein College of MedicineBronxNYUSA
| | - Fraser Symmans
- University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | | | | | - Sabine Tejpar
- Digestive Oncology, Department of OncologyKU LeuvenLeuvenBelgium
| | - Jonas Teuwen
- AI for Oncology Lab, The Netherlands Cancer InstituteAmsterdamThe Netherlands
| | | | - Trine Tramm
- Department of PathologyAarhus University HospitalAarhusDenmark
- Institute of Clinical MedicineAarhus UniversityAarhusDenmark
| | - William T Tran
- Department of Radiation OncologyUniversity of Toronto and Sunnybrook Health Sciences CentreTorontoOntarioCanada
| | - Jeroen van der Laak
- Department of PathologyRadboud University Medical CenterNijmegenThe Netherlands
| | - Paul J van Diest
- Department of PathologyUniversity Medical Center UtrechtThe Netherlands
- Johns Hopkins Oncology CenterBaltimoreMDUSA
| | - Gregory E Verghese
- Cancer Bioinformatics, School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences and MedicineKing's College LondonLondonUK
- The Breast Cancer Now Research Unit, School of Cancer and Pharmaceutical Sciences, Faculty of Life Sciences and MedicineKing's College LondonLondonUK
| | - Giuseppe Viale
- Department of PathologyEuropean Institute of OncologyMilanItaly
- Department of PathologyUniversity of MilanMilanItaly
| | - Michael Vieth
- Institute of Pathology, Klinikum Bayreuth GmbHFriedrich‐Alexander‐University Erlangen‐NurembergBayreuthGermany
| | - Noorul Wahab
- Tissue Image Analytics Centre, Department of Computer ScienceUniversity of WarwickCoventryUK
| | - Thomas Walter
- Centre for Computational Biology (CBIO)Mines Paris, PSL UniversityParisFrance
- Institut CuriePSL UniversityParisFrance
- INSERMParisFrance
| | | | - Hannah Y Wen
- Department of PathologyMemorial Sloan Kettering Cancer CenterNew YorkUSA
| | - Wentao Yang
- Fudan Medical University Shanghai Cancer CenterShanghaiPR China
| | - Yinyin Yuan
- Department of Translational Molecular Pathology, Division of Pathology and Laboratory MedicineThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Reena Md Zin
- Department of Pathology, Faculty of MedicineUniversiti Kebangsaan MalaysiaKuala LumpurMalaysia
| | - Sylvia Adams
- Perlmutter Cancer CenterNYU Langone HealthNew YorkNYUSA
- Department of MedicineNYU Grossman School of MedicineManhattanNYUSA
| | | | - Sibylle Loibl
- Department of Medicine and ResearchGerman Breast GroupNeu‐IsenburgGermany
| | - Carsten Denkert
- Institut für PathologiePhilipps‐Universität Marburg und Universitätsklinikum MarburgMarburgGermany
| | - Peter Savas
- Division of Cancer ResearchPeter MacCallum Cancer CentreMelbourneVictoriaAustralia
- The Sir Peter MacCallum Department of Medical OncologyUniversity of MelbourneMelbourneVictoriaAustralia
| | - Sherene Loi
- Division of Cancer ResearchPeter MacCallum Cancer CentreMelbourneVictoriaAustralia
- The Sir Peter MacCallum Department of Medical OncologyUniversity of MelbourneMelbourneVictoriaAustralia
| | - Roberto Salgado
- Department of PathologyGZA‐ZNA HospitalsAntwerpBelgium
- Division of Cancer ResearchPeter MacCallum Cancer CentreMelbourneVictoriaAustralia
| | - Elisabeth Specht Stovgaard
- Department of PathologyHerlev and Gentofte HospitalHerlevDenmark
- Department of Clinical MedicineUniversity of CopenhagenCopenhagenDenmark
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Li S, Zhang Y, Zhang P, Xue S, Chen Y, Sun L, Yang R. Predictive and prognostic values of tumor infiltrating lymphocytes in breast cancers treated with neoadjuvant chemotherapy: A meta-analysis. Breast 2022; 66:97-109. [PMID: 36219945 PMCID: PMC9550538 DOI: 10.1016/j.breast.2022.10.001] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 08/11/2022] [Accepted: 10/03/2022] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND This meta-analysis assessed the predictive and prognostic value of tumor infiltrating lymphocytes (TILs) in neoadjuvant chemotherapy (NACT) treated breast cancer and an optimal threshold for predicting pathologic complete response (pCR). METHODS A systematic search of PubMed, EMBASE and Web of Science electronic databases was conducted to identify eligible studies published before April 2022. Either a fixed or random effects model was applied to estimate the pooled hazard ratio (HR) and odds ratio (OR) for prognosis and predictive values of TILs in breast cancer patients treated with NACT. The study is registered with PROSPERO (CRD42020221521). RESULTS A total of 29 published studies were eligible. Increased levels of TILs predicted response to NACT in HER2 positive breast cancer (OR = 2.54 95%CI, 1.50-4.29) and triple negative breast cancer (TNBC) (OR = 3.67, 95%CI, 1.93-6.97), but not for hormone receptor (HR) positive breast cancer (OR = 1.68, 95 %CI, 0.67-4.25). A threshold of 20% of H & E-stained TILs was associated with prediction of pCR in both HER2 positive breast cancer (P = 0.035) and TNBC (P = 0.001). Moreover, increased levels of TILs (either iTILs or sTILs) were associated with survival benefit in HER2-positive breast cancer and TNBC. However, an increased level of TILs was not a prognostic factor for survival in HR positive breast cancer (pooled HR = 0.64, 95%CI: 0.03-14.1, P = 0.78). CONCLUSIONS Increased levels of TILs were associated with increased rates of response to NACT and improved prognosis for the molecular subtypes of TNBC and HER2-positive breast cancer, but not for patients with HR positive breast cancer. A threshold of 20% TILs was the most powerful outcome prognosticator of pCR.
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Affiliation(s)
- Shiqi Li
- Department of Pharmacy Administration, School of Business Administration, Shenyang Pharmaceutical University, Shenyang, China
| | - Ying Zhang
- Department of Clinical Pharmacy, School of Life Sciences and Biopharmaceuticals, Shenyang Pharmaceutical University, Shenyang, China
| | - Peigen Zhang
- Department of Pharmacy Administration, School of Business Administration, Shenyang Pharmaceutical University, Shenyang, China
| | - Shuijing Xue
- Department of Pharmacy Administration, School of Business Administration, Shenyang Pharmaceutical University, Shenyang, China
| | - Yu Chen
- Department of Pharmacy Administration, School of Business Administration, Shenyang Pharmaceutical University, Shenyang, China
| | - Lihua Sun
- Department of Pharmacy Administration, School of Business Administration, Shenyang Pharmaceutical University, Shenyang, China,Corresponding author. Department of pharmacy administration, School of Business Administration, Shenyang Pharmaceutical University, 103 Wen hua Road, Shenyang, 110016, Liaoning Province, PR China.
