Model-Informed Approaches and Innovative Clinical Trial Design for Adeno-Associated Viral Vector-Based Gene Therapy Product Development: A White Paper

The promise of viral vector-based gene therapy (GT) as a transformative paradigm for treating severely debilitating and life-threatening diseases is slowly coming to fruition with the recent approval of several drug products. However, they have a unique mechanism of action often necessitating a tortuous clinical development plan. Expertise in such complex therapeutic modality is still fairly limited in this emerging class of adeno-associated virus (AAV) vector-based gene therapies. Because of the irreversible mode of action and incomplete understanding of genotype-phenotype relationship and disease progression in rare diseases careful considerations should be given to GT product's benefit-risk profile. In particular, special attention needs to be paid to safe dose selection, reliable dose exposure response (including clinically relevant endpoints), or creative approaches in study design targeting small patient populations during clinical development. We believe that quantitative tools encompassed within model-informed drug development (MIDD) framework fits quite well in the development of such novel therapies, as they enable us to benefit from the totality of data approach in order to support dose selection as well as optimize clinical trial designs, end point selection, and patient enrichment. In this thought leadership paper, we provide our collective experiences, identify challenges, and suggest areas of improvement in applications of modeling and innovative trial design in development of AAV-based GT products and reflect on the challenges and opportunities for incorporating MIDD tools and more in rational development of these products.

Current practices for QSP model assessment: an IQ consortium survey

Quantitative Systems Pharmacology (QSP) modeling is increasingly applied in the pharmaceutical industry to influence decision making across a wide range of stages from early discovery to clinical development to post-marketing activities. Development of standards for how these models are constructed, assessed, and communicated is of active interest to the modeling community and regulators but is complicated by the wide variability in the structures and intended uses of the underlying models and the diverse expertise of QSP modelers. With this in mind, the IQ Consortium conducted a survey across the pharmaceutical/biotech industry to understand current practices for QSP modeling. This article presents the survey results and provides insights into current practices and methods used by QSP practitioners based on model type and the intended use at various stages of drug development. The survey also highlights key areas for future development including better integration with statistical methods, standardization of approaches towards virtual populations, and increased use of QSP models for late-stage clinical development and regulatory submissions.

A microfluidic system that replicates pharmacokinetic (PK) profiles in vitro improves prediction of in vivo efficacy in preclinical models

Test compounds used on in vitro model systems are conventionally delivered to cell culture wells as fixed concentration bolus doses; however, this poorly replicates the pharmacokinetic (PK) concentration changes seen in vivo and reduces the predictive value of the data. Herein, proof-of-concept experiments were performed using a novel microfluidic device, the Microformulator, which allows in vivo like PK profiles to be applied to cells cultured in microtiter plates and facilitates the investigation of the impact of PK on biological responses. We demonstrate the utility of the device in its ability to reproduce in vivo PK profiles of different oncology compounds over multiweek experiments, both as monotherapy and drug combinations, comparing the effects on tumour cell efficacy in vitro with efficacy seen in in vivo xenograft models. In the first example, an ERK1/2 inhibitor was tested using fixed bolus dosing and Microformulator-replicated PK profiles, in 2 cell lines with different in vivo sensitivities. The Microformulator-replicated PK profiles were able to discriminate between cell line sensitivities, unlike the conventional fixed bolus dosing. In a second study, murine in vivo PK profiles of multiple Poly(ADP-Ribose) Polymerase 1/2 (PARP) and DNA-dependent protein kinase (DNA-PK) inhibitor combinations were replicated in a FaDu cell line resulting in a reduction in cell growth in vitro with similar rank ordering to the in vivo xenograft model. Additional PK/efficacy insight into theoretical changes to drug exposure profiles was gained by using the Microformulator to expose FaDu cells to the DNA-PK inhibitor for different target coverage levels and periods of time. We demonstrate that the Microformulator enables incorporating PK exposures into cellular assays to improve in vitro-in vivo translation understanding for early therapeutic insight.

Quantitative Evaluation of Dendritic Nanoparticles in Mice: Biodistribution Dynamics and Downstream Tumor Efficacy Outcomes

A physiologically based pharmacokinetic model was developed to describe the tissue distribution kinetics of a dendritic nanoparticle and its conjugated active pharmaceutical ingredient (API) in plasma, liver, spleen, and tumors. Tumor growth data from MV-4-11 tumor-bearing mice were incorporated to investigate the exposure/efficacy relationship. The nanoparticle demonstrated improved antitumor activity compared to the conventional API formulation, owing to the extended released API concentrations at the site of action. Model simulations further enabled the identification of critical parameters that influence API exposure in tumors and downstream efficacy outcomes upon nanoparticle administration. The model was utilized to explore a range of dosing schedules and their effect on tumor growth kinetics, demonstrating the improved antitumor activity of nanoparticles with less frequent dosing compared to the same dose of naked APIs in conventional formulations.

AZD0364 Is a Potent and Selective ERK1/2 Inhibitor That Enhances Antitumor Activity in KRAS-Mutant Tumor Models when Combined with the MEK Inhibitor, Selumetinib

