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新型骨肉瘤免疫相关基因预后特征的建立。

Development of a novel immune-related genes prognostic signature for osteosarcoma.

机构信息

Guanghe Traditional Chinese and Western Medicine Hospital, Lanzhou, 730000, Gansu, China.

Department of Orthopaedics, Second Hospital of Lanzhou University, Lanzhou, 730000, Gansu, China.

出版信息

Sci Rep. 2020 Oct 27;10(1):18402. doi: 10.1038/s41598-020-75573-w.

Abstract

Immune-related genes (IRGs) are responsible for osteosarcoma (OS) initiation and development. We aimed to develop an optimal IRGs-based signature to assess of OS prognosis. Sample gene expression profiles and clinical information were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Genotype-Tissue Expression (GTEx) databases. IRGs were obtained from the ImmPort database. R software was used to screen differentially expressed IRGs (DEIRGs) and functional correlation analysis. DEIRGs were analyzed by univariate Cox regression and iterative LASSO Cox regression analysis to develop an optimal prognostic signature, and the signature was further verified by independent cohort (GSE39055) and clinical correlation analysis. The analyses yielded 604 DEIRGs and 10 hub IRGs. A prognostic signature consisting of 13 IRGs was constructed, which strikingly correlated with OS overall survival and distant metastasis (p < 0.05, p < 0.01), and clinical subgroup showed that the signature's prognostic ability was independent of clinicopathological factors. Univariate and multivariate Cox regression analyses also supported its prognostic value. In conclusion, we developed an IRGs signature that is a prognostic indicator in OS patients, and the signature might serve as potential prognostic indicator to identify outcome of OS and facilitate personalized management of the high-risk patients.

摘要

免疫相关基因(IRGs)负责骨肉瘤(OS)的发生和发展。我们旨在开发一种基于最佳 IRGs 的签名来评估 OS 预后。从 Therapeutically Applicable Research to Generate Effective Treatments(TARGET)和 Genotype-Tissue Expression(GTEx)数据库下载了样本基因表达谱和临床信息。IRGs 从 ImmPort 数据库中获得。使用 R 软件筛选差异表达的 IRGs(DEIRGs)和功能相关分析。通过单变量 Cox 回归和迭代 LASSO Cox 回归分析对 DEIRGs 进行分析,以开发最佳预后签名,并通过独立队列(GSE39055)和临床相关性分析进一步验证该签名。分析产生了 604 个 DEIRGs 和 10 个核心 IRGs。构建了由 13 个 IRGs 组成的预后签名,该签名与 OS 总生存期和远处转移显著相关(p<0.05,p<0.01),临床亚组表明该签名的预后能力独立于临床病理因素。单变量和多变量 Cox 回归分析也支持其预后价值。总之,我们开发了一种用于 OS 患者的 IRGs 签名,作为一种预后指标,该签名可能作为识别 OS 结果的潜在预后指标,并有助于高危患者的个性化管理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4bc/7591524/7f8856c79c1d/41598_2020_75573_Fig1_HTML.jpg

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