Comprehensive Target Engagement by the EZH2 Inhibitor Tulmimetostat Allows for Targeting of ARID1A Mutant Cancers.

Recurrent somatic mutations in the BAF chromatin remodeling complex subunit ARID1A occur frequently in advanced urothelial carcinoma, endometrial cancers, and ovarian clear cell carcinoma, creating an alternative chromatin state that may be exploited therapeutically. The histone methyltransferase EZH2 has previously been identified as targetable vulnerability in the context of ARID1A mutations. Here, we describe the discovery of tulmimetostat, an orally available, clinical stage EZH2 inhibitor and elucidate its therapeutic potential for treating ARID1A mutant tumors. Tulmimetostat administration achieved efficacy in multiple ARID1A mutant bladder, ovarian, and endometrial tumor models and improved cisplatin response in chemotherapy-resistant models. Consistent with its comprehensive and durable level of target coverage, tulmimetostat demonstrated greater efficacy than other PRC2-targeted inhibitors at comparable or lower exposures in a bladder cancer xenograft mouse model. Tulmimetostat mediated extensive changes in gene expression in addition to a profound reduction in global H3K27me3 levels in tumors. Phase I clinical pharmacokinetic and pharmacodynamic data indicated that tulmimetostat exhibits durable exposure and profound target engagement. Importantly, a tulmimetostat controlled gene expression signature identified in whole blood from a cohort of 32 cancer patients correlated with tulmimetostat exposure, representing a pharmacodynamic marker for the assessment of target coverage for PRC2-targeted agents in the clinic. Collectively, this data suggests that tulmimetostat has the potential to achieve clinical benefit in solid tumors as a monotherapy but also in combination with chemotherapeutic agents and may be beneficial in various indications with recurrent ARID1A mutations.

SpatialSort: a Bayesian model for clustering and cell population annotation of spatial proteomics data.

MOTIVATION: Recent advances in spatial proteomics technologies have enabled the profiling of dozens of proteins in thousands of single cells in situ. This has created the opportunity to move beyond quantifying the composition of cell types in tissue, and instead probe the spatial relationships between cells. However, most current methods for clustering data from these assays only consider the expression values of cells and ignore the spatial context. Furthermore, existing approaches do not account for prior information about the expected cell populations in a sample. RESULTS: To address these shortcomings, we developed SpatialSort, a spatially aware Bayesian clustering approach that allows for the incorporation of prior biological knowledge. Our method is able to account for the affinities of cells of different types to neighbour in space, and by incorporating prior information about expected cell populations, it is able to simultaneously improve clustering accuracy and perform automated annotation of clusters. Using synthetic and real data, we show that by using spatial and prior information SpatialSort improves clustering accuracy. We also demonstrate how SpatialSort can perform label transfer between spatial and nonspatial modalities through the analysis of a real world diffuse large B-cell lymphoma dataset. AVAILABILITY AND IMPLEMENTATION: Source code is available on Github at: https://github.com/Roth-Lab/SpatialSort.

Revisiting the vulnerable dark triad hypothesis using a bifactor model.

Miller et al. (2010) previously suggested that borderline pathology, vulnerable narcissism, and Factor 2 psychopathy share a common "Vulnerable Dark Triad" (VDT) core. The present study (N = 1,023 community participants) aims to test that hypothesis using exploratory and confirmatory bifactor analyses. We found support for a bifactor model that obtained satisfactory fits and other adequate validity indices, which included a general VDT factor and three group factors (Reckless, Entitled, Hiding). The general VDT factor was mostly saturated with borderline symptoms items reflecting self-hatred and worthlessness, which did not form a group factor; these results add to previous research suggesting that features of borderline pathology may represent the core of personality pathology. The three group factors had distinctive relationships with Dark Triad traits, pathological trait domains, and aggression. In contrast with the three group factors, the general VDT factor more strongly incremented the prediction of negative affectivity and hostility; the group factors more strongly incremented the prediction of grandiosity, egocentrism, callousness, Machiavellianism, and direct (physical/verbal) aggression. Alignment of the retained bifactor model with influent models of personality pathology and conceptual/methodological implications of the present results for research on the hypothesized VDT are discussed, as well as some clinical implications of the findings.

