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探索TCGA数据库以鉴定胃腺癌中的潜在预后基因。

Exploring TCGA database for identification of potential prognostic genes in stomach adenocarcinoma.

作者信息

Zhou Lin, Huang Wei, Yu He-Fen, Feng Ya-Juan, Teng Xu

机构信息

School of Information Science and Technology, University of Science and Technology of China, Hefei, 230026 Anhui China.

Beijing Key Laboratory for Tumor Invasion and Metastasis, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Capital Medical University, Beijing, 100069 China.

出版信息

Cancer Cell Int. 2020 Jun 23;20:264. doi: 10.1186/s12935-020-01351-3. eCollection 2020.

Abstract

BACKGROUND

Stomach adenocarcinoma (STAD) is the fifth most prevalent cancer in the world and ranks third among cancer-related deaths worldwide. The tumour microenvironment (TME) plays an important role in tumorigenesis, development, and metastasis. Hence, we calculated the immune and stromal scores to find the potential prognosis-related genes in STAD using bioinformatics analysis.

METHODS

The ESTIMATE algorithm was used to calculate the immune/stromal scores of the STAD samples. Functional enrichment analysis, protein-protein interaction (PPI) network analysis, and overall survival analysis were then performed on differential genes. And we validated these genes using data from the Gene Expression Omnibus database. Finally, we used the Human Protein Atlas (HPA) databases to verify these genes at the protein levels by IHC.

RESULTS

Data analysis revealed correlation between stromal/immune scores and the TNM staging system. The top 10 core genes extracted from the PPI network, and primarily involved in immune responses, extracellular matrix, and cell adhesion. There are 31 genes have been validated with poor prognosis and 16 genes were upregulated in tumour tissues compared with normal tissues at the protein level.

CONCLUSIONS

In summary, we identified genes associated with the tumour microenvironment with prognostic implications in STAD, which may become potential therapeutic markers leading to better clinical outcomes.

摘要

背景

胃腺癌(STAD)是全球第五大常见癌症,在全球癌症相关死亡中排名第三。肿瘤微环境(TME)在肿瘤发生、发展和转移中起重要作用。因此,我们使用生物信息学分析计算免疫和基质评分,以寻找STAD中潜在的预后相关基因。

方法

使用ESTIMATE算法计算STAD样本的免疫/基质评分。然后对差异基因进行功能富集分析、蛋白质-蛋白质相互作用(PPI)网络分析和总生存分析。我们使用基因表达综合数据库的数据验证了这些基因。最后,我们使用人类蛋白质图谱(HPA)数据库通过免疫组化在蛋白质水平验证这些基因。

结果

数据分析揭示了基质/免疫评分与TNM分期系统之间的相关性。从PPI网络中提取的前10个核心基因,主要参与免疫反应、细胞外基质和细胞粘附。有31个基因被验证预后不良,16个基因在蛋白质水平上与正常组织相比在肿瘤组织中上调。

结论

总之,我们在STAD中鉴定了与肿瘤微环境相关且具有预后意义的基因,这些基因可能成为导致更好临床结果的潜在治疗标志物。

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