Construction of mitochondrial signature (MS) for the prognosis of ovarian cancer
Abstract Background Ovarian cancer (OV) continues to be the most lethal type of gynecological cancer with a poor prognosis. During tumorigenesis and cancer advancement, mitochondria are key players in energy metabolism. This study focuses on exploring the mitochondria-related genes for the prognosis...
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| Format: | Article |
| Language: | English |
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Springer
2025-07-01
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| Series: | Discover Oncology |
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| Online Access: | https://doi.org/10.1007/s12672-025-02892-7 |
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| author | Miao Ao You Wu Kunyu Wang Haixia Luo Wei Mao Anqi Zhao Xiaomeng Su Yan Song Bin Li |
| author_facet | Miao Ao You Wu Kunyu Wang Haixia Luo Wei Mao Anqi Zhao Xiaomeng Su Yan Song Bin Li |
| author_sort | Miao Ao |
| collection | DOAJ |
| description | Abstract Background Ovarian cancer (OV) continues to be the most lethal type of gynecological cancer with a poor prognosis. During tumorigenesis and cancer advancement, mitochondria are key players in energy metabolism. This study focuses on exploring the mitochondria-related genes for the prognosis of OV. Methods RNA expression profiles and single-cell data were acquired from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus databases for screening and validating mitochondria-related differentially expressed genes (DEGs). After univariate Cox analysis, prognostic genes were carried out for modeling mitochondria signature (MS) based on 101 combinations of 10 machine learning algorithms. Functional enrichment analysis was performed on this prognostic gene set. Immune infiltration analysis was performed between MS groups. Validation for the prognostic model gene OAT was performed to identify the prognostic significance, combined with in vitro experiments to explore its expressions in OV cells. qRT-PCR assay was performed to examine the expression of OAT in human ovarian cancer cell samples and normal ovarian epithelial cells. Results A total of 21 prognostic mitochondria-related DEGs were identified for reliably constructing the model MS with excellent prognostic performance in OV. GO and KEGG analysis confirmed these genes were enriched in the generation of precursor metabolites and energy. It illustrated more lymphocyte infiltration in the high MS group than low MS group. OAT served as a novel biomarker for OV patients, showing poor survival in OV patients with high expression of OAT. qPCR assays confirmed its significantly high expression in human ovary cancer cell lines. Conclusions The MS offers tailored risk evaluations and immunotherapy treatments for each OV patient. MS model gene OAT has been recognized as a new oncogene for OV linked to immune escape. |
| format | Article |
| id | doaj-art-7a4bbcca7d3d4e6f85d9db0766903a05 |
| institution | Kabale University |
| issn | 2730-6011 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Oncology |
| spelling | doaj-art-7a4bbcca7d3d4e6f85d9db0766903a052025-08-20T03:43:16ZengSpringerDiscover Oncology2730-60112025-07-0116111510.1007/s12672-025-02892-7Construction of mitochondrial signature (MS) for the prognosis of ovarian cancerMiao Ao0You Wu1Kunyu Wang2Haixia Luo3Wei Mao4Anqi Zhao5Xiaomeng Su6Yan Song7Bin Li8A Department of Gynecology Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeA Department of Gynecology Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeA Department of Gynecology Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeA Department of Gynecology Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeA Department of Gynecology Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeA Department of Gynecology Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeObstetrics and Gynecology Department, Beijing Huairou Maternal and Child Health Care HospitalA Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeA Department of Gynecology Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeAbstract Background Ovarian cancer (OV) continues to be the most lethal type of gynecological cancer with a poor prognosis. During tumorigenesis and cancer advancement, mitochondria are key players in energy metabolism. This study focuses on exploring the mitochondria-related genes for the prognosis of OV. Methods RNA expression profiles and single-cell data were acquired from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus databases for screening and validating mitochondria-related differentially expressed genes (DEGs). After univariate Cox analysis, prognostic genes were carried out for modeling mitochondria signature (MS) based on 101 combinations of 10 machine learning algorithms. Functional enrichment analysis was performed on this prognostic gene set. Immune infiltration analysis was performed between MS groups. Validation for the prognostic model gene OAT was performed to identify the prognostic significance, combined with in vitro experiments to explore its expressions in OV cells. qRT-PCR assay was performed to examine the expression of OAT in human ovarian cancer cell samples and normal ovarian epithelial cells. Results A total of 21 prognostic mitochondria-related DEGs were identified for reliably constructing the model MS with excellent prognostic performance in OV. GO and KEGG analysis confirmed these genes were enriched in the generation of precursor metabolites and energy. It illustrated more lymphocyte infiltration in the high MS group than low MS group. OAT served as a novel biomarker for OV patients, showing poor survival in OV patients with high expression of OAT. qPCR assays confirmed its significantly high expression in human ovary cancer cell lines. Conclusions The MS offers tailored risk evaluations and immunotherapy treatments for each OV patient. MS model gene OAT has been recognized as a new oncogene for OV linked to immune escape.https://doi.org/10.1007/s12672-025-02892-7Ovarian cancerTumor microenvironmentImmunotherapyBiomarker |
| spellingShingle | Miao Ao You Wu Kunyu Wang Haixia Luo Wei Mao Anqi Zhao Xiaomeng Su Yan Song Bin Li Construction of mitochondrial signature (MS) for the prognosis of ovarian cancer Discover Oncology Ovarian cancer Tumor microenvironment Immunotherapy Biomarker |
| title | Construction of mitochondrial signature (MS) for the prognosis of ovarian cancer |
| title_full | Construction of mitochondrial signature (MS) for the prognosis of ovarian cancer |
| title_fullStr | Construction of mitochondrial signature (MS) for the prognosis of ovarian cancer |
| title_full_unstemmed | Construction of mitochondrial signature (MS) for the prognosis of ovarian cancer |
| title_short | Construction of mitochondrial signature (MS) for the prognosis of ovarian cancer |
| title_sort | construction of mitochondrial signature ms for the prognosis of ovarian cancer |
| topic | Ovarian cancer Tumor microenvironment Immunotherapy Biomarker |
| url | https://doi.org/10.1007/s12672-025-02892-7 |
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