Kapoor, Shweta

The effectiveness of in-person psychological interventions for chronic pain populations has been widely studied. The current retrospective pilot study evaluates the effectiveness of a 10-week integrative telehealth pain group intervention consisting of cognitive, behavioral, mindfulness, and lifestyle strategies on anxiety, depression, pain catastrophizing, pain interference, and pain intensity. Participants at a large multidisciplinary hospital are referred internally from various medical departments within the hospital. The present study consists of data from 9 group cohorts from October 2020 to June 2022. The study included 86 patients, with 52 completing all 10 weeks of the intervention with post-questionnaire data available. Measures assessing anxiety, depression, pain catastrophizing, pain interference, and pain intensity at baseline and at the completion of the intervention. A series of paired samples t-tests were used to assess change in each outcome measure from baseline to after completion of the program. All the outcome variables including anxiety, depression, pain interference, pain intensity, and pain catastrophizing showed statistically significant reductions after the intervention compared to baseline assessments. There were no significant differences in any of the demographic variables (age, gender, ethnicity, education level) or chronic pain condition between participants who did and did not complete the program. Preliminary data suggest that this 10-week integrative telehealth pain group intervention significantly lowered anxiety, depression, pain catastrophizing, pain interference, and pain intensity from pre- to post-intervention. Larger, randomized controlled studies are needed to validate these results.

Prescribed opioids are a mainstay pain treatment after traumatic injury, but a subgroup of patients may be at risk for continued opioid use. We evaluated the predictive utility of a traditional screening tool, the Opioid Risk Tool (ORT), and two other measures: average in-hospital milligram morphine equivalents (MME) per day and an assessment of opioid demand in predicting pain outcomes. Assessments of pain-related outcomes (pain intensity, interference, injury-related stress, and need for additional pain treatment) were administered at 2 weeks and 12 months post-discharge in a sample of 34 patients hospitalized for traumatic injury. Bayesian linear models were used to evaluate changes in responses over time as a function of predictors. High-risk ORT, higher MME per day, and greater opioid demand predicted less change in outcomes over time. This report provides first evidence that malleable factors of opioid and opioid demand have utility in predicting pain outcomes following traumatic injury.

Abstract Background: The concept of treatment personalization in cancer often means associating a drug with an actionable mutation. One limitation of this approach is that most tumors have multiple aberrations, which are not actionable. Here we present a predictive simulation based approach which models the molecular architecture and resulting physiology of advanced stage Waldenströms Macroglobulinemia (WM, a B-lymphoplasmacytic lymphoma) as well as the design of novel personalized treatments using existing drug agents for rapid clinical translation with validations. Methods: We used the human WM cell line, RPCI-WM1, as a surrogate model of refractory, advanced patient sub-groups. Publically available as well as proprietary genomic and cytogenetic data was utilized for the creation of an avatar of RPCI-WM1, which through simulation identified the salient and prominently dysregulated cellular pathways. Importantly, illustrating these pathways highlights common convergence points on increased proliferation and viability. These convergence points were then directly and indirectly targeted by simulated testing of a library of FDA approved drugs and those impacting these dysregulated pathways were shortlisted. Importantly, this simulation avatar approach not only looks for agents acting on the specific gene mutation, but also predicts the convergence points to be attacked. The personalized simulation avatar technology is a comprehensive functional proteomics representation of WM physiology network. A standardized library of equations models all the biological reactions such as enzymatic reactions, allosteric binding and protein modulation by phosphorylation, de-phosphorylation, ubiquitination, acetylation, prenylation and others. A library of over 150 digital functional library of FDA approved drug agents and those in clinical study has been developed and was simulated individually and in combination on the RPCI-WM1 (advanced stage WM patient) avatar. Results: Overall, there were 272 gene aberrations used to create the RPCI-WM1 simulation avatar. Importantly, presence of MYD88L265P mutation, absence of CXCR4 mutations and additional chromosomal aberrations (derivatives, translocations, deletions and amplifications of chromosomes 3, 6, 9, 13, 18 and 19) were taken into account. The RPCI-WM1 patient avatar predicted increased IRAK1/4 engagement due to MYD88 mutation and high copy number (CN) of IL18, to increased NFkB via TAK1, and increased ERK signaling through IRAK1/4 mediated down regulation of DUSP1. The RPCI-WM1 model also indicated high AKT due to indirect convergence of multiple aberrations. Another key characteristic of the genomic aberrations driving proliferative phenotype was low CN of RB1, FOXO3, CDKN2A, CDKN2B, and CEBPa. Modeling predicted sensitivity to the aurora kinase (AURKA) inhibitor, tozasertib and resistance to cell cycle cyclin D-CDK4/6 pathway inhibitors., Although there was no CN variation in AURKA, as per simulation its expression and activity was upregulated due to high CN of ETS1 and PAK1 and increased activation of NFkB, HIF1A and STAT5 in the disease network. Despite high proliferation, LEE011 (representative CDK4/6 inhibitor) was predicted to exert no cytotoxic effect, due to the presence of an RB1 deletion. Through phosphorylation of RB1, the CDK4-CyclinD1 complex aids in release of E2F1 from the RB1 sequestered complex, to drive proliferation. However, predictive modeling suggested that with an RB1 deletion present, this regulation becomes irrelevant and therefore the inhibition of the CDK4/6-CyclinD1 complex would be ineffective. The simulation predictions were experimentally validated. As predicted, AURKA inhibition with tozasertib significantly inhibited viability and proliferation of RPCI-WM1 cells (IC50 ~7nM) whereas inhibition of CDK4/6 with LEE011 had no effect on tumor cell survival. Conclusions: This study demonstrates the utility of a novel technology for rapid translation of a (WM) genetic signature towards a personalized therapeutic strategy. This simulation avatar based approach holistically integrates all genomic aberration information to design personalized therapies architected from FDA approved and/or clinical drug agents with therapeutic potential for WM patients based on unique genetic signatures. Disclosures Vali: CellWorks: Employment. Kumar:CellWorks: Employment. Singh:CellWorks: Employment. Kapoor:Cellworks Research India Limited: Employment. Abbasi:CellWorks: Employment, Equity Ownership.