{"title":"Characteristics of Oxidative Phosphorylation-Related Subtypes and Construction of a Prognostic Signature in Ovarian Cancer","authors":"Jiaojiao Lu, Shuai Zhen, Xu Li","doi":"10.2174/0115665232323373240905104033","DOIUrl":null,"url":null,"abstract":"Background: Ovarian cancer is associated with a high mortality rate. Oxidative Phosphorylation (OXPHOS) is an active metabolic pathway in cancer; nevertheless, its role in ovarian cancer continues to be ambiguous. Therefore, the objective of this study was to identify the prognostic value of OXPHOS-related genes and the immune landscape in ovarian cancer. Methods: We obtained public ovarian cancer-related datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and recognized OXPHOS-related genes from the GeneCards database and literature. Cox regression analyses were conducted to identify prognostic OXPHOS-related genes and develop a prognostic nomogram based on the OXPHOS score and clinicopathological features of patients. Functional enrichment analyses were employed to identify related processes. Results: A 12-gene signature was identified to classify the ovarian cancer patients into high- and low-risk groups. The Immunophenoscore (IPS) was higher in the OXPHOS score-high group than in the OXPHOS score-low group, suggesting a better response to immune checkpoint inhibitors. Functional enrichment analyses unveiled that OXPHOS-related genes were considerably abundant in a series of immune processes. The calibration curves of the constructed prognostic nomograms at 1, 2, and 3 years exhibited strong concordance between the anticipated and observed survival probabilities of ovarian cancer patients. Conclusion: We have constructed a prognostic model containing 12 OXPHOS-related genes and demonstrated its strong predictive value in ovarian cancer patients. OXPHOS has been found to be closely linked to immune infiltration and the reaction to immunotherapy, which may contribute to improving individualized treatment and prognostic evaluation in ovarian cancer.","PeriodicalId":10798,"journal":{"name":"Current gene therapy","volume":"19 1","pages":""},"PeriodicalIF":3.8000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current gene therapy","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2174/0115665232323373240905104033","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Ovarian cancer is associated with a high mortality rate. Oxidative Phosphorylation (OXPHOS) is an active metabolic pathway in cancer; nevertheless, its role in ovarian cancer continues to be ambiguous. Therefore, the objective of this study was to identify the prognostic value of OXPHOS-related genes and the immune landscape in ovarian cancer. Methods: We obtained public ovarian cancer-related datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and recognized OXPHOS-related genes from the GeneCards database and literature. Cox regression analyses were conducted to identify prognostic OXPHOS-related genes and develop a prognostic nomogram based on the OXPHOS score and clinicopathological features of patients. Functional enrichment analyses were employed to identify related processes. Results: A 12-gene signature was identified to classify the ovarian cancer patients into high- and low-risk groups. The Immunophenoscore (IPS) was higher in the OXPHOS score-high group than in the OXPHOS score-low group, suggesting a better response to immune checkpoint inhibitors. Functional enrichment analyses unveiled that OXPHOS-related genes were considerably abundant in a series of immune processes. The calibration curves of the constructed prognostic nomograms at 1, 2, and 3 years exhibited strong concordance between the anticipated and observed survival probabilities of ovarian cancer patients. Conclusion: We have constructed a prognostic model containing 12 OXPHOS-related genes and demonstrated its strong predictive value in ovarian cancer patients. OXPHOS has been found to be closely linked to immune infiltration and the reaction to immunotherapy, which may contribute to improving individualized treatment and prognostic evaluation in ovarian cancer.
期刊介绍:
Current Gene Therapy is a bi-monthly peer-reviewed journal aimed at academic and industrial scientists with an interest in major topics concerning basic research and clinical applications of gene and cell therapy of diseases. Cell therapy manuscripts can also include application in diseases when cells have been genetically modified. Current Gene Therapy publishes full-length/mini reviews and original research on the latest developments in gene transfer and gene expression analysis, vector development, cellular genetic engineering, animal models and human clinical applications of gene and cell therapy for the treatment of diseases.
Current Gene Therapy publishes reviews and original research containing experimental data on gene and cell therapy. The journal also includes manuscripts on technological advances, ethical and regulatory considerations of gene and cell therapy. Reviews should provide the reader with a comprehensive assessment of any area of experimental biology applied to molecular medicine that is not only of significance within a particular field of gene therapy and cell therapy but also of interest to investigators in other fields. Authors are encouraged to provide their own assessment and vision for future advances. Reviews are also welcome on late breaking discoveries on which substantial literature has not yet been amassed. Such reviews provide a forum for sharply focused topics of recent experimental investigations in gene therapy primarily to make these results accessible to both clinical and basic researchers. Manuscripts containing experimental data should be original data, not previously published.