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对Notch信号通路相关基因进行综合分子分析以预测胃癌患者的预后和免疫治疗反应

Comprehensive Molecular Analyses of Notch Pathway-Related Genes to Predict Prognosis and Immunotherapy Response in Patients with Gastric Cancer.

作者信息

Song Yinsen, Gao Na, Yang Zhenzhen, Zhang Sisen, Fan Tianli, Zhang Baojun

机构信息

School of Basic Medical Sciences, Xi'an Jiaotong University, Translational Medicine Research Center, Zhengzhou People's Hospital, Zhengzhou, China.

Translational Medicine Research Center, Zhengzhou People's Hospital, Zhengzhou, China.

出版信息

J Oncol. 2023 Jan 24;2023:2205083. doi: 10.1155/2023/2205083. eCollection 2023.

Abstract

Gastric cancer (GC) is a highly molecular heterogeneous tumor with unfavorable outcomes. The Notch signaling pathway is an important regulator of immune cell differentiation and has been associated with autoimmune disorders, the development of tumors, and immunomodulation caused by tumors. In this study, by developing a gene signature based on genes relevant to the Notch pathway, we could improve our ability to predict the outcome of patients with GC. From the TCGA database, RNA sequencing data of GC tumors and associated normal tissues were obtained. Microarray data were collected from GEO datasets. The Molecular Signature Database (MSigDB) was accessed in order to retrieve sets of human Notch pathway-related genes (NPRGs). The LASSO analysis performed on the TCGA cohort was used to generate a multigene signature based on prognostic NPRGs. In order to validate the gene signature, the GEO cohort was utilized. Using the CIBERSORT method, we were able to determine the amounts of immune cell infiltration in the GC. In this study, a total of 21 differentially expressed NPRGs were obtained between GC specimens and nontumor specimens. The construction of a prognostic prediction model for patients with GC involved the identification and selection of three different NPRGs. According to the appropriate cutoff value, the patients with GC were divided into two groups: those with a low risk and those with a high risk. The time-dependent ROC curves demonstrated that the new model had satisfactory performance when it came to prognostic prediction. Multivariate assays confirmed that the risk score was an independent marker that may be used to predict the outcome of GC. In addition, the generated nomogram demonstrated a high level of predictive usefulness. Moreover, the scores of immunological infiltration of the majority of immune cells were distinctly different between the two groups, and the low-risk group responded to immunotherapy in a significantly greater degree. According to the results of a functional enrichment study of candidate genes, there are multiple pathways and processes associated with cancer. Taken together, a new gene model associated with the Notch pathway may be utilized for the purpose of predicting the prognosis of GC. One potential method of treatment for GC is to focus on NPRGs.

摘要

胃癌(GC)是一种分子异质性高且预后不良的肿瘤。Notch信号通路是免疫细胞分化的重要调节因子,与自身免疫性疾病、肿瘤发展以及肿瘤引起的免疫调节相关。在本研究中,通过基于与Notch通路相关的基因开发基因特征,我们能够提高预测GC患者预后的能力。从TCGA数据库中获取了GC肿瘤及相关正常组织的RNA测序数据。从GEO数据集中收集了微阵列数据。访问分子特征数据库(MSigDB)以检索人类Notch通路相关基因(NPRGs)集。对TCGA队列进行的LASSO分析用于基于预后NPRGs生成多基因特征。为了验证该基因特征,使用了GEO队列。使用CIBERSORT方法,我们能够确定GC中免疫细胞浸润的数量。在本研究中,GC标本与非肿瘤标本之间共获得21个差异表达的NPRGs。构建GC患者的预后预测模型涉及识别和选择三种不同的NPRGs。根据适当的临界值,将GC患者分为两组:低风险组和高风险组。时间依赖性ROC曲线表明,新模型在预后预测方面具有令人满意的性能。多变量分析证实风险评分是可用于预测GC预后的独立标志物。此外,生成的列线图显示出高度的预测实用性。而且,两组之间大多数免疫细胞的免疫浸润评分明显不同,低风险组对免疫治疗的反应程度明显更高。根据候选基因的功能富集研究结果,有多个与癌症相关的途径和过程。综上所述,一种与Notch通路相关的新基因模型可用于预测GC的预后。GC的一种潜在治疗方法是关注NPRGs。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4aea/9889149/8d39dfe9ad3d/JO2023-2205083.001.jpg

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