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Assessment of hepatocyte growth factor in ovarian cancer mortality

Ellen L Goode et al. Cancer Epidemiol Biomarkers Prev. 2011 Aug.

Abstract

Background: Invasive ovarian cancer is a significant cause of gynecologic cancer mortality.

Methods: We examined whether this mortality was associated with inherited variation in approximately 170 candidate genes/regions [993 single-nucleotide polymorphisms (SNPs)] in a multistage 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 microarrays (TMA, 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 (r(2) = 0.96 with rs1800793): TCGA HR = 2.4, CI = 1.4-4.1, P = 2.2 × 10(-3); Mayo Clinic + TCGA HR = 1.6, CI = 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 (C-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 (HR = 1.0, CI = 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 HGF genetic variation plays a major role in ovarian cancer mortality. Furthermore, any minor role is not related to genetically-determined expression.

Impact: Our study shows the utility of multiple data types and multiple data sets in observational studies.

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Figures

Figure 1
Figure 1. HGF, MET, and phospho-MET staining in epithelial ovarian cancer TMAs
Immunohistochemical staining of a tissue microarray of epithelial ovarian cancer samples. Representative images are shown of weak (panels A, C, and E) and strong (B, D, and F) staining. Panels A and B show cores stained with antibodies recognizing HGF; Panels C and D represent MET staining, and Panels E and F represent phospho-MET staining.
Figure 2
Figure 2. Kaplan-Meier ovarian cancer survival curves by HGF rs5745709 genotype, initial Mayo Clinic and TCGA analysis
Genotype-specific Kaplan-Meier survival curves based on (a) MAY1, (b) TCGA1, and (c) MAY1+TCGA1. Numbers superimposed on curves represent genotype-specific cumulative number of deaths/number remaining at risk
Figure 3
Figure 3. rs5745709 and ovarian cancer mortality, all studies
Hazard ratios and 95% confidence intervals by study site, study phase (initial vs. replication) and overall, from Cox proportional hazards regression analysis. Site-specific analyses adjust for age at diagnosis, tumor stage, and tumor grade. Combined initial, replication and overall analyses adjust additionally for study site.

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