SynergyFinder™ Explained
Identification of Synergistic Combinations
SynergyFinder™ helps to ensure that new therapies are combined in the best way possible. Combination therapies are applied to halt cancer growth and to overcome emerging resistance mechanisms. To identify the right combination of your lead compound with standards of care or new drugs, NTRC has developed SynergyFinder™.
SynergyFinder™ Characteristics
Synergy testing in in vitro cellular assays
Evaluates if combinations of two or three anti cancer drugs have a greater than additive effect
Allows rapid identification of the best out of many possible combination treatments
Scalable from 1 to 1,000 combinations within a study
- Database of anti cancer drugs pre-profiled in Oncolines™ for rapid experimental progress
Unique Features
Determination of full dose response curves for single agents and mixtures
Synergies are determined by Fixed Ratio experiments and Fixed Dose combination experiments
Quantitative synergy scoring with Chou-Talalay method
Visualization of synergy by curve (IC50) shift and isobolograms
Reproducibility of cancer drug synergy is covered by independent repeat experiments before finalisation of the study
Equipotent Mixtures
Synergy drug screening via fixed ratio combination experiments uses equipotent mixtures of the anti cancer drugs. The mixtures contain fixed ratios of Compound A at IC50 and Compound B at IC50. Since Compound A and Compound B are equipotent (viz. both are at IC50), they are interchangeable and there is no dilution effect of mixing the compounds. To expedite synergy testing, NTRC has predetermined IC50 values, curve shapes and efficacy parameters of many relevant anti cancer drugs, covering the relevant anti cancer drug classes. The anti cancer drugs have been profiled in the full OncolinesTM panel, so the IC50 values of these drugs are available for 102 cancer cell lines.
Pre-profiled Anti Cancer Drugs
Recently approved small molecule oncology drugs
Targeted agents
Cytostatic agents
Epigenetic modulators
Selective tool compounds for investigational pathways
Cluster dendrogram of the response of more than 150 anti cancer agents in the Oncolines™ cancer cell line panel.
Distinguishing Synergy from Additivity
The goal of a SynergyFinderTM experiment is to identify cases where the joint effect of a compound combination is improved compared to the additive effects of the individual compounds (Uitdehaag et al., 2015). At NTRC we have developed two experimental set-ups to measure synergy, the fixed IC50 ratio experiment and the fixed dose combination experiment.
Fixed IC50 Ratio Experiment
This is the most robust experiment provided that the single agents show well-behaved dose-response curves. Based on predetermined IC50 values of the single agents, mixtures are generated with theoretical equipotency compared to the single agents. Subsequently, dose response curves of these mixtures are measured in duplicate via cellular profiling. A left-ward curve shift compared to the single agent curves indicates synergy, as described by Zhao et al. (2004).
SynergyFinder™ allows the testing of mixtures of three compounds. The individual contribution of each compound to the total synergy can be determined. In one such experiment, NTRC has shown that the FDA-approved combination of the BRAF inhibitor dabrafenib and the MEK inhibitor trametinib can be further supplemented with the PI3K inhibitor pictilisib to enhance synergy. By establishing such super-synergistic combinations in vitro, it is possible to effectively focus resources for in vivo studies on the most successful multi-combinations.
Dose response curves of single agents (green, blue) and fixed ratio mixtures (orange, yellow, red) allow for curve-shift analysis. The mixture curves are shifted to the left and CI value < 1, meaning synergy. This example is for the combination of a MEK inhibitor and PI3K inhibitor.
Triple synergistic combination of dabrafenib, trametinib and pictilisib (grey curve). The red, yellow and blue curves represent the single agents dabrafenib, trametinib and pictilisib, respectively.
CI Index
As a secondary analysis, we use the experimental data to generate Chou Talalay Combination Indices (Chou T., 2010) providing an independent, quantitative assessment of synergy. The CI Index is the most-used measure of synergy. It can be seen as the ‘dose reduction’ caused by synergy.
