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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.

The fibroblast growth factor receptors (FGFRs) 1-4 are receptor tyrosine kinases (RTKs) involved in activation of essential cellular processes such as differentiation, proliferation and migration. Since alterations in FGFRs are common in multiple cancers, including breast cancer, non-small cell lung cancer and endometrial cancer, several kinase inhibitors targeting FGFRs are in clinical development. Erdafitinib, a pan-FGFR inhibitor, has been approved as second-line treatment of locally advanced or metastatic urothelial carcinoma harboring genetic FGFR2 or FGFR3 alterations. Although erdafitinib is very effective against these tumors, progression-free survival lasts only a few months, indicating that resistance also develops fast. Insight into the evolved resistance mechanism is crucial for the development of improved therapies. In this study we generated cell lines resistant to erdafitinib by prolonged culturing of the endometrial carcinoma cell line AN3 CA, harboring FGFR2 gain-off-function mutation N549K, to increasing doses of erdafitinib. To gain insight into the developed resistance, the expression of genes that have previously been reported to be involved in resistance against FGFR inhibitors was analyzed by qPCR and immunoblot. In addition, anti-proliferative effects of target inhibition by small molecules was evaluated. To get an unbiased view on altered gene expression, RNA sequencing (RNA-seq) was performed, followed by Gene-Set-Enrichment Analysis (GSEA). Alterations in FGFR1-4 and cancer hotspot gene sequences were detected by DNA sequencing. Occurrence of resistance to erdafitinib was confirmed in proliferation assays by a decreased response of the erdafitinib-resistant cell lines compared to the parental line. In addition, cross-resistance to other FGFR inhibitors infigratinib, pemigatinib, derazantinib and AZD4547 was observed. Although mRNA expression was altered for several RTKs previously reported to be involved in resistance to FGFR inhibitors, such as EGFR, ERBB2/3 and c-MET, involvement in resistance to erdafitinib could be excluded, as no change in response was observed in proliferation assays with their associated targeted inhibitors. RNA-seq and GSEA indicated upregulation of c-Myc target genes in erdafitinib-resistant cell lines. The involvement of c-Myc in the developed resistance was further confirmed by increased response to BET-bromodomain inhibitors JQ1 and I-BET-762, which indirectly target c-Myc. Furthermore, DNA sequencing identified novel mutations in coding regions of FGFR1 and KRAS genes. In conclusion, we show that multiple factors contribute to the development of resistance against erdafitinib in an FGFR2-mutant endometrial carcinoma cell line. BET-bromodomain inhibitors are of potential interest as therapeutic agents to overcome resistance against FGFR inhibitors. Citation Format: Wilhelmina E VAN RIEL, Janneke J. Melis, Demi H. Vogels, Winfried R. Mulder, Jeffrey J. Kooijman, Rogier C. Buijsman, Guido J. Zaman. Altered response to BET-bromodomain inhibitors JQ1 and I-BET-762 targeting c-Myc in erdafitinib-resistant endometrial carcinoma cell line AN3 CA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1080.

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.

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.

