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Validation of predictive response biomarkers

Structures of compounds used in the study

Reanalyis of cell panel profilings of TTK inhibitors from literature

The spindle assembly checkpoint kinase TTK (Mps1) is a key regulator of chromosome segregation and is the subject of novel targeted therapy approaches by small-molecule inhibitors. Although the first TTK inhibitors have entered phase I dose escalating studies in combination with taxane chemotherapy, a patient stratification strategy is still missing. With the aim to identify a genomic biomarker to predict the response of tumor cells to TTK inhibitor therapy, we profiled a set of preclinical and clinical TTK inhibitors from different chemical series on a panel of 66 genetically characterized cell lines derived from different tumors (Oncolines). Cell lines harboring activating mutations in the CTNNB1 gene, encoding the Wnt pathway signaling regulator β-catenin, were on average up to five times more sensitive to TTK inhibitors than cell lines wild-type for CTNNB1. The association of CTNNB1-mutant status and increased cancer cell line sensitivity to TTK inhibition was confirmed with isogenic cell line pairs harboring either mutant or wild-type CTNNB1. Treatment of a xenograft model of a CTNNB1-mutant cell line with the TTK inhibitor NTRC 0066-0 resulted in complete inhibition of tumor growth. Mutations in CTNNB1 occur at relatively high frequency in endometrial cancer and hepatocellular carcinoma, which are known to express high TTK levels. We propose mutant CTNNB1 as a prognostic drug response biomarker, enabling the selection of patients most likely to respond to TTK inhibitor therapy in proof-of-concept clinical trials. Mol Cancer Ther; 16(11); 2609–17. ©2017 AACR.

All IC50 values, reproducibility, other metrics, all correlations, ibrutinib biochemical IC50

Cell panel data

Workflow for filtering cell line genomic data

Additional reproducibility data

Analysis of MEK and BRAF inhibitors approved before Nov. 2013 in a 102 cell line profiling

Biochemical profiling of kinase inhibitors

Chemical structures and suppliers of compounds used in study

Additional clustering data

Complete drug response biomarker analysis of all kinase inhibitors approved for clinical use since November 2013

Waterfall plots of the VEGFR inhibitors

Beta-catenin pathway is activated in CTNNB1 mutant cell lines, and TTK inhibition has no direct regulatory effect on beta-catenin

Relation between TTK inhibitor sensitivity and CTNNB1 mutant status on the basis of Oncolines data

Sensitivity and specificity of drug response markers

Analysis of EGFR and HER2 inhibitors approved before Nov. 2013 in a 102 cell line profiling

Workflow for identification and validation of predictive drug response biomarkers based on gene expression

Kinetic data derived from SPR experiments

Replicate dose-response data in additional cancer cell lines and isogenic cell lines

Chemical structures of TTK inhibitors

Validation of CTNNB1 as a drug sensitivity biomarker for TTK inhibitors using isogenic cell lines

Gene Set Analysis of NTRC 0066-0 response

Compounds tested in study, overview of cell lines, cancer genes present in cell lines

Indoleamine 2,3-dioxygenase (IDO1) is a key regulator of immune suppression by catalyzing the oxidation of L-tryptophan. IDO1 expression has been related to poor prognosis in several cancers and to resistance to checkpoint immunotherapies. We describe the characterization of a novel small molecule IDO1 inhibitor, NTRC 3883-0, in a panel of biochemical and cell-based assays, and various cancer models. NTRC 3883-0 released the inhibitory effect of IDO1 on CD8-positive T cell proliferation in co-cultures of IDO1-overexpressing cells with healthy donor lymphocytes, demonstrating its immune modulatory activity. In a syngeneic mouse model using IDO1-overexpressing B16F10 melanoma cells, NTRC 3883-0 effectively counteracted the IDO1-induced modulation of L-tryptophan and L-kynurenine levels, demonstrating its in vivo target modulation. Finally, we studied the expression and activity of IDO1 in primary cell cultures established from the malignant ascites of ovarian cancer patients. In these cultures, IDO1 expression was induced upon stimulation with IFNγ, and its activity could be inhibited by NTRC 3883-0. Based on these results, we propose the use of ascites cell-based functional assays for future patient stratification. Our results are discussed in light of the recent discontinuation of clinical trials of more advanced IDO1 inhibitors and the reconsideration of IDO1 as a valid drug target.

Kinase inhibitors form the largest class of precision medicine. From 2013 to 2017, 17 have been approved, with 8 different mechanisms. We present a comprehensive profiling study of all 17 inhibitors on a biochemical assay panel of 280 kinases and proliferation assays of 108 cancer cell lines. Drug responses of the cell lines were related to the presence of frequently recurring point mutations, insertions, deletions, and amplifications in 15 well-known oncogenes and tumor-suppressor genes. In addition, drug responses were correlated with basal gene expression levels with a focus on 383 clinically actionable genes. Cell lines harboring actionable mutations defined in the FDA labels, such as mutant BRAF(V600E) for cobimetinib, or ALK gene translocation for ALK inhibitors, are generally 10 times more sensitive compared with wild-type cell lines. This sensitivity window is more narrow for markers that failed to meet endpoints in clinical trials, for instance CDKN2A loss for CDK4/6 inhibitors (2.7-fold) and KRAS mutation for cobimetinib (2.3-fold). Our data underscore the rationale of a number of recently opened clinical trials, such as ibrutinib in ERBB2- or ERBB4-expressing cancers. We propose and validate new response biomarkers, such as mutation in FBXW7 or SMAD4 for EGFR and HER2 inhibitors, ETV4 and ETV5 expression for MEK inhibitors, and JAK3 expression for ALK inhibitors. Potentially, these new markers could be combined to improve response rates. This comprehensive overview of biochemical and cellular selectivities of approved kinase inhibitor drugs provides a rich resource for drug repurposing, basket trial design, and basic cancer research.

