Department of Gynecological Oncology, The First Hospital of Jilin University, Changchun, 130021, Jilin, China.
Department of Public Laboratory Platform, The First Hospital of Jilin University, Changchun, 130061, Jilin, China.
BMC Med Genomics. 2022 May 12;15(1):111. doi: 10.1186/s12920-022-01261-5.
To explore the autophagy-related prognostic signature (ARPs) via data mining in gene expression profiles for glioblastoma (GBM).
Using the Cancer Genome Atlas (TCGA) database, we obtained 156 GBM samples and 5 adjacent normal samples, and denoted them as discovery cohort. Univariate Cox regression analysis was used to screen autophagy genes that related to GBM prognosis. Then, the least absolute shrinkage and selection operator Cox regression model was used to construct an autophagy-based ARPs, which was validated in an external cohort containing 80 GBM samples. The patients in the above-mentioned cohorts were divided into low-risk group and high-risk group according to the median prognostic risk score, and the diagnostic performance of the model was assessed by receiver operating characteristic curve analyses. The gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment analyses were performed between the high-risk and low-risk patients. Additionally, the genetic features of ARPs, such as genetic variation profiles, correlations with tumor-infiltrating lymphocytes (TILs), and potential drug sensitivity, were further assessed in the TCGA-GBM data set.
A signature of ARPs including NDUFB9, BAK1, SUPT3H, GAPDH, CDKN1B, CHMP6, and EGFR were detected and validated. We identified a autophagy-related prognosis 7-gene signature correlated survival prognosis, immune infiltration, level of cytokines, and cytokine receptor in tumor microenvironment. Furthermore, the signature was tested in several pathways related to disorders of tumor microenvironment, as well as cancer-related pathways. Additionally, a range of small molecular drugs, shown to have a potential therapeutic effect on GBM.
We constructed an autophagy-based 7-gene signature, which could serve as an independent prognostic indicator for cases of GBM and sheds light on the role of autophagy as a potential therapeutic target in GBM.
通过基因表达谱数据挖掘，探讨胶质母细胞瘤（GBM）中与自噬相关的预后标志物（ARPs）。
利用癌症基因组图谱（TCGA）数据库，我们获得了 156 例 GBM 样本和 5 例相邻正常样本，并将其标记为发现队列。采用单因素 Cox 回归分析筛选与 GBM 预后相关的自噬基因。然后，采用最小绝对收缩和选择算子 Cox 回归模型构建基于自噬的 ARPs，并在包含 80 例 GBM 样本的外部队列中进行验证。根据中位预后风险评分，将上述队列中的患者分为低危组和高危组，并通过接受者操作特征曲线分析评估模型的诊断性能。对高风险和低风险患者进行基因本体论和京都基因与基因组百科全书通路富集分析。此外，还进一步在 TCGA-GBM 数据集中评估了 ARPs 的遗传特征，如遗传变异谱、与肿瘤浸润淋巴细胞（TILs）的相关性以及潜在的药物敏感性。
检测并验证了一个包括 NDUFB9、BAK1、SUPT3H、GAPDH、CDKN1B、CHMP6 和 EGFR 的 ARPs 标志。我们确定了一个与生存预后、免疫浸润、肿瘤微环境中细胞因子和细胞因子受体水平相关的自噬相关预后 7 基因标志。此外，该标志在肿瘤微环境紊乱相关的多个通路以及癌症相关通路中进行了测试。此外，还测试了一系列小分子药物，这些药物对 GBM 具有潜在的治疗效果。
我们构建了一个基于自噬的 7 基因标志，可以作为 GBM 的独立预后指标，并揭示了自噬作为 GBM 潜在治疗靶点的作用。
