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通过综合生物信息学分析鉴定与肺腺癌预后相关的关键候选基因

Identification of key candidate genes associated with prognosis of lung adenocarcinoma by integrated bioinformatical analysis.

作者信息

Li Jinghang, Li Yanxiu, Jin Min, Huang Lin, Wang Xiaowei

机构信息

Department of Thoracic and Cardiovascular Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.

Department of Critical Care Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.

出版信息

Transl Cancer Res. 2020 Nov;9(11):6841-6856. doi: 10.21037/tcr-20-2110.

DOI:10.21037/tcr-20-2110
PMID:35117293
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8798186/
Abstract

BACKGROUND

Lung adenocarcinoma (LUAD) is the most frequent histologic type of lung cancer and the morbidity of LUAD is increasing rapidly in the worldwide. But the mechanism of LUAD is still largely unknown.

METHODS

In this study, we analyzed three microarrays of gene expression profiles, containing 196 LUAD samples and 137 normal samples, to explore the potential key candidate genes in LUAD by integrated bioinformatical analysis.

RESULTS

A total of 240 shared differentially expressed genes (DEGs) were identified and pathways enrichment were analyzed. DEGs-associated protein-protein interaction (PPI) network was constructed and top 20 hub genes were established by calculating the degree of connectivity. We further validated these genes in TCGA and GTEx projects, and found all of these hub genes were differentially expressed in LUAD patients except and FOS. In these candidate genes, ten genes ( and ) were confirmed to associate with the prognosis of LUAD. Out of these ten genes, CENPF had the highest genetic alteration at a rate of 4% in LUAD patients, and the expression of was significantly increased in different subgroups of all age, gender, race, smoking condition and cancer stage groups of LUAD patients.

CONCLUSIONS

Our study contributes to comprehend the role of genes in LUAD and provides possible therapeutic targets for further clinical application.

摘要

背景

肺腺癌(LUAD)是肺癌最常见的组织学类型,在全球范围内其发病率正在迅速上升。但肺腺癌的发病机制仍很大程度上未知。

方法

在本研究中,我们分析了三个基因表达谱微阵列,包含196例肺腺癌样本和137例正常样本,通过综合生物信息学分析来探索肺腺癌中潜在的关键候选基因。

结果

共鉴定出240个共享差异表达基因(DEGs)并进行了通路富集分析。构建了DEGs相关的蛋白质-蛋白质相互作用(PPI)网络,并通过计算连通度确定了前20个枢纽基因。我们在TCGA和GTEx项目中进一步验证了这些基因,发现除了 和FOS外,所有这些枢纽基因在肺腺癌患者中均有差异表达。在这些候选基因中,有十个基因( 和 )被证实与肺腺癌的预后相关。在这十个基因中,CENPF在肺腺癌患者中的基因改变率最高,为4%,并且在肺腺癌患者的所有年龄、性别、种族、吸烟状况和癌症分期组的不同亚组中其表达均显著增加。

结论

我们的研究有助于理解基因在肺腺癌中的作用,并为进一步的临床应用提供了可能的治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5b/8798186/0d69dd87b1d5/tcr-09-11-6841-f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5b/8798186/17e505deeffe/tcr-09-11-6841-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5b/8798186/217919206cc8/tcr-09-11-6841-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5b/8798186/b0145aa9a7ae/tcr-09-11-6841-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5b/8798186/3e28dcd59792/tcr-09-11-6841-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5b/8798186/ce56dbf83e1b/tcr-09-11-6841-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5b/8798186/931e6ceb6fb4/tcr-09-11-6841-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5b/8798186/fe07ccda9796/tcr-09-11-6841-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5b/8798186/200c8a935c22/tcr-09-11-6841-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5b/8798186/0d69dd87b1d5/tcr-09-11-6841-f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5b/8798186/17e505deeffe/tcr-09-11-6841-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5b/8798186/217919206cc8/tcr-09-11-6841-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5b/8798186/b0145aa9a7ae/tcr-09-11-6841-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5b/8798186/3e28dcd59792/tcr-09-11-6841-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5b/8798186/ce56dbf83e1b/tcr-09-11-6841-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5b/8798186/931e6ceb6fb4/tcr-09-11-6841-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5b/8798186/fe07ccda9796/tcr-09-11-6841-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5b/8798186/200c8a935c22/tcr-09-11-6841-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc5b/8798186/0d69dd87b1d5/tcr-09-11-6841-f9.jpg

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Weighted gene coexpression network analysis identifies a new biomarker of CENPF for prediction disease prognosis and progression in nonmuscle invasive bladder cancer.加权基因共表达网络分析确定了 CENPF 作为非肌肉浸润性膀胱癌疾病预后和进展的新生物标志物。
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