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Systematic Screening of Targeted Chemical Combinations …Signaling, kinase, lipid Signaling,...
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Systematic Screening of Targeted Chemical Combinations for Cancer Therapy Systematic Screening of Targeted Chemical Combinations for Cancer Therapy Systematic Screening of Targeted Chemical Combinations for Cancer Therapy Systematic Screening of Targeted Chemical Combinations for Cancer Therapy Adrian Heilbut, Joseph Lehár , Glenn F. Short III, Grant R. Zimmermann and Curtis T. Keith Adrian Heilbut, Joseph Lehár , Glenn F. Short III, Grant R. Zimmermann and Curtis T. Keith Adrian Heilbut, Joseph Lehár , Glenn F. Short III, Grant R. Zimmermann and Curtis T. Keith CombinatoRx Inc., Cambridge, MA 02142, USA CombinatoRx Inc., Cambridge, MA 02142, USA #1410 #1410 Abstract Systematic Multi-Target Mechanism Screen Preliminary Results and Analysis Follow-on Studies Abstract Systematic Multi-Target Mechanism Screen Preliminary Results and Analysis Follow-on Studies Systematic Multi-Target Mechanism Screen Preliminary Results and Analysis Follow-on Studies Clinical experience and theoretical analyses suggest that multi-target approaches are required to Synergy Score Statistics Objective Modulators of DNA damage response pathways Clinical experience and theoretical analyses suggest that multi-target approaches are required to overcome redundant and adaptive oncogenic mechanisms, and cotherapies are indeed the standard of Synergy Score Statistics Experimental error estimate from self combinations Objective Screen diverse inhibitors of cellular processes to find 9 Histogram of Additivity Volumes Combos Combos + 0.1mM Topotecan Modulators of DNA damage response pathways DNA damage drugs remain central to cancer therapy care for many cancers. Identification of optimal and selective combinations of the many targeted agents Experimental error estimate from self combinations Scores > 1 are significant at p ~99% Screen diverse inhibitors of cellular processes to find selective antiproliferative synergies. Probe Set Cells 8 HCT116 A549 MRC9 + 0.1mM Topotecan DNA damage drugs remain central to cancer therapy becoming available presents a critical challenge. CombinatoRx has developed a platform for combination high throughput screening (cHTS TM ) that we have deployed to screen combinations of Scores > 1 are significant at p ~99% ~35% of Score>1 synergies are artifacts selective antiproliferative synergies. Cytoskeleton Pleiotropic Viral replication undefined Cytoskel. Probe Set Cells 7 MRC9 self/self Can combinations selectively modulate responses? combination high throughput screening (cHTS TM ) that we have deployed to screen combinations of approved drugs for the discovery of therapeutically relevant synergies in cell based models. In addition ~35% of Score>1 synergies are artifacts Score < 1 tails dominated by artifacts Receptor, neural Receptor, hormone Cytoskeleton Fungal cell wall DNA damage DNA Receptor Cytoskel. HCT116 carcinoma 6 approved drugs for the discovery of therapeutically relevant synergies in cell based models. In addition to providing effective treatments, chemical synergies can provide information on interactions between Score < 1 tails dominated by artifacts 1. Probe Library DNA metabolism DNA synthesis Transcription, activation Receptor, adenosine Receptor, adrenergic Receptor, growth factor DNA Receptor carcinoma (colon) 5 (Count) Selected 24 probes of survival and death pathways to providing effective treatments, chemical synergies can provide information on interactions between targeted pathways, elucidating previously unappreciated connections between disease mechanisms. 430 compounds, ~250 diverse targets Transcription, chromatin Signaling, kinase, PKC Signaling, kinase, MAPK Transcript. Kinase 3 4 log( Selected 24 probes of survival and death pathways Screening combinations in DNA damage background targeted pathways, elucidating previously unappreciated connections between disease mechanisms. Scores are correlated across cell types Probes not biased to therapeutic targets Transcription, machinery Translation, ribosome Signaling, kinase, PKA Signaling, kinase, PKB Kinase A549 2 3 Screening combinations in DNA damage background Here we extend systematic combination screening to probe perturbations of diverse cellular Scores are correlated across cell types Cell line commonalities dominate over artifacts Even coverage of sampled mechanisms Protein processing Signaling, kinase, lipid Signaling, kinase, tyrosine Protein A549 carcinoma (lung) 1 2 Synergies persist on top of DNA damage background Here we extend systematic combination screening to probe perturbations of diverse cellular mechanisms to discover novel pathway interactions with therapeutic potential, and to evaluate the utility Cell line commonalities dominate over artifacts Even coverage of sampled mechanisms Protein modification Protein degradation Signaling, phosphatase Signaling, phosphodiesterase Signaling, kinase modif. Lipid (lung) -4 -3 -2 -1 0 1 2 3 4 0 True 3 way synergies are rare (< ~0.25%) mechanisms to discover novel pathway interactions with therapeutic potential, and to evaluate the utility of combination effect measures for predicting mechanisms of action for novel compounds. A set of 180 Significant synergies occur at ~1% rate Proteasome Metabolism Metabolism, metals Signaling, lipid Signaling, phosphatase Lipid signal MRC9 T116 p53-/- T116 p53-/- T116 p53-/- T116 p53-/- T116 p53-/- T116 p53-/- T116 p53-/- T116 p53-/- T116 p53-/- T116 p53-/- T116 p53-/- T116 p53-/- T116 p53-/- T116 p53-/- T116 p53-/- T116 p53-/- T116 p53-/- T116 p53-/- T116 p53-/- T116 p53-/- T116 p53-/- T116 p53-/- T116 p53-/- T116 p53-/- T116 T116 T116 T116 T116 T116 T116 T116 T116 T116 T116 T116 T116 T116 T116 T116 T116 T116 T116 T116 T116 T116 T116 T116 -4 -3 -2 -1 0 1 2 3 4 Additivity Volume True 3 way synergies are rare (< ~0.25%) chemical probes were selected that modulate molecular targets involved in diverse cellular functions. All Significant synergies occur at ~1% rate 2. Screen Design Metabolism, energy Metabolism, redox Metabolism, lipid Signaling, apoptosis Metab. MRC9 fibroblast HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT HCT116 HCT116 p53 -/- Correlations Between Cell Lines 16,110 pair wise combinations of these probes were tested at multiple concentrations and ratios using cHTS in a proliferation assay with HCT116 human colon cancer cells. Interesting combinations were Synergies are rare but more common than 2. Screen Design Metabolism, sphingolipid Metabolism, sterol Metabolism, leukotriene Signaling, intracellular Signaling, cell cycle Metab. Ion Signaling (lung) HCT C-10331 C-10331 C-10677 C-10739 C-10896 C-11035 C-11343 C-11465 C-12220 C-12240 C-12312 C-12316 C-12317 C-12318 C-12353 C-12390 C-12395 C-12440 C-12460 C-12463 C-12477 C-12487 C-12488 C-12490 C-12505 C-10331 C-10677 C-10739 C-10896 C-11035 C-11343 C-11465 C-12220 C-12240 C-12312 C-12316 C-12317 C-12318 C-12353 C-12390 C-12395 C-12440 C-12460 C-12463 C-12477 C-12487 C-12488 C-12490 C-12505 HCT116 HCT116 p53 -/- 3 re Most combinations behave similarly cHTS in a proliferation assay with HCT116 human colon cancer cells. Interesting combinations were further evaluated for tumor selectivity using additional cell lines. The screen identified both previously Genotype-Specific Synergies r = 0.27±0.08 genetic interactions (~0.5%, Tong et al. 2004) Selected 