|
1
|
Li X, Hu Z, Shi Q, Qiu W, Liu Y, Liu Y, Huang S, Liang L, Chen Z, He X. Elevated choline drives KLF5-dominated transcriptional reprogramming to facilitate liver cancer progression. Oncogene 2024; 43:3121-3136. [PMID: 39251845 DOI: 10.1038/s41388-024-03150-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 08/28/2024] [Accepted: 08/30/2024] [Indexed: 09/11/2024]
Abstract
An increase in the total choline-containing compound content is a common characteristic of cancer cells, and aberrant choline metabolism in cancer is closely associated with malignant progression. However, the potential role of choline-induced global transcriptional changes in cancer cells remains unclear. In this study, we reveal that an elevated choline content facilitates hepatocellular carcinoma (HCC) cell proliferation by reprogramming Krüppel-like factor 5 (KLF5)-dominated core transcriptional regulatory circuitry (CRC). Mechanistically, choline administration leads to elevated S-adenosylmethionine (SAM) levels, inducing the formation of H3K4me1 within the super-enhancer (SE) region of KLF5 and activating its transcription. KLF5, as a key transcription factor (TF) of CRC established by choline, further transactivates downstream genes to facilitate HCC cell cycle progression. Additionally, KLF5 can increase the expression of choline kinase-α (CHKA) and CTP:phosphocholine cytidylyltransferase (CCT) resulting in a positive feedback loop to promote HCC cell proliferation. Notably, the histone deacetylase inhibitor (HDACi) vorinostat (SAHA) significantly suppressed KLF5 expression and liver tumor growth in mice, leading to a prolonged lifespan. In conclusion, these findings highlight the epigenetic regulatory mechanism of the SE-driven key regulatory factor KLF5 conducted by choline metabolism in HCC and suggest a potential therapeutic strategy for HCC patients with high choline content.
Collapse
Affiliation(s)
- Xinrong Li
- Fudan University Shanghai Cancer Center and Institutes of Biomedical Sciences; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Zhixiang Hu
- Fudan University Shanghai Cancer Center and Institutes of Biomedical Sciences; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Qili Shi
- Fudan University Shanghai Cancer Center and Institutes of Biomedical Sciences; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wenying Qiu
- Fudan University Shanghai Cancer Center and Institutes of Biomedical Sciences; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yizhe Liu
- Fudan University Shanghai Cancer Center and Institutes of Biomedical Sciences; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yanfang Liu
- Fudan University Shanghai Cancer Center and Institutes of Biomedical Sciences; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Shenglin Huang
- Fudan University Shanghai Cancer Center and Institutes of Biomedical Sciences; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Linhui Liang
- Fudan University Shanghai Cancer Center and Institutes of Biomedical Sciences; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Zhiao Chen
- Fudan University Shanghai Cancer Center and Institutes of Biomedical Sciences; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
| | - Xianghuo He
- Fudan University Shanghai Cancer Center and Institutes of Biomedical Sciences; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
- Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China.
- Shanghai Key Laboratory of Radiation Oncology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China.
| |
Collapse
|
|
2
|
Mrowiec K, Debik J, Jelonek K, Kurczyk A, Ponge L, Wilk A, Krzempek M, Giskeødegård GF, Bathen TF, Widłak P. Profiling of serum metabolome of breast cancer: multi-cancer features discriminate between healthy women and patients with breast cancer. Front Oncol 2024; 14:1377373. [PMID: 38646441 PMCID: PMC11027565 DOI: 10.3389/fonc.2024.1377373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Accepted: 03/25/2024] [Indexed: 04/23/2024] Open
Abstract
Introduction The progression of solid cancers is manifested at the systemic level as molecular changes in the metabolome of body fluids, an emerging source of cancer biomarkers. Methods We analyzed quantitatively the serum metabolite profile using high-resolution mass spectrometry. Metabolic profiles were compared between breast cancer patients (n=112) and two groups of healthy women (from Poland and Norway; n=95 and n=112, respectively) with similar age distributions. Results Despite differences between both cohorts of controls, a set of 43 metabolites and lipids uniformly discriminated against breast cancer patients and healthy women. Moreover, smaller groups of female patients with other types of solid cancers (colorectal, head and neck, and lung cancers) were analyzed, which revealed a set of 42 metabolites and lipids that uniformly differentiated all three cancer types from both cohorts of healthy women. A common part of both sets, which could be called a multi-cancer signature, contained 23 compounds, which included reduced levels of a few amino acids (alanine, aspartate, glutamine, histidine, phenylalanine, and leucine/isoleucine), lysophosphatidylcholines (exemplified by LPC(18:0)), and diglycerides. Interestingly, a reduced concentration of the most abundant cholesteryl ester (CE(18:2)) typical for other cancers was the least significant in the serum of breast cancer patients. Components present in a multi-cancer signature enabled the establishment of a well-performing breast cancer classifier, which predicted cancer with a very high precision in independent groups of women (AUC>0.95). Discussion In conclusion, metabolites critical for discriminating breast cancer patients from controls included components of hypothetical multi-cancer signature, which indicated wider potential applicability of a general serum metabolome cancer biomarker.
Collapse
Affiliation(s)
- Katarzyna Mrowiec
- Center for Translational Research and Molecular Biology of Cancer, Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice, Poland
| | - Julia Debik
- Department of Circulation and Medical Imaging, The Norwegian University of Science and Technology, Trondheim, Norway
- Department of Public Health and Nursing, The Norwegian University of Science and Technology, Trondheim, Norway
| | - Karol Jelonek
- Center for Translational Research and Molecular Biology of Cancer, Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice, Poland
| | - Agata Kurczyk
- Department of Biostatistics and Bioinformatics, Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice, Poland
| | - Lucyna Ponge
- Center for Translational Research and Molecular Biology of Cancer, Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice, Poland
| | - Agata Wilk
- Department of Biostatistics and Bioinformatics, Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice, Poland
- Department of Systems Biology and Engineering, Silesian University of Technology, Gliwice, Poland
| | - Marcela Krzempek
- Department of Biostatistics and Bioinformatics, Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice, Poland
| | - Guro F. Giskeødegård
- Department of Circulation and Medical Imaging, The Norwegian University of Science and Technology, Trondheim, Norway
| | - Tone F. Bathen
- Department of Circulation and Medical Imaging, The Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Piotr Widłak
- 2nd Department of Radiology, Medical University of Gdansk, Gdansk, Poland
| |
Collapse
|
|
3
|
Bel’skaya LV, Gundyrev IA, Solomatin DV. The Role of Amino Acids in the Diagnosis, Risk Assessment, and Treatment of Breast Cancer: A Review. Curr Issues Mol Biol 2023; 45:7513-7537. [PMID: 37754258 PMCID: PMC10527988 DOI: 10.3390/cimb45090474] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 09/05/2023] [Accepted: 09/12/2023] [Indexed: 09/28/2023] Open
Abstract
This review summarizes the role of amino acids in the diagnosis, risk assessment, imaging, and treatment of breast cancer. It was shown that the content of individual amino acids changes in breast cancer by an average of 10-15% compared with healthy controls. For some amino acids (Thr, Arg, Met, and Ser), an increase in concentration is more often observed in breast cancer, and for others, a decrease is observed (Asp, Pro, Trp, and His). The accuracy of diagnostics using individual amino acids is low and increases when a number of amino acids are combined with each other or with other metabolites. Gln/Glu, Asp, Arg, Leu/Ile, Lys, and Orn have the greatest significance in assessing the risk of breast cancer. The variability in the amino acid composition of biological fluids was shown to depend on the breast cancer phenotype, as well as the age, race, and menopausal status of patients. In general, the analysis of changes in the amino acid metabolism in breast cancer is a promising strategy not only for diagnosis, but also for developing new therapeutic agents, monitoring the treatment process, correcting complications after treatment, and evaluating survival rates.