Accurate determination of CRISPR-mediated gene fitness in transplantable tumours.

Assessing tumour gene fitness in physiologically-relevant model systems is challenging due to biological features of in vivo tumour regeneration, including extreme variations in single cell lineage progeny. Here we develop a reproducible, quantitative approach to pooled genetic perturbation in patient-derived xenografts (PDXs), by encoding single cell output from transplanted CRISPR-transduced cells in combination with a Bayesian hierarchical model. We apply this to 181 PDX transplants from 21 breast cancer patients. We show that uncertainty in fitness estimates depends critically on the number of transplant cell clones and the variability in clone sizes. We use a pathway-directed allelic series to characterize Notch signaling, and quantify TP53 / MDM2 drug-gene conditional fitness in outlier patients. We show that fitness outlier identification can be mirrored by pharmacological perturbation. Overall, we demonstrate that the gene fitness landscape in breast PDXs is dominated by inter-patient differences.

GNE-064: A Potent, Selective, and Orally Bioavailable Chemical Probe for the Bromodomains of SMARCA2 and SMARCA4 and the Fifth Bromodomain of PBRM1.

Bromodomains are acetyllysine recognition domains present in a variety of human proteins. Bromodomains also bind small molecules that compete with acetyllysine, and therefore bromodomains have been targets for drug discovery efforts. Highly potent and selective ligands with good cellular permeability have been proposed as chemical probes for use in exploring the functions of many of the bromodomain proteins. We report here the discovery of a class of such inhibitors targeting the family VIII bromodomains of SMARCA2 (BRM) and SMARCA4 (BRG1), and PBRM1 (polybromo-1) bromodomain 5. We propose one example from this series, GNE-064, as a chemical probe for the bromodomains SMARCA2, SMARCA4, and PBRM1(5) with the potential for in vivo use.

Social protection and access to assistive technology in low- and middle-income countries.

To overcome widespread barriers and lack of support, persons with disabilities face significant disability-related costs, including assistive technology (AT), that drive them to or maintain them in poverty and undermine their socio-economic participation. In many countries, social protection systems are a gateway to accessing assistive devices either through health insurance, integration in Universal Health Coverage (UHC) packages, subsidies, cash transfers or direct provision. However, the broader issues of access to AT (lack of awareness, information, availability, human resources, etc.) are compounded by barriers to social protection. In low- and middle-income countries globally, less than 20% of persons with significant disabilities, who are likely to need AT, receive disability benefits. This paper reflects on the relation of AT and disability-related costs, the evolution of the role of social protection in line with the CRPD, and the different social protection mechanisms used at the national level to provide access to AT. It further highlights some of the key issues to be tackled by social protection systems to enhance access to AT, with a focus on low- and middle-income countries.

Clonal fitness inferred from time-series modelling of single-cell cancer genomes.

Progress in defining genomic fitness landscapes in cancer, especially those defined by copy number alterations (CNAs), has been impeded by lack of time-series single-cell sampling of polyclonal populations and temporal statistical models1-7. Here we generated 42,000 genomes from multi-year time-series single-cell whole-genome sequencing of breast epithelium and primary triple-negative breast cancer (TNBC) patient-derived xenografts (PDXs), revealing the nature of CNA-defined clonal fitness dynamics induced by TP53 mutation and cisplatin chemotherapy. Using a new Wright-Fisher population genetics model8,9 to infer clonal fitness, we found that TP53 mutation alters the fitness landscape, reproducibly distributing fitness over a larger number of clones associated with distinct CNAs. Furthermore, in TNBC PDX models with mutated TP53, inferred fitness coefficients from CNA-based genotypes accurately forecast experimentally enforced clonal competition dynamics. Drug treatment in three long-term serially passaged TNBC PDXs resulted in cisplatin-resistant clones emerging from low-fitness phylogenetic lineages in the untreated setting. Conversely, high-fitness clones from treatment-naive controls were eradicated, signalling an inversion of the fitness landscape. Finally, upon release of drug, selection pressure dynamics were reversed, indicating a fitness cost of treatment resistance. Together, our findings define clonal fitness linked to both CNA and therapeutic resistance in polyclonal tumours.

