Persistence and gazing at humans during an unsolvable task in dogs: The influence of ownership duration, living situation, and prior experience with humans.

The experiences that domestic dogs have with humans take many forms. We hypothesized that more experience with humans would lead to greater dependence on humans in problem-solving situations. We used the unsolvable task to compare persistence and gazing in dogs with differing degrees of experience with humans: 1) dogs living in a home for a year or more; 2) dogs living in a home for less than a year (including foster dogs); and 3) shelter dogs. Dogs first learned a solvable task; we then measured persistence as well as gazing at humans when the task was unsolvable. Dogs living in a home for a year or more gazed sooner and longer than shelter dogs. Formally trained dogs from breeders also gazed sooner than formally trained dogs from shelters. There were no differences in overall persistence among the three types of dog. However, shelter dogs spent more time biting the box and gazing at it than dogs in the home. Former shelter dogs, former strays, and dogs that had no formal training also spent more time biting the box. We conclude that ownership duration, background, and prior experiences with humans influence human-directed communication and persistence behaviors in dogs.

Addressing Unusual Assay Variability with Robust Statistics.

Well-behaved, in vitro bioassays generally produce normally distributed values in their primary (efficacy) data. Accordingly, the best practices for statistical analysis are well documented and understood. However, assays may occasionally display unusually high variability and fall outside the assumptions inherent in these standard analyses. These assays may still be in the optimization phase, in which the source of variation could be identified and addressed. They might also represent the best available option to address the biological process being examined. In these cases, the use of robust statistical methods may provide a more appropriate set of tools for both data analysis and assay optimization. This article provides guidance on best practices for the use of robust statistical methods for the analysis of bioassay data as an alternative to standard methods. Impacts on experimental design and interpretation will be discussed.

A pan-cancer transcriptome analysis identifies replication fork and innate immunity genes as modifiers of response to the CHK1 inhibitor prexasertib.

The combined influence of oncogenic drivers, genomic instability, and/or DNA damage repair deficiencies increases replication stress in cancer. Cells with high replication stress rely on the upregulation of checkpoints like those governed by CHK1 for survival. Previous studies of the CHK1 inhibitor prexasertib demonstrated activity across multiple cancer types. Therefore, we sought to (1) identify markers of prexasertib sensitivity and (2) define the molecular mechanism(s) of intrinsic and acquired resistance using preclinical models representing multiple tumor types. Our findings indicate that while cyclin E dysregulation is a driving mechanism of prexasertib response, biomarkers associated with this aberration lack sufficient predictive power to render them clinically actionable for patient selection. Transcriptome analysis of a pan-cancer cell line panel and in vivo models revealed an association between expression of E2F target genes and prexasertib sensitivity and identified innate immunity genes associated with prexasertib resistance. Functional RNAi studies supported a causal role of replication fork components as modulators of prexasertib response. Mechanisms that protect cells from oncogene-induced replication stress may safeguard tumors from such stress induced by a CHK1 inhibitor, resulting in acquired drug resistance. Furthermore, resistance to prexasertib may be shaped by innate immunity.

A phase 1 dose-escalation study of checkpoint kinase 1 (CHK1) inhibitor prexasertib in combination with p38 mitogen-activated protein kinase (p38 MAPK) inhibitor ralimetinib in patients with advanced or metastatic cancer.