The RAS-regulated RAF-MEK1/2-ERK1/2 (RAS/MAPK) signaling pathway is a major driver in oncogenesis and is frequently dysregulated in human cancers, primarily by mutations in BRAF or RAS genes. The clinical benefit of inhibitors of this pathway as single agents has only been realized in BRAF-mutant melanoma, with limited effect of single-agent pathway inhibitors in KRAS-mutant tumors. Combined inhibition of multiple nodes within this pathway, such as MEK1/2 and ERK1/2, may be necessary to effectively suppress pathway signaling in KRAS-mutant tumors and achieve meaningful clinical benefit. Here, we report the discovery and characterization of AZD0364, a novel, reversible, ATP-competitive ERK1/2 inhibitor with high potency and kinase selectivity. In vitro, AZD0364 treatment resulted in inhibition of proximal and distal biomarkers and reduced proliferation in sensitive BRAF-mutant and KRAS-mutant cell lines. In multiple in vivo xenograft models, AZD0364 showed dose- and time-dependent modulation of ERK1/2-dependent signaling biomarkers resulting in tumor regression in sensitive BRAF- and KRAS-mutant xenografts. We demonstrate that AZD0364 in combination with the MEK1/2 inhibitor, selumetinib (AZD6244 and ARRY142886), enhances efficacy in KRAS-mutant preclinical models that are moderately sensitive or resistant to MEK1/2 inhibition. This combination results in deeper and more durable suppression of the RAS/MAPK signaling pathway that is not achievable with single-agent treatment. The AZD0364 and selumetinib combination also results in significant tumor regressions in multiple KRAS-mutant xenograft models. The combination of ERK1/2 and MEK1/2 inhibition thereby represents a viable clinical approach to target KRAS-mutant tumors.

AZD4320, A Dual Inhibitor of Bcl-2 and Bcl-xL, Induces Tumor Regression in Hematologic Cancer Models without Dose-limiting Thrombocytopenia

PURPOSE

Targeting Bcl-2 family members upregulated in multiple cancers has emerged as an important area of cancer therapeutics. While venetoclax, a Bcl-2-selective inhibitor, has had success in the clinic, another family member, Bcl-x_L, has also emerged as an important target and as a mechanism of resistance. Therefore, we developed a dual Bcl-2/Bcl-x_L inhibitor that broadens the therapeutic activity while minimizing Bcl-x_L-mediated thrombocytopenia.

EXPERIMENTAL DESIGN

We used structure-based chemistry to design a small-molecule inhibitor of Bcl-2 and Bcl-x_L and assessed the activity against in vitro cell lines, patient samples, and in vivo models. We applied pharmacokinetic/pharmacodynamic (PK/PD) modeling to integrate our understanding of on-target activity of the dual inhibitor in tumors and platelets across dose levels and over time.

RESULTS

We discovered AZD4320, which has nanomolar affinity for Bcl-2 and Bcl-x_L, and mechanistically drives cell death through the mitochondrial apoptotic pathway. AZD4320 demonstrates activity in both Bcl-2- and Bcl-x_L-dependent hematologic cancer cell lines and enhanced activity in acute myeloid leukemia (AML) patient samples compared with the Bcl-2-selective agent venetoclax. A single intravenous bolus dose of AZD4320 induces tumor regression with transient thrombocytopenia, which recovers in less than a week, suggesting a clinical weekly schedule would enable targeting of Bcl-2/Bcl-x_L-dependent tumors without incurring dose-limiting thrombocytopenia. AZD4320 demonstrates monotherapy activity in patient-derived AML and venetoclax-resistant xenograft models.

CONCLUSIONS

AZD4320 is a potent molecule with manageable thrombocytopenia risk to explore the utility of a dual Bcl-2/Bcl-x_L inhibitor across a broad range of tumor types with dysregulation of Bcl-2 prosurvival proteins.

Multiscale Model Identifies Improved Schedule for Treatment of Acute Myeloid Leukemia In Vitro With the Mcl-1 Inhibitor AZD5991

Anticancer efficacy is driven not only by dose but also by frequency and duration of treatment. We describe a multiscale model combining cell cycle, cellular heterogeneity of B‐cell lymphoma 2 family proteins, and pharmacology of AZD5991, a potent small‐molecule inhibitor of myeloid cell leukemia 1 (Mcl‐1). The model was calibrated using in vitro viability data for the MV‐4‐11 acute myeloid leukemia cell line under continuous incubation for 72 hours at concentrations of 0.03–30 μM. Using a virtual screen, we identified two schedules as having significantly different predicted efficacy and showed experimentally that a “short” schedule (treating cells for 6 of 24 hours) is significantly better able to maintain the rate of cell kill during treatment than a “long” schedule (18 of 24 hours). This work suggests that resistance can be driven by heterogeneity in protein expression of Mcl‐1 alone without requiring mutation or resistant subclones and demonstrates the utility of mathematical models in efficiently identifying regimens for experimental exploration.

Abstract 56: AZD0466, a nanomedicine of a potent dual Bcl-2/Bcl-xL inhibitor, exhibits anti-tumor activity in a range of hematological and solid tumor models

The induction of apoptosis in tumor cells represents a promising approach to the treatment of cancer. In tumor cells, the B cell lymphoma 2 (Bcl-2) protein family promotes cell survival through upregulation of anti-apoptotic Bcl-2 proteins, such as Bcl-2, Bcl-xL, Mcl-1 and Bcl-w. Clinical activity of the Bcl-2 inhibitor venetoclax has validated the approach of targeting this class of molecules, but additional value remains in jointly targeting Bcl-2 with other family members. AZD0466 is a novel drug-dendrimer conjugate, where the active moiety, AZD4320, is chemically conjugated to Starpharma's DEP® dendrimer platform, a 5-generation PEGylated poly-lysine dendrimer via a hydrolytically labile linker. AZD4320 is a potent dual Bcl-2/Bcl-xL inhibitor, with nanomolar affinity for both proteins1. AZD0466 has been optimized to maintain efficacy whilst mitigating anticipated on-target toxicities of AZD4320. The active moiety, AZD4320, was profiled in an unbiased 72 h cell proliferation screen of 764 cancer cell lines. The greatest degree of sensitivity to AZD4320 (IC50 value ≤0.1 µM) was observed in hematological and small cell lung cancer (SCLC) cell lines. AZD0466 demonstrated greater monotherapy activity than platinum/etoposide chemotherapy regimen or venetoclax monotherapy in 6 out of 11 SCLC PDX models. AZD0466 was also evaluated at different doses in the RS4;11 B-ALL xenograft model. Weekly intravenous dose of AZD0466 resulted in complete tumor regression at 34 and 103 mg/kg doses. Administration of a single dose of AZD0466 produced dose dependent induction of cleaved caspase 3 in tumors as measured by MSD ELISA, which was consistent with the concentrations of released AZD4320 measured in the tumor. All treatments were well tolerated. Anti-tumor activity of AZD0466 was also evaluated in the disseminated luciferase-tagged Ri-1-DLBCL tumor model. AZD0466 dosed weekly IV at 34 mg/kg showed approximately 82% inhibition of bioluminescence compared to vehicle treated animals, whereas 103 mg/kg and 340 mg/kg showed complete inhibition of bioluminescence. In the SUDHL-4 GCB DLBCL model, 103 mg/kg AZD0466 with 10 mg/kg Rituximab resulted in complete and durable regressions in 5/6 animals. Finally, combination of 103 mg/kg AZD0466 with 12.5 mg/kg BID Acalabrutinib, a Bruton's Tyrosine kinase inhibitor, was investigated in OCI-LY10 DLBCL model. While neither agent showed any demonstrable monotherapy activity the combination resulted in complete regressions in 8/8 mice in this model. These data show that AZD0466 has monotherapy activity and a differentiated response from Venetoclax in SCLC models. AZD0466 also has therapeutic potential as monotherapy and a combinatorial agent to increase the depth and duration of response to standard of care and BTK inhibitors in hematological tumors. 1Cidado, J; et al. AACR (2018)

