A novel mitochondrial-related risk model for predicting prognosis and immune checkpoint blockade therapy response in uterine corpus endometrial carcinoma
Abstract Uterine Corpus Endometrial Carcinoma (UCEC) represents a common malignant neoplasm in women, with its prognosis being intricately associated with available therapeutic interventions. In the past few decades, there has been a burgeoning interest in the role of mitochondria within the context...
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Nature Portfolio
2025-01-01
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| Online Access: | https://doi.org/10.1038/s41598-025-85537-7 |
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| author | Ru-Gen Liao Jin-Hong Wang Fan Zhang Yu-Tong Fang Li Zhou Yong-Qu Zhang |
| author_facet | Ru-Gen Liao Jin-Hong Wang Fan Zhang Yu-Tong Fang Li Zhou Yong-Qu Zhang |
| author_sort | Ru-Gen Liao |
| collection | DOAJ |
| description | Abstract Uterine Corpus Endometrial Carcinoma (UCEC) represents a common malignant neoplasm in women, with its prognosis being intricately associated with available therapeutic interventions. In the past few decades, there has been a burgeoning interest in the role of mitochondria within the context of UCEC. Nevertheless, the development and application of prognostic models predicated on mitochondrial-related genes (MRGs) in UCEC remains in the exploratory stages. This study utilized RNA sequencing data and clinical information from the TCGA database to identify differentially expressed MRGs (DEMRGs) between UCEC and normal groups that are associated with overall survival (OS). Patients were randomly assigned to training and testing cohorts in a 1:1 ratio. In the training cohort, a risk model based on DEMRGs was developed using Lasso Cox regression analysis. Subsequently, patients in both cohorts were stratified into high-risk and low-risk groups based on their median risk scores. The prognostic performance of the model was validated through Kaplan-Meier survival analysis, ROC curves, and nomograms. Additionally, further analyses including functional enrichment, immune landscape assessment, prediction of response to ICB therapy, mutation profiling, and drug sensitivity analysis elucidated biological distinctions between the identified risk groups. We established a risk model incorporating eight MRGs. Patients classified within he high-risk group exhibited significantly poorer prognoses relative to those in the low-risk group. Functional enrichment analysis identified substantial differences in biological processes and signaling pathways between the high-risk and low-risk cohorts. Immune landscape analysis showed that patients with elevated risk scores exhibited significant immunosuppressive and immune evasion mechanisms. Conversely, low-risk patients exhibited higher expression of human leukocyte antigen (HLA) family members and immune checkpoint genes (ICGs) compared to their high-risk counterparts.Consequently, low-risk patients showed greater responsiveness to immunotherapy and potential small molecule drugs, whereas high-risk patients were more susceptible to chemotherapy. The mitochondrial-related risk model formulated in this study demonstrates efficacy in predicting both prognosis and response to immunotherapy in patients with UCEC, thereby providing a scientific basis for personalized treatment strategies. Future research endeavors should focus on further validating the clinical utility of this model and investigate the specific mechanisms of the identified MRGs in UCEC. |
| format | Article |
| id | doaj-art-3ce1a7d83b3e4ef489a12386b3f8f0fb |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-3ce1a7d83b3e4ef489a12386b3f8f0fb2025-01-12T12:20:34ZengNature PortfolioScientific Reports2045-23222025-01-0115111810.1038/s41598-025-85537-7A novel mitochondrial-related risk model for predicting prognosis and immune checkpoint blockade therapy response in uterine corpus endometrial carcinomaRu-Gen Liao0Jin-Hong Wang1Fan Zhang2Yu-Tong Fang3Li Zhou4Yong-Qu Zhang5Department of Obstetrics and Gynecology, The Second People’s Hospital of ShantouDepartment of Ultrasound, The First Affiliated Hospital of Shantou University Medical CollegeOncology Research Laboratory, Cancer Hospital of Shantou University Medical CollegeDepartment of Breast Surgery, Cancer Hospital of Shantou University Medical CollegeDepartment of Gynecology, Cancer Hospital of Shantou University