| | - Rui Yang
- Clinical Pharmacology Laboratory, The Second Affiliated Hospital, Liaoning University of Traditional Chinese Medicine, Shenyang, 110034, China
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12
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Corchado-Cobos R, García-Sancha N, Mendiburu-Eliçabe M, Gómez-Vecino A, Jiménez-Navas A, Pérez-Baena MJ, Holgado-Madruga M, Mao JH, Cañueto J, Castillo-Lluva S, Pérez-Losada J. Pathophysiological Integration of Metabolic Reprogramming in Breast Cancer. Cancers (Basel) 2022; 14:322. [PMID: 35053485 PMCID: PMC8773662 DOI: 10.3390/cancers14020322] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 01/03/2022] [Accepted: 01/06/2022] [Indexed: 02/04/2023] Open
Abstract
Metabolic changes that facilitate tumor growth are one of the hallmarks of cancer. The triggers of these metabolic changes are located in the tumor parenchymal cells, where oncogenic mutations induce an imperative need to proliferate and cause tumor initiation and progression. Cancer cells undergo significant metabolic reorganization during disease progression that is tailored to their energy demands and fluctuating environmental conditions. Oxidative stress plays an essential role as a trigger under such conditions. These metabolic changes are the consequence of the interaction between tumor cells and stromal myofibroblasts. The metabolic changes in tumor cells include protein anabolism and the synthesis of cell membranes and nucleic acids, which all facilitate cell proliferation. They are linked to catabolism and autophagy in stromal myofibroblasts, causing the release of nutrients for the cells of the tumor parenchyma. Metabolic changes lead to an interstitium deficient in nutrients, such as glucose and amino acids, and acidification by lactic acid. Together with hypoxia, they produce functional changes in other cells of the tumor stroma, such as many immune subpopulations and endothelial cells, which lead to tumor growth. Thus, immune cells favor tissue growth through changes in immunosuppression. This review considers some of the metabolic changes described in breast cancer.
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Affiliation(s)
- Roberto Corchado-Cobos
- Instituto de Biología Molecular y Celular del Cáncer (IBMCC-CIC), Universidad de Salamanca/CSIC, 37007 Salamanca, Spain; (R.C.-C.); (N.G.-S.); (M.M.-E.); (A.G.-V.); (A.J.-N.); (M.J.P.-B.); (J.C.)
- Instituto de Investigación Biosanitaria de Salamanca (IBSAL), 37007 Salamanca, Spain;
| | - Natalia García-Sancha
- Instituto de Biología Molecular y Celular del Cáncer (IBMCC-CIC), Universidad de Salamanca/CSIC, 37007 Salamanca, Spain; (R.C.-C.); (N.G.-S.); (M.M.-E.); (A.G.-V.); (A.J.-N.); (M.J.P.-B.); (J.C.)
- Instituto de Investigación Biosanitaria de Salamanca (IBSAL), 37007 Salamanca, Spain;
| | - Marina Mendiburu-Eliçabe
- Instituto de Biología Molecular y Celular del Cáncer (IBMCC-CIC), Universidad de Salamanca/CSIC, 37007 Salamanca, Spain; (R.C.-C.); (N.G.-S.); (M.M.-E.); (A.G.-V.); (A.J.-N.); (M.J.P.-B.); (J.C.)
- Instituto de Investigación Biosanitaria de Salamanca (IBSAL), 37007 Salamanca, Spain;
| | - Aurora Gómez-Vecino
- Instituto de Biología Molecular y Celular del Cáncer (IBMCC-CIC), Universidad de Salamanca/CSIC, 37007 Salamanca, Spain; (R.C.-C.); (N.G.-S.); (M.M.-E.); (A.G.-V.); (A.J.-N.); (M.J.P.-B.); (J.C.)
- Instituto de Investigación Biosanitaria de Salamanca (IBSAL), 37007 Salamanca, Spain;
| | - Alejandro Jiménez-Navas
- Instituto de Biología Molecular y Celular del Cáncer (IBMCC-CIC), Universidad de Salamanca/CSIC, 37007 Salamanca, Spain; (R.C.-C.); (N.G.-S.); (M.M.-E.); (A.G.-V.); (A.J.-N.); (M.J.P.-B.); (J.C.)
- Instituto de Investigación Biosanitaria de Salamanca (IBSAL), 37007 Salamanca, Spain;
| | - Manuel Jesús Pérez-Baena
- Instituto de Biología Molecular y Celular del Cáncer (IBMCC-CIC), Universidad de Salamanca/CSIC, 37007 Salamanca, Spain; (R.C.-C.); (N.G.-S.); (M.M.-E.); (A.G.-V.); (A.J.-N.); (M.J.P.-B.); (J.C.)
- Instituto de Investigación Biosanitaria de Salamanca (IBSAL), 37007 Salamanca, Spain;
| | - Marina Holgado-Madruga
- Instituto de Investigación Biosanitaria de Salamanca (IBSAL), 37007 Salamanca, Spain;
- Departamento de Fisiología y Farmacología, Universidad de Salamanca, 37007 Salamanca, Spain
- Instituto de Neurociencias de Castilla y León (INCyL), Universidad de Salamanca, 37007 Salamanca, Spain
| | - Jian-Hua Mao
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA;
- Berkeley Biomedical Data Science Center, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Javier Cañueto
- Instituto de Biología Molecular y Celular del Cáncer (IBMCC-CIC), Universidad de Salamanca/CSIC, 37007 Salamanca, Spain; (R.C.-C.); (N.G.-S.); (M.M.-E.); (A.G.-V.); (A.J.-N.); (M.J.P.-B.); (J.C.)
- Instituto de Investigación Biosanitaria de Salamanca (IBSAL), 37007 Salamanca, Spain;
- Departamento de Dermatología, Hospital Universitario de Salamanca, Paseo de San Vicente 58-182, 37007 Salamanca, Spain
- Complejo Asistencial Universitario de Salamanca, 37007 Salamanca, Spain
| | - Sonia Castillo-Lluva
- Departamento de Bioquímica y Biología Molecular, Facultad de Ciencias Químicas, Universidad Complutense, 28040 Madrid, Spain
- Instituto de Investigaciones Sanitarias San Carlos (IdISSC), 28040 Madrid, Spain
| | - Jesús Pérez-Losada
- Instituto de Biología Molecular y Celular del Cáncer (IBMCC-CIC), Universidad de Salamanca/CSIC, 37007 Salamanca, Spain; (R.C.-C.); (N.G.-S.); (M.M.-E.); (A.G.-V.); (A.J.-N.); (M.J.P.-B.); (J.C.)
- Instituto de Investigación Biosanitaria de Salamanca (IBSAL), 37007 Salamanca, Spain;
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Yu Y, Wu S, Xing H, Han M, Li J, Liu Y. Development and Validation of a Novel Model for Predicting Prognosis of Non-PCR Patients After Neoadjuvant Therapy for Breast Cancer. Front Oncol 2021; 11:675533. [PMID: 34540660 PMCID: PMC8440922 DOI: 10.3389/fonc.2021.675533] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 08/09/2021] [Indexed: 12/31/2022] Open
Abstract
Purpose Pathologic complete response (pCR) after neoadjuvant therapy is an important indicator of long-term prognosis and the primary endpoint of many neoadjuvant studies. For breast cancer patients who do not achieve pCR, prognostic indicators related to prognosis are particularly important. This study is constructing a prediction model with more accurate and reliable prediction results by combining multiple clinicopathological factors, so as to provide a more accurate decision-making basis for subsequent clinical treatment. Patients and Methods In this study, 1,009 cases of invasive breast cancer and surgically resected after neoadjuvant therapy from 2010 to 2017. All indicators in this trial were interpreted in a double-blind manner by two pathologists with at least 10 years of experience, including histological grading, Tils, ER, PR, HER2, and Ki67. The prediction model used R language to calculate the calibration degree and ROC curve of the prediction model in the training set and validation set. Results Through univariate survival analysis, the results showed histological grade (P=0.037), clinical stage (P<0.001), HER2 (P=0.044), RCB class (P<0.001), Tils (P<0.001), lymph node status (P =0.049), MP grade (P=0.013) are related to OS in non-PCR patients after neoadjuvant. Data were analyzed by substituting in a multivariate analysis, and the results were that clinical stage, HER2, RCB grading, and Tils grading were correlated with OS in non-PCR patients after neoadjuvant therapy for breast cancer. Among all cases in the training set, the prediction model predicted that the 3-year survival AUC value was 0.95 and 5-year survival AUC value was 0.79, and the RCB classification of 3-year survival and 5-year survival were 0.70 and 0.67, respectively, which proved that the prediction model could predict the OS of non-PCR patients after neoadjuvant therapy for breast cancer more accurately than the RCB classification, and showed the same results in HR, HER2+, and TN classifications. It also showed the same results in validation set. Conclusion These data indicate that the predicted values of the prediction model developed in this study match the actual survival rates without underestimating the mortality risk and have a relatively accurate prediction effect.