Profiling of new drug candidates on cancer cell line panels is an important tool to identify candidate drug response biomarkers for clinical studies. We have set up a platform, called Oncolines™, that comprises 102 genetically well-characterized cell lines from diverse tumor tissues. The cell lines are screened in parallel in a high-throughput proliferation assay based on ATP-lite read-out with 9 point dose-response curves in duplicate and manual inspection of curve fitting. We have recently shown that this workflow leads to highly reproducible IC50s which are necessary for genomic biomarker discovery [1]. Here we apply this platform to investigate BTK and CDK4/6 inhibitors. In previous work [1,2] we correlated the IC50 profiles of small molecule inhibitors through Anova to curated databases of somatic mutations and copy numbers. To obtain a more comprehensive view of oncogenic signaling inside a cell, we calculated in this study correlations between the log IC50s and basal gene expression levels for more than 18,000 genes. To reduce the number of false positives, we first considered only genes with a known role in cancer biology or drug resistance. Secondly, correlations were corrected for the average correlations seen in an Oncolines™ database of more than 150 anti-cancer agents [1]. Thirdly, we looked at co-correlation of genes that interact on a protein level (StringDB) or at a pathway level (Gene Set Analysis). Our method, called GeneNominator™, was validated by profiling the microtubule binder vincristine, the EGFR inhibitor gefitinib, and the MDM2 antagonist nutlin, and confirmed known pharmacogenomic relations.In a first study we tested three CDK4/6 inhibitors, ribociclib, palbociclib and abemaciclib. Although their response patterns cluster together, they show significant differences. For instance, palbociclib is more active on cell lines that express the transcription factor GATA3, which is linked to cyclin signalling in neuroblastoma.In a second study we tested the BTK inhibitors ibrutinib and acalabrutinib. Both show very different inhibition profiles across the 102 cell lines. Ibrutinib shows considerable activity in cell lines that overexpress ERBB4, FGFR2 and ERBB2, reflecting its biochemical inhibition of these kinases. Acalabrutinib, which is more selective, is most active in cell lines that highly express IRF4, a known genetic driver in multiple myeloma. and the B-cell receptor subunit CD79B, of which mutations are often found in diffuse large B-cell lymphoma. When mutations and copy number changes are studied, acalabrutinib is particularly active in cell lines with CREBBP or EZH2 mutations, which occur in diffuse large B-cell lymphomas. Our data demonstrate that our in vitro cell panel screening method can uncover new mechanistic information on clinically used anti-cancer agents. [1] Uitdehaag et al. (2016) Mol. Cancer Ther. 15, 3097-3109.[2] Uitdehaag et al. (2014) PLOS ONE 9: e92146 Citation Format: Joost C. Uitdehaag, Jeffrey J. Kooijman, Jeroen A.D.M. de Roos, Martine B.W. Prinsen, Jelle Dylus, Judith de Vetter, Nicole Willemsen-Seegers, Jos de Man, Suzanne J.C. van Gerwen, Rogier C. Buijsman, Guido J.R. Zaman. Cell line panel profiling reveals novel drug response biomarkers for BTK and CDK4/6 inhibitors [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 4907.

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 aim of combination drug treatment in cancer therapy is to improve response rate and to decrease the probability of the development of drug resistance. Preferably, drug combinations are synergistic rather than additive, and, ideally, drug combinations work synergistically only in cancer cells and not in non-malignant cells. We have developed a workflow to identify such targeted synergies, and applied this approach to selectively inhibit the proliferation of cell lines with mutations in genes that are difficult to modulate with small molecules. The approach is based on curve shift analysis, which we demonstrate is a more robust method of determining synergy than combination matrix screening with Bliss-scoring. We show that the MEK inhibitor trametinib is more synergistic in combination with the BRAF inhibitor dabrafenib than with vemurafenib, another BRAF inhibitor. In addition, we show that the combination of MEK and BRAF inhibitors is synergistic in BRAF-mutant melanoma cells, and additive or antagonistic in, respectively, BRAF-wild type melanoma cells and non-malignant fibroblasts. This combination exemplifies that synergistic action of drugs can depend on cancer genotype. Next, we used curve shift analysis to identify new drug combinations that specifically inhibit cancer cell proliferation driven by difficult-to-drug cancer genes. Combination studies were performed with compounds that as single agents showed preference for inhibition of cancer cells with mutations in either the CTNNB1 gene (coding for β-catenin), KRAS, or cancer cells expressing increased copy numbers of MYC. We demonstrate that the Wnt-pathway inhibitor ICG-001 and trametinib acted synergistically in Wnt-pathway-mutant cell lines. The ERBB2 inhibitor TAK-165 was synergistic with trametinib in KRAS-mutant cell lines. The EGFR/ERBB2 inhibitor neratinib acted synergistically with the spindle poison docetaxel and with the Aurora kinase inhibitor GSK-1070916 in cell lines with MYC amplification. Our approach can therefore efficiently discover novel drug combinations that selectively target cancer genes.

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.

