School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian province, China.
Laboratory of Immuno- oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China.
Recent Pat Anticancer Drug Discov. 2024;19(4):530-542. doi: 10.2174/0115748928255417230924191157.
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).
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.
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.
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.
细胞衰老（CS）被认为是癌症发生和发展的主要原因。本研究旨在探讨 CS 相关基因在胃癌（GC）中的预后作用和分子亚型。
利用 CellAge 数据库获取 CS 相关基因。从癌症基因组图谱（TCGA）数据库获取 GC 患者的表达数据和临床信息。然后，使用“Consesus-ClusterPlus”R 包根据 CS 相关基因将患者分为不同的亚型。对每个亚型进行深入分析，评估基因表达、分子功能、预后、基因突变、免疫浸润和耐药性。此外，还基于 Cox 回归分析构建了 CS 相关风险模型。基于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。
根据聚类结果，患者分为两个分子亚型（C1 和 C2）。这两个亚型的表达水平、总生存期（OS）和临床表现、突变谱、肿瘤微环境（TME）和耐药性均存在显著差异。通过从两个分子亚型的差异表达基因（DEGs）中选择 8 个基因，构建了风险模型。GC 患者被分为两个风险组，高风险组预后较差，TME 水平较高，免疫检查点表达增加。功能富集结果表明，低风险组的基因富集在 DNA 修复途径中。此外，肿瘤免疫功能障碍和排除（TIDE）分析表明，免疫治疗可能对低风险组患者更有益。药物分析结果表明，包括 ML210、ML162、达沙替尼、依地膦酸和替西罗莫司在内的几种药物可能有助于治疗高风险组的 GC 患者。此外，风险模型基因在 GSE150290 数据集的单细胞水平上呈现出明显的表达差异。
两个具有各自独立 OS 率、表达模式和免疫浸润的分子亚型为进一步探索 GC 分子机制奠定了基础。这 8 个基因特征可以有效地预测 GC 的预后，并可作为 GC 患者的可靠标志物。
