Yang Qi, Liu Le, Zhu Yawen, Shen Zhengchao, Xu Yifan, Zhang Mengjie, Chen Xi
Department of Gastroenterology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Department of Gastroenterology, The First Affiliated Hospital of Wannan Medical College, Wuhu, China.
J Gastrointest Oncol. 2025 Jun 30;16(3):1127-1143. doi: 10.21037/jgo-2025-50. Epub 2025 Jun 27.
BACKGROUND: T cells are essential mediators of antitumor immune responses. While T cell proliferation-related genes (TRGs) have been identified, how they relate to prognostic outcomes in hepatocellular carcinoma (HCC) patients remains uncertain. This study attempts to analyze the relationship between TRGs and the prognosis of patients with HCC from multiple perspectives. METHODS: The expression of 33 TRGs and associated clinical data from HCC patients were obtained from several datasets and used to conduct bioinformatics analyses. T cell proliferation-related molecular subtypes were established via consensus clustering, while a least absolute shrinkage and selection operator (LASSO)-Cox regression approach was used to develop a predictive gene signature that was validated in an external cohort. These results were also used to guide the design of a nomogram with high levels of accuracy to improve the clinical value of TRG scores. analyses were also used to establish and validate candidate biomarkers. RESULTS: Patients with HCC were divided into two TRG-based clusters and differentially expressed genes (DEGs) between the clusters were identified. Three gene clusters were separated according to the DEGs and the associations among the two TRG subtypes, the three gene clusters, patient survival, and immune cells were investigated. Multiple datasets were used to successfully validate the utility of this risk score to gauge survival outcomes in patients. Key TRGs identified through these analyses included SOX12, LPCAT, MMP1, CLEC3B, and KRT17. HCC tumor tissue samples exhibited high levels of keratin 17 (KRT17) expression, and the knockdown of this gene hampered HCC cell proliferation and invasivity while promoting the upregulation of apoptosis-related markers and suppressing Akt/mTOR signaling activity. CONCLUSIONS: The use of T cell proliferation-based molecular subtyping and related predictive signatures can enable the effective prognostic assessment of HCC patients. KRT17 may also hold promise as a target for therapeutic interventions in the cancer type.
背景：T细胞是抗肿瘤免疫反应的重要介质。虽然已经鉴定出与T细胞增殖相关的基因（TRGs），但它们与肝细胞癌（HCC）患者预后结果的关系仍不明确。本研究试图从多个角度分析TRGs与HCC患者预后的关系。 方法：从多个数据集中获取33个TRGs的表达以及HCC患者的相关临床数据，并用于进行生物信息学分析。通过一致性聚类建立T细胞增殖相关分子亚型，同时使用最小绝对收缩和选择算子（LASSO）-Cox回归方法开发预测基因特征，并在外部队列中进行验证。这些结果还用于指导设计具有高准确性的列线图，以提高TRG评分的临床价值。分析还用于建立和验证候选生物标志物。 结果：HCC患者被分为两个基于TRG的簇，并鉴定出簇间差异表达基因（DEGs）。根据DEGs分离出三个基因簇，并研究了两种TRG亚型、三个基因簇、患者生存和免疫细胞之间的关联。使用多个数据集成功验证了该风险评分在评估患者生存结果方面的效用。通过这些分析确定的关键TRGs包括SOX12、LPCAT、MMP1、CLEC3B和KRT17。HCC肿瘤组织样本显示角蛋白17（KRT17）表达水平较高，该基因的敲低阻碍了HCC细胞的增殖和侵袭，同时促进凋亡相关标志物的上调并抑制Akt/mTOR信号活性。 结论：使用基于T细胞增殖的分子亚型和相关预测特征能够对HCC患者进行有效的预后评估。KRT17也有望成为该癌症类型治疗干预的靶点。
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