程序性细胞死亡方式焦亡相关基因特征的系统转录组分析预测低级别脑胶质瘤的预后和免疫图谱。
Systematic transcriptome profiling of pyroptosis related signature for predicting prognosis and immune landscape in lower grade glioma.
机构信息
School of Basic Medical Sciences, Anhui Medical University, No. 81, Meishan Road, Hefei, 230032, Anhui, China.
Anhui Province Key Laboratory of Medical Physics and Technology; Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, No. 350, Shushan Hu Road, Hefei, 230031, Anhui, China.
出版信息
BMC Cancer. 2022 Aug 13;22(1):885. doi: 10.1186/s12885-022-09982-7.
BACKGROUND
Pyroptosis is a programmed cell death mediated by the gasdermin superfamily, accompanied by inflammatory and immune responses. Exogenously activated pyroptosis is still not well characterized in the tumor microenvironment. Furthermore, whether pyroptosis-related genes (PRGs) in lower-grade glioma (LGG) may be used as a biomarker remains unknown.
METHODS
The RNA-Sequencing and clinical data of LGG patients were downloaded from publicly available databases. Bioinformatics approaches were used to analyze the relationship between PRGs and LGG patients' prognosis, clinicopathological features, and immune status. The NMF algorithm was used to differentiate phenotypes, the LASSO regression model was used to construct prognostic signature, and GSEA was used to analyze biological functions and pathways. The expression of the signature genes was verified using qRT-PCR. In addition, the L1000FWD and CMap tools were utilized to screen potential therapeutic drugs or small molecule compounds and validate their effects in glioma cell lines using CCK-8 and colony formation assays.
RESULTS
Based on PRGs, we defined two phenotypes with different prognoses. Stepwise regression analysis was carried out to identify the 3 signature genes to construct a pyroptosis-related signature. After that, samples from the training and test cohorts were incorporated into the signature and divided by the median RiskScore value (namely, Risk-H and Risk-L). The signature shows excellent predictive LGG prognostic power in the training and validation cohorts. The prognostic signature accurately stratifies patients according to prognostic differences and has predictive value for immune cell infiltration and immune checkpoint expression. Finally, the inhibitory effect of the small molecule inhibitor fedratinib on the viability and proliferation of various glioma cells was verified using cell biology-related experiments.
CONCLUSION
This study developed and validated a novel pyroptosis-related signature, which may assist instruct clinicians to predict the prognosis and immunological status of LGG patients more precisely. Fedratinib was found to be a small molecule inhibitor that significantly inhibits glioma cell viability and proliferation, which provides a new therapeutic strategy for gliomas.
背景
细胞焦亡是由gasdermin 超家族介导的程序性细胞死亡，伴有炎症和免疫反应。外源性激活的细胞焦亡在肿瘤微环境中仍未得到很好的描述。此外，低级别胶质瘤（LGG）中与细胞焦亡相关的基因（PRGs）是否可以作为生物标志物尚不清楚。
方法
从公共数据库中下载 LGG 患者的 RNA-Sequencing 和临床数据。使用生物信息学方法分析 PRGs 与 LGG 患者预后、临床病理特征和免疫状态之间的关系。使用 NMF 算法对表型进行区分，使用 LASSO 回归模型构建预后签名，使用 GSEA 分析生物学功能和途径。使用 qRT-PCR 验证签名基因的表达。此外，使用 L1000FWD 和 CMap 工具筛选潜在的治疗药物或小分子化合物，并使用 CCK-8 和集落形成实验验证其在神经胶质瘤细胞系中的作用。
结果
基于 PRGs，我们定义了两种具有不同预后的表型。逐步回归分析确定了 3 个签名基因来构建一个与细胞焦亡相关的签名。之后，将训练和测试队列的样本纳入签名，并通过中位数 RiskScore 值（即 Risk-H 和 Risk-L）进行划分。该签名在训练和验证队列中对 LGG 预后具有出色的预测能力。该预后签名可以根据预后差异准确分层患者，并且对免疫细胞浸润和免疫检查点表达具有预测价值。最后，通过细胞生物学相关实验验证了小分子抑制剂 fedratinib 对各种神经胶质瘤细胞活力和增殖的抑制作用。
结论
本研究开发并验证了一种新的与细胞焦亡相关的签名，该签名可能有助于临床医生更准确地预测 LGG 患者的预后和免疫状态。发现小分子抑制剂 fedratinib 显著抑制神经胶质瘤细胞的活力和增殖，为神经胶质瘤提供了新的治疗策略。
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