Zhi Xu, Rui Miao, Tao Han, Yafeng Liu, Jiawei Zhou, Jianqiang Guo, Yingru Xing, Ying Bai, Jing Wu and Dong Hu
{"title":"作为潜在治疗靶点的 KIF2C:肺腺癌亚型分类和功能实验的启示。","authors":"Zhi Xu, Rui Miao, Tao Han, Yafeng Liu, Jiawei Zhou, Jianqiang Guo, Yingru Xing, Ying Bai, Jing Wu and Dong Hu","doi":"10.1039/D4MO00044G","DOIUrl":null,"url":null,"abstract":"<p >\r\n <em>Objective</em>: this study evaluates the prognostic relevance of gene subtypes and the role of kinesin family member 2C (KIF2C) in lung cancer progression. <em>Methods</em>: high-expression genes linked to overall survival (OS) and progression-free interval (PFI) were selected from the TCGA-LUAD dataset. Consensus clustering analysis categorized lung adenocarcinoma (LUAD) patients into two subtypes, C1 and C2, which were compared using clinical, drug sensitivity, and immunotherapy analyses. A random forest algorithm pinpointed KIF2C as a prognostic hub gene, and its functional impact was assessed through various assays and <em>in vivo</em> experiments. <em>Results</em>: The study identified 163 key genes and distinguished two LUAD subtypes with differing OS, PFI, pathological stages, drug sensitivity, and immunotherapy response. KIF2C, highly expressed in the C2 subtype, was associated with poor prognosis, promoting cancer cell proliferation, migration, invasion, and epithelial–mesenchymal transition (EMT), with knockdown reducing tumor growth in mice. <em>Conclusion</em>: The research delineates distinct LUAD subtypes with significant clinical implications and highlights KIF2C as a potential therapeutic target for personalized treatment in LUAD.</p>","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" 6","pages":" 417-429"},"PeriodicalIF":3.0000,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"KIF2C as a potential therapeutic target: insights from lung adenocarcinoma subtype classification and functional experiments†\",\"authors\":\"Zhi Xu, Rui Miao, Tao Han, Yafeng Liu, Jiawei Zhou, Jianqiang Guo, Yingru Xing, Ying Bai, Jing Wu and Dong Hu\",\"doi\":\"10.1039/D4MO00044G\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >\\r\\n <em>Objective</em>: this study evaluates the prognostic relevance of gene subtypes and the role of kinesin family member 2C (KIF2C) in lung cancer progression. <em>Methods</em>: high-expression genes linked to overall survival (OS) and progression-free interval (PFI) were selected from the TCGA-LUAD dataset. Consensus clustering analysis categorized lung adenocarcinoma (LUAD) patients into two subtypes, C1 and C2, which were compared using clinical, drug sensitivity, and immunotherapy analyses. A random forest algorithm pinpointed KIF2C as a prognostic hub gene, and its functional impact was assessed through various assays and <em>in vivo</em> experiments. <em>Results</em>: The study identified 163 key genes and distinguished two LUAD subtypes with differing OS, PFI, pathological stages, drug sensitivity, and immunotherapy response. KIF2C, highly expressed in the C2 subtype, was associated with poor prognosis, promoting cancer cell proliferation, migration, invasion, and epithelial–mesenchymal transition (EMT), with knockdown reducing tumor growth in mice. <em>Conclusion</em>: The research delineates distinct LUAD subtypes with significant clinical implications and highlights KIF2C as a potential therapeutic target for personalized treatment in LUAD.</p>\",\"PeriodicalId\":19065,\"journal\":{\"name\":\"Molecular omics\",\"volume\":\" 6\",\"pages\":\" 417-429\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-06-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Molecular omics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://pubs.rsc.org/en/content/articlelanding/2024/mo/d4mo00044g\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular omics","FirstCategoryId":"99","ListUrlMain":"https://pubs.rsc.org/en/content/articlelanding/2024/mo/d4mo00044g","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
KIF2C as a potential therapeutic target: insights from lung adenocarcinoma subtype classification and functional experiments†
Objective: this study evaluates the prognostic relevance of gene subtypes and the role of kinesin family member 2C (KIF2C) in lung cancer progression. Methods: high-expression genes linked to overall survival (OS) and progression-free interval (PFI) were selected from the TCGA-LUAD dataset. Consensus clustering analysis categorized lung adenocarcinoma (LUAD) patients into two subtypes, C1 and C2, which were compared using clinical, drug sensitivity, and immunotherapy analyses. A random forest algorithm pinpointed KIF2C as a prognostic hub gene, and its functional impact was assessed through various assays and in vivo experiments. Results: The study identified 163 key genes and distinguished two LUAD subtypes with differing OS, PFI, pathological stages, drug sensitivity, and immunotherapy response. KIF2C, highly expressed in the C2 subtype, was associated with poor prognosis, promoting cancer cell proliferation, migration, invasion, and epithelial–mesenchymal transition (EMT), with knockdown reducing tumor growth in mice. Conclusion: The research delineates distinct LUAD subtypes with significant clinical implications and highlights KIF2C as a potential therapeutic target for personalized treatment in LUAD.
Molecular omicsBiochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
5.40
自引率
3.40%
发文量
91
期刊介绍:
Molecular Omics publishes high-quality research from across the -omics sciences.
Topics include, but are not limited to:
-omics studies to gain mechanistic insight into biological processes – for example, determining the mode of action of a drug or the basis of a particular phenotype, such as drought tolerance
-omics studies for clinical applications with validation, such as finding biomarkers for diagnostics or potential new drug targets
-omics studies looking at the sub-cellular make-up of cells – for example, the subcellular localisation of certain proteins or post-translational modifications or new imaging techniques
-studies presenting new methods and tools to support omics studies, including new spectroscopic/chromatographic techniques, chip-based/array technologies and new classification/data analysis techniques. New methods should be proven and demonstrate an advance in the field.
Molecular Omics only accepts articles of high importance and interest that provide significant new insight into important chemical or biological problems. This could be fundamental research that significantly increases understanding or research that demonstrates clear functional benefits.
Papers reporting new results that could be routinely predicted, do not show a significant improvement over known research, or are of interest only to the specialist in the area are not suitable for publication in Molecular Omics.