Mapping transcriptomic signatures of tumor stem cells in gliomas: correlating glioma stem cells with clinical and molecular data

• Grant number: 20/13533-0
• Support Opportunities: Scholarships in Brazil - Master
• Start date: December 01, 2020
• End date: November 30, 2022
• Field of knowledge: Health Sciences - Medicine
• Principal Investigator: Tathiane Maistro Malta Pereira
• Grantee: Renan de Lima Santos Simões
• Host Institution: Faculdade de Ciências Farmacêuticas de Ribeirão Preto (FCFRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil
• Associated research grant: 18/00583-0 - Integrative epigenomic analysis of gliomas: defining regulatory regions associated with stemness and with the hypermethylator phenotype of IDH1/2 mutant tumors, AP.JP

Abstract

Gliomas are the most common primary brain tumors in the central nervous system (CNS) and although they have been known and studied since the last century, the cellular origins and the process of gliomagenesis are still not well understood. For a long time, the classification, diagnosis and treatment of gliomas were based on histological characteristics, following the WHO classification where the gliomas are divided according to their histological similarity with CNS cells (astrocytic, oligodendroglial, oligoastrocytic and ependimals) in addition to assigning degrees (I to IV), reflecting the range from low to high degree of malignancy. Over time, it was observed that within the same classification group, distinct morphological and clinical characteristics were found. The advancement of technologies and knowledge has enabled the identification of new methods of molecular classification capable of stratifying gliomas more efficiently and targeting treatments for specific phenotypes. A revision of the classification was published by the WHO in 2016, in which, in addition to the histological aspects, it also covers molecular parameters, including in the classification the main molecular findings so far: mutations in the IDH1/2 and 1p19q codelection genes. Even with recent advances, the treatment of gliomas are still inefficient and unspecified. Following the new lines of research and technology, this project aims to develop a quantitative molecular measure of tumor stem cell enrichment in glioma samples, using gene expression data. Gene expression signatures analyzes in tumor cells within analysis of signaling pathways of the genes most important in defining the metric can help in the identification of molecular subtypes of gliomas, providing important data for a better understanding of tumor biology, a better diagnosis and treatment. (AU)