[purpose] An abnormal number of chromosomes, or ‘aneuploidy’, is a common feature of solid human tumors and a predictor of poor prognosis in breast, lung, brain and colorectal cancer. Aneuploidy is caused by malfunctioning of the Spindle Assembly Checkpoint (SAC), a surveillance mechanism that ensures the fidelity of chromosome segregation. The protein kinase TTK (commonly referred to as Mps1) is a component of the SAC. Inhibition of TTK gene expression by RNA interference and inhibition of TTK kinase activity by small molecule kinase inhibitors causes chromosome missegregation and cancer cell death. [experimental procedures] A novel class of compounds was identified that potently inhibits TTK enzyme activity and cancer cell line proliferation [1]. Its binding mode and that of reference inhibitors was characterized by protein crystallography. Binding kinetics and target residence time were determined by surface plasmon resonance using Biacore T200. Anti-proliferative activity was measured on a broad panel of cancer cell lines [2]. [results] The clinical candidate, NTRC 0066-0, inhibits TTK with subnanomolar potency (IC50) in a kinase enzyme assay and is more than 200 times selective over 276 kinases examined, including mitotic and cell cycle dependent kinases (CDKs). X-ray structures of the TTK kinase domain in complex with NTRC 0066-0 and analogs indicate that this class of compounds induces a large conformational shift in the glycine-rich loop, invoking an inactive kinase conformation. In surface plasmon resonance experiments, NTRC 0066-0 exhibited slow dissociation kinetics, resulting in a long target residence time. Parallel surface plasmon resonance experiments with mitotic kinases confirmed the exquisite selectivity of NTRC 0066-0 for TTK over Aurora and Polo-like kinases. NTRC 0066-0 potently inhibited the proliferation of a wide variety of human cancer cell lines with potencies in the same range as marketed cytotoxic agents. The crystal structure, binding kinetics and cellular potency of NTRC 0066-0 were compared to that of other TTK inhibitors such as Mps1-IN-2, AZD-3146, Mps-BAY2b and Bay 1161909 as well as analogs from the NTRC 0066-0 series. This suggest that the unique binding mode of NTRC 0066-0 results in long target residence time which contributes to its strong anti-tumor activity. In subsequent mouse xenograft models of human cancer cell lines, NTRC 0066-0 inhibited tumor growth as a single agent after oral administration at 20 mg per kg. [conclusions] NTRC 0066-0 is a novel TTK inhibitor with outstanding in vitro properties and potent anti-tumor activity in mouse xenograft models. Our data suggest that long target residence time corresponds with potent cellular activity for TTK inhibitors. References [1] Maia et al. (2015) Annals of Oncology 26, 2180-2192; [2] Uitdehaag et al. (2014) PLOS ONE 9(3) e92146. Citation Format: Jos de Man, Joost C.M. Uitdehaag, Nicole Willemsen-Seegers, Jan Gerard Sterrenburg, Joeri J.P. de Wit, Jeroen A.D.M. de Roos, Martine B.W. Prinsen, Rogier C. Buijsman, Guido J.R. Zaman. The unique binding mode of NTRC 0066-0, a novel inhibitor of the spindle assembly checkpoint kinase TTK (Mps1), leads to long target residence time and potent antitumor activity. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2646.