Purpose The primary objective was to determine the recommended Phase 2 dose (RP2D) of checkpoint kinase 1 inhibitor, prexasertib, in combination with the p38 mitogen-activated protein kinase inhibitor, ralimetinib, which may be safely administered to patients with advanced cancer. Methods This Phase 1, nonrandomized, open-label, dose-escalation study of prexasertib+ralimetinib included patients with advanced and/or metastatic cancer, followed by a planned cohort expansion in patients with colorectal or non-small-cell lung cancer with KRAS and/or BRAF mutations. Intravenous prexasertib was administered at 60 mg/m2 (days 1 and 15 of a 28-day cycle), together with oral ralimetinib every 12 h (days 1 to 14 at 100 mg [Cohort 1, n = 3] or 200 mg [Cohort 2, n = 6]). Dose escalations for each agent were planned using a model-based 3 + 3 escalation paradigm. Safety was assessed using Common Terminology Criteria for Adverse Events (CTCAE) v4.0X. Tumor response was determined by Response Evaluation Criteria in Solid Tumors (RECIST) v1.1. Results Nine patients were treated; 3 experienced dose-limiting toxicities, all in Cohort 2, prohibiting further dose escalation. The most common ≥Grade 3 adverse event was neutrophil count decreased; other reported ≥Grade 3 hematological toxicities included febrile neutropenia and anemia. The pharmacokinetics of prexasertib+ralimetinib was comparable to the monotherapy population profile for each agent. One patient achieved a best overall response of stable disease (for 2 cycles); there were no complete/partial responses. Conclusions This study did not achieve its primary objective of establishing an RP2D of combination prexasertib + ralimetinib that could be safely administered to patients with advanced cancer.

Translational Framework Predicting Tumour Response in Gemcitabine-Treated Patients with Advanced Pancreatic and Ovarian Cancer from Xenograft Studies.

The aim of this evaluation was to predict tumour response to gemcitabine in patients with advanced pancreas or ovarian cancer using pre-clinical data obtained from xenograft tumour-bearing mice. The approach consisted of building a translational model combining pre-clinical pharmacokinetic-pharmacodynamic (PKPD) models and parameters, with dosing paradigms used in the clinics along with clinical PK models to derive tumour profiles in humans driving overall survival. Tumour growth inhibition simulations were performed using drug effect parameters obtained from mice, system parameters obtained from mice after appropriate scaling, patient PK models for gemcitabine and carboplatin, and the standard dosing schedules given in the clinical scenario for both types of cancers. Tumour profiles in mice were scaled by body weight to their equivalent values in humans. As models for survival in humans showed that tumour size was the main driver of the hazard rate, it was possible to describe overall survival in pancreatic and ovarian cancer patients. Simulated tumour dynamics in pancreatic and ovarian cancer patients were evaluated using available data from clinical trials. Furthermore, calculated metrics showed values (maximal tumour regression [0-17%] and tumour size ratio at week 12 with respect to baseline [- 9, - 4.5]) in the range of those predicted with the clinical PKPD models. The model-informed Drug Discovery and Development paradigm has been successfully applied retrospectively to gemcitabine data, through a semi-mechanistic translational approach, describing the time course of the tumour response in patients from pre-clinical studies.

Aurora A Kinase Inhibition Is Synthetic Lethal with Loss of the RB1 Tumor Suppressor Gene.

Loss-of-function mutations in the retinoblastoma gene RB1 are common in several treatment-refractory cancers such as small-cell lung cancer and triple-negative breast cancer. To identify drugs synthetic lethal with RB1 mutation (RB1 mut), we tested 36 cell-cycle inhibitors using a cancer cell panel profiling approach optimized to discern cytotoxic from cytostatic effects. Inhibitors of the Aurora kinases AURKA and AURKB showed the strongest RB1 association in this assay. LY3295668, an AURKA inhibitor with over 1,000-fold selectivity versus AURKB, is distinguished by minimal toxicity to bone marrow cells at concentrations active against RB1 mut cancer cells and leads to durable regression of RB1 mut tumor xenografts at exposures that are well tolerated in rodents. Genetic suppression screens identified enforcers of the spindle-assembly checkpoint (SAC) as essential for LY3295668 cytotoxicity in RB1-deficient cancers and suggest a model in which a primed SAC creates a unique dependency on AURKA for mitotic exit and survival. SIGNIFICANCE: The identification of a synthetic lethal interaction between RB1 and AURKA inhibition, and the discovery of a drug that can be dosed continuously to achieve uninterrupted inhibition of AURKA kinase activity without myelosuppression, suggest a new approach for the treatment of RB1-deficient malignancies, including patients progressing on CDK4/6 inhibitors.See related commentary by Dick and Li, p. 169.This article is highlighted in the In This Issue feature, p. 151.

