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Large-scale cross-cancer fine-mapping of the 5p15.33 region reveals multiple independent signals
Department of Epidemiology, University of Washington, WA, Seattle, United States.
Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, Los Angeles, United States; Department of Mathematics, Indian Institute of Technology Hyderabad, Kandi, India.
Department of Environmental and Occupational Health Sciences, University of Washington, WA, Seattle, United States.
Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.
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2021 (English)In: Human Genetics and Genomics Advances, E-ISSN 2666-2477, Vol. 2, no 3, article id 100041Article in journal (Refereed) Published
Abstract [en]

Genome-wide association studies (GWASs) have identified thousands of cancer risk loci revealing many risk regions shared across multiple cancers. Characterizing the cross-cancer shared genetic basis can increase our understanding of global mechanisms of cancer development. In this study, we collected GWAS summary statistics based on up to 375,468 cancer cases and 530,521 controls for fourteen types of cancer, including breast (overall, estrogen receptor [ER]-positive, and ER-negative), colorectal, endometrial, esophageal, glioma, head/neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancer, to characterize the shared genetic basis of cancer risk. We identified thirteen pairs of cancers with statistically significant local genetic correlations across eight distinct genomic regions. Specifically, the 5p15.33 region, harboring the TERT and CLPTM1L genes, showed statistically significant local genetic correlations for multiple cancer pairs. We conducted a cross-cancer fine-mapping of the 5p15.33 region based on eight cancers that showed genome-wide significant associations in this region (ER-negative breast, colorectal, glioma, lung, melanoma, ovarian, pancreatic, and prostate cancer). We used an iterative analysis pipeline implementing a subset-based meta-analysis approach based on cancer-specific conditional analyses and identified ten independent cross-cancer associations within this region. For each signal, we conducted cross-cancer fine-mapping to prioritize the most plausible causal variants. Our findings provide a more in-depth understanding of the shared inherited basis across human cancers and expand our knowledge of the 5p15.33 region in carcinogenesis.

Place, publisher, year, edition, pages
Cell Press , 2021. Vol. 2, no 3, article id 100041
Keywords [en]
5p15.33 region, cancer, CLPTM1L, fine-mapping, pleiotropy, TERT
National Category
Medical Genetics and Genomics Cancer and Oncology
Identifiers
URN: urn:nbn:se:umu:diva-191266DOI: 10.1016/j.xhgg.2021.100041ISI: 000787665000010Scopus ID: 2-s2.0-85120473119OAI: oai:DiVA.org:umu-191266DiVA, id: diva2:1627224
Available from: 2022-01-13 Created: 2022-01-13 Last updated: 2025-02-10Bibliographically approved

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Melin, Beatrice S.

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