Citations

Background: Integrating machine learning (ML) with population pharmacokinetic (PPK) modeling may improve therapeutic drug monitoring predictions. Methods: Tacrolimus trough concentrations from lung transplant patients were split into a training data set (1151 concentrations in 80 patients) and a testing data set (224 concentrations in 20 patients). A PPK model was developed using NONMEM, followed by the development of 10 ML models to fit individual pharmacokinetic parameters from the PPK model with Bayesian forecasting. The best performing ML model was selected as the final model. Both the final PPK and ML models were compared for prediction performance. A web-based dashboard was established with R-shiny to recommend dosing regimens based on patient data. Results: In the PPK model, postoperative days, hematocrit, aspartate aminotransferase, tacrolimus daily dose, coadministered voriconazole or posaconazole, and the CYP3A5*3 genotype were identified significant covariates on the clearance. The Cubist ML model outperformed the PPK model, showing lower root mean squared error for tacrolimus concentrations in the testing data set. An online web-based precision dosing dashboard was created, accessible at (https://tac-dose-ml.shinyapps.io/shiny/). Conclusions: Integrating ML with PPK modeling could yield superior tacrolimus concentration predictions for lung transplant patients, offering an efficient alternative to Bayesian forecasting. The online dashboard provides rapid, individualized dosing recommendations.

Patients with plasma cell leukemia (PCL) are generally excluded from pivotal T-cell redirecting bispecific antibody (BsAb) trials. We evaluated real-world outcomes in a multicenter retrospective study of 122 patients with primary or secondary PCL across 15 academic centers, categorized as 'active' (≥5% circulating plasma cells within 30 days of BsAb initiation) or 'historical'. In a heavily pretreated population, patients received teclistamab (37%), elranatamab (11%), talquetamab as a line of therapy (Tal LOT, 42%), or talquetamab as bridging therapy to CAR-T (Tal Bridge, 11%). Cytokine release syndrome (CRS) was grade 1-2 in 56% and grade 3-4 in 4%, whereas neurotoxicity was grade 1-2 in 16% and grade 3-4 in 5%. Among 110 evaluable patients, the overall response rate (ORR) was 55%, including 61% with Tal LOT, 58% with Tal Bridge, 46% with elranatamab, and 33% with teclistamab. With a median follow-up of 8.3 months, talquetamab demonstrated superior survival. Tal LOT showed a median progression-free survival (mPFS) of 5.5 months and a median overall survival (mOS) of 11.5 months, and both were unreached in the Tal Bridge cohort. In contrast, teclistamab and elranatamab showed a mPFS of 1.2 and 1.6 months and mOS of 8.1 and 3.6 months, respectively (P=0.007, P=0.023). In active PCL, Tal LOT achieved mPFS/mOS of 6.9/12.2 months versus 0.7/1.4 months with teclistamab and 1.0/3.1 months with elranatamab, respectively (P<0.001, P=0.002). Multivariable analysis associated active PCL with worse survival and Tal LOT with improved outcomes. BsAbs were safe in PCL, with talquetamab showing superior outcomes compared with BCMA-directed BsAbs.

ABSTRACT Introduction Chronic gastroduodenal disorders remain challenging to manage, and new diagnostic approaches are needed to better delineate underlying causes and guide therapeutic decisions. Body Surface Gastric Mapping (BSGM) technologies combine high‐resolution gastric myoelectrical activity measurements with symptom and psychological profiling to provide mechanistic insights into gastric motor and sensory dysfunction. An International Working Group convened to derive the first consensus classification of BSGM phenotypes (the “Auckland Classification”). Methods A Technical Group conducted a systematic literature and clinical database review to identify objective test biomarkers and candidate disease mechanisms. Evidence was synthesized across 50 studies (primarily in gastroparesis, chronic nausea and vomiting, and functional dyspepsia), and BSGM phenotypes were mapped to existing treatment guidelines. Subsequently, iterative review and development of consensus was performed by a Consensus Group composed of international clinical experts familiar with BSGM. Eleven statements underlying the classification were then derived and circulated as a final survey to establish agreement. Results Six BSGM phenotypes were endorsed: three defined by myoelectrical abnormalities (Dysrhythmic, High Frequency, and Low Meal Response) and three by characteristic symptom associations (Sensorimotor, Continuous, and Delayed Onset Symptoms). Published studies plausibly linked these phenotypes to mechanisms including interstitial cell of Cajal depletion, vagal impairment, hypomotility, visceral hypersensitivity, gut‐brain dysregulation, and small bowel dysfunction. Phenotypes were also mapped to existing mechanism‐based treatment guidelines. Ten out of the eleven statements had > 80% agreement. Conclusions The Auckland Classification, derived by international consensus, presents a structured framework for BSGM‐defined patient phenotypes. Evidence and mechanism‐based treatment options are suggested for each phenotype to provide a foundation for research, further validation, and a pathway for integrating BSGM into clinical care.

