Department of Statistics, University of Salamanca, Salamanca, Spain.
Instituto de Investigación biomédica de Salamanca, IBSAL- University Hospital of Salamanca, Salamanca, Spain.
Sci Rep. 2020 Jul 9;10(1):11270. doi: 10.1038/s41598-020-67743-7.
Diagnosis and classification of gliomas mostly relies on histopathology and a few genetic markers. Here we interrogated microarray gene expression profiles (GEP) of 268 diffuse astrocytic gliomas-33 diffuse astrocytomas (DA), 52 anaplastic astrocytomas (AA) and 183 primary glioblastoma (GBM)-based on multivariate analysis, to identify discriminatory GEP that might support precise histopathological tumor stratification, particularly among inconclusive cases with II-III grade diagnosed, which have different prognosis and treatment strategies. Microarrays based GEP was analyzed on 155 diffuse astrocytic gliomas (discovery cohort) and validated in another 113 tumors (validation set) via sequential univariate analysis (pairwise comparison) for discriminatory gene selection, followed by nonnegative matrix factorization and canonical biplot for identification of discriminatory GEP among the distinct histological tumor subtypes. GEP data analysis identified a set of 27 genes capable of differentiating among distinct subtypes of gliomas that might support current histological classification. DA + AA showed similar molecular profiles with only a few discriminatory genes overexpressed (FSTL5 and SFRP2) and underexpressed (XIST, TOP2A and SHOX2) in DA vs AA and GBM. Compared to DA + AA, GBM displayed underexpression of ETNPPL, SH3GL2, GABRG2, SPX, DPP10, GABRB2 and CNTN3 and overexpression of CHI3L1, IGFBP3, COL1A1 and VEGFA, among other differentially expressed genes.
诊断和分类胶质瘤主要依赖于组织病理学和少数遗传标志物。在这里，我们通过多元分析研究了 268 例弥漫性星形细胞瘤-33 例弥漫性星形细胞瘤（DA）、52 例间变性星形细胞瘤（AA）和 183 例原发性胶质母细胞瘤（GBM）的微阵列基因表达谱（GEP），以确定具有鉴别能力的 GEP，这些 GEP 可能支持精确的组织病理学肿瘤分层，特别是在诊断为 II-III 级的不确定病例中，这些病例的预后和治疗策略不同。基于微阵列的 GEP 分析了 155 例弥漫性星形细胞瘤（发现队列），并在另外 113 例肿瘤（验证集）中通过顺序单变量分析（成对比较）进行了验证，以进行鉴别基因选择，然后进行非负矩阵分解和规范双图，以识别不同组织学肿瘤亚型之间的鉴别 GEP。GEP 数据分析确定了一组 27 个基因，这些基因能够区分不同类型的胶质瘤，可能支持当前的组织学分类。DA+AA 显示出相似的分子谱，仅在 DA 与 AA 和 GBM 中过表达（FSTL5 和 SFRP2）和低表达（XIST、TOP2A 和 SHOX2）少数鉴别基因。与 DA+AA 相比，GBM 显示出 ETNPPL、SH3GL2、GABRG2、SPX、DPP10、GABRB2 和 CNTN3 的低表达以及 CHI3L1、IGFBP3、COL1A1 和 VEGFA 等其他差异表达基因的高表达。
