HCC, one of the most common and deadly cancers worldwide, develops from hepatocytes and accounts for more than 90% of primary liver cancers. The current widely used treatment modalities are far from meeting the needs of liver cancer patients. CAR-T cell therapy, which has recently emerged, has shown promising efficacy in lymphoma and hematologic cancers, but there are still many challenges to overcome in its application to the clinical treatment of HCC, including osmotic barriers, the inhibition of hepatocellular carcinoma microenvironment activity, the limited survival and killing ability of CAR-T cells, and inevitable side effects, among others. As a result, a number of studies have begun to address the suboptimal efficacy of CAR-T cells in HCC, and many of these schemes hold good promise. This review focuses on advances in the past five years aimed at promoting the efficacy of CAR-T cell therapy for treatment of HCC.

To build a prognostic and immunotherapeutic response prediction model for liver cancer based on marker genes of tumor-associated endothelial cell (TEC). Single cell sequencing data from Gene Expression Omnibus (GEO) liver cancer patients were utilized to identify TEC subpopulations. Models were built from transcriptomic and clinical data of TCGA liver cancer patients. The GSE76427 and ICGC databases were used as independent validation sets. Time-dependent receiver operating characteristic (ROC) curves and Kaplan-Meier curves were used to verify the ability of the model to predict survival. XCELL, TIMER, QUANTISEQ, CIBERSORT, CIBERSORT-ABS, and ssGSEA were applied to evaluate tumor immune cell infiltration. The TIDE score was used to predict the effect of immunotherapy. Immune blockade checkpoint gene, tumor mutational load and GSVA enrichment analyses were further explored. The expression levels of candidate genes were measured and validated by real-time PCR between liver cancer tissues and adjacent nontumor liver tissues. Eighty-seven genes were identified as marker genes for TECs. IGFBP3, RHOC, S100A16, FSCN1, and CLEC3B were included in the constructed prognostic model. Time-dependent ROC curve values were higher than 0.700 in both the model and validation groups. The low risk group exhibited high immune cell infiltration and function than the higher risk group. The TIDE score indicated that the low-risk group benefited more from immunotherapy than the high-risk group. The risk score and multiple immune blockade checkpoint genes and immune-related pathways were strongly correlated. Novel signatures of TEC marker genes showed a powerful ability to predict prognosis and immunotherapy response in patients with liver cancer.