Abstract Background: Antigen receptor stimulation induces assembly of the CARMA1-BCL10-MALT1 (CBM) signaling complex, which leads to activation of downstream transcriptional regulators including NF-κB and subsequent lymphocyte activation. Gain-of-function mutations in B-cell receptor subunits, CARMA1, or BCL10 which lead to constitutive activation of MALT1 underly the pathogenesis of multiple lymphoid malignancies, including activated B-cell–type diffuse large B-cell lymphoma (ABC-DLBCL). During previous efforts to identify regulators of MALT1 activity in lymphocytes, we discovered that G-protein-coupled receptor kinase 2 (GRK2) binds to MALT1, inhibits MALT1 scaffolding and proteolytic activities, and functions as a tumor suppressor in MALT1-dependent lymphomas. Notably, GRK2 mRNA expression is markedly lower in a subset of DLBCL tumors in comparison to normal B cells and lower GRK2 is associated with decreased patient survival in ABC-DLBCL. In light of these findings, we investigated the molecular mechanisms regulating GRK2 expression and then characterized the roles of specific GRK2-targeting miRNAs in ABC-DLBCL. Methods and Results: After finding that global impairment of miRNA processing through DICER1 depletion leads to increased GRK2 protein, we conducted bioinformatic analyses of patient tumor samples and microRNA Data Integration Portal screening to identify candidate microRNAs that target GRK2 in ABC-DLBCL. Direct targeting of GRK2 by candidate miRNAs was then confirmed by GRK2 3’UTR reporter assay. We tested for expression of three candidate microRNAs in ABC-DLBCL cells and observed elevated expression in both OCI-LY3 and TMD8 cells, which exhibited reduced GRK2 mRNA expression compared with primary B cells. Inhibition of candidate miRNAs in ABC-DLBCL cells, using anti-miRNA Locked Nucleic Acids (LNA) inhibitors, led to enhanced GRK2 expression, reduced MALT1 activity and decreased cell proliferation. Conversely, stable overexpression of candidate microRNAs led to reduced GRK2 expression, enhanced MALT1 activity and increased cell proliferation. In vivo, treatment of mice with inhibitors of candidate microRNAs abrogates the growth of ABC-DLBCL xenograft tumors. Conclusion: We have identified three miRNAs that negatively regulate GRK2 expression in ABC-DLBCL. By targeting GRK2 for downregulation, these miRNAs promote MALT1 oncoprotein scaffold and protease activities. Furthermore, inhibitors of these miRNAs enhance GRK2 expression and thereby suppress MALT1 activity and MALT1-dependent tumor cell proliferation in vitro and inhibit MALT1-dependent tumor growth in vivo. MicroRNA inhibitors that enhance GRK2 expression could represent a new approach for restraining MALT1-dependent lymphoma. Citation Format: Jing Cheng, Mei Smyers, Matt Trotta, Neil M. Carleton, Lisa M. Maurer, Uma R. Chandran, Min Xia, Ari M. Melnick, Peter C. Lucas, Linda M. McAllister-Lucas. Inhibitors of GRK2-targeting-microRNAs: New therapeutic strategies for MALT1-dependent lymphomas [abstract]. In: Proceedings of the Fifth AACR International Meeting on Advances in Malignant Lymphoma: From Discovery to Clinical Impact; 2026 Jun 24-27; Philadelphia, PA. Philadelphia (PA): AACR; Blood Cancer Discov 2026;7(3_Suppl):Abstract nr A033.

Abstract Objective . Phase gating is a critical technique to mitigate tumor motion during radiotherapy, particularly in spot-scanned particle therapy where internal motion can interfere with dynamic spot scanning patterns and, simultaneously, introducing substantial range uncertainties. However, the current commercial state of the art in real-time phase prediction is challenged by patient-specific breathing variability as well as detection and delivery system latencies. This leads to suboptimal efficiency, mis-timed radiation delivery and requires frequent manual intervention. This study aims to improve phase prediction accuracy using deep learning (DL)-based time series forecasting to enable more accurate dose delivery. Approach . Retrospective breathing waveforms from 69 proton therapy patients, sampled at 30 Hz, were labeled with inspiratory peaks and assigned subjective regularity scores (four levels). DL models with various architectures were trained using waveform amplitude to predict current or future breathing phases. Model performance was evaluated using mean squared error, phase binning accuracy, and timing deviation for radiation on/off events. Bayesian optimization was used for hyperparameter tuning. Results were compared between models and against a commercial algorithm currently in clinical use. Main Results . The curated waveform dataset included 165 242 s for training, 24 057 s for validation, and 30 322 s for testing, with an additional 40 604 s from separate patients for extended validation. The long short-term memory and temporal fusion transformer models significantly outperformed the commercial algorithm, improving phase prediction accuracy by nearly 20% and reducing timing deviations across all regularity levels. Significance . DL-based time series forecasting may substantially improve breathing phase prediction accuracy over current clinically available methods, offering a more precise and reliable approach to phase-gated radiation delivery.

