Identification and validation of the important role of KIF11 in the development and progression of endometrial cancer
Abstract Background Human kinesin family member 11 (KIF11) plays a vital role in regulating the cell cycle and is implicated in the tumorigenesis and progression of various cancers, but its role in endometrial cancer (EC) is still unclear. Our current research explored the prognostic value, biologic...
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2025-01-01
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| Series: | Journal of Translational Medicine |
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| Online Access: | https://doi.org/10.1186/s12967-025-06081-6 |
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| author | Biying Wang Lunmin Bao Xiaoduo Li Guang Sun Wu Yang Nanzi Xie Ling Lei Wei Chen Hailong Zhang Man Chen Xing Zhao Xiufang Wan Rui Yuan Hongmei Jiang |
| author_facet | Biying Wang Lunmin Bao Xiaoduo Li Guang Sun Wu Yang Nanzi Xie Ling Lei Wei Chen Hailong Zhang Man Chen Xing Zhao Xiufang Wan Rui Yuan Hongmei Jiang |
| author_sort | Biying Wang |
| collection | DOAJ |
| description | Abstract Background Human kinesin family member 11 (KIF11) plays a vital role in regulating the cell cycle and is implicated in the tumorigenesis and progression of various cancers, but its role in endometrial cancer (EC) is still unclear. Our current research explored the prognostic value, biological function and targeting strategy of KIF11 in EC through approaches including bioinformatics, machine learning and experimental studies. Methods The GSE17025 dataset from the GEO database was analyzed via the limma package to identify differentially expressed genes (DEGs) in EC. Functional enrichment analysis of the DEGs was conducted using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. DEGs were further screened for hub genes through protein–protein interaction (PPI) network analysis and machine learning. The role of the hub gene KIF11 in EC was analyzed using clinical data from the TCGA database. The expression of KIF11 in EC was subsequently validated in clinical samples. In vitro experiments were utilized to evaluate the effects of KIF11 on biological functions such as proliferation, migration, apoptosis, and the cell cycle in endometrial cancer cells. Results A total of 877 DEGs, which are widely involved in important biological processes such as cell division, tubulin binding, and the cell cycle, were identified. Through PPI network analysis and machine learning, KIF11 was selected as the hub gene for subsequent analysis and experimental validation. An analysis of TCGA data revealed that KIF11 is highly expressed in EC and is associated with tumor grade, stage, and a low survival rate. The overexpression of KIF11 in tumor tissues was further confirmed in EC patient samples. KIF11 knockdown had inhibitory effects on cell proliferation, migration and invasion. Flow cytometry analysis revealed that KIF11 knockdown induced G2/M phase arrest and promoted apoptosis in EC cells. Conclusion Our study demonstrated that KIF11 was upregulated in EC and was strongly associated with a poor prognosis. Notably, we found that reduced KIF11 expression inhibited EC cell proliferation, migration and invasion. KIF11 knockdown caused more EC cells to arrest in the G2/M phase and undergo apoptosis. The findings of our study emphasized that KIF11 may be a promising prognostic biomarker and therapeutic target for EC patients. |
| format | Article |
| id | doaj-art-5627e2b8212b4ffc84e51ab43156b97e |
| institution | Kabale University |
| issn | 1479-5876 |
| language | English |
| publishDate | 2025-01-01 |
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| series | Journal of Translational Medicine |
| spelling | doaj-art-5627e2b8212b4ffc84e51ab43156b97e2025-01-19T12:37:18ZengBMCJournal of Translational Medicine1479-58762025-01-0123111710.1186/s12967-025-06081-6Identification and validation of the important role of KIF11 in the development and progression of endometrial cancerBiying Wang0Lunmin Bao1Xiaoduo Li2Guang Sun3Wu Yang4Nanzi Xie5Ling Lei6Wei Chen7Hailong Zhang8Man Chen9Xing Zhao10Xiufang Wan11Rui Yuan12Hongmei Jiang13School of Clinical Laboratory Science, Guizhou Medical UniversitySchool of Clinical Laboratory Science, Guizhou Medical UniversityDepartment of Laboratory Medicine, Peoples’ Hospital of Anshun CityDepartment of Laboratory Medicine, Peoples’ Hospital of Anshun CityDepartment of Gynaecology, Peoples’ Hospital of Anshun CityDepartment of Pathology, Peoples’ Hospital of Anshun CityDepartment of Gynaecology, Peoples’ Hospital of Anshun CityDepartment of Pathology, Peoples’ Hospital of Anshun CityDepartment of Laboratory Medicine, Peoples’ Hospital of Anshun CityDepartment of Gynaecology, Peoples’ Hospital of Anshun CitySchool of Clinical Laboratory Science, Guizhou Medical UniversitySchool of Clinical Laboratory Science, Guizhou Medical UniversitySchool of Clinical Laboratory Science, Guizhou Medical UniversitySchool of Clinical Laboratory Science, Guizhou Medical UniversityAbstract Background Human kinesin family member 11 (KIF11) plays a vital role in regulating the cell cycle and is implicated in the tumorigenesis and progression of various cancers, but its role in endometrial cancer (EC) is still unclear. Our current research explored the prognostic value, biological function and targeting strategy of KIF11 in EC through approaches including bioinformatics, machine learning and experimental studies. Methods The GSE17025 dataset from the GEO database was analyzed via the limma package to identify differentially expressed genes (DEGs) in EC. Functional enrichment analysis of the DEGs was conducted using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. DEGs were further screened for hub genes through protein–protein interaction (PPI) network analysis and machine learning. The role of the hub gene KIF11 in EC was analyzed using clinical data from the TCGA database. The expression of KIF11 in EC was subsequently validated in clinical samples. In vitro experiments were utilized to evaluate the effects of KIF11 on biological functions such as proliferation, migration, apoptosis, and the cell cycle in endometrial cancer cells. Results A total of 877 DEGs, which are widely involved in important biological processes such as cell division, tubulin binding, and the cell cycle, were identified. Through PPI network analysis and machine learning, KIF11 was selected as the hub gene for subsequent analysis and experimental validation. An analysis of TCGA data revealed that KIF11 is highly expressed in EC and is associated with tumor grade, stage, and a low survival rate. The overexpression of KIF11 in tumor tissues was further confirmed in EC patient samples. KIF11 knockdown had inhibitory effects on cell proliferation, migration and invasion. Flow cytometry analysis revealed that KIF11 knockdown induced G2/M phase arrest and promoted apoptosis in EC cells. Conclusion Our study demonstrated that KIF11 was upregulated in EC and was strongly associated with a poor prognosis. Notably, we found that reduced KIF11 expression inhibited EC cell proliferation, migration and invasion. KIF11 knockdown caused more EC cells to arrest in the G2/M phase and undergo apoptosis. The findings of our study emphasized that KIF11 may be a promising prognostic biomarker and therapeutic target for EC patients.https://doi.org/10.1186/s12967-025-06081-6Endometrial cancerMachine learningKIF11Bioinformatics |
| spellingShingle | Biying Wang Lunmin Bao Xiaoduo Li Guang Sun Wu Yang Nanzi Xie Ling Lei Wei Chen Hailong Zhang Man Chen Xing Zhao Xiufang Wan Rui Yuan Hongmei Jiang Identification and validation of the important role of KIF11 in the development and progression of endometrial cancer Journal of Translational Medicine Endometrial cancer Machine learning KIF11 Bioinformatics |
| title | Identification and validation of the important role of KIF11 in the development and progression of endometrial cancer |
| title_full | Identification and validation of the important role of KIF11 in the development and progression of endometrial cancer |
| title_fullStr | Identification and validation of the important role of KIF11 in the development and progression of endometrial cancer |
| title_full_unstemmed | Identification and validation of the important role of KIF11 in the development and progression of endometrial cancer |
| title_short | Identification and validation of the important role of KIF11 in the development and progression of endometrial cancer |
| title_sort | identification and validation of the important role of kif11 in the development and progression of endometrial cancer |
| topic | Endometrial cancer Machine learning KIF11 Bioinformatics |
| url | https://doi.org/10.1186/s12967-025-06081-6 |
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