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差异表达基因的综合分析揭示了子宫内膜癌的一个 17 基因预后特征。

Integrative Analysis of Differently Expressed Genes Reveals a 17-Gene Prognosis Signature for Endometrial Carcinoma.

机构信息

Department of Gynecology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Liaoning, China.

Department of Information Engineering, Shenyang Polytechnic College, Liaoning, China.

出版信息

Biomed Res Int. 2021 Jul 14;2021:4804694. doi: 10.1155/2021/4804694. eCollection 2021.

Abstract

Endometrial carcinoma (EC) is the fifth widely occurring malignant neoplasm among women all over the world. However, there is still lacking efficacy indicators for EC's prognosis. Here, we analyzed two databases including an RNA-sequencing-based TCGA dataset and a microarray-based GSE106191. After normalizing the raw data, we identified 114 common genes with upregulation and 308 common genes with downregulation in both the TCGA and GSE106191 databases. Bioinformatics analysis showed that the differently expressed genes in EC were related to the IL17 signaling pathway, PI3K-Akt signaling pathway, and cGMP-PKG signaling pathway. Furthermore, we performed the least absolute shrinkage and selection operator (LASSO) Cox regression analysis and generated a signature featuring 17 prognosis-related genes (MAL2, ANKRD22, METTL7B, IL32, ERFE, OAS1, TRPC1, SRPX, RAPGEF4, PSD3, SIMC1, TRPC6, WFS1, PGR, PAMR1, KCNK6, and FAM189A2) and found that it could predict OS in EC patients. The further analysis showed that OAS1, MAL2, ANKRD22, METTL7B, and IL32 were significantly upregulated in EC samples after comparison with normal samples. However, TRPC1, SRPX, RAPGEF4, PSD3, SIMC1, TRPC6, WFS1, PGR, PAMR1, KCNK6, and FAM189A2 were significantly downregulated in EC samples in comparison with normal samples. And correlation analysis showed that our results showed that the expressions of 17 prognosis-related hub genes were significantly correlated based on Pearson correlation. We here offer a newly genetic biomarker for the prediction of EC patients' prognosis.

摘要

子宫内膜癌(EC)是全球女性中第五种广泛发生的恶性肿瘤。然而,EC 的预后仍然缺乏疗效指标。在这里,我们分析了两个数据库,包括一个基于 RNA 测序的 TCGA 数据集和一个基于微阵列的 GSE106191 数据集。在对原始数据进行标准化后,我们在 TCGA 和 GSE106191 数据库中都鉴定出了 114 个上调的常见基因和 308 个下调的常见基因。生物信息学分析表明,EC 中差异表达的基因与 IL17 信号通路、PI3K-Akt 信号通路和 cGMP-PKG 信号通路有关。此外,我们进行了最小绝对收缩和选择算子(LASSO)Cox 回归分析,并生成了一个包含 17 个与预后相关的基因(MAL2、ANKRD22、METTL7B、IL32、ERFE、OAS1、TRPC1、SRPX、RAPGEF4、PSD3、SIMC1、TRPC6、WFS1、PGR、PAMR1、KCNK6 和 FAM189A2)的特征,并发现它可以预测 EC 患者的 OS。进一步分析表明,与正常样本相比,EC 样本中 OAS1、MAL2、ANKRD22、METTL7B 和 IL32 的表达显著上调。然而,与正常样本相比,EC 样本中 TRPC1、SRPX、RAPGEF4、PSD3、SIMC1、TRPC6、WFS1、PGR、PAMR1、KCNK6 和 FAM189A2 的表达显著下调。并且相关分析表明,我们的结果表明,基于 Pearson 相关性,17 个预后相关的核心基因的表达具有显著相关性。我们在此提供了一种新的遗传生物标志物,用于预测 EC 患者的预后。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22ae/8298166/b104bab3eef1/BMRI2021-4804694.001.jpg

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