Broad Spectrum Activity of the Checkpoint Kinase 1 Inhibitor Prexasertib as a Single Agent or Chemopotentiator Across a Range of Preclinical Pediatric Tumor Models.

PURPOSE: Checkpoint kinase 1 (CHK1) inhibitors potentiate the DNA-damaging effects of cytotoxic therapies and/or promote elevated levels of replication stress, leading to tumor cell death. Prexasertib (LY2606368) is a CHK1 small-molecule inhibitor under clinical evaluation in multiple adult and pediatric cancers. In this study, prexasertib was tested in a large panel of preclinical models of pediatric solid malignancies alone or in combination with chemotherapy. EXPERIMENTAL DESIGN: DNA damage and changes in cell signaling following in vitro prexasertib treatment in pediatric sarcoma cell lines were analyzed by Western blot and high content imaging. Antitumor activity of prexasertib as a single agent or in combination with different chemotherapies was explored in cell line-derived (CDX) and patient-derived xenograft (PDX) mouse models representing nine different pediatric cancer histologies. RESULTS: Pediatric sarcoma cell lines were highly sensitive to prexasertib treatment in vitro, resulting in activation of the DNA damage response. Two PDX models of desmoplastic small round cell tumor and one malignant rhabdoid tumor CDX model responded to prexasertib with complete regression. Prexasertib monotherapy also elicited robust responses in mouse models of rhabdomyosarcoma. Concurrent administration with chemotherapy was sufficient to overcome innate resistance or prevent acquired resistance to prexasertib in preclinical models of neuroblastoma, osteosarcoma, and Ewing sarcoma, or alveolar rhabdomyosarcoma, respectively. CONCLUSIONS: Prexasertib has significant antitumor effects as a monotherapy or in combination with chemotherapy in multiple preclinical models of pediatric cancer. These findings support further investigation of prexasertib in pediatric malignancies.

Characterization of a novel AICARFT inhibitor which potently elevates ZMP and has anti-tumor activity in murine models.

AICARFT is a folate dependent catalytic site within the ATIC gene, part of the purine biosynthetic pathway, a pathway frequently upregulated in cancers. LSN3213128 is a potent (16 nM) anti-folate inhibitor of AICARFT and selective relative to TS, SHMT1, MTHFD1, MTHFD2 and MTHFD2L. Increases in ZMP, accompanied by activation of AMPK and cell growth inhibition, were observed with treatment of LY3213128. These effects on ZMP and proliferation were dependent on folate levels. In human breast MDA-MB-231met2 and lung NCI-H460 cell lines, growth inhibition was rescued by hypoxanthine, but not in the A9 murine cell line which is deficient in purine salvage. In athymic nude mice, LSN3213128 robustly elevates ZMP in MDA-MB-231met2, NCI-H460 and A9 tumors in a time and dose dependent manner. Significant tumor growth inhibition in human breast MDA-MB231met2 and lung NCI-H460 xenografts and in the syngeneic A9 tumor model were observed with oral administration of LSN3213128. Strikingly, AMPK appeared activated within the tumors and did not change even at high levels of intratumoral ZMP after weeks of dosing. These results support the evaluation of LSN3213128 as an antineoplastic agent.

Abemaciclib Is Active in Preclinical Models of Ewing Sarcoma via Multipronged Regulation of Cell Cycle, DNA Methylation, and Interferon Pathway Signaling.