Collapse
Affiliation(s)
- Lyudmila V. Bel’skaya
- Biochemistry Research Laboratory, Omsk State Pedagogical University, 644099 Omsk, Russia;
| | - Ivan A. Gundyrev
- Biochemistry Research Laboratory, Omsk State Pedagogical University, 644099 Omsk, Russia;
| | - Denis V. Solomatin
- Department of Mathematics and Mathematics Teaching Methods, Omsk State Pedagogical University, 644043 Omsk, Russia;
| |
Collapse
|
|
4
|
Mrowiec K, Kurczyk A, Jelonek K, Debik J, Giskeødegård GF, Bathen TF, Widłak P. Association of serum metabolome profile with the risk of breast cancer in participants of the HUNT2 study. Front Oncol 2023; 13:1116806. [PMID: 37007110 PMCID: PMC10061137 DOI: 10.3389/fonc.2023.1116806] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 03/06/2023] [Indexed: 03/18/2023] Open
Abstract
Background The serum metabolome is a potential source of molecular biomarkers associated with the risk of breast cancer. Here we aimed to analyze metabolites present in pre-diagnostic serum samples collected from healthy women participating in the Norwegian Trøndelag Health Study (HUNT2 study) for whom long-term information about developing breast cancer was available. Methods Women participating in the HUNT2 study who developed breast cancer within a 15-year follow-up period (BC cases) and age-matched women who stayed breast cancer-free were selected (n=453 case-control pairs). Using a high-resolution mass spectrometry approach 284 compounds were quantitatively analyzed, including 30 amino acids and biogenic amines, hexoses, and 253 lipids (acylcarnitines, glycerides, phosphatidylcholines, sphingolipids, and cholesteryl esters). Results Age was a major confounding factor responsible for a large heterogeneity in the dataset, hence age-defined subgroups were analyzed separately. The largest number of metabolites whose serum levels differentiated BC cases and controls (82 compounds) were observed in the subgroup of younger women (<45 years old). Noteworthy, increased levels of glycerides, phosphatidylcholines, and sphingolipids were associated with reduced risk of cancer in younger and middle-aged women (≤64 years old). On the other hand, increased levels of serum lipids were associated with an enhanced risk of breast cancer in older women (>64 years old). Moreover, several metabolites could be detected whose serum levels were different between BC cases diagnosed earlier (<5 years) and later (>10 years) after sample collecting, yet these compounds were also correlated with the age of participants. Current results were coherent with the results of the NMR-based metabolomics study performed in the cohort of HUNT2 participants, where increased serum levels of VLDL subfractions were associated with reduced risk of breast cancer in premenopausal women. Conclusions Changes in metabolite levels detected in pre-diagnostic serum samples, which reflected an impaired lipid and amino acid metabolism, were associated with long-term risk of breast cancer in an age-dependent manner.
Collapse
Affiliation(s)
- Katarzyna Mrowiec
- Center for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie National Research Institute of Oncology, Gliwice Branch, Gliwice, Poland
| | - Agata Kurczyk
- Center for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie National Research Institute of Oncology, Gliwice Branch, Gliwice, Poland
| | - Karol Jelonek
- Center for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie National Research Institute of Oncology, Gliwice Branch, Gliwice, Poland
| | - Julia Debik
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Guro F. Giskeødegård
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Clinic of Surgery, St. Olavs University Hospital, Trondheim, Norway
| | - Tone F. Bathen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Department of Medical Imaging and Nuclear Medicine, St. Olavs University Hospital, Trondheim, Norway
| | - Piotr Widłak
- Clinical Research Support Centre, Medical University of Gdańsk, Gdańsk, Poland
| |
Collapse
|
|
5
|
Roth HE, Powers R. Meta-Analysis Reveals Both the Promises and the Challenges of Clinical Metabolomics. Cancers (Basel) 2022; 14:3992. [PMID: 36010984 PMCID: PMC9406125 DOI: 10.3390/cancers14163992] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Revised: 08/09/2022] [Accepted: 08/16/2022] [Indexed: 11/17/2022] Open
Abstract
Clinical metabolomics is a rapidly expanding field focused on identifying molecular biomarkers to aid in the efficient diagnosis and treatment of human diseases. Variations in study design, metabolomics methodologies, and investigator protocols raise serious concerns about the accuracy and reproducibility of these potential biomarkers. The explosive growth of the field has led to the recent availability of numerous replicate clinical studies, which permits an evaluation of the consistency of biomarkers identified across multiple metabolomics projects. Pancreatic ductal adenocarcinoma (PDAC) is the third-leading cause of cancer-related death and has the lowest five-year survival rate primarily due to the lack of an early diagnosis and the limited treatment options. Accordingly, PDAC has been a popular target of clinical metabolomics studies. We compiled 24 PDAC metabolomics studies from the scientific literature for a detailed meta-analysis. A consistent identification across these multiple studies allowed for the validation of potential clinical biomarkers of PDAC while also highlighting variations in study protocols that may explain poor reproducibility. Our meta-analysis identified 10 metabolites that may serve as PDAC biomarkers and warrant further investigation. However, 87% of the 655 metabolites identified as potential biomarkers were identified in single studies. Differences in cohort size and demographics, p-value choice, fold-change significance, sample type, handling and storage, data collection, and analysis were all factors that likely contributed to this apparently large false positive rate. Our meta-analysis demonstrated the need for consistent experimental design and normalized practices to accurately leverage clinical metabolomics data for reliable and reproducible biomarker discovery.
Collapse
Affiliation(s)
- Heidi E. Roth
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, USA
| | - Robert Powers
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, USA
- Nebraska Center for Integrated Biomolecular Communication, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, USA
| |
Collapse
|
|
6
|
An R, Yu H, Wang Y, Lu J, Gao Y, Xie X, Zhang J. Integrative analysis of plasma metabolomics and proteomics reveals the metabolic landscape of breast cancer. Cancer Metab 2022; 10:13. [PMID: 35978348 PMCID: PMC9382832 DOI: 10.1186/s40170-022-00289-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 08/03/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Breast cancer (BC) is the most commonly diagnosed cancer. Currently, mammography and breast ultrasonography are the main clinical screening methods for BC. Our study aimed to reveal the specific metabolic profiles of BC patients and explore the specific metabolic signatures in human plasma for BC diagnosis. METHODS This study enrolled 216 participants, including BC patients, benign patients, and healthy controls (HC) and formed two cohorts, one training cohort and one testing cohort. Plasma samples were collected from each participant and subjected to perform nontargeted metabolomics and proteomics. The metabolic signatures for BC diagnosis were identified through machine learning. RESULTS Metabolomics analysis revealed that BC patients showed a significant change of metabolic profiles compared to HC individuals. The alanine, aspartate and glutamate pathways, glutamine and glutamate metabolic pathways, and arginine biosynthesis pathways were the critical biological metabolic pathways in BC. Proteomics identified 29 upregulated and 2 downregulated proteins in BC. Our integrative analysis found that aspartate aminotransferase (GOT1), L-lactate dehydrogenase B chain (LDHB), glutathione synthetase (GSS), and glutathione peroxidase 3 (GPX3) were closely involved in these metabolic pathways. Support vector machine (SVM) demonstrated a predictive model with 47 metabolites, and this model achieved a high accuracy in BC prediction (AUC = 1). Besides, this panel of metabolites also showed a fairly high predictive power in the testing cohort between BC vs HC (AUC = 0.794), and benign vs HC (AUC = 0.879). CONCLUSIONS This study uncovered specific changes in the metabolic and proteomic profiling of breast cancer patients and identified a panel of 47 plasma metabolites, including sphingomyelins, glutamate, and cysteine could be potential diagnostic biomarkers for breast cancer.
