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基于肿瘤微环境的新型肉瘤标志物可改善预后预测。

A New Signature of Sarcoma Based on the Tumor Microenvironment Benefits Prognostic Prediction.

机构信息

Key Laboratory for Experimental Teratology of Ministry of Education, Department of Histology & Embryology, School of Basic Medical Sciences, Shandong University, Jinan 250012, China.

Key Laboratory of Molecular Oncology, Department of Medical Oncology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100021, China.

出版信息

Int J Mol Sci. 2023 Feb 3;24(3):2961. doi: 10.3390/ijms24032961.

Abstract

Sarcomas are a group of malignant tumors derived from mesenchymal tissues that display complex and variable pathological types. The impact of the immune properties of the tumor microenvironment (TME) on the prognosis, treatment, and management of sarcomas has attracted attention, requiring the exploration of sensitive and accurate signatures. In this study, The Cancer Genome Atlas (TCGA) database was searched to screen for an RNA sequencing dataset, retrieving 263 sarcoma and 2 normal samples with survival data. Genes associated with immune regulation in sarcomas were retrieved from the Tumor Immune Estimation Resource database to estimate tumor purity and immune cell infiltration levels. The samples were then divided into the immune-high and immune-low groups. Then, we screened for differentially expressed genes (DEGs) between the two groups. The intersection between immune-related genes and DEGs was then determined. Univariate Cox and least absolute shrinkage and selection operator analyses were used to select ideal genes for prognostic prediction and subsequent construction of a risk signature. A survival analysis was performed to reveal the dissimilarity in survival between the high- and low-score groups. Finally, a nomogram was generated to verify the accuracy and reliability of the signature. Through Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression (ESTIMATE) analysis, high ESTIMATE, and low tumor purity were significantly associated with a favorable prognosis. Moreover, a total of 5259 DEGs were retrieved, the majority of which were downregulated. In total, 590 immune-associated genes overlapped with the DEGs, among which nine hub genes were identified. Finally, two candidate genes, and , were identified, based on which a risk signature was constructed. The risk signature constructed in this study is accurate and reliable for the prognostic prediction and phenotyping of sarcomas.

摘要

肉瘤是一组源自间充质组织的恶性肿瘤,具有复杂和多变的病理类型。肿瘤微环境(TME)的免疫特性对肉瘤的预后、治疗和管理产生影响,这引起了人们的关注,需要探索敏感和准确的特征。本研究在 The Cancer Genome Atlas(TCGA)数据库中搜索 RNA 测序数据集,检索到 263 个肉瘤和 2 个有生存数据的正常样本。从肿瘤免疫估计资源数据库中检索与肉瘤免疫调节相关的基因,以估计肿瘤纯度和免疫细胞浸润水平。然后将样本分为免疫高和免疫低两组。然后,筛选两组之间差异表达基因(DEGs)。确定免疫相关基因和 DEGs 的交集。使用单变量 Cox 和最小绝对值收缩和选择算子分析选择理想的基因进行预后预测,并随后构建风险签名。进行生存分析以揭示高分和低分组之间生存的差异。最后,生成一个列线图来验证签名的准确性和可靠性。通过使用表达(ESTIMATE)分析估计肿瘤间质和免疫细胞在恶性肿瘤组织中的含量(ESTIMATE)分析,高 ESTIMATE 和低肿瘤纯度与预后良好显著相关。此外,共检索到 5259 个 DEGs,其中大部分下调。总共与 DEGs 重叠的 590 个免疫相关基因,其中鉴定出 9 个枢纽基因。最后,基于两个候选基因 和 ,构建了一个风险签名。本研究构建的风险签名对肉瘤的预后预测和表型具有准确可靠的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6f1/9918054/bed79a2c9776/ijms-24-02961-g001.jpg

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