RESUMEN
Emergent resistance to all clinical antibiotics calls for the next generation of therapeutics. Here we report an effective antimicrobial strategy targeting the bacterial hydrogen sulfide (H2S)-mediated defense system. We identified cystathionine γ-lyase (CSE) as the primary generator of H2S in two major human pathogens, Staphylococcus aureus and Pseudomonas aeruginosa, and discovered small molecules that inhibit bacterial CSE. These inhibitors potentiate bactericidal antibiotics against both pathogens in vitro and in mouse models of infection. CSE inhibitors also suppress bacterial tolerance, disrupting biofilm formation and substantially reducing the number of persister bacteria that survive antibiotic treatment. Our results establish bacterial H2S as a multifunctional defense factor and CSE as a drug target for versatile antibiotic enhancers.
Asunto(s)
Antibacterianos/farmacología , Cistationina gamma-Liasa/antagonistas & inhibidores , Inhibidores Enzimáticos/farmacología , Sulfuro de Hidrógeno/metabolismo , Pseudomonas aeruginosa/efectos de los fármacos , Staphylococcus aureus/efectos de los fármacos , Animales , Antibacterianos/química , Antibacterianos/metabolismo , Biopelículas , Cristalografía por Rayos X , Cistationina gamma-Liasa/química , Cistationina gamma-Liasa/genética , Cistationina gamma-Liasa/metabolismo , Descubrimiento de Drogas , Farmacorresistencia Bacteriana , Sinergismo Farmacológico , Tolerancia a Medicamentos , Inhibidores Enzimáticos/química , Inhibidores Enzimáticos/metabolismo , Ratones , Pruebas de Sensibilidad Microbiana , Modelos Moleculares , Simulación del Acoplamiento Molecular , Estructura Molecular , Infecciones por Pseudomonas/tratamiento farmacológico , Infecciones por Pseudomonas/microbiología , Pseudomonas aeruginosa/enzimología , Pseudomonas aeruginosa/genética , Pseudomonas aeruginosa/crecimiento & desarrollo , Bibliotecas de Moléculas Pequeñas/química , Bibliotecas de Moléculas Pequeñas/metabolismo , Bibliotecas de Moléculas Pequeñas/farmacología , Infecciones Estafilocócicas/tratamiento farmacológico , Infecciones Estafilocócicas/microbiología , Staphylococcus aureus/enzimología , Staphylococcus aureus/genética , Staphylococcus aureus/crecimiento & desarrolloRESUMEN
Multiple myeloma remains treatable but incurable. Despite a growing armamentarium of effective agents, choice of therapy, especially in relapse, still relies almost exclusively on clinical acumen. We have developed a system, Ex vivo Mathematical Myeloma Advisor (EMMA), consisting of patient-specific mathematical models parameterized by an ex vivo assay that reverse engineers the intensity and heterogeneity of chemosensitivity of primary cells from multiple myeloma patients, allowing us to predict clinical response to up to 31 drugs within 5 days after bone marrow biopsy. From a cohort of 52 multiple myeloma patients, EMMA correctly classified 96% as responders/nonresponders and correctly classified 79% according to International Myeloma Working Group stratification of level of response. We also observed a significant correlation between predicted and actual tumor burden measurements (Pearson r = 0.5658, P < 0.0001). Preliminary estimates indicate that, among the patients enrolled in this study, 60% were treated with at least one ineffective agent from their therapy combination regimen, whereas 30% would have responded better if treated with another available drug or combination. Two in silico clinical trials with experimental agents ricolinostat and venetoclax, in a cohort of 19 multiple myeloma patient samples, yielded consistent results with recent phase I/II trials, suggesting that EMMA is a feasible platform for estimating clinical efficacy of drugs and inclusion criteria screening. This unique platform, specifically designed to predict therapeutic response in multiple myeloma patients within a clinically actionable time frame, has shown high predictive accuracy in patients treated with combinations of different classes of drugs. The accuracy, reproducibility, short turnaround time, and high-throughput potential of this platform demonstrate EMMA's promise as a decision support system for therapeutic management of multiple myeloma. Cancer Res; 77(12); 3336-51. ©2017 AACR.
Asunto(s)
Algoritmos , Antineoplásicos/uso terapéutico , Técnicas de Apoyo para la Decisión , Modelos Teóricos , Mieloma Múltiple/tratamiento farmacológico , Ensayos Analíticos de Alto Rendimiento , HumanosRESUMEN
The novel Bruton's tyrosine kinase inhibitor ibrutinib has demonstrated high response rates in B-cell lymphomas; however, a growing number of ibrutinib-treated patients relapse with resistance and fulminant progression. Using chemical proteomics and an organotypic cell-based drug screening assay, we determine the functional role of the tumour microenvironment (TME) in ibrutinib activity and acquired ibrutinib resistance. We demonstrate that MCL cells develop ibrutinib resistance through evolutionary processes driven by dynamic feedback between MCL cells and TME, leading to kinome adaptive reprogramming, bypassing the effect of ibrutinib and reciprocal activation of PI3K-AKT-mTOR and integrin-ß1 signalling. Combinatorial disruption of B-cell receptor signalling and PI3K-AKT-mTOR axis leads to release of MCL cells from TME, reversal of drug resistance and enhanced anti-MCL activity in MCL patient samples and patient-derived xenograft models. This study unifies TME-mediated de novo and acquired drug resistance mechanisms and provides a novel combination therapeutic strategy against MCL and other B-cell malignancies.