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ORIGINAL RESEARCH article

Front. Immunol.
Sec. Cancer Immunity and Immunotherapy
Volume 15 - 2024 | doi: 10.3389/fimmu.2024.1458264
This article is part of the Research Topic Investigating tumor immunotherapy responses in lung cancer using deep learning View all 4 articles

Explore the expression of mitochondria-related genes to construct prognostic risk model for ovarian cancer and validate it, so as to provide optimized treatment for ovarian cancer

Provisionally accepted
Yun Y. Zheng Yun Y. Zheng 1,2Wang Guihu Wang Guihu 1,3An Jiang An Jiang 1,3*
  • 1 Department of Hepatobiliary pancreas surgery and liver transplantation, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, 710004, China., xian, China
  • 2 Department of Obstetrics and Gynecology, The First Afliated Hospital of AFM (Air Force Medical University), Xi’an 710032, Shaanxi, China., Xian, China
  • 3 National and Local Joint Engineering Research Center of Biodiagnostics and Biotherapy, Second Affiliated Hospital, Xi’an Jiaotong University, Xi’an, 710004, China., xian, China

The final, formatted version of the article will be published soon.

    The use of gene development data from public database has become a new starting point to explore mitochondrial related gene expression and construct a prognostic prediction model of ovarian cancer.Methods Data were obtained from the TCGA and ICGC databases, and the intersection with mitochondrial genes was used to obtain the differentially expressed genes. q-PCR, Cox proportional risk regression, minimal absolute contraction and selection operator regression analysis were performed to construct the prognostic risk model, and ROC curve was used to evaluate the model for centralized verification.The association between risk scores and clinical features, tumor mutation load, immune cell infiltration, macrophage activation analysis, immunotherapy, and chemosensitivity was further evaluated.A prognostic risk score model for ovarian cancer patients was constructed based on 12 differentially expressed genes. The score was highly correlated with ovarian cancer macrophage infiltration and was a good predictor of the response to immunotherapy. M1 and M2 macrophages in the ovarian tissue in the OV group were significantly activated, providing a reference for the study of the polarity change of tumor-related macrophages for the prognosis and treatment of ovarian cancer. In terms of drug sensitivity, the high-risk group was more sensitive to vinblastine, Acetalax, VX-11e, and PD-0325901, while the low-risk group was more sensitive to Sabutoclax, SB-505124, cisplatin, and erlotinib.The prognostic risk model of ovarian cancer associated to mitochondrial genes built on the basis of public database better evaluated the prognosis of ovarian cancer patients and guided individual treatment.

    Keywords: Mitochondria, Differentially expressed genes, Prediction model, ovarian cancer, Immunotherapy

    Received: 02 Jul 2024; Accepted: 17 Sep 2024.

    Copyright: © 2024 Zheng, Guihu and Jiang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: An Jiang, Department of Hepatobiliary pancreas surgery and liver transplantation, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, 710004, China., xian, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.