ARAF mutations confer resistance to the RAF inhibitor belvarafenib in melanoma.

Although RAF monomer inhibitors (type I.5, BRAF(V600)) are clinically approved for the treatment of BRAFV600-mutant melanoma, they are ineffective in non-BRAFV600 mutant cells1-3. Belvarafenib is a potent and selective RAF dimer (type II) inhibitor that exhibits clinical activity in patients with BRAFV600E- and NRAS-mutant melanomas. Here we report the first-in-human phase I study investigating the maximum tolerated dose, and assessing the safety and preliminary efficacy of belvarafenib in BRAFV600E- and RAS-mutated advanced solid tumours (NCT02405065, NCT03118817). By generating belvarafenib-resistant NRAS-mutant melanoma cells and analysing circulating tumour DNA from patients treated with belvarafenib, we identified new recurrent mutations in ARAF within the kinase domain. ARAF mutants conferred resistance to belvarafenib in both a dimer- and a kinase activity-dependent manner. Belvarafenib induced ARAF mutant dimers, and dimers containing mutant ARAF were active in the presence of inhibitor. ARAF mutations may serve as a general resistance mechanism for RAF dimer inhibitors as the mutants exhibit reduced sensitivity to a panel of type II RAF inhibitors. The combination of RAF plus MEK inhibition may be used to delay ARAF-driven resistance and suggests a rational combination for clinical use. Together, our findings reveal specific and compensatory functions for the ARAF isoform and implicate ARAF mutations as a driver of resistance to RAF dimer inhibitors.

PharmacoDB 2.0: improving scalability and transparency of in vitro pharmacogenomics analysis.

Cancer pharmacogenomics studies provide valuable insights into disease progression and associations between genomic features and drug response. PharmacoDB integrates multiple cancer pharmacogenomics datasets profiling approved and investigational drugs across cell lines from diverse tissue types. The web-application enables users to efficiently navigate across datasets, view and compare drug dose-response data for a specific drug-cell line pair. In the new version of PharmacoDB (version 2.0, https://pharmacodb.ca/), we present (i) new datasets such as NCI-60, the Profiling Relative Inhibition Simultaneously in Mixtures (PRISM) dataset, as well as updated data from the Genomics of Drug Sensitivity in Cancer (GDSC) and the Genentech Cell Line Screening Initiative (gCSI); (ii) implementation of FAIR data pipelines using ORCESTRA and PharmacoDI; (iii) enhancements to drug-response analysis such as tissue distribution of dose-response metrics and biomarker analysis; and (iv) improved connectivity to drug and cell line databases in the community. The web interface has been rewritten using a modern technology stack to ensure scalability and standardization to accommodate growing pharmacogenomics datasets. PharmacoDB 2.0 is a valuable tool for mining pharmacogenomics datasets, comparing and assessing drug-response phenotypes of cancer models.

Targeting MCL-1 and BCL-2 with polatuzumab vedotin and venetoclax overcomes treatment resistance in R/R non-Hodgkin lymphoma: Results from preclinical models and a Phase Ib study.

The treatment of patients with relapsed or refractory lymphoid neoplasms represents a significant clinical challenge. Here, we identify the pro-survival BCL-2 protein family member MCL-1 as a resistance factor for the BCL-2 inhibitor venetoclax in non-Hodgkin lymphoma (NHL) cell lines and primary NHL samples. Mechanistically, we show that the antibody-drug conjugate polatuzumab vedotin promotes MCL-1 degradation via the ubiquitin/proteasome system. This targeted MCL-1 antagonism, when combined with venetoclax and the anti-CD20 antibodies obinutuzumab or rituximab, results in tumor regressions in preclinical NHL models, which are sustained even off-treatment. In a Phase Ib clinical trial (NCT02611323) of heavily pre-treated patients with relapsed or refractory NHL, 25/33 (76%) patients with follicular lymphoma and 5/17 (29%) patients with diffuse large B-cell lymphoma achieved complete or partial responses with an acceptable safety profile when treated with the recommended Phase II dose of polatuzumab vedotin in combination with venetoclax and an anti-CD20 antibody.

USP7 small-molecule inhibitors interfere with ubiquitin binding.