A Proposed Classification of ICD-11 Severity Degrees of Personality Pathology Using the Self and Interpersonal Functioning Scale.

Background: The 11th version of the World Health Organization's International Classification of Diseases (ICD-11) has adopted a dimensional approach to personality disorder (PD) nosology. Notably, it includes an assessment of PD degree of severity, which can be classified according to five categories. To date, there is no gold standard measure for assessing degree of PD severity based on the ICD-11 model, and there are no empirically-based anchor points to delineate the proposed categories. With the operationalization of PD degrees of severity in the ICD-11 PD model now being closely aligned with Criterion A of the DSM-5 Alternative Model for Personality Disorders (AMPD), sharing a focus on self and interpersonal dysfunction, self-report instruments developed for the latter model might prove useful as screening tools to determine degrees of severity in the former. Methods: The Self and Interpersonal Functioning Scale, a brief validated self-report questionnaire originally designed to assess level of personality pathology according to the AMPD framework, was used to derive anchor points to delineate the five severity degrees from the ICD-11 PD model. Data from five clinical and non-clinical samples (total N = 2,240) allowed identifying anchor points for classification, based on Receiver Operating Characteristic curve analysis, Latent Class Analysis, and data distribution statistics. Categories were validated using multiple indices pertaining to externalizing and internalizing symptoms relevant to PD. Results: Analyses yielded the following anchor points for PD degrees of severity: No PD = 0-1.04; Personality Difficulty = 1.05-1.29; Mild PD = 1.30-1.89; Moderate PD = 1.90-2.49; and Severe PD = 2.50 and above. A clear gradient of severity across the five categories was observed in all samples. A high number of significant contrasts among PD categories were also observed on external variables, consistent with the ICD-11 PD degree of severity operationalization. Conclusions: The present study provides potentially useful guidelines to determine severity of personality pathology based on the ICD-11 model. The use of a brief self-report questionnaire as a screening tool for assessing PD degrees of severity should be seen as a time-efficient support for clinical decision and treatment planning.

Identification and characterization of second-generation EZH2 inhibitors with extended residence times and improved biological activity.

The histone methyltransferase EZH2 has been the target of numerous small-molecule inhibitor discovery efforts over the last 10+ years. Emerging clinical data have provided early evidence for single agent activity with acceptable safety profiles for first-generation inhibitors. We have developed kinetic methodologies for studying EZH2-inhibitor-binding kinetics that have allowed us to identify a unique structural modification that results in significant increases in the drug-target residence times of all EZH2 inhibitor scaffolds we have studied. The unexpected residence time enhancement bestowed by this modification has enabled us to create a series of second-generation EZH2 inhibitors with sub-pM binding affinities. We provide both biophysical evidence validating this sub-pM potency and biological evidence demonstrating the utility and relevance of such high-affinity interactions with EZH2.

Latent profiles of patients with borderline pathology based on the alternative DSM-5 model for personality disorders.

