Screening and Validation of Immune Infiltration-Related Prognostic Biomarkers for Cholangiocarcinoma

Abstract

Background: Immune infiltration-related genes have reported to play important roles in the prognosis of cholangiocarcinoma (CHOL). This study aimed to screen for prognostic markers of CHOL and construct a prognostic prediction model based on prognostic markers. Methods: Immune cell infiltration was evaluated in CHOL tumor samples using the single sample Gene Set Enrichment Analysis (ssGSEA) algorithm, followed by immune clustering grouping. Based on immune grouping, differentially expressed genes (DEGs) were selected, and the prognostic markers of CHOL were screened from these DEGs through Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) algorithm. A survival prognostic prediction model was constructed and validated based on the prognostic markers of CHOL. Results: The samples were divided into two clusters, and 349 intersection DEGs were identified between the tumor and normal and cluster 2 groups and cluster 1 comparison groups, which were enriched in immune response, inflammatory response, and cytokine-cytokine receptor interaction-related functions and pathways. Based on these genes, six DEGs were screened to construct a prognostic risk prediction model. In the training and validation datasets, there was a significant correlation between the actual prognosis and the different risk groups of the samples divided based on the prediction model. Conclusion: Our study established a prognostic signature associated with immune cell infiltration in patients with CHOL. This prognostic model may be used for diagnosis and prognosis of this disease.