180 probes covering ~120 targets Ion transport Signaling, ion Signaling, inflammatory Signaling, neural Ion Signaling C-10331 C-10677 C-10739 C-10896 C-11035 1 2 y scor Most combinations behave similarly across isogenic cell lines further evaluated for tumor selectivity using additional cell lines. The screen identified both previously reported and novel synergies and antagonisms that reflect connections between pathways relevant to Genotype-Specific Synergies Does synergy depend on p53 status? Only 1/3 of probes account for 70% of synergies All pairwise combinations in sparse dose matrix C-11035 C-11343 C-11465 C-12220 C-12240 r = 0.20±0.08 -1 0 ditivity reported and novel synergies and antagonisms that reflect connections between pathways relevant to cancer proliferation. Synergy profiles of compounds with proximal targets were found to be correlated, Does synergy depend on p53 status? Only 1/3 of probes account for 70% of synergies Finding unexpected synergies requires Two cancer and one “normal” cell line C-12240 C-12312 C-12316 C-12317 C-12318 -2 -1 C9 add cancer proliferation. Synergy profiles of compounds with proximal targets were found to be correlated, suggesting that such profiles may be used to infer mechanism of action. Combination screening data Finding unexpected synergies requires very large combination screens identify cancer selective synergies A549 MRC9 C-12318 C-12353 C-12390 C-12395 C-12440 r = 0.19± 0.08 -5 -4 -3 -2 -1 0 1 2 3 -4 -3 MRC r = 0.27 ± 0.08 suggesting that such profiles may be used to infer mechanism of action. Combination screening data using cell lines analyzed in the context of emerging knowledge of cancer genotypes and expression Screened combinations of the same 24 probes very large combination screens C-12460 C-12463 C-12477 C-12487 r = 0.19± 0.08 -5 -4 -3 -2 -1 0 1 2 3 HCT116 synergy score using cell lines analyzed in the context of emerging knowledge of cancer genotypes and expression profiles may lead to the development of more selective, personalized, and effective cancer therapies. 384-well Incubate 72h Add ATP-Lite C-12488 C-12490 C-12505 profiles may lead to the development of more selective, personalized, and effective cancer therapies. preliminary data suggests rare selective 3. Quality Control and Filtering 384-well Assay Plate Add ATP-Lite (Luminescence) Profiles for Two Statins Correlation No single-agent effect; Qualitatively different synerty Single-agent effect References: preliminary data suggests rare selective synergies Synergy profiles 2 2.5 3. Quality Control and Filtering Failed plates and bad wells flagged for exclusion Correlation HCT p53 +/+ HCT p53 -/- 1.5 Qualitatively different synerty from secondary target Single-agent effect and modest synergy orB 7 7 Borisy AA et al. “Systematic Discovery of Multicomponent Therapeutics” PNAS 100 (13):7977 (2003) Keith CT, Borisy AA, Stockwell BR. “Multicomponent Therapeutics for Networked Systems” Nat Rev Drug Discov. 4(1):71 (2005) synergies Profile = vector of all scores involving a probe 1 1.5 Failed plates and bad wells flagged for exclusion 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 A B C 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 A e HCT p53 +/+ HCT p53 -/- 0.5 1 core fo (uM) .83 1.7 (uM) .83 1.7 Keith CT, Borisy AA, Stockwell BR. “Multicomponent Therapeutics for Networked Systems” Nat Rev Drug Discov. 4(1):71 (2005) Zimmermann G, Lehar J & Keith CT. “Multi-target therapeutics: when the whole is greater than the sum of the parts” Drug Disc Tod 12(1): 34 Profile = vector of all scores involving a probe Expect similar mechanism correlated profiles 0 0.5 C D E F B C D E Score nhib -0.5 0 Sc lysin ( 1 .41 lysin ( 1 .41 Zimmermann G, Lehar J & Keith CT. “Multi-target therapeutics: when the whole is greater than the sum of the parts” Drug Disc Tod 12(1): 34 Lehar J et al. “Chemical combination effects predict connectivity in biological systems” Mol Syst Biol 3:80 (2007) Eg: p53 pathway modulator + kinase inhibitor Expect similar mechanism correlated profiles -1.5 -1 -0.5 Intra plate artifacts quantified with control wells and G H I J E F G H S ase in -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 -1.5 -1 r = 0.57 ± 0.06 Probe number ascapl .1 .21 ascapl .1 .21 Lehar J et al. “Chemical combination effects predict connectivity in biological systems” Mol Syst Biol 3:80 (2007) potential secondary target of p53 pathway 0 20 40 60 80 100 120 140 160 180 -1.5 Intra plate artifacts quantified with control wells and corrected computationally J K L M N I J K L Score for A Kina -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 -1.5 Fa 0 N=1 Fa 0 N=1 Combination High Throughput Screening potential secondary target of p53 pathway probe whose effect is unmasked in corrected computationally 2005 Q4 Mech Onc MTM Sparse6 / aheilbut-2006-09-06-1 / CT00032194 N O P M N O P Combination High Throughput Screening probe whose effect is unmasked in absence of p53 Cluster analysis HCT116 Compounds with unstable single agent activity Plate Responses 2005 Q4 Mech Onc MTM Sparse6 / aheilbut-2006-09-06-1 / CT00032194 2005 Q4 Mech Onc MTM Sparse6 / aheilbut-2006-09-06-1 / CT00032194 P P53 pathway inhib P53 pathway inhib absence of p53 Clustered profiles by score correlation S D W 3 M HCT116 Score Compounds with unstable single agent activity Plate Responses after Quality Control Sparse Dose Matrix P53 pathway inhib P53 pathway inhib Cell based phenotypic assays Highlights Clustered profiles by score correlation Many probes with similar annotations S 1 S I H P C C G C P P F L U C S M D 2 M S D identified and excluded from analysis Cell based phenotypic assays Highlights Many probes with similar annotations group together T M A 3 P R C M C S P A D T G 5 E H O R S S 1 Statins Preserve biological networks to measure effects in a disease relevant context, and provide group together Profiles contain information on mechanism M T P N N C T C S M V D C E F T I M G B L C T M Dose Response Curve Statins Tubulin inhibitors an opportunity to observe target interactions. Comprehensive, well sampled survey Chemical library Profiles contain information on mechanism A A I A 4 R E J S 8 B F A C S P A I M T C M T 4. Quantifying combination effects I X 1:10? Dose Response Curve Tubulin inhibitors MAPK inhibitors Comprehensive, well sampled survey of antiproliferative chemical combinations Chemical library 2,400+ bioactive agents include: T R L H N S C T C N A M A A U P T N T 2 E A A 4. Quantifying combination effects Different types and patterns of synergy: ect I ug Y 1:1? 