Loewe Additivity Research Articles

Abstract 262: Statistical Bliss: A novel framework for statistical assessment of drug synergy

Abstract Combination therapy is a common feature of cancer treatment, aiming to maximize efficacy while minimizing toxicity and opportunities for acquired resistance. It is critical to assess which combinations achieve best effects. This requires rigorous, statistically sound methods of characterizing the relationships between drugs as synergistic, independent, or antagonistic. Current frameworks, including Bliss independence and Loewe additivity as implemented by the Chou-Talalay method, are not statistical and assess effects at discrete points rather than across the entirety of a dose-response curve, limiting their application. We aimed to create a comprehensive statistical framework applicable to dose-response curves of all forms and any number of drugs in combination. We developed a generalized definition of independent action to construct theorized dose-response curves of drugs in combination informed by empirically fitted dose-response curves for individual drugs. We derive uncertainty estimates for theorized curves, which are compared to empirical measurements of fixed- or variable-ratio drug combinations at all measured concentrations. Separately accounting for variability in technical and experimental replicates allows robust statistics at each experimental condition as well as globally across the range of conditions. As an example of its utility, we applied this model to a system of known synthetic lethality. We exposed BRCA-mutant (HCC1937) and wild-type (MDA-MB-231) triple-negative breast cancer cell lines to PARP inhibitor (PARPi) olaparib and RAD51 inhibitors (RAD51i) IBR2 or B02 singly and in variable-ratio combinations and evaluated cell viability at 96 hours post-treatment by MTT assay. We hypothesized that combination of RAD51i, producing a defect in homologous recombination, with olaparib in BRCA-WT cells would phenocopy the synthetic lethal effect of PARPi in BRCA-Mut cells and demonstrate synergy, whereas there would be no synergy in BRCA-Mut cells. HCC1937 cells demonstrated antagonism between olaparib and B02 (p < 0.001) or IBR2 (p < 0.001). MDA-MB-231 cells demonstrated significant synergy of olaparib and B02 (p < 0.001) or IBR2 (p < 0.001), consistent with our hypothesis. However, the interaction of olaparib and B02 was dose-dependent with synergy overall but antagonism at high concentrations. This shows that (1) measurements at single concentrations may be misleading and (2) our new method may guide optimal drug concentration selection. We also assessed a “sham” combination of B02 with itself in MDA-MB-231 cells and predictably detected neither synergy nor antagonism (p = 0.39). Not only do these data provide evidence for expanded use of PARPi alongside RAD51i in BRCA-WT cancers, they validate this statistical approach that offers a robust calculation of synergy or antagonism with broad applicability to any study of combination therapies, especially for high-throughput screening. Citation Format: Richard E. Grewelle, Kalin L. Wilson, Dana M. Brantley-Sieders. Statistical Bliss: A novel framework for statistical assessment of drug synergy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 262.

Solving the Problem of Assessing Synergy and Antagonism for Non-Traditional Dosing Curve Compounds Using the DE/ZI Method: Application to Nrf2 Activators.

Multi-drug combination therapy carries significant promise for pharmacological intervention, primarily better efficacy with less toxicity and fewer side effects. However, the field lacks methodology to assess synergistic or antagonistic interactions for drugs with non-traditional dose response curves. Specifically, our goal was to assess small-molecule modulators of antioxidant response element (ARE)-driven gene expression, which is largely regulated by the Nrf2 transcription factor. Known as Nrf2 activators, this class of compounds upregulates a battery of cytoprotective genes and shows significant promise for prevention of numerous chronic diseases. For example, sulforaphane sourced from broccoli sprouts is the subject of over 70 clinical trials. Nrf2 activators generally have non-traditional dose response curves that are hormetic, or U-shaped. We introduce a method based on the principles of Loewe Additivity to assess synergism and antagonism for two compounds in combination. This method, termed Dose-Equivalence/Zero Interaction (DE/ZI), can be used with traditional Hill-slope response curves, and it also can assess interactions for compounds with non-traditional curves, using a nearest-neighbor approach. Using a Monte-Carlo method, DE/ZI generates a measure of synergy or antagonism for each dosing pair with an associated error and p-value, resulting in a 3D response surface. For the assessed Nrf2 activators, sulforaphane and di-tert-butylhydroquinone, this approach revealed synergistic interactions at higher dosing concentrations consistently across data sets and potential antagonistic interactions at lower concentrations. DE/ZI eliminates the need to determine the best fit equation for a given data set and values experimentally-derived results over formulated fits.

