Single-cell panleukemia signatures of HSPC-like blasts predict drug response and clinical outcome.

The critical role of leukemic initiating cells as a therapy-resistant population in myeloid leukemia is well established, however, the molecular signatures of such cells in acute lymphoblastic leukemia remain underexplored. Moreover, their role in therapy response and patient prognosis is yet to be systematically investigated across various types of acute leukemia. We employed single-cell multiomics to analyze diagnostic specimens from 96 pediatric patients with acute lymphoblastic, myeloid, and lineage ambiguous leukemias.

Native stem cell transcriptional circuits define cardinal features of high-risk leukemia.

While the mutational landscape across early T-cell precursor acute lymphoblastic leukemia (ETP-ALL) and ETP-like leukemia is known, establishing a unified framework that activates stem cell genes characteristic of these tumors remains elusive. Using complementary mouse and human models, chromatin mapping, and enhancer profiling, we show that the coactivator ZMIZ1 promotes normal and malignant ETP population growth by inducing the transcription factor MYB in feedforward circuits to convergently activate oncogenes (MEF2C, MYCN, and BCL2) through essential enhancers. A key superenhancer, the N-Myc regulating enhancer (NMRE), drives malignant ETP population growth but is dispensable for normal lymphopoiesis.

Targeting senescent stemlike subpopulations in Philadelphia chromosome-like acute lymphoblastic leukemia.

Philadelphia chromosome-like B-cell acute lymphoblastic leukemia (Ph-like ALL) is driven by genetic alterations that induce constitutive kinase signaling and is associated with chemoresistance and high relapse risk in children and adults. Preclinical studies in the most common CRLF2-rearranged/JAK pathway-activated Ph-like ALL subtype have revealed variable responses to JAK inhibitor-based therapies, suggesting incomplete oncogene addiction and highlighting a need to elucidate alternative biologic dependencies and therapeutic vulnerabilities, whereas the ABL-class Ph-like ALL subtype seems preferentially sensitive to SRC/ABL- or PDGFRB-targeting inhibitors. Which patients may be responsive vs resistant to tyrosine kinase inhibitor (TKI)-based precision medicine approaches remains a critical knowledge gap.

A multiomic atlas identifies a treatment-resistant, bone marrow progenitor-like cell population in T cell acute lymphoblastic leukemia.

Refractoriness to initial chemotherapy and relapse after remission are the main obstacles to curing T cell acute lymphoblastic leukemia (T-ALL). While tumor heterogeneity has been implicated in treatment failure, the cellular and genetic factors contributing to resistance and relapse remain unknown. Here we linked tumor subpopulations with clinical outcome, created an atlas of healthy pediatric hematopoiesis and applied single-cell multiomic analysis to a diverse cohort of 40 T-ALL cases.

Prevalence and Prognostication of CD5+ Mature T-Cell Lymphomas.

T-cell lymphomas (TCLs) are a group of heterogenous cancers with poor rates and duration of response. There remains a great challenge in risk stratification of these cancers. Cluster of differentiation (CD) 5 has shown prognostic implication in many subtypes of B-cell lymphoma; however, its role in TCLs is not known.

Orthopedic Injections: A Longitudinal Musculoskeletal Curriculum in a Family Medicine Residency.

Background And Objectives: Musculoskeletal (MSK) complaints comprise more than 20% of all visits to health care providers each year. Despite required experiences in MSK care, family physicians report low confidence in diagnosing and treating MSK conditions. The purpose of this study was to analyze the effects of early and longitudinal exposure to MSK education on residents' confidence in and likelihood of performing MSK physical exams and injections in future practice.

The genomic basis of childhood T-lineage acute lymphoblastic leukaemia.

T-lineage acute lymphoblastic leukaemia (T-ALL) is a high-risk tumour that has eluded comprehensive genomic characterization, which is partly due to the high frequency of noncoding genomic alterations that result in oncogene deregulation. Here we report an integrated analysis of genome and transcriptome sequencing of tumour and remission samples from more than 1,300 uniformly treated children with T-ALL, coupled with epigenomic and single-cell analyses of malignant and normal T cell precursors. This approach identified 15 subtypes with distinct genomic drivers, gene expression patterns, developmental states and outcomes.

