Contribution of allelic imbalance to colorectal cancer

Abstract

Point mutations in cancer have been extensively studied but chromosomal gains and losses have been more challenging to interpret due to their unspecific nature. Here we examine high-resolution allelic imbalance (AI) landscape in 1699 colorectal cancers, 256 of which have been whole-genome sequenced (WGSed). The imbalances pinpoint 38 genes as plausible AI targets based on previous knowledge. Unbiased CRISPR-Cas9 knockout and activation screens identified in total 79 genes within AI peaks regulating cell growth. Genetic and functional data implicate loss of TP53 as a sufficient driver of AI. The WGS highlights an influence of copy number aberrations on the rate of detected somatic point mutations. Importantly, the data reveal several associations between AI target genes, suggesting a role for a network of lineage-determining transcription factors in colorectal tumorigenesis. Overall, the results unravel the contribution of AI in colorectal cancer and provide a plausible explanation why so few genes are commonly affected by point mutations in cancers.

Retrotransposon insertions can initiate colorectal cancer and are associated with poor survival

“…3Retrotransposon insertion distribution in LRP1B and DLG2 . Mapping of retrotransposon insertions identified in 202 colorectal tumors, HPV integration hotspots reported in 135 cervical cancers and allelic imbalance breakpoints identified in 1,699 CRCs 31,36 . Figure plotted with genoPlotR 64 .…”

“…We observed recurrent insertions in 12 out of 21 genes with high probability of being fragile as estimated in another study 30 (Supplementary Data 3). Since common fragile sites are prone to copy number alterations (CNAs) 35 , we evaluated whether retrotransposition and CNAs—in this study detected as AI 36 —were correlated (Supplementary Data 3). Fragile sites with high frequency of insertions seemed to display lower frequency of AI (Fig.…”

“…We utilized 196 colorectal tumors with complete information on molecular and clinical variables that were included in the model (Table 2, Supplementary Data 5). We applied a multiple linear regression model for log-transformed insertion counts, and hypothesized that the number of somatic insertions may be associated with tumor location, TP53 mutation, MSI, genomic fraction of AI 36 and CIMP. The model was adjusted for mean sequencing coverage, tumor stage, sex and age at diagnosis (Table 2).…”

Developmental and MAPK-responsive transcription factors drive distinct malignant subtypes and genetic dependencies in pancreatic cancer

“…Pooled CRISPR/Cas9-mediated knockout screens were performed in each cell line, using guide RNAs (sgRNAs) targeting 3,179 genes including all TR proteins studied in the VIPER analysis 12 , as well as selected core essential and non-essential genes, as positive and negative controls 33,34 (Extended Data Fig. 6b).…”

Cellular transformation by combined lineage conversion and oncogene expression

“…Cancer genomes harbor large-scale chromosomal aberrations and are characterized by aneuploidy 27,28 . To understand the gross chromosomal aberrations in the transformed tumorigenic CMT and CMT+sgTP53 iHeps compared to normal HFs, we performed spectral karyotyping, which showed a normal diploid male (46,XY) in HFs and aneuploid karyotypes in transformed iHeps (Fig.…”