KIF2C as a potential therapeutic target: insights from lung adenocarcinoma subtype classification and functional experiments.
Zhi XuRui MiaoTao HanYafeng LiuJiawei ZhouJianqiang GuoYingru XingYing BaiJing WuDong HuPublished in: Molecular omics (2024)
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.
Keyphrases
- poor prognosis
- epithelial mesenchymal transition
- genome wide
- long non coding rna
- cell proliferation
- genome wide identification
- end stage renal disease
- machine learning
- peritoneal dialysis
- ejection fraction
- copy number
- type diabetes
- bioinformatics analysis
- prognostic factors
- signaling pathway
- transcription factor
- high throughput
- clinical practice
- patient reported
- replacement therapy