衰老基因在胃癌治疗、预后及肿瘤微环境中的作用。
The role of senescence genes in the treatment, prognosis, and tumor microenvironment of gastric cancer.
作者信息
Xuan Jinfeng, Li Feng, Li Jiongxian, Gong Chao, Li Jiaming, Mo Zhenchang, Jin Qinwen
机构信息
Department of Gastrointestinal Surgery, Wuzhou Red Cross Hospital 3-1 Xinxing 1st Road, Wanxiu District, Wuzhou 543000, Guangxi Zhuang Autonomous Region, China.
Department of Gastrointestinal Surgery, Guangxi Medical University Cancer Hospital 71 Hedi Road, Nanning 530021, Guangxi Zhuang Autonomous Region, China.
出版信息
Am J Transl Res. 2023 Dec 15;15(12):6926-6938. eCollection 2023.
AIM
Gastric cancer (GC) has a high incidence and poor prognosis. Senescence genes are suggested to participate in immune cell infiltration, thus affecting the immunotherapy of GC. In this research, we established a senescence-related GC model to explore and verify the role of senescence genes in the prognosis, treatment, and tumor microenvironment (TME) of GC.
METHODS
The TCGA GC (TCGA-STAD) dataset was used to screen key senescence genes from differentially expressed genes (DEGs). A prognostic risk model was trained utilizing the TCGA-STAD dataset and validated using an external GEO dataset. The CIBERSORT algorithm was run to explore the relationship between senescence genes and TME. The chemotherapy drug sensitivities in GC patients were calculated utilizing R package pRRophetic.
RESULTS
A total of 37 senescence-related DEGs were obtained. Five key senescence-related genes were further screened to establish a senescence-related risk model based on Cox regression. The survival status of GC patients in the high-risk group was found to be worse than that in the low-risk group. According to the results of gene set enrichment analysis, the senescence-related risk was mainly associated with cytokine activity, immune mechanism, and related pathways. By analyzing the sensitivity of common chemotherapy drugs in GC patients, it was revealed that the sensitivities of high-risk patients to Dasatinib, Lapatinib, and Pazopanib were lower than those of low-risk patients. The CIBERSORT algorithm was executed to analyze the TME in the high-risk group, revealing elevated levels of CD8 T cells, Macrophages M2, and resting Mast cells. In addition, decreased levels of resting memory CD4 T cells , resting NK cells, activated Dendritic cells, and activated Mast cells were also observed.
CONCLUSION
Senescence genes were related to the prognosis, response to chemotherapy drugs, and TME of GC. Our senescence-related risk model could forecast the survival of patients, their response to chemotherapy drugs, and the TME to a certain extent.
目的
胃癌（GC）发病率高且预后差。衰老基因被认为参与免疫细胞浸润，从而影响GC的免疫治疗。在本研究中，我们建立了一个与衰老相关的GC模型，以探索和验证衰老基因在GC预后、治疗及肿瘤微环境（TME）中的作用。
方法
利用TCGA GC（TCGA-STAD）数据集从差异表达基因（DEG）中筛选关键衰老基因。使用TCGA-STAD数据集训练预后风险模型，并使用外部GEO数据集进行验证。运行CIBERSORT算法以探索衰老基因与TME之间的关系。利用R包pRRophetic计算GC患者的化疗药物敏感性。
结果
共获得37个与衰老相关的DEG。进一步筛选出5个关键的衰老相关基因，基于Cox回归建立衰老相关风险模型。发现高危组GC患者的生存状况比低危组差。根据基因集富集分析结果，衰老相关风险主要与细胞因子活性、免疫机制及相关途径有关。通过分析GC患者对常用化疗药物的敏感性，发现高危患者对达沙替尼、拉帕替尼和帕唑帕尼的敏感性低于低危患者。执行CIBERSORT算法分析高危组的TME，发现CD8 T细胞、M2巨噬细胞和静息肥大细胞水平升高。此外，还观察到静息记忆CD4 T细胞、静息NK细胞、活化树突状细胞和活化肥大细胞水平降低。
结论
衰老基因与GC的预后、化疗药物反应及TME有关。我们的衰老相关风险模型在一定程度上可以预测患者的生存情况、对化疗药物的反应及TME。
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