1:10? MAPK inhibitors of antiproliferative chemical combinations 2,400+ bioactive agents include: • approved pharmaceutical ingredients J C A R C 2 I R U U R D C O B N E B G 3 T T R Different types and patterns of synergy: Effe Dru 10:1? • approved pharmaceutical ingredients • chemical probes with known targets C H W F P S A G H N 2 F D T A P R W F t T J C potency shift vs. efficacy boost at unknown ratios Concentration X Drug X RTK inhibitors Synergistic antiproliferative combinations are rare • chemical probes with known targets • drugs in development A S A D E T C N L T C S Z D O S G P F T P C Selected Hits M) Dose matrices test many doses and ratios Inhibition (%) Dose Matrix Top view Response Surface RTK inhibitors Synergistic antiproliferative combinations are rare • drugs in development • biologics (antibodies, proteins, siRNA) F R Z S A Probes, by profile similarity Selected Hits Combinations for further investigation: (uM 10 Dose matrices test many doses and ratios Inhibition (%) Dose Matrix Top view Response Surface Synergistic hits reflect both known biology and novel interactions • biologics (antibodies, proteins, siRNA) Combinations for further investigation: d B 3 2.5 1 Response = Inhibition = (untreated-treated)/untreated 5 4 n step Y ion C Y 80 90 100 100 80 80 90 100 100 80 %) Synergistic hits reflect both known biology and novel interactions Dose matrix data . synergistic, selective, novel mechanisms ound 039 .16.63 Response = Inhibition = (untreated-treated)/untreated 3 2 entration rug Y centrati 40 50 60 70 80 60 40 40 50 60 70 80 60 40 ition I (% HCT116 Inhibition (%) DT-1032204 71 70 63 Dose matrix data Inhibition (%) DT-1024585 81 87 89 mpo 0 .01 .0 1 0 Conce Dr Conc 0 00 .00 0 00 0.00 0 10 20 30 5 1.0 .0 20 0 0 00 .00 0 00 0.00 0 10 20 30 5 1.0 .0 20 0 Inhibi MRC9 HCT116 uM) 26 79 43 71 44 70 46 63 46 Subset being followed up with DNA damage and loss of p53 Orthogonally titrated compounds generate 20 81 25 87 65 89 85 Some hits reflect known biology Com Compound A (uM 0 .01 .039.16 .63 2.5 10 Compare response to Loewe additivity model 0 0 1 2 3 4 5 Concentration step Drug X 0.00 0.01 0.02 0.04 0.08 0.16 0.31 0.63 1.25 2.50 5.0 10. 0.00 0.01 0.02 0.04 0.08 0.16 0.31 0.63 1.25 2.50 5.0 10 C o m p o un d B ( u M ) C o m po und A (u M ) 0.0 .03 .13 .25 0.5 1 .03 .13 .25 0.5 1. C o n ce ntra t ion X C o n c e n tra tio n Y .06 .06 0.00 0.01 0.02 0.04 0.08 0.16 0.31 0.63 1.25 2.50 5.0 10. 0.00 0.01 0.02 0.04 0.08 0.16 0.31 0.63 1.25 2.50 5.0 10 C o m p o un d B ( u M ) C o m po und A (u M ) 0.0 .03 .13 .25 0.5 1 .03 .13 .25 0.5 1. C o n ce ntra t ion X C o n c e n tra tio n Y .06 .06 hib hib enin (u 2.9 8.8 -1.6 8.8 19 34 32 36 33 Subset being followed up with DNA damage and loss of p53 a two dimensional dose response matrix. 2 18 4.5 27 17 44 38 Some hits reflect known biology SAMD and ODC inhibs cut off parallel metabolic (expected response for drug-with-itself) Concentration C X C o n ce n Y C o n ce n Y C inh C inh Apige .98 2 =1-2 0 -1.5 -1.6 15 19 20 18 25 32 28 30 32 33 -.4 1.7 4.7 1.7 .1 .4 15 21 33 SAMD and ODC inhibs cut off parallel metabolic pathways in spermine biosynthesis Isobologram Isobologram Additive model Excess (data-model) Observed data ODC ODC 0 Methylglyoxal bis(guanylhydrazone) 0 .41 1.2 3.7 11 33 N= 0 15 20 25 28 32 Synergies and antagonisms can be Methods Methylglyoxal bis(guanylhydrazone) 0 .41 1.2 3.7 11 33 -.4 4.7 1.7 .4 15 33 pathways in spermine biosynthesis Synergy Score = Volume between data and Loewe EC Y 1 d d i t i v i t y 1 d d i t i v i t y O O SAMD inhib SAMD inhib Methylglyoxal bis(guanylhydrazone) dihydrochloride hydrate (uM) identified over many doses and ratios. Methods dihydrochloride hydrate (uM) Synergy Score = Volume between data and Loewe C Y /E . 5 A d 7 5 . 5 A d 7 5 SAMD inhib SAMD inhib Inhibition (%) 2 DT-1032209 -5.8 -12 40 Cell Culture Hits suggest novel biological interactions near 0. on ( %)= 7 0. on ( %)= 7 Inhibition (%) DT-1024587 A549 HCT116 b b M) 17 52 -3.1 -5.8 -10 -12 -.7 40 64 Quantify synergy relative to reference Cell Culture Cell lines were obtained from ATCC and grown in RPMI-1640 media with 10% FBS, 2 mM glutamine, and 1% penicillin/streptomycin. Protein modification inhibitor + Kinase inhibitor Isobologram shows amount of potency shifting Lin 0 0.5 1 0 I n h i b iti o 0 0.5 1 0 I n h i b iti o 0 1.9 -.9 7.2 16 70 76 nhib nhib 490 (uM 1.9 5.8 3.3 8.2 -6.2 -7.7 -7.5 11 55 models. Cell lines were obtained from ATCC and grown in RPMI-1640 media with 10% FBS, 2 mM glutamine, and 1% penicillin/streptomycin. P53-null HCT116 cells were obtained from the Vogelstein Lab at Johns Hopkins. Protein modification inhibitor + Kinase inhibitor Suggests an additional mode of regulation of Linear C X /EC X 0 0.5 1 0 0.5 1 -1.2 -1.5 .4 1.5 4.2 30 54 se in se in AG-4 .64 1 =1-2 -1.2 -.1 3.3 -8.5 -6.2 -4.1 -7.1 -.3 -7.5 3.5 6.3 50 55 Compounds Suggests an additional mode of regulation of a specific kinase signaling pathway X X ∑ 1.6 -1.2 .4 3 4.2 17 54 inas inas 0 Trichostatin A (uM) 0 3e-3 .0091 .027 .081 .24 N= -1.2 -8.5 -4.1 -.3 3.5 50 cHTS TM provides a powerful tool to: Compounds Stock solutions of each compound were prepared in DMSO, and serial dilutions were created in 384 well plates using a MiniTrak (PerkinElmer). Compounds were diluted 1:100 into culture media to create 10X stock on the day of the assay. Combinations were created by a specific kinase signaling pathway 5. Screen Results A549 MRC9 HCT116 Trichostatin A (uM) 0 3e-3 .0091 .027 .081 .24 0 -2.4 4.3 7.1 15 30 Ki Ki Trichostatin A (uM) cHTS provides a powerful tool to: • Discover multi-target mechanisms and (PerkinElmer). Compounds were diluted 1:100 into culture media to create 10X stock on the day of the assay. Combinations were created by diluting (1:10) the plates containing individual compounds into assay plates. 5. Screen Results Full screen performed in HCT116 cells; A549 MRC9 HCT116 Trichostatin A (uM) Prot. Modif inhib Prot. Modif inhib • Discover multi-target mechanisms and therapies diluting (1:10) the plates containing individual compounds into assay plates. Assays Potential therapeutic combination Full screen performed in HCT116 cells; HCT116 MRC9 therapies • Characterize patterns of drug synergy Assays Cells were seeded at 1500 cells per well (A549, HCT116) or 3000 cells per well (MRC9) in 384 well plates and allowed to recover overnight at DNA Damage Agent + Kinase Inhibitor (uM) 3 40 (uM) 3 40 120x120 subset tested in A549 and MRC9 age age • Characterize patterns of drug synergy and antagonism Cells were seeded at 1500 cells per well (A549, HCT116) or 3000 cells per well (MRC9) in 384 well plates and allowed to recover overnight at 37°C. Compounds were added and assay plates incubated at 37°C for proliferation differences to occur. Total time of compound treatment was 72 hours. Effect on cell proliferation was quantified using ATP-Lite 1Step (PerkinElmer), and luminescence was measured using a Wallac Novel interaction between two targets in ipivoxil 4.4 13 ipivoxil 4.4 13 ama dama and antagonism • Guide clinical cotherapy development was 72 hours. Effect on cell proliferation was quantified using ATP-Lite 1Step (PerkinElmer), and luminescence was measured using a Wallac VictorV or Envision plate reader. Percent inhibition of proliferation was calculated compared to vehicle-treated controls. Novel interaction between two targets in clinical development fovir Di .49 1.5 3 fovir Di .49 1.5 2 NA da NA d • Guide clinical cotherapy development decisions VictorV or Envision plate reader. Percent inhibition of proliferation was calculated compared to vehicle-treated controls. Acknowledgements clinical development Selective synergy in HCT116 over MRC9 Adef 0 N=1-3 Adef 0 N=1-2 Synergy Score for the 120x120 probe subset DN DN decisions Acknowledgements We would like to thank John Healy and Yiqun Bai for assistance with screening, and Margaret Lee and Ricky Rickles for valuable advice. Selective synergy in HCT116 over MRC9 Kinase inhib Kinase inhib We would like to thank John Healy and Yiqun Bai for assistance with screening, and Margaret Lee and Ricky Rickles for valuable advice. Kinase inhib AACR Annual Meeting, Los Angeles, April 2007 AACR, Los Angeles, CA, USA, April 2007 AACR Annual Meeting, Los Angeles, April 2007 AACR, Los Angeles, CA, USA, April 2007
Transcript of Systematic Screening of Targeted Chemical Combinations …Signaling, kinase, lipid Signaling,...
