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1.
Int J Oncol ; 58(2): 211-225, 2021 02.
Article in English | MEDLINE | ID: mdl-33491755

ABSTRACT

Neuroblastoma (NB) is a heterogenous disease with treatment varying from observation for low­risk tumors, to extensive therapy with chemotherapy, surgery, radiotherapy, and autologous bone­marrow­transplantation and immunotherapy. However, a high frequency of primary­chemo­refractory disease and recurrences urgently require novel treatment strategies. The present study therefore investigated the anti­NB efficacy of the recently FDA­approved phosphoinositide 3­kinase (PI3K) and fibroblast growth factor receptor (FGFR) inhibitors, alpelisib (BYL719) and erdafitinib (JNJ­42756493), alone and in combination with or without cisplatin, vincristine, or doxorubicin on 5 NB cell lines. For this purpose, the NB cell lines, SK­N­AS, SK­N­BE(2)­C, SK­N­DZ, SK­N­FI and SK­N­SH (where SK­N­DZ had a deletion of PIK3C2G and none had FGFR mutations according to the Cancer Program's Dependency Map, although some were chemoresistant), were tested for their sensitivity to FDA­approved inhibitors alone or in combination, or together with cytostatic drugs by viability, cytotoxicity, apoptosis and proliferation assays. The results revealed that monotherapy with alpelisib or erdafitinib resulted in a dose­dependent inhibition of cell viability and proliferation. Notably, the combined use of PI3K and FGFR inhibitors resulted in an enhanced efficacy, while their combined use with the canonical cytotoxic agents, cisplatin, vincristine and doxorubicin, resulted in variable synergistic, additive and antagonistic effects. Collectively, the present study provides pre­clinical evidence that PI3K and FGFR inhibitors exhibit promising anti­NB activity. The data presented herein also indicate that the incorporation of these inhibitors into chemotherapeutic regimens requires careful consideration and further research in order to obtain a beneficial efficacy. Nevertheless, the addition of PI3K and FGFR inhibitors to the treatment arsenal might reduce the occurrence of refractory and relapsing disease in NB without FGFR and PI3K mutations.


Subject(s)
Antineoplastic Combined Chemotherapy Protocols/pharmacology , Cytostatic Agents/pharmacology , Neuroblastoma/drug therapy , Phosphoinositide-3 Kinase Inhibitors/pharmacology , Receptors, Fibroblast Growth Factor/antagonists & inhibitors , Antineoplastic Combined Chemotherapy Protocols/therapeutic use , Apoptosis/drug effects , Cell Line, Tumor , Cell Proliferation/drug effects , Cell Survival/drug effects , Child , Cisplatin/pharmacology , Cisplatin/therapeutic use , Cytostatic Agents/therapeutic use , Doxorubicin/pharmacology , Doxorubicin/therapeutic use , Drug Resistance, Neoplasm , Drug Synergism , Humans , Neuroblastoma/pathology , Phosphoinositide-3 Kinase Inhibitors/therapeutic use , Pyrazoles/pharmacology , Pyrazoles/therapeutic use , Quinoxalines/pharmacology , Quinoxalines/therapeutic use , Receptors, Fibroblast Growth Factor/metabolism , Thiazoles/pharmacology , Thiazoles/therapeutic use , Vincristine/pharmacology , Vincristine/therapeutic use
2.
Pharmacol Res Perspect ; 8(4): e00600, 2020 08.
Article in English | MEDLINE | ID: mdl-32662237

ABSTRACT

Drug development is an arduous procedure, necessitating testing the interaction of a large number of potential candidates with potential interacting (macro)molecules. Therefore, any method which could provide an initial screening of potential candidate drugs might be of interest for the acceleration of the procedure, by highlighting interesting compounds, prior to in vitro and in vivo validation. In this line, we present a method which may identify potential hits, with agonistic and/or antagonistic properties on GPCR receptors, integrating the knowledge on signaling events triggered by receptor activation (GPCRs binding to Gα,ß,γ proteins, and activating Gα , exchanging GDP for GTP, leading to a decreased affinity of the Gα for the GPCR). We show that, by integrating GPCR-ligand and Gα -GDP or -GTP binding in docking simulation, which correctly predicts crystallographic data, we can discriminate agonists, partial agonists, and antagonists, through a linear function, based on the ΔG (Gibbs-free energy) of liganded-GPCR/Gα -GDP. We built our model using two Gαs (ß2-adrenergic and prostaglandin-D2 ), four Gαi (µ-opioid, dopamine-D3, adenosine-A1, rhodopsin), and one Gαo (serotonin) receptors and validated it with a series of ligands on a recently deorphanized Gαi receptor (OXER1). This approach could be a valuable tool for initial in silico validation and design of GPRC-interacting ligands.


Subject(s)
Drug Development/methods , Receptors, G-Protein-Coupled/agonists , Receptors, G-Protein-Coupled/antagonists & inhibitors , Computational Biology/methods , Crystallography , Guanosine Diphosphate/metabolism , Guanosine Triphosphate/metabolism , Humans , Ligands , Molecular Docking Simulation , Receptors, G-Protein-Coupled/metabolism , Signal Transduction
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