DataSheet_1_Integrated analysis of single-cell and bulk RNA-sequencing identifies a signature based on T-cell marker genes to predict prognosis and therapeutic response in lung squamous cell carcinoma.zip

Cancer immunotherapy is an increasingly successful strategy for treating patients with advanced or conventionally drug-resistant cancers. T cells have been proved to play important roles in anti-tumor and tumor microenvironment shaping, while these roles have not been explained in lung squamous cell carcinoma (LUSC). In this study, we first performed a comprehensive analysis of single-cell RNA sequencing (scRNA-seq) data from the gene expression omnibus (GEO) database to identify 72 T-cell marker genes. Subsequently, we constructed a 5-gene prognostic signature in the training cohort based on the T-cell marker genes from the cancer genome atlas (TCGA) database, which was further validated in the testing cohort and GEO cohort. The areas under the receiver operating characteristic curve at 1-, 3-, and 5-years were 0.614, 0.713 and 0.702 in the training cohort, 0.669, 0.603 and 0.645 in the testing cohort, 0.661, 0.628 and 0.590 in the GEO cohort, respectively. Furthermore, we created a highly reliable nomogram to facilitate clinical application. Gene set enrichment analysis showed that immune-related pathways were mainly enriched in the high-risk group. Tumor immune microenvironment indicated that high-risk group exhibited higher immune score, stromal score, and immune cell infiltration levels. Moreover, genes of the immune checkpoints and human leukocyte antigen family were all overexpressed in high-risk group. Drug sensitivity revealed that low-risk group was sensitive to 8 chemotherapeutic drugs and high-risk group to 4 chemotherapeutic drugs. In short, our study reveals a novel prognostic signature based on T-cell marker genes, which provides a new target and theoretical support for LUSC patients.

癌症免疫治疗作为一种日益有效的治疗手段，正被广泛应用于治疗晚期或传统药物难以奏效的癌症患者。研究表明，T细胞在抗肿瘤和肿瘤微环境的塑造中发挥着至关重要的作用，然而这些作用在肺鳞状细胞癌（LUSC）中尚未得到充分阐释。在本研究中，我们首先对基因表达综合数据库（GEO）中的单细胞RNA测序（scRNA-seq）数据进行了全面分析，以识别72个T细胞标志基因。随后，基于癌症基因组图谱（TCGA）数据库中的T细胞标志基因，我们在训练队列中构建了一个包含5个基因的预后特征，并在测试队列和GEO队列中进一步验证了其有效性。在训练队列中，1年、3年和5年的受试者工作特征曲线下面积（AUC）分别为0.614、0.713和0.702；在测试队列中分别为0.669、0.603和0.645；在GEO队列中分别为0.661、0.628和0.590。此外，我们创建了一个高度可靠的诺模图，以促进其临床应用。基因集富集分析显示，免疫相关通路主要在高风险组中富集。肿瘤免疫微环境分析表明，高风险组表现出更高的免疫评分、间质评分和免疫细胞浸润水平。此外，免疫检查点和人类白细胞抗原家族的基因在高风险组中均过表达。药物敏感性分析显示，低风险组对8种化疗药物敏感，而高风险组对4种化疗药物敏感。总之，我们的研究揭示了基于T细胞标志基因的新型预后特征，为LUSC患者提供了新的治疗靶点和理论支持。