PURPOSE: Ewing sarcoma (ES) is a rare and highly malignant cancer that occurs in the bone and surrounding tissue of children and adolescents. The EWS/ETS fusion transcription factor that drives ES pathobiology was previously demonstrated to modulate cyclin D1 expression. In this study, we evaluated abemaciclib, a small-molecule CDK4 and CDK6 (CDK4 and 6) inhibitor currently under clinical investigation in pediatric solid tumors, in preclinical models of ES. EXPERIMENTAL DESIGN: Using Western blot, high-content imaging, flow cytometry, ELISA, RNA sequencing, and CpG methylation assays, we characterized the in vitro response of ES cell lines to abemaciclib. We then evaluated abemaciclib in vivo in cell line-derived xenograft (CDX) and patient-derived xenograft (PDX) mouse models of ES as either a monotherapy or in combination with chemotherapy. RESULTS: Abemaciclib induced quiescence in ES cell lines via a G1 cell-cycle block, characterized by decreased proliferation and reduction of Ki-67 and FOXM1 expression and retinoblastoma protein (RB) phosphorylation. In addition, abemaciclib reduced DNMT1 expression and promoted an inflammatory immune response as measured by cytokine secretion, antigen presentation, and interferon pathway upregulation. Single-agent abemaciclib reduced ES tumor volume in preclinical mouse models and, when given in combination with doxorubicin or temozolomide plus irinotecan, durable disease control was observed. CONCLUSIONS: Collectively, our data demonstrate that the antitumor effects of abemaciclib in preclinical ES models are multifaceted and include cell-cycle inhibition, DNA demethylation, and immunogenic changes.

Assay Guidance Manual: Quantitative Biology and Pharmacology in Preclinical Drug Discovery.

The Assay Guidance Manual (AGM) is an eBook of best practices for the design, development, and implementation of robust assays for early drug discovery. Initiated by pharmaceutical company scientists, the manual provides guidance for designing a "testing funnel" of assays to identify genuine hits using high-throughput screening (HTS) and advancing them through preclinical development. Combined with a workshop/tutorial component, the overall goal of the AGM is to provide a valuable resource for training translational scientists.

Targeting the TGFß pathway with galunisertib, a TGFßRI small molecule inhibitor, promotes anti-tumor immunity leading to durable, complete responses, as monotherapy and in combination with checkpoint blockade.

BACKGROUND: TGFß signaling plays a pleotropic role in tumor biology, promoting tumor proliferation, invasion and metastasis, and escape from immune surveillance. Inhibiting TGFß's immune suppressive effects has become of particular interest as a way to increase the benefit of cancer immunotherapy. Here we utilized preclinical models to explore the impact of the clinical stage TGFß pathway inhibitor, galunisertib, on anti-tumor immunity at clinically relevant doses. RESULTS: In vitro treatment with galunisertib reversed TGFß and regulatory T cell mediated suppression of human T cell proliferation. In vivo treatment of mice with established 4T1-LP tumors resulted in strong dose-dependent anti-tumor activity with close to 100% inhibition of tumor growth and complete regressions upon cessation of treatment in 50% of animals. This effect was CD8+ T cell dependent, and led to increased T cell numbers in treated tumors. Mice with durable regressions rejected tumor rechallenge, demonstrating the establishment of immunological memory. Consequently, mice that rejected immunogenic 4T1-LP tumors were able to resist rechallenge with poorly immunogenic 4 T1 parental cells, suggesting the development of a secondary immune response via antigen spreading as a consequence of effective tumor targeting. Combination of galunisertib with PD-L1 blockade resulted in improved tumor growth inhibition and complete regressions in colon carcinoma models, demonstrating the potential synergy when cotargeting TGFß and PD-1/PD-L1 pathways. Combination therapy was associated with enhanced anti-tumor immune related gene expression profile that was accelerated compared to anti-PD-L1 monotherapy. CONCLUSIONS: Together these data highlight the ability of galunisertib to modulate T cell immunity and the therapeutic potential of combining galunisertib with current PD-1/L1 immunotherapy.

Systematic Modeling and Design Evaluation of Unperturbed Tumor Dynamics in Xenografts.

Xenograft mice are largely used to evaluate the efficacy of oncological drugs during preclinical phases of drug discovery and development. Mathematical models provide a useful tool to quantitatively characterize tumor growth dynamics and also optimize upcoming experiments. To the best of our knowledge, this is the first report where unperturbed growth of a large set of tumor cell lines (n = 28) has been systematically analyzed using a previously proposed model of nonlinear mixed effects (NLME). Exponential growth was identified as the governing mechanism in the majority of the cell lines, with constant rate values ranging from 0.0204 to 0.203 day-1 No common patterns could be observed across tumor types, highlighting the importance of combining information from different cell lines when evaluating drug activity. Overall, typical model parameters were precisely estimated using designs in which tumor size measurements were taken every 2 days. Moreover, reducing the number of measurements to twice per week, or even once per week for cell lines with low growth rates, showed little impact on parameter precision. However, a sample size of at least 50 mice is needed to accurately characterize parameter variability (i.e., relative S.E. values below 50%). This work illustrates the feasibility of systematically applying NLME models to characterize tumor growth in drug discovery and development, and constitutes a valuable source of data to optimize experimental designs by providing an a priori sampling window and minimizing the number of samples required.

The CDK4/6 Inhibitor Abemaciclib Induces a T Cell Inflamed Tumor Microenvironment and Enhances the Efficacy of PD-L1 Checkpoint Blockade.

Abemaciclib, an inhibitor of cyclin dependent kinases 4 and 6 (CDK4/6), has recently been approved for the treatment of hormone receptor-positive breast cancer. In this study, we use murine syngeneic tumor models and in vitro assays to investigate the impact of abemaciclib on T cells, the tumor immune microenvironment and the ability to combine with anti-PD-L1 blockade. Abemaciclib monotherapy resulted in tumor growth delay that was associated with an increased T cell inflammatory signature in tumors. Combination with anti-PD-L1 therapy led to complete tumor regressions and immunological memory, accompanied by enhanced antigen presentation, a T cell inflamed phenotype, and enhanced cell cycle control. In vitro, treatment with abemaciclib resulted in increased activation of human T cells and upregulated expression of antigen presentation genes in MCF-7 breast cancer cells. These data collectively support the clinical investigation of the combination of abemaciclib with agents such as anti-PD-L1 that modulate T cell anti-tumor immunity.

Preclinical assessment of galunisertib (LY2157299 monohydrate), a first-in-class transforming growth factor-ß receptor type I inhibitor.

Transforming growth factor-ß (TGFß) is an important driver of tumor growth via intrinsic and extrinsic mechanisms, and is therefore an attractive target for developing cancer therapeutics. Using preclinical models, we characterized the anti-tumor activity of a small molecule inhibitor of TGFß receptor I (TGFßRI), galunisertib (LY2157299 monohydrate). Galunisertib demonstrated potent and selective inhibition of TGFßRI with corresponding inhibition of downstream signaling via inhibition of SMAD phosphorylation (pSMAD). Galunisertib also inhibited TGFß-induced pSMAD in vivo, which enabled a pharmacokinetic/pharmacodynamic profile in Calu6 and EMT6-LM2 tumors. Galunisertib demonstrated anti-tumor activity including inhibition of tumor cell migration and mesenchymal phenotype, reversal of TGFß-mediated immune-suppression, and tumor growth delay. A concentration-effect relationship was established with a dosing schedule to achieve the optimal level of target modulation. Finally, a rat model demonstrated a correlation between galunisertib-dependent inhibition of pSMAD in tumor tissues and in PBMCs, supporting the use of PBMCs for assessing pharmacodynamic effects. Galunisertib has been tested in several clinical studies with evidence of anti-tumor activity observed in subsets of patients. Here, we demonstrate that galunisertib inhibits a number of TGFß-dependent functions leading to anti-tumor activity. The enhanced understanding of galunisertib provides rationale for further informed clinical development of TGFß pathway inhibitors.

Predicting tumour growth and its impact on survival in gemcitabine-treated patients with advanced pancreatic cancer.

