Computational identification of specific genes for glioblastoma stem-like cells identity

• Published in: Scientific reports 2018-05, Vol.8 (1), p.7769-10, Article 7769
• Main Authors: Fiscon, Giulia, Conte, Federica, Licursi, Valerio, Nasi, Sergio, Paci, Paola
• Format: Article
• Language: English
• Subjects: 38; 38/91; 45/100; 631/114/2413; 692/53/2423; Brain cancer; Brain Neoplasms - genetics; Brain Neoplasms - pathology; Brain stem; Brain tumors; Cell differentiation; Cell Differentiation - genetics; Computational Biology; Computational neuroscience; Computer applications; Extracellular matrix; Gene expression; Gene Expression Regulation, Neoplastic; Gene regulation; Glioblastoma; Glioblastoma - genetics; Glioblastoma - pathology; Glioblastoma cells; Glioma cells; Humanities and Social Sciences; Humans; multidisciplinary; Neoplastic Stem Cells - metabolism; Neoplastic Stem Cells - pathology; Olig2 protein; Phenotypes; Science; Science (multidisciplinary); Software; Therapeutic applications; Transcription factors; Transcription Factors - genetics; Transcription Factors - metabolism; Transcription Factors - physiology; Transcriptome
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-018-26081-5

Glioblastoma, the most malignant brain cancer, contains self-renewing, stem-like cells that sustain tumor growth and therapeutic resistance. Identifying genes promoting stem-like cell differentiation might unveil targets for novel treatments. To detect them, here we apply SWIM – a software able to unveil genes (named switch genes) involved in drastic changes of cell phenotype – to public datasets of gene expression profiles from human glioblastoma cells. By analyzing matched pairs of stem-like and differentiated glioblastoma cells, SWIM identified 336 switch genes, potentially involved in the transition from stem-like to differentiated state. A subset of them was significantly related to focal adhesion and extracellular matrix and strongly down-regulated in stem-like cells, suggesting that they may promote differentiation and restrain tumor growth. Their expression in differentiated cells strongly correlated with the down-regulation of transcription factors like OLIG2, POU3F2, SALL2, SOX2, capable of reprogramming differentiated glioblastoma cells into stem-like cells. These findings were corroborated by the analysis of expression profiles from glioblastoma stem-like cell lines, the corresponding primary tumors, and conventional glioma cell lines. Switch genes represent a distinguishing feature of stem-like cells and we are persuaded that they may reveal novel potential therapeutic targets worthy of further investigation.