Abstract
BackgroundVarious components of the immune system play a critical role in the prognosis and treatment response in ovarian cancer (OC). Immunotherapy has been recognized as a hallmark of cancer but the effect is contradictional. Reliable immune gene-based prognostic biomarkers or regulatory factors are necessary to be systematically explored to develop an individualized prediction signature.MethodsThis study systematically explored the gene expression profiles in patients with ovarian cancer from RNA-seq data set for The Cancer Genome Atlas (TCGA). Differentially expressed immune genes and transcription factors (TFs) were identified using the collected immune genes from ImmPort dataset and TFs from Cistoma database. Survival associated immune genes and TFs were identified in terms of overall survival. The prognostic signature was developed based on survival associated immune genes with LASSO (Least absolute shrinkage and selection operator) Cox regression analysis. Further, we performed network analysis to uncover the potential regulators of immune-related genes with the help of computational biology.ResultsThe prognostic signature, a weighted combination of the 21 immune-related genes, performed moderately in survival prediction with AUC was 0.746, 0.735, and 0.749 for 1, 3, and 5 year overall survival, respectively. Network analysis uncovered the regulatory role of TFs in immune genes. Intriguingly, the prognostic signature reflected the immune cells landscape and infiltration of some immune cell subtypes.ConclusionsWe first constructed a signature with 21 immune genes of clinical significance, which showed promising predictive value in the surveillance, and prognosis of OC patients.
Highlights
Ovarian cancer (OC) causes the most deaths among gynecological cancers, with more than 22,000 new cases and 14,000 deaths each year in the United States [1]
The current study aimed to identify the immune genes correlated with the clinical prognosis in ovarian patients, and to develop and validate an individualized prognostic signature based on immune-related genes
The prognostic signature is established with 21 immunebased genes A total of 376 ovarian cancer cases and 88 normal ovarian tissues were included in the eanalysis
Summary
Ovarian cancer (OC) causes the most deaths among gynecological cancers, with more than 22,000 new cases and 14,000 deaths each year in the United States [1]. Immunotherapy has shown to be correlated with improved clinical outcome. Finding the neo-antigens or effective biomarkers, and identification of transcriptional regulators in the immune system and the regulatory networks between immune genes and transcriptional factors in the microenvironment is critical to improve the clinical outcome. The current study aimed to identify the immune genes correlated with the clinical prognosis in ovarian patients, and to develop and validate an individualized prognostic signature based on immune-related genes. A prognostic signature based on 21 immune genes was identified, and it is closely related with aggressive clinical outcomes of OC. Various components of the immune system play a critical role in the prognosis and treatment response in ovarian cancer (OC). Reliable immune gene-based prognostic biomarkers or regulatory factors are necessary to be systematically explored to develop an individualized prediction signature
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