Characterization of the Prognosis and Tumor Microenvironment of Cellular Senescence-related Genes through scRNA-seq and Bulk RNA-seq Analysis in GC.

Guoxiang Guo, Zhifeng Zhou, Shuping Chen, Jiaqing Cheng, Yang Wang, Tianshu Lan, Yunbin Ye
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Abstract

Background: Cellular senescence (CS) is thought to be the primary cause of cancer development and progression. This study aimed to investigate the prognostic role and molecular subtypes of CS-associated genes in gastric cancer (GC).

Materials and methods: The CellAge database was utilized to acquire CS-related genes. Expression data and clinical information of GC patients were obtained from The Cancer Genome Atlas (TCGA) database. Patients were then grouped into distinct subtypes using the "Consesus- ClusterPlus" R package based on CS-related genes. An in-depth analysis was conducted to assess the gene expression, molecular function, prognosis, gene mutation, immune infiltration, and drug resistance of each subtype. In addition, a CS-associated risk model was developed based on Cox regression analysis. The nomogram, constructed on the basis of the risk score and clinical factors, was formulated to improve the clinical application of GC patients. Finally, several candidate drugs were screened based on the Cancer Therapeutics Response Portal (CTRP) and PRISM Repurposing dataset.

Results: According to the cluster result, patients were categorized into two molecular subtypes (C1 and C2). The two subtypes revealed distinct expression levels, overall survival (OS) and clinical presentations, mutation profiles, tumor microenvironment (TME), and drug resistance. A risk model was developed by selecting eight genes from the differential expression genes (DEGs) between two molecular subtypes. Patients with GC were categorized into two risk groups, with the high-risk group exhibiting a poor prognosis, a higher TME level, and increased expression of immune checkpoints. Function enrichment results suggested that genes were enriched in DNA repaired pathway in the low-risk group. Moreover, the Tumor Immune Dysfunction and Exclusion (TIDE) analysis indicated that immunotherapy is likely to be more beneficial for patients in the low-risk group. Drug analysis results revealed that several drugs, including ML210, ML162, dasatinib, idronoxil, and temsirolimus, may contribute to the treatment of GC patients in the high-risk group. Moreover, the risk model genes presented a distinct expression in single-cell levels in the GSE150290 dataset.

Conclusion: The two molecular subtypes, with their own individual OS rate, expression patterns, and immune infiltration, lay the foundation for further exploration into the GC molecular mechanism. The eight gene signatures could effectively predict the GC prognosis and can serve as reliable markers for GC patients.

通过GC中的scRNA-Seq和Bulk-RNA-Seq分析表征细胞衰老相关基因的预后和肿瘤微环境。
背景:细胞衰老(CS)被认为是癌症发生发展的主要原因。本研究旨在探讨CS相关基因在癌症(GC)中的预后作用和分子亚型。方法:利用CellAge数据库获取CS相关基因。GC患者的表达数据和临床信息来自癌症基因组图谱(TCGA)数据库。然后使用基于CS相关基因的“ConsesusClusterPlus”R包将患者分组为不同的亚型。对每个亚型的基因表达、分子功能、预后、基因突变、免疫浸润和耐药性进行了深入分析。此外,基于Cox回归分析,建立了CS相关风险模型。根据风险评分和临床因素构建列线图,以提高GC患者的临床应用。最后,基于癌症治疗反应门户(CTRP)和PRISM再利用数据集筛选了几种候选药物。结果:根据聚类结果,将患者分为两种分子亚型(C1和C2)。这两种亚型显示出不同的表达水平、总生存期(OS)和临床表现、突变谱、肿瘤微环境(TME)和耐药性。通过从两种分子亚型之间的差异表达基因(DEG)中选择八个基因来开发风险模型。GC患者被分为两个风险组,其中高危组表现出预后不良、TME水平较高和免疫检查点表达增加。功能富集结果表明,在低风险组中,基因在DNA修复途径中富集。此外,肿瘤免疫功能障碍和排除(TIDE)分析表明,免疫疗法可能对低风险组的患者更有益。药物分析结果显示,包括ML210、ML162、达沙替尼、依罗诺西和替莫西在内的几种药物可能有助于治疗高危人群中的GC患者。此外,在GSE150290数据集中,风险模型基因在单细胞水平上表现出不同的表达。结论:这两种分子亚型具有各自的OS率、表达模式和免疫浸润,为进一步探索GC分子机制奠定了基础。这八个基因特征可以有效地预测GC的预后,并可以作为GC患者的可靠标志物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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