The spindle assembly checkpoint kinase TTK (Mps1) is a key regulator of chromosome segregation and is the subject of novel targeted therapy approaches by small-molecule inhibitors. Although the first TTK inhibitors have entered phase I dose escalating studies in combination with taxane chemotherapy, a patient stratification strategy is still missing. With the aim to identify a genomic biomarker to predict the response of tumor cells to TTK inhibitor therapy, we profiled a set of preclinical and clinical TTK inhibitors from different chemical series on a panel of 66 genetically characterized cell lines derived from different tumors (Oncolines). Cell lines harboring activating mutations in the CTNNB1 gene, encoding the Wnt pathway signaling regulator β-catenin, were on average up to five times more sensitive to TTK inhibitors than cell lines wild-type for CTNNB1. The association of CTNNB1-mutant status and increased cancer cell line sensitivity to TTK inhibition was confirmed with isogenic cell line pairs harboring either mutant or wild-type CTNNB1. Treatment of a xenograft model of a CTNNB1-mutant cell line with the TTK inhibitor NTRC 0066-0 resulted in complete inhibition of tumor growth. Mutations in CTNNB1 occur at relatively high frequency in endometrial cancer and hepatocellular carcinoma, which are known to express high TTK levels. We propose mutant CTNNB1 as a prognostic drug response biomarker, enabling the selection of patients most likely to respond to TTK inhibitor therapy in proof-of-concept clinical trials. Mol Cancer Ther; 16(11); 2609–17. ©2017 AACR.

The protein kinase threonine tyrosine kinase (TTK; also known as Mps1) is a critical component of the spindle assembly checkpoint and a promising drug target for the treatment of aggressive cancers, such as triple negative breast cancer. While the first TTK inhibitors have entered clinical trials, little is known about how the inhibition of TTK with small-molecule compounds affects cellular activity. We studied the selective TTK inhibitor NTRC 0066-0, which was developed in our own laboratory, together with 11 TTK inhibitors developed by other companies, including Mps-BAY2b, BAY 1161909, BAY 1217389 (Bayer), TC-Mps1-12 (Shionogi), and MPI-0479605 (Myrexis). Parallel testing shows that the cellular activity of these TTK inhibitors correlates with their binding affinity to TTK and, more strongly, with target residence time. TTK inhibitors are therefore an example where target residence time determines activity in in vitro cellular assays. X-ray structures and thermal stability experiments reveal that the most potent compounds induce a shift of the glycine-rich loop as a result of binding to the catalytic lysine at position 553. This "lysine trap" disrupts the catalytic machinery. Based on these insights, we developed TTK inhibitors, based on a (5,6-dihydro)pyrimido[4,5-e]indolizine scaffold, with longer target residence times, which further exploit an allosteric pocket surrounding Lys553. Their binding mode is new for kinase inhibitors and can be classified as hybrid Type I/Type III. These inhibitors have very potent anti-proliferative activity that rivals classic cytotoxic therapy. Our findings will open up new avenues for more applications for TTK inhibitors in cancer treatment.

// Marion A.A. Libouban 1, 2 , Jeroen A.D.M. de Roos 1 , Joost C.M. Uitdehaag 1 , Nicole Willemsen-Seegers 1 , Sara Mainardi 2 , Jelle Dylus 1 , Jos de Man 1 , Bastiaan Tops 3 , Jules P.P. Meijerink 4 , Zuzana Storchova 5 , Rogier C. Buijsman 1 , Rene H. Medema 2 , Guido J.R. Zaman 1 1 Netherlands Translational Research Center B.V., Oss, The Netherlands 2 Netherlands Cancer Institute, Amsterdam, The Netherlands 3 Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands 4 Princess Maxima Center for Pediatric Oncology, Utrecht, The Netherlands 5 University of Kaiserslautern, Kaiserslautern, Germany Correspondence to: Guido J.R. Zaman, email: guido.zaman@ntrc.nl Keywords: TTK, Mps1, kinase inhibitor, chromosome instability, aneuploidy Received: November 16, 2016 Accepted: March 03, 2017 Published: March 15, 2017 ABSTRACT Inhibition of the spindle assembly checkpoint kinase TTK causes chromosome mis-segregation and tumor cell death. However, high levels of TTK correlate with chromosomal instability (CIN), which can lead to aneuploidy. We show that treatment of tumor cells with the selective small molecule TTK inhibitor NTRC 0066-0 overrides the mitotic checkpoint, irrespective of cell line sensitivity. In stable aneuploid cells NTRC 0066-0 induced acute CIN, whereas in cells with high levels of pre-existing CIN there was only a small additional fraction of cells mis-segregating their chromosomes. In proliferation assays stable aneuploid cells were more sensitive than cell lines with pre-existing CIN. Tetraploids are thought to be an intermediate between diploid and unstable aneuploid cells. TTK inhibitors had the same potency on post-tetraploid and parental diploid cells, which is remarkable because the post-tetraploids are more resistant to mitotic drugs. Finally, we confirm that the reference compound reversine is a TTK inhibitor and like NTRC 0066-0, inhibits the proliferation of patient-derived colorectal cancer organoids. In contrast, treatment with TTK inhibitor did not reduce the viability of non-proliferating T cell acute lymphoblastic leukemia cells samples. Consequently, TTK inhibitor therapy is expected to spare non-dividing cells, and may be used to target stable aneuploid tumors.

Cancer cell line panels are important tools to characterize the in vitro activity of new investigational drugs. Here, we present the inhibition profiles of 122 anticancer agents in proliferation assays with 44 or 66 genetically characterized cancer cell lines from diverse tumor tissues (Oncolines). The library includes 29 cytotoxics, 68 kinase inhibitors, and 11 epigenetic modulators. For 38 compounds this is the first comparative profiling in a cell line panel. By strictly maintaining optimized assay protocols, biological variation was kept to a minimum. Replicate profiles of 16 agents over three years show a high average Pearson correlation of 0.8 using IC50 values and 0.9 using GI50 values. Good correlations were observed with other panels. Curve fitting appears a large source of variation. Hierarchical clustering revealed 44 basic clusters, of which 26 contain compounds with common mechanisms of action, of which 9 were not reported before, including TTK, BET and two clusters of EZH2 inhibitors. To investigate unexpected clusterings, sets of BTK, Aurora and PI3K inhibitors were profiled in biochemical enzyme activity assays and surface plasmon resonance binding assays. The BTK inhibitor ibrutinib clusters with EGFR inhibitors, because it cross-reacts with EGFR. Aurora kinase inhibitors separate into two clusters, related to Aurora A or pan-Aurora selectivity. Similarly, 12 inhibitors in the PI3K/AKT/mTOR pathway separated into different clusters, reflecting biochemical selectivity (pan-PI3K, PI3Kβγδ-isoform selective or mTOR-selective). Of these, only allosteric mTOR inhibitors preferentially targeted PTEN-mutated cell lines. This shows that cell line profiling is an excellent tool for the unbiased classification of antiproliferative compounds. Mol Cancer Ther; 15(12); 3097–109. ©2016 AACR.

