Investigator
Associate Professor · Dana-Farber Cancer Institute, Medical Oncology
Germline Cancer Gene Expression Quantitative Trait Loci Are Associated with Local and Global Tumor Mutations
Abstract Somatic mutations drive cancer development and are relevant to patient responses to treatment. Emerging evidence shows that variations in the somatic genome can be influenced by the germline genetic background. However, the mechanisms underlying these germline–somatic associations remain largely obscure. We hypothesized that germline variants can influence somatic mutations in a nearby cancer gene (“local impact”) or a set of recurrently mutated cancer genes across the genome (“global impact”) through their regulatory effect on gene expression. To test this hypothesis, tumor targeted sequencing data from 12,413 patients across 11 cancer types in the Dana-Farber Profile cohort were integrated with germline cancer gene expression quantitative trait loci (eQTL) from the Genotype-Tissue Expression Project. Variants that upregulate ATM expression were associated with a decreased risk of somatic ATM mutations across 8 cancer types. GLI2, WRN, and CBFB eQTL were associated with global tumor mutational burden of cancer genes in ovarian cancer, glioma, and esophagogastric carcinoma, respectively. An EPHA5 eQTL was associated with mutations in cancer genes specific to colorectal cancer, and eQTL related to expression of APC, WRN, GLI1, FANCA, and TP53 were associated with mutations in genes specific to endometrial cancer. These findings provide evidence that germline–somatic associations are mediated through expression of specific cancer genes, opening new avenues for research on the underlying biological processes. Significance: Analysis of associations between the germline genetic background and somatic mutations in patients with cancer suggests that germline variants can influence local and global tumor mutations by altering expression of cancer-related genes. See related commentary by Kar, p. 1165.
Obesity-dependent selection of driver mutations in cancer
Obesity is a risk factor for cancer, but whether obesity is linked to specific genomic subtypes of cancer is unknown. We examined the relationship between obesity and tumor genotype in two clinicogenomic corpora. Obesity was associated with specific driver mutations in lung adenocarcinoma, endometrial carcinoma and cancers of unknown primaries, independent of clinical covariates, demographic factors and genetic ancestry. Obesity is therefore a driver of etiological heterogeneity in some cancers.
Associate Professor
Dana-Farber Cancer Institute · Medical Oncology
Postdoctoral Fellow
Harvard School of Public Health · Epidemiology & Biostatistics