Systematic Screening of Targeted Chemical Combinations for Cancer TherapySystematic Screening of Targeted Chemical Combinations for Cancer TherapySystematic Screening of Targeted Chemical Combinations for Cancer TherapySystematic Screening of Targeted Chemical Combinations for Cancer TherapyAdrian Heilbut, Joseph Lehár, Glenn F. Short III, Grant R. Zimmermann and Curtis T. KeithAdrian Heilbut, Joseph Lehár, Glenn F. Short III, Grant R. Zimmermann and Curtis T. KeithAdrian Heilbut, Joseph Lehár, Glenn F. Short III, Grant R. Zimmermann and Curtis T. Keith
CombinatoRx Inc., Cambridge, MA 02142, USACombinatoRx Inc., Cambridge, MA 02142, USA
#1410CombinatoRx Inc., Cambridge, MA 02142, USA
#1410#1410
Abstract Systematic Multi-Target Mechanism Screen Preliminary Results and Analysis Follow-on StudiesAbstract Systematic Multi-Target Mechanism Screen Preliminary Results and Analysis Follow-on StudiesAbstract Systematic Multi-Target Mechanism Screen Preliminary Results and Analysis Follow-on Studies
Clinical experience and theoretical analyses suggest that multi-target approaches are required to Synergy Score StatisticsObjective Modulators of DNA damage response pathwaysClinical experience and theoretical analyses suggest that multi-target approaches are required to
overcome redundant and adaptive oncogenic mechanisms, and cotherapies are indeed the standard ofSynergy Score Statistics
Experimental error estimate from self combinations
Objective
Screen diverse inhibitors of cellular processes to find 9
Histogram of Additivity Volumes Combos
Combos
+ 0.1mM Topotecan
Modulators of DNA damage response pathways
DNA damage drugs remain central to cancer therapyovercome redundant and adaptive oncogenic mechanisms, and cotherapies are indeed the standard of
care for many cancers. Identification of optimal and selective combinations of the many targeted agentsExperimental error estimate from self combinations
Scores > 1 are significant at p ~99%
Screen diverse inhibitors of cellular processes to find
selective antiproliferative synergies. Probe Set Cells 8
HCT116
A549
MRC9
Combos+ 0.1mM TopotecanDNA damage drugs remain central to cancer therapycare for many cancers. Identification of optimal and selective combinations of the many targeted agents
becoming available presents a critical challenge. CombinatoRx has developed a platform for
combination high throughput screening (cHTSTM) that we have deployed to screen combinations of
Scores > 1 are significant at p ~99%~35% of Score>1 synergies are artifacts
selective antiproliferative synergies.Cytoskeleton
Pleiotropic
Viral replication
undefined
Cytoskel.
Probe Set Cells7
MRC9
self /self Can combinations selectively modulate responses?combination high throughput screening (cHTSTM) that we have deployed to screen combinations of
approved drugs for the discovery of therapeutically relevant synergies in cell based models. In addition
~35% of Score>1 synergies are artifactsScore < 1 tails dominated by artifacts
Receptor, neural
Receptor, hormone
CytoskeletonFungal cell wall
DNA damage
DNAReceptor
Cytoskel. HCT116carcinoma
6
approved drugs for the discovery of therapeutically relevant synergies in cell based models. In addition
to providing effective treatments, chemical synergies can provide information on interactions betweenScore < 1 tails dominated by artifacts1. Probe Library
DNA metabolism
DNA synthesis
Transcription, activation
Receptor, adenosine
Receptor, adrenergic
Receptor, growth factor
DNAReceptor carcinoma
(colon)5
log(
Cou
nt)
Selected 24 probes of survival and death pathways to providing effective treatments, chemical synergies can provide information on interactions between
targeted pathways, elucidating previously unappreciated connections between disease mechanisms. 430 compounds, ~250 diverse targets Transcription, chromatin
Signaling, kinase, PKC
Signaling, kinase, MAPK
Transcript.
Kinase3
4
log(
Cou
nt)
Selected 24 probes of survival and death pathways
Screening combinations in DNA damage backgroundtargeted pathways, elucidating previously unappreciated connections between disease mechanisms.Scores are correlated across cell types
430 compounds, ~250 diverse targetsProbes not biased to therapeutic targets
Transcription, machinery
Translation, ribosome
Signaling, kinase, PKA
Signaling, kinase, PKBKinaseA549 2
3 Screening combinations in DNA damage background
Here we extend systematic combination screening to probe perturbations of diverse cellular
Scores are correlated across cell types
� Cell line commonalities dominate over artifacts
Probes not biased to therapeutic targets
Even coverage of sampled mechanismsProtein processing
Signaling, kinase, lipid
Signaling, kinase, tyrosine
Protein
A549carcinoma
(lung) 1
2
� Synergies persist on top of DNA damage backgroundHere we extend systematic combination screening to probe perturbations of diverse cellular
mechanisms to discover novel pathway interactions with therapeutic potential, and to evaluate the utility� Cell line commonalities dominate over artifactsEven coverage of sampled mechanisms
Protein modification
Protein degradation
Signaling, phosphatase
Signaling, phosphodiesterase
Signaling, kinase
Protein
modif.Lipid
(lung)
-4 -3 -2 -1 0 1 2 3 40
1
� Synergies persist on top of DNA damage background
� True 3 way synergies are rare (< ~0.25%)mechanisms to discover novel pathway interactions with therapeutic potential, and to evaluate the utility
of combination effect measures for predicting mechanisms of action for novel compounds. A set of 180Significant synergies occur at ~1% rate
Proteasome
Metabolism
Metabolism, metals
Signaling, lipid
Signaling, phosphataseLipid
signalMRC9
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116 p53-/-
T116
T116
T116
T116
T116
T116
T116
T116
T116
T116
T116
T116
T116
T116
T116
T116
T116
T116
T116
T116
T116
T116
T116
T116
-4 -3 -2 -1 0 1 2 3 4
Additivity Volume
� True 3 way synergies are rare (< ~0.25%)of combination effect measures for predicting mechanisms of action for novel compounds. A set of 180
chemical probes were selected that modulate molecular targets involved in diverse cellular functions. All Significant synergies occur at ~1% rate2. Screen Design
Metabolism, energy
Metabolism, redox
Metabolism, lipid
Signaling, apoptosis
Metab.
signalMRC9
fibroblast
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT
HCT116 HCT116 p53 -/-
Correlations
Between Cell Lines
16,110 pair wise combinations of these probes were tested at multiple concentrations and ratios using
cHTS in a proliferation assay with HCT116 human colon cancer cells. Interesting combinations were� Synergies are rare but more common than2. Screen Design Metabolism, sphingolipid
Metabolism, sterol
Metabolism, leukotrieneSignaling, intracellular
Signaling, cell cycle Metab.
