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Hu J, Li T, Wang S, Zhang H. Supervariants identification for breast cancer. Genet Epidemiol 2020; 44:934-947. [PMID: 32808324 PMCID: PMC7924970 DOI: 10.1002/gepi.22350] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 07/24/2020] [Accepted: 08/05/2020] [Indexed: 01/02/2023]
Abstract
In genome-wide association studies, signals associated with rare variants and interactions between genes are hard to detect even when the sample size is in tens of thousands. To overcome these problems, we examine the concept of supervariant. Like the classic concept of the gene, a supervariant is a combination of alleles in multiple loci, but the contributing loci can be anywhere in the genome. We hypothesize that supervariants are easy to detect and the aggregated signals are more stable in their associations with the disease than that from a single nucleoid polymorphism. Using the UK Biobank databases, we develop a ranking and aggregation method for identifying supervariants. Specifically, we examine 9,377 breast cancer cases with 46,861 controls matched by sex and age. In our simulations, the use of supervariants outperforms single-nucleotide polymorphism-based association method in detecting rare variants and signals with interactive structure. In real data analysis, we identify supervariants on Chromosomes 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 16, and 22 which cover previously reported loci that have associations with breast or other cancers, and several novel loci on Chromosomes 2, 5, 9, and 12. These findings demonstrate the validity of supervariants and its potential of discovering replicable and novel results for complex disease.
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Affiliation(s)
- Jianchang Hu
- Department of Biostatistics, Yale University School of Public Health, New Haven, Connecticut
| | - Ting Li
- Department of Biostatistics, Yale University School of Public Health, New Haven, Connecticut
| | - Shiying Wang
- Department of Biostatistics, Yale University School of Public Health, New Haven, Connecticut
| | - Heping Zhang
- Department of Biostatistics, Yale University School of Public Health, New Haven, Connecticut
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Kim G, Pastoriza JM, Condeelis JS, Sparano JA, Filippou PS, Karagiannis GS, Oktay MH. The Contribution of Race to Breast Tumor Microenvironment Composition and Disease Progression. Front Oncol 2020; 10:1022. [PMID: 32714862 PMCID: PMC7344193 DOI: 10.3389/fonc.2020.01022] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 05/22/2020] [Indexed: 12/12/2022] Open
Abstract
Breast cancer is the second most commonly diagnosed cancer in American women following skin cancer. Despite overall decrease in breast cancer mortality due to advances in treatment and earlier screening, black patients continue to have 40% higher risk of breast cancer related death compared to white patients. This disparity in outcome persists even when controlled for access to care and stage at presentation and has been attributed to differences in tumor subtypes or gene expression profiles. There is emerging evidence that the tumor microenvironment (TME) may contribute to the racial disparities in outcome as well. Here, we provide a comprehensive review of current literature available regarding race-dependent differences in the TME. Notably, black patients tend to have a higher density of pro-tumorigenic immune cells (e.g., M2 macrophages, regulatory T cells) and microvasculature. Although immune cells are classically thought to be anti-tumorigenic, increase in M2 macrophages and angiogenesis may lead to a paradoxical increase in metastasis by forming doorways of tumor cell intravasation called tumor microenvironment of metastasis (TMEM). Furthermore, black patients also have higher serum levels of inflammatory cytokines, which provide a positive feedback loop in creating a pro-metastatic TME. Lastly, we propose that the higher density of immune cells and angiogenesis observed in the TME of black patients may be a result of evolutionary selection for a more robust immune response in patients of African geographic ancestry. Better understanding of race-dependent differences in the TME will aid in overcoming the racial disparity in breast cancer mortality.
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Affiliation(s)
- Gina Kim
- Department of Anatomy and Structural Biology, Montefiore Medical Center, Einstein College of Medicine, Bronx, NY, United States.,Integrated Imaging Program, Montefiore Medical Center, Einstein College of Medicine, Bronx, NY, United States.,Department of Surgery, Montefiore Medical Center, Einstein College of Medicine, Bronx, NY, United States
| | - Jessica M Pastoriza
- Department of Surgery, Montefiore Medical Center, Einstein College of Medicine, Bronx, NY, United States
| | - John S Condeelis
- Department of Anatomy and Structural Biology, Montefiore Medical Center, Einstein College of Medicine, Bronx, NY, United States.,Integrated Imaging Program, Montefiore Medical Center, Einstein College of Medicine, Bronx, NY, United States.,Department of Surgery, Montefiore Medical Center, Einstein College of Medicine, Bronx, NY, United States.,Gruss-Lipper Biophotonics Center, Montefiore Medical Center, Einstein College of Medicine, Bronx, NY, United States
| | - Joseph A Sparano
- Integrated Imaging Program, Montefiore Medical Center, Einstein College of Medicine, Bronx, NY, United States.,Department of Medicine (Oncology), Montefiore Medical Center, Einstein College of Medicine, Bronx, NY, United States
| | - Panagiota S Filippou
- School of Health & Life Sciences, Teesside University, Middlesbrough, United Kingdom.,National Horizons Centre, Teesside University, Darlington, United Kingdom
| | - George S Karagiannis
- Department of Anatomy and Structural Biology, Montefiore Medical Center, Einstein College of Medicine, Bronx, NY, United States.,Integrated Imaging Program, Montefiore Medical Center, Einstein College of Medicine, Bronx, NY, United States.,Gruss-Lipper Biophotonics Center, Montefiore Medical Center, Einstein College of Medicine, Bronx, NY, United States
| | - Maja H Oktay
- Department of Anatomy and Structural Biology, Montefiore Medical Center, Einstein College of Medicine, Bronx, NY, United States.,Integrated Imaging Program, Montefiore Medical Center, Einstein College of Medicine, Bronx, NY, United States.,Gruss-Lipper Biophotonics Center, Montefiore Medical Center, Einstein College of Medicine, Bronx, NY, United States.,Department of Pathology, Montefiore Medical Center, Einstein College of Medicine, Bronx, NY, United States
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