Abstract
BACKGROUND: Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related death worldwide. The T cell receptor (TCR) and B cell receptor (BCR) are the receptors on the surface of T or B cell, which are crucial for recognizing tumor antigens. It is profound to establish a practical TCR/BCR-related gene signature prognostic model for the further diagnosis and treatment among HCC patients. METHODS: In this study, we categorized gene expression data of HCC patients from The Cancer Genome Altas and identified TCR related genes by the Least Absolute Shrinkage and Selection Operator and multivariate Cox regression analysis. Both the CIBERSORT algorithm and the TB tools were used to analyze the features and heterogeneity of the tumor microenvironment. RESULTS: Finally, an 8-gene prognostic model was successfully established and achieved the validation in both the International Cancer Genome Consortium and Nanfang Hospital cohorts. Patients were divided into high-risk and low-risk groups based on the median of the risk scores. We observed that tumor differentiation was worse while the fibrinogen concentration was higher in the high-risk group of patients. Both the number of unique TCR and BCR clonotypes and the expanded clones were higher in the low-risk group than in the high-risk group. CONCLUSIONS: Together, our study screened a TCR/BCR-related signature prognostic model, which might turn into a beneficial and practical tool to solve the perplexities of the treatment, prognosis prediction and management for HCC patients.