Identification of gene-set signature and relevant immune cell infiltration in early-stage hepatocellular carcinoma

Abstract

The incidence of hepatocellular carcinoma (HCC) is rising worldwide, and there is limited therapeutic efficacy due to tumor microenvironment heterogeneity and difficulty in early-stage screening. This study aimed to develop and validate a gene setbased signature for early-stage hepatocellular carcinoma patients and further explored specific marker dysregulation mechanisms as well as immune characteristics. We performed an integrated bioinformatics analysis of genomic, transcriptomic and clinical data with three independent cohorts. We systematically reviewed the crosstalk between specific genes, tumor prognosis, immune characteristics and biological function in the different pathological stage samples. Univariate and multivariate survival analysis were performed in the cancer genome atlas (TCGA) patients with survival data. Diethylnitrosamine (DEN)-induced HCC in wistar rat was employed to verify the reliability of the predictions. We identified a Cluster gene that potentially segregate patients with early-stage HCC (eHCC) from non-tumor, through integrated analysis of expression, overall survival, immune cells characteristics and biology function landscapes. Immune infiltration analysis showed that lower-infiltration of specific immune cells may be responsible for significantly worse prognosis in HCC (Hazard ratio, 1.691; 95%CI, 1.171-2.441; P=0.012), such as CD8 Tem and CTLs in eHCC. Our results identified that Cluster C1 signature presented a high accuracy in predicting CD8 Tem and CTLs immune cells (ROC=0.647) and cancerization (ROC=0.946) in liver. As a central member of Cluster C1, overexpressed DNA-dependent protein kinase catalytic subunit (PRKDC) was associated with the higher genetic alteration in eHCC than aHCC, which was also connected to immune cell-related poor prognosis. Finally, the predictive outcome of Cluster C1 and PRKDC alteration in DEN-induced eHCC rat was also confirmed. As a tumor prognosis-relevant gene-set based signature, the Cluster C1 showed an effective approach to predict cancenrization of eHCC and its related immune characteristics with considerable clinical value.