Graphical abstract, Highlights • Side-by-side biochemical comparison of the inhibitors ABH, nor-NOHA and CB-1158. • Arginase-1 binding, inhibition and stabilization by ABH and CB-1158 is pH-dependent. • ABH and CB-1158 have slow association kinetics and a long target residence time. • At higher pH, the catalytic center adopts a more symmetrical coordination structure. • CB-1158 forms an additional hydrogen-bond network in the active site compared to ABH., Arginase-1 is a manganese-dependent metalloenzyme that catalyzes the hydrolysis of L-arginine into L-ornithine and urea. Arginase-1 is abundantly expressed by tumor-infiltrating myeloid cells that promote tumor immunosuppression, which is relieved by inhibition of Arginase-1. We have characterized the potencies of the Arginase-1 reference inhibitors (2S)-2-amino-6-boronohexanoic acid (ABH) and Nω-hydroxy-nor-L-arginine (nor-NOHA), and studied their pH-dependence and binding kinetics. To gain a better understanding of the structural changes underlying the high pH optimum of Arginase-1 and its pH-dependent inhibition, we determined the crystal structure of the human Arginase-1/ABH complex at pH 7.0 and 9.0. These structures revealed that at increased pH, the manganese cluster assumes a more symmetrical coordination structure, which presumably contributes to its increase in catalytic activity. Furthermore, we show that binding of ABH involves the presence of a sodium ion close to the manganese cluster. We also studied the investigational new drug CB-1158 (INCB001158). This inhibitor has a low-nanomolar potency at pH 7.4 and increases the thermal stability of Arginase-1 more than ABH and nor-NOHA. Moreover, CB-1158 displays slow association and dissociation kinetics at both pH 9.5 and 7.4, as indicated by surface plasmon resonance. The potent character of CB-1158 is presumably due to its increased rigidity compared to ABH as well as the formation of an additional hydrogen-bond network as observed by resolution of the Arginase-1/CB-1158 crystal structure.

Introduction: Indoleamine 2,3-dioxygenase (IDO1) is a heme-containing oxidoreductase enzyme that converts L-tryptophan (Trp) into N’-formylkynurenine (NFK). IDO1 is broadly expressed by tumor cells as well as immune cells in the tumor microenvironment of many cancers, which is often correlated with poor prognosis. Depletion of Trp and increased L-kynurenine (Kyn) levels induce immune tolerance by suppression of effector T-cell and natural killer cell functions, and activation of regulatory T-cells and myeloid-derived suppressor cells. Four small molecule inhibitors are currently investigated in phase III (linrodostat/BMS-986205), phase II (epacadostat/INCB024360) or phase I (MK7162 and LY3381916) clinical trials. Linrodostat, epacadostat and LY3381916 are reported as being selective for IDO1 over TDO, while details on MK7162 have not yet been disclosed. The compounds inhibit IDO1 with different mechanisms, with epacadostat binding to the heme-group in the catalytic center of IDO1, while linrodostat and LY3381916 bind to apo-IDO1 and compete with heme for the active site [1-3]. Experimental procedures Clinical and reference IDO1 inhibitors were characterized in biochemical assays for IDO1 and tryptophan 2,3-dioxygenase (TDO), a structurally different enzyme, which also catalyzes the conversion of Trp to NFK. Furthermore, the compounds were profiled in a panel of functional cell-based assays, including human cancer cell lines and assays based on IDO1- or TDO2-overexpressing HEK293 cells. A IDO1-expressing subline of the mouse B16F10 melanoma cell line was generated and used to develop a syngeneic mouse model at Charles River Laboratories (USA) to determine target modulation in vivo [4]. Stable gene expression was confirmed by qPCR and target modulation was examined by measurement of Trp and Kyn levels using LC-MS/MS. Results: Linrodostat has sub-nanomolar cellular potency, despite the absence of any biochemical activity on the timescale of our assays, which is consistent with its reported heme-competing mechanism of inhibition [1]. Linrodostat also inhibits different Cytochrome P450 enzymes with micromolar activity. In our biochemical assays, epacadostat was not selective for IDO1 over TDO, whereas in the IDO1- and TDO2-overexpressing HEK293 cell lines it was 2000 times selective for IDO1. High level expression of IDO1 in B16F10 cells did not result in enhanced tumor growth after grafting in syngeneic mice, which contrasts published data with a similar model [4]. Nonetheless, we observed strong modulation of Trp and Kyn levels in plasma and in tumors of the IDO1-overexpressing mouse model, compared to non-tumor bearing mice. Treatment of the B16F10-IDO1 model with epacadostat did not result in a reduction of tumor growth, though epacadostat did induce clear changes in Trp and Kyn in both plasma and tumor tissue. Conclusion: Our comparative study of the potencies and selectivities of IDO1 inhibitors, as well as our model for measuring in vivo target modulation, helps to identify strengths and weaknesses of current IDO1 inhibitors, and supports the development of new inhibitors. [1] Nelp et al. (2018) Proc. Natl. Acad. Sci. U.S.A. 115, 3249-3254; [2] Yue et al. (2017) ACS Med. Chem. Lett. 8, 486-491; [3] Dorsey et al. (2018) Proceedings: AACR Annual Meeting 2018, Abstract nr. 5245; [4] Holmgaard et al. (2015) Cell Rep. 13, 412-424. Citation Format: Yvonne Grobben, Joost C.M. Uitdehaag, Antoon M. van Doornmalen, Nicole Willemsen-Seegers, Diep Vu-Pham, Jos de Man, Rogier C. Buijsman, Guido J.R. Zaman. Side-by-side comparison of small molecule IDO1 inhibitors in biochemical and cell-based assays and development of a IDO1-expressing mouse model to evaluate target modulation [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr B060. doi:10.1158/1535-7163.TARG-19-B060