The aim of this evaluation was to characterize the impact of the tumour size (TS) effects driven by the anticancer drug gemcitabine on overall survival (OS) in patients with advanced pancreatic cancer by building and validating a predictive semi-mechanistic joint TS-OS model. TS and OS data were obtained from one phase II and one phase III study where gemcitabine was administered (1000-1250 mg/kg over 30-60 min i.v infusion) as single agent to patients (n = 285) with advanced pancreatic cancer. Drug exposure, TS and OS were linked using the population approach with NONMEM 7.3. Pancreatic tumour progression was characterized by exponential growth (doubling time = 67 weeks), and tumour response to treatment was described as a function of the weekly area under the gemcitabine triphosphate concentration vs time curve (AUC), including treatment-related resistance development. The typical predicted percentage of tumour growth inhibition with respect to no treatment was 22.3% at the end of 6 chemotherapy cycles. Emerging resistance elicited a 57% decrease in drug effects during the 6th chemotherapy cycle. Predicted TS profile was identified as main prognostic factor of OS, with tumours responders' profiles improving median OS by 30 weeks compared to stable-disease TS profiles. Results of NCT00574275 trial were predicted using this modelling framework, thereby validating the approach as a prediction tool in clinical development. Our analyses show that despite the advanced stage of the disease in this patient population, the modelling framework herein can be used to predict the likelihood of treatment success using early clinical data.

Genomic Aberrations that Activate D-type Cyclins Are Associated with Enhanced Sensitivity to the CDK4 and CDK6 Inhibitor Abemaciclib.

Most cancers preserve functional retinoblastoma (Rb) and may, therefore, respond to inhibition of D-cyclin-dependent Rb kinases, CDK4 and CDK6. To date, CDK4/6 inhibitors have shown promising clinical activity in breast cancer and lymphomas, but it is not clear which additional Rb-positive cancers might benefit from these agents. No systematic survey to compare relative sensitivities across tumor types and define molecular determinants of response has been described. We report a subset of cancers highly sensitive to CDK4/6 inhibition and characterized by various genomic aberrations known to elevate D-cyclin levels and describe a recurrent CCND1 3'UTR mutation associated with increased expression in endometrial cancer. The results suggest multiple additional classes of cancer that may benefit from CDK4/6-inhibiting drugs such as abemaciclib.

Mouse PDX Trial Suggests Synergy of Concurrent Inhibition of RAF and EGFR in Colorectal Cancer with BRAF or KRAS Mutations.

Purpose: To evaluate the antitumor efficacy of cetuximab in combination with LSN3074753, an analog of LY3009120 and pan-RAF inhibitor in 79 colorectal cancer patient-derived xenograft (PDX) models.Experimental Design: Seventy-nine well-characterized colorectal cancer PDX models were employed to conduct a single mouse per treatment group (n = 1) trial.Results: Consistent with clinical results, cetuximab was efficacious in wild-type KRAS and BRAF PDX models, with an overall response rate of 6.3% and disease control rate (DCR) of 20.3%. LSN3074753 was active in a small subset of PDX models that harbored KRAS or BRAF mutations. However, the combination treatment displayed the enhanced antitumor activity with DCR of 35.4%. Statistical analysis revealed that BRAF and KRAS mutations were the best predictors of the combinatorial activity and were significantly associated with synergistic effect with a P value of 0.01 compared with cetuximab alone. In 12 models with BRAF mutations, the combination therapy resulted in a DCR of 41.7%, whereas either monotherapy had a DCR of 8.3%. Among 44 KRAS mutation models, cetuximab or LSN3074753 monotherapy resulted in a DCR of 13.6% or 11.4%, respectively, and the combination therapy increased DCR to 34.1%. Molecular analysis suggests that EGFR activation is a potential feedback and resistant mechanism of pan-RAF inhibition.Conclusions: MAPK and EGFR pathway activations are two major molecular hallmarks of colorectal cancer. This mouse PDX trial recapitulated clinical results of cetuximab. Concurrent EGFR and RAF inhibition demonstrated synergistic antitumor activity for colorectal cancer PDX models with a KRAS or BRAF mutation. Clin Cancer Res; 23(18); 5547-60. ©2017 AACR.

Characterizing Gemcitabine Effects Administered as Single Agent or Combined with Carboplatin in Mice Pancreatic and Ovarian Cancer Xenografts: A Semimechanistic Pharmacokinetic/Pharmacodynamics Tumor Growth-Response Model.

