Contribution of allelic imbalance to colorectal cancer

• DOI: 10.1038/s41467-018-06132-1
• Publication Date: 2018-09-04T09:47:50Z
• Authors: Kimmo Palin; Esa Pitkänen; Mikko Turunen; Biswajyoti Sahu; Päivi Pihlajamaa; Teemu Kivioja; Eevi Kaasinen; Niko Välimäki; Ulrika A. Hänninen; Tatiana Cajuso; Mervi Aavikko; Sari Tuupanen; Outi Kilpivaara; Linda van den Berg; Johanna Kondelin; Tomas Tanskanen; Riku Katainen; Marta Grau; Heli Rauanheimo; Roosa-Maria Plaketti; Aurora Taira; Päivi Sulo; Tuomo Hartonen; Kashyap Dave; Bernhard Schmierer; Sandeep Botla; Maria Sokolova; Anna Vähärautio; Kornelia Gladysz; Halit Ongen; Emmanouil Dermitz...; Jesper Bertram Br...; Torben Falck Ørntoft; Claus Lindbjerg A...; Ari Ristimäki; Anna Lepistö; Laura Renkonen-Si...; Jukka-Pekka Mecklin; Jussi Taipale; Lauri A. Aaltonen
• Keywords: 0301 basic medicine; GENES; DNA Copy Number Variations; Genotype; Science; Denmark; Transcription Factors/genetics; Loss of Heterozygosity; colorectal cancer; Allelic Imbalance; Article; Proto-Oncogene Proteins p21(ras)/genetics; Proto-Oncogene Proteins p21(ras); 03 medical and health sciences; Humans; Point Mutation; ddc:576.5; Genetic Predisposition to Disease; RNA, Small Interfering; paksusuolisyöpä; RNA, Small Interfering/genetics; Chromosome Aberrations; Whole Genome Sequencing; HUMAN-COLON; info:eu-repo/classification/ddc/576.5; Gene Expression Profiling; Q; Genomics; Colorectal Neoplasms/genetics; 3. Good health; GENOME; ENHANCERS; Biomedicine; Phenotype; syöpägeenit; CELLS; Tumor Suppressor Protein p53/genetics; mutaatiot; CRISPR-Cas Systems; Tumor Suppressor Protein p53; Colorectal Neoplasms; Chromosomes, Human, Pair 8; Microsatellite Repeats; Transcription Factors

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