Department of Neurosurgery, The First Hospital of China Medical University, No. 155, Nanjing North Street, Heping District, Shenyang, Liaoning Province, 110001, PR China.
Sci Rep. 2019 Jan 14;9(1):96. doi: 10.1038/s41598-018-36471-4.
Diffuse astrocytoma (including glioblastoma) is morbid with a worse prognosis than other types of glioma. Therefore, we sought to build a progression-associated score to improve malignancy and prognostic predictions for astrocytoma. The astrocytoma progression (AP) score was constructed through bioinformatics analyses of the training cohort (TCGA RNA-seq) and included 18 genes representing distinct aspects of regulation during astrocytoma progression. This classifier could successfully discriminate patients with distinct prognoses in the training and validation (REMBRANDT, GSE16011 and TCGA-GBM Microarray) cohorts (P < 0.05 in all cohorts) and in different clinicopathological subgroups. Distinct patterns of somatic mutations and copy number variation were also observed. The bioinformatics analyses suggested that genes associated with a higher AP score were significantly involved in cancer progression-related biological processes, such as the cell cycle and immune/inflammatory responses, whereas genes associated with a lower AP score were associated with relatively normal nervous system biological processes. The analyses indicated that the AP score was a robust predictor of patient survival, and its ability to predict astrocytoma malignancy was well elucidated. Therefore, this bioinformatics-based scoring system suggested that astrocytoma progression could distinguish patients with different underlying biological processes and clinical outcomes, facilitate more precise tumour grading and possibly shed light on future classification strategies and therapeutics for astrocytoma patients.
弥漫性星形细胞瘤（包括胶质母细胞瘤）的预后较差，比其他类型的胶质瘤更具侵袭性。因此，我们试图构建一个与进展相关的评分，以提高星形细胞瘤的恶性程度和预后预测。星形细胞瘤进展（AP）评分是通过对训练队列（TCGA RNA-seq）的生物信息学分析构建的，包括代表星形细胞瘤进展过程中不同调节方面的 18 个基因。该分类器可以成功区分训练和验证队列（REMBRANDT、GSE16011 和 TCGA-GBM Microarray）以及不同临床病理亚组中具有不同预后的患者（所有队列中的 P 值均<0.05）。还观察到不同的体细胞突变和拷贝数变异模式。生物信息学分析表明，与较高 AP 评分相关的基因与癌症进展相关的生物学过程显著相关，如细胞周期和免疫/炎症反应，而与较低 AP 评分相关的基因与相对正常的神经系统生物学过程相关。分析表明，AP 评分是患者生存的可靠预测因子，其预测星形细胞瘤恶性程度的能力得到了很好的阐明。因此，这种基于生物信息学的评分系统表明，星形细胞瘤的进展可以区分具有不同潜在生物学过程和临床结局的患者，有助于更精确的肿瘤分级，并可能为星形细胞瘤患者的未来分类策略和治疗提供启示。