Collapse
Affiliation(s)
- Rui An
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China.,Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China
| | - Haitao Yu
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China.,Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China
| | - Yanzhong Wang
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China.,Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China
| | - Jie Lu
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China.,Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China
| | - Yuzhen Gao
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China.,Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China
| | - Xinyou Xie
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China.,Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China
| | - Jun Zhang
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China. .,Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, 3 East Qingchun Road, Hangzhou, Zhejiang, 310016, People's Republic of China.
| |
Collapse
|
|
7
|
Optimization and normalization strategies for long term untargeted HILIC-LC-qTOF-MS based metabolomics analysis: Early diagnosis of breast cancer. Microchem J 2022. [DOI: 10.1016/j.microc.2022.107658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
|
|
8
|
Da Cunha PA, Nitusca D, Canto LMD, Varghese RS, Ressom HW, Willey S, Marian C, Haddad BR. Metabolomic Analysis of Plasma from Breast Cancer Patients Using Ultra-High-Performance Liquid Chromatography Coupled with Mass Spectrometry: An Untargeted Study. Metabolites 2022; 12:447. [PMID: 35629952 PMCID: PMC9147455 DOI: 10.3390/metabo12050447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 05/04/2022] [Accepted: 05/07/2022] [Indexed: 11/16/2022] Open
Abstract
Breast cancer (BC) is one of the leading causes of cancer mortality in women worldwide, and therefore, novel biomarkers for early disease detection are critically needed. We performed herein an untargeted plasma metabolomic profiling of 55 BC patients and 55 healthy controls (HC) using ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC/Q-TOF-MS). Pre-processed data revealed 2494 ions in total. Data matrices’ paired t-tests revealed 792 ions (both positive and negative) which presented statistically significant changes (FDR < 0.05) in intensity levels between cases versus controls. Metabolites identified with putative names via MetaboQuest using MS/MS and mass-based approaches included amino acid esters (i.e., N-stearoyl tryptophan, L-arginine ethyl ester), dipeptides (ile-ser, met-his), nitrogenous bases (i.e., uracil derivatives), lipid metabolism-derived molecules (caproleic acid), and exogenous compounds from plants, drugs, or dietary supplements. LASSO regression selected 16 metabolites after several variables (TNM Stage, Grade, smoking status, menopausal status, and race) were adjusted. A predictive conditional logistic regression model on the 16 LASSO selected ions provided a high diagnostic performance with an area-under-the-curve (AUC) value of 0.9729 (95% CI 0.96−0.98) on all 55 samples. This study proves that BC possesses a specific metabolic signature that could be exploited as a novel metabolomics-based approach for BC detection and characterization. Future studies of large-scale cohorts are needed to validate these findings.
Collapse
Affiliation(s)
- Patricia A. Da Cunha
- Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington, DC 20057, USA; (P.A.D.C.); (L.M.D.C.); (R.S.V.); (H.W.R.); (S.W.)
| | - Diana Nitusca
- Department of Biochemistry and Pharmacology, Victor Babeş University of Medicine and Pharmacy, Pta Eftimie Murgu Nr. 2, 300041 Timişoara, Romania; (D.N.); (C.M.)
- Center for Complex Networks Science, Victor Babeş University of Medicine and Pharmacy, Pta Eftimie Murgu Nr. 2, 300041 Timişoara, Romania
| | - Luisa Matos Do Canto
- Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington, DC 20057, USA; (P.A.D.C.); (L.M.D.C.); (R.S.V.); (H.W.R.); (S.W.)
| | - Rency S. Varghese
- Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington, DC 20057, USA; (P.A.D.C.); (L.M.D.C.); (R.S.V.); (H.W.R.); (S.W.)
| | - Habtom W. Ressom
- Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington, DC 20057, USA; (P.A.D.C.); (L.M.D.C.); (R.S.V.); (H.W.R.); (S.W.)
| | - Shawna Willey
- Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington, DC 20057, USA; (P.A.D.C.); (L.M.D.C.); (R.S.V.); (H.W.R.); (S.W.)
- Department of Surgery, Georgetown University Medical Center, Georgetown University, Washington, DC 20007, USA
| | - Catalin Marian
- Department of Biochemistry and Pharmacology, Victor Babeş University of Medicine and Pharmacy, Pta Eftimie Murgu Nr. 2, 300041 Timişoara, Romania; (D.N.); (C.M.)
- Center for Complex Networks Science, Victor Babeş University of Medicine and Pharmacy, Pta Eftimie Murgu Nr. 2, 300041 Timişoara, Romania
| | - Bassem R. Haddad
- Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington, DC 20057, USA; (P.A.D.C.); (L.M.D.C.); (R.S.V.); (H.W.R.); (S.W.)
| |
Collapse
|
|
9
|
Prommajun P, Phetcharaburanin J, Namwat N, Klanrit P, Sa-Ngiamwibool P, Thanee M, Dokduang H, Kittirat Y, Li JV, Loilome W. Metabolic Profiling of Praziquantel-mediated Prevention of Opisthorchis viverrini-induced Cholangiocyte Transformation in the Hamster Model of Cholangiocarcinoma. Cancer Genomics Proteomics 2021; 18:29-42. [PMID: 33419894 DOI: 10.21873/cgp.20239] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 10/10/2020] [Accepted: 10/13/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Opisthorchis viverrini (Ov) infection-induced cholangiocarcinoma (CCA) is a major public health problem in northeastern Thailand. Praziquantel was shown to prevent CCA development in an Ov-infected hamster model; however, the molecular mechanism remains unknown. MATERIALS AND METHODS In this study, we used a hamster model with Ov and N-nitrosodimethylamine-induced CCA to study the mechanisms of praziquantel action. The liver tissues from the hamsters with and without praziquantel treatment were analyzed using 1H nuclear magnetic resonance spectroscopy. RESULTS A total of 14 metabolites were found to be significantly different between the two groups. Furthermore, the combination of acetate, inosine and sarcosine was shown to exert an anti-inflammatory effect through interleukin-6 inhibition in a macrophage cell line, suggesting a mechanism by which praziquantel may prevent inflammation caused by Ov, cholangiocyte transformation and further CCA develpoment. CONCLUSION These findings might avail the development of a preventive strategy for CCA in high-risk populations.
