Comprehensive analysis of histone deacetylases genes in the prognosis and immune infiltration of glioma patients
Comprehensive analysis of histone deacetylases genes in the prognosis and immune infiltration of glioma patients
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DOI：
10.1101/2022.01.24.22269795
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发表时间：
2022-01
影响因子：
4.6
通讯作者：
Lin Shen;Yanyan Li;Na Li;Liang Shen;Zhanzhan Li
中科院分区：
文献类型：
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作者：
Lin Shen;Yanyan Li;Na Li;Liang Shen;Zhanzhan Li
研究背景肿瘤的发生、发展与组蛋白脱乙酰酶(HDAC)密切相关。然而，神经胶质瘤的总体生物学和预后仍不清楚。在本研究中，我们全面探讨了胶质瘤中11个HDAC基因的生物学功能和预后，这可能有助于更多地了解胶质瘤患者的分子机制和潜在的治疗靶点。方法使用TCGA和CGGA数据集系统描述表达文件、分子亚型、预后价值、免疫过滤和肿瘤微环境和基因改变、功能和通路富集以及药物敏感性。我们使用 LASSO、单变量和多变量 cox 回归开发并验证了基于神经胶质瘤 HDAC 基因的预后模型。接受者操作特征分析用于模型评估。我们还验证了模型中包含的 HDAC 基因在非肿瘤和神经胶质瘤组织样本中的表达。结果根据11个HDAC基因，胶质瘤患者可分为两个亚类，两个亚类患者的生存结果明显不同。然后，使用六个 HDAC 基因（HDAC1、HDAC3、HDAC4、HDAC5、HDAC7 和 HDAC9），我们在神经胶质瘤患者中建立了预后模型，并且该预后模型在独立队列人群中得到了很好的验证。此外，根据六个 HDACA 基因表达计算出的风险评分被认为是一个独立的预后因素，可以很好地预测神经胶质瘤患者的五年总生存率。高危患者可归因于多种复杂的功能和分子信号通路，高危和低危患者的基因改变存在显着差异。我们还发现，高风险和低风险患者的不同生存结果可能与免疫过滤水平和肿瘤微环境的差异有关。随后，我们鉴定了几种可能有利于神经胶质瘤患者治疗的小分子化合物。最后，在神经胶质瘤和非肿瘤组织样本中验证了预后模型中 HDAC 基因的表达水平。结论 我们的结果揭示了 HDAC 基因在胶质瘤中的临床效用和潜在的分子机制。基于六个HDAC基因的模型可以很好地预测胶质瘤患者的总体生存率，可以作为潜在的治疗靶点。
Background The occurrence and development of tumors are closely related to histone deacetylases (HDACs). However,the overall biology and prognosis are still unknown in glioma. In the present study,we comprehensively explored the biology function and prognosis of eleven HDAC genes in glioma,which may contribute the more understanding of molecular mechanisms and potential therapeutic targets for glioma patients. Methods We systematically described the expression files, molecular subtypes, prognostic value,immune filtration and tumor microenvironment and gene alteration,function and pathways enrichment,and drug sensitivity using TCGA and CGGA datasets. We developed and validated the prognostic model based on HDACs genes in glioma using LASSO,univariate, and multivariate cox regression. Receiver operating characteristic analyses were used for model evaluating. We also validated the expressions of HDACs genes included in the model in non-tumor and glioma tissues samples. Results Glioma patients can be divided into two subclasses based on eleven HDAC genes, and patients from two subclasses had markedly different survival outcomes. Then, using six HDAC genes (HDAC1, HDAC3, HDAC4, HDAC5, HDAC7, and HDAC9), we established a prognostic model in glioma patients, and this prognostic model was well validated in an independent cohort population. Furthermore, the calculated risk score from six HDACA genes expression was suggested to be an independent prognostic factor, which can predict the five-year overall survival of glioma patients well. High-risk patients can be attributed to multiple complex function and molecular signaling pathways, and the genes alterations of high- and low-risk patients were significantly different. We also found that different survival outcomes of high- and low- risk patients could be involved in the differences of immune filtration level and tumor microenvironment. Subsequently, we identified several small molecular compounds that could be favorable for glioma patients treatment. And finally, the expression levels of HDAC genes from prognostic model were validated in glioma and non-tumor tissues samples. Conclusion Our results revealed the clinical utility and potential molecular mechanisms of HDAC genes in glioma. Model based on six HDAC genes can predict the overall survival of glioma patients well, which can be served as potential therapeutic targets.