Medical CollegeDepartment of Breast Surgery, Cancer Hospital of Shantou University Medical CollegeAbstract Uterine Corpus Endometrial Carcinoma (UCEC) represents a common malignant neoplasm in women, with its prognosis being intricately associated with available therapeutic interventions. In the past few decades, there has been a burgeoning interest in the role of mitochondria within the context of UCEC. Nevertheless, the development and application of prognostic models predicated on mitochondrial-related genes (MRGs) in UCEC remains in the exploratory stages. This study utilized RNA sequencing data and clinical information from the TCGA database to identify differentially expressed MRGs (DEMRGs) between UCEC and normal groups that are associated with overall survival (OS). Patients were randomly assigned to training and testing cohorts in a 1:1 ratio. In the training cohort, a risk model based on DEMRGs was developed using Lasso Cox regression analysis. Subsequently, patients in both cohorts were stratified into high-risk and low-risk groups based on their median risk scores. The prognostic performance of the model was validated through Kaplan-Meier survival analysis, ROC curves, and nomograms. Additionally, further analyses including functional enrichment, immune landscape assessment, prediction of response to ICB therapy, mutation profiling, and drug sensitivity analysis elucidated biological distinctions between the identified risk groups. We established a risk model incorporating eight MRGs. Patients classified within he high-risk group exhibited significantly poorer prognoses relative to those in the low-risk group. Functional enrichment analysis identified substantial differences in biological processes and signaling pathways between the high-risk and low-risk cohorts. Immune landscape analysis showed that patients with elevated risk scores exhibited significant immunosuppressive and immune evasion mechanisms. Conversely, low-risk patients exhibited higher expression of human leukocyte antigen (HLA) family members and immune checkpoint genes (ICGs) compared to their high-risk counterparts.Consequently, low-risk patients showed greater responsiveness to immunotherapy and potential small molecule drugs, whereas high-risk patients were more susceptible to chemotherapy. The mitochondrial-related risk model formulated in this study demonstrates efficacy in predicting both prognosis and response to immunotherapy in patients with UCEC, thereby providing a scientific basis for personalized treatment strategies. Future research endeavors should focus on further validating the clinical utility of this model and investigate the specific mechanisms of the identified MRGs in UCEC.https://doi.org/10.1038/s41598-025-85537-7Uterine corpus endometrial cancerMitochondrialPrognosisImmunotherapyTumor microenvironment |
| spellingShingle | Ru-Gen Liao Jin-Hong Wang Fan Zhang Yu-Tong Fang Li Zhou Yong-Qu Zhang A novel mitochondrial-related risk model for predicting prognosis and immune checkpoint blockade therapy response in uterine corpus endometrial carcinoma Scientific Reports Uterine corpus endometrial cancer Mitochondrial Prognosis Immunotherapy Tumor microenvironment |
| title | A novel mitochondrial-related risk model for predicting prognosis and immune checkpoint blockade therapy response in uterine corpus endometrial carcinoma |
| title_full | A novel mitochondrial-related risk model for predicting prognosis and immune checkpoint blockade therapy response in uterine corpus endometrial carcinoma |
| title_fullStr | A novel mitochondrial-related risk model for predicting prognosis and immune checkpoint blockade therapy response in uterine corpus endometrial carcinoma |
| title_full_unstemmed | A novel mitochondrial-related risk model for predicting prognosis and immune checkpoint blockade therapy response in uterine corpus endometrial carcinoma |
| title_short | A novel mitochondrial-related risk model for predicting prognosis and immune checkpoint blockade therapy response in uterine corpus endometrial carcinoma |
| title_sort | novel mitochondrial related risk model for predicting prognosis and immune checkpoint blockade therapy response in uterine corpus endometrial carcinoma |
| topic | Uterine corpus endometrial cancer Mitochondrial Prognosis Immunotherapy Tumor microenvironment |
| url | https://doi.org/10.1038/s41598-025-85537-7 |
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