Introduction: Epithelial ovarian cancer (EOC) is the most lethal gynecologic malignancy. First-line therapy in advanced EOC is surgery in combination with platinum-based chemotherapy and paclitaxel. 15-20% of patients do not respond and in 80% of advanced cases, the disease recurs within three years. PARP inhibitors synergize with platinum therapy and have been approved for platinum sensitive EOC. Clinical trials with immunotherapies, such as PD-1/PD-L1 blockade, have so far not been successful. Currently, the only approved companion diagnostic is BRCA gene mutations for PARP inhibitors. More diagnostic assays to predict the clinical response to chemo- or immunotherapies are needed. We have developed a biomarker discovery platform using ascites of ovarian cancer patients. Experimental procedures Ascites was gathered from patients by punction or during debulking surgery. Cells were collected by centrifugation and characterized by flow cytometry using specific antibodies. Genomic DNA was sequenced using Illumina cancer gene panels. Gene expression was analyzed by quantitative PCR (qPCR). Cellular activity of the tryptophan metabolizing enzymes IDO1 and TDO was measured with NFK Green [1]. Levels of L-tryptophan and its metabolite L-kynurenine in ascites fluid and blood were determined with LC-MS/MS. In vitro data were related to tumor histopathology and clinical response data. Results: Low passage cell samples from twenty patients were profiled for sensitivity to various cytotoxic agents and targeted anti-cancer therapies in cell proliferation assays. In parallel the mutation status of fifty cancer genes including BRCA1 and 2 was assessed by DNA sequencing. The expression of genes implicated in resistance to chemotherapy (CCNE1, ABCB1) or immunotherapy (PD-L1, IDO1, TDO) was determined with qPCR. The immune status of ascites was analyzed by measuring the relative proportion of different immune cell populations, i.e., cytotoxic and regulatory T cells, monocytes, dendritic and natural killer cells. The expression of the immune suppressive markers PD-L1, IDO1 and TDO was related to the immune cell composition of the ascites, kynurenine-tryptophan ratio, and clinical response data. A tumor cell sample derived from a patient with low grade serous ovarian cancer (LGSOC) was heterozygous for an oncogenic NRAS mutation and was much more sensitive to MEK inhibitors than other samples not harboring the mutation. The cells also expressed IDO1 and high levels of PD-L1 at the cell surface. Two other samples derived from high grade serous ovarian cancer (HGSOC) expressed high PD-L1 and one also IDO1. Several HGSOC samples expressed TDO. One HGSOC sample showed high expression of the ABCB1 gene, encoding the multidrug transporter P-glycoprotein. The sample was relatively resistant to paclitaxel, a known substrate of P-glycoprotein Conclusion: Our study shows that in vitro drug sensitivity assays with primary patient samples can be used to confirm or identify predictive drug response biomarkers. In an ongoing study, in which hundred patients with HGSOC will be included, the in vitro drug response of tumor cells from ascites to first-line cytotoxic anti-cancer agents will be determined and compared to the clinical response of patients bearing specific genomic biomarkers. [1] Seegers et al. (2014) J Biomol Screen 19, 1266-1272 Citation Format: Guido J.R. Zaman, Judith E. den Ouden, Jelle Dylus, Antoon M. van Doornmalen, Winfried R. Mulder, Diep Vu-Pham, Suzanne J.C. van Gerwen, Joost C.M. Uitdehaag, Rogier C. Buijsman, Leon F. Massuger, Anne M. van Altena. A precision medicine platform to predict the clinical response to chemo- and immunotherapy for epithelial ovarian cancer [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr A044. doi:10.1158/1535-7163.TARG-19-A044

Introduction: Combination drug treatment in cancer therapy aims to improve response rate and decrease the development of drug resistance. The discovery of novel drug combinations is constrained by the cost and effort of carrying out large unbiased screens and is hampered by poor translation towards the clinic. We investigate if computational models combined with screening can more efficiently reveal synergistic combinations and improve translation towards the clinic. The models are based on three different biological views of synergy. First, compounds that exploit similar vulnerabilities in cancer cells frequently show synergy in a particular genetic context (targeted synergy, model 1) [1,2]. Secondly, drugs with non-overlapping resistance mechanisms often yield clinically relevant drug combinations (model 2) [3]. Finally, drugs that mimic synthetic lethal interactions will often act synergistically (model 3) [4]. Experimental procedures Oncolines™ is a panel of 102 genetically characterized cell lines from diverse tumor origins, on which proliferation assays are run in parallel in nine-point dose-response curves. In this cell panel we profiled 162 different cancer therapeutics, including many standard of care, chemotherapeutic agents, epigenetic modulators, and approved and pre-clinical drugs such as CDK4/6, ALK and PI3K-inhibitors [5]. Cancer hotspot mutations and gene expression data were downloaded from the DepMap and CCLE databases. ANOVA and Pearson correlations were used to analyze the single agent response and genetic data in the statistical software R, to determine gene mutation (model 1) and resistance markers (model 2). For model 3, clinically relevant synthetic lethal pairs were combined with gene expression data [4]. The methods were used to predict results from published synergy screens, e.g. DREAM [6] and results from an independent experiment (NTRC SynergyScreen™) in which fixed concentrations of the poly-ADP ribose polymerase (PARP) inhibitor niraparib and the BET bromodomain inhibitor JQ1, were combined with nine-point dose-response curves of 150 anticancer agents. Synergies were quantified using curve-shift and CI-index. Results: Using a cancer cell line IC50 profile of a compound (such as Oncolines™), all three computational models of synergy prediction can be applied. Method 1 is successful in predicting combinations that augment a targeted effect, such as combining BRAF and MEK inhibitors in BRAF-mutant cancer [1]. Method 2 does not distinguish between additive or synergistic combinations but can identify clinically relevant combinations [3]. For method 3, a tool was developed that computationally assesses if drug pairs can pharmacologically mimic clinically validated synthetic lethal interactions [4]. This can predict DREAM data with a high AUC of 0.67 in a ROC curve. The tool successfully predicts synergy between niraparib and the SUMO inhibitor 2-D08, and niraparib and BCL2 inhibitors, which we observed in our screen. Conclusions: Computational tools for synergy have predictive value and can be useful to prioritize libraries for empirical combination screening. References: [1] Uitdehaag et al. (2015). PLoS ONE 10(5): e0125021. [2] Seashore-Ludlow et al. (2015) Cancer Discovery, 5: 1210-1223. [3] Palmer et al. (2017) Cell 171: 1678-1691. [4] Lee et al. (2018). Nature Communications 9: 2546. [5] Uitdehaag et al. (2016). Mol. Cancer Ther. 15: 3097-3109. [6] Menden et al. (2019) Nature Communications 10: 2674. Citation Format: Joost C.M. Uitdehaag, Martine B.W. Prinsen, Derek W. van Tilborg, Jeffrey J. Kooijman, Jelle Dylus, Jeroen A.D.M. de Roos, Suzanne J.C. van Gerwen, Jos de Man, Rogier C. Buijsman, Guido J.R. Zaman. Computational models of synergy contribute to efficient combination screening [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr A141. doi:10.1158/1535-7163.TARG-19-A141

