Abstract
A systematic cataloging of genes affected by genomic rearrangement, using multiple patient cohorts and cancer types, can provide insight into cancer-relevant alterations outside of exomes. By integrative analysis of whole-genome sequencing (predominantly low pass) and gene expression data from 1,448 cancers involving 18 histopathological types in The Cancer Genome Atlas, we identified hundreds of genes for which the nearby presence (within 100 kb) of a somatic structural variant (SV) breakpoint is associated with altered expression. While genomic rearrangements are associated with widespread copy-number alteration (CNA) patterns, approximately 1,100 genes-including overexpressed cancer driver genes (e.g., TERT, ERBB2, CDK12, CDK4) and underexpressed tumor suppressors (e.g., TP53, RB1, PTEN, STK11)-show SV-associated deregulation independent of CNA. SVs associated with the disruption of topologically associated domains, enhancer hijacking, or fusion transcripts are implicated in gene upregulation. For cancer-relevant pathways, SVs considerably expand our understanding of how genes are affected beyond point mutation or CNA.
Highlights
Somatic structural variant (SV) across Cancer Types We analyzed WGS data from 1,493 individuals across 18 cancer types represented in The Cancer Genome Atlas (TCGA) cohort (Tables 1 and S1), with cases including 114 bladder urothelial carcinomas (BLCAs), 89 breastinvasive carcinomas (BRCAs), 51 cervical squamous cell cytoband-level copy-number alteration (CNA) BLCA 9611 BRCA 38449 CESC 1653 colorectal adenocarcinomas (CRCs) 2395 esophageal carcinomas (ESCAs) 4063 head and neck squamous cell carcinomas (HNSCs) 4078 KICH 1380 kidney clear cell renal cell carcinomas (KIRCs) 1779 kidney renal papillary cell carcinomas (KIRPs) 1042 lower-grade gliomas (LGGs) 1696 lung adenocarcinomas (LUADs) 5899
In addition to CNA at the cytoband level, we considered CNAs at the gene level to be associated with SV breakpoints
For each of the genomic regions relative to genes that were considered, we found widespread associations between SV event and expression, after correcting for expression patterns associated with tumor type or CNA (Figures 2B and S2A; Table S4)
Summary
We aimed to identify genes for which the nearby presence of an SV breakpoint could be significantly associated with changes in expression
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