BACKGROUND: There have been multiple attempts to try to parse out heterogeneity within borderline pathology by identifying patient subtypes; thus far, these works have yielded few consistent results. Recent developments in the operationalization of borderline pathology may provide new opportunities to identify clinically and conceptually meaningful subgroups of patients. The Alternative DSM-5 Model for Personality Disorders (AMPD) offers a categorical-dimensional operationalization of Borderline personality disorder (BPD) that has yet to be tested for identification of patient subgroups. The purpose of the present study is to test whether the combination of the Criterion A elements (pertaining to level of severity) and the seven pathological facets from Criterion B that define BPD in the AMPD can yield meaningful patient profiles. METHODS: A total of 211 outpatients from a specialized PD treatment program (133 women, Mage = 33.66, SD = 10.97) were selected based on the presence of at least moderate borderline pathology according to cutoffs recently proposed for the Borderline Symptom List-23. Valid Criterion A (Self and Interpersonal Functioning Scale) and B (Personality Inventory for DSM-5 Faceted Brief Form) self-reports were administered to measure elements and facets that define BPD in the AMPD model; these variables were used as indicators in a latent profile analysis (LPA). RESULTS: The optimal solution generated by LPA yielded four distinct profiles: (a) Borderline traits; (b) Moderate pathology with Impulsivity; (c) Moderate pathology with Identity problems and Depressivity; and (d) Severe pathology. Clinically meaningful distinctions emerged among profiles on AMPD indicators and external variables relevant to PD, especially aggression and impulsivity. CONCLUSIONS: Profiles reflected both the "severity" and "style" components imbedded within Criterion A and B of the AMPD, as they were mainly distinguished by a continuum of severity but also by some meaningful qualitative differences that may have important clinical implications for treatment planning and contracting. Results also suggest that the four Criterion A elements have independent value to identify important differences in patients with borderline pathology. They also highlight that some Criterion B facets that define BPD in the AMPD may be especially important to identify subgroups of patients, mainly Impulsivity and Depressivity.

Design, Synthesis, and Pharmacological Evaluation of Second Generation EZH2 Inhibitors with Long Residence Time.

Histone methyltransferase EZH2, which is the catalytic subunit of the PRC2 complex, catalyzes the methylation of histone H3K27-a transcriptionally repressive post-translational modification (PTM). EZH2 is commonly mutated in hematologic malignancies and frequently overexpressed in solid tumors, where its expression level often correlates with poor prognosis. First generation EZH2 inhibitors are beginning to show clinical benefit, and we believe that a second generation EZH2 inhibitor could further build upon this foundation to fully realize the therapeutic potential of EZH2 inhibition. During our medicinal chemistry campaign, we identified 4-thiomethyl pyridone as a key modification that led to significantly increased potency and prolonged residence time. Leveraging this finding, we optimized a series of EZH2 inhibitors, with enhanced antitumor activity and improved physiochemical properties, which have the potential to expand the clinical use of EZH2 inhibition.

Design and Synthesis of Styrenylcyclopropylamine LSD1 Inhibitors.

Leveraging the catalytic machinery of LSD1 (KDM1A), a series of covalent styrenylcyclopropane LSD1 inhibitors were identified. These inhibitors represent a new class of mechanism-based inhibitors that target and covalently label the FAD cofactor of LSD1. The series was rapidly progressed to potent biochemical and cellular LSD1 inhibitors with good physical properties. This effort resulted in the identification of 34, a highly potent (<4 nM biochemical, 2 nM cell, and 1 nM GI50), and selective LSD1 inhibitor. In-depth kinetic profiling of 34 confirmed its covalent mechanism of action, validated the styrenylcyclopropane as an FAD-directed warhead, and demonstrated that the potency of this inhibitor is driven by improved non-covalent binding (K I). 34 demonstrated robust cell-killing activity in a panel of AML cell lines and robust antitumor activity in a Kasumi-1 xenograft model of AML when dosed orally at 1.5 mg/kg once daily.

An Annealed Sequential Monte Carlo Method for Bayesian Phylogenetics.

We describe an "embarrassingly parallel" method for Bayesian phylogenetic inference, annealed Sequential Monte Carlo (SMC), based on recent advances in the SMC literature such as adaptive determination of annealing parameters. The algorithm provides an approximate posterior distribution over trees and evolutionary parameters as well as an unbiased estimator for the marginal likelihood. This unbiasedness property can be used for the purpose of testing the correctness of posterior simulation software. We evaluate the performance of phylogenetic annealed SMC by reviewing and comparing with other computational Bayesian phylogenetic methods, in particular, different marginal likelihood estimation methods. Unlike previous SMC methods in phylogenetics, our annealed method can utilize standard Markov chain Monte Carlo (MCMC) tree moves and hence benefit from the large inventory of such moves available in the literature. Consequently, the annealed SMC method should be relatively easy to incorporate into existing phylogenetic software packages based on MCMC algorithms. We illustrate our method using simulation studies and real data analysis.