[purpose] Profiling of drug candidates in cell line panels is an important tool to compare the selectivity and targeting of new anti-cancer agents. In addition, comparative profiling may be used to repurpose established therapeutics by identifying new mechanisms of action or cross-selectivities. [experimental procedures] A collection of more than 120 anti-cancer agents, targeting all important oncogenic signaling pathways, including classic cytotoxic agents as well as many targeted kinase inhibitors and epigenetic modulators, was profiled on a panel of 44 or 66 parallel cell line proliferation assays (Oncolines™) [1,2]. The Oncolines™ profiles of the compounds were compared by Pearson correlations of their inhibitor responses. Inhibitor sets were clustered using hierarchical trees. Response profiles were correlated to the genetic background of the cell lines by Analysis of Variance (Anova). [results] Reproducibility of the NTRC Oncolines™ cell panel was validated by monitoring cell growth rate and the variation in IC50s of replicate profiles over a period of three years. The Pearson correlation between replicates ranged between 0.60 and 0.99 for 16 different inhibitors, depending on dose-response curve shape. Correlation analyses of the > 120 profiled anti-cancer agents revealed separate clusters of, a.o., taxanes, platins, topo-isomerase inhibitors, and EGFR, ABL, MEK and BRAF inhibitors. This demonstrates that the Oncolines™ profiles are an unbiased representation of the compound's mechanisms. The profile of the BTK inhibitor ibrutinib correlated with EGFR inhibitors. In biochemical experiments we showed that this due to its cross-reactivity with EGFR. The six Aurora kinase inhibitors profiled fall into two separate clusters, which are related to their biochemical selectivity. Thus, Aurora A-selective inhibitors are relatively more active in cell lines with mutations in cell cycle checkpoint-related genes such as TP53 and RB1; whereas pan-Aurora inhibitors are more active in cell lines with mutations in growth factor signaling pathways, such as NRAS. Profiling of eleven PI3 kinase and mTOR inhibitors revealed four distinct clusters. PI3Kalpha and PI3Kdelta isoform selective inhibitors each target genetically distinct subgroups of cell lines. Rapamycin-analogs, such as everolimus, specifically target PTEN-mutant cell lines. Finally, profiling of EZH2 inhibitors indicates that there are essentially two classes and that these have a cellular profile that is distinct from HDAC, DOT1L or BET inhibitors. [conclusions] Comparative cancer cell line profiling is a powerful tool to rapidly explore the pharmacogenomics of drug action in cancer cells and to identify new or previously unnoted activities of compounds. [references]: [1] Uitdehaag et al. (2014) PLOS ONE 9(3) e92146; [2] Uitdehaag et al. (2015) PLOS ONE 10(6) e0132230. Citation Format: Joost C.M. Uitdehaag, Jeroen A.D.M. de Roos, Martine B.W. Prinsen, Judith R.F. de Vetter, Jelle Dylus, Antoon M. van Doornmalen, Suzanne J.C. van Gerwen, Jos de Man, Rogier C. Buijsman, Guido J.R. Zaman. Comparative cancer cell line profiling differentiates the mechanism of action of different PI3K/mTOR, Aurora kinase and EZH2 inhibitors. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4635.

Background: Pediatric T-cell acute lymphoblastic leukemia patients frequently harbor mutations in IL7Ra or downstream molecules encoded by JAK1, JAK3, N-RAS, K-RAS, NF1, AKT, and PTEN. These mutated signaling molecules can contribute to leukemia by disturbing a multitude of cellular processes such as the cell cycle, epigenetics, apoptosis, or affecting other important signal transduction pathways. Aims: We aimed to determine the overall incidence of mutations in IL7Ra and downstream signaling components in a large cohort of pediatric T-ALL patients. In order to find better treatment options for patients with these mutations, we analyzed the effect of selected IL7Ra-pathway inhibitors-individually and in combinations-on downstream signaling and cytotoxicity in Ba/F3 cells expressing each of the mutations. Methods: We sequenced 146 pediatric T-ALL patient samples for mutations in the FERM, pseudokinase and kinase domains of the Janus kinase gene family (JAK1, JAK2, JAK3, TYK2) and hotspot regions of N-RAS and K-RAS. We adapted the IL3-dependent Ba/F3 cell line to express mutant or wild type genes upon induction by doxycycline and assessed cell viability and signaling in the absence of IL3. Various IL7Ra-pathway inhibitors were tested using this system, and the synergy of combined inhibitors was determined by comparing the dose-response curve of different ratios of IC50-based inhibitor concentrations to the curves for each of the single inhibitors. The Combination Index was calculated using Calcusyn™ software. Results: IL7Ra, JAK, RAS, AKT and PTEN mutations are present in approximately 45% of patients and occur in a predominantly mutually exclusive fashion, suggesting they share aberrant activation of similar downstream targets. We found JAK1, JAK3 and RAS mutations as previously reported, but also identified new JAK1 mutations including V427M, L624YPILKV, E668Q, P815S, and T901G. A novel three-dimensional model of JAK1 reveals that mutations in JAK molecules affect important amino acids that are involved in the interaction between the pseudokinase and kinase domains, facilitating constitutive kinase activity. In our doxycycline-inducible IL3-dependent Ba/F3 system, expression of mutant genes-in contrast to the wild type genes-transforms Ba/F3 cells by supporting IL3-independent growth through activation of the RAS-MEK-ERK and PI3K-AKT pathways. We used this system to test the sensitivity to pharmacological inhibitors; IL7Ra and JAK mutant Ba/F3 cells are sensitive to JAK inhibition, so JAK inhibitors such as ruxolitinib may offer therapeutic potential for IL7Ra, JAK1 or most JAK3 mutated T-ALL patients. The RAS and AKT mutants respond to RAS-MEK and PI3K-AKT-mTOR inhibition, respectively, but are-as expected-insensitive to JAK inhibition. Remarkably, IL7Ra and JAK mutants are relatively resistant to downstream RAS-MEK-ERK or PI3K-AKT-mTOR inhibition, indicating that inhibiting just one of these downstream pathways is insufficient. We provide evidence of (cross-)activation of the alternate pathway when one of these pathways is inhibited. Combined inhibition of MEK and PI3K/AKT synergistically prevents proliferation of the IL7Ra- and JAK-mutants by efficiently blocking both downstream signaling pathways. Furthermore, this combined inhibition is cytotoxic in two out of five tested primary T-ALL specimens. Summary/Conclusion: We show that the combined inhibition of MEK and PI3K/AKT leads to strong and synergistic cytotoxic effects in the IL7Ra and JAK mutants and efficiently blocks signaling downstream of both pathways. This inhibitor combination is effective in two out of five primary T-ALL samples. Therefore, the cytotoxic effects of synergistic MEK and PI3K/AKT inhibition should be further explored as a therapeutic option for (relapsed) ALL patients. Disclosures Buijsman: Netherlands Translational Research Center B.V.: Equity Ownership, Other: founder and shareholder. Zaman:Netherlands Translational Research Center B.V.: Equity Ownership, Other: founder and shareholder.

