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生物信息学分析结直肠癌相关预后基因及 CXCL8 的表达。

Bioinformatics Analysis of Prognosis-Related Genes and Expression of CXCL8 in Colorectal Cancer.

机构信息

Department of Pulmonary and Critical Care Medicine, The Second Affiliated Hospital of Soochow University, Suzhou 215004, China.

Department of Nuclear Accident Medical Emergency, The Second Affiliated Hospital of Soochow University, Suzhou 215004, China.

出版信息

Biomed Res Int. 2022 Jul 6;2022:3149887. doi: 10.1155/2022/3149887. eCollection 2022.

DOI:10.1155/2022/3149887
PMID:35845924
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9279071/
Abstract

BACKGROUND

Colorectal cancer (CRC), one of the main causes of death, remains a leading cause of mortality in gastrointestinal cancer and tends to affect the younger generation. However, the pathological process of colorectal cancer is unclear. Exploring potential pathogenesis and therapeutic targets of CRC is significant as its high prevalence and high mortality. Nowadays, the rapid development of bioinformatics provides us an opportunity to explore potential molecular markers of CRC.

MATERIALS AND METHODS

First, three CRC gene chips with paracancerous controls were downloaded from the Gene Expression Omnibus (GEO) database. Second, after combining and batch correcting the three chips using the R language and Perl language, the differentially expressed genes (DEGs) were selected to investigate how they affect the CRC occurrence and development by GO and KEGG enrichment analysis. Third, based on the STRING website and the Cytoscape software, the protein-protein interaction (PPI) network was constructed and the core genes were screened out. Finally, through polymerase chain reaction (PCR) and immunohistochemistry (IHC), the expression and function of the core gene CXCL8 in CRC were explored.

RESULTS

GSE10950, GSE44076, and GSE75970, including 126 intestinal cancer samples and 126 paracancer samples, were screened as the datasets. 192 DEGs were screened, including 43 upregulated genes and 149 downregulated genes. Through the DEGs screened out, GO enrichment analysis, KEGG enrichment analysis, and the construction of PPI interaction network were carried out. Finally, according to the nodes and edges in the PPI network, the DEGs were sorted and the core genes were selected. Through basic experiments, the first ranked CXCL8 was further studied, and the results suggest that the expression of CXCL8 is related to the proliferation, migration, invasion, and even distant metastasis of CRC.

CONCLUSION

The present study showed that DEGs of CRC are associated with multiple tumor-related biological processes and signaling pathways. The core gene CXCL8 has the potential to be a new therapeutic target for CRC.

摘要

背景

结直肠癌(CRC)是主要的死亡原因之一,仍是胃肠道癌症死亡的主要原因,并倾向于影响年轻一代。然而,CRC 的病理过程尚不清楚。探索 CRC 的潜在发病机制和治疗靶点具有重要意义,因为其发病率和死亡率都很高。如今,生物信息学的快速发展为我们探索 CRC 的潜在分子标志物提供了机会。

材料和方法

首先,从基因表达综合数据库(GEO)下载了三个带有癌旁对照的 CRC 基因芯片。其次,使用 R 语言和 Perl 语言对三个芯片进行组合和批量校正后,选择差异表达基因(DEGs),通过 GO 和 KEGG 富集分析来研究它们如何影响 CRC 的发生和发展。然后,基于 STRING 网站和 Cytoscape 软件构建蛋白质-蛋白质相互作用(PPI)网络,并筛选出核心基因。最后,通过聚合酶链反应(PCR)和免疫组织化学(IHC),探索 CRC 中核心基因 CXCL8 的表达和功能。

结果

筛选出 GSE10950、GSE44076 和 GSE75970 三个数据集,包含 126 个肠癌样本和 126 个癌旁样本。筛选出 192 个 DEGs,包括 43 个上调基因和 149 个下调基因。通过筛选出的 DEGs 进行 GO 富集分析、KEGG 富集分析和 PPI 互作网络构建,最后根据 PPI 网络中的节点和边对 DEGs 进行排序,选择核心基因。通过基础实验,进一步研究排名第一的 CXCL8,结果表明 CXCL8 的表达与 CRC 的增殖、迁移、侵袭甚至远处转移有关。

结论

本研究表明 CRC 的 DEGs 与多个肿瘤相关的生物学过程和信号通路有关。核心基因 CXCL8 有可能成为 CRC 的新治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef35/9279071/fa408dcff892/BMRI2022-3149887.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef35/9279071/9ae362d65c10/BMRI2022-3149887.001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef35/9279071/fa408dcff892/BMRI2022-3149887.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef35/9279071/9ae362d65c10/BMRI2022-3149887.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef35/9279071/dd412eace2cc/BMRI2022-3149887.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef35/9279071/d9bac2b69a42/BMRI2022-3149887.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef35/9279071/1a8d2cb4d468/BMRI2022-3149887.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef35/9279071/9e2f7557ea7c/BMRI2022-3149887.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef35/9279071/744bfb88ffcc/BMRI2022-3149887.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef35/9279071/9dc5474a34a2/BMRI2022-3149887.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef35/9279071/c176c3875269/BMRI2022-3149887.008.jpg
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