Collapse
Affiliation(s)
- Pattama Prommajun
- Department of Biochemistry, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.,Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen, Thailand
| | - Jutarop Phetcharaburanin
- Department of Biochemistry, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.,Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen, Thailand.,Khon Kaen University International Phenome Laboratory, Northeastern Science Park, Khon Kaen University, Khon Kaen, Thailand
| | - Nisana Namwat
- Department of Biochemistry, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.,Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen, Thailand
| | - Poramate Klanrit
- Department of Biochemistry, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.,Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen, Thailand
| | - Prakasit Sa-Ngiamwibool
- Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen, Thailand.,Department of Pathology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand
| | - Malinee Thanee
- Faculty of Medical Science, Nakhonratchasima College, Nakhon Ratchasima, Thailand
| | - Hasaya Dokduang
- Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen, Thailand
| | - Yingpinyapat Kittirat
- Department of Biochemistry, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.,Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen, Thailand
| | - Jia V Li
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, South Kensington Campus, London, U.K
| | - Watcharin Loilome
- Department of Biochemistry, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand; .,Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen, Thailand.,Khon Kaen University International Phenome Laboratory, Northeastern Science Park, Khon Kaen University, Khon Kaen, Thailand
| |
Collapse
|
|
10
|
Stolzenberg-Solomon RZ, Derkach A, Moore S, Weinstein S, Albanes D, Sampson J. Associations between metabolites and pancreatic cancer risk in a large prospective epidemiological study. Gut 2020; 69:2008-2015. [PMID: 32060129 PMCID: PMC7980697 DOI: 10.1136/gutjnl-2019-319811] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 01/17/2020] [Accepted: 01/20/2020] [Indexed: 12/15/2022]
Abstract
OBJECTIVE To assess whether prediagnostic metabolites were associated with incident pancreatic ductal adenocarcinoma (PDAC) in a prospective cohort study. DESIGN We conducted an untargeted analysis of 554 known metabolites measured in prediagnostic serum (up to 24 years) to determine their association with incident PDAC in a nested case-control study of male smokers (372 matched case-control sets) and an independent nested case-control study that included women and non-smokers (107 matched sets). Metabolites were measured using Orbitrap Elite or Q-Exactive high-resolution/accurate mass spectrometers. Controls were matched to cases by age, sex, race, date of blood draw, and follow-up time. We used conditional logistic regression adjusted for age to calculate ORs and 95% CIs for a 1 SD increase in log-metabolite level separately in each cohort and combined the two ORs using a fixed-effects meta-analysis. RESULTS Thirty-one metabolites were significantly associated with PDAC at a false discovery rate <0.05 with 12 metabolites below the Bonferroni-corrected threshold (p<9.04×10-5). Similar associations were observed in both cohorts. The dipeptides glycylvaline, aspartylphenylalanine, pyroglutamylglycine, phenylalanylphenylalanine, phenylalanylleucine and tryptophylglutamate and amino acids aspartate and glutamate were positively while the dipeptides tyrosylglutamine and α-glutamyltyrosine, fibrinogen cleavage peptide DSGEGDFXAEGGGVR and glutathione-related amino acid cysteine-glutathione disulfide were inversely associated with PDAC after Bonferroni correction. Five top metabolites demonstrated significant time-varying associations (p<0.023) with the strongest associations observed 10-15 years after participants' blood collection and attenuated thereafter. CONCLUSION Our results suggest that prediagnostic metabolites related to subclinical disease, γ-glutamyl cycle metabolism and adiposity/insulin resistance are associated with PDAC.
Collapse
Affiliation(s)
- Rachael Z. Stolzenberg-Solomon
- Metabolic Epidemiology Branch, Division Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, United States
| | - Andriy Derkach
- Biostatistics Branch, Division Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, United States
| | - Steven Moore
- Metabolic Epidemiology Branch, Division Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, United States
| | - Stephanie Weinstein
- Metabolic Epidemiology Branch, Division Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, United States
| | - Demetrius Albanes
- Metabolic Epidemiology Branch, Division Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, United States
| | - Joshua Sampson
- Biostatistics Branch, Division Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, United States
| |
Collapse
|
|
11
|
Label-free visualization and characterization of extracellular vesicles in breast cancer. Proc Natl Acad Sci U S A 2019; 116:24012-24018. [PMID: 31732668 DOI: 10.1073/pnas.1909243116] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Despite extensive interest, extracellular vesicle (EV) research remains technically challenging. One of the unexplored gaps in EV research has been the inability to characterize the spatially and functionally heterogeneous populations of EVs based on their metabolic profile. In this paper, we utilize the intrinsic optical metabolic and structural contrast of EVs and demonstrate in vivo/in situ characterization of EVs in a variety of unprocessed (pre)clinical samples. With a pixel-level segmentation mask provided by the deep neural network, individual EVs can be analyzed in terms of their optical signature in the context of their spatial distribution. Quantitative analysis of living tumor-bearing animals and fresh excised human breast tissue revealed abundance of NAD(P)H-rich EVs within the tumor, near the tumor boundary, and around vessel structures. Furthermore, the percentage of NAD(P)H-rich EVs is highly correlated with human breast cancer diagnosis, which emphasizes the important role of metabolic imaging for EV characterization as well as its potential for clinical applications. In addition to the characterization of EV properties, we also demonstrate label-free monitoring of EV dynamics (uptake, release, and movement) in live cells and animals. The in situ metabolic profiling capacity of the proposed method together with the finding of increasing NAD(P)H-rich EV subpopulations in breast cancer have the potential for empowering applications in basic science and enhancing our understanding of the active metabolic roles that EVs play in cancer progression.
Collapse
|
|
12
|
Zang HL, Huang GM, Ju HY, Tian XF. Integrative analysis of the inverse expression patterns in pancreas development and cancer progression. World J Gastroenterol 2019; 25:4727-4738. [PMID: 31528097 PMCID: PMC6718033 DOI: 10.3748/wjg.v25.i32.4727] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Revised: 07/05/2019] [Accepted: 07/19/2019] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND As the malignant tumor, pancreatic cancer with a meager 5-years survival rate has been widely concerning. However, the molecular mechanisms that result in malignant transformation of pancreatic cells remain elusive.
AIM To investigate the gene expression profiles in normal or malignant transformed pancreas development.
METHODS MaSigPro and ANOVA were performed on two pancreas development datasets downloaded from the Gene Expression Omnibus database. Six pancreatic cancer datasets collected from TCGA database were used to establish differentially expressed genes related to pancreas development and pancreatic cancer. Moreover, gene clusters with highly similar interpretation patterns between pancreas development and pancreatic cancer progression were established by self-organizing map and singular value decomposition. Additionally, the hypergeometric test was performed to compare the corresponding interpretation patterns. Abnormal regions of metabolic pathway were analyzed using the Sub-pathway-GM method.
RESULTS This study established the continuously upregulated and downregulated genes at different stages in pancreas development and progression of pancreatic cancer. Through analysis of the differentially expressed genes, we established the inverse and consistent direction development-cancer pattern associations. Based on the application of the Subpathway-GM analysis, we established 17 significant metabolic sub-pathways that were closely associated with pancreatic cancer. Of note, the most significant metabolites sub-pathway was related to glycerophospholipid metabolism.
CONCLUSION The inverse and consistent direction development-cancer pattern associations were established. There was a significant correlation in the inverse patterns, but not consistent direction patterns.
Collapse
Affiliation(s)
- Hong-Liang Zang
- Department of Hepatobiliary and Pancreatic Surgery, China-Japan Union Hospital of Jilin University, Changchun 130033, Jilin Province, China
| | - Guo-Min Huang
- Department of Hepatobiliary and Pancreatic Surgery, China-Japan Union Hospital of Jilin University, Changchun 130033, Jilin Province, China
| | - Hai-Ying Ju
- Department of Hematology, Jilin Province Blood Center, Changchun 130000, Jilin Province, China
| | - Xiao-Feng Tian
- Department of Hepatobiliary and Pancreatic Surgery, China-Japan Union Hospital of Jilin University, Changchun 130033, Jilin Province, China
| |
Collapse
|
|
13
|
Haznadar M, Diehl CM, Parker AL, Krausz KW, Bowman ED, Rabibhadana S, Forgues M, Bhudhisawasdi V, Gonzalez FJ, Mahidol C, Budhu A, Wang XW, Ruchirawat M, Harris CC. Urinary Metabolites Diagnostic and Prognostic of Intrahepatic Cholangiocarcinoma. Cancer Epidemiol Biomarkers Prev 2019; 28:1704-1711. [PMID: 31358519 DOI: 10.1158/1055-9965.epi-19-0453] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2019] [Revised: 06/06/2019] [Accepted: 07/23/2019] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Liver cancer is the second leading cause of cancer-related deaths worldwide. With a predicted 2.4-fold rise in liver cancer incidence by 2020, there is an urgent need for early, inexpensive diagnostic biomarkers to deploy in the clinic. METHODS We employed ultraperformance liquid chromatography tandem mass-spectrometry (UPLC/MS-MS) for the quantitation of four metabolites, creatine riboside (CR), N-acetylneuraminic acid (NANA), cortisol sulfate, and a lipid molecule designated as 561+, in urine samples from the NCI-MD cohort comprising 98 hepatocellular carcinoma (HCC) cases, 101 high-risk subjects, and 95 controls. Validation was carried out in the TIGER-LC cohort [n = 370 HCC and intrahepatic cholangiocarcinoma (ICC) cases, 471 high-risk subjects, 251 controls], where ICC, the second most common primary hepatic malignancy, is highly prevalent. Metabolite quantitation was also conducted in TIGER-LC tissue samples (n = 48 ICC; n = 51 HCC). RESULTS All profiled metabolites were significantly increased in liver cancer when compared with high-risk subjects and controls in the NCI-MD study. In the TIGER-LC cohort, the four-metabolite profile was superior at classifying ICC than a clinically utilized marker, CA19-9, and their combination led to a significantly improved model (AUC = 0.88, P = 4E-8). Metabolites CR and NANA were significantly elevated in ICC when compared with HCC cases in both urine and tissue samples. High levels of CR were associated with poorer prognosis in ICC. CONCLUSIONS Four metabolites are significantly increased in HCC and ICC and are robust at classifying ICC in combination with the clinically utilized marker CA19-9. IMPACT Noninvasive urinary metabolite biomarkers hold promise for diagnostic and prognostic evaluation of ICC.
