Patterns of substrate affinity, competition, and degradation kinetics underlie biological activity of thalidomide analogs.

Pharmacologic agents that modulate ubiquitin ligase activity to induce protein degradation are a major new class of therapeutic agents, active in a number of hematologic malignancies. However, we currently have a limited understanding of the determinants of activity of these agents and how resistance develops. We developed and used a novel quantitative, targeted mass spectrometry (MS) assay to determine the relative activities, kinetics, and cell-type specificity of thalidomide and 4 analogs, all but 1 of which are in clinical use or clinical trials for hematologic malignancies. Thalidomide analogs bind the CRL4CRBN ubiquitin ligase and induce degradation of particular proteins, but each of the molecules studied has distinct patterns of substrate specificity that likely underlie the clinical activity and toxicities of each drug. Our results demonstrate that the activity of molecules that induce protein degradation depends on the strength of ligase-substrate interaction in the presence of drug, the levels of the ubiquitin ligase, and the expression level of competing substrates. These findings highlight a novel mechanism of resistance to this class of drugs mediated by competition between substrates for access to a limiting pool of the ubiquitin ligase. We demonstrate that increased expression of a nonessential substrate can lead to decreased degradation of other substrates that are critical for antineoplastic activity of the drug, resulting in drug resistance. These studies provide general rules that govern drug-dependent substrate degradation and key differences between thalidomide analog activity in vitro and in vivo.

Acquired Multidrug Resistance in AML Is Caused by Low Apoptotic Priming in Relapsed Myeloblasts.

In many cancers, mortality is associated with the emergence of relapse with multidrug resistance (MDR). Thus far, the investigation of cancer relapse mechanisms has largely focused on acquired genetic mutations. Using acute myeloid leukemia (AML) patient-derived xenografts (PDX), we systematically elucidated a basis of MDR and identified drug sensitivity in relapsed AML. We derived pharmacologic sensitivity for 22 AML PDX models using dynamic BH3 profiling (DBP), together with genomics and transcriptomics. Using in vivo acquired resistant PDXs, we found that resistance to unrelated, narrowly targeted agents in distinct PDXs was accompanied by broad resistance to drugs with disparate mechanisms. Moreover, baseline mitochondrial apoptotic priming was consistently reduced regardless of the class of drug-inducing selection. By applying DBP, we identified drugs showing effective in vivo activity in resistant models. This study implies evasion of apoptosis drives drug resistance and demonstrates the feasibility of the DBP approach to identify active drugs for patients with relapsed AML. SIGNIFICANCE: Acquired resistance to targeted therapy remains challenging in AML. We found that reduction in mitochondrial priming and common transcriptomic signatures was a conserved mechanism of acquired resistance across different drug classes in vivo. Drugs active in vivo can be identified even in the multidrug resistant state by DBP.

Formative evaluation prior to implementation of a brief treatment for posttraumatic stress disorder in primary care.

BACKGROUND: Successful implementation of evidence-based treatments (EBT) for posttraumatic stress disorder (PTSD) in primary care may address treatment access and quality gaps by providing care in novel and less stigmatized settings. Yet, PTSD treatments are largely unavailable in safety net primary care. We aimed to collect clinician stakeholder data on organizational, attitudinal, and contextual factors relevant to EBT implementation. METHODS: Our developmental formative evaluation was guided by the Consolidated Framework for Implementation Research (CFIR), including (a) surveys assessing implementation climate and attitudes towards EBTs and behavioral health integration and (b) semi-structured interviews to identify barriers and facilitators to implementation and need for augmentation. Participants were hospital employees (N = 22), including primary care physicians (n = 6), integrated behavioral health clinicians (n = 8), community wellness advocates (n = 3), and clinic leadership (n = 5). We report frequency and descriptives of survey data and findings from directed content analysis of interviews. We used a concurrent mixed-methods approach, integrating survey and interview data collected simultaneously using a joint display approach. A primary care community advisory board (CAB) helped to refine interview guides and interpret findings. RESULTS: Stakeholders described implementation determinants of the EBT related to the CFIR domains of intervention characteristics (relative advantage, adaptability), outer setting (patient needs and resources), inner setting (networks and communication, relative priority, leadership engagement, available resources), and individuals involved (knowledge and beliefs, cultural considerations). Stakeholders described strong attitudinal support (relative advantage), yet therapist time and capacity restraints are major PTSD treatment implementation barriers (available resources). Changes in hospital management were perceived as potentially allowing for greater access to behavioral health services, including EBTs. Patient engagement barriers such as stigma, mistrust, and care preferences were also noted (patient needs and resources). Recommendations included tailoring the intervention to meet existing workflows (adaptability), system alignment efforts focused on improving detection, referral, and care coordination processes (networks and communication), protecting clinician time for training and consultation (leadership engagement), and embedding a researcher in the practice (available resources). CONCLUSIONS: Our evaluation identified key CFIR determinants of implementation of PTSD treatments in safety net integrated primary care settings. Our project also demonstrates that successful implementation necessitates strong stakeholder engagement.

Dynamic BH3 profiling method for rapid identification of active therapy in BH3 mimetics resistant xenograft mouse models.

The clinical effectiveness of BH3 mimetics therapy is limited by the inevitable emergence of acquired resistance. We present a protocol to model in vivo acquired resistance to BH3 mimetics in patient-derived xenograft (PDX) mouse models of acute myeloid leukemia. Using resistant PDXs as a valuable model, we next introduce a protocol for dynamic BH3 profiling (DBP) method. DBP allows functional identification of effective drug therapies based on measurements of drug-induced apoptosis signaling to overcome in vivo BH3 mimetics resistance. For complete details on the use and execution of this protocol, please refer to Bhatt et al. (2020).