The ubiquitin system regulates essential cellular processes in eukaryotes. Ubiquitin is ligated to substrate proteins as monomers or chains and the topology of ubiquitin modifications regulates substrate interactions with specific proteins. Thus ubiquitination directs a variety of substrate fates including proteasomal degradation. Deubiquitinase enzymes cleave ubiquitin from substrates and are implicated in disease; for example, ubiquitin-specific protease-7 (USP7) regulates stability of the p53 tumour suppressor and other proteins critical for tumour cell survival. However, developing selective deubiquitinase inhibitors has been challenging and no co-crystal structures have been solved with small-molecule inhibitors. Here, using nuclear magnetic resonance-based screening and structure-based design, we describe the development of selective USP7 inhibitors GNE-6640 and GNE-6776. These compounds induce tumour cell death and enhance cytotoxicity with chemotherapeutic agents and targeted compounds, including PIM kinase inhibitors. Structural studies reveal that GNE-6640 and GNE-6776 non-covalently target USP7 12 Å distant from the catalytic cysteine. The compounds attenuate ubiquitin binding and thus inhibit USP7 deubiquitinase activity. GNE-6640 and GNE-6776 interact with acidic residues that mediate hydrogen-bond interactions with the ubiquitin Lys48 side chain, suggesting that USP7 preferentially interacts with and cleaves ubiquitin moieties that have free Lys48 side chains. We investigated this idea by engineering di-ubiquitin chains containing differential proximal and distal isotopic labels and measuring USP7 binding by nuclear magnetic resonance. This preferential binding protracted the depolymerization kinetics of Lys48-linked ubiquitin chains relative to Lys63-linked chains. In summary, engineering compounds that inhibit USP7 activity by attenuating ubiquitin binding suggests opportunities for developing other deubiquitinase inhibitors and may be a strategy more broadly applicable to inhibiting proteins that require ubiquitin binding for full functional activity.

Evaluation of statistical approaches for association testing in noisy drug screening data.

BACKGROUND: Identifying associations among biological variables is a major challenge in modern quantitative biological research, particularly given the systemic and statistical noise endemic to biological systems. Drug sensitivity data has proven to be a particularly challenging field for identifying associations to inform patient treatment. RESULTS: To address this, we introduce two semi-parametric variations on the commonly used concordance index: the robust concordance index and the kernelized concordance index (rCI, kCI), which incorporate measurements about the noise distribution from the data. We demonstrate that common statistical tests applied to the concordance index and its variations fail to control for false positives, and introduce efficient implementations to compute p-values using adaptive permutation testing. We then evaluate the statistical power of these coefficients under simulation and compare with Pearson and Spearman correlation coefficients. Finally, we evaluate the various statistics in matching drugs across pharmacogenomic datasets. CONCLUSIONS: We observe that the rCI and kCI are better powered than the concordance index in simulation and show some improvement on real data. Surprisingly, we observe that the Pearson correlation was the most robust to measurement noise among the different metrics.

Reproducible pharmacogenomic profiling of cancer cell line panels.

The use of large-scale genomic and drug response screening of cancer cell lines depends crucially on the reproducibility of results. Here we consider two previously published screens, plus a later critique of these studies. Using independent data, we show that consistency is achievable, and provide a systematic description of the best laboratory and analysis practices for future studies.

Exploration of Pyrrolobenzodiazepine (PBD)-Dimers Containing Disulfide-Based Prodrugs as Payloads for Antibody-Drug Conjugates.

A number of cytotoxic pyrrolobenzodiazepine (PBD) monomers containing various disulfide-based prodrugs were evaluated for their ability to undergo activation (disulfide cleavage) in vitro in the presence of either glutathione (GSH) or cysteine (Cys). A good correlation was observed between in vitro GSH stability and in vitro cytotoxicity toward tumor cell lines. The prodrug-containing compounds were typically more potent against cells with relatively high intracellular GSH levels (e.g., KPL-4 cells). Several antibody-drug conjugates (ADCs) were subsequently constructed from PBD dimers that incorporated selected disulfide-based prodrugs. Such HER2 conjugates exhibited potent antiproliferation activity against KPL-4 cells in vitro in an antigen-dependent manner. However, the disulfide prodrugs contained in the majority of such entities were surprisingly unstable toward whole blood from various species. One HER2-targeting conjugate that contained a thiophenol-derived disulfide prodrug was an exception to this stability trend. It exhibited potent activity in a KPL-4 in vivo efficacy model that was approximately three-fold weaker than that displayed by the corresponding parent ADC. The same prodrug-containing conjugate demonstrated a three-fold improvement in mouse tolerability properties in vivo relative to the parent ADC, which did not contain the prodrug.