Collapse
Affiliation(s)
- Majda Haznadar
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland
| | - Christopher M Diehl
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland
| | - Amelia L Parker
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland
| | - Kristopher W Krausz
- Laboratory of Metabolism, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland
| | - Elise D Bowman
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland
| | - Siritida Rabibhadana
- Laboratory of Chemical Carcinogenesis, Chulabhorn Research Institute, Bangkok, Thailand
| | - Marshonna Forgues
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland
| | | | - Frank J Gonzalez
- Laboratory of Metabolism, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland
| | - Chulabhorn Mahidol
- Laboratory of Chemical Carcinogenesis, Chulabhorn Research Institute, Bangkok, Thailand.,Laboratory of Environmental Toxicology, Chulabhorn Research Institute, Bangkok, Thailand
| | - Anuradha Budhu
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland
| | - Xin W Wang
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland
| | - Mathuros Ruchirawat
- Laboratory of Environmental Toxicology, Chulabhorn Research Institute, Bangkok, Thailand.,Center of Excellence on Environmental Health and Toxicology, Office of Higher Education Commission, Ministry of Education, Bangkok, Thailand
| | - Curtis C Harris
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.
| |
Collapse
|
|
14
|
Hiraoka N, Toue S, Okamoto C, Kikuchi S, Ino Y, Yamazaki-Itoh R, Esaki M, Nara S, Kishi Y, Imaizumi A, Ono N, Shimada K. Tissue amino acid profiles are characteristic of tumor type, malignant phenotype, and tumor progression in pancreatic tumors. Sci Rep 2019; 9:9816. [PMID: 31285536 PMCID: PMC6614459 DOI: 10.1038/s41598-019-46404-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Accepted: 06/28/2019] [Indexed: 12/13/2022] Open
Abstract
Tissue amino acid profiles depend on the cell types and extracellular components that constitute the tissue, and their functions and activities. We aimed to characterize the tissue amino acid profiles in several types of pancreatic tumors and lesions. We examined tissue amino acid profiles in 311 patients with pancreatic tumors or lesions. We used newly developed LC-MS/MS methods to obtain the profiles, which were compared with clinicopathological data. Each tumor or lesion presented a characteristic tissue amino acid profile. Certain amino acids were markedly altered during the multistep pancreatic carcinogenesis and pancreatic ductal adenocarcinoma (PDAC) progression. A tissue amino acid index (TAAI) was developed based on the amino acids that were notably changed during both carcinogenesis and cancer progression. Univariate and multivariate survival analyses revealed that PDAC patients with a high TAAI exhibited a significantly shorter survival rate, and these findings were validated using a second cohort. We suggest that tissue amino acid profiles are characteristic for normal tissue type, tumor histological type, and pathological lesion, and are representative of the cancer grade or progression stage in multistep carcinogenesis and of malignant characteristics. The TAAI could serve as an independent prognosticator for patients with PDAC.
Collapse
Affiliation(s)
- Nobuyoshi Hiraoka
- Division of Molecular Pathology, National Cancer Center Research Institute, Tokyo, Japan. .,Division of Pathology and Clinical Laboratories, National Cancer Center Hospital, Tokyo, Japan.
| | - Sakino Toue
- Research Institute for Bioscience Products and Fine Chemicals, Ajinomoto Co., Inc, Kanagawa, Japan
| | - Chisato Okamoto
- Institute for Innovation, Ajinomoto Co., Inc, Kanagawa, Japan
| | - Shinya Kikuchi
- Research Institute for Bioscience Products and Fine Chemicals, Ajinomoto Co., Inc, Kanagawa, Japan
| | - Yoshinori Ino
- Division of Molecular Pathology, National Cancer Center Research Institute, Tokyo, Japan
| | - Rie Yamazaki-Itoh
- Division of Molecular Pathology, National Cancer Center Research Institute, Tokyo, Japan
| | - Minoru Esaki
- Hepato-Biliary and Pancreatic Surgery Division, National Cancer Center Hospital, Tokyo, Japan
| | - Satoshi Nara
- Hepato-Biliary and Pancreatic Surgery Division, National Cancer Center Hospital, Tokyo, Japan
| | - Yoji Kishi
- Hepato-Biliary and Pancreatic Surgery Division, National Cancer Center Hospital, Tokyo, Japan
| | - Akira Imaizumi
- Institute for Innovation, Ajinomoto Co., Inc, Kanagawa, Japan
| | - Nobukazu Ono
- Institute for Innovation, Ajinomoto Co., Inc, Kanagawa, Japan
| | - Kazuaki Shimada
- Hepato-Biliary and Pancreatic Surgery Division, National Cancer Center Hospital, Tokyo, Japan
| |
Collapse
|
|
15
|
Ciocan-Cartita CA, Jurj A, Buse M, Gulei D, Braicu C, Raduly L, Cojocneanu R, Pruteanu LL, Iuga CA, Coza O, Berindan-Neagoe I. The Relevance of Mass Spectrometry Analysis for Personalized Medicine through Its Successful Application in Cancer "Omics". Int J Mol Sci 2019; 20:ijms20102576. [PMID: 31130665 PMCID: PMC6567119 DOI: 10.3390/ijms20102576] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Revised: 05/21/2019] [Accepted: 05/24/2019] [Indexed: 01/06/2023] Open
Abstract
Mass spectrometry (MS) is an essential analytical technology on which the emerging omics domains; such as genomics; transcriptomics; proteomics and metabolomics; are based. This quantifiable technique allows for the identification of thousands of proteins from cell culture; bodily fluids or tissue using either global or targeted strategies; or detection of biologically active metabolites in ultra amounts. The routine performance of MS technology in the oncological field provides a better understanding of human diseases in terms of pathophysiology; prevention; diagnosis and treatment; as well as development of new biomarkers; drugs targets and therapies. In this review; we argue that the recent; successful advances in MS technologies towards cancer omics studies provides a strong rationale for its implementation in biomedicine as a whole.
