Abstract
Simple SummaryThe current classification of central nervous system tumors has incorporated molecular changes that have clarified biological behavior and categorized gliomas into different types and malignancy grades. The most malignant type—glioblastoma, represents one of the most therapeutically challenging tumors, with a median survival of only 12–14 months despite trimodal therapy. In our integrative large-scale study, we used genomics, transcriptomics, epigenomics, and proteomics to investigate and make sense of the molecular changes that activate or inhibit the EGFR-PI3K-AKT-mTOR signaling pathway. Different pathohistological types of diffuse brain gliomas harbored distinct changes. A better understanding of signaling pathway regulation helps to the discovery of new targets for glioma therapies. Our results have potential for diagnostics improvement and tailored therapies.Diffuse gliomas are a heterogeneous group of tumors with aggressive biological behavior and a lack of effective treatment methods. Despite new molecular findings, the differences between pathohistological types still require better understanding. In this in silico analysis, we investigated AKT1, AKT2, AKT3, CHUK, GSK3β, EGFR, PTEN, and PIK3AP1 as participants of EGFR-PI3K-AKT-mTOR signaling using data from the publicly available cBioPortal platform. Integrative large-scale analyses investigated changes in copy number aberrations (CNA), methylation, mRNA transcription and protein expression within 751 samples of diffuse astrocytomas, anaplastic astrocytomas and glioblastomas. The study showed a significant percentage of CNA in PTEN (76%), PIK3AP1 and CHUK (75% each), EGFR (74%), AKT2 (39%), AKT1 (32%), AKT3 (19%) and GSK3β (18%) in the total sample. Comprehensive statistical analyses show how genomics and epigenomics affect the expression of examined genes differently across various pathohistological types and grades, suggesting that genes AKT3, CHUK and PTEN behave like tumor suppressors, while AKT1, AKT2, EGFR, and PIK3AP1 show oncogenic behavior and are involved in enhanced activity of the EGFR-PI3K-AKT-mTOR signaling pathway. Our findings contribute to the knowledge of the molecular differences between pathohistological types and ultimately offer the possibility of new treatment targets and personalized therapies in patients with diffuse gliomas.
Highlights
Gliomas are a heterogeneous group of central nervous system tumors that still lack efficient treatment methods regardless of medical progress [1]
This study aims to understand the significance of the EGFR-PI3K-AKT-mTOR signaling pathway and reveal differences between AKT1, AKT2, AKT3, CHUK, GSK3β, EGFR, PTEN, and PIK3AP1 roles within different grades and types of diffuse brain gliomas
We found that aberrations in the lowest malignancy type (DA) affects AKT1, AKT2 and GSK3β genes with a similar frequency, while a different set of genes (CHUK, EGFR, PIK3AP1, and PTEN) were highly affected in glioblastomas multiforme (GBM) (Table 2)
Summary
Gliomas are a heterogeneous group of central nervous system tumors that still lack efficient treatment methods regardless of medical progress [1]. Recent studies of the molecular profile of gliomas show the complex dynamics of tumor progression and explain the evolution of mutations of this biologically aggressive group of tumors [4]. Recent findings in neurooncology have led to changes in the WHO (World Health Organization) classification from 2016 of tumors of the central nervous system, which incorporated both phenotypic and molecular parameters in the division of glial tumors. New classification improved the prognosis of diffuse glioma. The new classification groups tumors that share the same prognostic markers and potentially allows for common treatment of molecularly similar entities [5]. Despite new knowledge that has united diffuse gliomas, the molecular differences between individual pathohistological types and grades are still insufficiently explained [6]. One of the reasons why we focused our interest on EGFR-PI3K-AKT-mTOR signaling pathway is that our previous investigation, using Array
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