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Tran V, Kim R, Maertens M, Hartung T, Maertens A. Similarities and Differences in Gene Expression Networks Between the Breast Cancer Cell Line Michigan Cancer Foundation-7 and Invasive Human Breast Cancer Tissues. Front Artif Intell 2021; 4:674370. [PMID: 34056582 PMCID: PMC8155268 DOI: 10.3389/frai.2021.674370] [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: 03/01/2021] [Accepted: 04/23/2021] [Indexed: 12/31/2022] Open
Abstract
Failure to adequately characterize cell lines, and understand the differences between in vitro and in vivo biology, can have serious consequences on the translatability of in vitro scientific studies to human clinical trials. This project focuses on the Michigan Cancer Foundation-7 (MCF-7) cells, a human breast adenocarcinoma cell line that is commonly used for in vitro cancer research, with over 42,000 publications in PubMed. In this study, we explore the key similarities and differences in gene expression networks of MCF-7 cell lines compared to human breast cancer tissues. We used two MCF-7 data sets, one data set collected by ARCHS4 including 1032 samples and one data set from Gene Expression Omnibus GSE50705 with 88 estradiol-treated MCF-7 samples. The human breast invasive ductal carcinoma (BRCA) data set came from The Cancer Genome Atlas, including 1212 breast tissue samples. Weighted Gene Correlation Network Analysis (WGCNA) and functional annotations of the data showed that MCF-7 cells and human breast tissues have only minimal similarity in biological processes, although some fundamental functions, such as cell cycle, are conserved. Scaled connectivity—a network topology metric—also showed drastic differences in the behavior of genes between MCF-7 and BRCA data sets. Finally, we used canSAR to compute ligand-based druggability scores of genes in the data sets, and our results suggested that using MCF-7 to study breast cancer may lead to missing important gene targets. Our comparison of the networks of MCF-7 and human breast cancer highlights the nuances of using MCF-7 to study human breast cancer and can contribute to better experimental design and result interpretation of study involving this cell line.
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Affiliation(s)
- Vy Tran
- Department of Environmental Health and Engineering, Center for Alternatives to Animal Testing, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
| | - Robert Kim
- Department of Environmental Health and Engineering, Center for Alternatives to Animal Testing, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
| | - Mikhail Maertens
- Department of Environmental Health and Engineering, Center for Alternatives to Animal Testing, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
| | - Thomas Hartung
- Department of Environmental Health and Engineering, Center for Alternatives to Animal Testing, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States.,Department of Biology, Center for Alternatives to Animal Testing-Europe, University of Konstanz, Konstanz, Germany.,Department of Environmental Health and Engineering, Doerenkamp-Zbinden Professor and Chair for Evidence-Based Toxicology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
| | - Alexandra Maertens
- Department of Environmental Health and Engineering, Center for Alternatives to Animal Testing, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
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102
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Xing X, Fan Z, Gao Y, Liu Z. High Prevalence of Triple-Negative Breast Cancer in Southern Shaanxi Province, China. Cancer Manag Res 2021; 13:1609-1615. [PMID: 33628051 PMCID: PMC7898196 DOI: 10.2147/cmar.s295085] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 01/22/2021] [Indexed: 01/05/2023] Open
Abstract
Purpose Describing the clinical features of patients with breast cancer in an area is important to provide the information for the local oncologist to make sound treatment plans. In this study, we explored the clinical features of breast cancer patients in Southern Shaanxi Province, China. Patients and Methods A total of 328 breast cancer patients between 2010 and 2015 were recruited at our hospital. Patients' clinical information and the results of the histopathological examination were collected. Independent sample t-test and Cox regression were used to analyze the data. Results The peak age onset of these patients was between 45 and 50. At diagnosis, 8.23% of patients were at clinical stage 1 and 29.57% were triple-negative breast cancer subtype. High expression of Ki-67 in these patients was found associated with triple-negative breast cancer. The 5-year survival rate in these patients was 66.4%, and the survival rate in stage 1 and 2 patients (88.2%) was significantly higher than that in stage 3 and4 (57.4%). Conclusion We here reported the clinical features of patients with breast cancer in Southern Shaanxi Province, China. The breast cancer patients in Southern Shaanxi Province showed a unique clinical feature.
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Affiliation(s)
- Xuemei Xing
- Department of Clinical Laboratory, 3201 Hospital, Xi'an Jiaotong University Health Science Center, Hanzhong, Shaanxi, 723000, People's Republic of China
| | - Zhigang Fan
- Department of Oncology, 3201 Hospital, Xi'an Jiaotong University Health Science Center, Hanzhong, Shaanxi, 723000, People's Republic of China
| | - Yue Gao
- College of Medical Laboratory Science, Guilin Medical University, Guilin, Guangxi, 541004, People's Republic of China
| | - Zheng Liu
- Department of Clinical Laboratory, 3201 Hospital, Xi'an Jiaotong University Health Science Center, Hanzhong, Shaanxi, 723000, People's Republic of China.,College of Medical Laboratory Science, Guilin Medical University, Guilin, Guangxi, 541004, People's Republic of China
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