Institute for Systems Biology, Seattle, WA 98109, USA.
The Ben and Catherine Ivy Center for Advanced Brain Tumor Treatment, Swedish Neuroscience Institute, Seattle, WA 98122, USA.
Cell Syst. 2017 May 24;4(5):516-529.e7. doi: 10.1016/j.cels.2017.03.004. Epub 2017 Mar 29.
We present a systems strategy that facilitated the development of a molecular signature for glioblastoma (GBM), composed of 33 cell-surface transmembrane proteins. This molecular signature, GBMSig, was developed through the integration of cell-surface proteomics and transcriptomics from patient tumors in the REMBRANDT (n = 228) and TCGA datasets (n = 547) and can separate GBM patients from control individuals with a Matthew's correlation coefficient value of 0.87 in a lock-down test. Functionally, 17/33 GBMSig proteins are associated with transforming growth factor β signaling pathways, including CD47, SLC16A1, HMOX1, and MRC2. Knockdown of these genes impaired GBM invasion, reflecting their role in disease-perturbed changes in GBM. ELISA assays for a subset of GBMSig (CD44, VCAM1, HMOX1, and BIGH3) on 84 plasma specimens from multiple clinical sites revealed a high degree of separation of GBM patients from healthy control individuals (area under the curve is 0.98 in receiver operating characteristic). In addition, a classifier based on these four proteins differentiated the blood of pre- and post-tumor resections, demonstrating potential clinical value as biomarkers.
我们提出了一种系统策略,该策略有助于开发胶质母细胞瘤(GBM)的分子特征,该特征由 33 个细胞表面跨膜蛋白组成。该分子特征 GBMSig 是通过整合 REMBRANDT(n=228)和 TCGA 数据集(n=547)中患者肿瘤的细胞表面蛋白质组学和转录组学而开发的,在锁定测试中,它可以将 GBM 患者与对照个体区分开来,马修斯相关系数值为 0.87。从功能上讲,GBMSig 的 17/33 种蛋白与转化生长因子 β 信号通路有关,包括 CD47、SLC16A1、HMOX1 和 MRC2。这些基因的敲低会损害 GBM 的侵袭,反映了它们在 GBM 疾病扰动变化中的作用。对来自多个临床站点的 84 份血浆标本中的一部分 GBMSig(CD44、VCAM1、HMOX1 和 BIGH3)进行 ELISA 检测,结果显示 GBM 患者与健康对照个体之间具有高度的分离度(曲线下面积在接收者操作特征中为 0.98)。此外,基于这四种蛋白质的分类器可以区分肿瘤前后的血液,证明了作为生物标志物的潜在临床价值。