Collapse
Affiliation(s)
- Cristina Alexandra Ciocan-Cartita
- MEDFUTURE -Research Center for Advanced Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy, 4-6 Louis Pasteur Street, 400349 Cluj-Napoca, Romania.
| | - Ancuța Jurj
- Research Center for Functional Genomics, Biomedicine and Translational Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy.
| | - Mihail Buse
- MEDFUTURE -Research Center for Advanced Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy, 4-6 Louis Pasteur Street, 400349 Cluj-Napoca, Romania.
| | - Diana Gulei
- MEDFUTURE -Research Center for Advanced Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy, 4-6 Louis Pasteur Street, 400349 Cluj-Napoca, Romania.
| | - Cornelia Braicu
- Research Center for Functional Genomics, Biomedicine and Translational Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy.
| | - Lajos Raduly
- Research Center for Functional Genomics, Biomedicine and Translational Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy.
| | - Roxana Cojocneanu
- Research Center for Functional Genomics, Biomedicine and Translational Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy.
| | - Lavinia Lorena Pruteanu
- MEDFUTURE -Research Center for Advanced Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy, 4-6 Louis Pasteur Street, 400349 Cluj-Napoca, Romania.
| | - Cristina Adela Iuga
- MEDFUTURE -Research Center for Advanced Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy, 4-6 Louis Pasteur Street, 400349 Cluj-Napoca, Romania.
- Department of Pharmaceutical Analysis, Faculty of Pharmacy, "Iuliu Hațieganu" University of Medicine and Pharmacy, 6 Louis Pasteur Street, 400349 Cluj-Napoca.
| | - Ovidiu Coza
- Department of Oncology, "Iuliu Hațieganu" University of Medicine and Pharmacy, 34-36 Republicii Street, 400015 Cluj-Napoca, Romania.
- Department of Radiotherapy with High Energies and Brachytherapy, Oncology Institute "Prof. Dr. Ion Chiricuta", 34-36 Republicii Street, 400015 Cluj-Napoca.
| | - Ioana Berindan-Neagoe
- MEDFUTURE -Research Center for Advanced Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy, 4-6 Louis Pasteur Street, 400349 Cluj-Napoca, Romania.
- Research Center for Functional Genomics, Biomedicine and Translational Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy.
- Department of Functional Genomics and Experimental Pathology, Ion Chiricuțǎ Oncology Institute, 34-36 Republicii Street, 400015 Cluj-Napoca.
| |
Collapse
|
|
16
|
Breast Cancer Metabolomics: From Analytical Platforms to Multivariate Data Analysis. A Review. Metabolites 2019; 9:metabo9050102. [PMID: 31121909 PMCID: PMC6572290 DOI: 10.3390/metabo9050102] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Revised: 05/13/2019] [Accepted: 05/17/2019] [Indexed: 12/24/2022] Open
Abstract
Cancer is a major health issue worldwide for many years and has been increasing significantly. Among the different types of cancer, breast cancer (BC) remains the leading cause of cancer-related deaths in women being a disease caused by a combination of genetic and environmental factors. Nowadays, the available diagnostic tools have aided in the early detection of BC leading to the improvement of survival rates. However, better detection tools for diagnosis and disease monitoring are still required. In this sense, metabolomic NMR, LC-MS and GC-MS-based approaches have gained attention in this field constituting powerful tools for the identification of potential biomarkers in a variety of clinical fields. In this review we will present the current analytical platforms and their applications to identify metabolites with potential for BC biomarkers based on the main advantages and advances in metabolomics research. Additionally, chemometric methods used in metabolomics will be highlighted.
Collapse
|
|
17
|
Amara CS, Vantaku V, Lotan Y, Putluri N. Recent advances in the metabolomic study of bladder cancer. Expert Rev Proteomics 2019; 16:315-324. [PMID: 30773067 DOI: 10.1080/14789450.2019.1583105] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
INTRODUCTION Metabolomics is a chemical process, involving the characterization of metabolites and cellular metabolism. Recent studies indicate that numerous metabolic pathways are altered in bladder cancer (BLCA), providing potential targets for improved detection and possible therapeutic intervention. We review recent advances in metabolomics related to BLCA and identify various metabolites that may serve as potential biomarkers for BLCA. Areas covered: In this review, we describe the latest advances in defining the BLCA metabolome and discuss the possible clinical utility of metabolic alterations in BLCA tissues, serum, and urine. In addition, we focus on the metabolic alterations associated with tobacco smoke and racial disparity in BLCA. Expert commentary: Metabolomics is a powerful tool which can shed new light on BLCA development and behavior. Key metabolites may serve as possible markers of BLCA. However, prospective validation will be needed to incorporate these markers into clinical care.
Collapse
Affiliation(s)
- Chandra Sekhar Amara
- a Department of Molecular and Cell Biology , Baylor College of Medicine , Houston , TX , USA
| | - Venkatrao Vantaku
- a Department of Molecular and Cell Biology , Baylor College of Medicine , Houston , TX , USA
| | - Yair Lotan
- b Department of Urology , University of Texas Southwestern , Dallas , TX , USA
| | - Nagireddy Putluri
- a Department of Molecular and Cell Biology , Baylor College of Medicine , Houston , TX , USA.,c Dan L. Duncan Cancer Center, Advanced Technology Core, Alkek Center for Molecular Discovery , Baylor College of Medicine , Houston , TX , USA
| |
Collapse
|
|
18
|
An Y, Cai H, Yang Y, Zhang Y, Liu S, Wu X, Duan Y, Sun D, Chen X. Identification of ENTPD8 and cytidine in pancreatic cancer by metabolomic and transcriptomic conjoint analysis. Cancer Sci 2018; 109:2811-2821. [PMID: 29987902 PMCID: PMC6125470 DOI: 10.1111/cas.13733] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2018] [Revised: 07/06/2018] [Accepted: 07/08/2018] [Indexed: 12/12/2022] Open
Abstract
To identify metabolic pathways that were perturbed in pancreatic cancer (PC), we investigated gene‐metabolite networks by integration of metabolomic and transcriptomic. In this research, we undertook the metabolomic study of 43 paired human PC samples, aiming to identify key metabolic alterations in PC. We also carried out in vitro experiments to validate that the key metabolite cytidine and its related gene ENTPD8 played an important role in PC cell proliferation. We screened out 13 metabolites differentially expressed in PC tissue (PCT) by liquid chromatography/mass spectrometry analysis on 34 metabolites, and the partial least square discrimination analysis results revealed that 9 metabolites among them were remarkably altered in PCT compared to adjacent noncancerous tissue (variable importance in projection >1, P < .05). Among the 9 metabolites, 7 might be potential biomarkers. The most significantly enriched metabolic pathway was pyrimidine metabolism. We analyzed 351 differentially expressed genes from The Cancer Genome Atlas and intersected them with Kyoto Encyclopedia of Genes and Genomes metabolic pathways. We found that ENTPD8 had a gene‐metabolite association with cytidine in the CTP dephosphorylation pathway. We verified by in vitro experiments that the CTP dephosphorylation pathway was changed in PCT compared with adjacent noncancerous tissue. ENTPD8 was downregulated in PCT, causing a reduction in cytidine formation and hence weakened CTP dephosphorylation in pyrimidine metabolism.