Background: Many pediatric T-cell acute lymphoblastic leukemia patients harbor mutations in IL7Ra or downstream molecules encoded by JAK1, JAK3, N-RAS, K-RAS, NF1, AKT, and PTEN. These mutated signaling molecules can contribute to leukemia by disturbing a multitude of cellular processes such as the cell cycle, epigenetics, apoptosis, or affecting other important signal transduction pathways. Aims: We aimed to determine the overall incidence of JAK family mutations in a large cohort of T-ALL patients. We also aimed to generate a 3D JAK1 model including known and newly identified JAK mutations in order to better understand how these contribute to JAK kinase activity and the transformation of cells. Methods: We screened 146 pediatric T-ALL patient samples for mutations in the FERM, pseudokinase and kinase domains of the Janus kinase gene family (JAK1-3, TYK2). To establish a 3D JAK1 model, we superimposed individual pseudokinase and kinase crystallographic structures on the homologous TYK2 pseudokinase-kinase structure. We visualized JAK mutations and their effects on the 3D structure. We modified the IL3-dependent Ba/F3 cell line to express JAK mutant or wild type genes upon induction by doxycycline. We tested these Ba/F3 derivative lines for transforming ability, signaling, and resistance to various inhibitors in the absence of IL3. Results: JAK1 or JAK3 mutations were found in 10 patients; no mutations were found in JAK2 or TYK2. We found JAK1 and JAK3 mutations as previously reported, but also identified amino acid substitutions as a result of novel JAK1 mutations including V427M, L624YPILKV, E668Q, P815S, and T901G. Our novel 3D model of JAK1 places most mutations in one of two crucial pseudokinase-kinase interaction sites, which can weaken the interaction and facilitate constitutive kinase activity. One interaction is between the hinge region of the pseudokinase domain and the loop in the kinase domain, which is supported by four salt bridges. Mutations in T-ALL disrupting these salt bridges include E668Q, R724H and its JAK3 equivalent R657Q, and T901G. The second interaction with the kinase domain is formed by a helical domain in the pseudokinase domain, located just upstream of the conserved F575-F636-V658 triad. This F-F-V triad is predicted to act as a structural switch that controls the catalytic activity of JAK kinases. Various mutations occur in the direct vicinity and can affect the function of this switch. V658F in T-ALL and its JAK2 equivalent V617F in polycythemia vera patients are mutations in this triad. The frequent JAK3 mutation M511I in T-ALL flanks the F513 residue (equivalent of JAK1 F575) and also affects the F-F-V triad. The L624YPILKV insertion mutation is located in a loop near the helical domain, which may also subtly compromise the F-F-V triad structural switch leading to derepression of the kinase domain. Expression of mutant JAK genes-in contrast to the wild type genes-transforms Ba/F3 cells by supporting IL3-independent growth, and by activating downstream RAS-MEK-ERK and PI3K-AKT pathways. This pathway activation as a result of ligand-independent mutant JAK kinase activity was confirmed by measuring phospho-proteins including p-MEK, p-ERK, p-AKT, p-mTOR, and p-p70S6K, and can be blocked by JAK inhibitors. Notably, JAK3 mutants signal significantly weaker than JAK1 mutants, possibly due to different dependence on (endogenous) receptors that normally mediate wild type JAK signaling. Summary/Conclusion: In a 3D model, we show that JAK mutations are located in critical interface regions between the pseudokinase and kinase domains, maintaining the kinase in an open, active confirmation. The inducible Ba/F3 model system confirms the transforming capacity of JAK mutations, reveals constitutive active downstream signaling, and is also suitable to test the effect of various inhibitors. The visualization of various JAK mutations in a 3D model and how these contribute to kinase activity provides insight in how mutant JAK could be inhibited, helping guide the development of new small molecule inhibitors of mutant JAKs. Disclosures Buijsman: Netherlands Translational Research Center B.V.: Equity Ownership, Other: founder and shareholder. Zaman:Netherlands Translational Research Center B.V.: Equity Ownership, Other: founder and shareholder.