EMBR-11. SYNERGISTIC DRUG COMBINATIONS FOR THE TREATMENT OF MYC AMPLIFIED GROUP 3 MEDULLOBLASTOMA

Abstract Background Medulloblastoma (MB) is a highly aggressive brain tumour in children. Patients with Group 3 MB harbouring a MYC-amplification (subtype II) show a particularly poor outcome despite high-intensity multimodal therapy. We and others have previously shown that MYC amplified Group 3 MB cells are highly susceptible towards treatment with class I histone deacetylase (HDAC) inhibitors such as entinostat. However, in clinical trials HDACi as a monotherapy show only modest efficacy in solid tumours. We propose to increase the efficacy of class I HDACi by drug combinations. Methods To identify synergistic drug combinations (entinostat + X) for the treatment of MYC amplified MB we performed a drug screen with a library of n=75 clinically available compounds as single agents and in combination with entinostat in n=3 MYC amplified vs. n=1 MYC-non amplified cell lines. Synergistic behaviour of the six most promising drug combinations was validated by metabolic activity assays, cell count experiments and gene expression profiling. Synergy was assessed by the Loewe additivity model using a combination of ray design and checkerboard matrix. Results The drug screen revealed n=20/75 drugs that were particularly effective (drug sensitivity score ≥10) in combination with entinostat treatment in all three MYC amplified cell lines. Synergy assessment of the top n=6 drugs confirmed strong synergistic activity with entinostat for n=2 drugs (navitoclax, irinotecan). The BCL-2 family inhibitor navitoclax showed the most robust synergy with entinostat in subsequent validation experiments. Conclusion Several drugs either clinically available or currently in clinical trials, including the BCL-2/Xl/w inhibitor navitoclax, show promising effects in a combination therapy with entinostat for the treatment of MYC amplified Group 3 MB.

Complex interactions of lovastatin with 10 chemotherapeutic drugs: a rigorous evaluation of synergism and antagonism

BackgroundEvidence bearing on the role of statins in the prevention and treatment of cancer is confounded by the diversity of statins, chemotherapeutic agents and cancer types included in the numerous published studies; consequently, the adjunctive value of statins with chemotherapy remains uncertain.MethodsWe assayed lovastatin in combination with each of ten commonly prescribed chemotherapy drugs in highly reproducible in vitro assays, using a neutral cellular substrate, Saccharomyces cerevisiae. Cell density (OD600) data were analyzed for synergism and antagonism using the Loewe additivity model implemented with the Combenefit software.ResultsFour of the ten chemotherapy drugs – tamoxifen, doxorubicin, methotrexate and rapamycin – exhibited net synergism with lovastatin. The remaining six agents (5-fluorouracil, gemcitabine, epothilone, cisplatin, cyclophosphamide and etoposide) compiled neutral or antagonistic scores. Distinctive patterns of synergism and antagonism, often coexisting within the same concentration space, were documented with the various combinations, including those with net synergism scores. Two drug pairs, lovastatin combined with tamoxifen or cisplatin, were also assayed in human cell lines as proof of principle.ConclusionsThe synergistic interactions of tamoxifen, doxorubicin, methotrexate and rapamycin with lovastatin – because they suggest the possibility of clinical utility - merit further exploration and validation in cell lines and animal models. No less importantly, strong antagonistic interactions between certain agents and lovastatin argue for a cautious, data-driven approach before adding a statin to any chemotherapeutic regimen. We also urge awareness of adventitious statin usage by patients entering cancer treatment protocols.

Combinatorial Drug Treatments Reveal Promising Anticytomegaloviral Profiles for Clinically Relevant Pharmaceutical Kinase Inhibitors (PKIs)

Human cytomegalovirus (HCMV) is a human pathogenic herpesvirus associated with a variety of clinical symptoms. Current antiviral therapy is not always effective, so that improved drug classes and drug-targeting strategies are needed. Particularly host-directed antivirals, including pharmaceutical kinase inhibitors (PKIs), may help to overcome problems of drug resistance. Here, we focused on utilizing a selection of clinically relevant PKIs and determined their anticytomegaloviral efficacies. Particularly, PKIs directed to host or viral cyclin-dependent kinases, i.e., abemaciclib, LDC4297 and maribavir, exerted promising profiles against human and murine cytomegaloviruses. The anti-HCMV in vitro activity of the approved anti-cancer drug abemaciclib was confirmed in vivo using our luciferase-based murine cytomegalovirus (MCMV) animal model in immunocompetent mice. To assess drug combinations, we applied the Bliss independence checkerboard and Loewe additivity fixed-dose assays in parallel. Results revealed that (i) both affirmative approaches provided valuable information on anti-CMV drug efficacies and interactions, (ii) the analyzed combinations comprised additive, synergistic or antagonistic drug interactions consistent with the drugs’ antiviral mode-of-action, (iii) the selected PKIs, especially LDC4297, showed promising inhibitory profiles, not only against HCMV but also other α-, β- and γ-herpesviruses, and specifically, (iv) the combination treatment with LDC4297 and maribavir revealed a strong synergism against HCMV, which might open doors towards novel clinical options in the near future. Taken together, this study highlights the potential of therapeutic drug combinations of current developmental/preclinical PKIs.

