Integrative Analysis of Novel Ferroptosis-Related Genes Signatures as Prognostic Biomarkers in Ovarian Cancer

Ferroptosis, an iron-dependent form of cell death, has been implicated in the pathogenesis of several types of cancer. Nevertheless, the exact correlation between ferroptosis-related gene mutations and their influence on ovarian cancer (OV) diagnosis and treatment strategies remains to be fully elucidated. It is crucial to identify the ferroptosis-related gene signature in OV and elucidate the impact of these mutations and their expression on the diagnosis and treatment of OV.

In this study, we collected data from the TCGA and GEO databases. We utilized various tools and packages for data analysis, including the cBio Cancer Genomics Portal, Tumor Immune Estimation Resource (TIMER), GSVA package, and WGCNA R packages.

Our results showed that ferroptosis subtypes 1 (FS1) and 2 (FS2) exhibited different levels of expression and tumor mutation burden (TMB). FS2 had a higher TMB level and survival rate compared to FS1. Furthermore, our analysis identified three ferroptosis-related genes, including IFNG, KEAP1, and PHKG2, as key biomarkers in prognosis prediction and potential targets for OV cancer therapy. The elevated expression levels of IFNG, KEAP1, and PHKG2 were found to be correlated with a good prognosis. These three genes showed a positive correlation with TMB in OV. We also observed that high TMB was more robustly associated with immune response-related gene expression, including CD28, CD40L, and type I IFN family members. Moreover, high TMB was associated with increased T cell infiltration and exhibited a distinct gene signature, which highlights the potential of IFNG, KEAP1, and PHKG2 as predictive markers for T cell infiltration and the tumor microenvironment status in OV. A significant correlation exists between the expression levels of KEAP1 and PHKG2 and TMB in OV cell lines.

In conclusion, our study identified KEAP1, IFNG, and PHKG2 as potential prognostic biomarkers and therapeutic targets in OV. Their expression and mutation burden were correlated with a good prognosis. The association between ferroptosis subtypes, TMB, and survival rates further supports the relevance of these biomarkers. Additionally, the positive correlation between KEAP1, IFNG, and PHKG2 with TMB and immune response-related gene expression highlights their potential as predictive markers for immunotherapy efficacy in OV. The observed association of high TMB with increased T cell infiltration and distinct gene signature further emphasizes its role as a potential biomarker for immune response. Further research is warranted to validate these findings and explore their clinical implications in OV treatment.