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• W2810346511 abstract "Introduction According to models of known mutational processes, site-specific hotspots of even just a few mutations become unlikely in large cancer genomic datasets (four mutations in our case). These hotspots may affect cancer development or be a consequence of localised mutational processes. Here, we identify and characterise protein-coding and non-coding site-specific hotspots. Material and methods We use whole genome sequencing data from 2583 cancer patients across 37 cancer types from Pan-Cancer Analysis of Whole Genomes (PCAWG) under ICGC/TCGA. We identify SNV and indel hotspots genome-wide, annotate them with their genomic features, and investigate expression-correlation and cancer allele fractions. Results and discussions We find 566,760 SNV and 1 69 839 indel hotspots, which are genomic positions with two or more SNVs/indels across patients. A small fraction of the hotspots are in protein-coding regions (0.7% for both sets; 3.3x enrichment of local mutation rate in genomic region for SNVs; 1.7x for indels) and regulatory elements of protein-coding genes (0.9%/1.3 x for SNVs; 1.8%/1.04 x for indels). Only a small fraction of the protein-coding hotspots fall in the known drivers from Cancer Gene Census (0.9% for SNVs; 0.8% for indels). Among the top-20 SNV hotspots are 13 positions in known driver sites in protein-coding genes, a known driver site in the TERT promoter, two positions in the PLEKHS1 promoter and a position in a GPR126 intron now known to likely be caused by APOBEC editing, and four non-coding sites possibly caused by different mutational processes. In contrast, none of the top-20 indel hotspots overlap protein-coding genes or regulatory elements. All 20 are deletion-hotspots, and they are located at least 14 kb away from the transcription start site of the nearest protein-coding gene. One third of the SNV hotspots are almost exclusive to a single cancer type. Cancers with high mutational burden and cancer-type specific mutational processes top the list. E.g. colorectal cancer hotspots, likely caused by patients with microsatellite-instability, and melanoma hotspots, likely caused by UV-induced DNA damages. Moreover, analyses of cancer allele fractions and expression correlation in stratified promoter sets indicate a weak signal of positive selection on a few hotspots in promoters of oncogenes. Conclusion We see no clear driver signal from other non-coding hotspots than two already known positions in the TERT promoter. Mutational processes appear to be the dominating contributor to non-coding hotspots." @default.
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• W2810346511 date "2018-06-01" @default.
• W2810346511 modified "2023-09-26" @default.
• W2810346511 title "PO-313 Genome-wide analysis of site-specific hotspots in cancer" @default.
• W2810346511 doi "https://doi.org/10.1136/esmoopen-2018-eacr25.343" @default.
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