Quantifying synergy in the bioassay-guided fractionation of natural product extracts.

Mixtures of drugs often have greater therapeutic value than any of their constituent drugs alone, and such combination therapies are widely used to treat diseases such as cancer, malaria, and viral infections. However, developing useful drug mixtures is challenging due to complex interactions between drugs. Natural substances can be fruitful sources of useful drug mixtures because secondary metabolites produced by living organisms do not often act in isolation in vivo. In order to facilitate the study of interactions within natural substances, a new analytical method to quantify interactions using data generated in the process of bioassay-guided fractionation is presented here: the extract fractional inhibitory concentration index (EFICI). The EFICI method uses the framework of Loewe additivity to calculate fractional inhibitory concentration values by which interactions can be determined for any combination of fractions that make up a parent extract. The EFICI method was applied to data on the bioassay-guided fractionation of Lechea mucronata and Schinus terebinthifolia for growth inhibition of the pathogenic bacterium Acinetobacter baumannii. The L. mucronata extract contained synergistic interactions (EFICI = 0.4181) and the S. terebinthifolia extract was non-interactive overall (EFICI = 0.9129). Quantifying interactions in the bioassay-guided fractionation of natural substances does not require additional experiments and can be useful to guide the experimental process and to support the development of standardized extracts as botanical drugs.

Abstract 1773: Targeting HER2 and Src in HER2-driven ovarian and esophagogastric cancers

Abstract Background: Neratinib, an oral, irreversible pan-HER tyrosine kinase inhibitor, has exhibited clinical activity against HER2-mutant and HER2 over-expressing cancers. Our previous pre-clinical studies have shown that combining the multi-kinase inhibitor dasatinib with neratinib is highly synergistic in HER2-positive breast cancer. Therefore, the aim of this study was to examine the potential of combining neratinib and dasatinib in HER2 over-expressing/mutant esophagogastric (EG) and ovarian cancer. Methods: The prevalence of HER2 mutation and amplification levels in ovarian and EG cancers was determined using the AACR Project GENIE database. The anti-proliferative effects of neratinib and dasatinib were assessed by acid phosphatase assay in a panel of HER2-altered ovarian (Caov3, OVCAR8, IGROV-1) and EG (NCI-N87, OE19) cancers. Synergy was assessed using Combenefit software with the Loewe additivity model, with additivity and synergy > 0 and antagonism < 0. Western blotting was used to examine the basal expression of HER2 and downstream signalling activity and to investigate the signalling effects of drug treatment in HER2-mutant OVCAR8 cells. Results: HER2 was the most commonly amplified gene in EG cancers (14.1%) and was also amplified in 2.4% of ovarian cancers. HER2 mutations occurred in 6.1% of EG and 1.5% ovarian cancers. All five cell lines tested displayed nanomolar sensitivity to single agent neratinib or dasatinib (Table). The combination of neratinib and dasatinib was synergistic in all cell lines. The greatest synergy was observed with low concentrations of neratinib in EG cell lines. Synergistic interactions occurred across a range of concentrations with both drugs in ovarian cancer cell lines. Antagonism was not observed at any concentration tested. Neratinib plus dasatinib inhibited Src and MAPK activity in OVCAR8 cells. Neratinib and dasatinib in ovarian and EG cancersCell linesCancertypeNeratinib EC50 value (nM)Dasatinib EC50 value (nM)Combination effectNCI-N87Esophagogastric0.188979SynergismOE19Esophagogastric0.432284SynergismOVCAR8Ovarian16281SynergismIGROV-1Ovarian1706SynergismCaov3Ovarian13730Synergism Conclusions: These data suggest that the addition of dasatinib may enhance the anti-cancer effect of neratinib in HER2-driven ovarian and EG cancers and warrants further investigation. Citation Format: Neil T. Conlon, Keshia Kroh, John Crown, Denis M. Collins. Targeting HER2 and Src in HER2-driven ovarian and esophagogastric cancers [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1773.

Abstract A50: Lapatinib potentiates the antitumor effects of paclitaxel treatment in resistant ovarian cancer cells