Widespread potential for growth-factor-driven resistance to anticancer kinase inhibitors.

Mutationally activated kinases define a clinically validated class of targets for cancer drug therapy. However, the efficacy of kinase inhibitors in patients whose tumours harbour such alleles is invariably limited by innate or acquired drug resistance. The identification of resistance mechanisms has revealed a recurrent theme­the engagement of survival signals redundant to those transduced by the targeted kinase. Cancer cells typically express multiple receptor tyrosine kinases (RTKs) that mediate signals that converge on common critical downstream cell-survival effectors­most notably, phosphatidylinositol-3-OH kinase (PI(3)K) and mitogen-activated protein kinase (MAPK). Consequently, an increase in RTK-ligand levels, through autocrine tumour-cell production, paracrine contribution from tumour stroma or systemic production, could confer resistance to inhibitors of an oncogenic kinase with a similar signalling output. Here, using a panel of kinase-'addicted' human cancer cell lines, we found that most cells can be rescued from drug sensitivity by simply exposing them to one or more RTK ligands. Among the findings with clinical implications was the observation that hepatocyte growth factor (HGF) confers resistance to the BRAF inhibitor PLX4032 (vemurafenib) in BRAF-mutant melanoma cells. These observations highlight the extensive redundancy of RTK-transduced signalling in cancer cells and the potentially broad role of widely expressed RTK ligands in innate and acquired resistance to drugs targeting oncogenic kinases.

Computational modeling of drug response identifies mutant-specific constraints for dosing panRAF and MEK inhibitors in melanoma.

Purpose: This study explores the potential of preclinical in vitro cell line response data and computational modeling in identifying optimal dosage requirements of pan-RAF (Belvarafenib) and MEK (Cobimetinib) inhibitors in melanoma treatment. Our research is motivated by the critical role of drug combinations in enhancing anti-cancer responses and the need to close the knowledge gap around selecting effective dosing strategies to maximize their potential. Results: In a drug combination screen of 43 melanoma cell lines, we identified unique dosage landscapes of panRAF and MEK inhibitors for NRAS vs BRAF mutant melanomas. Both experienced benefits, but with a notably more synergistic and narrow dosage range for NRAS mutant melanoma. Computational modeling and molecular experiments attributed the difference to a mechanism of adaptive resistance by negative feedback. We validated in vivo translatability of in vitro dose-response maps by accurately predicting tumor growth in xenografts. Then, we analyzed pharmacokinetic and tumor growth data from Phase 1 clinical trials of Belvarafenib with Cobimetinib to show that the synergy requirement imposes stricter precision dose constraints in NRAS mutant melanoma patients. Conclusion: Leveraging pre-clinical data and computational modeling, our approach proposes dosage strategies that can optimize synergy in drug combinations, while also bringing forth the real-world challenges of staying within a precise dose range.

The Exonuclease TREX1 Constitutes an Innate Immune Checkpoint Limiting cGAS/STING-Mediated Antitumor Immunity.

The DNA exonuclease three-prime repair exonuclease 1 (TREX1) is critical for preventing autoimmunity in mice and humans by degrading endogenous cytosolic DNA, which otherwise triggers activation of the innate cGAS/STING pathway leading to the production of type I IFNs. As tumor cells are prone to aberrant cytosolic DNA accumulation, we hypothesized that they are critically dependent on TREX1 activity to limit their immunogenicity. Here, we show that in tumor cells, TREX1 restricts spontaneous activation of the cGAS/STING pathway, and the subsequent induction of a type I IFN response. As a result, TREX1 deficiency compromised in vivo tumor growth in mice. This delay in tumor growth depended on a functional immune system, systemic type I IFN signaling, and tumor-intrinsic cGAS expression. Mechanistically, we show that tumor TREX1 loss drove activation of CD8+ T cells and NK cells, prevented CD8+ T-cell exhaustion, and remodeled an immunosuppressive myeloid compartment. Consequently, TREX1 deficiency combined with T-cell-directed immune checkpoint blockade. Collectively, we conclude that TREX1 is essential to limit tumor immunogenicity, and that targeting this innate immune checkpoint remodels the tumor microenvironment and enhances antitumor immunity by itself and in combination with T-cell-targeted therapies. See related article by Toufektchan et al., p. 673.