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Affiliation(s)
- Yongqiang Yu
- Department of Pathology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Si Wu
- Department of Pathology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Hui Xing
- Department of Pathology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Mengxue Han
- Department of Pathology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Jinze Li
- Department of Pathology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Yueping Liu
- Department of Pathology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
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14
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Saraiva DP, Azeredo-Lopes S, Antunes A, Salvador R, Borralho P, Assis B, Pereira IL, Seabra Z, Negreiros I, Jacinto A, Braga S, Cabral MG. Expression of HLA-DR in Cytotoxic T Lymphocytes: A Validated Predictive Biomarker and a Potential Therapeutic Strategy in Breast Cancer. Cancers (Basel) 2021; 13:cancers13153841. [PMID: 34359741 PMCID: PMC8345089 DOI: 10.3390/cancers13153841] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 07/21/2021] [Accepted: 07/27/2021] [Indexed: 12/09/2022] Open
Abstract
Simple Summary More than 50% of breast cancer (BC) patients selected for neoadjuvant chemotherapy (NACT) are subjected to at least a 6-month regimen of this treatment without a clear benefit, probably delaying more effective therapeutic strategies and being exposed to potential treatment-associated toxicity. Thus, it is urgent to implement reliable predictive biomarkers, as well as novel treatments for NACT non-responder patients. This study validates that the HLA-DR level in cytotoxic T lymphocytes (CTLs) is an independent and robust predictive factor of BC patients’ response to NACT, as previously proposed. Hence, a predictive probability model of response was developed as a new tool to improve treatment decisions. HLA-DR level in CTLs also have a general prognostic value, which might be relevant for long-term BC management. In addition, our results suggest that increasing the expression of HLA-DR in CTLs of non-responders could be a promising therapeutic strategy to ameliorate BC response to NACT. Abstract Neoadjuvant chemotherapy (NACT) is common in breast cancer (BC) treatment, though more than half of the patients lack an effective response. Therefore, new predictive biomarkers and alternative therapies are crucial. Previously, we proposed HLA-DR-expressing cytotoxic T lymphocytes (CTLs) as a potential biomarker of the response to NACT. To validate this observation and further investigate these cells, 202 BC patients were enrolled. Flow cytometry analyses were performed in 61 biopsies and 41 blood samples pre-NACT and 100 non-NACT tumor samples. All the patients were followed up for 34 months. Blood-isolated immune cells were cultured with BC cell lines in a 3D system. We confirmed that HLA-DR level in CTLs is a highly sensitive, specific, and independent biomarker to predict response to NACT and developed a predictive probability model. This biomarker was also associated with progression-free survival, regardless of the treatment. The clinical observations are substantiated by the anti-tumor properties of HLA-DR-expressing CTLs. Intriguingly, HLA-DR level in CTLs can be modulated ex vivo, boosting their capacity to kill tumor cells synergistically with doxorubicin. Thus, HLA-DR expression in CTLs is a validated tool to select patients that will actually benefit from NACT, and its stimulation might be a novel therapeutic approach for BC.
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Affiliation(s)
- Diana P. Saraiva
- iNOVA4Health, CEDOC, NOVA Medical School (NMS), Universidade Nova de Lisboa, 1150-082 Lisbon, Portugal; (D.P.S.); (R.S.); (A.J.); (S.B.)
| | - Sofia Azeredo-Lopes
- Public Health and Biostatistics Department, NOVA Medical School (NMS), Universidade Nova de Lisboa, 1150-082 Lisbon, Portugal;
| | - Ana Antunes
- CHRC, CEDOC, NOVA Medical School (NMS), Universidade Nova de Lisboa, 1150-082 Lisbon, Portugal;
| | - Rute Salvador
- iNOVA4Health, CEDOC, NOVA Medical School (NMS), Universidade Nova de Lisboa, 1150-082 Lisbon, Portugal; (D.P.S.); (R.S.); (A.J.); (S.B.)
| | - Paula Borralho
- Unidade de Mama, Instituto CUF de Oncologia, 1998-018 Lisbon, Portugal; (P.B.); (B.A.); (I.L.P.); (I.N.)
- Instituto de Anatomia Patológica, Faculdade de Medicina da Universidade de Lisboa, 1649-028 Lisbon, Portugal
| | - Beatriz Assis
- Unidade de Mama, Instituto CUF de Oncologia, 1998-018 Lisbon, Portugal; (P.B.); (B.A.); (I.L.P.); (I.N.)
| | - Isabel L. Pereira
- Unidade de Mama, Instituto CUF de Oncologia, 1998-018 Lisbon, Portugal; (P.B.); (B.A.); (I.L.P.); (I.N.)
| | - Zita Seabra
- Unidade de Imagiologia, Hospital Vila Franca de Xira, 2600-009 Vila Franca de Xira, Portugal;
| | - Ida Negreiros
- Unidade de Mama, Instituto CUF de Oncologia, 1998-018 Lisbon, Portugal; (P.B.); (B.A.); (I.L.P.); (I.N.)
| | - António Jacinto
- iNOVA4Health, CEDOC, NOVA Medical School (NMS), Universidade Nova de Lisboa, 1150-082 Lisbon, Portugal; (D.P.S.); (R.S.); (A.J.); (S.B.)
| | - Sofia Braga
- iNOVA4Health, CEDOC, NOVA Medical School (NMS), Universidade Nova de Lisboa, 1150-082 Lisbon, Portugal; (D.P.S.); (R.S.); (A.J.); (S.B.)
- Unidade de Mama, Instituto CUF de Oncologia, 1998-018 Lisbon, Portugal; (P.B.); (B.A.); (I.L.P.); (I.N.)
| | - M. Guadalupe Cabral
- iNOVA4Health, CEDOC, NOVA Medical School (NMS), Universidade Nova de Lisboa, 1150-082 Lisbon, Portugal; (D.P.S.); (R.S.); (A.J.); (S.B.)