Abstract Introduction: Frontline treatment regimens for ovarian cancer routinely consist of repeated cycles of paclitaxel/platinum doublets; however, chemotherapy resistance frequently leads to recurrent or refractory disease. Novel therapeutic strategies aimed at circumventing or preventing resistance are needed for improved disease control. Experimental Procedures: Multiple paclitaxel-resistant ovarian cancer cell line models were established via repeated cycles of paclitaxel treatment in vitro. Resistance to paclitaxel was assessed using dose response cell viability assays with CellTiter-Glo 2.0 and calculation of IC50 values using a 4-parameter logistic regression model. RNAseq and whole-exome sequencing were used to examine genomic variation distinguishing resistant lines from their sensitive counterparts. Recurrent expression differences associated with paclitaxel resistance were identified, a subset of which were selected for further validation. Candidate genes and pathways associated with paclitaxel resistance were manipulated using siRNA and/or small-molecule inhibitors and assessed for the ability to alter the resistant phenotype. Synergistic interactions for drug combinations were evaluated using the Loewe Additivity model. Results: Paclitaxel-resistant ovarian cancer cell lines were derived from TOV-21G, OVCAR-3, and UWB1.289 cells. Resistant cell lines exhibited increases in paclitaxel IC50 ranging from 6.5 to 94-fold over their parental control cells. RNAseq analysis identified the transcript encoding P-glycoprotein (P-gp), ABCB1, among the most highly upregulated genes in the resistant TOV-21G and OVCAR-3 cells while no such induction of expression was seen in resistant UWB1.289 cells. Previous reports have shown several different tyrosine kinase inhibitors (e.g., lapatinib, neratinib, dasatinib, etc.) have the ability to inhibit P-gp function. We tested a panel of tyrosine kinase inhibitors for the ability to sensitize resistant P-gp-overexpressing ovarian cancer cells to paclitaxel. The most potent synergistic antiproliferative activity was observed when lapatinib was combined with paclitaxel treatment of resistant TOV-21G and OVCAR-3 cells; however, a similar interaction was not observed in resistant UWB1.289 cells that do not overexpress P-gp. The dependence of this synergistic effect on P-gp expression was confirmed by using siRNA to inhibit P-gp expression in paclitaxel-resistant TOV-21G and OVCAR-3 cells, significantly reducing paclitaxel IC50 by 20.7 and 6.2-fold, respectively, and eliminating cytotoxic synergy. Conclusions: Paclitaxel and lapatinib have synergistic anticancer properties when used to treat P-gp-overexpressing ovarian cancer cells. The addition of lapatinib to second-line dose-dense paclitaxel therapy could be an effective strategy for a subset of ovarian cancer patients with recurrent disease and warrants further clinical exploration. Citation Format: Rob McCorkle, Justin W. Gorski, Abigail Anderson, Jill M. Kolesar. Lapatinib potentiates the antitumor effects of paclitaxel treatment in resistant ovarian cancer cells [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr A50.

Identification of the uterine‐relaxant effect of mundulone as a natural‐product for therapeutic control of preterm labor

IntroductionPreterm birth rate continues to rise with over 15 million cases/year and remains the greatest contributor to neonatal morbidities and mortalities. Currently, there are no FDA‐approved tocolytics for the management of preterm labor due to the off‐target side effects and short duration of benefit of current off‐label therapeutics. High‐throughput screening of oxytocin‐induced Ca2+‐mobilization in uterine myometrial cells identified mundulone and mundulone acetate (MA) as hit‐antagonists. The aim of this work was to:1) examine the uterine‐selectivity of mundulone and MA by counterscreening vascular smooth muscle cells (VSMCs)—the major off‐target limiting the use of current tocolytics, 2) determine cytotoxic effects, 3) identify synergistic combinations of mundulone (and MA) with current tocolytics to increase efficacy and/or potency to decrease off‐target side effects and 4) determine the ex vivo tocolytic efficacy and potency on human myometrial tissue and confirm uterine selectivity at the tissue level by evaluating their effect on constriction of fetal ductus arteriosus (DA), a major off target of known tocolytics.MethodsPrimary human myometrial cells were isolated from tissue collected at the time of cesarean delivery from women at term (≥39 weeks) pregnancy. A phenotypic high‐throughput Ca2+‐ mobilization assay was performed to compare concentration‐response (10‐ point, 3‐fold dilutions) between myometrial and aorta VSMCs (Emax and IC50). The high‐throughput Ca2+‐mobilization assay was adapted for combination screening in 8×8 concentration‐response matrix format. Current tocolytics used for combination included: atosiban, indomethacin and nifedipine. Three models (Bliss independence, HSA and Loewe additivity) were used to determine synergy using Combenefit software. Cytotoxicity of mundulone and MA were determined using WST‐1 cell viability assay using myometrial, hepatic and renal cells. Ex vivo organ bath studies using myometrial tissue and isolated term fetal DA vessels were performed to examine concentration‐response on contractility and vessel diameter, respectively.ResultsMA was found to display a greater selectivity towards myometrial cells when counter screened against aorta VSMCs. Fold change (FC) in efficacy (Emax) was 13.5 and FC in potency was >4.5 for MA while fold change in potency for mundulone was only >2.3. We found that mundulone displayed synergism with two current tocolytics (atosiban and nifedipine), while MA displayed synergistic efficacy with nifedipine. Mundulone was found to affect the viability of myometrial cells while MA demonstrated a selectivity index of >10 (Ratio of IC50 in cell viability assay to IC50 in Ca2+‐mobilization assay). Both mundulone and MA showed concentration dependent inhibition of uterine contractions, without affecting fetal DA vasoreactivity at the tissue level.ConclusionBased on differences in uterine‐selectivity and tocolytic efficacy between mundulone and MA, this natural product could benefit from medicinal chemistry efforts to study structural activity relationship.Support or Funding InformationNICHD grant HD088830 and Turner Hazinski research award.

