Multi-omics analysis of tumor mutational burden combined with prognostic assessment in epithelial ovarian cancer based on TCGA database

Int J Med Sci. 2020 Oct 23;17(18):3200-3213. doi: 10.7150/ijms.50491. eCollection 2020.

Abstract

Background: Tumor mutation burden (TMB) is considered as a novel biomarker of response to immunotherapy and correlated with survival outcomes in various malignancies. Here, TMB-related genes (TRGs) expression signatures were constructed to investigate the association between TMB and prognosis in epithelial ovarian cancer (EOC), and the potential mechanism in immunoregulation was also explored. Methods: Based on somatic mutation data of 436 EOC samples from The Cancer Genome Atlas database, we examined the relationship between TMB level and overall survival (OS), as well as disease-free survival (DFS). Next, the TRGs signatures were constructed and validated. Differential abundance of immune cell infiltration, expression levels of immunomodulators and functional enrichment in high- and low-risk groups were also analyzed. Results: Higher TMB level revealed better OS and DFS, and correlated with earlier clinical stages in EOCs (P = 2.796e-04). The OS-related prognostic model constructed based on seven TRGs (B3GALT1, LIN7B, ANGPT2, D2HGDH, TAF13, PFDN4 and DNAJC19) significantly stratified EOC patients into high- and low-risk groups (P < 0.001). The AUC values of the seven-gene prognostic signature at 1 year, 3 years, and 5 years were 0.703, 0.758 and 0.777. While the DFS-related prognostic model was constructed based on the 4 TRGs (LPIN3, PXYLP1, IGSF23 and B3GALT1), with AUCs of 0.617, 0.756, and 0.731, respectively. Functional analysis indicated that immune-related pathways were enriched in low-risk groups. When considering the infiltration patterns of immune cells, we found higher proportions of follicular helper T (Tfh) cell and M1 macrophage, while lower infiltration of M0 macrophage in low-risk groups (P < 0.05). Accordingly, TMB levels of low-risk patients were significantly higher both in OS and DFS model (P < 0.01). Conclusions: Our TRGs-based models are reliable predictive tools for OS and DFS. High TMB may confer with an immunogenic microenvironment and predict favorable outcomes in EOCs.

Keywords: epithelial ovarian cancer; immune infiltrates; prognostic signature; tumor mutational burden.

MeSH terms

  • Biomarkers, Tumor / genetics*
  • Carcinoma, Ovarian Epithelial / genetics*
  • Carcinoma, Ovarian Epithelial / immunology
  • Carcinoma, Ovarian Epithelial / mortality
  • Carcinoma, Ovarian Epithelial / therapy
  • DNA Mutational Analysis
  • Datasets as Topic
  • Disease-Free Survival
  • Female
  • Gene Expression Profiling
  • Gene Expression Regulation, Neoplastic / immunology
  • Humans
  • Middle Aged
  • Mutation
  • Neoplasm Recurrence, Local / epidemiology*
  • Neoplasm Recurrence, Local / genetics
  • Ovarian Neoplasms / genetics*
  • Ovarian Neoplasms / immunology
  • Ovarian Neoplasms / mortality
  • Ovarian Neoplasms / therapy
  • Prognosis
  • ROC Curve
  • Risk Assessment / methods
  • Time Factors
  • Tumor Microenvironment / genetics
  • Tumor Microenvironment / immunology*

Substances

  • Biomarkers, Tumor