- Correspondence: ; Tel.: +351-218-803-000
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15
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Lusho S, Durando X, Mouret-Reynier MA, Kossai M, Lacrampe N, Molnar I, Penault-Llorca F, Radosevic-Robin N, Abrial C. Platelet-to-Lymphocyte Ratio Is Associated With Favorable Response to Neoadjuvant Chemotherapy in Triple Negative Breast Cancer: A Study on 120 Patients. Front Oncol 2021; 11:678315. [PMID: 34367964 PMCID: PMC8331686 DOI: 10.3389/fonc.2021.678315] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 06/29/2021] [Indexed: 12/31/2022] Open
Abstract
Introduction Triple negative breast cancer (TNBC) is highly heterogeneous, but still most of the patients are treated by the anthracycline/taxane-based neoadjuvant therapy (NACT). Tumor-infiltrating lymphocytes (TILs) are a strong predictive and prognostic biomarker in TNBC, however are not always available. Peripheral blood counts, which reflect the systemic inflammatory/immune status, are easier to obtain than TILs. We investigated whether baseline white cell or platelet counts, as well as, Neutrophil-to-Lymphocyte Ratio (NLR) or Platelet-to-Lymphocyte Ratio (PLR) could replace baseline TILs as predictive or prognostic biomarkers in a series of TNBC treated by standard NACT. Patients and Methods One hundred twenty patients uniformly treated by FEC/taxane NACT in a tertiary cancer care center were retrospectively analyzed. The presence of pathological complete response (pCR: ypT0/Tis, ypN0) or the presence of pCR and/small residual disease (ypT0/Tis/T1ab, ypN0) were considered as good responses in data analysis. Baseline/pre-NACT blood count, NLR, PLR and TILs were evaluated as predictors of response, distant recurrence rate and distant recurrence-free survival (DRFS). Results TILs ≥30% and ≥1.5% were best predictors of pCR and distant recurrence risk, respectively (p = 0.007, p = 0.012). However, in this cohort, pCR status was not significantly associated with recurrence. Only the ensemble of patients with pCR and small residual disease had lower recurrence risk and longer survival DRFS (p = 0.042, p = 0.024, respectively) than the rest of the cohort (larger residual disease). The only parameter which could predict the pCR/small residual disease status was PLR: patients with values lower than 133.25 had significantly higher chance of reaching that status after NACT (p = 0.045). However, no direct correlation could be established between baseline PLR and metastatic recurrence. No correlation either was found between TIL and individual blood counts, or between TILs and NLR or PLR. Conclusion In this cohort, TILs retained their pCR predictive value; however PLR was a better predictor of the ensemble of responses which had good outcome in terms of less distant recurrences or longer DRFS (pCR or small residual disease). Thus, baseline PLR is worth further, prospective investigation together with baseline TILs, as it might indicate a good TNBC response to NACT when TILs are unavailable.
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Affiliation(s)
- Sejdi Lusho
- Clermont Auvergne University, INSERM U1240 "Molecular Imaging and Theranostic Strategies", Centre Jean Perrin, Clermont-Ferrand, France.,Delegation for Clinical Research and Innovation, Centre Jean Perrin, Clermont-Ferrand, France.,Centre for Clinical Investigation, INSERM U501, Clermont-Ferrand, France
| | - Xavier Durando
- Clermont Auvergne University, INSERM U1240 "Molecular Imaging and Theranostic Strategies", Centre Jean Perrin, Clermont-Ferrand, France.,Delegation for Clinical Research and Innovation, Centre Jean Perrin, Clermont-Ferrand, France.,Centre for Clinical Investigation, INSERM U501, Clermont-Ferrand, France.,Department of Medical Oncology, Centre Jean Perrin, Clermont-Ferrand, France
| | - Marie-Ange Mouret-Reynier
- Clermont Auvergne University, INSERM U1240 "Molecular Imaging and Theranostic Strategies", Centre Jean Perrin, Clermont-Ferrand, France.,Delegation for Clinical Research and Innovation, Centre Jean Perrin, Clermont-Ferrand, France.,Centre for Clinical Investigation, INSERM U501, Clermont-Ferrand, France.,Department of Medical Oncology, Centre Jean Perrin, Clermont-Ferrand, France
| | - Myriam Kossai
- Clermont Auvergne University, INSERM U1240 "Molecular Imaging and Theranostic Strategies", Centre Jean Perrin, Clermont-Ferrand, France.,Department of Pathology, Centre Jean Perrin, Clermont-Ferrand, France
| | - Nathalie Lacrampe
- Clermont Auvergne University, INSERM U1240 "Molecular Imaging and Theranostic Strategies", Centre Jean Perrin, Clermont-Ferrand, France.,Department of Pathology, Centre Jean Perrin, Clermont-Ferrand, France
| | - Ioana Molnar
- Clermont Auvergne University, INSERM U1240 "Molecular Imaging and Theranostic Strategies", Centre Jean Perrin, Clermont-Ferrand, France.,Delegation for Clinical Research and Innovation, Centre Jean Perrin, Clermont-Ferrand, France.,Centre for Clinical Investigation, INSERM U501, Clermont-Ferrand, France
| | - Frederique Penault-Llorca
- Clermont Auvergne University, INSERM U1240 "Molecular Imaging and Theranostic Strategies", Centre Jean Perrin, Clermont-Ferrand, France
| | - Nina Radosevic-Robin
- Clermont Auvergne University, INSERM U1240 "Molecular Imaging and Theranostic Strategies", Centre Jean Perrin, Clermont-Ferrand, France.,Department of Pathology, Centre Jean Perrin, Clermont-Ferrand, France
| | - Catherine Abrial
- Clermont Auvergne University, INSERM U1240 "Molecular Imaging and Theranostic Strategies", Centre Jean Perrin, Clermont-Ferrand, France.,Delegation for Clinical Research and Innovation, Centre Jean Perrin, Clermont-Ferrand, France.,Centre for Clinical Investigation, INSERM U501, Clermont-Ferrand, France
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16
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Wang Y, Zong B, Yu Y, Wang Y, Tang Z, Chen R, Huang M, Liu S. Ki67 Index Changes and Tumor-Infiltrating Lymphocyte Levels Impact the Prognosis of Triple-Negative Breast Cancer Patients With Residual Disease After Neoadjuvant Chemotherapy. Front Oncol 2021; 11:668610. [PMID: 34235079 PMCID: PMC8256666 DOI: 10.3389/fonc.2021.668610] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 06/02/2021] [Indexed: 11/13/2022] Open
Abstract
Purpose The aim of this study was to assess the prognostic influence of Ki67 index changes in patients with primary triple-negative breast cancer (TNBC) treated with neoadjuvant chemotherapy (NAC), and to evaluate whether the combination of Ki67 index changes and residual disease (RD) tumor-infiltrating lymphocytes (TILs) provides additional prognostic information for this group. Materials and Methods Data from 109 patients with primary TNBC and RD after NAC were analyzed retrospectively. Ki67 changes and RD TIL levels were investigated for associations with recurrence-free survival (RFS) and overall survival (OS) using Kaplan-Meier and Cox analyses. Results Ki67 index decreased after NAC in 53 patients (48.6%) and high RD TIL levels (≥30%) were observed in 54 patients (49.5%). In multivariate Cox analyses, no Ki67 decrease status and low RD TIL levels were significantly associated with reduced RFS (hazard ratio (HR): 2.038, 95% confidence interval (CI): 1.135-3.658, P = 0.017; HR: 2.493, 95% CI: 1.335-4.653, P = 0.004), and OS (HR: 2.187, 95% CI: 1.173-4.077, P = 0.014; HR: 2.499, 95% CI: 1.285-4.858, P = 0.007), respectively. Notably, low RD TIL levels were significantly associated with reduced RFS (HR: 3.567, 95% CI: 1.475-8.624, P = 0.005) and reduced OS (HR: 3.873, 95% CI: 1.512-9.918, P = 0.005) in only the no Ki67 decrease group. The differences in 3-year RFS and OS between patients with no Ki67 decrease and low or high RD TIL levels were 24.4% vs 79.1% (P = 0.0001) and 33.1% vs 87.5% (P = 0.0001), respectively. Conclusion Ki67 index changes and RD TIL levels were associated with the prognosis of patients with primary TNBC with RD after NAC. RD TIL levels had greater prognostic significance in the no Ki67 decrease group.