In cancer therapy, combination drug treatment aims to improve response rate and decrease the development of drug resistance. The discovery of new effective drug combinations is constrained by the cost and effort of carrying out large unbiased screens and by poor translation of results towards the clinic. Here we describe how focusing on the biological mechanisms underlying the activity of drug candidates may aid a priori selection of promising synergy candidates and help in translate synergistic combinations towards a clinical situation. We have previously shown [1] that curve shift analysis as developed by Straetemans et al. [2] is a better method than combination-matrix screening. Also a dose based score such as the isobologram or the CI-index more robustly assesses synergy than an effect-based score such as the Bliss-additivity [1]. On this basis, we developed a two-step synergy screening approach, called SynergyScreen™. By distinguishing separate synergy screening and synergy confirmation stages, this setup capitalizes on insights from high throughput screening to discover robust and reproducible pharmacologically synergistic pairs. To further improve the efficiency of synergy screening, we focused on pre-selecting compounds in our screening library according to their biological mechanism. We profiled a library of more than 160 anti-cancer agents in a cell panel of 102 cell lines from diverse tumor origins [3]. Agents were clustered according to response and so-called exemplars were collected into a focused library that represents the spectrum of biological mechanisms of current cancer therapy. This synergy screening library includes many standard of care chemotherapeutic agents, approved and pre-clinical kinase inhibitors, epigenetic modulators and compounds acting by other mechanisms. Finally, we harnassed recent insights into the biology of synergy to understand and predict synergistic pairs. A tool was developed that uses the response of a compound in a 102 cell line panel to pick potential synergistic partners from the database of preprofiled compounds. It does this by computationally assessing if pairs can pharmacologically mimick clinically validated synthetic lethal interactions [4]. We optimized prediction accuracy using the results of internal and external synergy screens. The tool was applied to specifically enrich test libraries and to predict synergies at clinically relevant doses, including the results of a SynergyScreen™ with the poly-ADP ribose polymerase (PARP) inhibitor niraparib and the BET bromodomain inhibitor JQ1. References [1] Uitdehaag et al. (2015). PLoS ONE 10(5): e0125021. [2] Straetemans et al. (2005). Biometrical J. 47, 299-308. [3] Uitdehaag et al. (2016). Mol. Cancer Ther. 15, 3097-3109. [4] Lee et al. (2018). Nature Communications 9, 2546. Citation Format: Joost C. Uitdehaag, Derek W. van Tilborg, Martine B.W. Prinsen, Jeffrey J. Kooijman, Jelle Dylus, Jeroen A.D.M. de Roos, Suzanne J.C. van Gerwen, Jos de Man, Rogier C. Buijsman, Guido J.R. Zaman. Combining cell panel profiling and synthetic lethality data to efficiently screen for synergistic combinations [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 2158.

Target residence time (τ) has been suggested to be a better predictor of the biological activity of kinase inhibitors than inhibitory potency (IC50) in enzyme assays. Surface plasmon resonance binding assays for 46 human protein and lipid kinases were developed. The association and dissociation constants of 80 kinase inhibitor interactions were determined. τ and equilibrium affinity constants (KD) were calculated to determine kinetic selectivity. Comparison of τ and KD or IC50 values revealed a strikingly different view on the selectivity of several kinase inhibitors, including the multi-kinase inhibitor ponatinib, which was tested on 10 different kinases. In addition, known pan-Aurora inhibitors resided much longer on Aurora B than on Aurora A, despite having comparable affinity for Aurora A and B. Furthermore, the γ/δ-selective PI3K inhibitor duvelisib and the δ-selective drug idelalisib had similar 20-fold selectivity for δ- over γ-isoform but duvelisib resided much longer on both targets.

To establish the druggability of a target, genetic validation needs to be supplemented with pharmacological validation. Pharmacological studies, especially in the kinase field, are hampered by the fact that many reference inhibitors are not fully selective for one target. Fortunately, the initial trickle of selective inhibitors released in the public domain has steadily swelled into a stream. However, rationally picking the most selective tool compound out of the increasing amounts of available inhibitors has become progressively difficult due to the lack of accurate quantitative descriptors of drug selectivity. A recently published approach, termed ‘selectivity entropy’, is an improved way of expressing selectivity as a single-value parameter and enables rank ordering of inhibitors. We provide a guide to select the best tool compounds for pharmacological validation experiments of candidate drug targets using selectivity entropy. In addition, we recommend which inhibitors to use for studying the biology of the 20 most investigated kinases that are clinically relevant: Abl (ABL1), AKT1, ALK, Aurora A/B, CDKs, MET, CSF1R (FMS), EGFR, FLT3, ERBB2 (HER2), IKBKB (IKK2), JAK2/3, JNK1/2/3 (MAPK8/9/10), MEK1/2, PLK1, PI3Ks, p38α (MAPK14), BRAF, SRC and VEGFR2 (KDR).

