Abstract
Ovarian cancer (OC) is a highly heterogeneous disease with different cellular origins reported; thus, precise prognostic strategies and effective new therapies are urgently needed for patients with OC. A growing number of studies have shown that most malignancies have intensive angiogenesis and rapid growth. Therefore, angiogenesis plays an important role in the development of tumor metastasis. However, the prognostic value of angiogenesis-related genes (ARGs) in OC remains to be further elucidated. In this study, the expression data and corresponding clinical data from patients with OC and normal control samples were downloaded with UCSC XENA. A total of 1,960 differentially expressed ARGs were screened and functionally annotated through Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Univariate Cox regression analysis was performed to identify ARGs associated with prognosis. New ARGs signatures (including ESM1, CXCL13, TPCN2, PTPRD, FOXO1, and ELK3) were constructed for the prediction of overall survival (OS) in OC based on the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis. Patients were divided based on their median risk score. In the The Cancer Genome Atlas (TCGA) training dataset, the survival analysis showed that overall survival was lower in the high-risk group than that in the low-risk group (p < 0.0001). The International Cancer Genome Consortium (ICGC) database was used for validation, and the receiver operating characteristic (ROC) curves showed good performance. Univariate and multivariate Cox analyses were conducted to identify independent predictors of OS. The nomogram, including the risk score, age, stage, grade, and position, can not only show good predictive ability but also can explore the correlation analysis based on ARGs for immunogenicity, immune components, and immune phenotypes with risk score. Risk scores were correlated strongly with the type of immune infiltration. Furthermore, homologous recombination defect (HRD), NtAIscore, LOH score, LSTm score, stemness index (mRNAsi), and stromal cells were significantly correlated with risk score. The present study suggests that the novel signature constructed from six ARGs may serve as effective prognostic biomarkers for OC and contribute to clinical decision making and personalized prognostic monitoring of OC.
Highlights
Ovarian cancer (OC) is a global problem, ranking eighth in mortality and morbidity among women
Angiogenesis is a complex process triggered by many genes, and many reports have shown that Angiogenesis factors (AFs) are the potential prognostic gene is associated with OC
The prognostic model was significantly better than the widely used clinical staging and Federation of Gynecology and Obstetrics (FIGO) staging, and its development could improve the management of patients with OC
Summary
Ovarian cancer (OC) is a global problem, ranking eighth in mortality and morbidity among women. Due to its insidious clinical presentation and no effective screening method in the early stage, most cases (almost 75%) are diagnosed at its late stage, resulting in a poor 5-year survival rate [2]. The current standard front-line treatment, including cytoreductive surgery and a combination chemotherapy, such as platinum and paclitaxel, has been performed on patients with OC, with a 5year survival rate of OC with stage III–IV
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