An R Package for Assessing Drug Synergism/Antagonism

Synergistic and antagonistic drug interactions are important to consider when developing mixtures of anticancer or other types of drugs. Boik, Newman, and Boik (2008) proposed the MixLow method as an alternative to the Median-Effect method of Chou and Talalay (1984) for estimating drug interaction indices. One advantage of the MixLow method is that the nonlinear mixed-effects model used to estimate parameters of concentration-response curves can provide more accurate parameter estimates than the log linearization and least-squares analysis used in the Median-Effect method. This paper introduces the mixlow package in R, an implementation of the MixLow method. Results are reported for a small simulation study.

Combined immunosuppressive therapy with low dose FK506 and antimetabolites in rat allogeneic heart transplantation

Following rat heterotopic heart allotransplantation, low to lethal doses of the antimetabolites mizoribine (MIZ), RS-61443 (RS), and AZA were given alone or in combination with subtherapeutic doses of FK506 (0.04 mg/kg/day) for 14 days after transplantation. With the median effect analysis of Chou and Kahan for quantitative drug interactions, substantial therapeutic synergism was demonstrated between FK506 and nontoxic doses of MĪZ (2.5, 5, and 10 mg/kg/day) or AZA (5, 30, and 45 mg/kg/day), which was particularly evident with the lowest dose MIZ (2.5 mg/kg/day). When FK506 was used in combination with MIZ or AZA but not with RS, the maximum effect (peak median graft survival) was enhanced significantly from 15 days (MIZ alone) to 26 days (P<0.05), and from 19 days (AZA alone) to 32 days (P<0.0l). In contrast, RS interacted with FK506 no more than additively. Although RS was the most powerful single antimetabolite, the best overall survival was obtained by combining AZA and FK506. The addition of FK506 did not significantly increase the percent mortality and LD50 of the antimetabolites. © 1994 by Williams and Wilkins

An R Package for Assessing Drug Synergism/Antagonism

Synergistic and antagonistic drug interactions are important to consider when developing mixtures of anticancer or other types of drugs. Boik, Newman, and Boik (2008) proposed the MixLow method as an alternative to the Median-Effect method of Chou and Talalay (1984) for estimating drug interaction indices. One advantage of the MixLow method is that the nonlinear mixed-effects model used to estimate parameters of concentration-response curves can provide more accurate parameter estimates than the log linearization and least-squares analysis used in the Median-Effect method. This paper introduces the mixlow package in R, an implementation of the MixLow method. Results are reported for a small simulation study

Synergistic drug combinations from electronic health records and gene expression.

ObjectiveUsing electronic health records (EHRs) and biomolecular data, we sought to discover drug pairs with synergistic repurposing potential. EHRs provide real-world treatment and outcome patterns, while complementary biomolecular data, including disease-specific gene expression and drug-protein interactions, provide mechanistic understanding.MethodWe applied Group Lasso INTERaction NETwork (glinternet), an overlap group lasso penalty on a logistic regression model, with pairwise interactions to identify variables and interacting drug pairs associated with reduced 5-year mortality using EHRs of 9945 breast cancer patients. We identified differentially expressed genes from 14 case-control human breast cancer gene expression datasets and integrated them with drug-protein networks. Drugs in the network were scored according to their association with breast cancer individually or in pairs. Lastly, we determined whether synergistic drug pairs found in the EHRs were enriched among synergistic drug pairs from gene-expression data using a method similar to gene set enrichment analysis.ResultsFrom EHRs, we discovered 3 drug-class pairs associated with lower mortality: anti-inflammatories and hormone antagonists, anti-inflammatories and lipid modifiers, and lipid modifiers and obstructive airway drugs. The first 2 pairs were also enriched among pairs discovered using gene expression data and are supported by molecular interactions in drug-protein networks and preclinical and epidemiologic evidence.ConclusionsThis is a proof-of-concept study demonstrating that a combination of complementary data sources, such as EHRs and gene expression, can corroborate discoveries and provide mechanistic insight into drug synergism for repurposing

Death effector domain-containing protein induces vulnerability to cell cycle inhibition in triple-negative breast cancer