Citation Format: Srividya B. Balachander, Areya Tabatabai, Shenghua Wen, Francis D. Gibbons, Giulia Fabbri, Guangnong Sunny Zhang, Justin Cidado, Lorraine Graham, Marianne Ashford, Barry Davies. AZD0466, a nanomedicine of a potent dual Bcl-2/Bcl-xL inhibitor, exhibits anti-tumor activity in a range of hematological and solid tumor models [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 56.

Abstract 1718: Design and optimization of a dendrimer-conjugated dual Bcl-2/Bcl-xL inhibitor, AZD0466, with improved therapeutic index

Dual Bcl-2/Bcl-xL inhibitors are expected to deliver therapeutic benefit in many hematological and solid tumors, but their clinical application has been limited by tolerability issues, including thrombocytopenia. AZD4320, a potent dual Bcl-2/Bcl-xL inhibitor, showed good efficacy but encountered dose limiting cardiovascular toxicity in preclinical species, and had challenging physicochemical properties which prevented its clinical development. Nanocarriers can provide prolonged circulation time, controlled release, tumor accumulation and retention. Consequently, they have been explored to improve the therapeutic index of small molecules in oncology. This work describes the design and development of AZD0466, a novel drug-dendrimer conjugate, where AZD4320 is chemically conjugated to Starpharma's DEP® dendrimer platform, a 5-generation PEGylated poly-lysine dendrimer via a hydrolytically labile linker. Release of AZD4320 is through hydrolytic cleavage of the linker, which is characterized by a “release half-life”, defined as the time to release 50% of the active moiety. This release half-life can be modified through linker design.

Initially, three drug-dendrimer conjugates with a range of AZD4320 release half-lives (from 1.7 h to 217 h) were synthesized and efficacy was investigated in C.B-17 SCID mice bearing RS4;11 tumors while cardiovascular parameters and tolerance were assessed in a telemetered rat model. A mathematical model was developed and used to optimize the desired release rate of the active moiety, AZD4320, from the dendrimer conjugate for maximal therapeutic index in terms of preclinical anti-tumor efficacy and cardiovascular profile. Based on this modeling, AZD0466, with a release half-life of 25.5 h, was synthesized and selected for further in vivo efficacy and tolerability assessment.

Efficacy studies in the RS4;11 xenograft model showed similar efficacy to AZD4320, while cardiovascular studies in rat and dog demonstrated that AZD0466 was tolerated at doses of active-moiety that are more than ten-fold higher. In addition, it can be easily formulated for intravenous administration due to significantly enhanced solubility.

The AZD4320-dendrimer conjugate, AZD0466, identified in this study has resulted in an improved therapeutic index and enabled progression of this promising Bcl-2/Bcl-xL inhibitor into clinical development.

Citation Format: Marianne B. Ashford, Srividya B. Balachander, Lorraine Graham, Iain Grant, Francis D. Gibbons, Kathryn J. Hill, Alexander R. Harmer, Sonya Gales, Sean Redmond, Brian Kelly, William McCoull, Shenghua Wen, Martin Wild, Eric Gangl, David J. Owen, Barry R. Davies. Design and optimization of a dendrimer-conjugated dual Bcl-2/Bcl-xL inhibitor, AZD0466, with improved therapeutic index [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1718.

Abstract 311: AZD4320 is a potent, dual Bcl-2/xLinhibitor that rapidly induces apoptosis in preclinical hematologic tumor models

Apoptosis is a normal cellular process that is regulated by the dynamic interaction of pro- and anti-apoptotic proteins of the B-cell lymphoma 2 (Bcl-2) family. Cancers, however, have evolved mechanisms to hijack this process and tip the balance in favor of anti-apoptotic proteins, conferring a survival advantage for tumor cells as well as a means of resistance to anti-cancer therapies. Indeed, the Bcl-2 family are some of the most frequently amplified genes and over-expressed proteins across various tumor types. As a result, tumor cells can become addicted to Bcl-2 family members and, hence, vulnerable to targeted BH3 mimetics. Clinical validation of this concept has been demonstrated by venetoclax with its approval for treatment of R/R CLL patients with 17p deletion. Given the great potential that directly targeting the apoptotic machinery holds in treating cancer, developing BH3 mimetics is an attractive proposition.

To that end, we have developed a potent small molecule, AZD4320,1 that has nanomolar affinity for Bcl-2 and Bcl-xL, similar to navitoclax, but has physicochemical properties suitable for IV administration. This will help mitigate toxicities observed with oral administration of navitoclax (e.g. allow recovery of platelets), thus improving therapeutic index. AZD4320 also displays the hallmarks of a bona fide BH3 mimetic, most notably the ability to disrupt the complex formation of Bcl-2 with BH3-only proteins and the necessity for intact BAK and BAX to propagate the apoptotic cascade. A kinetic study was also conducted to explore apoptosis induction in the Bcl-2-addicted B-ALL cell line, RS4;11, which revealed both a dose- and time-dependent increase in cleaved caspase-3 (CC3) and corresponding reduction in cell viability. In an expanded panel of human cancer cell lines, AZD4320 rapidly induced CC3 (6h) and loss of viability (24h) in a diverse set of hematological lines with a median EC50 of 182nM. Solid tumor cell lines, however, were much less responsive (median EC50 >30μM). A comparison to venetoclax from the same cell line panel screen revealed that many more hematological tumor cell lines were sensitive to AZD4320, highlighting the utility and promise of a dual Bcl-2/xL inhibitor. Furthermore, in a venetoclax-resistant derived ABC-DLBCL cell line, AZD4320 was equally potent when compared to the parental cell line whereas venetoclax exhibited a >20-fold reduction in activity. Lastly, for in vivo efficacy studies with RS4;11 xenograft tumors, regressions with corresponding induction of CC3 were observed following a single dose of AZD4320.

Together, these results highlight the therapeutic potential of a dual Bcl-2/xL inhibitor to be used as a foundation therapy across a broad range of hematological tumor types as well as combat resistance to other BH3 mimetics and targeted therapies.

1Hennessy, E; et al. ACS National Meeting 24 (2015).

Citation Format: Justin Cidado, J Paul Secrist, Francis D. Gibbons, Edward J. Hennessy, Stephanos Ioannidis, Edwin A. Clark. AZD4320 is a potent, dual Bcl-2/xLinhibitor that rapidly induces apoptosis in preclinical hematologic tumor models [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 311.

Abstract 4913: A PK/PD model quantitatively describes inhibition and down-regulation of p90RSK by ERK inhibitor AZD0364

ERK1/2 is a key protein in the MAPK pathway, regulating phenotypes such as proliferation and migration. Upstream mutations (e.g., KRAS mutations in non-small-cell lung (NSCLC)) can cause the pathway to become constitutively activated, driving tumor growth. AZD0364 is a potent, selective inhibitor of ERK's kinase activity against its cytosolic substrate p90RSK. It is currently in preclinical development, where it has shown dose-dependent, anti-tumor activity in xenograft models of KRAS-mutant NSCLC, including Calu-6 (where it shows regression) and A549. Treatment with AZD0364 demonstrates rapid and near-complete inhibition of phospho-p90RSK. In addition, prolonged inhibition with AZD0364 causes a gradual downregulation of p90RSK protein over time, without any corresponding change in p90RSK mRNA. Here we present a pharmacokinetic/pharmacodynamic (PK/PD) model that links AZD0364 concentration to inhibition of ERK activity through both a direct inhibition of phospho-p90RSK and an indirect down-regulation of total-p90RSK protein. Anti-proliferative and pro-apoptotic effects on efficacy are linked to changes in p90RSK. The model leads to two key implications (i) repeated dosing will cause apparent potency to improve over time, since the pool of available substrate (i.e., p90RSK) is itself being reduced and (ii) recovery of signaling to baseline will depend not on washout of the inhibitor but on protein synthesis rates. Protein half-lives appear quite different between tumor models of KRAS-mutant NSCLC, with A549 (~20h) significantly slower than Calu-6 (~4h). The model provides a conceptual framework on which to link the timescale of PD changes with those seen in efficacy. Taken together, this means that while a new PD steady-state is achieved in Calu-6 in a few days, it also recovers quickly, necessitating constant cover (daily dosing) to drive regression. On the other hand, while A549 is more robust to inhibition, and slower to reach steady-state inhibition (~2 weeks), it is also slower to recover, so that intermittent schedules can achieve efficacy similar to those achievable with daily dosing.

Citation Format: Francis D. Gibbons, Linda Sandin, Lyndsey Hanson, Rebecca Whiteley, Paul Farrington, Nicola Lindsay, Emma Davies, J Elizabeth Pease, Vikki Flemington. A PK/PD model quantitatively describes inhibition and down-regulation of p90RSK by ERK inhibitor AZD0364 [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 4913.

Abstract 3975: Target engagement, thrombocytopenia, and efficacy induced by the dual Bcl2/xL inhibitor AZD4320 are quantitatively linked by a PK/PD model in leukemia xenografts

The proteins Bcl2 and Bcl-xL are often up-regulated in cancer, and hold in check the apoptosis that would normally be initiated by accumulation of the BH3-only proteins Bax and Bak in response to genomic dysregulation. AZD4320 potently disrupts that interaction, initiating the apoptotic cascade in Bcl-2 or Bcl-xL-dependent tumors. Because platelets are known to be dependent on Bcl-xL, thrombocytopenia is an expected on-target effect. AZD4320 was administered at dose levels 0.5-10 mg/kg, both intravenously and extravascularly, to immune-compromised mice inoculated subcutaneously with the RS4;11 model of acute lymphocytic leukemia (ALL). Drug concentrations were measured by liquid chromatography-mass spectrometry (LC-MS) in plasma and tumor. A cleaved-caspase-3 ELISA was used to assess apoptotic activity in the tumor. Parallel efficacy studies, were used to assess tumor growth compared to vehicle, following tumors from initial regression at tolerated doses to regrowth. Tumors were measured using calipers, and tumor volumes computed using an ellipsoid approximation. We present a mini-physiologically based pharmacokinetic/pharmacodynamic (mPBPK/PD) model that links drug concentrations in plasma and tumor to observed caspase activity and efficacy in an integrated manner, across multiple dose levels and schedules. The tumor is modeled as a pool of sensitive cells which can be triggered rapidly by AZD4320 to apoptose, from which point they transition gradually to death, reducing tumor volume. Cleaved caspase-3 is used as a marker of apoptosis, and modeled using a sigmoidal response function with steep slope parameter. In this way, we effectively capture the transient nature of the response, despite AZD4320's long residence in the tumor. Thrombocytopenia is described not as an effect on the megakaryocyte precursors, but as a linear concentration-dependent effect on circulating platelets. Feedback from the circulation to megakaryocytes drives increased production to fill the deficit. Parameters are well-estimated throughout. Together, these components provide a comprehensive means to investigate the effects of dose and schedule with a dual Bcl2/BCL-xL inhibitor.

