Title: Evaluating the role of inflammation in cancer: robust target identification using genomic data
Funder: Cancer Research UK

Abstract: Background Prospective observational studies have reported associations between circulating inflammatory markers and incident and fatal cancer. These findings, consistent with inflammation as a hallmark of cancer, suggest that targeting inflammatory pathways with new or repurposed drugs could be an effective strategy for cancer prevention and treatment. However, the causal nature of these inflammatory markers in different stages of carcinogenesis, and thus their suitability as intervention targets, is often unclear. This is because of the susceptibility of conventional observational designs to various biases such as residual confounding, reverse causation, and measurement error, which undermine causal inference. Aims This proposal aims to use Mendelian randomization (MR), a genetic epidemiological approach that is less susceptible to these biases, to understand whether observed associations of circulating inflammatory markers with cancer incidence and progression are causal. I will systematically evaluate 30 inflammatory markers for causal associations with incidence of 10 adult cancers along with progression of 3 of these cancers. I will follow-up top findings from these analyses for replication in independent datasets. For inflammatory markers showing evidence of replication, I will then perform analyses to: i) map findings to approved drugs for repurposing opportunities; ii) examine existing biological evidence to support their prioritisation as drug targets using a “target validation” platform; and iii) predict potential adverse effects of their pharmacological targeting. Methods Summary genetic association data for associations of single nucleotide polymorphisms (SNPs) with inflammatory markers and cancer outcomes will be obtained from large genome-wide association studies (GWAS) and cancer GWAS consortia, respectively. Genetic instruments to proxy inflammatory markers will be constructed by identifying single SNPs robustly associated with circulating inflammatory markers or through combining multiple SNPs into multi-allelic instruments to increase statistical power. MR estimates per standard deviation increase in genetically-proxied inflammatory markers will be generated using the Wald ratio method (1 SNP instrument) or inverse-variance weighted models (=2 SNP multi-allelic instruments). Violations of MR assumptions will be assessed by performing various established sensitivity analyses. Validation analyses will be performed in two large independent datasets and causal estimates across analyses will be meta-analysed, when appropriate. How the results of this research will be used Findings from these proposed analyses can help to resolve the causal role of previously reported associations between inflammatory markers and cancer incidence and progression. Robust identification of inflammatory markers that contribute aetiologically to disease development could have implications for the design of effective primary and tertiary cancer prevention strategies.


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: CANCER AND NEOPLASMS