Lacking targetable molecular drivers, triple-negative breast cancer (TNBC) is the most clinically challenging subtype of breast cancer. In this study, we reveal that Death Effector Domain-containing DNA-binding protein (DEDD), which is overexpressed in > 60% of TNBCs, drives a mitogen-independent G1/S cell cycle transition through cytoplasm localization. The gain of cytosolic DEDD enhances cyclin D1 expression by interacting with heat shock 71 kDa protein 8 (HSC70). Concurrently, DEDD interacts with Rb family proteins and promotes their proteasome-mediated degradation. DEDD overexpression renders TNBCs vulnerable to cell cycle inhibition. Patients with TNBC have been excluded from CDK 4/6 inhibitor clinical trials due to the perceived high frequency of Rb-loss in TNBCs. Interestingly, our study demonstrated that, irrespective of Rb status, TNBCs with DEDD overexpression exhibit a DEDD-dependent vulnerability to combinatorial treatment with CDK4/6 inhibitor and EGFR inhibitor in vitro and in vivo. Thus, our study provided a rationale for the clinical application of CDK4/6 inhibitor combinatorial regimens for patients with TNBC

Overcoming steroid resistance in T cell acute lymphoblastic leukemia

In a Perspective, Pieter Van Vlierberghe and Steven Goossens discuss Meijerink and colleagues' findings on steroid resistance in pediatric T cell acute lymphoblastic leukemia

Synergistic mutual potentiation of antifungal activity of Zuccagnia punctata Cav. and Larrea nitida Cav. extracts in clinical isolates of Candida albicans and Candida glabrata

Background: Zuccagnia punctata Cav. (Fabaceae) and Larrea nitida Cav. (Zygophyllaceae) are indistinctly or jointly used in traditional medicine for the treatment of fungal-related infections. Although their dichloromethane (DCM) extract have demonstrated moderate antifungal activities when tested on their own, antifungal properties of combinations of both plants have not been assessed previously. Purpose: The aim of this study was to establish with statistical rigor whether Z. punctata (ZpE) and L. nitida DCM extract (LnE) interact synergistically against the clinically important fungi Candida albicans and Candida glabrata and to characterize the most synergistic combinations. Study design: For synergism assessment, the statistical-based Boik's design was applied. Eight ZpE–LnE fixed-ratio mixtures were prepared from four different months of 1 year and tested against Candida strains. Lϕ (Loewe index) of each mixture at different fractions affected (ϕ) allowed for the finding of the most synergistic combinations, which were characterized by HPLC fingerprint and by the quantitation of the selected marker compounds. Methods: Lϕ and confidence intervals were determined in vitro with the MixLow method, once the estimated parameters from the dose–response curves of independent extracts and mixtures, were obtained. Markers (four flavonoids for ZpE and three lignans for LnE) were quantified in each extract and their combinations, with a valid HPLC–UV method. The 3D-HPLC profiles of the most synergistic mixtures were obtained by HPLC–DAD. Results: Three over four IC50ZpE/IC50LnE fixed-ratio mixtures displayed synergistic interactions at effect levels ϕ > 0.5 against C. albicans. The dosis of the most synergistic (Lϕ = 0.62) mixture was 65.96 µg/ml (ZpE = 28%; LnE = 72%) containing 8 and 36% of flavonoids and lignans respectively. On the other hand, one over four IC50ZpE/IC50LnE mixtures displays synergistic interactions at ϕ > 0.5 against C. glabrata. The dosis of the most synergistic (Lϕ = 0.67) mixture was 168.23 µg/ml (ZpE = 27%; LnE = 73%) with 9.7 and 31.6% of flavonoids and lignans respectively. Conclusions: Studies with the statistical-based MixLow method, allowed for the finding of the most ZpE–LnE synergistic mixtures, giving support to a proper joint use of both antifungal herbs in traditional medicine.Fil: Butassi, Estefanía. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Svetaz, Laura Andrea. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Ivancovich, Juan J.. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; ArgentinaFil: Feresin, Gabriela Egly. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Tapia, Alejandro A.. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Biotecnología; ArgentinaFil: Zacchino, Susana Alicia Stella. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin