开发和验证一种新型与 T 细胞增殖相关的预后模型，以预测黑色素瘤患者的生存和免疫治疗获益。

BACKGROUND: T cell plays a crucial role in the occurrence and progression of Skin cutaneous melanoma (SKCM). This research aims to identify the actions of T cell proliferation-related genes (TRGs) on the prognosis and immunotherapy response of tumor patients. METHOD: The clinical manifestation and gene expression data of SKCM patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. T cell proliferation-related molecular subtypes were identified utilizing consensus clustering. Subsequently, Cox and Lasso regression analysis was conducted to identify six prognostic genes, and a prognostic signature was constructed. A series of experiments, such as qRT-PCR, Western blotting and CCK8 assay, were then conducted to verify the reliability of the six genes. RESULTS: In this study, a grading system was established to forecast survival time and responses to immunotherapy, providing an overview of the tumoral immune landscape. Meanwhile, we identified six prognostic signature genes. Notably, we also found that C1RL protein may inhibit the growth of melanoma cell lines. CONCLUSION: The scoring system depending on six prognostic genes showed great efficiency in predicting survival time. The system could help to forecast prognosis of SKCM patients, characterize SKCM immunological condition, assess patient immunotherapy response.

背景：T 细胞在皮肤黑色素瘤（SKCM）的发生和发展中起着至关重要的作用。本研究旨在确定 T 细胞增殖相关基因（TRGs）对肿瘤患者预后和免疫治疗反应的作用。

方法：从癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）中获取 SKCM 患者的临床表现和基因表达数据。利用共识聚类识别 T 细胞增殖相关的分子亚型。随后，进行 Cox 和 Lasso 回归分析以确定六个预后基因，并构建预后特征。然后进行一系列实验，如 qRT-PCR、Western blot 和 CCK8 测定，以验证这六个基因的可靠性。

结果：本研究建立了一个分级系统来预测生存时间和免疫治疗反应，全面描绘了肿瘤免疫景观。同时，我们确定了六个预后特征基因。值得注意的是，我们还发现 C1RL 蛋白可能抑制黑色素瘤细胞系的生长。

结论：基于六个预后基因的评分系统在预测生存时间方面显示出了很高的效率。该系统有助于预测 SKCM 患者的预后，描绘 SKCM 的免疫状况，评估患者的免疫治疗反应。