Stochastic EM algorithm for partially observed stochastic epidemics with individual heterogeneity.

We develop a stochastic epidemic model progressing over dynamic networks, where infection rates are heterogeneous and may vary with individual-level covariates. The joint dynamics are modeled as a continuous-time Markov chain such that disease transmission is constrained by the contact network structure, and network evolution is in turn influenced by individual disease statuses. To accommodate partial epidemic observations commonly seen in real-world data, we propose a stochastic EM algorithm for inference, introducing key innovations that include efficient conditional samplers for imputing missing infection and recovery times which respect the dynamic contact network.

Enrollment Trends Among Patients with Melanoma Brain Metastasis in Active Clinical Trials.

The CNS is a common site for distant metastasis and treatment failure in melanoma patients. This study aimed to evaluate the inclusion rate of patients with melanoma brain metastases (MBM) in prospective clinical trials. 69.

Mapping the cellular biogeography of human bone marrow niches using single-cell transcriptomics and proteomic imaging.

Non-hematopoietic cells are essential contributors to hematopoiesis. However, heterogeneity and spatial organization of these cells in human bone marrow remain largely uncharacterized. We used single-cell RNA sequencing (scRNA-seq) to profile 29,325 non-hematopoietic cells and discovered nine transcriptionally distinct subtypes.

Diagnosis, management, and outcomes of immune checkpoint inhibitor induced acute interstitial nephritis: A single-center experience.

Background: Immune checkpoint inhibitor (ICI)-associated acute interstitial nephritis (AIN) is a recognized complication of immunotherapy (IO), but literature on its management and outcomes is limited.

Methods: We retrospectively reviewed patients who received ICIs and developed biopsy-proven or clinically-suspected ICI-associated AIN at the University of Virginia Comprehensive Cancer Center from 2012-2023. We analyzed baseline characteristics and clinical outcomes, including treatment interruption and rechallenge rates.

Multiplexed Imaging Mass Cytometry Analysis Characterizes the Vascular Niche in Pancreatic Cancer.

Oncogenesis and progression of pancreatic ductal adenocarcinoma (PDAC) are driven by complex interactions between the neoplastic component and the tumor microenvironment, which includes immune, stromal, and parenchymal cells. In particular, most PDACs are characterized by a hypovascular and hypoxic environment that alters tumor cell behavior and limits the efficacy of chemotherapy and immunotherapy. Characterization of the spatial features of the vascular niche could advance our understanding of inter- and intratumoral heterogeneity in PDAC.

All-trans retinoic acid induces durable tumor immunity in IDH-mutant gliomas by rescuing transcriptional repression of the CRBP1-retinoic acid axis.

Diffuse gliomas are epigenetically dysregulated, immunologically cold, and fatal tumors characterized by mutations in isocitrate dehydrogenase (IDH). Although IDH mutations yield a uniquely immunosuppressive tumor microenvironment, the regulatory mechanisms that drive the immune landscape of IDH mutant (IDHm) gliomas remain unknown. Here, we reveal that transcriptional repression of retinoic acid (RA) pathway signaling impairs both innate and adaptive immune surveillance in IDHm glioma through epigenetic silencing of retinol binding protein 1 (RBP1) and induces a profound anti-inflammatory landscape marked by loss of inflammatory cell states and infiltration of suppressive myeloid phenotypes.

The FDA Reclassification of Cervical Pedicle and Lateral Mass Screws: A Case Study in Regulatory History.

The classification of medical devices by the Food and Drug Administration (FDA) involves rigorous scrutiny from specialized panels that designate devices as Class I, II, or III depending on their levels of relative risk to patient health. Posterior rigid pedicle screw systems were first classified by the FDA in 1984 and have since revolutionized the treatment of many spine pathologies. Despite this early classification by the FDA, posterior cervical pedicle and lateral mass screws were not reclassified from unclassified to Class III and then to Class II until 2019, nearly 35 years after their initial classification.

