Priority Research Papers:
Computational drugs repositioning identifies inhibitors of oncogenic PI3K/AKT/P70S6K-dependent pathways among FDA-approved compounds
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Diego Carrella1, Isabella Manni3, Barbara Tumaini1, Rosanna Dattilo2 , Federica Papaccio3, Margherita Mutarelli1, Francesco Sirci1, Carla A. Amoreo4, Marcella Mottolese4, Manuela Iezzi5, Laura Ciolli5, Valentina Aria6, Roberta Bosotti7, Antonella Isacchi7, Fabrizio Loreni6, Alberto Bardelli8,9, Vittorio E. Avvedimento10, Diego di Bernardo1,11 and Luca Cardone3
1 Telethon Institute of Genetics and Medicine, Pozzuoli, Naples, Italy
2 Department of Hematology, Oncology and Molecular Medicine, Biobank Unit, Istituto Superiore di Sanità, Rome, Italy
3 Department of Research, Advanced Diagnostics, and Technological Innovations, Regina Elena National Cancer Institute, Rome, Italy
4 S.C. Anatomia Patologica, Regina Elena National Cancer Institute, Rome, Italy
5 Immuno-Oncology Laboratory, Aging Research Center, G. d’Annunzio University of Chieti, Pescara, Italy
6 Department of Biology, University of Rome Tor Vergata, Rome, Italy
7 Nerviano Medical Sciences SRL, Nerviano, Italy
8 Candiolo Cancer Institute-FPO, IRCCS, Candiolo, Torino, Italy
9 Department of Oncology, University of Torino, Candiolo, Torino, Italy
10 Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università degli Studi di Napoli “Federico II”, Naples, Italy
11 Department of Electrical Engineering and Information Technology, University of Naples “Federico II”, Naples, Italy
Luca Cardone, email:
Diego di Bernardo, email:
Keywords: oncogenes, PI3K-dependent pathways, gene expression signatures, drugs network, FDA-approved drugs
Received: January 03, 2016 Accepted: August 03, 2016 Published: August 16, 2016
The discovery of inhibitors for oncogenic signalling pathways remains a key focus in modern oncology, based on personalized and targeted therapeutics. Computational drug repurposing via the analysis of FDA-approved drug network is becoming a very effective approach to identify therapeutic opportunities in cancer and other human diseases. Given that gene expression signatures can be associated with specific oncogenic mutations, we tested whether a “reverse” oncogene-specific signature might assist in the computational repositioning of inhibitors of oncogenic pathways. As a proof of principle, we focused on oncogenic PI3K-dependent signalling, a molecular pathway frequently driving cancer progression as well as raising resistance to anticancer-targeted therapies. We show that implementation of “reverse” oncogenic PI3K-dependent transcriptional signatures combined with interrogation of drug networks identified inhibitors of PI3K-dependent signalling among FDA-approved compounds. This led to repositioning of Niclosamide (Niclo) and Pyrvinium Pamoate (PP), two anthelmintic drugs, as inhibitors of oncogenic PI3K-dependent signalling. Niclo inhibited phosphorylation of P70S6K, while PP inhibited phosphorylation of AKT and P70S6K, which are downstream targets of PI3K. Anthelmintics inhibited oncogenic PI3K-dependent gene expression and showed a cytostatic effect in vitro and in mouse mammary gland. Lastly, PP inhibited the growth of breast cancer cells harbouring PI3K mutations. Our data indicate that drug repositioning by network analysis of oncogene-specific transcriptional signatures is an efficient strategy for identifying oncogenic pathway inhibitors among FDA-approved compounds. We propose that PP and Niclo should be further investigated as potential therapeutics for the treatment of tumors or diseases carrying the constitutive activation of the PI3K/P70S6K signalling axis.
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