Contribution of allelic imbalance to colorectal cancer

Study ID Alternative Stable ID Type
EGAS00001002966 Other

Study Description

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, and unbiased CRISPR-Cas9 knockout and activation screens identified altogether 79 genes within AI peaks regulating cell growth. Genetic and functional data implicates 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.

Study Datasets 4 datasets.

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Dataset ID Description Technology Samples
siRNA knockdown of 43 Allelic Imbalance target TFs followed by mRNA-seq done in triplicates in three (GP5D, LoVo, COLO320DM) different cell colorectal adenocarcinoma cell lines.
Illumina HiSeq 2000,Illumina HiSeq 4000 426
Chip-exo and Chip-nexus for FOXA1, HNF4A, KLF5, MYC, and TCF7L2 in colorectal cancer cell lines LoVo, GP5D, COLO320DM
Illumina HiSeq 4000 23
Whole genome sequencing of commercial LoVo, GP5D, COLO320DM, CaCo-2 and RPE1 cell lines and three RPE1-TP53 knock-out cell lines separated by 6 months of culture from their most recent common ancestor.
HiSeq X Ten,Illumina HiSeq 2500 8
Allelic imbalance data for cell lines derived from RPE1 with TP53 knockout
humanomniexpress-24-v1-1-a 2

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