The CI is dependent on the fraction effect considered (e.g. 75% growth inhibition). NTRC determines CIs at various effect sizes and drug ratiosGenerally, a CI < 1 indicates synergy for a compound pair, a CI < 0.3 indicates strong synergy, as described by Haagensen et al. (2012). CI > 1 indicates antagonism.
CI values for the combination of a MEK and PI3K inhibitor at various effect levels. Circles represent experimentally determined CI values (Chou Talalay method).
Isobolograms
An isobologram is a graphic way of assessing if combinations show synergy. It shows the effect of a combination at a particular effect level, for instance 50% or 75%. The isobologram draws an isobolic line of theoretical additivity. It is a straight line between the concentration of Compound A to achieve the effect (x-axis) and the concentration of Compound B (y-axis). Mixtures below the line are synergistic. Below the line indicates that the compound concentrations can be decreased to achieve the same effect.
The isobologram for the combination of the MEK and PI3K inhibitor visualizes the effect of mixtures at a % effect. The blue line represents additivity. Mixtures that are below the blue line are synergistic, mixtures at the blue line are additive and mixtures above the line are antagonistic.
Custom Based Studies and Large Combinatorial Screens
The service SynergyFinder™ is highly suitable for small-scale, custom-based studies as well as large combinatorial screens. Small-scale studies can be performed for a selection of Oncolines™ cell lines and selected combinations of your compound with anti-cancer agents. Usually these studies are based on hypotheses regarding genetic background and targeting of compounds. Examples are provided by Uitdehaag et al. (2015) and Canté-Barrett et al. (2016).
Large combinatorial screens, referred to as SynergyScreen™, are generally performed for combinations of your compound with representatives of the diverse anti cancer drug classes that are covered in the compound database. We have identified 42 exemplars covering approved and novel targets. You can also screen the full library of 160 pre-profiled anti cancer drugs, with the purpose to look broadly for opportunities that may go beyond rationalisation.
Cancer Drug Synergy Prediction
Synthetic lethal combinations are identified by a computational approach, referred to as SynergyPredict™. The approach consists of several steps. First, gene expression analysis is performed on drug IC50 data according to GeneNominator™. Gene expression markers, viz. genes for which high expression significantly correlates to drug response are identified for your anti cancer drug. Via a database search, ‘combination genes’ are identified that result in synthetic lethality when combined to your compound’s gene markers (Lee et al., 2018). The identification of gene markers is explained in GeneNominator™. As a last step, compounds are selected for which the ‘combination genes’ are gene expression markers via a query in NTRC’s anti cancer drug database.
Workflow of the synergy prediction algorithm
References
Uitdehaag et al. (2015) Selective Targeting of CTNNB1-, KRAS- or MYC-Driven Cell Growth by Combinations of Existing Drugs, PLoS ONE, 10 (5): e0125021.
http://dx.plos.org/10.1371/journal.pone.0125021
Zhao et al. (2004) Evaluation of combination chemotherapy: integration of nonlinear regression, curve shift, isobologram, and combination index analyses, Clinical Cancer Research, 10 (23): 7994-8004.
http://clincancerres.aacrjournals.org/content/10/23/7994.full.pdf+html
Chou, T. (2010) Drug Combination Studies and Their Synergy Quantification Using the Chou-Talalay Method, Cancer Research, 70 (2): 440-446.
https://cancerres.aacrjournals.org/content/70/2/440
Haagensen et al. (2012) The synergistic interaction of MEK and PI3K inhibitors is modulated by mTOR inhibition, British Journal of Cancer, 106: 1386-1394.
https://www.nature.com/articles/bjc201270
Canté-Barrett et al. (2016) MEK and PI3K-AKT inhibitors synergistically block activated IL7 receptor signaling in T-cell acute lymphoblastic leukemia, Leukemia, 30: 1832-1843.
https://www.nature.com/articles/leu201683
Lee et al. (2018) Harnessing synthetic lethality to predict the response to cancer treatment, Nature Communications, 9: 2546.
https://www.nature.com/articles/s41467-018-04647-1