The cis-regulatory effects responsible for cancer development have not been as extensively studied as the perturbations of the protein coding genome in tumorigenesis1,2. To better characterize colorectal cancer (CRC) development we conducted an RNA-sequencing experiment of 103 matched tumour and normal colon mucosa samples from Danish CRC patients, 90 of which were germline-genotyped. By investigating allele-specific expression (ASE) we show that the germline genotypes remain important determinants of allelic gene expression in tumours. Using the changes in ASE in matched pairs of samples we discover 71 genes with excess of somatic cis-regulatory effects in CRC, suggesting a cancer driver role. We correlate genotypes and gene expression to identify expression quantitative trait loci (eQTLs) and find 1,693 and 948 eQTLs in normal samples and tumours, respectively. We estimate that 36% of the tumour eQTLs are exclusive to CRC and show that this specificity is partially driven by increased expression of specific transcription factors and changes in methylation patterns. We show that tumour-specific eQTLs are more enriched for low CRC genome-wide association study (GWAS) P values than shared eQTLs, which suggests that some of the GWAS variants are tumour specific regulatory variants. Importantly, tumour-specific eQTL genes also accumulate more somatic mutations when compared to the shared eQTL genes, raising the possibility that they constitute germline-derived cancer regulatory drivers. Collectively the integration of genome and the transcriptome reveals a substantial number of putative somatic and germline cis-regulatory cancer changes that may have a role in tumorigenesis.
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The RNA-sequencing and genotype data are deposited in the European Genome-phenome Archive (EGA, https://www.ebi.ac.uk/ega/) for controlled accesses; the study accession number is EGAS00001000854.
This study was designed under the SYSCOL project and samples were collected with informed consent in accordance with local law. This research is supported by grants from European Commission SYSCOL FP7 (UE7-SYSCOL-258236), European Research Council (ERC 260927), Louis Jeantet Foundation, Swiss National Science Foundation (130326, 130342), the NIH-NIMH (MH090941), the Danish National Advanced Technology Foundation, the John and Birthe Meyer Foundation, the Danish Council for Independent Research (Medical Sciences), the Danish Council for Strategic Research, the Danish Cancer Society, The Cellex Foundation, the Botin Foundation, the Fundacion Olga Torres, and the Health and Science Departments of the Catalan Government (Generalitat de Catalunya). The Danish Cancer Biobank is acknowledged for biological material. We thank S. Moran, D. Garcia and C. Arribas for their technical support. This study was also funded by Cancer Research UK and The Oxford Comprehensive Biomedical Research Centre (I.P.T.). Core infrastructure support to the Wellcome Trust Centre for Human Genetics, Oxford, was provided by grant (090532/Z/09/Z). Cancer Research UK provided funding individually to R.S.H. (C1298/A8362–Bobby Moore Fund for Cancer Research UK). This study made use of genotyping data from the 1958 Birth Cohort and NBS samples, kindly made available by the Wellcome Trust Case Control Consortium 2. The computations were performed at the Vital-IT (http://www.vital-it.ch) Center for high-performance computing of the SIB Swiss Institute of Bioinformatics.
This file contains Supplementary Tables 1-13.
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Nature Communications (2018)