Exploration of Immune-Related Gene Expression in Osteosarcoma and Association With Outcomes.
Exploration of Immune-Related Gene Expression in Osteosarcoma and Association With Outcomes.
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DOI：
10.1001/jamanetworkopen.2021.19132
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发表时间：
2021-08-02
影响因子：
13.8
通讯作者：
Wu J
中科院分区：
文献类型：
--
作者：
Liu W;Xie X;Qi Y;Wu J
骨肉瘤的免疫基因组图谱是什么？在这项基于84个癌症基因组图谱样本的遗传关联研究中，鉴定了14个与骨肉瘤存活相关的免疫相关基因。这些发现表明，基于免疫相关基因表达谱的诊断风险评分可能有助于规划骨肉瘤的个体化治疗。本遗传关联研究检测了来自癌症基因组图谱项目的骨肉瘤样本中的免疫相关基因表达，并评估了基因表达谱与生存结果的关联。宿主免疫失调与骨肉瘤的发生和发展有关。此外，骨肉瘤的免疫治疗需要对患者的免疫状态有一定的了解。基于癌症基因组图谱（TCGA）项目进行免疫基因组景观分析，该项目为骨肉瘤样本提供临床信息。本遗传关联研究于2020年7月20日至2020年9月20日进行，作为对公共数据的二次分析。采用Cox回归和风险评分分析，构建84例TCGA骨肉瘤患者的免疫相关基因（IRGs）特征，并提供相应的临床信息。根据患者的风险评分，将患者分为高危组和低危组，每组42人。数据分析时间为2020年7月20日至9月20日。利用生物信息学方法分析各组间差异表达基因（DEGs），并探讨其潜在的分子机制、表达调控和免疫细胞浸润。建立基于多变量Cox风险比回归选择的独立危险因素的预后模型来估计1年总生存率。在这项基于84例TCGA骨肉瘤患者样本（平均[SD]年龄15.0[4.8]岁；47例[56.0%]男性；平均[SD]随访时间4.1[2.8]年）的遗传关联研究中，共鉴定出14个与生存相关的IRGs。高危组患者的生存期比低危组患者差（1例死亡[2.4%]vs 26例死亡[61.9%];P < 0.001）。蛋白质消化吸收途径是功能富集分析的相关途径之一（基因比为2:8；P < .001）。基于诊断时转移和风险评分的预后模型在1年总生存估计中表现良好（曲线下面积，0.947;95% CI, 0.832-0.972）。风险评分与免疫细胞浸润相关（B细胞：r = 0.331, P = 0.002；巨噬细胞：r = 0.410, P < 0.001； CD8 T细胞：r = 0.230, P = 0.04）。这项遗传关联研究开发了一种基于IRG表达谱的骨肉瘤预后建模工具，可以通过更个性化的治疗提高生存率。进一步研究IRG表达谱可为今后骨肉瘤免疫治疗研究提供潜在靶点。
What is the immunogenomic landscape of osteosarcoma? In this genetic association study based on 84 samples from The Cancer Genome Atlas, 14 immune-related genes associated with survival in osteosarcoma were identified. These findings suggest that a diagnostic risk score based on immune-related gene expression profiles may be useful to planning individualized therapies for osteosarcoma. This genetic association study examines immune-related gene expression in osteosarcoma samples from The Cancer Genome Atlas project and assesses the association of gene expression profiles with survival outcomes. Host immune dysregulation is associated with initiation and development of osteosarcoma. In addition, immunotherapy for osteosarcomas requires some knowledge of the immune state of patients. To perform an immunogenomic landscape analysis based on The Cancer Genome Atlas (TCGA) project, which provides osteosarcoma samples with clinical information. This genetic association study was conducted from July 20, 2020, to September 20, 2020, as a secondary analysis of public data. Cox regression and risk score analyses were used to construct signatures of immune-related genes (IRGs) in 84 patients with osteosarcoma from TCGA with corresponding clinical information. Patients were divided into high- and low-risk groups with 42 individuals in each group according to their risk scores. Data were analyzed from July 20 to September 20, 2020. Differentially expressed genes (DEGs) were analyzed between groups, and potential molecular mechanisms, expression regulation, and immune cell infiltration were also explored using bioinformation methods. A prognostic model based on independent risk factors selected from multivariate Cox hazard ratio regression was established to estimate 1-year overall survival. In this genetic association study based on 84 samples from patients with osteosarcoma from TCGA (mean [SD] age, 15.0 [4.8] years; 47 [56.0%] men; mean [SD] follow-up time, 4.1 [2.8] years), a total of 14 survival-associated IRGs were identified. Patients assigned to the high-risk group had worse survival than patients from the low-risk group (1 death [2.4%] vs 26 deaths [61.9%%]; P < .001). The protein digestion and absorption pathway was one of the associated pathways in the functional enrichment analysis (gene ratio, 2:8; P < .001). The prognostic model based on metastases at diagnosis and risk score performed well in 1-year overall survival estimations (area under the curve, 0.947; 95% CI, 0.832-0.972). The risk score was correlated with immune cell infiltration (B cells: r = 0.331; P = .002; macrophages: r = 0.410; P < .001; CD8 T cells: r = 0.230; P = .04). This genetic association study developed a prognostic modeling tool for osteosarcoma based on IRG expression profiles, which could result in improved survival rates through more individualized therapies. Further research on IRG expression profiles could provide potential targets for future studies on immune treatment for osteosarcoma.
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