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Affiliation(s)
- Yihua Wang
- Department of Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Beige Zong
- Department of Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yu Yu
- Department of Pathology, Chongqing Medical University, Chongqing, China
| | - Yu Wang
- Department of Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Zhenrong Tang
- Department of Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Rui Chen
- Department of Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.,Department of Thyroid and Breast Surgery, The Affiliated Hospital of Zunyi Medical University, Zunyi, China
| | - Man Huang
- Department of Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Shengchun Liu
- Department of Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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17
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Sarradin V, Lusque A, Filleron T, Dalenc F, Franchet C. Immune microenvironment changes induced by neoadjuvant chemotherapy in triple-negative breast cancers: the MIMOSA-1 study. Breast Cancer Res 2021; 23:61. [PMID: 34039396 PMCID: PMC8157437 DOI: 10.1186/s13058-021-01437-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Accepted: 05/12/2021] [Indexed: 02/06/2023] Open
Abstract
Background The immune microenvironment (IME) of triple-negative breast cancers (TNBCs) and its modulation by neoadjuvant chemotherapy (NACT) remain to be fully characterized. Our current study aims to evaluate NACT-induced IME changes and assess the prognostic value of specific immune biomarkers. Methods Tumor-infiltrating lymphocytes (TILs) were identified from hematoxylin-eosin-stained sections of paired pre- and post-NACT tumor samples from a TNBC cohort (n = 66) and expression of PD-L1, TIM-3, and LAG-3 evaluated by immunohistochemistry. Results Overall TIL counts and PD-L1 expression did not differ pre- and post-NACT, but there was a response-specific statistically significant difference. TIL counts decreased in 65.5% of patients who achieved a pathological complete response (pCR) and increased in 56.8% of no-pCR patients (p = 0.0092). PD-L1 expression was significantly more frequently lost after NACT in pCR than in no-pCR patients (41.4% vs 16.2%, p = 0.0020). TIM-3 positivity (≥ 1%) was significantly more frequent after NACT (p < 0.0001) with increases in expression levels occurring more frequently in no-pCR than in pCR patients (51.4% vs 31%). LAG-3 expression significantly decreased after NACT, but there was no difference between response groups. Before NACT, a high TIL count (> 10%) was significantly associated with better overall survival (OS), p = 0.0112. After NACT, PD-L1 positivity and strong TIM-3 positivity (≥ 5%) were both associated with significantly worse OS (p = 0.0055 and p = 0.0274, respectively). Patients positive for both PD-L1 and TIM-3 had the worst prognosis (p = 0.0020), even when only considering patients who failed to achieve a pCR, p = 0.0479. Conclusions NACT induces significant IME changes in TNBCs. PD-L1 and TIM-3 expression post-NACT may yield important prognostic information for TNBC patients. Supplementary Information The online version contains supplementary material available at 10.1186/s13058-021-01437-4.
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Affiliation(s)
- Victor Sarradin
- Department of Medical Oncology, Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse, IUCT-Oncopole, 1 avenue Irène Joliot-Curie, 31059, Toulouse Cedex 9, France.
| | - Amélie Lusque
- Department of Biostatistics, Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse, IUCT-Oncopole, Toulouse, France
| | - Thomas Filleron
- Department of Biostatistics, Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse, IUCT-Oncopole, Toulouse, France
| | - Florence Dalenc
- Department of Medical Oncology, Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse, IUCT-Oncopole, 1 avenue Irène Joliot-Curie, 31059, Toulouse Cedex 9, France
| | - Camille Franchet
- Department of Pathology, Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse, IUCT-Oncopole, Toulouse, France
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Goldberg J, Pastorello RG, Vallius T, Davis J, Cui YX, Agudo J, Waks AG, Keenan T, McAllister SS, Tolaney SM, Mittendorf EA, Guerriero JL. The Immunology of Hormone Receptor Positive Breast Cancer. Front Immunol 2021; 12:674192. [PMID: 34135901 PMCID: PMC8202289 DOI: 10.3389/fimmu.2021.674192] [Citation(s) in RCA: 74] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Accepted: 04/13/2021] [Indexed: 12/11/2022] Open
Abstract
Immune checkpoint blockade (ICB) has revolutionized the treatment of cancer patients. The main focus of ICB has been on reinvigorating the adaptive immune response, namely, activating cytotoxic T cells. ICB has demonstrated only modest benefit against advanced breast cancer, as breast tumors typically establish an immune suppressive tumor microenvironment (TME). Triple-negative breast cancer (TNBC) is associated with infiltration of tumor infiltrating lymphocytes (TILs) and patients with TNBC have shown clinical responses to ICB. In contrast, hormone receptor positive (HR+) breast cancer is characterized by low TIL infiltration and minimal response to ICB. Here we review how HR+ breast tumors establish a TME devoid of TILs, have low HLA class I expression, and recruit immune cells, other than T cells, which impact response to therapy. In addition, we review emerging technologies that have been employed to characterize components of the TME to reveal that tumor associated macrophages (TAMs) are abundant in HR+ cancer, are highly immune-suppressive, associated with tumor progression, chemotherapy and ICB-resistance, metastasis and poor survival. We reveal novel therapeutic targets and possible combinations with ICB to enhance anti-tumor immune responses, which may have great potential in HR+ breast cancer.
