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Molecular Features, Prognostic Value, and Cancer Immune Interactions of Angiogenesis-Related Genes in Ovarian Cancer

  • Gynecologic Oncology: Original Paper
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Abstract

Angiogenesis is crucial to tumor growth and metastasis; it plays a key role in various cancers development and progression. However, the potential effects of angiogenesis-related genes (ARGs) in ovarian cancer (OC) remain to be further investigated. We discussed the characteristics changes of ARGs in 784 OC samples from genomic and transcriptional levels, as well as their expression patterns based on four distinct datasets. First, 784 OC patients were divided into three molecular subtypes, and the findings indicated that ARG changes were correlated with clinicopathological parameters, prognosis, and immune cell-infiltrating tumor microenvironment (TME). OC patients were subsequently divided into two gene subtypes depending on differentially expressed genes (DEGs) of the abovementioned molecular subtypes. We also established an ARGs-related score (ARGs score) model for evaluating overall survival (OS) and determining the immunological landscape of OC patients, therefore predicting patients’ prognosis and therapeutic responses. A lower ARGs’ score accompanied by a high mutation frequency implies a higher probability of survival. Furthermore, the ARG score was correlated with the cancer stem cell (CSC) index and chemotherapeutic sensitivity. The significant involvement of ARGs in the tumor-immune-stromal microenvironment, clinicopathological characteristics, and prognosis were established in our systematic investigation of ARGs for OC patients. These discoveries might help us to better understand the role of ARGs in OC, as well as give new insight for predicting the prognosis and providing promising immunotherapy.

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Data Availability

Publicly available datasets were analyzed in this study; these can be found in the Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/) and UCSC Xena (http://xena.ucsc.edu/). All procedure in this study followed corresponding guidelines and relative policies of above public database. The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Code Availability

The R markdown code used to conduct these analyses.

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Acknowledgements

We sincerely thank the R package developers and the maintainers of The Cancer Genome Atlas (TCGA) project and the Gene Expression Omnibus (GEO).

Funding

This work was supported by the National Natural Science Foundation of China (No. 81802605), Gynecological tumor special research Fund of Bei**g Kanghua Traditional Chinese and Western Medicine Development Foundation (No. KH-2021-LLZX-044), Tian** Key Medical Discipline (Specialty) Construction Project, and Natural Science Foundation of Tian** municipality (No. 21JCQNJC00230).

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Authors and Affiliations

  1. Clinical School of Obstetrics and Gynecology Center, Tian** Medical University, No. 22 Meteorological Observatory Road, He** District, Tian**, 300070, China

    Yurou Ji & Qi Ge

  2. Tian** Medical University, No. 22 Meteorological Observatory Road, He** District, Tian**, 300070, China

    Yurou Ji & Qi Ge

  3. Research Institute of Obstetrics and Gynecology, Tian** Central Hospital of Gynecology Obstetrics, Tian**, 300100, China

    Wenwen Zhang & Pengpeng Qu

  4. Tian** Central Hospital of Gynecology Obstetrics, Nankai District, No. 156 Nankai San Ma Road, Tian**, 300100, China

    Wenwen Zhang & Pengpeng Qu

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  1. Yurou Ji
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Yurou Ji and Qi Ge contributed to the conception, data collection and analysis of the study. All authors drafted the manuscript. Wenwen Zhang and Pengpeng Qu revised the manuscript for important intellectual content. All authors read and approved the final version of the manuscript.

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Correspondence to Wenwen Zhang or Pengpeng Qu.

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All data in this article comes from the public databases including the Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/) and UCSC Xena (http://xena.ucsc.edu/) and does not involve animal or human subjects in any way, so the IRB Approval is not available.

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Ji, Y., Ge, Q., Zhang, W. et al. Molecular Features, Prognostic Value, and Cancer Immune Interactions of Angiogenesis-Related Genes in Ovarian Cancer. Reprod. Sci. 30, 1637–1650 (2023). https://doi.org/10.1007/s43032-022-01123-6

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