Transitions from inpatient rehabilitation to home critically affect patient recovery and caregiver well-being. Social determinants of health (SDoH) shape these outcomes yet remain underexamined in rehabilitation settings. The objective of this study was to examine the prevalence of SDoH on patient and caregiver experiences during the first 30 days following discharge from a multi-site inpatient rehabilitation facility in the southeastern United States and explore patterns of patient satisfaction and caregiver burden that can influence care transitions. A prospective cross-sectional descriptive study surveyed 61 patients and 50 caregivers using validated instruments assessing SDoH, communication, discharge preparedness, and caregiver burden. Social isolation, affecting 18% of patients and 10% of caregivers, was the most prevalent challenge. Additional challenges include health literacy and transportation barriers. Caregivers experienced substantial burden: 60% decline in social activities, 50% decreased energy, and 40.9% negative physical health effects. However, 58.1% reported strengthened patient relationships. This study identifies the importance of care continuity and SDoHs after inpatient rehabilitation. Interdisciplinary interventions focused on these key challenges are essential for improving outcomes.

Background: Alcohol-associated hepatitis (AH) is a severe inflammatory liver condition driven by dysregulated immune responses. CD8 T cells accumulate in the liver during AH, yet their functional role remains poorly defined. Methods: A murine NIAAA chronic-binge model with lipopolysaccharide (LPS) challenge was used. Single-cell RNA sequencing of liver and blood immune cells defined CD8 T cell subsets, followed by pathway analysis and reanalysis of human AH datasets. Spatial relationships were validated by immunohistochemistry of human AH liver tissue with CD8 T RM and liver sinusoidal endothelial cell (LSEC) co-staining. LSEC–CD8 T cell interactions were examined using in vitro co-culture, and signaling pathways were assessed by bulk RNA sequencing and phospho-protein analyses. IL15 function was evaluated by in vivo neutralization. Results: Single-cell RNA sequencing in the murine AH model revealed a distinct population of CD8 tissue-resident memory T cells (T RM ) with heightened activation and proinflammatory cytokine production. Analysis of human AH liver single-cell RNA sequencing data, along with immunohistochemistry validation, supported CD8 T RM enrichment in diseased tissue. IL15 emerged as a prominent pathway linked to T RM activation, and IL15 blockade reduced T RM abundance and attenuated EtOH/ lipopolysaccharide-induced liver injury. Mechanistically, LSECs not only provided a structural niche for T RM retention but also amplified IL15 signalling. In vitro, coculture experiments demonstrated that LSECs intensified activation in pre-stimulated CD8 T cells in a stimulus-dependent manner: under IL15 stimulation, LSECs boosted effector function without inducing cell death, whereas under T-cell receptor stimulation, LSECs drove hyperactivation and activation-induced cell death. Bulk RNA-seq and phospho-protein analysis identified the PI3K-AKT pathway as a shared pathway enhanced by LSEC coculture in activated CD8 T cells. These findings define a context-dependent mechanism in which LSECs promote IL15-driven signaling through AKT pathway amplification, promoting T RM persistence and inflammatory activity in AH. Conclusions: IL15-associated signaling within the hepatic microenvironment, shaped by LSEC-CD8 T-cell interactions, promotes activation and persistence of CD8 T RM cells in AH. Targeting the IL15-LSEC-AKT axis may disrupt pathogenic T RM niches and represent a promising therapeutic strategy for severe AH.

Abstract The minichromosome maintenance 2-7 (MCM2-7) proteins form a hexameric protein complex that is the structural core of replicative helicase, which is essential for accurate DNA replication. While their role in replication is well-established, the biological functions of excess chromatin-bound MCM2-7 proteins remain unclear. Here, we identify a transcriptional regulatory function of MCM2-7 through its interaction with nuclear factor κB (NF-κB) p65. We demonstrate that MCM2-7 proteins and NF-κB p65 reciprocally recruit each other to target gene promoters. Consequently, MCM2-7 proteins facilitate the localization of RNA Pol II to NF-κB target gene promoters and along the gene body, thereby promoting transcription of NF-κB target genes. These findings reveal MCM2-7 proteins promote NF-κB target gene transcription by facilitating p65 and RNA Pol II recruitment, offering a potential avenue for fine-tuning NF-κB target gene transcription.