Arginase I (ArgI) is an important small molecule drug target in cancer immunotherapy. Arg1 converts L-arginine into L-ornithine and urea. Recruitment of ArgI-expressing myeloid-derived suppressor cells (MSDCs) at a tumor site results in the depletion of L-arginine, which causes reduced proliferation of T-cells and natural killer cells and inhibition of the antitumor immune response. In patient material, MSDC-induced T-cell suppression can be reverted by arginase inhibitors. ArgI inhibitors work synergistically with checkpoint inhibitor therapy in syngeneic mouse models. In order to find novel inhibitors for ArgI, we developed a set of tools to enable screening and hit validation. The first is an activity assay that enables the high-throughput screening (HTS) of compound libraries. Previously reported arginase assays are poorly compatible with HTS due to the requirement of multiple reactions steps, harsh assay conditions, or the use of low-turnover substrates other than L-arginine. We developed a novel ArgI activity assay, which has a homogenous format and requires only two addition steps before readout. The assay makes use of a fluorescence readout and has a high robustness (Z'-factor > 0.7). Progression of the assay can be followed in real time, allowing for kinetic experiments. To investigate the false positive hit rate, the assay was screened at the Pivot Park Screening Centre with a library consisting of 233 compounds with known interference in other assay formats. Using a simple background signal control, the number of false positives in this library was minimized to below 0.2%. The assay was subsequently used to accurately determine the dissociation constants and binding kinetics of the reference inhibitors ABH, NOHA and CB1158. In order to validate the binding of screening hits to ArgI, we developed a thermal shift assay. We observed a shift in the ArgI melting temperature of up to 3.8°C after addition of the most potent inhibitors. In addition, we developed a Surface Plasmon Resonance binding assay. This showed that ABH and CB1158 have long residence times on ArgI. To allow the development of novel inhibitors through rational drug design, we successfully crystallized human ArgI in a novel space group with higher symmetry (P63) compared to those previously reported (space group P3), and without the presence of hemihedral twinning. We determined a series of high resolution (< 1.7 Å) crystal structures at various pH values and with several ligands. These demonstrate that a series of peptide flips lies at the basis of the pH-dependent symmetry of ArgI and its unusually high pH optimum of 9.0 to 9.5. Finally, to assess the cellular activity of ArgI inhibitors, we examined 102 cancer cell lines for ArgI activity and correlated the results to public gene expression profiles. The novel assay portfolio will help to deliver a new generation of ArgI inhibitors. Citation Format: Yvonne Grobben, Joost C. Uitdehaag, Nicole Willemsen-Seegers, Werner W. Tabak, Martine B. Prinsen, Suzanne J. van Gerwen, Jan van Groningen, Johan Friesen, Helma Rutjes, Jos de Man, Rogier C. Buijsman, Guido J. Zaman. High-throughput fluorescence-based assay for screening of Arginase I inhibitors for cancer immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1944.

Morphing structural features of HTS-derived chemotypes led to the discovery of novel 2-cyano-pyrimidine inhibitors of cathepsin K with good pharmacokinetic profiles, for example, compound 20 showed high catK potency (IC(50)=4nM), >580-fold selectivity over catL and catB, and oral bioavailability in the rat of 52%.

In the standard model for reciprocal collaboration, the repeated prisoner's dilemma (PD), it has proved difficult to establish collaboration in larger groups, necessitating the introduction of additional mechanisms such as reputation or assortedness. The problem is corroborated because current multiperson PDs model simultaneous player action, known as a common goods situation, whereas multiperson collaboration could be easier to obtain in a PD with alternate player action, a private goods situation. Here we present such a game, called a dependency game, and show that stable collaboration can be obtained in a 255 player simulation if only players are allowed to remember three previous benefactors, so they can play advanced tit-for-tat. Furthermore, we show that such a freely collaborating population is threatened by assorted strategies, which define groups that parasitize on independent tit-for-tat players. By excluding others, these groups engage in indirect reciprocal behaviour. Our model therefore combines many hitherto separate collaboration-enhancing concepts into one game, and suggests that group formation and collaboration are two separate social phenomena.

We identified mutations in the IL7Ra gene or in genes encoding the downstream signaling molecules JAK1, JAK3, STAT5B, N-RAS, K-RAS, NF1, AKT and PTEN in 49% of patients with pediatric T-cell acute lymphoblastic leukemia (T-ALL). Strikingly, these mutations (except RAS/NF1) were mutually exclusive, suggesting that they each cause the aberrant activation of a common downstream target. Expressing these mutant signaling molecules-but not their wild-type counterparts-rendered Ba/F3 cells independent of IL3 by activating the RAS-MEK-ERK and PI3K-AKT pathways. Interestingly, cells expressing either IL7Ra or JAK mutants are sensitive to JAK inhibitors, but respond less robustly to inhibitors of the downstream RAS-MEK-ERK and PI3K-AKT-mTOR pathways, indicating that inhibiting only one downstream pathway is not sufficient. Here, we show that inhibiting both the MEK and PI3K-AKT pathways synergistically prevents the proliferation of BaF3 cells expressing mutant IL7Ra, JAK and RAS. Furthermore, combined inhibition of MEK and PI3K/AKT was cytotoxic to samples obtained from 6 out of 11 primary T-ALL patients, including 1 patient who had no mutations in the IL7R signaling pathway. Taken together, these results suggest that the potent cytotoxic effects of inhibiting both MEK and PI3K/AKT should be investigated further as a therapeutic option using leukemia xenograft models.

Constitutive JAK-STAT pathway activation occurs in most myeloproliferative neoplasms as well as in a significant proportion of other hematologic malignancies, and is frequently a marker of poor prognosis. The underlying molecular alterations are heterogeneous as they include activating mutations in distinct components (cytokine receptor, JAK, STAT), overexpression (cytokine receptor, JAK) or rare JAK2 fusion proteins. In some cases, concomitant loss of negative regulators contributes to pathogenesis by further boosting the activation of the cascade. Exploiting the signaling bottleneck provided by the limited number of JAK kinases is an attractive therapeutic strategy for hematologic neoplasms driven by constitutive JAK-STAT pathway activation. However, given the conserved nature of the kinase domain among family members and the interrelated roles of JAK kinases in many physiological processes, including hematopoiesis and immunity, broad usage of JAK inhibitors in hematology is challenged by their narrow therapeutic window. Novel therapies are, therefore, needed. The development of more selective inhibitors is a questionable strategy as such inhibitors might abrogate the beneficial contribution of alleviating the cancer-related pro-inflammatory microenvironment and raise selective pressure to a threshold that allows the emergence of malignant subclones harboring drug-resistant mutations. In contrast, synergistic combinations of JAK inhibitors with drugs targeting cascades that work in concert with JAK-STAT pathway appear to be promising therapeutic alternatives to JAK inhibitors as monotherapies.

Mutations in the collagen-like domain of serum mannose-binding protein (MBP) interfere with the ability of the protein to initiate complement fixation through the MBP-associated serine proteases (MASPs). The resulting deficiency in the innate immune response leads to susceptibility to infections. Studies have been undertaken to define the region of MBP that interacts with MASPs and to determine how the naturally occurring mutations affect this interaction. Truncated and modified MBPs and synthetic peptides that represent segments of the collagen-like domain of MBP have been used to demonstrate that MASPs bind on the C-terminal side of the hinge region formed by an interruption in the Gly-X-Y repeat pattern of the collagen-like domain. The binding sites for MASP-2 and for MASP-1 and -3 overlap but are not identical. The two most common naturally occurring mutations in MBP result in substitution of acidic amino acids for glycine residues in Gly-X-Y triplets on the N-terminal side of the hinge. Circular dichroism analysis and differential scanning calorimetry demonstrate that the triple helical structure of the collagen-like domain is largely intact in the mutant proteins, but it is more easily unfolded than in wild-type MBP. Thus, the effect of the mutations is to destabilize the collagen-like domain, indirectly disrupting the binding sites for MASPs. In addition, at least one of the mutations has a further effect on the ability of MBP to activate MASPs.