Dose–response analysis of toxicological and pharmacological mixtures with the model deviation ratio method: Problems and solutions

Risk assessment for mixtures of chemicals requires to investigate the magnitude of their potential adverse effects on living organisms. This is usually done by assessing how experimental toxicological mixture data depart from the model of Loewe additivity. Several recent scientific studies propose to perform this task using an ad hoc method known as model deviation ratio (MDR) method. Moreover, the first official European regulatory document for the study of combined exposures explicitly recommends the use of the MDR method (EFSA Scientific Committee et al. Guidance on harmonised methodologies for human health, animal health and ecological risk assessment of combined exposure to multiple chemicals. EFSA Journal, 2019).We show here that the MDR method is not rooted in statistical principles and can lead to erroneous claims. We show however that the distribution of the MDR can be evaluated by simulations and show how this allows us to devise and carry out a bona fide statistical test. The proposed method accounts for uncertainty in the estimation of ED/EC50 and does not require a minimum sample size. The computer code developped in this study is made available as an R package called MDR.

Additive Dose Response Models: Defining Synergy.

In synergy studies, one focuses on compound combinations that promise a synergistic or antagonistic effect. With the help of high-throughput techniques, a huge amount of compound combinations can be screened and filtered for suitable candidates for a more detailed analysis. Those promising candidates are chosen based on the deviance between a measured response and an expected non-interactive response. A non-interactive response is based on a principle of no interaction, such as Loewe Additivity or Bliss Independence. In a previous study, we introduced, an explicit formulation of the hitherto implicitly defined Loewe Additivity, the so-called Explicit Mean Equation. In the current study we show that this Explicit Mean Equation outperforms the original implicit formulation of Loewe Additivity and Bliss Independence when measuring synergy in terms of the deviance between measured and expected response, called the lack-of-fit. Further, we show that computing synergy as lack-of-fit outperforms a parametric approach. We show this on two datasets of compound combinations that are categorized into synergistic, non-interactive, and antagonistic.

Antimicrobial Drug Interactions: Systematic Evaluation of Protein and Nucleic Acid Synthesis Inhibitors.

Antimicrobial multidrug resistance and its transmission among strains are serious problems. Success rate is decreased and treatment options are narrowed due to increasing bacterial multidrug resistance. On the other hand, the need for long-term efforts to discover new antibiotics and difficulties finding new treatment protocols make this problem more complex. Combination therapy, especially with synergistic use of antimicrobials is a rational treatment option with huge benefits. Thus, screening antibiotic interactions is crucial for finding better treatment options. Clinicians currently use combinatorial antibiotic treatment as an effective treatment option. However, antibiotics can show synergistic or antagonistic interactions when used together. In our study, we aimed to investigate interactions of antibiotics with different mechanisms of action. Antibiotics, which act as protein synthesis inhibitors (P) and nucleic acid synthesis inhibitors (N) were used in our study. We tested 66 (PN), 15 (NN), and 55 (PP) drug pairs on the Escherichia coli strain. The Loewe additivity model was used and alpha scores were calculated for analysis of interactions of drug combinations. Drug interactions were categorized as synergistic or antagonistic. Accordingly, pairwise combinations of protein synthesis inhibitors (PP) showed stronger synergistic interactions than those of nucleic acid synthesis inhibitors (NN) and nucleic acid synthesis–protein synthesis inhibitors (PN). As a result, the importance of mechanisms of action of drugs is emphasized in the selection of synergistic drug combinations.

To Combine or Not Combine: Drug Interactions and Tools for Their Analysis. Reflections from the EORTC-PAMM Course on Preclinical and Early-phase Clinical Pharmacology.

Combination therapies are used in the clinic to achieve cure, better efficacy and to circumvent resistant disease in patients. Initial assessment of the effect of such combinations, usually of two agents, is frequently performed using in vitro assays. In this review, we give a short summary of the types of analyses that were presented during the Preclinical and Early-phase Clinical Pharmacology Course of the Pharmacology and Molecular Mechanisms Group, European Organization for Research and Treatment on Cancer, that can be used to determine the efficacy of drug combinations. The effect of a combination treatment can be calculated using mathematical equations based on either the Loewe additivity or Bliss independence model, or a combination of both, such as Chou and Talalay's median-drug effect model. Interactions can be additive, synergistic (more than additive), or antagonistic (less than additive). Software packages CalcuSyn (also available as CompuSyn) and Combenefit are designed to calculate the extent of the combined effects. Interestingly, the application of machine-learning methods in the prediction of combination treatments, which can include pharmacogenomic, genetic, metabolomic and proteomic profiles, might contribute to further refinement of combination regimens. However, more research is needed to apply appropriate rules of machine learning methods to ensure correct predictive models.

