Identification of TNFRSF1A as a potential biomarker for osteosarcoma.

IF 2.2 4区 医学 Q3 ONCOLOGY Cancer Biomarkers Pub Date : 2024-01-01 DOI:10.3233/CBM-230086
Yuke Zhang, Kai Liu, Jianzhong Wang
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Abstract

Background: Osteosarcoma (OS) is a relatively rare malignant bone tumor in teenagers; however, its molecular mechanisms are not yet understood comprehensively.

Objective: The study aimed to use necroptosis-related genes (NRGs) and their relationships with immune-related genes to construct a prognostic signature for OS.

Methods: TARGET-OS was used as the training dataset, and GSE 16091 and GSE 21257 were used as the validation datasets. Univariate regression, survival analysis, and Kaplan-Meier curves were used to screen for hub genes. The immune-related targets were screened using immune infiltration assays and immune checkpoints. The results were validated using nomogram and decision curve analyses (DCA).

Results: Using univariate Cox regression analysis, TNFRSF1A was screened from 14 NRGs as an OS prognostic signature. Functional enrichment was analyzed based on the median expression of TNFRSF1A. The prognosis of the TNFRSF1A low-expression group in the Kaplan-Meier curve was notably worse. Immunohistochemistry analysis showed that the number of activated T cells and tumor purity increased considerably. Furthermore, the immune checkpoint lymphocyte activation gene 3 (LAG-3) is a possible target for intervention. The nomogram accurately predicted 1-, 3-, and 5-year survival rates. DCA validated the model (C = 0.669).

Conclusion: TNFRSF1A can be used to elucidate the potential relationship between the immune microenvironment and NRGs in OS pathogenesis.

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将 TNFRSF1A 鉴定为骨肉瘤的潜在生物标记物。
背景:骨肉瘤(Osteosarcoma,OS)是一种在青少年中较为罕见的恶性骨肿瘤,但其分子机制尚未得到全面了解:本研究旨在利用坏死相关基因(NRGs)及其与免疫相关基因的关系构建骨肉瘤的预后特征:方法: 使用TARGET-OS作为训练数据集,使用GSE 16091和GSE 21257作为验证数据集。采用单变量回归、生存分析和 Kaplan-Meier 曲线筛选枢纽基因。利用免疫浸润检测和免疫检查点筛选免疫相关靶点。使用提名图和决策曲线分析(DCA)对结果进行了验证:结果:通过单变量考克斯回归分析,从14个NRG中筛选出TNFRSF1A作为OS预后特征。根据TNFRSF1A的中位表达量分析了功能富集。在 Kaplan-Meier 曲线中,TNFRSF1A 低表达组的预后明显较差。免疫组化分析显示,活化的T细胞数量和肿瘤纯度显著增加。此外,免疫检查点淋巴细胞活化基因3(LAG-3)也是一个可能的干预靶点。提名图准确预测了1年、3年和5年的生存率。DCA验证了该模型(C = 0.669):TNFRSF1A可用于阐明OS发病机制中免疫微环境与NRGs之间的潜在关系。
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来源期刊
Cancer Biomarkers
Cancer Biomarkers ONCOLOGY-
CiteScore
5.20
自引率
3.20%
发文量
195
审稿时长
3 months
期刊介绍: Concentrating on molecular biomarkers in cancer research, Cancer Biomarkers publishes original research findings (and reviews solicited by the editor) on the subject of the identification of markers associated with the disease processes whether or not they are an integral part of the pathological lesion. The disease markers may include, but are not limited to, genomic, epigenomic, proteomics, cellular and morphologic, and genetic factors predisposing to the disease or indicating the occurrence of the disease. Manuscripts on these factors or biomarkers, either in altered forms, abnormal concentrations or with abnormal tissue distribution leading to disease causation will be accepted.
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