Our genome-wide association studies of breast cancer risk have been extremely successful, identifying over 180 susceptibility loci. The vast majority of candidate causal variants at these loci are non-coding and likely to impact on gene regulation, so a major challenge lies in identifying their target genes in the relevant cell types, and translating these findings into actionable molecular mechanisms. In order to direct functional follow up studies of breast cancer risk loci, we have developed a heuristic scoring system, Integrated expression quantitative trait and in silico prediction of GWAS targets (INQUISIT), to rank the candidate target genes, based on multiple features derived mostly from in silico data in breast cell lines and tissue. Pathway analysis conducted using the high-confidence target gene predictions found over-representation of immune system pathways with 17% target genes acting in the immune system. These over-represented pathways are partly driven by immuno-suppressive genes, TLR1 and GATA3.
INQUISIT has to date only predicted targets of candidate causal variants for breast cancer risk in breast tissue but there is accumulating evidence that cancer is a dynamic process of immunoediting involving both the tumour and the ‘host’ in which both the innate and adaptive immune systems play a role. However, little is understood about the elimination mechanisms involved in cancer aetiology; most studies of tumour/immune system interactions in humans have focused on the escape phase but most of the evidence for immune elimination comes from animal models. We hypothesized that some breast cancer risk-associated variants might act in immune cells. Using expression quantitative trait loci (eQTL) reported in immune cells, we identified 25 previously unreported, likely target genes of overall breast cancer risk variants, expressed in immune cells, and 17 for estrogen receptor (ER)-negative breast cancer, several with a known immune function...