Citations

Abstract Introduction: Early relapse limits durable remissions in multiple myeloma (MM). Cell-free DNA (cfDNA) fragment patterns capture tumor burden and nucleosome positioning. We tested whether a fragmentomics signature trained at MRD time points stratifies progression-free survival (PFS) when applied to pretreatment plasma. Methods: We performed 30-40× whole-genome sequencing of plasma cfDNA from 43 newly diagnosed MM patients, with 65 additional MRD timepoint samples from 41 of those patients (post-ASCT n=30; 1-year maintenance n=30; other maintenance n=5) across eight Canadian sites (TFRIM4 and IMMAGINE studies) and one U.S. site (Mayo SPORE). MRD testing used multiparameter flow cytometry for all follow-up samples (n=65) and clonoSEQ in a subset (n=31). Logistic and elastic-net models were trained at MRD timepoints on fragmentomics features (short-fragment burden; a combined model integrating fragment-length distributions with inferred nucleosome positioning at MM-specific chromatin accessibility regions [Ordoñez et al., Genome Res. 2020]). A decision threshold was fixed by the Youden index during training and applied unchanged to diagnosis samples. PFS was analyzed by Kaplan-Meier, log-rank, and Cox models. Results: After a median follow-up of 49.1 months, 16 of 43 patients (37%) progressed. Using the prespecified locked threshold, patients classified as MRD+ by the proportion-of-short-fragments model had significantly shorter PFS than MRD- patients (HR = 5.12; 95% CI 1.16-22.57; log-rank p = 0.016), with median PFS of 49.2 months for MRD+ cases versus not reached for the MRD- group. Fixed-horizon PFS favored MRD- samples at 24/36/48 months (100/94/87% vs 85/81/53% for MRD+). A combined model integrating weighted fragment lengths with inferred nucleosome positioning also separated outcomes (log-rank p=0.054); the Cox HR was not estimable because no MRD- patients relapsed. At 24, 36, and 48 months, baseline MRD positivity by the short-fragment model identified 100%, 83%, and 86% of patients who relapsed within those intervals (specificity 44%, 43%, and 52%), while the combined model detected all early relapses across the same horizons (specificity 15-21%), indicating consistently high sensitivity but modest specificity for predicting early progression. Conclusions: A cfDNA fragmentomics signature trained at MRD time points stratified PFS when applied to diagnostic plasma, identifying patients at risk of early relapse. Short-fragment burden was most discriminative, and a combined model with nucleosome positioning recapitulated it with higher sensitivity, albeit lower specificity. These data support cfDNA fragmentomics as a practical liquid-biopsy risk biomarker in MM and suggest higher signals may proxy aggressive disease with greater tumor shedding and chromatin disorganization. Future work will validate findings in larger cohorts and integrate cytogenetic and immune features. Citation Format: Dor David Abelman, Jenna Eagles, Aimee Wong, Saumil Shah, Jeffrey Bruce, Stephanie Pedersen, David S. Scott, Cecilia Bonolo de Campos, Signy Chow, Darrell White, Irwindeed Sandhu, Kevin Song, Esteban Braggio, Shaji Kunnathu Kumar, Alli Murugesan, Tony Reiman, A. Keith Stewart, Suzanne Trudel, Trevor J. Pugh. Baseline cfDNA fragmentomics identifies multiple myeloma patients at risk of early progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2597.

Background: Hepatorenal syndrome–acute kidney injury (HRS-AKI) is associated with high mortality in cirrhosis. Recent FDA approval of terlipressin and updated clinical guidance have expanded management options, but real-world practice patterns remain unknown. Methods: We conducted a nationwide survey of U.S. hepatology providers regarding HRS-AKI management practices. The 33-question survey assessed provider demographics, vasoconstrictor selection, treatment timing, and adherence to guideline recommendations. Results: Among 162 respondents, most were hepatologists (94%) at academic centers (83%). Only 11% obtained a nephrology consultation at AKI detection, with 44% waiting until worsening renal function. Terlipressin was available at 80% of institutions but more commonly at academic centers (84% vs. 53%, p =0.003). Consistent with guideline recommendations, 77% of providers initiate vasoconstrictors only after completing a trial of volume expansion (if no renal improvement), particularly in academic centers (80% vs. 60% non-academic, p =0.03). Terlipressin (49%) and midodrine/octreotide (44%) were preferred first-line treatments, with providers at academic centers more likely to use midodrine/octreotide (46% vs. 30%, p =0.008). Mean arterial pressure was used by 62% of providers to guide vasoconstrictor dosing. Most providers (73%) discontinued vasoconstrictor treatment after 4 days if no improvement. Conclusions: Significant variations exist between guideline recommendations and real-world HRS-AKI management, especially first-line treatment choice, treatment monitoring, and nephrology consultation. These findings highlight opportunities to improve guideline implementation and identify areas where practice patterns might inform provider education and future guidance updates.

