Large-scale cross-cancer fine-mapping of the 5p15.33 region reveals multiple independent signals

Endometrial Cancer Association Consortium (ECAC), Esophageal Cancer GWAS Consortium, Glioma International Case Control Consortium (GICC), Head-Neck Cancer GWAS Consortium, International Lung Cancer Consortium (ILCCO), Melanoma GWAS Consortium, Ovarian Cancer Association Consortium (OCAC), Pancreatic Cancer Case-Control Consortium (PANC4), Pancreatic Cancer Cohort Consortium (PanScan), PRACTICAL consortium, CRUK, BPC3, CAPS, PEGASUS, Renal Cancer GWAS Consortium, Breast Cancer Association Consortium (BCAC), Colorectal Transdisciplinary Study (CORECT), Colon Cancer Family Registry Study (CCFR), Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO)

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7 Scopus citations


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.

Original languageEnglish
Article number100041
JournalHuman Genetics and Genomics Advances
Issue number3
StatePublished - 8 Jul 2021


  • 5p15.33 region
  • TERT
  • cancer
  • fine-mapping
  • pleiotropy


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