IonSignaling
fibroblast
(lung)HCT
C-10331
C-10331
C-10677
C-10739
C-10896
C-11035
C-11343
C-11465
C-12220
C-12240
C-12312
C-12316
C-12317
C-12318
C-12353
C-12390
C-12395
C-12440
C-12460
C-12463
C-12477
C-12487
C-12488
C-12490
C-12505
C-10331
C-10677
C-10739
C-10896
C-11035
C-11343
C-11465
C-12220
C-12240
C-12312
C-12316
C-12317
C-12318
C-12353
C-12390
C-12395
C-12440
C-12460
C-12463
C-12477
C-12487
C-12488
C-12490
C-12505HCT116 HCT116 p53 -/-
3
ad
ditiv
ity s
co
re
Most combinations behave similarlycHTS in a proliferation assay with HCT116 human colon cancer cells. Interesting combinations were
further evaluated for tumor selectivity using additional cell lines. The screen identified both previouslyGenotype-Specific Synergiesr = 0.27±0.08
� Synergies are rare but more common than
genetic interactions (~0.5%, Tong et al. 2004)Selected 180 probes covering ~120 targetsIon transport
Signaling, ionSignaling, inflammatory
Signaling, neural IonSignalingC-10331
C-10677
C-10739
C-10896
C-110351
2
ad
ditiv
ity s
co
re
Most combinations behave similarly
across isogenic cell lines
further evaluated for tumor selectivity using additional cell lines. The screen identified both previously
reported and novel synergies and antagonisms that reflect connections between pathways relevant to
Genotype-Specific Synergies
Does synergy depend on p53 status?
genetic interactions (~0.5%, Tong et al. 2004)
� Only 1/3 of probes account for 70% of synergies
Selected 180 probes covering ~120 targetsAll pairwise combinations in sparse dose matrix
C-11035
C-11343
C-11465
C-12220
C-12240
r = 0.20±0.08
-1
0
ad
ditiv
ity s
co
re
reported and novel synergies and antagonisms that reflect connections between pathways relevant to
cancer proliferation. Synergy profiles of compounds with proximal targets were found to be correlated,
Does synergy depend on p53 status?� Only 1/3 of probes account for 70% of synergies
� Finding unexpected synergies requires
All pairwise combinations in sparse dose matrix
Two cancer and one “normal” cell lineC-12240
C-12312
C-12316
C-12317
C-12318
-2
-1
MR
C9
ad
ditiv
ity s
co
re
cancer proliferation. Synergy profiles of compounds with proximal targets were found to be correlated,
suggesting that such profiles may be used to infer mechanism of action. Combination screening data� Finding unexpected synergies requires
very large combination screens
Two cancer and one “normal” cell line� identify cancer selective synergies A549 MRC9
C-12318
C-12353
C-12390
C-12395
C-12440
r = 0.19±0.08-5 -4 -3 -2 -1 0 1 2 3
-4
-3
MR
C
r = 0.27 ± 0.08
suggesting that such profiles may be used to infer mechanism of action. Combination screening data
using cell lines analyzed in the context of emerging knowledge of cancer genotypes and expression Screened combinations of the same 24 probesvery large combination screens� identify cancer selective synergies
C-12460
C-12463
C-12477
C-12487
r = 0.19±0.08-5 -4 -3 -2 -1 0 1 2 3
HCT116 synergy scoreusing cell lines analyzed in the context of emerging knowledge of cancer genotypes and expression
profiles may lead to the development of more selective, personalized, and effective cancer therapies.
Screened combinations of the same 24 probes
384-well
Incubate 72h
Add ATP-Lite
C-12488
C-12490
C-12505
profiles may lead to the development of more selective, personalized, and effective cancer therapies.
� preliminary data suggests rare selective 3. Quality Control and Filtering
384-well
Assay Plate
Add ATP-Lite
(Luminescence)Profiles for Two Statins Correlation
No single-agent effect;
Qualitatively different synertySingle-agent effect
References:� preliminary data suggests rare selective
synergiesSynergy profiles
2
2.53. Quality Control and Filtering
Failed plates and bad wells flagged for exclusion
Correlation
HCT p53 +/+ HCT p53 -/-
1.5
Qualitatively different synerty
from secondary target
Single-agent effect
and modest synergy
Score
forB
77
Borisy AA et al. “Systematic Discovery of Multicomponent Therapeutics” PNAS 100 (13):7977 (2003)
Keith CT, Borisy AA, Stockwell BR. “Multicomponent Therapeutics for Networked Systems” Nat Rev Drug Discov. 4(1):71 (2005)
synergiesProfile = vector of all scores involving a probe 1
1.5Failed plates and bad wells flagged for exclusion1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
A
B
C
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
A
Score
HCT p53 +/+ HCT p53 -/-0.5
1
Score
forB
(uM)
.83
1.7
(uM)
.83
1.7Keith CT, Borisy AA, Stockwell BR. “Multicomponent Therapeutics for Networked Systems” Nat Rev Drug Discov. 4(1):71 (2005)
Zimmermann G, Lehar J & Keith CT. “Multi-target therapeutics: when the whole is greater than the sum of the parts” Drug Disc Tod 12(1): 34
Profile = vector of all scores involving a probe
Expect similar mechanism � correlated profiles0
0.5
C
D
E
F
B
C
D
E Score
inhib
-0.5
0
Score
forB
lysin (
1.41
lysin (
1.41
Zimmermann G, Lehar J & Keith CT. “Multi-target therapeutics: when the whole is greater than the sum of the parts” Drug Disc Tod 12(1): 34
Lehar J et al. “Chemical combination effects predict connectivity in biological systems” Mol Syst Biol 3:80 (2007) Eg: p53 pathway modulator + kinase inhibitorExpect similar mechanism � correlated profiles
-1.5
-1
-0.5
Intra plate artifacts quantified with control wells and G
H
I
J
E
F
G
H
Score
Kin
ase
inhib
-1.5 -1 -0.5 0 0.5 1 1.5 2 2.5-1.5
-1
r = 0.57 ± 0.06
Probe number ascapl
.1.21
ascapl
.1.21Lehar J et al. “Chemical combination effects predict connectivity in biological systems” Mol Syst Biol 3:80 (2007) Eg: p53 pathway modulator + kinase inhibitor
� potential secondary target of p53 pathway0 20 40 60 80 100 120 140 160 180
-1.5Intra plate artifacts quantified with control wells and corrected computationally
J
K
L
M
N
I
J
K
LScore for A K
inase
-1.5 -1 -0.5 0 0.5 1 1.5 2 2.5-1.5
Fa
0
N=1Fa
0
N=1
Combination High Throughput Screening� potential secondary target of p53 pathway
probe whose effect is unmasked in corrected computationally
2005 Q4 Mech Onc MTM Sparse6 / aheilbut-2006-09-06-1 / CT00032194
N
O
P
L
M
N
O
PCombination High Throughput Screening probe whose effect is unmasked in
absence of p53Cluster analysisHCT116Compounds with unstable single agent activity Plate Responses