Liver macrophages are central in maintaining hepatic homeostasis and mediating immune responses during liver injury, including fibrosis. Macrophages may have proinflammatory or antiinflammatory properties, but which properties influence fibrosis remains unclear. To explore the role of macrophages in liver fibrosis, we performed single-cell RNA-seq in a mouse model of liver injury and found that macrophage diversity was increased. Marco was among the most significantly upregulated genes, and a population of Marco hi macrophages increased with injury and spatially segregated to nonfibrotic areas. The macrophage receptor with collagenous structure (MARCO) protein is a scavenger receptor expressed by specific subsets of macrophages, and its role in liver fibrosis is unclear. In vitro induction of Marco in bone marrow–derived macrophages decreased proinflammatory gene expression, increased antiinflammatory and antifibrotic gene expression, and enhanced phagocytosis, indicating a restorative phenotype. Adoptive transfer of MARCO + macrophages in a mouse model of liver fibrosis reduced the expression of extracellular matrix–associated (ECM-associated) genes in hepatic stellate cells (HSCs) and reduced collagen deposition, which did not occur with the transfer of MARCO – macrophages. Therefore, MARCO + macrophages have a tissue restorative role in the liver and attenuate fibrogenesis through interaction with HSCs, thereby providing a potential therapeutic pathway for liver fibrosis.

Abstract In epilepsy patients lacking magnetic resonance imaging‐visible lesions such as focal cortical dysplasia (FCD), surgical resections target regions with abnormal electroencephalographic (EEG) activity. However, histopathological identification of subtle cortical architectural abnormalities in these specimens remains challenging. We investigated whether artificial intelligence (AI)‐based morphometric and spatial analysis of NeuN‐stained cortical sections could detect neuronal architectural disorganization in epilepsy resections, including regions without definitive histologic dysplasia. Whole slide images were generated from 83 FCD regions and 19 neurologically normal autopsy controls. Regions of interest were annotated in QuPath as FCD, FCD‐adjacent, FCD‐distant, apparently normal (abnormal EEG without histologic dysplasia), and true normal (autopsy controls). NeuN‐positive neurons were detected using QuPath (90% sensitivity, 12% false positive rate). Spatial and morphometric features—including neuronal clustering, distribution inhomogeneity, and nuclear morphology—were extracted and used to train a multinomial, Least Absolute Shrinkage and Selection Operator‐regularized regression classifier. The classifier achieved 70.6% accuracy in subregion classification and 88.2% accuracy in overall specimen diagnosis. Notably, regions with abnormal EEG but lacking histologic dysplasia exhibited quantifiable architectural disorganization similar to those seen in areas adjacent to FCD and distinct from control tissue. AI‐driven analysis of neuronal morphology and spatial distribution reveals subtle cortical disorganization in epilepsy resections, including in histologically ambiguous regions. Further investigation is warranted to determine if this methodology can enhance the diagnostic yield of neuropathological evaluation and support more precise surgical targeting in epilepsy.

