Identification and validation of a prognostic signature of drug resistance and mitochondrial energy metabolism-related differentially expressed genes for breast cancer
Abstract Background Drug resistance constitutes one of the principal causes of poor prognosis in breast cancer patients. Although cancer cells can maintain viability independently of mitochondrial energy metabolism, they remain reliant on mitochondrial functions for the synthesis of new DNA strands....
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BMC
2025-01-01
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| Series: | Journal of Translational Medicine |
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| Online Access: | https://doi.org/10.1186/s12967-025-06080-7 |
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| author | Tiankai Xu Chu Chu Shuyu Xue Tongchao Jiang Ying Wang Wen Xia Huanxin Lin |
| author_facet | Tiankai Xu Chu Chu Shuyu Xue Tongchao Jiang Ying Wang Wen Xia Huanxin Lin |
| author_sort | Tiankai Xu |
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| description | Abstract Background Drug resistance constitutes one of the principal causes of poor prognosis in breast cancer patients. Although cancer cells can maintain viability independently of mitochondrial energy metabolism, they remain reliant on mitochondrial functions for the synthesis of new DNA strands. This dependency underscores a potential link between mitochondrial energy metabolism and drug resistance. Hence, drug resistance and mitochondrial energy metabolism-related differentially expressed genes (DMRDEGs) may emerge as candidates for novel cancer biomarkers. This study endeavors to assess the viability of DMRDEGs as biomarkers or therapeutic targets for breast cancer. Methods We utilized the DRESIS database and MSigDB to identify genes related to drug resistance. Additionally, we sourced genes associated with mitochondrial energy metabolism from GeneCards and extant literature. By merging these genes with differentially expressed genes observed in normal and tumor tissues from the TCGA-BRCA and GEO databases, we successfully identified the DMRDEGs. Employing unsupervised consensus clustering, we divided breast cancer patients into two distinct groups based on the DMRDEGs. Consequently, we identified four hub genes to formulate a prognostic model, applying Cox regression, LASSO regression, and Random Forest methods. Furthermore, we examined immune infiltration and tumor mutation burden of the genes within our model and scrutinized divergences in the immune microenvironment between high- and low-risk groups. Small hairpin RNA and lentiviral plasmids were designed for stable transfection of breast cancer cell lines MDA-MB-231 and HCC1806. By conducting clone formation, scratch test, transwell assays, cell viability assay and measurement of oxygen consumption we initiated a preliminary investigation into mechanistic roles of AIFM1. Results We utilized DMRDEGs to develop a prognostic model that includes four mRNAs for breast cancer. This model combined with various clinical features and critical breast cancer facets, demonstrated remarkable efficacy in predicting patient outcomes. AIFM1 appeared to enhance the proliferation, migration, and invasiveness of breast cancer cell lines MDA-MB-231 and HCC1806. Moreover, by reducing oxygen consumption, it aids in the cancer cells' acquisition of drug resistance. Conclusions DMRDEGs hold promise as diagnostic markers and therapeutic targets for breast cancer. Among the associated mutated genes, ATP7B, FUS, AIFM1, and PPARG could serve as early diagnostic indicators, and notably, AIFM1 may present itself as a promising therapeutic target. |
| format | Article |
| id | doaj-art-902b41d4a52445079474966706e99d42 |
| institution | Kabale University |
| issn | 1479-5876 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Translational Medicine |
| spelling | doaj-art-902b41d4a52445079474966706e99d422025-02-02T12:40:19ZengBMCJournal of Translational Medicine1479-58762025-01-0123112710.1186/s12967-025-06080-7Identification and validation of a prognostic signature of drug resistance and mitochondrial energy metabolism-related differentially expressed genes for breast cancerTiankai Xu0Chu Chu1Shuyu Xue2Tongchao Jiang3Ying Wang4Wen Xia5Huanxin Lin6Department of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer CenterDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer CenterDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer CenterDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer CenterDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer CenterDepartment of Medical Oncology, State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer CenterDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer CenterAbstract Background Drug resistance constitutes one of the principal causes of poor prognosis in breast cancer patients. Although cancer cells can maintain viability independently of mitochondrial energy metabolism, they remain reliant on mitochondrial functions for the synthesis of new DNA strands. This dependency underscores a potential link between mitochondrial energy metabolism and drug resistance. Hence, drug resistance and mitochondrial energy metabolism-related differentially expressed genes (DMRDEGs) may emerge as candidates for novel cancer biomarkers. This study endeavors to assess the viability of DMRDEGs as biomarkers or therapeutic targets for breast cancer. Methods We utilized the DRESIS database and MSigDB to identify genes related to drug resistance. Additionally, we sourced genes associated with mitochondrial energy metabolism from GeneCards and extant literature. By merging these genes with differentially expressed genes observed in normal and tumor tissues from the TCGA-BRCA and GEO databases, we successfully identified the DMRDEGs. Employing unsupervised consensus clustering, we divided breast cancer patients into two distinct groups based on the DMRDEGs. Consequently, we identified four hub genes to formulate a prognostic model, applying Cox regression, LASSO regression, and Random Forest methods. Furthermore, we examined immune infiltration and tumor mutation burden of the genes within our model and scrutinized divergences in the immune microenvironment between high- and low-risk groups. Small hairpin RNA and lentiviral plasmids were designed for stable transfection of breast cancer cell lines MDA-MB-231 and HCC1806. By conducting clone formation, scratch test, transwell assays, cell viability assay and measurement of oxygen consumption we initiated a preliminary investigation into mechanistic roles of AIFM1. Results We utilized DMRDEGs to develop a prognostic model that includes four mRNAs for breast cancer. This model combined with various clinical features and critical breast cancer facets, demonstrated remarkable efficacy in predicting patient outcomes. AIFM1 appeared to enhance the proliferation, migration, and invasiveness of breast cancer cell lines MDA-MB-231 and HCC1806. Moreover, by reducing oxygen consumption, it aids in the cancer cells' acquisition of drug resistance. Conclusions DMRDEGs hold promise as diagnostic markers and therapeutic targets for breast cancer. Among the associated mutated genes, ATP7B, FUS, AIFM1, and PPARG could serve as early diagnostic indicators, and notably, AIFM1 may present itself as a promising therapeutic target.https://doi.org/10.1186/s12967-025-06080-7Breast cancerMitochondrial energy metabolismDrug resistancePrognostic model |
| spellingShingle | Tiankai Xu Chu Chu Shuyu Xue Tongchao Jiang Ying Wang Wen Xia Huanxin Lin Identification and validation of a prognostic signature of drug resistance and mitochondrial energy metabolism-related differentially expressed genes for breast cancer Journal of Translational Medicine Breast cancer Mitochondrial energy metabolism Drug resistance Prognostic model |
| title | Identification and validation of a prognostic signature of drug resistance and mitochondrial energy metabolism-related differentially expressed genes for breast cancer |
| title_full | Identification and validation of a prognostic signature of drug resistance and mitochondrial energy metabolism-related differentially expressed genes for breast cancer |
| title_fullStr | Identification and validation of a prognostic signature of drug resistance and mitochondrial energy metabolism-related differentially expressed genes for breast cancer |
| title_full_unstemmed | Identification and validation of a prognostic signature of drug resistance and mitochondrial energy metabolism-related differentially expressed genes for breast cancer |
| title_short | Identification and validation of a prognostic signature of drug resistance and mitochondrial energy metabolism-related differentially expressed genes for breast cancer |
| title_sort | identification and validation of a prognostic signature of drug resistance and mitochondrial energy metabolism related differentially expressed genes for breast cancer |
| topic | Breast cancer Mitochondrial energy metabolism Drug resistance Prognostic model |
| url | https://doi.org/10.1186/s12967-025-06080-7 |
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