Table_1_Establishment and validation of exhausted CD8+ T cell feature as a prognostic model of HCC.xlsx

ObjectivesThe exhausted CD8+T (Tex) cells are a unique cell population of activated T cells that emerges in response to persistent viral infection or tumor antigens. Tex cells showed the characteristics of aging cells, including weakened self-renewal ability, effector function inhibition, sustained high expression of inhibitory receptors including PD-1, TIGIT, TIM-3, and LAG-3, and always accompanied by metabolic and epigenetic reprogramming. Tex cells are getting more and more attention in researching immune-related diseases and tumor immunotherapy. However, studies on Tex-related models for tumor prognosis are still lacking. We hope to establish a risk model based on Tex-related genes for HCC prognosis.
MethodsTex-related GEO datasets from different pathologic factors (chronic HBV, chronic HCV, and telomere shortening) were analyzed respectively to acquire differentially expressed genes (DEGs) by the ‘limma’ package of R. Genes with at least one intersection were incorporated into Tex-related gene set. GO, KEGG, and GSEA enrichment analyses were produced. Hub genes and the PPI network were established and visualized by the STRING website and Cytoscape software. Transcription factors and targeting small molecules were predicted by the TRUST and CLUE websites. The Tex-related HCC prognostic model was built by Cox regression and verified based on different datasets. Tumor immune dysfunction and exclusion (TIDE) and SubMap algorithms tested immunotherapy sensitivity. Finally, qRT-PCR and Flow Cytometry was used to confirm the bioinformatic results.
ResultsHub genes such as AKT1, CDC6, TNF and their upstream transcription factor ILF3, Regulatory factor X-associated protein, STAT3, JUN, and RELA/NFKB1 were identified as potential motivators for Tex. Tex-related genes SLC16A11, CACYBP, HSF2, and ATG10 built the HCC prognostic model and helped with Immunotherapy sensitivity prediction.
ConclusionOur study demonstrated that Tex-related genes might provide accurate prediction for HCC patients in clinical decision-making, prognostic assessment, and immunotherapy. In addition, targeting the hub genes or transcription factors may help to reverse T cell function and enhance the effect of tumor immunotherapy.

研究目的：耗竭性CD8+T细胞（exhausted CD8+T cells, Tex）是一类独特的活化T细胞群体，在持续性病毒感染或肿瘤抗原刺激下产生。Tex细胞呈现衰老细胞的特征：自我更新能力减弱、效应功能受抑制，持续高表达PD-1、TIGIT、TIM-3、LAG-3等抑制性受体，并伴随代谢与表观遗传重编程。目前Tex细胞在免疫相关疾病及肿瘤免疫治疗领域的研究关注度与日俱增，但针对Tex相关模型用于肿瘤预后的研究仍较为匮乏。本研究旨在构建基于Tex相关基因的肝细胞癌（Hepatocellular carcinoma, HCC）预后风险模型。

研究方法：分别分析来自不同病理因素（慢性HBV感染、慢性HCV感染及端粒缩短）的Tex相关GEO数据集，通过R语言limma包筛选差异表达基因（differentially expressed genes, DEGs）；将存在至少一个交集的基因整合为Tex相关基因集。随后开展GO、KEGG及GSEA富集分析。借助STRING数据库与Cytoscape软件构建并可视化蛋白互作（Protein-Protein Interaction, PPI）网络，筛选核心基因（hub genes）。通过TRUST与CLUE数据库预测转录因子及靶向小分子化合物。采用Cox回归构建Tex相关HCC预后模型，并基于多组独立数据集进行验证。运用肿瘤免疫功能异常与排斥（Tumor Immune Dysfunction and Exclusion, TIDE）算法及SubMap算法分析免疫治疗敏感性。最后通过实时定量聚合酶链反应（qRT-PCR）与流式细胞术（Flow Cytometry）验证生物信息学分析结果。

研究结果：本研究鉴定出AKT1、CDC6、TNF等核心基因，及其上游转录因子ILF3、调控因子X相关蛋白、STAT3、JUN及RELA/NFKB1，上述分子或可作为Tex细胞形成的潜在驱动因素。基于Tex相关基因SLC16A11、CACYBP、HSF2及ATG10构建的HCC预后模型，可辅助免疫治疗敏感性预测。

研究结论：本研究证实，Tex相关基因可为肝细胞癌患者的临床决策、预后评估及免疫治疗提供精准预测依据；此外，靶向核心基因或转录因子或可逆转T细胞功能耗竭，增强肿瘤免疫治疗效果。