Cross-coupling by a noncanonical mechanism involving the addition of aryl halide to Cu(II).

Copper complexes are widely used in the synthesis of fine chemicals and materials to catalyze couplings of heteroatom nucleophiles with aryl halides. We show that cross-couplings catalyzed by some of the most active catalysts occur by a mechanism not previously considered. Copper(II) [Cu(II)] complexes of oxalamide ligands catalyze Ullmann coupling to form the C-O bond in aryl ethers by concerted oxidative addition of an aryl halide to Cu(II) to form a high-valent species that is stabilized by radical character on the oxalamide ligand. This mechanism diverges from those involving Cu(I) and Cu(III) intermediates that have been posited for other Ullmann-type couplings. The stability of the Cu(II) state leads to high turnover numbers, >1000 for the coupling of phenoxide with aryl chloride electrophiles, as well as an ability to run the reactions in air.

An allosteric pan-TEAD inhibitor blocks oncogenic YAP/TAZ signaling and overcomes KRAS G12C inhibitor resistance.

The Hippo pathway is a key growth control pathway that is conserved across species. The downstream effectors of the Hippo pathway, YAP (Yes-associated protein) and TAZ (transcriptional coactivator with PDZ-binding motif), are frequently activated in cancers to drive proliferation and survival. Based on the premise that sustained interactions between YAP/TAZ and TEADs (transcriptional enhanced associate domain) are central to their transcriptional activities, we discovered a potent small-molecule inhibitor (SMI), GNE-7883, that allosterically blocks the interactions between YAP/TAZ and all human TEAD paralogs through binding to the TEAD lipid pocket. GNE-7883 effectively reduces chromatin accessibility specifically at TEAD motifs, suppresses cell proliferation in a variety of cell line models and achieves strong antitumor efficacy in vivo. Furthermore, we uncovered that GNE-7883 effectively overcomes both intrinsic and acquired resistance to KRAS (Kirsten rat sarcoma viral oncogene homolog) G12C inhibitors in diverse preclinical models through the inhibition of YAP/TAZ activation. Taken together, this work demonstrates the activities of TEAD SMIs in YAP/TAZ-dependent cancers and highlights their potential broad applications in precision oncology and therapy resistance.

Distinct resistance mechanisms arise to allosteric vs. ATP-competitive AKT inhibitors.

The AKT kinases have emerged as promising therapeutic targets in oncology and both allosteric and ATP-competitive AKT inhibitors have entered clinical investigation. However, long-term efficacy of such inhibitors will likely be challenged by the development of resistance. We have established prostate cancer models of acquired resistance to the allosteric inhibitor MK-2206 or the ATP-competitive inhibitor ipatasertib following prolonged exposure. While alterations in AKT are associated with acquired resistance to MK-2206, ipatasertib resistance is driven by rewired compensatory activity of parallel signaling pathways. Importantly, MK-2206 resistance can be overcome by treatment with ipatasertib, while ipatasertib resistance can be reversed by co-treatment with inhibitors of pathways including PIM signaling. These findings demonstrate that distinct resistance mechanisms arise to the two classes of AKT inhibitors and that combination approaches may reverse resistance to ATP-competitive inhibition.

Selective PROTAC-mediated degradation of SMARCA2 is efficacious in SMARCA4 mutant cancers.

