Background
Invasive ovarian cancer is a significant cause of gynecologic cancer mortality.
Methods
We examined whether this mortality was associated with inherited variation in ~170 candidate genes/regions (993 SNPs) in a multi-stage analysis based initially on 312 Mayo Clinic cases (172 deaths). Additional analyses used The Cancer Genome Atlas (TCGA; 127 cases, 62 deaths). For the most compelling gene, we immunostained Mayo Clinic tissue micro-arrays (TMAs, 326 cases) and conducted consortium-based SNP replication analysis (2,560 cases, 1,046 deaths).
Results
The strongest initial mortality association was in HGF (hepatocyte growth factor) at rs1800793 (HR 1.7, 95% CI 1.3–2.2, p=2.0×10−5) and with overall variation in HGF (gene-level test, p=3.7×10−4). Analysis of TCGA data revealed consistent associations (e.g., rs5745709 [r2=0.96 with rs1800793]: TCGA 2.4, 1.4–4.1, p=2.2×10−3; Mayo Clinic+TCGA 1.6, 1.3–1.9, p=7.0×10−5) and suggested genotype correlation with reduced HGF mRNA levels (p=0.01). In Mayo Clinic TMAs, protein levels of HGF, its receptor MET, and phospho-MET were not associated with genotype and did not serve as an intermediate phenotype; however, phospho-MET was associated with reduced mortality (p=0.01) likely due to higher expression in early-stage disease. In eight additional ovarian cancer case series, HGF rs5745709 was not associated with mortality (1.0, 0.9–1.1, p=0.87).
Conclusions
We conclude that although HGF signaling is critical to migration, invasion, and apoptosis, it is unlikely that genetic variation plays a major role in ovarian cancer mortality; any minor role is not related to genetically-determined expression.
Impact
Our study demonstrates the utility of multiple data types and multiple datasets in observational studies.