Predictive value analysis of the interaction network of Tks4 scaffold protein in colon cancer.

Background: Colorectal carcinoma (CRC) has emerged as one of the most widespread cancers and was the third leading cause of cancer-related mortality in 2020. The role of the podosomal protein Tks4 in tumor formation and progression is well established, including its involvement in gastric carcinoma and hepatocellular carcinoma; however, exploration of Tks4 and its associated EMT-regulating interactome in the context of colon cancer remains largely unexplored. Methods: We conducted a comprehensive bioinformatic analysis to investigate the mRNA and protein expression levels of Tks4 and its associated partner molecules (CD2AP, GRB2, WASL, SRC, CTTN, and CAPZA1) across different tumor types. We quantified the expression levels of Tks4 and its partner molecules using qPCR, utilizing a TissueScan colon cancer array. We then validated the usefulness of Tks4 and its associated molecules as biomarkers via careful statistical analyses, including Pearson's correlation analysis, principal component analysis (PCA), multiple logistic regression, confusion matrix analysis, and ROC analysis. Results: Our findings indicate that the co-expression patterns of the seven examined biomarker candidates better differentiate between tumor and normal samples compared with the expression levels of the individual genes. Moreover, variable importance analysis of these seven genes revealed four core genes that yield consistent results similar to the seven genes. Thus, these four core genes from the Tks4 interactome hold promise as potential combined biomarkers for colon adenocarcinoma diagnosis and prognosis. Conclusion: Our proposed biomarker set from the Tks4 interactome shows promising sensitivity and specificity, aiding in colon cancer prevention and diagnosis.