2005 Q4 Mech Onc MTM Sparse6 / aheilbut-2006-09-06-1 / CT00032194
2005 Q4 Mech Onc MTM Sparse6 / aheilbut-2006-09-06-1 / CT00032194
P
P53 pathway inhib P53 pathway inhibabsence of p53Cluster analysis
Clustered profiles by score correlation Staurosporine tyrosine kinaseDigoxin Sodium/Potassium ATPase inhibitorW-7 Calmodulin inhibitor3-Bromopyruvate hexokinase II inhibitorMitomycin DNA cross-linker
HCT116ScoreCompounds with unstable single agent activity Plate Responses
after Quality ControlSparse Dose Matrix
P53 pathway inhib P53 pathway inhib
Cell based phenotypic assaysHighlights
Clustered profiles by score correlation
Many probes with similar annotations Sirolimus mTOR inhibitor1-[(3,4-Dichlorophenyl)methyl]-1H-indole-2,3-dione Apaf-1 activatorS-Trityl-L-cysteine Eg5 inhibitorIbudilast PDE inhibitorH-8 PKA inhibitorParthenolide NFkB inhibitorChelerythrine Chloride PKC inhibitorClomiphene Citrate Squalene epoxidase inhibitorGefitinib (Base) EGFR inhibitorChk2 Inh II Chk2 inhibitorPD169316 p38 inhibitorPrednisolone GC receptor activatorForskolin Adenylate cyclase activatorLY 294002 PI3KUCH-L1 inhibitor UCH-L1 inhibitorCladribine DNA polymerase inhibitorSB 202190 p38 inhibitorMenadione CDC25 phosphatase inhibitorDeferoxamine Mesylate Iron chelator2-amino-8-hydroxyquinoline Urokinase inhibitorMG115 proteasome 26S inhibitorStaurosporine tyrosine kinaseDigoxin Sodium/Potassium ATPase inhibitor
identified and excluded from analysisCell based phenotypic assaysHighlightsMany probes with similar annotations
group togetherTunicamycin P-MurNAc penapeptide synthase; glycosyltransferase inhibitorMethylglyoxal bis(guanylhydrazone) dihydrochloride hydrate S-adenosyl-L-methionine decarboxylase inhibitorAdenosine-5'-(N-ethylcarboxamide) Adenosine receptor agonist3-Aminobenzamide PARP inhibitor; Tubulin binder; HIF-1 antagonistPurvalanol B CDK1 inhibitorRoscovitine CDK1, CDK2, CDK5 inhibitorCelastrol HSF1 inhibitor; cytokine antagonistMycophenolic Acid INPDH (inosine phosphate dehydrogenase) inhibitorC75 Fatty acid synthase inhibitorShikonin Caspase 3/8 activatorProscillaridin Sodium/Potassium ATPase inhibitorAG-1296 PDGFR inhibitor; tyrosine kinase inhibitor; Kit inhibitorDMNB DNAPK inhibitorTG003 Clk inhibitor (Clk1-5)GW9662 PPAR gamma agonist 5,6-Dichloro-1-Beta-D-Ribofuranosylbenzimidazole RNA polymerase IIEthinyl Estradiol Estrogen receptor agonistH 89 PKA inhibitorOlomoucine CDK2 inhibitorRwj-60475 PTP, CD45 inhibitorSuccinylcholine Sirolimus mTOR inhibitor1-[(3,4-Dichlorophenyl)methyl]-1H-indole-2,3-dione Apaf-1 activator
StatinsPreserve biological networks to measure effects in a disease relevant context, and provide Highlights
group together
� Profiles contain information on mechanismManumycin A Ras farnesyltransferase inhibitorTyrphostin 9 PDGFRPaclitaxel Tubulin stabilizerNocodazole Tubulin destabilizerNSC-95397 CDC25 phosphatase inhibitor Calcimycin A23187 Calcium binderTPEN Heavy metal chelatorCyclosporine Calcineurin inhibitorSB218078 Chk1 inhibitorMethotrexate Vinblastine Sulfate Tubulin destabilizerDL-PPMP glucosylceramide synthase inhibitorC6-Ceramide Sphingosine kinase inhibitorEthacrynic Acid Glutathione S-transferase inhibitorFascaplysin CDK4/Cyclin D1 inhibitorToremifene Estrogen receptor inhibitorIMD-0354 IkappaB-alpha kinase inhibitorMonorden HSP90 inhibitorGF 109203X PKC inhibitor Bax Channel Blocker Bax channel blockerLovastatin HMG-CoA reductase inhibitorCerivastatin Sodium HMG-CoA reductase inhibitorTunicamycin P-MurNAc penapeptide synthase; glycosyltransferase inhibitorMethylglyoxal bis(guanylhydrazone) dihydrochloride hydrate S-adenosyl-L-methionine decarboxylase inhibitor
Dose Response Curve
Statins
Tubulin inhibitorsan opportunity to observe target interactions.
Comprehensive, well sampled survey Chemical library
� Profiles contain information on mechanismAphidicolin DNA polymerase inhibitorAdefovir Dipivoxil Reverse transcriptase inhibitorIsotretinoin Retinoic acid receptor binderActinonin MMP, aminopeptidase M4-ANI PARP inhibitorRo106-9920 IkappaB EE ubiquitination inhibitorExo1 ARF1 binderJSH-23 NFkB translocation inhibitorSirtinol HDAC Class III inhibitor8-bromo-cAMP PKA activator; Epac activatorBaicalein LOX (5-Lipoxygenase) inhibitorFluoxetine Hydrochloride Serotonin 5-HT transporterAclarubicin DNA topoisomerase inhibitorCalmidazolium Calmodulin inhibitorSU9516 CDK inhibitorPKR inhibitor PKR inhibitorAnisomycin ribosomal peptidyl transferase inhibitor; p38 activator; JNK activator Imatinib Mesylate (free base) tyrosine kinaseMechlorethamine Hydrochloride DNA alkylatorTrichostatin A HDAC inhibitorClotrimazole Lanosterol 14-alpha-demethylase inhibitorManumycin A Ras farnesyltransferase inhibitorTyrphostin 9 PDGFRPaclitaxel Tubulin stabilizer
4. Quantifying combination effects I X 1:10?
Dose Response Curve Tubulin inhibitors
MAPK inhibitors
an opportunity to observe target interactions.
Comprehensive, well sampled survey
of antiproliferative chemical combinationsChemical library2,400+ bioactive agents include:
Topotecan Hydrochloride DNA topoisomerase I inhibitorRaltitrexed DHFR inhibitorLY 83583 Guanylate cyclase inhibitorHC Toxin HDAC inhibitorN6-Benzyladenosine Adenosine deaminase inhibitorSangivamycin Hydrate PKC inhibitorChlorpromazine Hydrochloride PDE inhibitor; phospholipase A2 inhibitor; NOS inhibitorTrans-4-iodo, 4'-boranyl-chalcone MDM2 inhibitor Cantharidic acid PP1 inhibitor; PP2A inhibitorNifedipine Calcium channel blockerAntimycin A mitochondrial complex III inhibitorMG-132 proteasome 26S inhibitor, NFkB inhibitorApigenin MAP kinase inhibitor; ODC inhibitorAloisine A CDK5/p25 inhibitorU-0126 MEK inhibitorPurvalanol A CDC2 inhibitorTerbinafine Hydrochloride Squalene epoxidase inhibitorNaftopidil adrenergic receptor alpha1 antagonistT0070907 PPAR gamma inhibitor2-methoxyestradiol PARP inhibitor; Tubulin binder; HIF-1 antagonistEtoposide DNA topoisomerase II inhibitorAphidicolin DNA polymerase inhibitorAdefovir Dipivoxil Reverse transcriptase inhibitorIsotretinoin Retinoic acid receptor binder
4. Quantifying combination effects
Different types and patterns of synergy: Effect
I
Dru
g Y 1:1?