Purpose: Combination therapy plays an important role in achieving durable responses in anticancer therapy. Ideally, compound combinations work synergistically in cancer cells and not in non-malignant cells. Here we present a rational approach for identifying pairs of selective inhibitors that show a synergistic interaction only in specific genetic backgrounds, i.e. mutated in the CTNNB1 (β-catenin) or KRAS genes, or expressing amplified MYC. Experimental Procedures: We have established a panel of sixty six genetically well-characterized cell lines that represents the most frequently occurring oncogenic drivers in cancer (1). A collection of more than 100 inhibitors targeting all important oncogenic signaling pathways, including many kinase and epigenetic regulators, was profiled in a subset of forty four cell lines, generating highly reproducible and high-quality cell proliferation data. The inhibitor response was correlated to the genetic background of the cell lines by Anova analysis (1). Compounds that targeted similar subsets of cell lines, were tested in combination for synergistic interaction, using in vitro proliferation assays with equipotent mixtures, followed by curve shift analysis, isobolograms and combination index scoring. The approach was validated by showing that the MEK inhibitor trametinib and the BRAF inhibitor dabrafenib, which are targeted to BRAF-mutant cell lines, show synergistic interaction in this subpopulation, and not in other cell line types. Results: For all inhibitors, the drug response in cell line panel (Oncolines™) was analyzed. Notably, the Wnt-pathway inhibitor ICG-001 and the MEK inhibitor trametinib were shown to preferentially inhibit CTNNB1-mutated cancer cell lines. Neratinib, a spectrum selective EGFR inhibitor, and GSK-1070916, an Aurora kinase inhibitor, were shown to target MYC-amplified cell lines. The ERBB2 inhibitor TAK-165 and trametinib targeted KRAS mutant cell lines. These compounds thus show a pharmacological synthetic lethal effect. Subsequent combination studies showed synergy on cell proliferation in a high number of cases. ICG-001 works synergistically with trametinib in a CTNNB1-mutant colon cell line, and not in CTNNB1-wild type colon cell lines. Neratinib and GSK-1070916 work synergistically in MYC-amplified cell lines and not in non-MYC-amplified lines. Conclusions: Pharmacogenomic analysis of single agent responses identified compounds that preferentially inhibit the growth of cell lines harbouring mutant CTNNB1 or KRAS, or amplified MYC. Synergy studies in the pertinent genetic background identified new combinations of existing drugs with enhanced targeting of CTNNB1-mutated or MYC-amplified cancer cell lines. Our approach can efficiently discover novel drug combinations that target cancer genes more selectively and more potently. References: 1. Uitdehaag et al. (2014) PLOS ONE 9(3) e92146. Citation Format: Joost C.M. Uitdehaag, Jeroen A.D.M. de Roos, Antoon M. van Doornmalen, Martine B.W. Prinsen, Jill A.P. Spijkers - Hagelstein, Judith R.F. de Vetter, Jos de Man, Rogier C. Buijsman, Guido J.R. Zaman. Selective targeting of CTNBB1-, KRAS- or MYC-driven cell growth by combinations of existing drugs. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3502. doi:10.1158/1538-7445.AM2015-3502

