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一个七基因特征和 C-C 基序趋化因子受体家族基因是与肉瘤相关的免疫基因。

A seven-gene signature and the C-C motif chemokine receptor family genes are the sarcoma-related immune genes.

机构信息

Spine and Osteopathy Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China.

Respiratory Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China.

出版信息

Bioengineered. 2021 Dec;12(1):7616-7630. doi: 10.1080/21655979.2021.1981797.

Abstract

Cells of the tumor microenvironment exert a vital influence on sarcoma prognosis. This study aimed to analyze and identify differentially expressed genes (DEGs) related to immunity and their significance as immune biomarkers for the accurate prediction of overall survival of patients with sarcoma. The Cancer Genome Atlas was adopted for obtaining sarcoma gene microarray and corresponding clinical information. ESTIMATE algorithm was used to calculate tumor immune microenvironment indices. Immune-associated DEGs were identified using the limma packages and were further analyzed using the ClusterProfiler package and STRING website. Based on the results of these analyses, we constructed a prognostic model. Furthermore, we assessed the prognosis prediction model through functional evaluation and analysis of GSE17674. The functional analysis revealed that the upregulated immune DEGs were related to immune-related aspects. Chemokine ligands/receptors and immune-related genes were found to be vital for sarcoma formation and progression. We established a prognostic signature of seven genes, which indicated that high-risk cases exhibit poor prognostic outcome. The prognostic signature constructed in this study can accurately predict the overall prognosis in patients with sarcoma. Moreover, the novel immune gene expression analysis may provide clinical guidance for predicting prognosis in patients with sarcoma.

摘要

肿瘤微环境中的细胞对肉瘤的预后有重要影响。本研究旨在分析和鉴定与免疫相关的差异表达基因(DEGs),并将其作为免疫生物标志物,以准确预测肉瘤患者的总生存率。本研究采用癌症基因组图谱获取肉瘤基因微阵列及相应的临床信息。使用 ESTIMATE 算法计算肿瘤免疫微环境指数。使用 limma 包鉴定免疫相关的 DEGs,并使用 ClusterProfiler 包和 STRING 网站进行进一步分析。基于这些分析的结果,我们构建了一个预后模型。此外,我们通过功能评估和对 GSE17674 的分析来评估预后预测模型。功能分析表明,上调的免疫 DEGs 与免疫相关方面有关。趋化因子配体/受体和免疫相关基因对肉瘤的形成和进展至关重要。我们建立了一个由七个基因组成的预后特征,表明高危病例预后不良。本研究构建的预后特征可准确预测肉瘤患者的总体预后。此外,新型免疫基因表达分析可能为预测肉瘤患者的预后提供临床指导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/333c/8806857/caf240489537/KBIE_A_1981797_F0001_OC.jpg

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