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Affiliation(s)
- Jonathan Goldberg
- Breast Tumor Immunology Laboratory, Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, United States
| | - Ricardo G. Pastorello
- Breast Tumor Immunology Laboratory, Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, United States
- Division of Breast Surgery, Department of Surgery, Brigham and Women’s Hospital, Boston, MA, United States
| | - Tuulia Vallius
- Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Medical School, Boston, MA, United States
| | - Janae Davis
- Breast Tumor Immunology Laboratory, Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, United States
- Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Medical School, Boston, MA, United States
| | - Yvonne Xiaoyong Cui
- Breast Tumor Immunology Laboratory, Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, United States
| | - Judith Agudo
- Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA, United States
- Department of Immunology, Harvard Medical School, Boston, MA, United States
| | - Adrienne G. Waks
- Breast Oncology Program, Dana-Farber Cancer Institute, Boston, MA, United States
| | - Tanya Keenan
- Breast Oncology Program, Dana-Farber Cancer Institute, Boston, MA, United States
| | - Sandra S. McAllister
- Division of Hematology, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, United States
- Department of Medicine, Harvard Medical School, Boston, MA, United States
- Harvard Stem Cell Institute, Cambridge, MA, United States
| | - Sara M. Tolaney
- Breast Oncology Program, Dana-Farber Cancer Institute, Boston, MA, United States
| | - Elizabeth A. Mittendorf
- Breast Tumor Immunology Laboratory, Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, United States
- Division of Breast Surgery, Department of Surgery, Brigham and Women’s Hospital, Boston, MA, United States
- Breast Oncology Program, Dana-Farber Cancer Institute, Boston, MA, United States
- Ludwig Center for Cancer Research at Harvard, Harvard Medical School, Boston, MA, United States
| | - Jennifer L. Guerriero
- Breast Tumor Immunology Laboratory, Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, United States
- Division of Breast Surgery, Department of Surgery, Brigham and Women’s Hospital, Boston, MA, United States
- Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Medical School, Boston, MA, United States
- Ludwig Center for Cancer Research at Harvard, Harvard Medical School, Boston, MA, United States
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Tumor-Infiltrating Lymphocytes in Low-Risk Patients With Breast Cancer Treated With Single-Dose Preoperative Partial Breast Irradiation. Int J Radiat Oncol Biol Phys 2020; 109:1325-1331. [PMID: 33333201 DOI: 10.1016/j.ijrobp.2020.12.009] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Revised: 12/03/2020] [Accepted: 12/07/2020] [Indexed: 12/25/2022]
Abstract
PURPOSE Preoperative partial breast irradiation (PBI) has the potential to induce tumor regression. We evaluated the differences in the numbers of preirradiation tumor infiltrating lymphocytes (TILs) between responders and nonresponders after preoperative PBI in low-risk patients with breast cancer. Furthermore, we evaluated the change in number of TILs before and after irradiation. METHODS AND MATERIALS In the prospective ABLATIVE study, low-risk patients with breast cancer underwent treatment with single-dose preoperative PBI (20 Gy) to the tumor and breast-conserving surgery after 6 or 8 months. In the preirradiation diagnostic biopsy and postirradiation resection specimen, numbers of TILs in 3 square regions of 450 × 450 μm were counted manually. TILs were visualized with CD3, CD4, and CD8 immunohistochemistry. Differences in numbers of preirradiation TILs between responders and nonresponders were tested using Mann-Whitney U test. Responders were defined as pathologic complete or near-complete response, and nonresponders were defined "as all other response." Changes in numbers of TILs after preoperative PBI was evaluated with the Wilcoxon signed rank test. RESULTS Preirradiation tissue was available from 28 patients, postirradiation tissue from 29 patients, resulting in 22 pairs of preirradiation and postirradiation tissue. In these 35 patients, 15 had pathologic complete response (43%), 11 had a near-complete response (31%), 7 had a partial response (20%), and 2 had stable disease (6%). The median numbers of CD3+ TILs, CD4+ TILs, and CD8+ TILs in the preirradiation tumor tissue were 49 (interquartile range [IQR], 36-80), 45 (IQR, 28-57), and 19 (IQR, 8-35), respectively. The number of preirradiation TILs did not differ significantly between responders and nonresponders. The median numbers of CD3+ TILs, CD4+ TILs, and CD8+ TILs in postirradiation tumor tissue were 17 (IQR, 13-31), 26 (IQR, 16-35), and 7 (IQR, 5-11), respectively. CONCLUSIONS After preoperative PBI in this limited cohort, the number of TILs in tumor tissue decreased. No differences in numbers of preirradiation TILs between responders and nonresponders were observed.
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Flerin NC, Cappellesso F, Pretto S, Mazzone M. Metabolic traits ruling the specificity of the immune response in different cancer types. Curr Opin Biotechnol 2020; 68:124-143. [PMID: 33248423 DOI: 10.1016/j.copbio.2020.10.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Accepted: 10/26/2020] [Indexed: 12/24/2022]
Abstract
Cancer immunotherapy aims to augment the response of the patient's own immune system against cancer cells. Despite effective for some patients and some cancer types, the therapeutic efficacy of this treatment is limited by the composition of the tumor microenvironment (TME), which is not well-suited for the fitness of anti-tumoral immune cells. However, the TME differs between cancer types and tissues, thus complicating the possibility of the development of therapies that would be effective in a large range of patients. A possible scenario is that each type of cancer cell, granted by its own mutations and reminiscent of the functions of the tissue of origin, has a specific metabolism that will impinge on the metabolic composition of the TME, which in turn specifically affects T cell fitness. Therefore, targeting cancer or T cell metabolism could increase the efficacy and specificity of existing immunotherapies, improving disease outcome and minimizing adverse reactions.
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Affiliation(s)
- Nina C Flerin
- Laboratory of Tumor Inflammation and Angiogenesis, Center for Cancer Biology, VIB, Leuven, B3000, Belgium; Laboratory of Tumor Inflammation and Angiogenesis, Center for Cancer Biology, Department of Oncology, KU Leuven, Leuven, B3000, Belgium
| | - Federica Cappellesso
- Laboratory of Tumor Inflammation and Angiogenesis, Center for Cancer Biology, VIB, Leuven, B3000, Belgium; Laboratory of Tumor Inflammation and Angiogenesis, Center for Cancer Biology, Department of Oncology, KU Leuven, Leuven, B3000, Belgium
| | - Samantha Pretto
- Laboratory of Tumor Inflammation and Angiogenesis, Center for Cancer Biology, VIB, Leuven, B3000, Belgium; Laboratory of Tumor Inflammation and Angiogenesis, Center for Cancer Biology, Department of Oncology, KU Leuven, Leuven, B3000, Belgium
| | - Massimiliano Mazzone
- Laboratory of Tumor Inflammation and Angiogenesis, Center for Cancer Biology, VIB, Leuven, B3000, Belgium; Laboratory of Tumor Inflammation and Angiogenesis, Center for Cancer Biology, Department of Oncology, KU Leuven, Leuven, B3000, Belgium.
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Tang S, Wang K, Zheng K, Liu J, Zhang H, Tan M, Li H, Li H, Tan X, Liu D, Guo R. Clinical and pathological response to neoadjuvant chemotherapy with different chemotherapy regimens predicts the outcome of locally advanced breast cancer. Gland Surg 2020; 9:1415-1427. [PMID: 33224817 DOI: 10.21037/gs-20-209] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Background This retrospective analysis was designed to research whether clinical response partial response (PR)/complete response (CR) and pathological response (PCR) to neoadjuvant chemotherapy can translate into prognosis benefit pathological response in patients with locally advanced breast cancer and whether different chemotherapy regimens will influence the outcomes. Methods One hundred and thirty-five patients with breast cancer patients who received neoadjuvant chemotherapy were included in the retrospective analysis. Patients were followed up strictly. Overall survival (OS) was evaluated by the Kaplan-Meier analysis. The comparison of the clinical and pathological characteristics and recurrence was performed using the carried out by chi-squared and Fisher's exact tests. Univariate and multivariate analyses were performed by the Cox regression analysis. Results Clinical response was strongly correlated with lymph nodes status (P=0.032). The OS comparison of pathological response between the pCR group and non-pCR groups did not exhibit statistically significant differences (P=0.400). A similar non-significant response result was observed in the comparison of clinical response between the PR/CR and SD/PD groups group (P=0.108). Univariate and multivariate analyses did not support clinical response (P=0.156 P=0.095 respectively) or pathological response (P=0.600 P=0.144 respectively) as the predictors of prognosis. There were no significant differences in either the comparison of the clinical response group it seems no statistically significance (P=0.496) or the comparison of the pathological response group (P=0.460). OS analyses across different neoadjuvant chemotherapy regimens demonstrated no significant differences (P=0.307). In the PR/CR and PD/SD comparison of every single regimen, there were no significant differences. However, for patients with PR/CR patients from the comparison of five regimens, namely, TAC, FAC, AC-T, AT and TCBP demonstrated a significant difference (P=0.022). In the group of patients with luminal A breast cancer, the result of the Fisher's exact test approached significant (P=0.059). Conclusions Neither PR/CR nor pCR can translate into long-term outcome benefit. PR/CR and PCR are not independent predictors in patients with advanced breast cancer. Patients who received a taxane + anthracycline regimen exhibited a higher recurrence rate than any other regimens, especially those patients with luminal A breast cancer.
