Identification and validation of glucose metabolism-related gene signature in endometrial cancer
Abstract Background Metabolic syndrome associated with glucose metabolism plays a pivotal role in tumorigenesis, potentially elevating the risk of endometrial cancer (EC). This study sought to establish a glucose metabolism-related gene (GMRG) signature linked to EC. Methods Differential analysis wa...
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BMC
2025-01-01
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| Series: | BMC Cancer |
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| Online Access: | https://doi.org/10.1186/s12885-024-13418-9 |
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| author | Juan Jiang Nan Xia Mei Yang Ping Qiu Wei Zhu Jing Chen Jiamei Zhu |
| author_facet | Juan Jiang Nan Xia Mei Yang Ping Qiu Wei Zhu Jing Chen Jiamei Zhu |
| author_sort | Juan Jiang |
| collection | DOAJ |
| description | Abstract Background Metabolic syndrome associated with glucose metabolism plays a pivotal role in tumorigenesis, potentially elevating the risk of endometrial cancer (EC). This study sought to establish a glucose metabolism-related gene (GMRG) signature linked to EC. Methods Differential analysis was conducted to identify differentially expressed genes (DEGs) between EC and normal samples from the TCGA-EC dataset. Glucose metabolism-related DEGs (GMR-DEGs) were then derived by intersecting these DEGs with GMRGs. A prognostic signature for EC was developed through the Least Absolute Shrinkage and Selection Operator (LASSO) regression and univariate Cox analysis. Additionally, immune profiling and immunotherapy responsiveness were evaluated across two distinct risk subgroups, accompanied by a single-cell analysis of prognostic genes. The expression levels of these prognostic genes were quantified at both transcriptional and translational stages using reverse transcription quantitative PCR (RT-qPCR) and immunohistochemistry (IHC) in clinical samples. Furthermore, the functional significance of key genes was explored through in vitro assays. Results 2,912 DEGs and 202 GMR-DEGs were identified between the EC and normal groups. Subsequently, six prognostic genes were derived, including ASRGL1, SLC38A3, SLC2A1, ALDH1B1, GAD1, and GLYATL1. EC patients were classified into high and low-risk subgroups based on the six genes. Independent prognostic analysis indicated that risk score and disease stage were significant independent prognostic factors. Single-cell analysis revealed that the six prognostic genes were highly expressed in ciliated and epithelial cells. Immune cell infiltration was generally lower in the high-risk group, where tumor purity was elevated. The expression levels of SLC38A3, SLC2A1, and ASRGL1 are higher in tumor samples by RT-qPCR, with IHC confirming increased SLC38A3 expression. Finally, SLC38A3 may function as oncogenes in EC, as revealed by the results of in vitro experiments. Conclusions In this study, we developed six novel prognostic genes in EC based on glycolysis, and corresponding prognostic models were developed. Notably, we identified SLC38A3 as the key gene, which offers valuable insights for further research into EC. |
| format | Article |
| id | doaj-art-a853e4129eac4fb1a736cfe28529bc9a |
| institution | Kabale University |
| issn | 1471-2407 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Cancer |
| spelling | doaj-art-a853e4129eac4fb1a736cfe28529bc9a2025-01-12T12:27:20ZengBMCBMC Cancer1471-24072025-01-0125111910.1186/s12885-024-13418-9Identification and validation of glucose metabolism-related gene signature in endometrial cancerJuan Jiang0Nan Xia1Mei Yang2Ping Qiu3Wei Zhu4Jing Chen5Jiamei Zhu6Department of Obstetrics and Gynecology, Jingjiang People’s Hospital Affiliated to Yangzhou UniversityDepartment of Pathology, Jingjiang People’s Hospital Affiliated to Yangzhou UniversityAdvanced Molecular Pathology, Institute of Soochow University and SANODepartment of Obstetrics and Gynecology, Jingjiang People’s Hospital Affiliated to Yangzhou UniversityDepartment of Obstetrics and Gynecology, Jingjiang People’s Hospital Affiliated to Yangzhou UniversityDepartment of Pathology, Jingjiang People’s Hospital Affiliated to Yangzhou UniversityDepartment of Obstetrics and Gynecology, Jingjiang People’s Hospital Affiliated to Yangzhou UniversityAbstract Background Metabolic syndrome associated with glucose metabolism plays a pivotal role in tumorigenesis, potentially elevating the risk of endometrial cancer (EC). This study sought to establish a glucose metabolism-related gene (GMRG) signature linked to EC. Methods Differential analysis was conducted to identify differentially expressed genes (DEGs) between EC and normal samples from the TCGA-EC dataset. Glucose metabolism-related DEGs (GMR-DEGs) were then derived by intersecting these DEGs with GMRGs. A prognostic signature for EC was developed through the Least Absolute Shrinkage and Selection Operator (LASSO) regression and univariate Cox analysis. Additionally, immune profiling and immunotherapy responsiveness were evaluated across two distinct risk subgroups, accompanied by a single-cell analysis of prognostic genes. The expression levels of these prognostic genes were quantified at both transcriptional and translational stages using reverse transcription quantitative PCR (RT-qPCR) and immunohistochemistry (IHC) in clinical samples. Furthermore, the functional significance of key genes was explored through in vitro assays. Results 2,912 DEGs and 202 GMR-DEGs were identified between the EC and normal groups. Subsequently, six prognostic genes were derived, including ASRGL1, SLC38A3, SLC2A1, ALDH1B1, GAD1, and GLYATL1. EC patients were classified into high and low-risk subgroups based on the six genes. Independent prognostic analysis indicated that risk score and disease stage were significant independent prognostic factors. Single-cell analysis revealed that the six prognostic genes were highly expressed in ciliated and epithelial cells. Immune cell infiltration was generally lower in the high-risk group, where tumor purity was elevated. The expression levels of SLC38A3, SLC2A1, and ASRGL1 are higher in tumor samples by RT-qPCR, with IHC confirming increased SLC38A3 expression. Finally, SLC38A3 may function as oncogenes in EC, as revealed by the results of in vitro experiments. Conclusions In this study, we developed six novel prognostic genes in EC based on glycolysis, and corresponding prognostic models were developed. Notably, we identified SLC38A3 as the key gene, which offers valuable insights for further research into EC.https://doi.org/10.1186/s12885-024-13418-9Endometrial cancerGlucose metabolismPrognostic signatureRisk subgroups |
| spellingShingle | Juan Jiang Nan Xia Mei Yang Ping Qiu Wei Zhu Jing Chen Jiamei Zhu Identification and validation of glucose metabolism-related gene signature in endometrial cancer BMC Cancer Endometrial cancer Glucose metabolism Prognostic signature Risk subgroups |
| title | Identification and validation of glucose metabolism-related gene signature in endometrial cancer |
| title_full | Identification and validation of glucose metabolism-related gene signature in endometrial cancer |
| title_fullStr | Identification and validation of glucose metabolism-related gene signature in endometrial cancer |
| title_full_unstemmed | Identification and validation of glucose metabolism-related gene signature in endometrial cancer |
| title_short | Identification and validation of glucose metabolism-related gene signature in endometrial cancer |
| title_sort | identification and validation of glucose metabolism related gene signature in endometrial cancer |
| topic | Endometrial cancer Glucose metabolism Prognostic signature Risk subgroups |
| url | https://doi.org/10.1186/s12885-024-13418-9 |
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