A novel signature derived from immunoregulatory and hypoxia genes predicts prognosis in liver and five other cancers

Abstract

Background: Despite much progress in cancer research, its incidence and mortality continue to rise. A robust biomarker that would predict tumor behavior is highly desirable and could improve patient treatment and prognosis. Methods: In a retrospective bioinformatics analysis involving patients with liver cancer (n = 839), we developed a prognostic signature consisting of 45 genes associated with tumor-infiltrating lymphocytes and cellular responses to hypoxia. From this gene set, we were able to identify a second prognostic signature comprised of 8 genes. Its performance was further validated in five other cancers: head and neck (n = 520), renal papillary cell (n = 290), lung (n = 515), pancreas (n = 178) and endometrial (n = 370). Results: The 45-gene signature predicted overall survival in three liver cancer cohorts: hazard ratio (HR) = 1.82, P = 0.006; HR = 1.84, P = 0.008 and HR = 2.67, P = 0.003. Additionally, the reduced 8-gene signature was sufficient and effective in predicting survival in liver and five other cancers: liver (HR = 2.36, P = 0.0003; HR = 2.43, P = 0.0002 and HR = 3.45, P = 0.0007), head and neck (HR = 1.64, P = 0.004), renal papillary cell (HR = 2.31, P = 0.04), lung (HR = 1.45, P = 0.03), pancreas (HR = 1.96, P = 0.006) and endometrial (HR = 2.33, P = 0.003). Receiver operating characteristic analyses demonstrated both signatures superior performance over current tumor staging parameters. Multivariate Cox regression analyses revealed that both 45-gene and 8-gene signatures were independent of other clinicopathological features in these cancers. Combining the gene signatures with somatic mutation profiles increased their prognostic ability. Conclusions: This study, to our knowledge, is the first to identify a gene signature uniting both tumor hypoxia and lymphocytic infiltration as a prognostic determinant in six cancer types (n = 2712). The 8-gene signature can be used for patient risk stratification by incorporating hypoxia information to aid clinical decision making.