A novel risk model consisting of nine platelet-related gene signatures for predicting prognosis, immune features and drug sensitivity in glioma.

IF 2.7 3区 生物学
Sanlin Wei, Junke Zhou, Bin Dong
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引用次数: 0

Abstract

Background: Glioma is a malignancy with challenging clinical treatment and poor prognosis. Platelets are closely associated with tumor growth, propagation, invasion, and angiogenesis. However, the role of platelet-related genes in glioma treatment and prognosis remains unclear.

Results: A prognostic risk model was established using nine platelet-related prognostic signature genes (CAPG, CLIC1, GLB1, GNG12, KIF20A, PDIA4, SULF2, TAGLN2, and WEE1), and the risk score of samples were calculated. Subsequently, the glioma samples were divided into high- and low-risk groups based on the median values of risk scores. scRNA-seq analysis revealed that the prognostic genes were primarily located in astrocytes and natural killer cells. The immune infiltration proportions of most immune cells differed significantly between high- and low-risk groups. Moreover, we found AZD7762 as a potential candidate for glioma treatment.

Conclusion: Nine platelet-related prognostic genes identified as prognostic signatures for glioma were closely associated with the TME and may aid in directing the clinical treatment and prognosis of gliomas.

由9个血小板相关基因特征组成的新型风险模型可用于预测胶质瘤的预后、免疫特征和药物敏感性。
背景:神经胶质瘤是一种临床治疗困难、预后差的恶性肿瘤。血小板与肿瘤的生长、繁殖、侵袭和血管生成密切相关。然而,血小板相关基因在胶质瘤治疗和预后中的作用尚不清楚。结果:利用9个血小板相关预后标志基因(CAPG、CLIC1、GLB1、GNG12、KIF20A、PDIA4、SULF2、TAGLN2、WEE1)建立预后风险模型,计算样本风险评分。随后,根据风险评分的中位数将胶质瘤样本分为高风险组和低风险组。scRNA-seq分析显示,预后基因主要位于星形胶质细胞和自然杀伤细胞。大多数免疫细胞的免疫浸润比例在高危组和低危组之间存在显著差异。此外,我们发现AZD7762是治疗胶质瘤的潜在候选者。结论:9个血小板相关预后基因与胶质瘤TME密切相关,可指导胶质瘤的临床治疗和预后。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Hereditas
Hereditas Biochemistry, Genetics and Molecular Biology-Genetics
CiteScore
3.80
自引率
3.70%
发文量
0
期刊介绍: For almost a century, Hereditas has published original cutting-edge research and reviews. As the Official journal of the Mendelian Society of Lund, the journal welcomes research from across all areas of genetics and genomics. Topics of interest include human and medical genetics, animal and plant genetics, microbial genetics, agriculture and bioinformatics.
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