ArticleScientific reports2025
Kinesin genes KIF4A, KIF20A and KIF11 as prognostic biomarkers in lung adenocarcinoma by integrative bioinformatic analysis and experimental validation.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Kinesins in Cancer Drug Resistance: Mechanisms, Therapeutic Targeting, and Translational Potential.Cancers · 2026Review
- KIF4A-KIF4B Paralog as a Prognostic Biomarker in Lung Adenocarcinoma.Medicina (Kaunas, Lithuania) · 2026Article
- Identification of replication factor C subunit 4 as a potential therapeutic target in esophageal squamous cell carcinoma based on bioinformatic analysis and machine learning.Discover oncology · 2026Article
- TGBWDriver: A Cancer Driver Gene Identification Method Based on GraphSAGE and Bidirectional Weighted Feature Aggregation.International journal of molecular sciences · 2026Article
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3 authors.
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Abstract
lung adenocarcinoma (LUAD) causes a large number of deaths worldwide each year. The pivotal involvement of Kinesin superfamily proteins (KIFs) plays a critical role in the progression of LUAD. This study primarily investigates the biological functionalities associated with specific genes within the KIF family while concurrently developing prognostic signatures of LUAD. The LUAD databases were examined to analyze differentially expressed genes (DEGs) associated with KIFs. Prognostic genes related to these DEG-KIFs were identified through univariate Cox analysis. A risk model incorporating these selected genes was constructed using LASSO regression technique. The predictive capability of this model was evaluated through survival analysis, while the functional role of KIF genes was investigated in vitro. The prognostic significance of a gene signature comprising 3 KIF genes (KIF4A, KIF20A, and KIF11) was confirmed. Overall survival analysis demonstrated the robust performance of the risk model. A nomogram and calibration curves based on 3 hub genes showed excellent prognosis predictive performance. The risk score of this risk model is closely related to the activation of ECM signaling pathway and the infiltration of multiple immune cells. The expression levels of the 3 KIF genes were also closely related to the dosages of various LUAD therapeutic drugs. In vitro experiments revealed that silencing KIF4A, KIF20A, and KIF11 effectively suppressed cell proliferation, invasion, and migration in LUAD cells. We found that this signature (KIF4A, KIF20A, KIF11) could be a potential biomarker and treatment target for LUAD patients. And our study plays a critical role in exploring the clinical application of KIFs for LUAD.
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