Integrated Single-Cell Virtual Knockout and Machine Learning Analyses Reveal a Protective Role of CKAP2 in Gastric Cancer.

Objective

To elucidate the role of cytoskeleton-associated protein 2 (CKAP2) in gastric cancer (GC) progression and evaluate its prognostic and potential protective significance.

Methods

The candidate genes for GC were identified using differential expression and weighted gene co-expression network analysis (WGCNA). A panel of machine learning algorithms was applied for obtaining the key genes and yielding the hub target gene CKAP2 through protein-protein interaction (PPI) networks and single-cell RNA sequencing analysis. Further, the functional role of CKAP2 was explored through single-cell virtual knockout and pathway enrichment analysis. Meanwhile, the survival analysis and Mendelian randomization (MR) were used to evaluate the clinical relevance and causality of CKAP2. Finally, the expression of CKAP2 was further validated in clinical tissues and GC cell lines through Western blot.

Results

A total of 20 candidate genes were identified, of which 8 were identified as hub genes through machine learning. Integrative PPI and single-cell analyses ultimately identified CKAP2 as the key gene. Virtual knockout analysis showed that the related differentially expressed genes were significantly enriched in the 5-HT pathway. Survival analysis demonstrated that elevated CKAP2 expression was associated with improved prognosis. MR analysis further suggested that CKAP2 might act as a protective factor, while 5-HT was associated with an increased risk of GC. Experimental validation confirmed that CKAP2 is significantly upregulated in GC tissues and cell lines.

Conclusions

CKAP2 is a potential prognostic biomarker and protective factor in GC, possibly exerting its effects through regulation of the 5-HT pathway. These findings provide new insights into the mechanisms and potential therapeutic targets of GC.