Abstract 363: CYT01B, a novel RAD51 inhibitor, acts synergistically with PARP inhibitors

Abstract Genomic instability is recognized as a driver of tumorigenesis and cancer progression. Loss of tumor suppressors or activation of oncogenes can induce DNA damage stress, promoting genomic instability and creating dependencies upon key DNA repair pathways. These dependencies can be targeted therapeutically to induce synthetic lethality. We have developed a novel RAD51 inhibitor, CYT01B, which we have previously shown to be preferentially active in Activation Induced Cytidine Deaminase (AID) expressing cells, and in other tumor derived cell lines with elevated levels of DNA damage and/or reduced DNA repair capabilities. CYT01B acts by reducing RAD51 focus formation, and depleting the nuclear pool of RAD51. We have observed anti-tumor effects with CYT01B in preclinical models, but have yet to determine if RAD51 could act as a sensitizer to current therapeutics. A main resistance mechanism to PARP inhibitors is the overexpression of RAD51, making it an attractive potential combination for our RAD51 inhibitor. To determine potential drug synergy, a matrix study was performed with CYT01B (concentration range of 20nM to 5µM) and 5 different PARP inhibitors including olaparib (78nM to 5µM), niraparib (78nM to 5µM), veliparib (780nM to 50µM), rucaparib (156nM to 10µM), and talazoparib (39nM to 2.5µM). The combination matrix was tested in cell lines of varying AID expression and PARP inhibitor sensitivity: ARPE19/HPV16 (HPV immortalized epithelial cell line), KYSE-70 (head and neck cancer cell line), Daudi (Burkitt’s Lymphoma cell line), HCC1143 (TNBC), and BT20 (TNBC). We used both the Loewe Additivity model and the Bliss Independence model to determine drug interaction (synergistic, independent, or antagonistic). In general, we observed synergy with all the combinations in the tumor derived cell lines. In the transformed epithelial cell line, synergy was observed only in the olaparib combination. The strength of the synergistic effect differed amongst the PARP inhibitors, with olaparib giving the strongest synergy scores. From this data we hypothesize that the synergistic activity with CYT01B is related to the PARP trapping efficiency of the PARP inhibitors; greater trapping efficiency the greater the synergy. These data suggest that CYT01B may be active as a combinatorial therapy with PARP inhibitors. Overall, we conclude that there is significant potential for combining RAD51 and PARP inhibition in future cancer treatment strategies, and warrants future exploration in vivo. Citation Format: Tyler Maclay, Melinda Day, Kevin Mills. CYT01B, a novel RAD51 inhibitor, acts synergistically with PARP inhibitors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 363.

Abstract 3512: AZD7648, a potent and selective inhibitor of DNA-PK, potentiates the activity of ionising radiation and doxorubicin in vitro and causes tumour regression in xenograft models

Abstract DNA-dependent kinase (DNA-PK) is a nuclear serine/threonine protein kinase complex that is a key component of the non-homologous end joining (NHEJ) process. DNA-PK plays an important role in the cellular response to DNA damage through the detection and repair of DNA double strand breaks (DSB). Cancer therapies such as ionising radiation (IR) or topoisomerase II inhibitors (doxorubicin) generate DSB which can be repaired by homologous recombination (HR) or non-homologous end-joining (NHEJ). It can therefore be hypothesised a DNA-PK inhibitor would potentiate the activity of these agents. We have developed a highly potent and selective inhibitor of DNA-PK, AZD7648, which inhibits IR-induced DNA-PK S2056 auto phosphoryalation with an IC50 = 92 nM in A549 non-small cell lung cancer (NSCLC) cells. AZD7648 is a potent radiosensitiser where treatment in combination with IR led to a concentration-dependent reduction of the colony survival capacity of A549 and H1299 NSCLC cells (DEF37 at 100 nM = 1.7 and 2.5, respectively). In A549 cells, AZD7648 (≥1 µM) in combination with 2Gy IR for 48 hours led to a significant accumulation of cells arrested in the G2/M of the cell cycle, a 4-fold increase in micronuclei formation, and 3-fold induction of γH2AX, pATM S1981 and 53BP1 foci formation compared with IR alone. AZD7648 was also found to combine synergistically with doxorubicin in a panel of ovarian and triple negative breast cancer (TNBC) cell lines in cell growth inhibition assays when applying the Loewe additivity model (synergy scores 4 - 35). In vivo the combination of AZD7648 with IR (5x 2Gy) induced tumour regression in H1299 and A549 NSCLC xenografts in a dose-dependent manner (84 and 11% regression respectively), while monotherapy treatment only achieved tumour growth inhibition. In these two models the increased activation by IR of three primary DNA-PK pharmacodynamic markers, pDNAPK (S2056), pRPA32 (S4/8) and γH2AX, was inhibited by AZD7648 treatment (70-90% inhibition 2 h after IR + AZD7648). Similarly, liposomal doxorubicin (2.5 mg/kg weekly) in combination with AZD7648 (37.5 mg/kg bid) induced tumour regressions in the BT474c ER+ breast cancer xenograft model and in a TNBC PDX model (63% and 33% regression respectively), while monotherapy treatments only achieved tumour growth inhibition. These data confirm that DNA-PK inhibition with AZD7648 enhances the efficacy of a range of DSB inducing agents in vitro and in vivo, providing a clear rationale for its clinical investigation. Citation Format: Jacqueline H. Fok, Antonio Ramos-Montoya, Neil James, Mercedes Vazquez-Chantada, Valeria Follia, Ankur Karmokar, Anna Staniszewska, Lenka Oplustil O’Connor, Emma Dean, Simon J. Hollingsworth, Barry R. Davies, Elaine B. Cadogan. AZD7648, a potent and selective inhibitor of DNA-PK, potentiates the activity of ionising radiation and doxorubicin in vitro and causes tumour regression in xenograft models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3512.