The mammalian SWItch/Sucrose Non-Fermentable (SWI/SNF) helicase SMARCA4 is frequently mutated in cancer and inactivation results in a cellular dependence on its paralog, SMARCA2, thus making SMARCA2 an attractive synthetic lethal target. However, published data indicates that achieving a high degree of selective SMARCA2 inhibition is likely essential to afford an acceptable therapeutic index, and realizing this objective is challenging due to the homology with the SMARCA4 paralog. Herein we report the discovery of a potent and selective SMARCA2 proteolysis-targeting chimera molecule (PROTAC), A947. Selective SMARCA2 degradation is achieved in the absence of selective SMARCA2/4 PROTAC binding and translates to potent in vitro growth inhibition and in vivo efficacy in SMARCA4 mutant models, compared to wild type models. Global ubiquitin mapping and proteome profiling reveal no unexpected off-target degradation related to A947 treatment. Our study thus highlights the ability to transform a non-selective SMARCA2/4-binding ligand into a selective and efficacious in vivo SMARCA2-targeting PROTAC, and thereby provides a potential new therapeutic opportunity for patients whose tumors contain SMARCA4 mutations.

Orchestrating and sharing large multimodal data for transparent and reproducible research.

Reproducibility is essential to open science, as there is limited relevance for findings that can not be reproduced by independent research groups, regardless of its validity. It is therefore crucial for scientists to describe their experiments in sufficient detail so they can be reproduced, scrutinized, challenged, and built upon. However, the intrinsic complexity and continuous growth of biomedical data makes it increasingly difficult to process, analyze, and share with the community in a FAIR (findable, accessible, interoperable, and reusable) manner. To overcome these issues, we created a cloud-based platform called ORCESTRA ( orcestra.ca ), which provides a flexible framework for the reproducible processing of multimodal biomedical data. It enables processing of clinical, genomic and perturbation profiles of cancer samples through automated processing pipelines that are user-customizable. ORCESTRA creates integrated and fully documented data objects with persistent identifiers (DOI) and manages multiple dataset versions, which can be shared for future studies.

Transcriptional Subtypes Resolve Tumor Heterogeneity and Identify Vulnerabilities to MEK Inhibition in Lung Adenocarcinoma.

PURPOSE: Lung adenocarcinomas comprise the largest fraction of non-small cell lung cancer, which is the leading cause of cancer-related deaths. Seventy-five percent of adenocarcinomas lack targeted therapies because of scarcity of druggable drivers. Here, we classified tumors on the basis of signaling similarities and discovered subgroups within this unmet patient population. EXPERIMENTAL DESIGN: We leveraged transcriptional data from >800 early- and advanced-stage patients. RESULTS: We identified three robust subtypes dubbed mucinous, proliferative, and mesenchymal with respective pathway phenotypes. These transcriptional states lack discrete and causative mutational etiology as evidenced by similarly distributed oncogenic drivers, including KRAS and EGFR. The subtypes capture heterogeneity even among tumors lacking known oncogenic drivers. Paired multi-regional intratumoral biopsies demonstrated unified subtypes despite divergently evolved prooncogenic mutations, indicating subtype stability during selective pressure. Heterogeneity among in vitro and in vivo preclinical models is expounded by the human lung adenocarcinoma subtypes and can be leveraged to discover subtype-specific vulnerabilities. As proof of concept, we identified differential subtype response to MEK pathway inhibition in a chemical library screen of 89 lung cancer cell lines, which reproduces across model systems and a clinical trial. CONCLUSIONS: Our findings support forward translational relevance of transcriptional subtypes, where further exploration therein may improve lung adenocarcinoma treatment.See related commentary by Skoulidis, p. 913.

Machine-Learning and Chemicogenomics Approach Defines and Predicts Cross-Talk of Hippo and MAPK Pathways.

Hippo pathway dysregulation occurs in multiple cancers through genetic and nongenetic alterations, resulting in translocation of YAP to the nucleus and activation of the TEAD family of transcription factors. Unlike other oncogenic pathways such as RAS, defining tumors that are Hippo pathway-dependent is far more complex due to the lack of hotspot genetic alterations. Here, we developed a machine-learning framework to identify a robust, cancer type-agnostic gene expression signature to quantitate Hippo pathway activity and cross-talk as well as predict YAP/TEAD dependency across cancers. Further, through chemical genetic interaction screens and multiomics analyses, we discover a direct interaction between MAPK signaling and TEAD stability such that knockdown of YAP combined with MEK inhibition results in robust inhibition of tumor cell growth in Hippo dysregulated tumors. This multifaceted approach underscores how computational models combined with experimental studies can inform precision medicine approaches including predictive diagnostics and combination strategies. SIGNIFICANCE: An integrated chemicogenomics strategy was developed to identify a lineage-independent signature for the Hippo pathway in cancers. Evaluating transcriptional profiles using a machine-learning method led to identification of a relationship between YAP/TAZ dependency and MAPK pathway activity. The results help to nominate potential combination therapies with Hippo pathway inhibition.This article is highlighted in the In This Issue feature, p. 521.