Citation Format: Francis D. Gibbons, Ammar Adam, Marie-Eve Beaudoin, Eric Gangl, Paul Secrist. Target engagement, thrombocytopenia, and efficacy induced by the dual Bcl2/xL inhibitor AZD4320 are quantitatively linked by a PK/PD model in leukemia xenografts [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 3975.

Abstract 1647: Discovery of AZD0364, a potent and selective oral inhibitor of ERK1/2 that is efficacious in both monotherapy and combination therapy in models of NSCLC

The RAS/MAPK pathway is a major driver in oncogenesis and is dysregulated in approximately 30% of human cancers, primarily by mutations in BRAF or RAS genes. The extracellular-signal-regulated kinases (ERK1 and ERK2) serve as key central nodes within this pathway. The feasibility of targeting the RAS/MAPK pathway has been demonstrated by the initial clinical responses observed to BRAF and MEK inhibitors in BRAF V600E/K metastatic melanoma, however resistance frequently develops by reactivation of the pathway. Direct targeting of ERK1/2, may provide another therapeutic option in tumours with mutations in BRAF or RAS genes. Importantly, ERK1/2 inhibition may have clinical utility in overcoming acquired resistance to RAF and MEK inhibitors where RAS/MAPK pathway reactivation has occurred, such as relapsed BRAF V600E/K melanoma. Starting from our published work,1 we will describe for the first time, a scaffold hopping approach leading to the identification of AZD0364, a pre-clinical ERK1/2 inhibitor candidate drug. Driven by conformational modelling and structure-based design, and by utilising novel sulfamidate ring opening chemistry, a high lipophilicity efficiency core was identified. Structure based, multi-parameter based optimisation of this improved core ultimately led to AZD0364. AZD0364 exhibits high cellular potency against a direct downstream substrate on the MAPK pathway (e.g. inhibition of phospho-p90RSK1 in BRAFV600E mutant A375 cells, IC50 = 6 nM). The molecule is a highly selective kinase inhibitor (10/329 kinases tested are inhibited at >50% at a 1 µM) and has long residence time on the protein (as determined by SPR on human unphosphorylated-ERK2: pKd = 10; t1/2 = 277 mins). The good in vitro potency and selectivity is complemented by excellent physico-chemical properties (maximum absorbable dose estimated to be >4 g) and good oral pharmacokinetics across species, leading to a low predicted dose to man. In xenograft models, AZD0364 inhibits phospho-p90RSK1 in tumors in a dose-dependent manner. AZD0364 induces regressions in the KRAS mutant NSCLC Calu 6 xenograft model. AZD0364 can also be combined safely and effectively with the MEK1/2 inhibitor selumetinib in KRAS mutant NSCLC xenograft models. 1Richard A. Ward et. al. Structure-Guided Discovery of Potent and Selective Inhibitors of ERK1/2 from a Modestly Active and Promiscuous Chemical Start Point, J. Med. Chem. 2017, 60, 3438−3450.

Citation Format: Iain Simpson, Mark J. Anderton, David M. Andrews, Jason Breed, Emma Davies, Judit E. Debreczeni, Vikki Flemington, Francis D. Gibbons, Mark A. Graham, Philip Hopcroft, Tina Howard, Julian Hudson, Clifford D. Jones, Christopher Jones, Nicola Lindsay, J Elizabeth Pease, Philip Rawlins, Karen Roberts, Steve Swallow, Steve St-Gallay, Michael E. Tonge, Richard A. Ward. Discovery of AZD0364, a potent and selective oral inhibitor of ERK1/2 that is efficacious in both monotherapy and combination therapy in models of NSCLC [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 1647.

Abstract 299: A susceptible-quiescent model can describe biphasic cell-kill by MCL1 inhibitor AZD5991 in vitro

AZD5991 is a potent and selective inhibitor of Mcl-1, now in phase 1 clinical development. Mcl-1 is an anti-apoptotic Bcl2-family protein that is up-regulated by cancer cells in order to avoid apoptosis. Disruption of binding of Mcl-1 to pro-apoptotic BH3-only proteins such as Bax and Bak results in loss in cellular viability of several cell-line models of multiple myeloma (MM). As a function of time, many cell lines display a biphasic response, with an initial period of rapid cell kill, followed by a period of slower kill. Such biphasic kill curves are not uncommonly seen in bacteria. As a function of concentration, cell lines display a range of efficacy (extent of cell kill) and potency (concentration of half-maximal cell kill). Here we apply a model originally developed for bacterial cell-kill to parameterize the in vitro cell kill over time and across several orders of magnitude in concentration. Cells from 10 MM cell lines were grown in culture, then plated at uniform density in microtiter plates where they were incubated at concentrations of AZD5991 ranging from 0.3nM to 30µM (with DMSO control), each plate for a duration of 0.5h to 72h. After the desired incubation period, Cell-Titer Glo® was used to assess cellular viability by luminescence. Plates were run in duplicate. A model of cell survival was implemented in MATLAB, in which cells can be in one of two states: a proliferating state ‘S' in which they are susceptible to a saturable concentration-dependent drug-induced cell death, or a quiescent state ‘Q' in which they don't proliferate and have only a constitutive death rate independent of drug concentration. Transition between the two states is possible in either direction. By fitting the model to the data across time and over a wide range of concentrations, we can succinctly and precisely describe the rate of growth and drug-induced cell death, as well as transition between the susceptible and quiescent states. To our knowledge, this represents the first application of such a model to a BH3 mimetic such as AZD5991. We find that the cell lines show much greater variation in efficacy (i.e., maximum inducible cell kill rate) than in potency, suggesting that the main difference between these lines lies in their dependence on Mcl-1 for survival.

