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基于mA调控因子的食管癌治疗分子亚型及潜在小分子药物的鉴定

Identification of Molecular Subtypes and Potential Small-Molecule Drugs for Esophagus Cancer Treatment Based on mA Regulators.

作者信息

Li Jianjun, Zhu Hongbo, Yang Qiao, Xiao Hua, Wu Haibiao, Fang Zhe, Li Wenjun, Cai Manbo

机构信息

Department of Oncology Radiotherapy, The First Affiliated Hospital, Hengyang Medical School, University of South China, No. 69 Chuanshan Road, Hengyang, Hunan, China.

出版信息

J Oncol. 2022 Jan 13;2022:5490461. doi: 10.1155/2022/5490461. eCollection 2022.

DOI:10.1155/2022/5490461
PMID:35069736
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8776445/
Abstract

BACKGROUND

Esophagus cancer (ESCA) is the sixth most frequent cancer in males, with 5-year overall survival of 15%-25%. RNA modifications function critically in cancer progression, and mA regulators are associated with ESCA prognosis. This study further revealed correlations between mA and ESCA development.

METHODS

Univariate Cox regression analysis and consensus clustering were applied to determine molecular subtypes. Functional pathways and gene ontology terms were enriched by gene set enrichment analysis. Protein-protein interaction (PPI) analysis on differentially expressed genes (DEGs) was conducted for hub gene screening. Public drug databases were employed to study the interactions between hub genes and small molecules.

RESULTS

Three molecular subtypes related to ESCA prognosis were determined. Based on multiple analyses among molecular subtypes, 146 DEGs were screened, and a PPT network of 15 hub genes was visualized. Finally, 8 potential small-molecule drugs (BMS-754807, gefitinib, neratinib, zuclopenthixol, puromycin, sulfasalazine, and imatinib) were identified for treating ESCA.

CONCLUSIONS

This study applied a new approach to analyzing the relation between mA and ESCA prognosis, providing a reference for exploring potential targets and drugs for ESCA treatment.

摘要

背景

食管癌(ESCA)是男性中第六大常见癌症,5年总生存率为15%-25%。RNA修饰在癌症进展中起关键作用,且mA调节因子与ESCA预后相关。本研究进一步揭示了mA与ESCA发生之间的相关性。

方法

应用单因素Cox回归分析和一致性聚类来确定分子亚型。通过基因集富集分析来富集功能通路和基因本体术语。对差异表达基因(DEGs)进行蛋白质-蛋白质相互作用(PPI)分析以筛选枢纽基因。利用公共药物数据库研究枢纽基因与小分子之间的相互作用。

结果

确定了三种与ESCA预后相关的分子亚型。基于分子亚型间的多项分析,筛选出146个DEGs,并构建了一个包含15个枢纽基因的PPI网络。最终,鉴定出8种潜在的小分子药物(BMS-754807、吉非替尼、奈拉替尼、氯普噻吨、嘌呤霉素、柳氮磺胺吡啶和伊马替尼)用于治疗ESCA。

结论

本研究应用了一种新方法来分析mA与ESCA预后之间的关系,为探索ESCA治疗的潜在靶点和药物提供了参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef9a/8776445/ee31fd7eb21b/JO2022-5490461.009.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef9a/8776445/ee31fd7eb21b/JO2022-5490461.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef9a/8776445/866cfded5839/JO2022-5490461.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef9a/8776445/a7e65d27cb0f/JO2022-5490461.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef9a/8776445/1dc39476f4b8/JO2022-5490461.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef9a/8776445/09c6cb8835b0/JO2022-5490461.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef9a/8776445/56344afcfc31/JO2022-5490461.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef9a/8776445/3b919a5e67f4/JO2022-5490461.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef9a/8776445/8d95495bcb6b/JO2022-5490461.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef9a/8776445/a3e1f74baa14/JO2022-5490461.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef9a/8776445/ee31fd7eb21b/JO2022-5490461.009.jpg

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