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Affiliation(s)
- Shicong Tang
- Department of Breast Surgery, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, China
| | - Ke Wang
- Department of Breast Surgery, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, China
| | - Kai Zheng
- Department of Breast Surgery, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, China
| | - Jiadong Liu
- Department of Breast Surgery, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, China
| | - Hengyu Zhang
- Department of Breast Surgery, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, China
| | - Mingjian Tan
- Department of Breast Surgery, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, China
| | - Hongwan Li
- Department of Breast Surgery, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, China
| | - Huimeng Li
- Department of Breast Surgery, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, China
| | - Xin Tan
- Department of Breast Surgery, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, China
| | - Dequan Liu
- Department of Breast Surgery, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, China
| | - Rong Guo
- Department of Breast Surgery, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, China
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22
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Liu S, Zeng S, Xia L, Yu M, Zhang X, Yang H, Ji J, Dong H, Zhang J, Zhang P. Tumor-infiltrating lymphocytes benefit prediction of axillary pathologic response and prognostication of event-free survival in HER2-positive and biopsy-proven node-positive breast cancer treated with neoadjuvant therapy. Breast Cancer Res Treat 2020; 185:629-638. [PMID: 33165709 DOI: 10.1007/s10549-020-06015-4] [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: 02/29/2020] [Accepted: 11/03/2020] [Indexed: 10/23/2022]
Abstract
PURPOSE The present study evaluated tumor-infiltrating lymphocytes (TILs) based on standardized scoring method and investigated its predictive value for axillary pathologic complete response (apCR) and prognostic significance for event-free survival (EFS) in neoadjuvant-treated HER2-positive breast cancer with initially biopsy-proven nodal metastasis. METHODS We assessed TILs in a total of 187 pretherapeutic core biopsies of primary tumors. Receiver operating characteristic curve analysis was conducted to calculate the optimal cut-off point of TILs in discriminating axillary pathologic response. The associations of TILs with apCR or EFS were investigated by univariate and multivariate analyses. RESULTS Receiver operating characteristic curve analysis identified a 10% cut-off point of TILs that optimally discriminated apCR from non-apCR (P < 0.001). High TILs were determined as TILs ≥ 10%, and tumor with TILs < 10% was defined as lymphocyte-depleted breast cancer (LDBC). The apCR rate of the entire cohort was 66.3% (124/187). Tumors with high TILs had a significantly higher apCR rate compared with LDBC (78.5% vs. 43.9%; P < 0.001). High TILs (P < 0.001), breast pathologic complete response (P = 0.006), and negative status of hormone receptor (P = 0.021) were independent predictors for apCR. High TILs were a markedly powerful predictor with an odds ratio of 4.01 (P < 0.001). EFS was significantly better among patients with high TILs than among those with LDBC (P < 0.001). Univariate and multivariate analyses indicated that high TILs (P = 0.019) and apCR (P = 0.013) were independent predictors for favorable EFS. CONCLUSIONS TILs have predictive value for apCR and prognostic significance for EFS in initially node-positive and HER2-positive breast cancer treated with neoadjuvant therapy. LDBC (TILs < 10%) has a significantly unfavorable impact on apCR rate and EFS.
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Affiliation(s)
- Shiwei Liu
- Department of Breast Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610000, China
| | - Shiyan Zeng
- Department of Breast Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610000, China
| | - Li Xia
- Department of Breast Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610000, China
| | - Miao Yu
- Department of Breast Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610000, China
| | - Xin Zhang
- Department of Breast Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610000, China
| | - Hong Yang
- Department of Pathology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610000, China
| | - Juan Ji
- Department of Pathology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610000, China
| | - Hao Dong
- Department of Pathology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610000, China
| | - Jianhui Zhang
- Department of Breast Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610000, China
| | - Purong Zhang
- Department of Breast Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610000, China.
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Zhao S, Zuo WJ, Shao ZM, Jiang YZ. Molecular subtypes and precision treatment of triple-negative breast cancer. ANNALS OF TRANSLATIONAL MEDICINE 2020; 8:499. [PMID: 32395543 PMCID: PMC7210152 DOI: 10.21037/atm.2020.03.194] [Citation(s) in RCA: 79] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Accepted: 03/25/2020] [Indexed: 12/16/2022]
Abstract
Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype. Despite the progress made in precision treatment of cancer patients, targeted treatment is still at its early stage in TNBC, and chemotherapy remains the standard treatment. With the advances in next generation sequencing technology, genomic and transcriptomic analyses have provided deeper insight into the inter-tumoral heterogeneity of TNBC. Much effort has been made to classify TNBCs into different molecular subtypes according to genetic aberrations and expression signatures and to uncover novel treatment targets. In this review, we summarized the current knowledge regarding the molecular classification of TNBC and explore the future paradigm for using molecular classification to guide the development of precision treatment and clinical practice.
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Affiliation(s)
- Shen Zhao
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China
| | - Wen-Jia Zuo
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China
| | - Zhi-Ming Shao
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China
| | - Yi-Zhou Jiang
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China
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Kagihara JA, Andress M, Diamond JR. Nab-paclitaxel and atezolizumab for the treatment of PD-L1-positive, metastatic triple-negative breast cancer: review and future directions. EXPERT REVIEW OF PRECISION MEDICINE AND DRUG DEVELOPMENT 2020; 5:59-65. [PMID: 32190733 DOI: 10.1080/23808993.2020.1730694] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Introduction Breast cancer is the most common malignancy in women in the United States and triple-negative breast cancer (TNBC) accounts for 15-20%. The standard of care for metastatic TNBC has been limited to cytotoxic chemotherapy with modest efficacy. TNBC is associated with high levels of tumor-infiltrating lymphocytes and PD-L1 expression, supporting the investigation of immune checkpoint inhibitors in this breast cancer subtype. Areas Covered This review summarizes the clinical data supporting the use of atezolizumab and nab-paclitaxel in the treatment of metastatic PD-L1-positive TNBC. It examines the pharmacology and toxicity profile of the combination in patients with metastatic TNBC. Expert Opinion The addition of atezolizumab to nab-paclitaxel prolonged progression-free survival in both the intention-to-treat and PD-L1-positive subgroups in the first line setting in patients with metastatic TNBC. The IMpassion 130 trial led to FDA-approval of this combination in patients with PD-L1-positive, metastatic TNBC and represents the first approval of immunotherapy for TNBC. This work supports ongoing investigations of other immunotherapy combinations in TNBC, predictive biomarker development and immunotherapy in patients with early stage TNBC. Immunotherapy combinations in TNBC have the potential to lead to improved survival in this group of patients with high risk disease.
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Affiliation(s)
- Jodi A Kagihara
- Division of Medical Oncology, University of Colorado Anschutz Medical Campus, Aurora, United States of America
| | - Michelle Andress
- Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, United States of America
| | - Jennifer R Diamond
- Division of Medical Oncology, University of Colorado Anschutz Medical Campus, Aurora, United States of America
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Dias AS, Almeida CR, Helguero LA, Duarte IF. Metabolic crosstalk in the breast cancer microenvironment. Eur J Cancer 2019; 121:154-171. [PMID: 31581056 DOI: 10.1016/j.ejca.2019.09.002] [Citation(s) in RCA: 128] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 09/03/2019] [Indexed: 02/08/2023]
Abstract
During tumorigenesis, breast tumour cells undergo metabolic reprogramming, which generally includes enhanced glycolysis, tricarboxylic acid cycle activity, glutaminolysis and fatty acid biosynthesis. However, the extension and functional importance of these metabolic alterations may diverge not only according to breast cancer subtypes, but also depending on the interaction of cancer cells with the complex surrounding microenvironment. This microenvironment comprises a variety of non-cancerous cells, such as immune cells (e.g. macrophages, lymphocytes, natural killer cells), fibroblasts, adipocytes and endothelial cells, together with extracellular matrix components and soluble factors, which influence cancer progression and are predictive of clinical outcome. The continuous interaction between cancer and stromal cells results in metabolic competition and symbiosis, with oncogenic-driven metabolic reprogramming of cancer cells shaping the metabolism of neighbouring cells and vice versa. This review addresses current knowledge on this metabolic crosstalk within the breast tumour microenvironment (TME). Improved understanding of how metabolism in the TME modulates cancer development and evasion of tumour-suppressive mechanisms may provide clues for novel anticancer therapeutics directed to metabolic targets.