Citation Format: Francis D. Gibbons, Matthew Belmonte, Paul Secrist, Alwin Schuller. A susceptible-quiescent model can describe biphasic cell-kill by MCL1 inhibitor AZD5991 in vitro [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 299.

Abstract 302: Selective Mcl-1 inhibition by AZD5991 induces on-target cell death and achieves antitumor activity in multiple myeloma and acute myeloid leukemia

Mcl-1 is a member of the Bcl/Mcl family of proteins that promotes cell survival by preventing induction of apoptosis in a broad range of cancers. High expression of Mcl-1 has been linked to tumor development and resistance to anticancer therapies, underscoring the potential of Mcl-1 inhibitors as anticancer drugs. We have previously shown that AZD5991, a rationally designed macrocycle with sub-nanomolar affinity for Mcl-1 and high selectivity, induces rapid and irreversible commitment to apoptosis in Mcl-1-dependent cancer cells in a manner dependent on proapoptotic BAK. Here, we demonstrate that AZD5991 exhibits cytotoxic activity (GI50<100nM) in various MM and AML cell lines in vitro with an activity profile distinct from the selective Bcl2 inhibitor venetoclax. In vivo, AZD5991 shows potent antitumor activity with complete (100%) tumor regression in several mouse MM and AML xenograft models after a single tolerated dose. AZD5991 shows enhanced efficacy in vivo when combined with standard-of-care agents. Pharmacodynamic studies confirmed that AZD5991 kills cancer cells by activation of the mitochondrial apoptotic pathway. Ex vivo analysis indicates that AZD5991 has single agent activity in primary AML patient samples with LC50 values in the low nanomolar range. Consistent with our findings in AML cell lines, the activity profile for AZD5991 in AML primary samples was distinct from venetoclax, highlighting the unique therapeutic opportunity for AZD5991. Based on these data a phase I clinical trial has been launched for evaluation of AZD5991 in patients with MM and other hematologic malignancies (NCT03218683).

Citation Format: Adriana E. Tron, Matthew A. Belmonte, Steven Criscione, Edwin A. Clark, Eric Gangl, Francis D. Gibbons, Jeffrey W. Tyner, Stephen E. Kurtz, Qing Ye, Alexander W. Hird, Alwin Schuller, J. Paul Secrist. Selective Mcl-1 inhibition by AZD5991 induces on-target cell death and achieves antitumor activity in multiple myeloma and acute myeloid leukemia [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 302.

Mixture dynamics: Combination therapy in oncology

In recent years combination therapies have become increasingly popular in most therapeutic areas. We present a qualitative and quantitative approach and elucidate some of the challenges and solutions to a more optimal therapy. For tumor growth this involves the study of semi-mechanistic cell-growth/kill models with multiple sites of action. We introduce such models and analyze their dynamic properties using simulations and mathematical analysis. This is done for two specific case studies, one involving a single compound and one a combination of two compounds. We generalize the notion of Tumor Static Concentration to cases when two compounds are involved and develop a graphical method for determining the optimal combination of the two compounds, using ideas akin to those used in studies employing isobolograms. In studying the dynamics of the second case study we focus, not only on the different concentrations, but also on the different dosing regimens and pharmacokinetics of the two compounds.

Abstract 3362: Miniaturized PBPK model improves pharmacodynamic characterization and physiological interpretability for compounds with profound hysteresis in tumor

Background:

Significant hysteresis between plasma concentration and target inhibition at the effect site (e.g., tumor) is a frequent observation, commonly described mathematically by connecting the central (i.e., plasma) compartment to an ‘effect compartment’ by a ‘link’ which causes the concentration in the latter to be delayed relative to the plasma. The result is a direct response between effect-compartment concentration and target inhibition. A significant drawback is that the effect compartment cannot be observed (making it impossible to validate) and has no physiological interpretation (rendering communication with other disciplines difficult). We develop a novel approach that is more physiologically meaningful, provides more-precise model parameter estimates, and gives insight into the physico-chemical factors limiting distribution into the tumor.

Method:

We orally administered single doses of several compounds (including Crizotinib, AZD3463, and others) targeting ALK to mice bearing tumors derived from the DEL and H3122 non-small-cell lung cancer line, at several dose levels. At 6, 24, and 48 hours post-dose, we measured the plasma and tumor concentrations of each compound and associated target inhibition (phosphorylated ALK, pALK) in the tumor. pALK inhibition shows a direct response not to plasma, but to tumor concentration, indicating that the delay is distributional in nature. We constructed a miniature physiologically-based pharmacokinetic (mPBPK) model consisting of a central compartment and a tumor of fixed physiological volume. pALK inhibition was modeled as a direct Emax response to tumor concentration. For each compound, we simultaneously fitted the mPBPK model to the naïve-pooled plasma and tumor concentrations, as well as pALK, using all available dose levels. Beyond the standard PK and PD parameters (Emax, E0, IC50) we also fitted the tumor partition constant Kp, and tumor blood flow rate Qt. For comparison, we fitted a standard effect-compartment (‘link’) model to the plasma concentrations and pALK levels to the same data.

