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基于癌症中免疫和特征基因集活性变化的胶质瘤亚型

Glioma Subtypes Based on the Activity Changes of Immunologic and Hallmark Gene Sets in Cancer.

作者信息

Chen Sihan

机构信息

Taikang (Ningbo) Hospital Co., Ltd. Yinzhou, Ningbo, China.

出版信息

Front Endocrinol (Lausanne). 2022 Jun 13;13:879233. doi: 10.3389/fendo.2022.879233. eCollection 2022.

DOI:10.3389/fendo.2022.879233
PMID:35774141
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9236851/
Abstract

PURPOSE

Glioma is the most common primary cranial brain tumor that arises from the cancelation of glial cells (which can be in the brain or spinal cord). It is due to innate genetic risk factors or induced by a carcinogenic environment. If left untreated, the disease has a poor prognosis.

METHODS

In this study, we downloaded glioma data from TCGA database and GEO (GSE4412). The GSEA database was used to screen tumor microenvironment-related gene sets. Cancer subtypes were classified by GSVA enrichment method.

RESULTS

By GSVA enrichment analysis, we obtain three Gliomas cancer subtypes. After further survival prognosis analysis and biological function analysis, we obtained 13 tumor microenvironment gene sets and 14 core genes that affect patients' survival prognosis, and these genes have the potential to become targets for targeted therapies and disease detection.

CONCLUSION

We screened a total of 13 gene sets through a series of enrichment analyses, statistical and prognostic analyses, etc. Among them, 14 core genes were identified, namely: TOP2A, TPX2, BUB1, AURKB, AURKA, CDK1, BUB1B, CCNA2, CCNB2, CDCA8, CDC20, KIF11, KIF20A and KIF2C.

摘要

目的

胶质瘤是最常见的原发性颅脑肿瘤，起源于神经胶质细胞（可位于脑或脊髓）的癌变。它是由先天遗传风险因素引起或由致癌环境诱发。如果不进行治疗，该疾病预后较差。

方法

在本研究中，我们从TCGA数据库和GEO（GSE4412）下载了胶质瘤数据。使用GSEA数据库筛选肿瘤微环境相关基因集。通过GSVA富集方法对癌症亚型进行分类。

结果

通过GSVA富集分析，我们获得了三种胶质瘤癌症亚型。经过进一步的生存预后分析和生物学功能分析，我们获得了13个肿瘤微环境基因集和14个影响患者生存预后的核心基因，这些基因有潜力成为靶向治疗和疾病检测的靶点。

结论

我们通过一系列富集分析、统计和预后分析等总共筛选出13个基因集。其中，鉴定出14个核心基因，即：TOP2A、TPX2、BUB1、AURKB、AURKA、CDK1、BUB1B、CCNA2、CCNB2、CDCA8、CDC20、KIF11、KIF20A和KIF2C。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a19b/9236851/2bfa744057b7/fendo-13-879233-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a19b/9236851/4bffc6a524a5/fendo-13-879233-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a19b/9236851/71d67f32f5a1/fendo-13-879233-g003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a19b/9236851/93954a60193a/fendo-13-879233-g006.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a19b/9236851/1386b83e96ab/fendo-13-879233-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a19b/9236851/9deeabda2621/fendo-13-879233-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a19b/9236851/2bfa744057b7/fendo-13-879233-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a19b/9236851/4bffc6a524a5/fendo-13-879233-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a19b/9236851/90e7064087b1/fendo-13-879233-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a19b/9236851/71d67f32f5a1/fendo-13-879233-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a19b/9236851/d7a8a864600b/fendo-13-879233-g004.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a19b/9236851/93954a60193a/fendo-13-879233-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a19b/9236851/259901ae4f77/fendo-13-879233-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a19b/9236851/1386b83e96ab/fendo-13-879233-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a19b/9236851/9deeabda2621/fendo-13-879233-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a19b/9236851/2bfa744057b7/fendo-13-879233-g010.jpg

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