Introducing a short self-report for the assessment of DSM-5 level of personality functioning for personality disorders: The Self and Interpersonal Functioning Scale.

In the present study, we report on the development and validation of the Self and Interpersonal Functioning Scale (SIFS), a 24-item self-report questionnaire designed to assess the four core elements of personality pathology (Identity, Self-direction, Empathy, and Intimacy) from the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Level of Personality Functioning for personality disorders. Participants from a community sample (n = 280) and patients from a specialized treatment facility for personality disorders (n = 106) were included in the validation sample. Overall, the SIFS showed sound psychometric properties. A second-order factor solution, which consisted of the four Level of Personality Functioning elements and an overarching personality pathology factor, showed the best fit indices. The four SIFS elements showed a well-differentiated and conceptually meaningful pattern of associations with related constructs. In light of these results, the SIFS should be considered as a promising, concise measure of Criterion A for clinical screening and research purposes. Its relative strengths and limitations in contrast with other existing self-report measures of Criterion A are discussed. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

clonealign: statistical integration of independent single-cell RNA and DNA sequencing data from human cancers.

Measuring gene expression of tumor clones at single-cell resolution links functional consequences to somatic alterations. Without scalable methods to simultaneously assay DNA and RNA from the same single cell, parallel single-cell DNA and RNA measurements from independent cell populations must be mapped for genome-transcriptome association. We present clonealign, which assigns gene expression states to cancer clones using single-cell RNA and DNA sequencing independently sampled from a heterogeneous population. We apply clonealign to triple-negative breast cancer patient-derived xenografts and high-grade serous ovarian cancer cell lines and discover clone-specific dysregulated biological pathways not visible using either sequencing method alone.

Somatic mutation detection and classification through probabilistic integration of clonal population information.

Somatic mutations are a primary contributor to malignancy in human cells. Accurate detection of mutations is needed to define the clonal composition of tumours whereby clones may have distinct phenotypic properties. Although analysis of mutations over multiple tumour samples from the same patient has the potential to enhance identification of clones, few analytic methods exploit the correlation structure across samples. We posited that incorporating clonal information into joint analysis over multiple samples would improve mutation detection, particularly those with low prevalence. In this paper, we develop a new procedure called MuClone, for detection of mutations across multiple tumour samples of a patient from whole genome or exome sequencing data. In addition to mutation detection, MuClone classifies mutations into biologically meaningful groups and allows us to study clonal dynamics. We show that, on lung and ovarian cancer datasets, MuClone improves somatic mutation detection sensitivity over competing approaches without compromising specificity.

GNE-371, a Potent and Selective Chemical Probe for the Second Bromodomains of Human Transcription-Initiation-Factor TFIID Subunit 1 and Transcription-Initiation-Factor TFIID Subunit 1-like.

The biological functions of the dual bromodomains of human transcription-initiation-factor TFIID subunit 1 (TAF1(1,2)) remain unknown, although TAF1 has been identified as a potential target for oncology research. Here, we describe the discovery of a potent and selective in vitro tool compound for TAF1(2), starting from a previously reported lead. A cocrystal structure of lead compound 2 bound to TAF1(2) enabled structure-based design and structure-activity-relationship studies that ultimately led to our in vitro tool compound, 27 (GNE-371). Compound 27 binds TAF1(2) with an IC50 of 10 nM while maintaining excellent selectivity over other bromodomain-family members. Compound 27 is also active in a cellular-TAF1(2) target-engagement assay (IC50 = 38 nM) and exhibits antiproliferative synergy with the BET inhibitor JQ1, suggesting engagement of endogenous TAF1 by 27 and further supporting the use of 27 in mechanistic and target-validation studies.

