Title |
Sonic Hedgehog Medulloblastoma Cancer Stem Cells Mirnome and Transcriptome Highlight Novel Functional Networks
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Published in |
International Journal of Molecular Sciences, August 2018
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DOI | 10.3390/ijms19082326 |
Pubmed ID | |
Authors |
Agnese Po, Luana Abballe, Claudia Sabato, Francesca Gianno, Martina Chiacchiarini, Giuseppina Catanzaro, Enrico De Smaele, Felice Giangaspero, Elisabetta Ferretti, Evelina Miele, Zein Mersini Besharat |
Abstract |
Molecular classification has improved the knowledge of medulloblastoma (MB), the most common malignant brain tumour in children, however current treatments cause severe side effects in patients. Cancer stem cells (CSCs) have been described in MB and represent a sub population characterised by self-renewal and the ability to generate tumour cells, thus representing the reservoir of the tumour. To investigate molecular pathways that characterise this sub population, we isolated CSCs from Sonic Hedgehog Medulloblastoma (SHH MB) arisen in Patched 1 (Ptch1) heterozygous mice, and performed miRNA- and mRNA-sequencing. Comparison of the miRNA-sequencing of SHH MB CSCs with that obtained from cerebellar Neural Stem Cells (NSCs), allowed us to obtain a SHH MB CSC miRNA differential signature. Pathway enrichment analysis in SHH MB CSCs mirnome and transcriptome was performed and revealed a series of enriched pathways. We focused on the putative targets of the SHH MB CSC miRNAs that were involved in the enriched pathways of interest, namely pathways in cancer, PI3k-Akt pathway and protein processing in endoplasmic reticulum pathway. In silico analysis was performed in SHH MB patients and identified several genes, whose expression was associated with worse overall survival of SHH MB patients. This study provides novel candidates whose functional role should be further investigated in SHH MB. |
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France | 1 | 100% |
Demographic breakdown
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Mendeley readers
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Readers by professional status | Count | As % |
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Student > Ph. D. Student | 7 | 37% |
Student > Bachelor | 3 | 16% |
Researcher | 3 | 16% |
Student > Master | 1 | 5% |
Professor > Associate Professor | 1 | 5% |
Other | 0 | 0% |
Unknown | 4 | 21% |
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Neuroscience | 2 | 11% |
Agricultural and Biological Sciences | 2 | 11% |
Chemical Engineering | 1 | 5% |
Other | 2 | 11% |
Unknown | 5 | 26% |