Co-expression in tissue-specific gene networks links genes in cancer-susceptibility loci to known somatic driver genes

Background The genetic background of cancer remains complex and challenging to integrate. Many somatic mutations in genes are known to cause and drive cancer, while genome-wide association studies (GWAS) of cancer have revealed many germline risk factors associated with cancer. However, the overlap between known somatic driver genes and positional candidate genes from GWAS loci is surprisingly small. We hypothesised that genes from multiple independent cancer GWAS loci should show tissue-specific co-regulation patterns that converge on cancer-specific driver genes. Results We studied recent well powered GWAS of breast, prostate, colorectal and skin cancer by estimating co-expression between genes and subsequently prioritising genes that show co- expression with genes mapping within susceptibility loci from cancer GWAS. We observed that the prioritised genes were strongly enriched for cancer drivers defined by COSMIC, intOGen and Dietlein et al . The enrichment of known cancer driver genes was most significant when using co-expression networks derived from non-cancer samples from the relevant tissue of origin. Conclusion We show how genes in risk loci identified by cancer GWAS can be linked to known cancer driver genes through tissue-specific co-expression networks. This provides an important explanation for why seemingly unrelated sets of genes that harbour either germline risk factors or somatic mutations can eventually cause the same type of disease. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement P.D. is supported by a Dutch Research Council (NWO) ZonMW-VENI grant (no. 9150161910057). L.F. is supported by a grant from the NWO (ZonMW-VICI 09150182010019 to L.F.), a European Research Council Starting Grant (grant agreement 637640 (ImmRisk)), and through a Senior Investigator Grant from the Oncode Institute and a grant from Saxum Volutum (Pericode). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The GWAS summary statistics are made available in the GWAS catalogue (https://www.ebi.ac.uk/gwas/) and BCAC (https://bcac.ccge.medschl.cam.ac.uk/). The data on the Cancer drivers is available under the website of intOGen (https://www.intogen.org/download), Zenodo of Dietlein et al. (https://zenodo.org/record/5913867) and the website of COSMIC (https://cancer.sanger.ac.uk/cosmic). RNA-seq samples can be retrieved from recount3 (http://rna.recount.bio/). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present work are contained in the manuscript with the exception of the generated tissue-specific networks that are available upon reasonable request to the authors.