In this work, a semimechanistic tumor growth-response model for gemcitabine in pancreatic (administered as single agent) and ovarian (given as single agent and in combination with carboplatin) cancer in mice was developed. Tumor profiles were obtained from nude mice, previously inoculated with KP4, ASPC1, MIA PACA2, PANC1 (pancreas), A2780, or SKOV3×luc (ovarian) cell lines, and then treated with different dosing schedules of gemcitabine and/or carboplatin. Data were fitted using the population approach with Nonlinear Mixed Effect Models 7.2. In addition to cell proliferation, the tumor progression model for both types of cancer incorporates a carrying capacity representing metabolite pool for DNA synthesis required to tumor growth. Analysis of data from the treated groups revealed that gemcitabine exerted its tumor effects by promoting apoptosis as well as decreasing the carrying capacity compartment. Pharmacodynamic parameters were cell-specific and overall had similar range values between cancer types. In pancreas, a linear model was used to describe both gemcitabine effects with parameter values between 3.26 × 10-2 and 4.2 × 10-1 L/(mg × d). In ovarian cancer, the apoptotic effect was driven by an EMAX model with an efficacy/potency ratio of 5.25-8.65 L/(mg × d). The contribution of carboplatin to tumor effects was lower than the response exerted by gemcitabine and was incorporated in the model as an inhibition of the carrying capacity. The model developed was consistent in its structure across different tumor cell lines and two tumor types where gemcitabine is approved. Simulation-based evaluation diagnostics showed that the model performed well in all experimental design scenarios, including dose, schedule, and tumor type.

Characterization of LY3023414, a Novel PI3K/mTOR Dual Inhibitor Eliciting Transient Target Modulation to Impede Tumor Growth.

The PI3K/AKT/mTOR pathway is among the most frequently altered pathways in cancer cell growth and survival. LY3023414 is a complex fused imidazoquinolinone with high solubility across a wide pH range designed to inhibit class I PI3K isoforms and mTOR kinase. Here, we describe the in vitro and in vivo activity of LY3023414. LY3023414 was highly soluble at pH 2-7. In biochemical testing against approximately 266 kinases, LY3023414 potently and selectively inhibited class I PI3K isoforms, mTORC1/2, and DNA-PK at low nanomolar concentrations. In vitro, inhibition of PI3K/AKT/mTOR signaling by LY3023414 caused G1 cell-cycle arrest and resulted in broad antiproliferative activity in cancer cell panel screens. In vivo, LY3023414 demonstrated high bioavailability and dose-dependent dephosphorylation of PI3K/AKT/mTOR pathway downstream substrates such as AKT, S6K, S6RP, and 4E-BP1 for 4 to 6 hours, reflecting the drug's half-life of 2 hours. Of note, equivalent total daily doses of LY3023414 given either once daily or twice daily inhibited tumor growth to similar extents in multiple xenograft models, indicating that intermittent target inhibition is sufficient for antitumor activity. In combination with standard-of-care drugs, LY3023414 demonstrated additive antitumor activity. The novel, orally bioavailable PI3K/mTOR inhibitor LY3023414 is highly soluble and exhibits potent in vivo efficacy via intermittent target inhibition. It is currently being evaluated in phase I and II trials for the treatment of human malignancies. Mol Cancer Ther; 15(10); 2344-56. ©2016 AACR.

Assay Establishment and Validation of a High-Throughput Screening Platform for Three-Dimensional Patient-Derived Colon Cancer Organoid Cultures.

The application of patient-derived three-dimensional culture systems as disease-specific drug sensitivity models has enormous potential to connect compound screening and clinical trials. However, the implementation of complex cell-based assay systems in drug discovery requires reliable and robust screening platforms. Here we describe the establishment of an automated platform in 384-well format for three-dimensional organoid cultures derived from colon cancer patients. Single cells were embedded in an extracellular matrix by an automated workflow and subsequently self-organized into organoid structures within 4 days of culture before being exposed to compound treatment. We performed validation of assay robustness and reproducibility via plate uniformity and replicate-experiment studies. After assay optimization, the patient-derived organoid platform passed all relevant validation criteria. In addition, we introduced a streamlined plate uniformity study to evaluate patient-derived colon cancer samples from different donors. Our results demonstrate the feasibility of using patient-derived tumor samples for high-throughput assays and their integration as disease-specific models in drug discovery.