Abstract
Background: Studies suggest that kinesin family (KIF) members can promote the occurrence of colorectal cancer (CRC). However, the mechanism of action has not yet been elucidated. The aim of this study was to identify CRC biomarkers associated with KIF members and to investigate their biological mechanisms in the treatment of colorectal cancer by analyzing multi-omics data. Methods: CRC-related datasets and KIF member-related genes (KIFRGs) were used. First, differentially expressed genes (DEGs) and differentially expressed methylation genes (DEMGs) in the TCGA-CRC were identified separately using different expression analyses (CRC vs. control). The intersecting genes were selected by overlapping the DEGs, DEMGs, and KIFRGs. Candidate genes were identified using survival analysis (p < 0.05). Subsequently, based on the candidate genes, biomarkers were selected by gene expression validation and survival analysis. Subsequently, functional enrichment, immune cell infiltration, and drug sensitivity analyses were performed. Single-cell analysis was utilized to perform cell annotation, and then function enrichment and pseudo-temporal analyses were performed. Results: The 12 intersecting genes were identified by overlapping 12,479 DEGs, 11,319 DEMGs, and 43 KIFRGs. The survival analysis showed that Kinesin Family Member C2 (KIFC2) and Kinesin Family Member C3 (KIFC3) had significant differences in survival (p < 0.05). Moreover, KIFC3 passed the gene expression validation and survival analysis validation (p < 0.05); thus, KIFC3 was deemed a biomarker. Subsequently, the pathways involved in KIFC3 were detected, such as the Ecm receptor intersection and chemokine signaling pathway. In addition, we found that KIFC3 was significantly positively correlated with natural killer (NK) cells (r = 0.455, p < 0.05) and NK T cells (r = 0.411, p < 0.05). Moreover, in the drug sensitivity of the CRC, the potential therapeutic benefits of AZD.2281, nilotinib, PD.173074, and shikonin were detected. Furthermore, using single-cell analysis, 16 cell clusters were annotated, and epithelial cells and M2-like macrophages were enriched in "rheumatoid arthritis". Additionally, we observed that most M1-like macrophages were present in the early stages of differentiation, whereas M2-like macrophages were predominant in the later stages of differentiation. Conclusions: This study identifies KIFC3 as a CRC biomarker through multi-omics analysis, highlighting its unique expression, survival association, immune correlations, and drug sensitivity for potential diagnostic and therapeutic applications.