Response envelope analysis for quantitative evaluation of drug combinations.

The concept of synergy between two agents, over a century old, is important to the fields of biology, chemistry, pharmacology and medicine. A key step in drug combination analysis is the selection of an additivity model to identify combination effects including synergy, additivity and antagonism. Existing methods for identifying and interpreting those combination effects have limitations. We present here a computational framework, termed response envelope analysis (REA), that makes use of 3D response surfaces formed by generalized Loewe Additivity and Bliss Independence models of interaction to evaluate drug combination effects. Because the two models imply two extreme limits of drug interaction (mutually exclusive and mutually non-exclusive), a response envelope defined by them provides a quantitatively stringent additivity model for identifying combination effects without knowing the inhibition mechanism. As a demonstration, we apply REA to representative published data from large screens of anticancer and antibiotic combinations. We show that REA is more accurate than existing methods and provides more consistent results in the context of cross-experiment evaluation. The open-source software package associated with REA is available at: https://github.com/4dsoftware/rea. Supplementary data are available at Bioinformatics online.

Brain permeant and impermeant inhibitors of fatty-acid amide hydrolase suppress the development and maintenance of paclitaxel-induced neuropathic pain without producing tolerance or physical dependence in vivo and synergize with paclitaxel to reduce tumor cell line viability in vitro

Activation of cannabinoid CB1 receptors suppresses pathological pain but also produces unwanted side effects, including tolerance and physical dependence. Inhibition of fatty-acid amide hydrolase (FAAH), the major enzyme catalyzing the degradation of anandamide (AEA), an endocannabinoid, and other fatty-acid amides, suppresses pain without unwanted side effects typical of direct CB1 agonists. However, FAAH inhibitors have failed to show efficacy in several clinical trials suggesting that the right partnership of FAAH inhibition and pathology has yet to be identified. We compared efficacy of chronic treatments with a centrally penetrant FAAH inhibitor (URB597), a peripherally restricted FAAH inhibitor (URB937) and an orthosteric pan-cannabinoid agonist (WIN55,212-2) in suppressing neuropathic pain induced by the chemotherapeutic agent paclitaxel. Each FAAH inhibitor suppressed the development of paclitaxel-induced neuropathic pain and reduced the maintenance of already established allodynia with sustained efficacy. Tolerance developed to the anti-allodynic efficacy of WIN55,212-2, but not to that of URB597 or URB937, in each dosing paradigm. Challenge with the CB1 antagonist rimonabant precipitated CB1-dependent withdrawal in paclitaxel-treated mice receiving WIN55,212-2 but not URB597 or URB937. When dosing with either URB597 or URB937 was restricted to the development of neuropathy, paclitaxel-induced allodynia emerged following termination of drug delivery. These observations suggest that both FAAH inhibitors were anti-allodynic rather than curative. Moreover, neither URB597 nor URB937 impeded the ability of paclitaxel to reduce breast (4T1) or ovarian (HeyA8) tumor cell line viability. In fact, URB597 and URB937 alone reduced 4T1 tumor cell line viability, albeit with low potency, and the dose matrix of each combination with paclitaxel was synergistic in reducing 4T1 and HeyA8 tumor cell line viability according to Bliss, Highest Single Agent (HSA) and Loewe additivity models. Both FAAH inhibitors synergized with paclitaxel to reduce 4T1 and HeyA8 tumor cell line viability without reducing viability of non-tumor HEK293 cells. Neither FAAH inhibitor reduced viability of non-tumor HEK293 cells in either the presence or absence of paclitaxel, suggesting that nonspecific cytotoxic effects were not produced by the same treatments. Our results suggest that FAAH inhibitors reduce paclitaxel-induced allodynia without the occurrence of CB1-dependence in vivo and may, in fact, enhance the anti-tumor actions of paclitaxel in vitro.