Multiomics Analysis of PCB126's Effect on a Mouse Chronic-Binge Alcohol Feeding Model.

Background: Environmental pollutants, including polychlorinated biphenyls (PCBs) have been implicated in the pathogenesis of liver disease. Our group recently demonstrated that PCB126 promoted steatosis, hepatomegaly, and modulated intermediary metabolism in a rodent model of alcohol-associated liver disease (ALD).

Objective: To better understand how PCB126 promoted ALD in our previous model, the current study adopts multiple omics approaches to elucidate potential mechanistic hypotheses.

A unified analysis of convex and non‑convex ‑ball projection problems.

The task of projecting onto norm balls is ubiquitous in statistics and machine learning, yet the availability of actionable algorithms for doing so is largely limited to the special cases of . In this paper, we introduce novel, scalable methods for projecting onto the -ball for general . For , we solve the univariate Lagrangian dual via a dual Newton method.

A longitudinal single-cell and spatial multiomic atlas of pediatric high-grade glioma.

Pediatric high-grade glioma (pHGG) is an incurable central nervous system malignancy that is a leading cause of pediatric cancer death. While pHGG shares many similarities to adult glioma, it is increasingly recognized as a molecularly distinct, yet highly heterogeneous disease. In this study, we longitudinally profiled a molecularly diverse cohort of 16 pHGG patients before and after standard therapy through single-nucleus RNA and ATAC sequencing, whole-genome sequencing, and CODEX spatial proteomics to capture the evolution of the tumor microenvironment during progression following treatment.

Detecting changes in the transmission rate of a stochastic epidemic model.

Throughout the course of an epidemic, the rate at which disease spreads varies with behavioral changes, the emergence of new disease variants, and the introduction of mitigation policies. Estimating such changes in transmission rates can help us better model and predict the dynamics of an epidemic, and provide insight into the efficacy of control and intervention strategies. We present a method for likelihood-based estimation of parameters in the stochastic susceptible-infected-removed model under a time-inhomogeneous transmission rate comprised of piecewise constant components.

Inferring HIV transmission patterns from viral deep-sequence data via latent typed point processes.

Viral deep-sequencing data play a crucial role toward understanding disease transmission network flows, providing higher resolution compared to standard Sanger sequencing. To more fully utilize these rich data and account for the uncertainties in outcomes from phylogenetic analyses, we propose a spatial Poisson process model to uncover human immunodeficiency virus (HIV) transmission flow patterns at the population level. We represent pairings of individuals with viral sequence data as typed points, with coordinates representing covariates such as gender and age and point types representing the unobserved transmission statuses (linkage and direction).

A proximal distance algorithm for likelihood-based sparse covariance estimation.

This paper addresses the task of estimating a covariance matrix under a patternless sparsity assumption. In contrast to existing approaches based on thresholding or shrinkage penalties, we propose a likelihood-based method that regularizes the distance from the covariance estimate to a symmetric sparsity set. This formulation avoids unwanted shrinkage induced by more common norm penalties, and enables optimization of the resulting nonconvex objective by solving a sequence of smooth, unconstrained subproblems.

Identification and targeting of treatment resistant progenitor populations in T-cell Acute Lymphoblastic Leukemia.

Refractoriness to initial chemotherapy and relapse after remission are the main obstacles to cure in T-cell Acute Lymphoblastic Leukemia (T-ALL). Biomarker guided risk stratification and targeted therapy have the potential to improve outcomes in high-risk T-ALL; however, cellular and genetic factors contributing to treatment resistance remain unknown. Previous bulk genomic studies in T-ALL have implicated tumor heterogeneity as an unexplored mechanism for treatment failure.

Towards a comprehensive regulatory map of Mammalian Genomes.

Genome mapping studies have generated a nearly complete collection of genes for the human genome, but we still lack an equivalently vetted inventory of human regulatory sequences. Cis-regulatory modules (CRMs) play important roles in controlling when, where, and how much a gene is expressed. We developed a training data-free CRM-prediction algorithm, the Mammalian Regulatory MOdule Detector (MrMOD) for accurate CRM prediction in mammalian genomes.