Interfaces of Malignant and Immunologic Clonal Dynamics in Ovarian Cancer.

High-grade serous ovarian cancer (HGSC) exhibits extensive malignant clonal diversity with widespread but non-random patterns of disease dissemination. We investigated whether local immune microenvironment factors shape tumor progression properties at the interface of tumor-infiltrating lymphocytes (TILs) and cancer cells. Through multi-region study of 212 samples from 38 patients with whole-genome sequencing, immunohistochemistry, histologic image analysis, gene expression profiling, and T and B cell receptor sequencing, we identified three immunologic subtypes across samples and extensive within-patient diversity. Epithelial CD8+ TILs negatively associated with malignant diversity, reflecting immunological pruning of tumor clones inferred by neoantigen depletion, HLA I loss of heterozygosity, and spatial tracking between T cell and tumor clones. In addition, combinatorial prognostic effects of mutational processes and immune properties were observed, illuminating how specific genomic aberration types associate with immune response and impact survival. We conclude that within-patient spatial immune microenvironment variation shapes intraperitoneal malignant spread, provoking new evolutionary perspectives on HGSC clonal dispersion.

Premature psychotherapy termination in an outpatient treatment program for personality disorders: a survival analysis.

OBJECTIVE: Psychological treatment for patients with personality disorders (PD) is plagued with a high proportion of early dropouts, and attempts to identify risk factors for attrition have generated very few conclusive results. The purpose of the present study is to identify significant predictors of early treatment termination in a long-term psychotherapy program for PD. METHODS: Data was retrospectively retrieved from 174 files of patients who began long-term psychotherapy in an outpatient treatment program in Quebec City, Canada. Socio-demographic, initial disturbance, and diagnostic variables were considered for prediction, along with a measure specifically designed to identify PD patients at risk of dropping out early from psychotherapy, the Treatment Attrition-Retention Scale for Personality Disorders (TARS-PD). Survival analysis using Cox proportional hazard regression was performed to identify significant predictors. RESULTS: Results using univariate Cox proportional hazards regressions revealed that unemployment, Global Assessment of Functioning scores, and recent hetero-aggressive behavior were significant predictors of early dropout in the first six months of therapy. Adjusting for these three confounders, four of the factor scores from the TARS-PD (Narcissism, Secondary gains, Low distress, and Cluster A features) were significantly associated with dropout in univariate Cox proportional hazards regressions. Secondary gains and Narcissism remained significant predictors after entering all five TARS-PD factors in a multivariate Cox proportional hazards regression adjusting for confounders. CONCLUSIONS: Taking into consideration specific treatment prognosis variables, such as those measured by the TARS-PD, might be more useful for dropout prediction in PD patients in comparison with more general demographic and diagnostic variables.

Premature Termination of Psychotherapy in Patients With Borderline Personality Disorder: A Cluster-Analytic Study.

The goal of the present study was to establish profiles of patients with borderline personality disorder (BPD) who dropped out early from an outpatient psychotherapy program. From a sample of 56 BPD patients who dropped out after the first of a three-year program, a TwoStep cluster analysis procedure was performed, using the five factors of the Treatment Attrition-Retention Scale for Personality Disorders (Gamache et al., J Pers Disord 1-21, 2017) and the Global Assessment of Functioning score (Spitzer et al., Global Assessment of Functioning [GAF] Scale. In Sederer LI, Dickey B [Eds], Outcomes assessment in clinical practice [pp 76-78]. Baltimore, MD: Walter and Williams) as clustering variables. Four clusters emerged: Higher-functioning, Narcissistic features/entitlement, Pseudo-normality, and Highly dysfunctional. Differences between the clusters were found on sex, occupational status, and presence of antisocial features. These findings could help both identify BPD patients at potential risk of dropping out of psychotherapy and adjust interventions accordingly to reduce premature termination.