Kinase-based molecular subtyping and a prognostic risk model in colorectal cancer with functional validation of PLK4

Colorectal cancer (CRC) exhibits marked molecular heterogeneity, yet prognostic tools centered specifically on protein kinases remain scarce. This study aimed to identify kinase-related molecular subtypes of CRC and to develop and validate a kinase-based prognostic risk model integrating clinical and immune features.

Transcriptomic data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) were integrated to identify prognosis-related kinase genes. Unsupervised consensus clustering was used to define molecular subtypes, and differences in survival, immune infiltration, and immune checkpoint expression between subtypes were assessed. A nine-gene prognostic model was constructed using least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression and validated in an independent external cohort. Associations with the consensus molecular subtypes (CMS), tumor mutational burden (TMB), drug sensitivity, and immunotherapy response were analyzed. The expression of core genes was verified by quantitative real-time polymerase chain reaction (qRT-PCR) in CRC cell lines, and the function of PLK4 was examined by knockdown experiments.

Consensus clustering revealed two distinct kinase-based subtypes with significantly different survival; the poorer-prognosis subtype overlapped predominantly with CMS4 and showed altered immune infiltration. The nine-gene risk model provided reproducible prognostic stratification, remained an independent predictor of survival after adjustment for tumor-node-metastasis (TNM) stage, and was validated in the external validation cohort. Compared with high-risk patients, low-risk patients showed higher TMB and greater predicted responsiveness to immunotherapy and selected chemotherapeutic agents. qRT-PCR confirmed that nine core genes exhibited expression trends consistent with the bioinformatics predictions, and PLK4 knockdown consistently inhibited cell proliferation and migration and promoted apoptosis in both HT-29 and HCT116 cells, supporting an oncogenic role.

This kinase-based subtyping and prognostic model offers a complementary tool for risk stratification and individualized treatment decisions in CRC. Further multi-omics and in vivo studies are warranted to facilitate clinical translation.