Results:

For each compound, we computed unbound EC50 for both effect-compartment and mPBPK models. We found that while the point estimates largely agree, the mPBPK model delivers more-precise estimates (typically 50% lower CV%). We attribute this to its use of additional data (tumor concentration) to constrain the model, which more than compensates for the additional parameters in the mPBPK model. We find that there is broad consistency in estimates of tumor flow rate Qt across the compounds studied, indicating that distribution from plasma to site of action is limited by blood flow, rather than by permeability. Additionally, we found that the greater physiological interpretability of the mPBPK model enhances cross-functional communication within project teams.

Citation Format: Francis D. Gibbons, Dan Widzowski, Minhui Shen, Jane Cheng, Lisa Drew, Jamal C. Saeh, Douglas Ferguson. Miniaturized PBPK model improves pharmacodynamic characterization and physiological interpretability for compounds with profound hysteresis in tumor. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3362. doi:10.1158/1538-7445.AM2013-3362

FuncBase: a resource for quantitative gene function annotation

SUMMARY

Computational gene function prediction can serve to focus experimental resources on high-priority experimental tasks. FuncBase is a web resource for viewing quantitative machine learning-based gene function annotations. Quantitative annotations of genes, including fungal and mammalian genes, with Gene Ontology terms are accompanied by a community feedback system. Evidence underlying function annotations is shown. For example, a custom Cytoscape viewer shows functional linkage graphs relevant to the gene or function of interest. FuncBase provides links to external resources, and may be accessed directly or via links from species-specific databases.

AVAILABILITY

FuncBase as well as all underlying data and annotations are freely available via http://func.med.harvard.edu/

A critical assessment of Mus musculus gene function prediction using integrated genomic evidence

BACKGROUND

Several years after sequencing the human genome and the mouse genome, much remains to be discovered about the functions of most human and mouse genes. Computational prediction of gene function promises to help focus limited experimental resources on the most likely hypotheses. Several algorithms using diverse genomic data have been applied to this task in model organisms; however, the performance of such approaches in mammals has not yet been evaluated.

RESULTS

In this study, a standardized collection of mouse functional genomic data was assembled; nine bioinformatics teams used this data set to independently train classifiers and generate predictions of function, as defined by Gene Ontology (GO) terms, for 21,603 mouse genes; and the best performing submissions were combined in a single set of predictions. We identified strengths and weaknesses of current functional genomic data sets and compared the performance of function prediction algorithms. This analysis inferred functions for 76% of mouse genes, including 5,000 currently uncharacterized genes. At a recall rate of 20%, a unified set of predictions averaged 41% precision, with 26% of GO terms achieving a precision better than 90%.

CONCLUSION

We performed a systematic evaluation of diverse, independently developed computational approaches for predicting gene function from heterogeneous data sources in mammals. The results show that currently available data for mammals allows predictions with both breadth and accuracy. Importantly, many highly novel predictions emerge for the 38% of mouse genes that remain uncharacterized.

An en masse phenotype and function prediction system for Mus musculus

BACKGROUND

Individual researchers are struggling to keep up with the accelerating emergence of high-throughput biological data, and to extract information that relates to their specific questions. Integration of accumulated evidence should permit researchers to form fewer - and more accurate - hypotheses for further study through experimentation.

RESULTS

Here a method previously used to predict Gene Ontology (GO) terms for Saccharomyces cerevisiae (Tian et al.: Combining guilt-by-association and guilt-by-profiling to predict Saccharomyces cerevisiae gene function. Genome Biol 2008, 9(Suppl 1):S7) is applied to predict GO terms and phenotypes for 21,603 Mus musculus genes, using a diverse collection of integrated data sources (including expression, interaction, and sequence-based data). This combined 'guilt-by-profiling' and 'guilt-by-association' approach optimizes the combination of two inference methodologies. Predictions at all levels of confidence are evaluated by examining genes not used in training, and top predictions are examined manually using available literature and knowledge base resources.

CONCLUSION

We assigned a confidence score to each gene/term combination. The results provided high prediction performance, with nearly every GO term achieving greater than 40% precision at 1% recall. Among the 36 novel predictions for GO terms and 40 for phenotypes that were studied manually, >80% and >40%, respectively, were identified as accurate. We also illustrate that a combination of 'guilt-by-profiling' and 'guilt-by-association' outperforms either approach alone in their application to M. musculus.

Combining guilt-by-association and guilt-by-profiling to predict Saccharomyces cerevisiae gene function

Background:

Learning the function of genes is a major goal of computational genomics. Methods for inferring gene function have typically fallen into two categories: 'guilt-by-profiling', which exploits correlation between function and other gene characteristics; and 'guilt-by-association', which transfers function from one gene to another via biological relationships.

Results:

We have developed a strategy ('Funckenstein') that performs guilt-by-profiling and guilt-by-association and combines the results. Using a benchmark set of functional categories and input data for protein-coding genes in Saccharomyces cerevisiae, Funckenstein was compared with a previous combined strategy. Subsequently, we applied Funckenstein to 2,455 Gene Ontology terms. In the process, we developed 2,455 guilt-by-profiling classifiers based on 8,848 gene characteristics and 12 functional linkage graphs based on 23 biological relationships.

Conclusion:

Funckenstein outperforms a previous combined strategy using a common benchmark dataset. The combination of 'guilt-by-profiling' and 'guilt-by-association' gave significant improvement over the component classifiers, showing the greatest synergy for the most specific functions. Performance was evaluated by cross-validation and by literature examination of the top-scoring novel predictions. These quantitative predictions should help prioritize experimental study of yeast gene functions.

Chipper: discovering transcription-factor targets from chromatin immunoprecipitation microarrays using variance stabilization

Chromatin immunoprecipitation combined with microarray technology (Chip2) allows genome-wide determination of protein-DNA binding sites. The current standard method for analyzing Chip2 data requires additional control experiments that are subject to systematic error. We developed methods to assess significance using variance stabilization, learning error-model parameters without external control experiments. The method was validated experimentally, shows greater sensitivity than the current standard method, and incorporates false-discovery rate analysis. The corresponding software ('Chipper') is freely available. The method described here should help reveal an organism's transcription-regulatory 'wiring diagram'.

