A novel prognostic index of stomach adenocarcinoma based on immunogenomic landscape analysis and immunotherapy options

IF 2.8 4区 医学 Q2 PATHOLOGY
Weijie Xue , Bingzi Dong , Yixiu Wang , Yuwei Xie , Pu Li , Zhiqi Gong , Zhaojian Niu
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引用次数: 8

Abstract

Stomach adenocarcinoma (STAD) is one of the most common malignant tumors worldwide. In this study, we attempted to construct a valid immune-associated gene prognostic index risk model that can predict the survival of patients with STAD and the efficacy of immune checkpoint inhibitors (ICIs) treatment. Transcriptome, clinical, and gene mutational data were obtained from the TCGA database. Immune-related genes were downloaded from the ImmPort and InnateDB databases. A total of 493 immune-related genes were identified to be enriched in functions associated with immune response, as well as in immune and tumor-related pathways. Further, 36 candidate genes related to the overall survival (OS) of STAD were obtained by weighted gene co-expression network analysis (WGCNA). Next, based on a Cox regression analysis, we constructed an immune-associated gene prognostic index (IAGPI) risk model based on eight genes, which was verified using the GEO STAD cohort. The patients were divided into two subsets according to their risk score. Patients in the low-risk group had better OS than those in the high-risk group. In the low-risk group, there were more CD8, activated memory CD4, and follicular helper T cells, and M1 macrophages, whereas monocytes, M2 macrophages, eosinophils, and neutrophils were more abundant in the high-risk group. The patients in the low-risk group were more sensitive to ICIs therapy. The IAGPI risk model can precisely predict the prognosis, reflect the tumor immune microenvironment, and predict the efficacy of ICIs therapy in patients with STAD.

基于免疫基因组景观分析和免疫治疗方案的胃腺癌新的预后指标
胃腺癌(STAD)是全球最常见的恶性肿瘤之一。在本研究中,我们试图构建一个有效的免疫相关基因预后指数风险模型,该模型可以预测STAD患者的生存和免疫检查点抑制剂(ici)治疗的疗效。转录组、临床和基因突变数据来自TCGA数据库。从import和InnateDB数据库下载免疫相关基因。共鉴定出493个免疫相关基因,这些基因在与免疫应答相关的功能以及免疫和肿瘤相关途径中富集。进一步,通过加权基因共表达网络分析(WGCNA)获得36个与STAD总生存期(OS)相关的候选基因。接下来,在Cox回归分析的基础上,我们构建了基于8个基因的免疫相关基因预后指数(IAGPI)风险模型,并使用GEO STAD队列进行验证。根据患者的风险评分将患者分为两个亚组。低危组患者的OS优于高危组。低危组CD8、活化记忆CD4、滤泡辅助性T细胞、M1巨噬细胞较多,高危组单核细胞、M2巨噬细胞、嗜酸性粒细胞、中性粒细胞较多。低危组患者对ICIs治疗更敏感。IAGPI风险模型可以准确预测预后,反映肿瘤免疫微环境,预测ICIs治疗STAD患者的疗效。
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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来源期刊
CiteScore
8.90
自引率
0.00%
发文量
78
审稿时长
11.5 weeks
期刊介绍: Under new editorial leadership, Experimental and Molecular Pathology presents original articles on disease processes in relation to structural and biochemical alterations in mammalian tissues and fluids and on the application of newer techniques of molecular biology to problems of pathology in humans and other animals. The journal also publishes selected interpretive synthesis reviews by bench level investigators working at the "cutting edge" of contemporary research in pathology. In addition, special thematic issues present original research reports that unravel some of Nature''s most jealously guarded secrets on the pathologic basis of disease. Research Areas include: Stem cells; Neoangiogenesis; Molecular diagnostics; Polymerase chain reaction; In situ hybridization; DNA sequencing; Cell receptors; Carcinogenesis; Pathobiology of neoplasia; Complex infectious diseases; Transplantation; Cytokines; Flow cytomeric analysis; Inflammation; Cellular injury; Immunology and hypersensitivity; Athersclerosis.
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