通过数据库挖掘鉴定骨膜蛋白作为脑胶质瘤的一个潜在的生物标志物。

Identification of Periostin as a Potential Biomarker in Gliomas by Database Mining.

机构信息

Department of Neurosurgery, Faculty of Medicine, Universitas Padjadjaran-Dr. Hasan Sadikin Hospital, Bandung, West Java, Indonesia; Oncology and Stem Cell Working Group, Faculty of Medicine, Universitas Padjadjaran-Dr. Hasan Sadikin Hospital, Bandung, West Java, Indonesia.

Oncology and Stem Cell Working Group, Faculty of Medicine, Universitas Padjadjaran-Dr. Hasan Sadikin Hospital, Bandung, West Java, Indonesia.

出版信息

World Neurosurg. 2020 Mar;135:e137-e163. doi: 10.1016/j.wneu.2019.11.077. Epub 2019 Nov 28.

DOI:10.1016/j.wneu.2019.11.077

PMID:31785437

Abstract

BACKGROUND

Bioinformatics analysis integrating microenvironmental factors and single cell analysis segregated the glioblastoma (GBM) subtype into 3 subtypes: proneural, classic, and mesenchymal. Mesenchymal GBM tends to have the worst survival but benefits from aggressive treatment protocols. Therefore, it is clinically meaningful to identify relevant biomarkers to distinguish the mesenchymal subtype. Moreover, in developing nations with limited resources, rigorous examinations are costly and inefficient for patient care.

METHODS

In this study, we analyzed The Cancer Genome Atlas (TCGA)-Glioblastoma and TCGA-Low-Grade Glioma RNA sequencing (RNAseq) cohorts and confirmed that the mesenchymal subtype was associated with the worst prognosis.

RESULTS

We identified periostin (POSTN) as a mesenchymal subtype biomarker with prognostic value across histologic grades and confirmed the reliability of POSTN by gene expression meta-analysis combining TCGA, Chinese Glioma Genome Atlas (CGGA) and REMBRANDT (Repository for Molecular Brain Neoplasia Data) GBM cohorts (hazard ratio, 1.71 [range, 1.47-2.07], n = 693) and LGG cohorts (hazard ratio, 2.55 [range, 1.61-4.05], n = 1226).

CONCLUSIONS

By using available online glioma databases, our study provided an insight into the expression of POSTN as an independent predictor for patients with glioma (GBM and LGG) and could be useful for diagnostic simplification to identify high-risk groups.

摘要

背景

整合微环境因素和单细胞分析的生物信息学分析将胶质母细胞瘤（GBM）亚型分为 3 种亚型：神经前型、经典型和间质型。间充质 GBM 往往生存最差，但受益于积极的治疗方案。因此，识别相关的生物标志物来区分间充质亚型在临床上具有重要意义。此外，在资源有限的发展中国家，对患者进行严格的检查既昂贵又效率低下。

方法

在本研究中，我们分析了癌症基因组图谱（TCGA）-胶质母细胞瘤和 TCGA-低级别胶质瘤 RNA 测序（RNAseq）队列，并证实间充质亚型与最差的预后相关。

结果

我们确定了骨粘连蛋白（POSTN）作为一种具有跨组织学分级预后价值的间充质亚型生物标志物，并通过结合 TCGA、中国脑肿瘤基因组图谱（CGGA）和 REMBRANDT（脑肿瘤数据存储库）GBM 队列（风险比，1.71 [范围，1.47-2.07]，n=693）和 LGG 队列（风险比，2.55 [范围，1.61-4.05]，n=1226）的基因表达荟萃分析，证实了 POSTN 的可靠性。