Screening of new drugs on large cell panels is an important tool to study the biologic mechanism of drug response. From a combination of parallel in vitro tests and bio-informatics analysis, important conclusions can be drawn, for instance about drug selectivity in a cellular context, about resistance mechanisms, and about the patient population in which a drug is effective. This makes cell panel screening indispensable in modern drug discovery. We have set up a platform called Oncolines™ that comprises 102 cell lines from diverse tumor tissues. All cell lines are screened in parallel in high-throughput proliferation assays based on ATP-lite™. Compounds are tested with 9 point dose-response curves in duplicate. Curves are visually inspected. In the past, we have shown that this workflow leads to highly reproducible IC50s, which are necessary for genomic biomarker discovery [1]. For instance, the IC50s have been coupled to curated databases of somatic mutations and copy numbers (1). However, these changes only reflect a small percentage of oncogenic transformations. A more comprehensive view of oncogenic signaling inside a cell can be obtained from mRNA expression levels (2). Here, we describe a workflow to investigate drug response in the 102 cell line Oncolines™ panel based on basal gene expression levels. Correlations between gene expression levels and the log IC50s were calculated for more than 18,000 genes. To reduce the number of false-positive correlations, we considered only genes with a known biologic role in cancer or that were clinically actionable. Secondly, we filtered out genes that correlated indiscriminately with drug responses, by correcting for the average correlations seen in our profiling database of more than 150 inhibitors. This filtered gene list was structured graphically by combining it with information on protein-protein interactions (using the StringDB) or information on which genes are part of the same pathways (a method called Gene Set Analysis). Our method reveals that gene overexpression correlates with drug responses for a number of targets. For instance, EGFR, IGFR, or ALK kinase inhibitors have more potent effects in cell lines that overexpress EGFR, IGFR, or ALK, respectively, and the MDM2 antagonist nutlin is more active in MDM2-overexpressing cell lines. This is irrespective of the genomic alterations driving overexpression of these genes. The distinct response profiles of the spectrum-selective BTK/EGFR/ERBB2 inhibitor ibrutinib and the more selective BTK inhibitor alcalabrutinib could be distinguished as well. Finally, the analysis shows mechanisms of drug resistance. For instance, the response of vincristine strongly correlates to cellular ABCB1 expression, the P-glycoprotein/MDR1 drug transporter, but also to ABCC3, another ABC transporter. Combining basal gene expression levels with cell panel data therefore allows discovery of novel mechanisms of drug response and resistance. References: 1. Uitdehaag et al. Cell panel profiling reveals conserved therapeutic clusters and differentiates the mechanism of action of different PI3K/mTOR, Aurora kinase and EZH2 inhibitors. Mol Cancer Therap 2016;15:3097-3109. 2. Rees et al. Correlating chemical sensitivity and basal gene expression reveals mechanism of action. Nature Chem Biol 2016;12:109-16. Citation Format: Joost C.M. Uitdehaag, Jeffrey Kooijman, Jeroen A.D.M. de Roos, Martine B.W. Prinsen, Jelle Dylus, Suzanne J.C. van Gerwen, Rogier C. Buijsman, Guido J.R. Zaman. Combining cell panel screening with analysis of gene expression levels reveals features of drug response and resistance [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2017 Oct 26-30; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2018;17(1 Suppl):Abstract nr B155.

The dual-specificity protein kinase TTK, commonly referred to as Mps1, is a component of the spindle assembly checkpoint, a surveillance mechanism that ensures the fidelity of chromosome segregation. Inhibition of TTK kinase activity with small molecule kinase inhibitors leads to chromosome segregation errors by allowing mitotic exit in the presence of unattached kinetochores (1). After several rounds of cell division, the accumulation of chromosome segregation errors results in cancer cell death by apoptosis (2). Several TTK inhibitors have been shown to reduce the growth of xenografts of human cancer cell lines from diverse tumor tissue origin in mice. In an immunocompetent mouse model of triple-negative breast cancer (TNBC), TTK inhibitors increased the efficacy of taxane chemotherapy (1). While the first TTK inhibitors have entered phase 1 dose escalating studies in combination with taxane chemotherapy, a patient stratification strategy is still missing. To enable the selection of patients most likely to respond to TTK inhibitor therapy, we profiled a set of ten preclinical and clinical inhibitors (3) on a panel of 66 genetically characterized cancer cell lines derived from different tumor tissues (Oncolines) (4). Drug sensitivity was related to the mutation status of 114 cancer genes in an unbiased way. Cell lines harboring activating mutations in the CTNNB1 gene, encoding the Wnt pathway signaling regulator β-catenin, were on average up to five times more sensitive to TTK inhibitors than cell lines wild-type for CTNNB1. The association of CTNNB1 mutant status and increased cancer cell line sensitivity to TTK inhibition was confirmed with isogenic cell line pairs harboring either mutant or wild-type CTNNB1. Treatment of a xenograft model of a CTNNB1 mutant cell line with the TTK inhibitor NTRC 0066-0 resulted in complete inhibition of tumor growth. Mutations in CTNNB1 occur at relatively high frequency in endometrial cancer and hepatocellular carcinoma, which are known to express high TTK levels (5). Interestingly, β-catenin signaling has also been implicated in intrinsic resistance against immunotherapy in melanoma by regulation of T cell infiltration (6). We propose mutant CTNNB1 as a prognostic drug response biomarker, enabling the selection of patients most likely to respond to TTK inhibitor therapy in proof-of-concept clinical trials. References: 1. Maia et al. Ann Oncol 2015;26:2180-92; 2. Libouban et al. Oncotarget 2017;8:38309-25; 3. Uitdehaag et al. J Mol Biol 2017;429:2211-30; 4. Uitdehaag et al. Mol Cancer Ther 2016;15:3097-109; 5. Liu et al. Oncotarget 2015;6:34309-20; 6. Spranger et al. Nature 2015;523:231-5. Citation Format: Guido Zaman, Jeroen de Roos, Marion Libouban, Martine Prinsen, Jos de Man, Rogier Buijsman, Joost Uitdehaag. TTK inhibitors as a targeted therapy for β-catenin mutant cancers [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2017 Oct 26-30; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2018;17(1 Suppl):Abstract nr B065.