Towards a proteome-scale map of the human protein-protein interaction network

Systematic mapping of protein-protein interactions, or 'interactome' mapping, was initiated in model organisms, starting with defined biological processes and then expanding to the scale of the proteome. Although far from complete, such maps have revealed global topological and dynamic features of interactome networks that relate to known biological properties, suggesting that a human interactome map will provide insight into development and disease mechanisms at a systems level. Here we describe an initial version of a proteome-scale map of human binary protein-protein interactions. Using a stringent, high-throughput yeast two-hybrid system, we tested pairwise interactions among the products of approximately 8,100 currently available Gateway-cloned open reading frames and detected approximately 2,800 interactions. This data set, called CCSB-HI1, has a verification rate of approximately 78% as revealed by an independent co-affinity purification assay, and correlates significantly with other biological attributes. The CCSB-HI1 data set increases by approximately 70% the set of available binary interactions within the tested space and reveals more than 300 new connections to over 100 disease-associated proteins. This work represents an important step towards a systematic and comprehensive human interactome project.

Genomewide identification of Sko1 target promoters reveals a regulatory network that operates in response to osmotic stress in Saccharomyces cerevisiae

In Saccharomyces cerevisiae, the ATF/CREB transcription factor Sko1 (Acr1) regulates the expression of genes induced by osmotic stress under the control of the high osmolarity glycerol (HOG) mitogen-activated protein kinase pathway. By combining chromatin immunoprecipitation and microarrays containing essentially all intergenic regions, we estimate that yeast cells contain approximately 40 Sko1 target promoters in vivo; 20 Sko1 target promoters were validated by direct analysis of individual loci. The ATF/CREB consensus sequence is not statistically overrepresented in confirmed Sko1 target promoters, although some sites are evolutionarily conserved among related yeast species, suggesting that they are functionally important in vivo. These observations suggest that Sko1 association in vivo is affected by factors beyond the protein-DNA interaction defined in vitro. Sko1 binds a number of promoters for genes directly involved in defense functions that relieve osmotic stress. In addition, Sko1 binds to the promoters of genes encoding transcription factors, including Msn2, Mot3, Rox1, Mga1, and Gat2. Stress-induced expression of MSN2, MOT3, and MGA1 is diminished in sko1 mutant cells, while transcriptional regulation of ROX1 seems to be unaffected. Lastly, Sko1 targets PTP3, which encodes a phosphatase that negatively regulates Hog1 kinase activity, and Sko1 is required for osmotic induction of PTP3 expression. Taken together our results suggest that Sko1 operates a transcriptional network upon osmotic stress, which involves other specific transcription factors and a phosphatase that regulates the key component of the signal transduction pathway.

SILVER helps assign peptides to tandem mass spectra using intensity-based scoring

Tandem mass spectrometry is commonly used to identify peptides (and thereby proteins) that are present in complex mixtures. Peptide identification from tandem mass spectra is partially automated, but still requires human curation to resolve "borderline" peptide-spectrum matches (PSMs). SILVER is web-based software that assists manual curation of tandem mass spectra, using a recently developed intensity-based machine-learning approach to scoring PSMs, Elias et al. In this method, a large training set of peptide, fragment, and peak-intensity properties for both matched and mismatched PSMs was used to develop a score measuring consistency between each predicted fragment ion of a candidate peptide and its corresponding observed spectral peak intensity. The SILVER interface provides a visual representation of match quality between each candidate fragment ion and the observed spectrum, thereby expediting manual curation of tandem mass spectra. SILVER is available online at http://llama.med.harvard.edu/Software.html.

Predicting protein complex membership using probabilistic network reliability

Evidence for specific protein-protein interactions is increasingly available from both small- and large-scale studies, and can be viewed as a network. It has previously been noted that errors are frequent among large-scale studies, and that error frequency depends on the large-scale method used. Despite knowledge of the error-prone nature of interaction evidence, edges (connections) in this network are typically viewed as either present or absent. However, use of a probabilistic network that considers quantity and quality of supporting evidence should improve inference derived from protein networks. Here we demonstrate inference of membership in a partially known protein complex by using a probabilistic network model and an algorithm previously used to evaluate reliability in communication networks.

Intensity-based protein identification by machine learning from a library of tandem mass spectra

Tandem mass spectrometry (MS/MS) has emerged as a cornerstone of proteomics owing in part to robust spectral interpretation algorithms. Widely used algorithms do not fully exploit the intensity patterns present in mass spectra. Here, we demonstrate that intensity pattern modeling improves peptide and protein identification from MS/MS spectra. We modeled fragment ion intensities using a machine-learning approach that estimates the likelihood of observed intensities given peptide and fragment attributes. From 1,000,000 spectra, we chose 27,000 with high-quality, nonredundant matches as training data. Using the same 27,000 spectra, intensity was similarly modeled with mismatched peptides. We used these two probabilistic models to compute the relative likelihood of an observed spectrum given that a candidate peptide is matched or mismatched. We used a 'decoy' proteome approach to estimate incorrect match frequency, and demonstrated that an intensity-based method reduces peptide identification error by 50-96% without any loss in sensitivity.

Judging the quality of gene expression-based clustering methods using gene annotation

We compare several commonly used expression-based gene clustering algorithms using a figure of merit based on the mutual information between cluster membership and known gene attributes. By studying various publicly available expression data sets we conclude that enrichment of clusters for biological function is, in general, highest at rather low cluster numbers. As a measure of dissimilarity between the expression patterns of two genes, no method outperforms Euclidean distance for ratio-based measurements, or Pearson distance for non-ratio-based measurements at the optimal choice of cluster number. We show the self-organized-map approach to be best for both measurement types at higher numbers of clusters. Clusters of genes derived from single- and average-linkage hierarchical clustering tend to produce worse-than-random results.