Objective This study evaluates the impact of international observerships organized by Help Ukraine Group (HUG) on professional development, knowledge transfer, and clinical practice improvement in radiation oncology in Ukraine. Methods A total of 50 observerships were facilitated for Ukrainian medical professionals at 14 institutions across the USA, Canada, Europe, and Australia from 2022 to 2024, including 31 radiation oncologists and medical physicists. A survey assessed their impact on oncology care, focusing on knowledge gained, lessons learned, and challenges in implementing new techniques. The primary outcome was the success score, defined as a composite score of implementing new procedures, initiating improvement projects, and knowledge dissemination efforts. Descriptive and comparative analyses examined satisfaction and success outcomes. Results A total of 43 respondents participated in the survey (response rate 86.0%). Twenty-eight of the responders were radiation oncology professionals (67.8% radiation oncologists, 32.1% medical physicists). The median observership duration for radiation oncology professionals was four weeks, with 96.4% also attending a professional conference. Overall satisfaction was high (mean 9.5 out of 10, median 10.0, IQR 9.0-10.0) while the success score was substantial (mean 6.1 out of 10, median 7.0, IQR 5.0-8.0). Time since certification influenced success, with ≥10 years’ experience associated with higher success scores (7.4 vs. 4.7, p=0.01). Importantly, 100% of respondents learned new procedures, 89.3% reported shifts in their clinical perspective, and 60.7% successfully implemented new techniques. Subsequent knowledge dissemination in Ukraine was substantial: 82.1% provided informal training, 60.7% delivered institutional or national presentations, 39.3% incorporated materials into lectures, and 10.7% engaged in all activities. Continued mentorship with host institutions was reported by 82.1%. Conclusions Amid the war, international observerships advanced clinical practice, education, and procedures in Ukraine, demonstrating the resilience of its medical community and providing a model that other LMICs/UMICs can follow.

ABSTRACT Background Acute heart failure (AHF) exhibits marked heterogeneity in diastolic hemodynamics, yet comprehensive echocardiographic assessment of diastolic function (DF) and filling pressure (FP) is often infeasible. We evaluated whether artificial intelligence–enabled electrocardiography (AI-ECG) could provide scalable DF grading and FP estimation in hospitalized AHF patients. Methods We retrospectively studied adults hospitalized for AHF across Mayo Clinic sites (2013–2023) who received ≥1 dose of intravenous loop diuretic and had paired 12-lead ECG and TTE. The previously validated AI-ECG DF model was applied without retraining to generate four DF grades and a continuous FP probability. Clinical outcomes were all-cause mortality and heart failure rehospitalization. Associations with clinical severity markers and echocardiographic indices were examined. Kaplan–Meier survival analysis and adjusted multivariable Cox proportional hazards models were performed. Exploratory analyses examine the kinetics of change in FP probability and impact on mortality. Results Among 11,513 patients (median age 75 years, 39% female), AI-ECG DF grading was feasible in 100%, whereas echocardiographic DF was indeterminate in 44% of clinically eligible patients. In 2,582 patients with determinate echocardiographic DF, AI-ECG FP probability discriminated TTE Grade 2–3 dysfunction with AUC 0.85 (95% CI 0.83 – 0.86). Higher AI-ECG DF grades were associated with higher comorbidity burden, worse NYHA class, elevated NT-proBNP, higher MAGGIC scores, elevated PCWP, and more advanced structural remodeling. After multivariable adjustment, AI-ECG DF remained independently associated with mortality (hazard ratio [HR] 1.25, 95% CI 1.16–1.35 for Grade 2; HR 1.44, 95% CI 1.33–1.56 for Grade 3 versus Normal/Grade 1). Combining AI-ECG DF with MAGGIC scores yielded ordered risk gradients, with highest mortality in patients with both high MAGGIC and Grade 2–3 DF. Among patients with serial ECGs, improvement in FP probability was independently associated with lower mortality (HR 0.85, 95% CI 0.79–0.91), whereas worsening did not show a consistent adverse gradient beyond baseline DF. Conclusions In a large, geographically diverse AHF cohort, AI-ECG DF grading was universally feasible, correlated with established hemodynamic severity markers, and provided independent prognostic information beyond established risk factors, supporting its role as a pragmatic, scalable diastolic biomarker in AHF. CLINICAL PERSPECTIVE What Is New? In 11,513 hospitalized acute heart failure (HF) patients, artificial intelligence-enabled electrocardiography provided diastolic function grading in 100% of patients from a single 12-lead ECG without requiring additional clinical variables, compared with 56% feasibility for guideline-based echocardiography grading. AI-ECG diastolic function grades correlated with established marker of severity (NYHA functional class, NT-proBNP, MAGGIC risk scores, and pulmonary capillary wedge pressure) and remained independently associated with both mortality and HF rehospitalization after multivariable adjustment. Serial AI-ECG measurements identified post-discharge filling pressure trajectories, with improvement independently associated with 15% lower mortality, a first demonstration that longitudinal ECG assessment can track post-discharge hemodynamic recovery. What Are the Clinical Implications? AI-ECG transforms the universally obtained 12-lead ECG into an actionable hemodynamic biomarker that addresses the critical gap when echocardiographic diastolic function assessment is indeterminate or unavailable in acute HF patients. Despite markedly different hemodynamic severity and long-term outcomes across AI-ECG diastolic function grades, hospitalization length of stay did not differ, suggesting advanced diastolic dysfunction represents occult risk not easily recognized during routine acute care and highlighting the need for improved post-discharge risk stratification. The continuous filling pressure probability metric enables longitudinal monitoring of post-discharge hemodynamic status using serial routine ECGs, potentially identifying patients requiring intensified follow-up or specialist referral.

