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免疫分型联合靶向治疗对非小细胞肺癌患者的预后价值及列线图模型的建立。

Prognostic Value of Immunotyping Combined with Targeted Therapy in Patients with Non-Small-Cell Lung Cancer and Establishment of Nomogram Model.

机构信息

Department of Internal Medicine, College of Integrated Chinese and Western Medicine, Hunan University of Chinese Medicine, China.

Hunan Key Laboratory of Traditional Chinese Medicine Prescription and Syndromes Translational Medicine, Hunan University of Chinese Medicine, China.

出版信息

Comput Math Methods Med. 2022 May 14;2022:3049619. doi: 10.1155/2022/3049619. eCollection 2022.

DOI:10.1155/2022/3049619
PMID:35607647
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9124071/
Abstract

OBJECTIVE

Bioinformatics methods were used to analyze non-small-cell lung cancer gene chip data, screen differentially expressed genes (DEGs), explore biomarkers related to NSCLC prognosis, provide new targets for the treatment of NSCLC, and build immunotyping and line-map model.

METHODS

NSCLC-related gene chip data were downloaded from the GEO database, and the common DEGs of the two datasets were screened by using the GEO2R tool and FunRich 3.1.3 software. DAVID database was used for GO analysis and KEGG analysis of DEGs, and protein-protein interaction (PPI) network was constructed by STRING database and Cytoscape 3.8.0 software, and the top 20 hub genes were analyzed and screened out. The expression of pivot genes and their relationship with prognosis were verified by multiple external databases.

RESULTS

159 common DEGs were screened from the two datasets. PPI network was constructed and analyzed, and the genes with the top 20 connectivity were selected as the pivotal genes of this study. The results of survival analysis and the patients' survival curve was reflected in the line graph model of NSCLC.

CONCLUSION

Through the screening and identification of the VIM-AS1 gene, as well as the analysis of immune infiltration and immune typing, the successful establishment of the rosette model has a certain guiding value for the molecular targeted therapy of patients with non-small-cell lung cancer.

摘要

目的

运用生物信息学方法分析非小细胞肺癌基因芯片数据，筛选差异表达基因（DEGs），探索与 NSCLC 预后相关的生物标志物，为 NSCLC 的治疗提供新的靶点，并构建免疫分型和线图模型。

方法

从 GEO 数据库中下载 NSCLC 相关基因芯片数据，使用 GEO2R 工具和 FunRich 3.1.3 软件筛选两个数据集的共同 DEGs。使用 DAVID 数据库对 DEGs 进行 GO 分析和 KEGG 分析，使用 STRING 数据库和 Cytoscape 3.8.0 软件构建蛋白质-蛋白质相互作用（PPI）网络，分析筛选出前 20 个枢纽基因。通过多个外部数据库验证枢纽基因的表达及其与预后的关系。

结果

从两个数据集筛选出 159 个共同的 DEGs。构建 PPI 网络并进行分析，选择连接度最高的 20 个基因作为本研究的枢纽基因。通过生存分析和患者生存曲线的结果反映在 NSCLC 的线图模型中。

结论

通过筛选和鉴定 VIM-AS1 基因，以及对免疫浸润和免疫分型的分析，成功建立了玫瑰花结模型，对非小细胞肺癌患者的分子靶向治疗具有一定的指导价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cebb/9124071/4937bee18ac3/CMMM2022-3049619.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cebb/9124071/14810f925b0e/CMMM2022-3049619.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cebb/9124071/0f9a0296d1af/CMMM2022-3049619.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cebb/9124071/3bf381b2d172/CMMM2022-3049619.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cebb/9124071/702f8b6cdbb0/CMMM2022-3049619.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cebb/9124071/5e7edc6ac19b/CMMM2022-3049619.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cebb/9124071/dd67ed035ebc/CMMM2022-3049619.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cebb/9124071/722947ca0dba/CMMM2022-3049619.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cebb/9124071/4937bee18ac3/CMMM2022-3049619.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cebb/9124071/14810f925b0e/CMMM2022-3049619.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cebb/9124071/0f9a0296d1af/CMMM2022-3049619.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cebb/9124071/3bf381b2d172/CMMM2022-3049619.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cebb/9124071/702f8b6cdbb0/CMMM2022-3049619.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cebb/9124071/5e7edc6ac19b/CMMM2022-3049619.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cebb/9124071/dd67ed035ebc/CMMM2022-3049619.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cebb/9124071/722947ca0dba/CMMM2022-3049619.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cebb/9124071/4937bee18ac3/CMMM2022-3049619.008.jpg

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3
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