[Purpose] Kinase inhibitors are a prime example of the success of targeted therapy. Crucial to the development of targeted therapies is the ability to couple drug response to genetic markers, such as mutations in oncogenes and/or tumor suppressors, chromosomal rearrangements, and/or gene amplifications. The efficacy of response to such markers is linked with the biochemical characteristics of kinase inhibitors. However, it is poorly understood what profiles are required to achieve the best targeting. We have systematically compared the biochemical potency and selectivity profiles of all kinase inhibitor drugs in clinical use with their ability to inhibit cell proliferation in a panel of forty-four human cancer cell lines from diverse tumor tissue origins.[Experimental procedures] Proliferation assays were established for a panel of forty-four human cancer cell lines licensed from the American Type Culture Collection. The panel represents twenty-three of the most frequently identified genetic changes in the COSMIC Cell Lines (CCL) project in at least two cell lines. We profiled all twenty-five kinase inhibitors in clinical use on the cancer cell line panel, together with a number of classic cytotoxic agents for comparison. The proliferation assay data were linked to genetic data from the CCL database by Anova and volcano plot analysis. In parallel the biochemical profiles of all twenty-five kinase inhibitor drugs were determined on a panel of 313 protein kinase enzyme activity assays. The biochemical profiling data were used to interpret the cellular targeting compounds in terms of biochemical potency, selectivity and kinase poly-pharmacology.[Results] The suitability of the cell line panel was validated by confirming the known sensitivity of mutant B-RAF to vemurafenib, of BCR-ABL to imatinib, and EGFR overexpression to erlotinib. Mutation in SMAD4 was identified as a novel drug sensitivity marker for EGFR inhibitors, while mutation in the gene for β-catenin was identified as a sensitivity marker for MEK inhibitors, such as trametinib. When comparing compounds with similar mechanisms, dabrafenib is more efficient at selectively inhibiting BRAF-mutant transformed cells than vemurafenib. Of all ABL inhibitors, imatinib has the best targeting efficacy. The compound that most selectively inhibits growth of EGFR-overexpressing cell lines, is gefitinib.[Conclusions] Cancer cell line profiling can be used to identify novel sensitivity markers of drug response. Cancer cell line profiling in combination with biochemical kinase profiling revealed biochemical selectivity and potencies as prime determinants of on target efficacy of kinase inhibitor drugs, the extent of which is target-dependent. The combination of cell panel profiling and kinome profiling is an important tool for the development of optimal targeted therapies for kinases. Citation Format: Guido J.R. Zaman, Joost C.M. Uitdehaag, Rogier C. Buijsman, Jeroen A.D.M. de Roos, Antoon M. van Doornmalen, Martine B.W. Prinsen, Jos de Man, Yusuke Kawase, Yoshinori Tanizawa, Kohichiro Yoshino. Analysis of the cancer gene targeting of clinical kinase inhibitor drugs by combining cellular and biochemical profiling. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2849. doi:10.1158/1538-7445.AM2014-2849

The synthesis of three heparin analogues (i.e. compounds VI-VIII) having perphosphorylated thrombin binding domains (TBDs) is reported. These compounds were tested in vitro for their antithrombin III (ATIII)-mediated anti-Xa and antithrombin activities. Conjugates VI and VIII show a remarkable increase in antithrombin activity compared to the structurally related conjugates with persulfated TBDs (i.e. compounds IV and V), whereas compound VII displays a diminished activity.

The synthesis of a novel antithrombotic consisting of a heparin pentasaccharide conjugated to the active site inhibitor N-(2- naphtalenesulfonyl)-glycyl-( d )-4-aminophenyl-alanyl-piperidine (NAPAP) (i.e. compound I) is reported. This conjugate shows a unique pharmacological profile both in vitro and in vivo having direct anti-thrombin and ATIII-mediated anti-Xa activity. Furthermore, conjugate I has a prolonged in vivo half-life compared to NAPAP (1.5 h vs 9 min.).