INTRODUCTION: Despite the widespread use of ursodeoxycholic acid (UDCA) in primary biliary cholangitis (PBC), many patients remain at risk of progression. Emerging data suggest that normalization of alkaline phosphatase (ALP) and total bilirubin (TB)—particularly when TB < 0.6 times the upper limit of normal (× ULN)—is associated with improved outcomes compared with ALP reduction to < 1.5 × ULN. This study investigated the association between ALP normalization in response to UDCA and long-term clinical outcomes in a real-world cohort of patients with PBC. METHODS: We compared complication-free survival in patients achieving an ALP > ULN and < 1.5 × ULN (adequate response) with those with an ALP ≤ ULN on UDCA monotherapy. Complication-free survival was defined as the absence of serious liver-related clinical events. Restricted mean survival time was used to quantify survival time gained. RESULTS: Patients achieving normal ALP and/or TB ≤ 0.6 × ULN demonstrated significantly improved complication-free survival compared with those with an adequate ALP response. Event-free survival was extended by 1.34 years (95% CI: 0.56, 2.11; P = 0.001) for ALP normalization alone, 3.7 years (95% CI: 3.11, 4.29; P < 0.001) for TB ≤ 0.6 × ULN, and 4.51 years (95% CI: 4.13, 4.88; P < 0.001) for those meeting both criteria. The risk of severe clinical events was reduced in patients achieving ALP normalization (hazard ratio [HR] 0.34; 95% CI: 0.15, 0.80; P = 0.01), TB ≤ 0.6 × ULN (HR 0.23; 95% CI: 0.09, 0.55; P = 0.001), or both (HR 0.14; 95% CI: 0.05, 0.38; P < 0.001). High-risk patients, defined by liver stiffness measurement ≥ 10 kPa or clinical, histological, or laboratory evidence of cirrhosis or portal hypertension, derived the greatest benefit. DISCUSSION: Achieving normal ALP and TB ≤ 0.6 × ULN is associated with significantly improved complication-free survival, particularly in high-risk patients. These findings highlight the potential of biochemical thresholds as a meaningful therapeutic goal in PBC management.

Background and Aims: Liver transplantation has evolved from a treatment restricted to patients with end-stage liver disease to a therapeutic option for selected patients with primary and metastatic liver malignancies. This review explores the rapidly expanding field of transplant oncology, highlighting its role in hepatocellular carcinoma, colorectal liver metastasis, neuroendocrine liver metastasis, and intrahepatic and perihilar cholangiocarcinoma. Emphasis is placed on strategies to broaden eligibility, optimize donor organ use, and improve oncologic outcomes. Approach and Results: We synthesized current evidence from clinical series, registries, and experimental protocols to evaluate patient selection criteria, outcomes, and peri-transplant management. Key topics include downstaging approaches to meet transplant criteria, such as locoregional therapies and systemic regimens, and their prognostic implications. Advances in donor utilization have been analyzed for their capacity to expand the graft pool. In addition, the review addresses the integration of oncologic principles into immunosuppression regimens, balancing graft protection with cancer control. Collectively, the reported studies demonstrate improved survival and reduced recurrence when stringent selection and multimodal therapy were applied. Conclusions: Transplant oncology reshapes the therapeutic landscape of liver malignancies, with growing evidence supporting liver transplantation in carefully selected patients beyond traditional indications. Optimized downstaging, innovative donor strategies, and tailored immunosuppression are pivotal for safe expansion. Continued collaboration between the transplant and oncology disciplines, along with prospective trials, is essential to further define standardized protocols and solidify transplantation as a cornerstone of multidisciplinary cancer care.