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CCR2 作为肺腺癌免疫指标的预后价值：基于肿瘤浸润免疫细胞分析的研究。

Prognostic value of CCR2 as an immune indicator in lung adenocarcinoma: A study based on tumor-infiltrating immune cell analysis.

机构信息

Department of Immunology, School of Basic Medicine, Qingdao University, Qingdao, Shandong Province, China.

School of Stomatology, Qingdao University, Qingdao, Shandong Province, China.

出版信息

Cancer Med. 2021 Jun;10(12):4150-4163. doi: 10.1002/cam4.3931. Epub 2021 May 4.

DOI:10.1002/cam4.3931
PMID:33949150
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8209599/
Abstract

BACKGROUND

Prognostic indicators in lung adenocarcinoma (LUAD) have been seeking under database analysis, and remarkable advance is on the way.

METHODS

This study calculated the scores of stromal and immune components of the tumor microenvironment (TME) in 551 LUAD samples using the ESTIMATE algorithm on The Cancer Genome Atlas (TCGA) database. R package ''limma'' was used to selected differentially expressed genes (DEG). We have analyzed the DEGs by means of Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichments. The protein-protein network, univariate Cox analysis, and Lasso regression analysis were performed to selected survival-related genes. Gene Set Enrichment Analysis (GSEA) represented the enriched pathway of CC chemokine receptor 2 (CCR2). The ratios of immune cells in the TME of each LUAD sample were obtained using the R package "limma" and CIBERSORT algorithm in R 4.0.2.

RESULTS

The ImmuneScore was positively correlated with prognosis regarding survival rate, T classification of TNM stages, and clinicopathological staging characteristics. GO and KEGG enrichments showed DEGs were associated with immune-related activities. Three genes of LUAD were selected from the PPI network and Cox proportional hazards regression analysis. CCR2 was the most survival correlated gene by Lasso regression analysis. GSEA results showed that C2 kegg gene sets in the CCR2 high-expression group were mainly enriched in the B cell or T cell receptor signaling pathway and natural killer cell-mediated cytotoxicity. Correlation of CCR2 expression with prognosis was conducted, implicating a positive correlation with the prognosis of survival rate and M classification, negative correlation with the prognosis of T and N classifications. The correlation between CCR2 and tumor-infiltrating immune cells (TICs) was analyzed, and 14 kinds of TICs were found closely correlated with CCR2 expression through difference analysis.

CONCLUSION

Therefore, CCR2 has prognostic value as an immune indicator in LUAD.

摘要

背景

在肺腺癌 (LUAD) 中，预后指标一直在数据库分析中寻找，并且正在取得显著进展。

方法

本研究使用 ESTIMATE 算法在癌症基因组图谱 (TCGA) 数据库中计算了 551 个 LUAD 样本的肿瘤微环境 (TME) 基质和免疫成分的分数。使用 R 包“limma”选择差异表达基因 (DEG)。我们通过基因本体论 (GO) 分析和京都基因与基因组百科全书 (KEGG) 富集分析对 DEGs 进行了分析。进行了蛋白质-蛋白质网络、单变量 Cox 分析和 Lasso 回归分析，以选择与生存相关的基因。基因集富集分析 (GSEA) 代表了 CC 趋化因子受体 2 (CCR2) 富集途径。使用 R 包“limma”和 R 4.0.2 中的 CIBERSORT 算法获得每个 LUAD 样本 TME 中免疫细胞的比例。

结果

免疫评分与生存率、TNM 分期的 T 分类和临床病理分期特征的预后呈正相关。GO 和 KEGG 富集表明 DEGs 与免疫相关活动有关。从 PPI 网络和 Cox 比例风险回归分析中选择了三个 LUAD 基因。通过 Lasso 回归分析，CCR2 是与生存相关性最强的基因。GSEA 结果表明，CCR2 高表达组的 C2 kegg 基因集主要富集在 B 细胞或 T 细胞受体信号通路和自然杀伤细胞介导的细胞毒性中。进行了 CCR2 表达与预后的相关性分析，结果表明 CCR2 表达与生存率和 M 分类的预后呈正相关，与 T 和 N 分类的预后呈负相关。分析了 CCR2 与肿瘤浸润免疫细胞 (TIC) 的相关性，通过差异分析发现 14 种 TIC 与 CCR2 表达密切相关。

结论

因此，CCR2 作为 LUAD 的免疫指标具有预后价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e110/8209599/3b4082700c2d/CAM4-10-4150-g003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e110/8209599/0dde9b5f9421/CAM4-10-4150-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e110/8209599/7950f81c5f15/CAM4-10-4150-g004.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e110/8209599/514878c7e8c7/CAM4-10-4150-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e110/8209599/5fa034a506af/CAM4-10-4150-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e110/8209599/1698da4b61ad/CAM4-10-4150-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e110/8209599/37e1c587c04e/CAM4-10-4150-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e110/8209599/e9f8c7cbcfe6/CAM4-10-4150-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e110/8209599/0dde9b5f9421/CAM4-10-4150-g009.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e110/8209599/3b4082700c2d/CAM4-10-4150-g003.jpg

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