Collapse
Affiliation(s)
- Yong An
- Department of Hepato-Pancreato-Biliary Surgery, Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, China
| | - Huihua Cai
- Department of Hepato-Pancreato-Biliary Surgery, Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, China
| | - Yong Yang
- Department of Hepato-Pancreato-Biliary Surgery, Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, China
| | - Yue Zhang
- Department of Hepato-Pancreato-Biliary Surgery, Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, China
| | - Shengyong Liu
- Department of Hepato-Pancreato-Biliary Surgery, Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, China
| | - Xinquan Wu
- Department of Hepato-Pancreato-Biliary Surgery, Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, China
| | - Yunfei Duan
- Department of Hepato-Pancreato-Biliary Surgery, Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, China
| | - Donglin Sun
- Department of Hepato-Pancreato-Biliary Surgery, Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, China
| | - Xuemin Chen
- Department of Hepato-Pancreato-Biliary Surgery, Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, China
| |
Collapse
|
|
19
|
Tayyari F, Gowda GN, Olopade OF, Berg R, Yang HH, Lee MP, Ngwa WF, Mittal SK, Raftery D, Mohammed SI. Metabolic profiles of triple-negative and luminal A breast cancer subtypes in African-American identify key metabolic differences. Oncotarget 2018; 9:11677-11690. [PMID: 29545929 PMCID: PMC5837744 DOI: 10.18632/oncotarget.24433] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Accepted: 01/20/2018] [Indexed: 11/25/2022] Open
Abstract
Breast cancer, a heterogeneous disease with variable pathophysiology and biology, is classified into four major subtypes. While hormonal- and antibody-targeted therapies are effective in the patients with luminal and HER-2 subtypes, the patients with triple-negative breast cancer (TNBC) subtype do not benefit from these therapies. The incidence rates of TNBC subtype are higher in African-American women, and the evidence indicates that these women have worse prognosis compared to women of European descent. The reasons for this disparity remain unclear but are often attributed to TNBC biology. In this study, we performed metabolic analysis of breast tissues to identify how TNBC differs from luminal A breast cancer (LABC) subtypes within the African-American and Caucasian breast cancer patients, respectively. We used High-Resolution Magic Angle Spinning (HR-MAS) 1H Nuclear magnetic resonance (NMR) to perform the metabolomic analysis of breast cancer and adjacent normal tissues (total n=82 samples). TNBC and LABC subtypes in African American women exhibited different metabolic profiles. Metabolic profiles of these subtypes were also distinct from those revealed in Caucasian women. TNBC in African-American women expressed higher levels of glutathione, choline, and glutamine as well as profound metabolic alterations characterized by decreased mitochondrial respiration and increased glycolysis concomitant with decreased levels of ATP. TNBC in Caucasian women was associated with increased pyrimidine synthesis. These metabolic alterations could potentially be exploited as novel treatment targets for TNBC.
Collapse
Affiliation(s)
- Fariba Tayyari
- Complex Carbohydrate Research Center, University of Georgia, Athens, Georgia 30602, USA
| | - G.A. Nagana Gowda
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington School of Medicine, Seattle, WA 98109, USA
| | | | - Richard Berg
- Indiana University Health Arnett Medical, Lafayette, IN 47905, USA
| | - Howard H. Yang
- Laboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892, USA
| | - Maxwell P. Lee
- Laboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892, USA
| | - Wilfred F. Ngwa
- Brigham and Women’s Hospital, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, MA 02115, USA
| | - Suresh K. Mittal
- Depatment of Comparative Pathobiology and Purdue University Center for Cancer Research, Purdue University, West Lafayette, IN 47907, USA
| | - Daniel Raftery
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington School of Medicine, Seattle, WA 98109, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Sulma I. Mohammed
- Depatment of Comparative Pathobiology and Purdue University Center for Cancer Research, Purdue University, West Lafayette, IN 47907, USA
| |
Collapse
|
|
20
|
Tokarz J, Haid M, Cecil A, Prehn C, Artati A, Möller G, Adamski J. Endocrinology Meets Metabolomics: Achievements, Pitfalls, and Challenges. Trends Endocrinol Metab 2017; 28:705-721. [PMID: 28780001 DOI: 10.1016/j.tem.2017.07.001] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2017] [Revised: 06/30/2017] [Accepted: 07/05/2017] [Indexed: 02/07/2023]
Abstract
The metabolome, although very dynamic, is sufficiently stable to provide specific quantitative traits related to health and disease. Metabolomics requires balanced use of state-of-the-art study design, chemical analytics, biostatistics, and bioinformatics to deliver meaningful answers to contemporary questions in human disease research. The technology is now frequently employed for biomarker discovery and for elucidating the mechanisms underlying endocrine-related diseases. Metabolomics has also enriched genome-wide association studies (GWAS) in this area by providing functional data. The contributions of rare genetic variants to metabolome variance and to the human phenotype have been underestimated until now.
Collapse
Affiliation(s)
- Janina Tokarz
- Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
| | - Mark Haid
- Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
| | - Alexander Cecil
- Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
| | - Cornelia Prehn
- Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
| | - Anna Artati
- Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
| | - Gabriele Möller
- Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
| | - Jerzy Adamski
- Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany; Lehrstuhl für Experimentelle Genetik, Technische Universität München, 85350 Freising-Weihenstephan, Germany; German Center for Diabetes Research (DZD), 85764 München-Neuherberg, Germany.
| |
Collapse
|
|
21
|
Attri KS, Murthy D, Singh PK. Racial disparity in metabolic regulation of cancer. Front Biosci (Landmark Ed) 2017; 22:1221-1246. [PMID: 28199202 DOI: 10.2741/4543] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Genetic mutations and metabolic reprogramming are two key hallmarks of cancer, required for proliferation, invasion, and metastasis of the disease. While genetic mutations, whether inherited or acquired, are critical for the initiation of tumor development, metabolic reprogramming is an effector mechanism imperative for adaptational transition during the progression of cancer. Recent findings in the literature emphasize the significance of molecular cross-talk between these two cellular processes in regulating signaling and differentiation of cancer cells. Genome-wide sequencing analyses of cancer genomes have highlighted the association of various genic mutations in predicting cancer risk and survival. Oncogenic mutational frequency is heterogeneously distributed among various cancer types in different populations, resulting in varying susceptibility to cancer risk. In this review, we explore and discuss the role of genetic mutations in metabolic enzymes and metabolic oncoregulators to stratify cancer risk in persons of different racial backgrounds.
Collapse
Affiliation(s)
- Kuldeep S Attri
- Eppley Institute for Research in Cancer and Allied Diseases, University of Nebraska Medical Center, Omaha, Nebraska, 68198, USA
| | - Divya Murthy
- Eppley Institute for Research in Cancer and Allied Diseases, University of Nebraska Medical Center, Omaha, Nebraska, 68198, USA
| | - Pankaj K Singh
- Eppley Institute for Research in Cancer and Allied Diseases, University of Nebraska Medical Center, Omaha, Nebraska, 68198, USA,
| |
Collapse
|
|
22
|
Do Canto LM, Marian C, Varghese RS, Ahn J, Da Cunha PA, Willey S, Sidawy M, Rone JD, Cheema AK, Luta G, Nezami ranjbar MR, Ressom HW, Haddad BR. Metabolomic profiling of breast tumors using ductal fluid. Int J Oncol 2016; 49:2245-2254. [PMID: 27748798 PMCID: PMC5117995 DOI: 10.3892/ijo.2016.3732] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2016] [Accepted: 09/26/2016] [Indexed: 12/12/2022] Open
Abstract
Identification of new biomarkers for breast cancer remains critical in order to enhance early detection of the disease and improve its prognosis. Towards this end, we performed an untargeted metabolomic analysis of breast ductal fluid using an ultra-performance liquid chromatography coupled with a quadrupole time-of-light (UPLC-QTOF) mass spectrometer. We investigated the metabolomic profiles of breast tumors using ductal fluid samples collected by ductal lavage (DL). We studied fluid from both the affected breasts and the unaffected contralateral breasts (as controls) from 43 women with confirmed unilateral breast cancer. Using this approach, we identified 1560 ions in the positive mode and 538 ions in the negative mode after preprocessing of the UPLC‑QTOF data. Paired t-tests applied on these data matrices identified 209 ions (positive and negative modes combined) with significant change in intensity level between affected and unaffected control breasts (adjusted p-values <0.05). Among these, 83 ions (39.7%) showed a fold change (FC) >1.2 and 66 ions (31.6%) were identified with putative compound names. The metabolites that we identified included endogenous metabolites such as amino acid derivatives (N-Acetyl-DL-tryptophan) or products of lipid metabolism such as N-linoleoyl taurine, trans-2-dodecenoylcarnitine, lysophosphatidylcholine LysoPC(18:2(9Z,12Z)), glycerophospholipids PG(18:0/0:0), and phosphatidylserine PS(20:4(5Z,8Z,11Z,14Z). Generalized LASSO regression further selected 21 metabolites when race, menopausal status, smoking, grade and TNM stage were adjusted for. A predictive conditional logistic regression model, using the LASSO selected 21 ions, provided diagnostic accuracy with the area under the curve of 0.956 (sensitivity/specificity of 0.907/0.884). This is the first study that shows the feasibility of conducting a comprehensive metabolomic profiling of breast tumors using breast ductal fluid to detect changes in the cellular microenvironment of the tumors and shows the potential for this approach to be used to improve detection of breast cancer.
