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利用人工智能鉴定骨肉瘤 m6A 相关预后生物标志物:RBM15.

Identification of osteosarcoma m6A-related prognostic biomarkers using artificial intelligence: RBM15.

机构信息

The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, 530021, People's Republic of China.

Department of Traditional Chinese Medicine, The People's Hospital of Guangxi Zhuang Autonmous Region, Nanning, 530016, People's Republic of China.

出版信息

Sci Rep. 2023 Mar 31;13(1):5255. doi: 10.1038/s41598-023-28739-1.

Abstract

Osteosarcoma has the worst prognosis among malignant bone tumors, and effective biomarkers are lacking. Our study aims to explore m6A-related and immune-related biomarkers. Gene expression profiles of osteosarcoma and healthy controls were downloaded from multiple public databases, and their m6A-based gene expression was utilized for tumor typing using bioinformatics. Subsequently, a prognostic model for osteosarcoma was constructed using the least absolute shrinkage and selection operator and multivariate Cox regression analysis, and its immune cell composition was calculated using the CIBERSORTx algorithm. We also performed drug sensitivity analysis for these two genes. Finally, analysis was validated using immunohistochemistry. We also examined the RBM15 gene by qRT-PCR in an in vitro experiment. We collected routine blood data from 1738 patients diagnosed with osteosarcoma and 24,344 non-osteosarcoma patients and used two independent sample t tests to verify the accuracy of the CIBERSORTx analysis for immune cell differences. The analysis based on m6A gene expression tumor typing was most reliable using the two typing methods. The prognostic model based on the two genes constituting RNA-binding motif protein 15 (RBM15) and YTDC1 had a much lower survival rate for patients in the high-risk group than those in the low-risk group (P < 0.05). CIBERSORTx immune cell component analysis demonstrated that RBM15 showed a negative and positive correlation with T cells gamma delta and activated natural killer cells, respectively. Drug sensitivity analysis showed that these two genes showed varying degrees of correlation with multiple drugs. The results of immunohistochemistry revealed that the expression of these two genes was significantly higher in osteosarcoma than in paraneoplastic tissues. The results of qRT-PCR experiments showed that the expression of RBM15 was significantly higher in both osteosarcomas than in the control cell lines. Absolute lymphocyte value, lymphocyte percentage, hematocrit and erythrocyte count were lower in osteosarcoma than in the control group (P < 0.001). RBM15 and YTHDC1 can serve as potential prognostic biomarkers associated with m6A in osteosarcoma.

摘要

骨肉瘤是恶性骨肿瘤中预后最差的一种,缺乏有效的生物标志物。本研究旨在探索 m6A 相关和免疫相关的生物标志物。从多个公共数据库下载骨肉瘤和健康对照的基因表达谱,并利用生物信息学基于 m6A 对肿瘤进行基因表达分类。然后,使用最小绝对收缩和选择算子(LASSO)和多变量 Cox 回归分析构建骨肉瘤的预后模型,并使用 CIBERSORTx 算法计算其免疫细胞成分。我们还对这两个基因进行了药物敏感性分析。最后,使用免疫组织化学进行验证。我们还在体外实验中通过 qRT-PCR 检测了 RBM15 基因。我们收集了 1738 名骨肉瘤患者和 24344 名非骨肉瘤患者的常规血液数据,并使用两个独立样本 t 检验验证 CIBERSORTx 分析对免疫细胞差异的准确性。基于 m6A 基因表达肿瘤分类的分析是最可靠的两种分类方法。基于 RNA 结合基序蛋白 15 (RBM15) 和 YTH 结构域包含蛋白 1 (YTHDC1) 这两个基因构建的预后模型,高危组患者的生存率明显低于低危组(P<0.05)。CIBERSORTx 免疫细胞成分分析表明,RBM15 与 T 细胞γδ和活化自然杀伤细胞呈负相关和正相关。药物敏感性分析表明,这两个基因与多种药物呈不同程度的相关性。免疫组织化学的结果表明,这两个基因在骨肉瘤中的表达明显高于癌旁组织。qRT-PCR 实验的结果表明,RBM15 在骨肉瘤中的表达明显高于对照细胞系。骨肉瘤患者的绝对淋巴细胞值、淋巴细胞百分比、红细胞压积和红细胞计数均低于对照组(P<0.001)。RBM15 和 YTHDC1 可作为骨肉瘤中与 m6A 相关的潜在预后生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16a0/10066227/235602d12fcb/41598_2023_28739_Fig1_HTML.jpg

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