The protein kinase TTK is a critical component of the spindle assembly checkpoint (SAC), which regulates the proper attachment of sister chromatids during mitosis. TTK is essential for normal progression of the cell cycle and is upregulated in various aggressive cancers such as triple negative breast cancer (TNBC). Inhibition of TTK leads to an overriding of the SAC, premature progression of the cell cycle and mitotic catastrophe. TTK inhibition therefore contrasts with e.g. Aurora and PLK1 inhibition, which block the cell cycle [1]. Various studies have shown the clinical utility of TTK inhibition, particularly in combination therapy with paclitaxel [1,2]. In vivo, TTK inhibitor monotherapy has shown partial tumor growth inhibition without weight loss [1,2]. We have developed a novel class of TTK inhibitors based on a pyrimido-indolizine scaffold. These bind selectively and with high affinity to the ATP pocket of TTK and potently inhibit the proliferation of a variety of cell lines [1]. Previously we published a representative of this class, NTRC 0066-0, which has an IC50 of 0.6 nM in a biochemical assay for TTK activity and which is more than 200 times selective over a panel of 276 kinases [1]. NTRC 0066-0 has an average IC50 of 98 nM in proliferation assays in 66 different cell lines (Oncolines™ panel) [3]. To further improve the potency of the pyrimido-indolizine series, we determined the X-ray structures of a dozen of class representatives in complex with TTK. The results were compared to 3D complexes of other chemical scaffolds such as BAY-1161909, Mps-Bay2b, MPI-0479605, NMS-P715 and Mps1-IN1. The pyrimido-indolizine series uses an aromatic moiety to trap the catalytic lysine in the active site, enforcing a catalytically incompetent conformation of TTK. Thermal melting and surface plasmon resonance experiments demonstrate that this leads to a strong stabilization of the kinase domain and a slow dissociation rate for the compounds, which is one of the key determinants for potent cellular activity. We took advantage of these structure-activity relationships to develop analogs of NTRC 0066-0 with increased residence time and cellular potency. One such analog, NTRC 1501-0, inhibits the proliferation of 66 cancer cell lines with an average IC50 of 18 nM, while retaining selectivity over the kinome. It has good pharmacokinetic properties and shows no cross-reactivity with drug safety targets in vitro. In a xenograft model of the human TNBC cell line MDA-MB-231, it completely inhibited tumor growth at a low oral dose, without effect on body weight, indicating good tolerability. These data show, for the first time, that TTK inhibition as monotherapy can achieve complete inhibition of tumor growth. [1] Maia et al. (2015) Annals of Oncology 26, 2180-2192; [2] Wengner et al (2016) Mol. Canc. Therap. 15, 583-592; [3] Uitdehaag et al. (2016) Mol. Canc. Therap., in the press. Citation Format: Joost C. Uitdehaag, Jos de Man, Marion Libouban, Nicole Willemsen-Seegers, Jan Gerard Sterrenburg, Joeri J. de Wit, Jeroen A.D de Roos, Martine B. Prinsen, Rogier C. Buijsman, Guido J. Zaman. NTRC 1501-0, a TTK kinase inhibitor selected for its long target residence time, completely inhibits tumor growth in the MDA-MB-231 xenograft model for triple-negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4185. doi:10.1158/1538-7445.AM2017-4185

Indoleamine 2,3-dioxygenase (IDO1) and tryptophan 2,3-dioxygenase (TDO) are two structurally different enzymes that have a different tissue distribution and physiological roles, but both catalyze the conversion of tryptophan to N-formylkynurenine (NFK). IDO1 has been clinically validated as a small-molecule drug target for cancer, while preclinical studies indicate that TDO may be a target for cancer immunotherapy and neurodegenerative disease. We have developed a high-throughput screening assay for IDO1 and TDO based on a novel chemical probe, NFK Green, that reacts specifically with NFK to form a green fluorescent molecule with an excitation wavelength of 400 nm and an emission wavelength of 510 nm. We provide the first side-by-side comparison of a number of published inhibitors of IDO1 and TDO and reveal that the preclinical IDO1 inhibitor Compound 5l shows significant cross-reactivity with TDO, while the relative selectivity of other published inhibitors was confirmed. The suitability for high-throughput screening of the assays was demonstrated by screening a library of 87,000 chemical substances in 384- or 1536-well format. Finally, we demonstrate that the assay can also be used to measure the capacity of cells to metabolize tryptophan and to measure the cellular potency of IDO1 and TDO inhibitors.

Cyclodextrin glycosyltransferase (CGTase) catalyzes three transglycosylation reactions via a double displacement mechanism involving a covalent enzyme-intermediate complex (substituted-enzyme intermediate). Characterization of the three transglycosylation reactions, however, revealed that they differ in their kinetic mechanisms. Disproportionation (cleavage of an alpha-glycosidic bond of a linear malto-oligosaccharide and transfer of one part to an acceptor substrate) proceeds according to a ping-pong mechanism. Cyclization (cleavage of an alpha-glycosidic bond in amylose or starch and subsequent formation of a cyclodextrin) is a single-substrate reaction with an affinity for the high molecular mass substrate used, which was too high to allow elucidation of the kinetic mechanism. Michaelis-Menten kinetics, however, have been observed using shorter amylose chains. Coupling (cleavage of an alpha-glycosidic bond in a cyclodextrin ring and transfer of the resulting linear malto-oligosaccharide to an acceptor substrate) proceeds according to a random ternary complex mechanism. In view of the different kinetic mechanisms observed for the various reactions, which can be related to differences in substrate binding, it should be possible to mutagenize CGTase in such a manner that a single reaction is affected most strongly. Construction of CGTase mutants that synthesize linear oligosaccharides instead of cyclodextrins thus appears feasible. Furthermore, the rate of interconversion of linear and circular conformations of oligosaccharides in the cyclization and coupling reactions was found to determine the reaction rate. In the cyclization reaction this conversion rate, together with initial binding of the high molecular mass substrate, may determine the product specificity of the enzyme. These new insights will allow rational design of CGTase mutant enzymes synthesizing cyclodextrins of specific sizes.