1:10?MAPK inhibitors
of antiproliferative chemical combinations2,400+ bioactive agents include:
• approved pharmaceutical ingredientsJuglone parvulin PPIases inhibitor; RNA polymerase II inhibitorCarbobenzoxy-valinyl-phenylalaninal Calpain I inhibitorAG-825 HER2Rottlerin PKC delta inhibitor, CaMKIII inhibitorCytochalasin B Actin polymerization inhibitor; phospholipid synthesis inhibitor2-(p-Hydroxyanilino)-4-(p-chlorophenyl) thiazole Sphingosine kinase inhibitorIndomethacin COX inhibitorRO-20-1724 PDE inhibitorUbenimex LTA4 HydrolaseUCH-L3 inhibitor UCH-L3 inhibitorResveratrol HDAC inhibitorDoxorubicin Hcl DNA topoisomerase II inhibitorCycloheximide ribosomal peptidyl transferase inhibitor; 23S rRNAOxaliplatin DNA cross-linkerBay 41-2272 Guanylate cyclaseNSC 663284 CDC25 phosphatase inhibitor EMETINE DIHYDROCHLORIDE HYDRATE ribosomeBafilomycin A1 mitochondrial F1 ATPase inhibitorGliotoxin farnesyltransferase inhibitor3-(2-Chloro-3-indolylmethylene)-1,3-dihydroindol-2-one CDK1 inhibitorTOFA Acetyl-CoA carboxylase inhibitorTopotecan Hydrochloride DNA topoisomerase I inhibitorRaltitrexed DHFR inhibitor
Different types and patterns of synergy: Effect
Dru
g
10:1?
• approved pharmaceutical ingredients• chemical probes with known targets
Caffeine ATM inhibitor; ATR inhibitorHemicholonium Choline kinase inhibitorWedelolactone IkappaB-alpha kinase inhibitorFluconazole Lanosterol 14-alpha-demethylase inhibitorPropranolol Hydrochloride Phosphatidate phosphohydrolase inhibitor; PKC inhibitorSU11652 PDGFR inhibitor; FGFR inhibitor; VEGFR inhibitor; Kit inhibitorAkt Inhibitor IV AKT inhibitorGenistein tyrosine kinaseHydroxyurea ribonucleoside diphosphate reductase inhibitorN-((3,3,3-Trifluoro-2-trifluromethyl)propionyl)sulfanilamide Hdm2 E3 Ligase inhibitor2-Thio(3-iodobenzyl)-5-(1-pyridyl)-[1,3,4]-oxadiazole GSK-3beta inhibitorFumagillin methionine amino-peptidaseDAG Inhibitor II Diacylglycerol kinase inhibitorTacrolimus (FK-506) Calcineurin inhibitorAG-370 PDGFR inhibitorPiceatannol Syk inhibitor; Lck inhibitor; mitochondrial F1 ATPase inhibitor; RG-14620 EGFR inhibitorWortmannin PI3KFlucytosine DHFS inhibitortrans-HR22C16 Eg5 inhibitorTamoxifen Citrate Estrogen receptor inhibitor; PKC inhibitorJuglone parvulin PPIases inhibitor; RNA polymerase II inhibitorCarbobenzoxy-valinyl-phenylalaninal Calpain I inhibitor
potency shift vs. efficacy boost at unknown ratios Concentration X Drug X
RTK inhibitors
Synergistic antiproliferative combinations are rare• chemical probes with known targets
• drugs in developmentAG-490 JAK tyrosine kinase inhibitorSulfamethoxazole dihydropteroate synthase Acyclovir DNA polymerase inhibitorDNA-PK inhibitor II DNAPK inhibitorEflornithine ODC (Ornithine decarboxylase) inhibitorTO-901317 LXR agonistCarmofur DHFS inhibitorNutlin-3 MDM2 inhibitor L-P-Bromotetramisole Oxalate tyrosine kinase inhibitor; alkaline phosphatase inhibitorThapsigargin Cerulenin HMG-CoA synthetase inhibitorSP 600125 JNK inhibitorZM 449829 JAK1 inhibitor; EGFRK inhibitor; JAK3 inhibitorDexamethasone GC receptor activatorOkadaic acid, Potassium salt PP1 inhibitor; PP2A inhibitorSU1498 Flk-1GW 5074 MAPK, cRAF1Pifithrin-alpha p53 inhibitorFluorouracil DHFR inhibitorTyrphostin 46 EGFR inhibitorPinacidil potassium channel activatorCaffeine ATM inhibitor; ATR inhibitorHemicholonium Choline kinase inhibitor
Selected Hits
Co
mp
ou
nd
B (
uM
)
potency shift vs. efficacy boost at unknown ratios
Dose matrices test many doses and ratios Inhibition (%)Dose Matrix Top viewResponse Surface
RTK inhibitors
Synergistic antiproliferative combinations are rare• drugs in development• biologics (antibodies, proteins, siRNA)
FR122047 COX-1 inhibitorRolipram PDE4 inhibitorZ-VAD (OMe)-FMK caspase inhibitorSU6656 SRC tyrosine kinase inhibitorAG-490 JAK tyrosine kinase inhibitor
Probes, by profile similaritySelected Hits
Combinations for further investigation:
Co
mp
ou
nd
B (
uM
)1
0
Dose matrices test many doses and ratios Inhibition (%)Dose Matrix Top viewResponse Surface
Synergistic hits reflect both known biology and novel interactions• biologics (antibodies, proteins, siRNA)
Probes, by profile similarityCombinations for further investigation:
Co
mp
ou
nd
B (
uM
)6
32
.51
0
Response = Inhibition = (untreated-treated)/untreated
5
4
Co
nce
ntr
atio
n s
tep
Y
Co
ncen
tra
tio
n C
Y
80
90
100100
8080
90
100100
80
(%)
Synergistic hits reflect both known biology and novel interactionsDose matrix data
.synergistic, selective, novel mechanisms
Co
mp
ou
nd
B (
uM
)0
39.1
6.6
3
Response = Inhibition = (untreated-treated)/untreated 3
2
Co
nce
ntr
atio
n s
tep
Dru
g Y
Co
ncen
tra
tio
n
40
50
60
70
80
Inhibition (%
)
80
60
4040
50
60
70
80
Inhibition (%
)
80
60
40
Inh
ibitio
n I
(%
)
HCT116 Inhibition (%)DT-1032204
71 70 63
Synergistic hits reflect both known biology and novel interactionsDose matrix data Inhibition (%)
DT-1024585
81 87 89
synergistic, selective, novel mechanisms
Co
mp
ou
nd
B (
uM
)0
.01
. 03
9
2
1
0
Co
nce
ntr
atio
n s
tep
Dru
g
Co
ncen
tra
tio
n
2.50
5.00
10.00
2.50
5.00
10.00
0
10
20
30Inhibition (%
)
0.5 1
.0
1.0
20
0
2.50
5.00
10.00
2.50
5.00
10.00
0
10
20
30Inhibition (%
)
0.5 1
.0
1.0
20
0
Inh
ibitio
n
MRC9HCT116
uM)
26
79
43
71
44
70
46
63
46
Subset being followed up with DNA damage and loss of p53 Orthogonally titrated compounds generate 20
81
25
87
65
89
85
Some hits reflect known biologyCo
mp
ou
nd
B (
uM
)
Compound A (uM0 .01 .039.16 .63 2.5 10
Compare response to Loewe additivity model0
0 1 2 3 4 5
Concentration stepDrug X 0
.00
0.01
0.02
0.04
0.08
0.16
0.31
0.63
1.25
2.50
5.00
10.00
0.00
0.01
0.02
0.04
0.08
0.16
0.31
0.63
1.25
2.50
5.00
10.00
Compound B (uM) Compo
und A
(uM)
0.0 .0
3
.13 .2
5 0.5 1
.0
.03
.13.2
50.51
.0
ConcentrationXConcentration
Y
.06
.06
0.00
0.01
0.02
0.04
0.08
0.16
0.31
0.63
1.25
2.50
5.00
10.00
0.00
0.01
0.02
0.04
0.08
0.16
0.31
0.63
1.25
2.50
5.00
10.00
Compound B (uM) Compo
und A
(uM)
0.0 .0
3
.13 .2
5 0.5 1
.0
.03
.13.2
50.51
.0
ConcentrationXConcentration
Y
.06
.06
inhib
OD
C inhib
enin (u
2.9
8.8
-1.6
8.8
19
34
32
36
33
Subset being followed up with DNA damage and loss of p53 a two dimensional dose response matrix. 2
18
4.5
27
17
44
38
Some hits reflect known biology
SAMD and ODC inhibs cut off parallel metabolic
Compound A (uMCompare response to Loewe additivity model
(expected response for drug-with-itself)Concentration step
Concentration CX
ConcentrationConcentration
Y ConcentrationConcentration
Y
OD
C inhib
OD
C inhib
Apige
.98
2
=1-2
0
-1.5
-1.6
15
19
20
18
25
32
28
30
32
33a two dimensional dose response matrix.