Identification of response signatures for tankyrase inhibitor treatment in tumor cell lines.

Small-molecule tankyrase 1 and tankyrase 2 (TNKS1/2) inhibitors are effective antitumor agents in selected tumor cell lines and mouse models. Here, we characterized the response signatures and the in-depth mechanisms for the antiproliferative effect of tankyrase inhibition (TNKSi). The TNKS1/2-specific inhibitor G007-LK was used to screen 537 human tumor cell lines and a panel of particularly TNKSi-sensitive tumor cell lines was identified. Transcriptome, proteome, and bioinformatic analyses revealed the overall TNKSi-induced response signatures in the selected panel. TNKSi-mediated inhibition of wingless-type mammary tumor virus integration site/ß-catenin, yes-associated protein 1 (YAP), and phosphatidylinositol-4,5-bisphosphate 3-kinase/AKT signaling was validated and correlated with lost expression of the key oncogene MYC and impaired cell growth. Moreover, we show that TNKSi induces accumulation of TNKS1/2-containing ß-catenin degradasomes functioning as core complexes interacting with YAP and angiomotin proteins during attenuation of YAP signaling. These findings provide a contextual and mechanistic framework for using TNKSi in anticancer treatment that warrants further comprehensive preclinical and clinical evaluations.

Towards in vitro in vivo correlation for modified release subcutaneously administered insulins.

Therapeutic proteins and peptides are mainly administrated by subcutaneous injection. In vitro release testing of subcutaneous injectables performed using methods that take the structure and environment of the subcutaneous tissue into account may improve predictability of the in vivo behavior and thereby facilitate establishment of in vitro in vivo correlations. The aim of the study was to develop a biopredictive flow-through in vitro release method with a gel-type matrix for subcutaneously administered formulations and to explore the possibility of establishing a level A in vitro in vivo correlation for selected insulin products. A novel gel-based flow-through method with the incorporation of an injection step was used to assess selected commercial insulin formulations with different duration of action (Actrapid®, Mixtard® 30, Insulatard®, Lantus®). The in vitro release method provided the correct rank ordering in relation to the in vivo performance. For the modified release insulins Insulatard® and Lantus®, an in vitro in vivo correlation using non-linear time scaling was established based on the in vitro release data and in vivo subcutaneous absorption data of the 125I-labeled insulins taken from literature. Predicted absorption profiles were constructed using the in vitro in vivo correlation and subsequently converted into simulated plasma profiles. The approach taken may be of wider utility in characterizing injectables for subcutaneous administration.

Autocrine CSF-1R activation promotes Src-dependent disruption of mammary epithelial architecture.

Elevated coexpression of colony-stimulating factor receptor (CSF-1R) and its ligand, CSF-1, correlates with invasiveness and poor prognosis of a variety of epithelial tumors (Kacinski, B.M. 1995. Ann. Med. 27:79-85). Apart from recruitment of macrophages to the tumor site, the mechanisms by which CSF-1 may potentiate invasion are poorly understood. We show that autocrine CSF-1R activation induces hyperproliferation and a profound, progressive disruption of junctional integrity in acinar structures formed by human mammary epithelial cells in three-dimensional culture. Acini coexpressing receptor and ligand exhibit a dramatic relocalization of E-cadherin from the plasma membrane to punctate intracellular vesicles, accompanied by its loss from the Triton-insoluble fraction. Interfering with Src kinase activity, either by pharmacological inhibition or mutation of the Y561 docking site on CSF-1R, prevents E-cadherin translocation, suggesting that CSF-1R disrupts cell adhesion by uncoupling adherens junction complexes from the cytoskeleton and promoting cadherin internalization through a Src-dependent mechanism. These findings provide a mechanistic basis whereby CSF-1R could contribute to invasive progression in epithelial cancers.