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多标记基因注释分析在来自中国人群的胃癌 GWAS 数据中的应用。

Multi-marker analysis of genomic annotation on gastric cancer GWAS data from Chinese populations.

机构信息

Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.

Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Centre For Cancer Medicine, Nanjing Medical University, Nanjing, 211166, China.

出版信息

Gastric Cancer. 2019 Jan;22(1):60-68. doi: 10.1007/s10120-018-0841-y. Epub 2018 Jun 1.

Abstract

BACKGROUND

Gastric cancer (GC) is one of the high-incidence and high-mortality cancers all over the world. Though genome-wide association studies (GWASs) have found some genetic loci related to GC, they could only explain a small fraction of the potential pathogenesis for GC.

METHODS

We used multi-marker analysis of genomic annotation (MAGMA) to analyze pathways from four public pathway databases based on Chinese GWAS data including 2631 GC cases and 4373 controls. The differential expressions of selected genes in certain pathways were assessed on the basis of The Cancer Genome Atlas database. Immunohistochemistry was also conducted on 55 GC and paired normal tissues of Chinese patients to localize the expression of genes and further validate the differential expression.

RESULTS

We identified three pathways including chemokine signaling pathway, potassium ion import pathway, and interleukin-7 (IL7) pathway, all of which were associated with GC risk. NMI in IL7 pathway and RAC1 in chemokine signaling pathway might be two new candidate genes involved in GC pathogenesis. Additionally, NMI and RAC1 were overexpressed in GC tissues than normal tissues.

CONCLUSION

Immune and inflammatory associated processes and potassium transporting might participate in the development of GC. Besides, NMI and RAC1 might represent two new key genes related to GC. Our findings might give new insight into the biological mechanism and immunotherapy for GC.

摘要

背景

胃癌(GC)是全球高发和高死亡率的癌症之一。尽管全基因组关联研究(GWAS)已经发现了一些与 GC 相关的遗传位点,但它们只能解释 GC 潜在发病机制的一小部分。

方法

我们使用基于中国 GWAS 数据的四个公共途径数据库的基因组注释多标记分析(MAGMA)方法,分析了 2631 例 GC 病例和 4373 例对照的途径。基于癌症基因组图谱数据库,评估了某些途径中选定基因的差异表达。还对 55 例中国 GC 患者及其配对正常组织进行了免疫组织化学染色,以定位基因的表达并进一步验证差异表达。

结果

我们确定了三条途径,包括趋化因子信号通路、钾离子导入通路和白细胞介素-7(IL7)通路,这些途径均与 GC 风险相关。IL7 通路中的 NMI 和趋化因子信号通路中的 RAC1 可能是参与 GC 发病机制的两个新候选基因。此外,GC 组织中的 NMI 和 RAC1 表达高于正常组织。

结论

免疫和炎症相关过程以及钾转运可能参与了 GC 的发生发展。此外,NMI 和 RAC1 可能代表与 GC 相关的两个新的关键基因。我们的研究结果可能为 GC 的生物学机制和免疫治疗提供新的思路。

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