-.4
1.7
4.7 1.7
.1
.4 15
21
33
SAMD and ODC inhibs cut off parallel metabolic
pathways in spermine biosynthesis
(expected response for drug-with-itself)IsobologramIsobologramAdditive modelExcess (data-model)Observed data O
DC
OD
C inhib
0
Methylglyoxal bis(guanylhydrazone)
0 .41 1.2 3.7 11 33
N=0 15 20 25 28 32
Synergies and antagonisms can be Methods
Methylglyoxal bis(guanylhydrazone)
0 .41 1.2 3.7 11 33
-.4 4.7 1.7 .4 15 33pathways in spermine biosynthesisSynergy Score = Volume between data and Loewe E
CY1
dditivity
1
dditivity O
DC
OD
C inhib
SAMD inhib SAMD inhibMethylglyoxal bis(guanylhydrazone)
dihydrochloride hydrate (uM)
Synergies and antagonisms can be identified over many doses and ratios. Methodsdihydrochloride hydrate (uM)Synergy Score = Volume between data and Loewe
Lin
ea
r C
Y/E
C.5
Ad
75.5
Ad
75
SAMD inhib SAMD inhib
Inhibition (%)
2
DT-1032209
-5.8 -12 40
identified over many doses and ratios.
Cell CultureHits suggest novel biological interactions
Lin
ea
r 0.
on( %
)=70.
on( %
)=7
Inhibition (%)DT-1024587
A549HCT116
Kin
ase in
hib
Kin
ase in
hib
M)17
52
-3.1
-5.8
-10
-12
-.7
40
64Quantify synergy relative to reference Cell Culture
Cell lines were obtained from ATCC and grown in RPMI-1640 media with 10% FBS, 2 mM glutamine, and 1% penicillin/streptomycin.
Hits suggest novel biological interactions
Protein modification inhibitor + Kinase inhibitorIsobologram shows amount of potency shifting
Lin
ea
r
0 0.5 1
0
Inhi biti o
0 0.5 1
0
Inhi biti o
0
1.9
-.9
7.2
16
70
76
Kin
ase in
hib
Kin
ase in
hib
490 (uM
1.9
5.8
3.3
8.2
-6.2
-7.7
-7.5
11
55
Quantify synergy relative to reference models.
Cell lines were obtained from ATCC and grown in RPMI-1640 media with 10% FBS, 2 mM glutamine, and 1% penicillin/streptomycin.
P53-null HCT116 cells were obtained from the Vogelstein Lab at Johns Hopkins.Protein modification inhibitor + Kinase inhibitor
Suggests an additional mode of regulation of Linear CX /ECX
0 0.5 10 0.5 1
-1.2
-1.5
.4
1.5
4.2
30
54
Kin
ase in
hib
Kin
ase in
hib
AG-4
.64
1
=1-2
-1.2
-.1
3.3
-8.5
-6.2
-4.1
-7.1
-.3
-7.5
3.5
6.3
50
55models.
Compounds
Suggests an additional mode of regulation of a specific kinase signaling pathway
Linear CX /ECX
∑ 1.6
-1.2 .4
3
4.2
17
54
Kin
ase in
hib
Kin
ase in
hib
0
Trichostatin A (uM)0 3e-3 .0091 .027 .081 .24
N=-1.2 -8.5 -4.1 -.3 3.5 50
cHTSTM provides a powerful tool to:CompoundsStock solutions of each compound were prepared in DMSO, and serial dilutions were created in 384 well plates using a MiniTrak
(PerkinElmer). Compounds were diluted 1:100 into culture media to create 10X stock on the day of the assay. Combinations were created by
a specific kinase signaling pathway
5. Screen Results A549 MRC9HCT116
∑
Trichostatin A (uM)0 3e-3 .0091 .027 .081 .24
0 -2.4 4.3 7.1 15 30Kin
ase in
hib
Kin
ase in
hib
Trichostatin A (uM)cHTS provides a powerful tool to:• Discover multi-target mechanisms and
(PerkinElmer). Compounds were diluted 1:100 into culture media to create 10X stock on the day of the assay. Combinations were created by
diluting (1:10) the plates containing individual compounds into assay plates.
5. Screen Results
Full screen performed in HCT116 cells;
A549 MRC9HCT116Trichostatin A (uM)
Prot. Modif inhib Prot. Modif inhib• Discover multi-target mechanisms and therapies
diluting (1:10) the plates containing individual compounds into assay plates.
Assays
Potential therapeutic combinationFull screen performed in HCT116 cells; HCT116 MRC9therapies
• Characterize patterns of drug synergyAssaysCells were seeded at 1500 cells per well (A549, HCT116) or 3000 cells per well (MRC9) in 384 well plates and allowed to recover overnight at DNA Damage Agent + Kinase Inhibitor (
uM)
340
(uM)
340
120x120 subset tested in A549 and MRC9
DN
A d
am
age
DN
A d
am
age
• Characterize patterns of drug synergyand antagonism
Cells were seeded at 1500 cells per well (A549, HCT116) or 3000 cells per well (MRC9) in 384 well plates and allowed to recover overnight at
37°C. Compounds were added and assay plates incubated at 37°C for proliferation differences to occur. Total time of compound treatment
was 72 hours. Effect on cell proliferation was quantified using ATP-Lite 1Step (PerkinElmer), and luminescence was measured using a Wallac
DNA Damage Agent + Kinase Inhibitor
Novel interaction between two targets in ipivoxil
4.4
13
ipivoxil
4.4
13
120x120 subset tested in A549 and MRC9
DN
A d
am
age
DN
A d
am
age
and antagonism
• Guide clinical cotherapy development was 72 hours. Effect on cell proliferation was quantified using ATP-Lite 1Step (PerkinElmer), and luminescence was measured using a Wallac
VictorV or Envision plate reader. Percent inhibition of proliferation was calculated compared to vehicle-treated controls.
Novel interaction between two targets in clinical development fo
vir Di
.49
1.5
3 fovir Di
.49
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• Guide clinical cotherapy development decisions
VictorV or Envision plate reader. Percent inhibition of proliferation was calculated compared to vehicle-treated controls.
Acknowledgements
clinical development
� Selective synergy in HCT116 over MRC9
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decisionsAcknowledgements
We would like to thank John Healy and Yiqun Bai for assistance with screening, and Margaret Lee and Ricky Rickles for valuable advice.
� Selective synergy in HCT116 over MRC9Kinase inhib Kinase inhib We would like to thank John Healy and Yiqun Bai for assistance with screening, and Margaret Lee and Ricky Rickles for valuable advice.Kinase inhib
AACR Annual Meeting, Los Angeles, April 2007AACR, Los Angeles, CA, USA, April 2007AACR Annual Meeting, Los Angeles, April 2007AACR, Los Angeles, CA, USA, April 2007