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Affiliation(s)
- Ana S Dias
- CICECO - Aveiro Institute of Materials, Department of Chemistry, University of Aveiro, Campus de Santiago, Aveiro, Portugal; iBiMED - Institute of Biomedicine, Department of Medical Sciences, University of Aveiro, Campus de Santiago, Aveiro, Portugal
| | - Catarina R Almeida
- iBiMED - Institute of Biomedicine, Department of Medical Sciences, University of Aveiro, Campus de Santiago, Aveiro, Portugal
| | - Luisa A Helguero
- iBiMED - Institute of Biomedicine, Department of Medical Sciences, University of Aveiro, Campus de Santiago, Aveiro, Portugal
| | - Iola F Duarte
- CICECO - Aveiro Institute of Materials, Department of Chemistry, University of Aveiro, Campus de Santiago, Aveiro, Portugal.
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Kim R, Kawai A, Wakisaka M, Sawada S, Shimoyama M, Yasuda N, Hidaka M, Morita Y, Ohtani S, Arihiro K. Immune correlates of the differing pathological and therapeutic effects of neoadjuvant chemotherapy in breast cancer. Eur J Surg Oncol 2019; 46:77-84. [PMID: 31563296 DOI: 10.1016/j.ejso.2019.09.146] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2019] [Revised: 08/26/2019] [Accepted: 09/17/2019] [Indexed: 01/21/2023] Open
Abstract
PURPOSE To evaluate immune responses paralleling the pathological and therapeutic effects of neoadjuvant chemotherapy (NAC) in the tumor microenvironment of breast cancer. PATIENTS AND METHODS 38 patients with stages II and III breast cancer received NAC followed by surgery in 2012-2018. Peripheral natural killer (pNK) cell activity, tumor-infiltrating lymphocytes (TILs), and levels of tumor microenvironmental factors were assessed before and after NAC. RESULTS In univariate analysis, grade 2 (G2) and better therapeutic effects were significantly associated with high post-NAC levels of NK cells and interleukin-6, and tended to be associated with higher CD4, CD8 and CTLA-4 transcripts. Disappearance of axillary lymph node metastasis (Ax+) was significantly associated with 1) increased NK and pNK levels, 2) decreased vascular endothelial growth factor (VEGF) transcripts after NAC, 3) the presence of ≥5% TILs, and tended to be associated with higher CTLA-4 levels before NAC. Multivariate analysis showed that G2 and better therapeutic effects were significantly associated with higher NK levels after NAC (OR = 1.07, 95% CI 1.00-1.14; p = 0.0255), and that disappearance of Ax+ was significantly associated with the presence of ≥5% pre-NAC TILs (OR = 19.87, 95% CI 2.24-175.80; p = 0.0072). CONCLUSIONS Increased NK cells after NAC, together with increased CD4+ and CD8+ T-cells, and decreased CTLA-4+ T cells and VEGF correlate with beneficial therapeutic effects. Systemic activation of pNK cell activity and the presence of pre-NAC TILs may improve the elimination of Ax + together with decreased immunosuppression by VEGF in tumors.
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Affiliation(s)
- Ryungsa Kim
- Breast Surgery, Hiroshima Mark Clinic, Hiroshima, Japan.
| | - Ami Kawai
- Breast Surgery, Hiroshima Mark Clinic, Hiroshima, Japan
| | | | - Sayaka Sawada
- Breast Surgery, Hiroshima Mark Clinic, Hiroshima, Japan
| | | | - Naomi Yasuda
- Breast Surgery, Hiroshima Mark Clinic, Hiroshima, Japan
| | | | | | - Shoichiro Ohtani
- Department of Breast Surgery, Hiroshima City Hospital, Hiroshima, Japan
| | - Koji Arihiro
- Department of Anatomical Pathology, Hiroshima University Hospital, Hiroshima, Japan
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Meisel JL, Zhao J, Suo A, Zhang C, Wei Z, Taylor C, Aneja R, Krishnamurti U, Li Z, Nahta R, O'Regan R, Li X. Clinicopathologic Factors Associated With Response to Neoadjuvant Anti-HER2-Directed Chemotherapy in HER2-Positive Breast Cancer. Clin Breast Cancer 2019; 20:19-24. [PMID: 31806448 DOI: 10.1016/j.clbc.2019.09.003] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2019] [Revised: 09/06/2019] [Accepted: 09/10/2019] [Indexed: 11/24/2022]
Abstract
BACKGROUND HER2-targeted neoadjuvant therapy has high efficacy in treating HER2-positive breast cancer. Response to neoadjuvant therapy helps clinicians make treatment decisions and make estimates about prognosis. This study examined clinicopathologic features to determine which may be most predictive of response to neoadjuvant therapy in HER2+ breast cancer. PATIENTS AND METHODS Patients with HER2+ breast cancer (n = 173) who had an initial biopsy performed between 2010 and 2016 were identified at our institution. Tumor response was evaluated on excisional specimens using the MD Anderson residual cancer burden (RCB) classification. Tumors with pathologic complete response (defined as no residual invasive carcinoma in the breast and lymph nodes) and RCB-I were classified as having response and tumors with RCB-II and -III as having no response. Patient age, tumor size, nuclear grade (1/2 vs. 3), mitosis, Nottingham grade, HER2 immunohistochemistry (1/2+ vs. 3+), HER2/CEP17 (chromosome enumeration probe 17) ratio, HER2 copy number, estrogen receptor, progesterone receptor, Ki-67, and tumor-infiltrating lymphocytes (TIL) were evaluated and correlated with response. TILs were evaluated for an average and also for the hot spot/total tumor stromal ratio. RESULTS Small tumor size, low estrogen receptor and progesterone receptor expression, HER2 immunohistochemistry 3+, high Ki-67, high HER2/CEP17 ratio, and high HER2 copy number were significantly associated with response (all P < .05). TIL hot spot was associated with RCB in univariate (P < .05) but not multivariate analyses. CONCLUSION Clinicopathologic features may help predict HER2+ breast cancer response to neoadjuvant therapy. Larger studies would be useful to confirm these associations, which may have relevance to clinical practice.
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Affiliation(s)
- Jane L Meisel
- Department of Hematology and Medical Oncology, Emory University, Atlanta, GA
| | - Jing Zhao
- Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Aili Suo
- Department of Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Chao Zhang
- Biostatistics and Bioinformatics Shared Resource, Emory University, Atlanta, GA
| | - Zhimin Wei
- Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Caitlin Taylor
- Department of Hematology and Medical Oncology, Emory University, Atlanta, GA
| | - Ritu Aneja
- Department of Biology, Georgia State University, Atlanta, GA
| | - Uma Krishnamurti
- Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA
| | - Zaibo Li
- Department of Pathology, Ohio State University, Columbus, OH
| | - Rita Nahta
- Department of Pharmacology, Emory University, Atlanta, GA
| | - Ruth O'Regan
- Department of Medicine, University of Wisconsin, Madison, WI
| | - Xiaoxian Li
- Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA.
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