New models for the time dependent toxicity of individual and combined toxicants.

Time-dependent toxicity data of specific toxicants observed against A. fischeri were analysed using a single time-dependent Weibull cumulative distribution function (CDF). For binary mixtures the individual Weibull parameters provided the marginals for a bivariate copula model, characterised by a single extra parameter, the interaction exponent, θ. The copula model unites both the dose addition (DA, Loewe additivity) and dose independence (DI, Bliss independence) hypotheses of combinations into a single explicit equation and returns both hypotheses as special cases. The model predicts the linear isoboles from sham (like against like) experiments and the linear, concave, convex and mixed concave-convex isoboles from true binary mixtures. Systems are defined as being independent when θ = 1, additive when min(n 1, n 2) ≤ θ ≤ max(n 1, n 2), antagonistic when θ < min(n 1, n 2) and synergistic when θ > max(n 1, n 2), where n i are the individual dose (concentration) exponents. More complex mixtures were analysed by developing n-dimensional copulas: two ternary systems were analysed using a ternary copula that returned the three bivariate marginals and the three individual marginals of the mixture. The general model can also be used for time-independent studies by simply removing the time dependency. Research into combined effects has often assumed that if both the parameters for all the individual components in a mixture and the model for combinations were known then the additive effect of the whole could be predicted. This hypothesis has been shown to be false because without knowing how the components in a mixture interact the predictions from the standard DI or DA models provide only an initial, best guess, analysis.

In vitro interactions of crocin with fluconazole against Candida isolates.

Background and Purpose:The incidence of invasive fungal infections has been increased in recent years. The growing use of azole drugs for prophylactic and therapeutic purposes has resulted in the gradual emergence of azole-resistant species. Accordingly, the introduction of a new strategy to improve the management of Candida infections is an urgent need. Regarding this, the present study was performed to evaluate the antifungal activities of crocin (Cro) alone and in combination with fluconazole.Materials and Methods: This study was conducted on 50 clinical isolates of four different Candida species. The identity of the isolates was confirmed using the internal transcribed spacer identification system. The interactions of Cro with fluconazole were investigated using a microdilution checkerboard method based on the Clinical and Laboratory Standards Institute reference technique with 96-well microtiter plates. Furthermore, the assessment of the interaction of drug combinations was accomplished using the fractional inhibitory concentration index (FICI) based on the Loewe additivity theory. Results:According to the results, Cro alone showed a relatively high MIC50 value (1 g/ml) against Candida species. Our results demonstrated indifferent interactions between Cro and fluconazole with a FICI range of 0.5-4 against Candida strains.Conclusion:The high MIC value for Cro against Candida species indicated its failure to show appropriate antifungal activity against this species. The MIC of this agent was not significantly reduced even by the addition of fluconazole. Therefore, other mechanisms which are not related to the mechanism of azole drugs are involved at high concentration of Cro.

284 - Quantifying synergy for hormetic compounds using the dose-equivalence/zero-interaction (DE/ZI) method: Nrf2/antioxidant response element pathway activation

Small molecule Nrf2/ARE pathway activators show promise to preventchronic disease conditions, given their role in mitigating oxidative and electrophilic stress. We find that the efficacy and potency of the clinically-studied electrophilic Nrf2/ARE activator sulforaphane are enhanced by 12.5 µM 2,5-di-tert-butyl hydroquinone (dtBHQ), a reactive oxygen species-generating diphenol. Because the maximum efficacy of sulforaphane is increased, the compounds are acting in a synergistic manner. The issue that arises is how to quantitate the extent of the synergistic interaction. Synergy is defined by a response greater than the predicted additive response. We investigated whether the commonly used dose-effect models, including Highest Single Agent, Response Additivity, and Bliss Independence, as well as the curve-based models, e.g. Loewe Additivity and the Chou-Talalay method, could be applied to sulforaphane and dtBHQ data sets to predict the additive response. Nrf2-targeted activators, including sulforaphane, do not exhibit a traditional Hill-slope dose-response curve, but rather a hormetic dose-response, with a U-shape. We show that, given the sulforaphane curve shape, published methods of determining the predictive additive effect are not appropriate. Therefore, we propose a model to assess synergistic interactions that can be applied to any curve shape. This method, termed dose-equivalence/zero-interaction (DE/ZI), is based on the principles of Loewe Additivity, in which additivity is determined not by adding the effects of doses of drug A and drug B, but by adding the dose of A and the equivalent dose of B and calculating the predicted effect. DE/ZI differs from Loewe Additivy in that DE/ZI releases the constraint that interpolation off curve A and curve B must give the same predicted additive result. DE/ZI generates a FoldSynergy value with error, based on a Monte Carlo simulation. DE/ZI allows drug combinations to be assessed for synergy or antagonism, even for compounds that do not fit to a traditional Hill-slope model.