Laser Capture Microdissection and RNA-Seq Analysis: High Sensitivity Approaches to Explain Histopathological Heterogeneity in Human Glioblastoma FFPE Archived Tissues.

Prospero Civita,Paolo Aretini,Michele Menicagli,Sara Franceschi,Chiara Maria Mazzanti,Antonio Giuseppe Naccarato,Francesco Pasqualetti,Francesca Lessi,Valerio Ortenzi

doi:10.3389/fonc.2019.00482

Abstract

Laser capture microdissection (LCM) coupled with RNA-seq is a powerful tool to identify genes that are differentially expressed in specific histological tumor subtypes. To better understand the role of single tumor cell populations in the complex heterogeneity of glioblastoma, we paired microdissection and NGS technology to study intra-tumoral differences into specific histological regions and cells of human GBM FFPE tumors. We here isolated astrocytes, neurons and endothelial cells in 6 different histological contexts: tumor core astrocytes, pseudopalisading astrocytes, perineuronal astrocytes in satellitosis, neurons with satellitosis, tumor blood vessels, and normal blood vessels. A customized protocol was developed for RNA amplification, library construction, and whole transcriptome analysis of each single portion. We first validated our protocol comparing the obtained RNA expression pattern with the gene expression levels of RNA-seq raw data experiments from the BioProject NCBI database, using Spearman's correlation coefficients calculation. We found a good concordance for pseudopalisading and tumor core astrocytes compartments (0.5 Spearman correlation) and a high concordance for perineuronal astrocytes, neurons, normal, and tumor endothelial cells compartments (0.7 Spearman correlation). Then, Principal Component Analysis and differential expression analysis were employed to find differences between tumor compartments and control tissue and between same cell types into distinct tumor contexts. Data consistent with the literature emerged, in which multiple therapeutic targets significant for glioblastoma (such as Integrins, Extracellular Matrix, transmembrane transport, and metabolic processes) play a fundamental role in the disease progression. Moreover, specific cellular processes have been associated with certain cellular subtypes within the tumor. Our results are promising and suggest a compelling method for studying glioblastoma heterogeneity in FFPE samples and its application in both prospective and retrospective studies.

Highlights

Glioblastoma (GBM) is considered the most malignant primary tumor of the brain accounting for ∼54% of all gliomas and 16% of all primary brain tumors [1]
We found an overexpression of proangiogenic genes and pathways and genes involved in cell migration in PTC cells, such as Angiopoietin 2 (ANGPT2), Urokinase Plasminogen Activator Receptor (PLAUR), Growth Differentiation Factor 15 (GDF15), Matrix Gla Protein (MGP), Proto-oncogene serine/threonine-protein kinase Pim-1 (PIM1), Cullin 1 (CUL1), and Mitogen-activated protein kinases—MAPK (MAP3K6 and MAPK7)
We provide a feasible and reliable method for isolating pure GBM cell populations from different histological compartments, with Laser capture microdissection (LCM) approach, minimizing cross-contamination

Summary

Introduction

Glioblastoma (GBM) is considered the most malignant primary tumor of the brain accounting for ∼54% of all gliomas and 16% of all primary brain tumors [1]. Histopathologic features, that distinguish GBM from lower grade astrocytomas, are found near the contrast-enhancing rim that surrounds the tumor core and includes [1] foci of necrosis, usually with evidence of surrounding cellular pseudopalisades (“pseudopalisading necrosis”); [2] microvascular hyperplasia, a form of angiogenesis morphologically recognized as endothelial proliferation within newly sprouted vessels [7], and [3] “perineuronal satellitosis,” typical grouping of neoplastic astrocytes around neurons when the tumor infiltrates the gray matter [8] Connections between these cells compartments play an important role in the development and malignant progression of glioblastoma

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Conclusion