A data-driven network model of primary myelofibrosis: transcriptional and post-transcriptional alterations in CD34+ cells
Articolo
Data di Pubblicazione:
2016
Citazione:
A data-driven network model of primary myelofibrosis: transcriptional and post-transcriptional alterations in CD34+ cells / Calura, E.; Pizzini, S.; Bisognin, A.; Coppe, A.; Sales, G.; Gaffo, E.; Fanelli, T.; Mannarelli, C.; Zini, Roberta; Norfo, Ruggiero; Pennucci, Valentina; Manfredini, Rossella; Romualdi, C.; Guglielmelli, P.; Vannucchi, A. M.; Bortoluzzi, Stefania; Associazione Italiana Per La Ricerca Sul Cancro Gruppo Italiano Malattie Mieloproliferative, Investigators. - In: BLOOD CANCER JOURNAL. - ISSN 2044-5385. - 6:6(2016), pp. 1-9. [10.1038/bcj.2016.47]
Abstract:
microRNAs (miRNAs) are relevant in the pathogenesis of primary myelofibrosis (PMF) but our understanding is limited to specific target genes and the overall systemic scenario islacking. By both knowledge-based and ab initio approaches for comparative analysis of CD34+ cells of PMF patients and healthy controls, we identified the deregulated pathways involving miRNAs and genes and new transcriptional and post-transcriptional regulatory circuits in PMF cells. These converge in a unique and integrated cellular process, in which the role of specific miRNAs is to wire, co-regulate and allow a fine crosstalk between the involved processes. The PMF pathway includes Akt signaling, linked to Rho GTPases, CDC42, PLD2, PTEN crosstalk with the hypoxia response and Calcium-linked cellular processes connected to cyclic AMP signaling. Nested on the depicted transcriptional scenario, predicted circuits are reported, opening new hypotheses. Links between miRNAs (miR-106a-5p, miR-20b-5p, miR-20a-5p, miR-17-5p, miR-19b-3p and let-7d-5p) and key transcription factors (MYCN, ATF, CEBPA, REL, IRF and FOXJ2) and their common target genes tantalizingly suggest new path to approach the disease. The study provides a global overview of transcriptional and post-transcriptional deregulations in PMF, and, unifying consolidated and predicted data, could be helpful to identify new combinatorial therapeutic strategy. Interactive PMF network model: http://compgen.bio.unipd.it/pmf-net/.
Tipologia CRIS:
Articolo su rivista
Elenco autori:
Calura, E.; Pizzini, S.; Bisognin, A.; Coppe, A.; Sales, G.; Gaffo, E.; Fanelli, T.; Mannarelli, C.; Zini, Roberta; Norfo, Ruggiero; Pennucci, Valentina; Manfredini, Rossella; Romualdi, C.; Guglielmelli, P.; Vannucchi, A. M.; Bortoluzzi, Stefania; Associazione Italiana Per La Ricerca Sul Cancro Gruppo Italiano Malattie Mieloproliferative, Investigators
Link alla scheda completa:
Link al Full Text:
Pubblicato in: