Predicting Drug Synergism by Means of Non-Negative Matrix Tri-Factorization

Author(s):  
Pietro Pinoli ◽  
Gaia Ceddia ◽  
Stefano Ceri ◽  
Marco Masseroli
Keyword(s):  
2011 ◽  
Vol 6 (1) ◽  
pp. 26-44 ◽  
Author(s):  
Ghazaleh Ghavami ◽  
Mohammad R. Kazemali ◽  
Soroush Sardari

2018 ◽  
Vol 35 (13) ◽  
pp. 2338-2339 ◽  
Author(s):  
Hongyang Li ◽  
Shuai Hu ◽  
Nouri Neamati ◽  
Yuanfang Guan

Abstract Motivation Combination therapy is widely used in cancer treatment to overcome drug resistance. High-throughput drug screening is the standard approach to study the drug combination effects, yet it becomes impractical when the number of drugs under consideration is large. Therefore, accurate and fast computational tools for predicting drug synergistic effects are needed to guide experimental design for developing candidate drug pairs. Results Here, we present TAIJI, a high-performance software for fast and accurate prediction of drug synergism. It is based on the winning algorithm in the AstraZeneca-Sanger Drug Combination Prediction DREAM Challenge, which is a unique platform to unbiasedly evaluate the performance of current state-of-the-art methods, and includes 160 team-based submission methods. When tested across a broad spectrum of 85 different cancer cell lines and 1089 drug combinations, TAIJI achieved a high prediction correlation (0.53), approaching the accuracy level of experimental replicates (0.56). The runtime is at the scale of minutes to achieve this state-of-the-field performance. Availability and implementation TAIJI is freely available on GitHub (https://github.com/GuanLab/TAIJI). It is functional with built-in Perl and Python. Supplementary information Supplementary data are available at Bioinformatics online.


2010 ◽  
Vol 33 (9) ◽  
pp. 1411-1418 ◽  
Author(s):  
Jung-Jin Lee ◽  
Chang-Yong Shin ◽  
Hong-Joon Park ◽  
Wei-Yun Zhang ◽  
Yohan Kim ◽  
...  

2008 ◽  
Vol 52 (3) ◽  
pp. 1127-1132 ◽  
Author(s):  
Priya Uppuluri ◽  
Jeniel Nett ◽  
Joseph Heitman ◽  
David Andes

ABSTRACT Calcineurin is a Ca2+-calmodulin-activated serine/threonine-specific protein phosphatase that governs multiple aspects of fungal physiology, including cation homeostasis, morphogenesis, antifungal drug susceptibility, and virulence. Growth of Candida albicans planktonic cells is sensitive to the calcineurin inhibitors FK506 and cyclosporine A (CsA) in combination with the azole antifungal fluconazole. This drug synergism is attributable to two effects: first, calcineurin inhibitors render fluconazole fungicidal rather than simply fungistatic, and second, membrane perturbation by azole inhibition of ergosterol biosynthesis increases intracellular calcineurin inhibitor concentrations. C. albicans cells in biofilms are up to 1,000-fold more resistant to fluconazole than planktonic cells. In both in vitro experiments and in an in vivo rat catheter model, C. albicans cells in biofilms were resistant to individually delivered fluconazole or calcineurin inhibitors but exquisitely sensitive to the combination of FK506-fluconazole or CsA-fluconazole. C. albicans strains lacking FKBP12 or expressing a dominant FK506-resistant calcineurin mutant subunit (Cnb1-1) formed biofilms that were resistant to FK506-fluconazole but susceptible to CsA-fluconazole, demonstrating that drug synergism is mediated via direct calcineurin inhibition. These findings reveal that calcineurin contributes to fluconazole resistance of biofilms and provide evidence that synergistic drug combinations may prove efficacious as novel therapeutic interventions to treat or prevent biofilms.


2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 2548-2548
Author(s):  
Vincent Chung ◽  
Komal L. Jhaveri ◽  
Daniel D. Von Hoff ◽  
Xin-Yun Huang ◽  
Edward Graeme Garmey ◽  
...  

2548 Background: Fascin inhibitors block tumor metastasis and increase antigen uptake in intra-tumoral dendritic cells. Filopodia, finger-like protrusions on cell surfaces, are necessary for migration of metastatic tumor cells and intra-tumoral dendritic cells. Fascin is the primary actin cross-linker in filopodia and elevated levels correlate with increased risk of metastasis, disease progression and mortality. NP-G2-044 is a novel small molecule that inhibits function of fascin. Pre-clinical data demonstrate drug-associated reductions in tumor growth and metastasis, enhanced immune response and survival in treated animals, and drug-drug synergism when combined with anti-PD-1 antibodies. Methods: This multicenter phase 1A clinical trial was designed to evaluate safety and tolerability of NP-G2-044 and to identify the drug’s recommended phase 2 dose (RP2D) using a 3+3 dose escalation design. NP-G2-044 was administered to patients (pts.) with treatment-refractory solid tumor malignancies as a single oral daily dose for 6-week cycles that included 4 weeks on (daily dosing) and 2 weeks off (rest). Results: A total of 23 pts. were enrolled in 7 dose cohorts ranging from 200-2100 mg. QD. Overall, NP-G2-044 appeared well-absorbed and distributed with Tmax of ̃4 hrs and T1/2 of 20-24 hrs. Across all cohorts, no DLTs, drug-related SAEs or patient deaths were observed. Based on PK and safety findings, 1600 mg. daily was selected as the provisional RP2D. While no formal RECIST-based objective responses were observed, consistent with the drug’s non-cytotoxic mechanism of action, preliminary signals of anti-tumor and anti-metastatic activity were observed. These include dose proportional increases in duration of treatment, progression-free-survival, and metastasis-free interval, in particular for 4/4 late-stage ovarian cancer patients (table). Comparison of time on treatment (TOT) for ovarian cancer patients. Conclusions: In this first-in-human clinical trial, the novel fascin inhibitor, NP-G2-044, appeared safe and well tolerated. Signals of single-drug anti-tumor and anti-metastatic activity were observed. A phase 2A clinical trial with a particular focus on Ovarian Cancer will seek to elucidate signals of RP2D activity in both monotherapy and the combination of NP-G2-044 with anti-PD-(L)1 immune checkpoint inhibitors. Clinical trial information: NCT03199586. [Table: see text]


Pain ◽  
2002 ◽  
Vol 98 (1) ◽  
pp. 163-168 ◽  
Author(s):  
Ronald J. Tallarida

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