Potential Prognostic Immune Biomarkers for Overall Survival in Ovarian Cancer Through Comprehensive Bioinformatics Study: Two Precision Medical Predictive Tools
2019
Background: More and more evidences proved that tumor immune microenvironment plays an important role in the biological mechanisms of tumorigenesis and progression. The current research aimed at exploring the potential associations of immune genes and tumor immune infiltrating cells with overall survival of ovarian cancer (OC).
Methods: Differentially expression analyses were carried out between normal tissues and tumor tissues. Potential prognostic biomarkers were recognized by univariate Cox regression. Immune regulatory network was constructed on prognostic immune genes and their highly related transcription factors.
Findings: Fourteen immune genes (PSMB9, FOXJ1, IFT57, MAL,ANXA4, CTSH, SCRN1, MIF, LTBR, CTSD, KIFAP3, PSMB8, HSPA5 and LTN1) were recognized as independent risk factors through multivariate Cox analyses. A prognostic nomogram was developed by using these prognostic genes. Concordance indexes were 0.760, 0.733, and 0.765 for 1-, 3- and 5- year overall survival. This prognostic model could identify high risk patients with poor overall survival.
Interpretation: The current study recognized fourteen prognostic immune biomarkers for ovarian cancer and revealed potential regulatory associations among immune genes and transcription factors. The current research further developed and validated two precision medical predictive tools for ovarian cancer, which are available at https://zhangzhiqiao8.shinyapps.ioSmart_Cancer_Survival_Predictive_System_17_OC_F1001/ and https://zhangzhiqiao8.shinyapps.ioGene_Survival_Subgroup_Analysis_17_OC_ F1001/. These two precision medical predictive tools were helpful to improve individualized treatment decision-making.
Funding Statement: The current research was funded by Medical Science and Technology Foundation of Guangdong Province (A2016450 and B2018237).
Declaration of Interests: The authors have no conflict of interest to declare.
Ethics Approval Statement: The studies in TCGA database and GEO database have received ethical approval from ethics committees of their respective research institutes. These studies obtained informed consent from patients before admission. The current study is a second study based on public datasets from TCGA database and GEO database. Details of all patients in public datasets have been anonymously processed and therefore the current research does not involve patients' privacy information. This study was performed according to public database policy and declaration of Helsinki. Ethical approval and informed consent were not applicable.
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