AUTHOR=Wang Yue , Li Bao Xuan , Li Xiang 

TITLE=Identification and Validation of Angiogenesis-Related Gene Expression for Predicting Prognosis in Patients With Ovarian Cancer

JOURNAL=Frontiers in Oncology

VOLUME=Volume 11 - 2021

YEAR=2022

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2021.783666

DOI=10.3389/fonc.2021.783666

ISSN=2234-943X

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 1960 differentially expressed ARGs were screened and functionally annotated through GO terms and 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 TCGA-training dataset, the survival analysis showed that the high-risk group was lower than the low-risk group (p < 0.0001). The ICGC database were used for validation and the 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 score were correlated strongly with tumor cell mutations and type of immune infiltration. Furthermore, homologous recombination defect (HRD), NtAIscore, LOH score, LSTm score, stemness index (mRNAsi), 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.