Collapse
MESH Headings
- Biomarkers, Tumor/metabolism
- Breast Neoplasms/diagnosis
- Breast Neoplasms/pathology
- Carcinoma, Intraductal, Noninfiltrating/diagnosis
- Carcinoma, Intraductal, Noninfiltrating/pathology
- Chromatography, Liquid
- Female
- Humans
- Mammary Glands, Human/physiology
- Mass Spectrometry
- Metabolome/physiology
- Metabolomics/methods
- Middle Aged
- Receptor, ErbB-2/metabolism
- Receptors, Estrogen/metabolism
- Receptors, Progesterone/metabolism
Collapse
Affiliation(s)
- Luisa Matos Do Canto
- Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington DC, USA
| | - Catalin Marian
- Biochemistry Department, ‘Victor Babes’ University of Medicine and Pharmacy, Timisoara, Romania
- Ohio State University Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
| | - Rency S. Varghese
- Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington DC, USA
| | - Jaeil Ahn
- Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington DC, USA
- Department of Biostatistics, Bioinformatics and Biomathematics, Georgetown University Medical Center, Georgetown University, Washington DC, 20007, USA
| | - Patricia A. Da Cunha
- Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington DC, USA
| | - Shawna Willey
- Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington DC, USA
- Department of Surgery, MedStar Georgetown University Hospital, Georgetown University, Washington DC, 20007, USA
| | - Mary Sidawy
- Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington DC, USA
- Department of Pathology, MedStar Georgetown University Hospital, Georgetown University, Washington DC, 20007, USA
| | - Janice D. Rone
- Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington DC, USA
| | - Amrita K. Cheema
- Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington DC, USA
- Department of Biochemistry and Molecular and Cellular Biology, Georgetown University Medical Center, Georgetown University, Washington DC, 20007, USA
| | - George Luta
- Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington DC, USA
- Department of Biostatistics, Bioinformatics and Biomathematics, Georgetown University Medical Center, Georgetown University, Washington DC, 20007, USA
| | - Mohammad R. Nezami ranjbar
- Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington DC, USA
| | - Habtom W. Ressom
- Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington DC, USA
| | - Bassem R. Haddad
- Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington DC, USA
| |
Collapse
|
|
23
|
Girotra S, Yeghiazaryan K, Golubnitschaja O. Potential biomarker panels in overall breast cancer management: advancements by multilevel diagnostics. Per Med 2016; 13:469-484. [PMID: 29767597 DOI: 10.2217/pme-2016-0020] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Breast cancer (BC) prevalence has reached an epidemic scale with half a million deaths annually. Current deficits in BC management include predictive and preventive approaches, optimized screening programs, individualized patient profiling, highly sensitive detection technologies for more precise diagnostics and therapy monitoring, individualized prediction and effective treatment of BC metastatic disease. To advance BC management, paradigm shift from delayed to predictive, preventive and personalized medical services is essential. Corresponding step forwards requires innovative multilevel diagnostics procuring specific panels of validated biomarkers. Here, we discuss current instrumental advancements including genomics, proteomics, epigenetics, miRNA, metabolomics, circulating tumor cells and cancer stem cells with a focus on biomarker discovery and multilevel diagnostic panels. A list of the recommended biomarker candidates is provided.
Collapse
|
|
24
|
Verbeck G, Hamilton J. One-Cell Analysis as a Technique for True Single-Cell Analysis of Organelles in Breast Tumor and Adjacent Normal Tissue to Profile Fatty Acid Composition of Triglyceride Species. ACTA ACUST UNITED AC 2016. [DOI: 10.6000/1927-7229.2016.05.02.1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
|
|
25
|
Metabolomic Approaches in Cancer Epidemiology. Diseases 2015; 3:167-175. [PMID: 28943618 PMCID: PMC5548249 DOI: 10.3390/diseases3030167] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2015] [Revised: 07/30/2015] [Accepted: 07/31/2015] [Indexed: 12/31/2022] Open
Abstract
Metabolomics is the study of low molecular weight molecules or metabolites produced within cells and biological systems. It involves technologies such as mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR) that can measure hundreds of thousands of unique chemical entities (UCEs). The metabolome provides one of the most accurate reflections of cellular activity at the functional level and can be leveraged to discern mechanistic information during normal and disease states. The advantages of metabolomics over other “omics” include its high sensitivity and ability to enable the analysis of relatively few metabolites compared with the number of genes and messenger RNAs (mRNAs). In clinical samples, metabolites are more stable than proteins or RNA. In fact, metabolomic profiling in basic, epidemiologic, clinical, and translational studies has revealed potential new biomarkers of disease and therapeutic outcome and has led to a novel mechanistic understanding of pathogenesis. These potential biomarkers include novel metabolites associated with cancer initiation, regression, and recurrence. Unlike genomics or even proteomics, however, the degree of metabolite complexity and heterogeneity within biological systems presents unique challenges that require specialized skills and resources to overcome. This article discusses epidemiologic studies of altered metabolite profiles in several cancers as well as challenges in the field and potential approaches to overcoming them.
Collapse
|
|
26
|
Bujak R, Struck-Lewicka W, Markuszewski MJ, Kaliszan R. Metabolomics for laboratory diagnostics. J Pharm Biomed Anal 2014; 113:108-20. [PMID: 25577715 DOI: 10.1016/j.jpba.2014.12.017] [Citation(s) in RCA: 273] [Impact Index Per Article: 24.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2014] [Revised: 12/08/2014] [Accepted: 12/10/2014] [Indexed: 12/24/2022]
Abstract
Metabolomics is an emerging approach in a systems biology field. Due to continuous development in advanced analytical techniques and in bioinformatics, metabolomics has been extensively applied as a novel, holistic diagnostic tool in clinical and biomedical studies. Metabolome's measurement, as a chemical reflection of a current phenotype of a particular biological system, is nowadays frequently implemented to understand pathophysiological processes involved in disease progression as well as to search for new diagnostic or prognostic biomarkers of various organism's disorders. In this review, we discussed the research strategies and analytical platforms commonly applied in the metabolomics studies. The applications of the metabolomics in laboratory diagnostics in the last 5 years were also reviewed according to the type of biological sample used in the metabolome's analysis. We also discussed some limitations and further improvements which should be considered taking in mind potential applications of metabolomic research and practice.
Collapse
Affiliation(s)
- Renata Bujak
- Department of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, ul. Gen J. Hallera 107, Gdańsk 80-416, Poland
| | - Wiktoria Struck-Lewicka
- Department of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, ul. Gen J. Hallera 107, Gdańsk 80-416, Poland
| | - Michał J Markuszewski
- Department of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, ul. Gen J. Hallera 107, Gdańsk 80-416, Poland.
| | - Roman Kaliszan
- Department of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, ul. Gen J. Hallera 107, Gdańsk 80-416, Poland.
| |
Collapse
|