基于单细胞转录组学的 TIL（肿瘤浸润淋巴细胞）与肝细胞癌作用及机制探索

Hepatocellular carcinoma (HCC) remains a major global health challenge, with limited effective treatment options, particularly in advanced-stage patients. The tumor immune microenvironment (TIME) plays a crucial role in HCC progression and treatment response, with tumor-infiltrating lymphocytes (TILs) being key modulators of immune activity. In this study, we investigated the immunosuppressive role of TIL-related genes in NASH-associated HCC (NASH-HCC) and identified their potential as independent prognostic factors.

We employed Gene Set Enrichment Analysis (GSEA) and Weighted Gene Coexpression Network Analysis (WGCNA) to explore immune suppression in NASH-HCC and identify TIL-related gene modules. Machine learning approaches were utilized to construct a prognostic model, validated using multiple cohorts from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). The model's predictive power was assessed using Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curves.

Furthermore, single-cell RNA sequencing (scRNA-seq) analysis was performed to examine the role of TIL-related genes in different immune cell populations within TIME.

We identified 10 distinct cell types in HCC and demonstrated that T cells exhibited the highest TIL pathway activity, playing a critical role in cellular communication via MIF signaling.

Our findings highlight the immunosuppressive nature of TILs in NASH-HCC and provide valuable insights into their prognostic significance, potentially guiding future immunotherapeutic strategies.