Nathan Salomonis

Pediatric acute myeloid leukemia (AML) is a devasting disease with 5-year survival outcomes of approximately 60%. Therefore, there is an urgent need to develop novel therapies for pediatric AML patients. Numerous studies have demonstrated that cellular metabolism is a key vulnerability in adult AML; however, metabolism in pediatric AML is less robustly characterized, limiting the development of metabolism targeting therapies for pediatric patients. We have previously shown that manipulation of polyamine metabolism offers a therapeutic window to target adult leukemia, but it is not known if pediatric AML is similarly sensitive. Using pediatric AML patient-derived xenograft models, we demonstrate that polyamine metabolism is a pharmacologically targetable vulnerability of pediatric AML cells. Further, depletion of polyamines sensitizes pediatric AML cells to chemotherapy in vitro and in vivo . Mechanistically, polyamine depletion reduces protein synthesis through decreased hypusination of translational elongation factor eIF5A. Pharmacologic polyamine depletion and inhibition of eIF5A hypusination result in reduced protein synthesis and decreased expression of cell cycle regulatory proteins resulting in a G ₁ cell cycle arrest and eventual cell death through apoptosis. In summary, this study reveals polyamine metabolism and hypusination of eIF5A as a vulnerability in pediatric AML that can be targeted using clinically tractable approaches.

Aberrant pre-mRNA splicing in cancer generates protein sequences that are rare or absent in normal tissues, creating a rich source of tumor-specific neoantigens for immunotherapy. These splicing-derived neoantigens arise through diverse mechanisms, including recurrent somatic mutations in core spliceosome components ( SF3B1 , SRSF2 , U2AF1 , and ZRSR2 ), epigenetic derepression of transposable elements that give rise to chimeric exon-TE junctions, and coordinated dysregulation of splicing regulatory networks in cancers lacking spliceosome coding mutations. These processes produce two major classes of immunotherapeutic targets: 1) MHC class I-restricted neopeptides that can be recognized by T-cell-based therapies, and 2) extracellular neoepitopes (ExNeoEpitopes) within transmembrane proteins that are accessible to HLA-independent antibody-based modalities, including monoclonal antibodies (mAbs), bispecific engagers (BiTEs), antibody-drug conjugates (ADCs), and chimeric antigen receptor (CAR)-T or CAR-NK cells. Despite their strong immunogenic potential, effective therapeutic exploitation requires overcoming key immunological barriers, including T-cell exhaustion, impaired antigen presentation through MHC-I downregulation, and suppression within the tumor microenvironment. Recent advances in computational neoantigen prediction, immunopeptidomics, surface proteomics, long-read and single-cell isoform sequencing, and AI-guided therapeutic design are enabling more systematic discovery and validation of splicing-derived targets. This review integrates current understanding of the biological origins, immunological barriers, target classes of splicing neoantigens, and the technologies that enable their advancement in cancer immunotherapy.

Rapid advances in single-cell technologies now allow measurement of thousands of transcripts and other molecular features of individual cells offering unprecedented insight into lung biology in homeostasis and in disease. The accelerated generation of multimodal data has, however, been accompanied by the reporting of putatively “novel” cell types described without consensus regarding their ontogeny, identity, function, or defining markers. To fully realize the value of the technological advances and to enable rigorous comparison across studies, respiratory research will benefit from standardized, quantitative, and biologically grounded cell classifications and nomenclature. Achieving the transformative potential of the multimodal data will depend on common, machine- and human-readable nomenclature, structured and expandable dictionary and atlas resources, and clear methodological standards that ensure consistency as technologies evolve. The American Thoracic Society (ATS) recognized the importance of promoting a common nomenclature to enhance equitable access and utility of the vast amounts of multimodal data generated by the lung research community. The Collaborative Cross-Consortium and Country Lung Cell Nomenclature Project (C3LCN) was adopted as an ATS Assembly Project in 2024. This is the consensus report outlining the goals and framework of the Project to foster coordinated progressive lung cell research to include: 1) providing best practices for analysis, publication and reporting of lung single-cell transcriptomic datasets; 2) establishing a contemporary lexicon for healthy adult human cells of the lower respiratory tract with structured, persistent, and resolvable identifiers; 3) defining a scalable taxonomy to organize a common lung cell nomenclature; 4) offering tools to support collaboration, knowledge dissemination, and translational advances rooted in modern lung biology augmenting, not replacing, pre-genomic biological knowledge; and 5) describing an infrastructure capable of incorporating new ontological refinements as higher-resolution, multimodal single-cell and spatial datasets emerge, cellular heterogeneity is better defined, and disease-associated abnormal cell types and reactive cell states are increasingly recognized and mechanistically interrogated. Together, this coordinated effort aims to provide the foundation necessary for a robust, harmonized, and expandable nomenclature for lung science.

Single-cell and spatial omics offer unprecedented opportunities to decipher the mechanisms of disease, however, this process requires teams of experts, iterative trial-and-error and reasoning across modalities. Here we present LungChat ( https://chat.lungmap.net ), a conversational system for integrated multi-omics analysis and biomedical discovery, deployed as a hierarchical multi-agent architecture in which a supervisor decomposes natural-language questions into parallel, tool-grounded tasks spanning single-cell and spatial analyses, literature and clinical-trial synthesis, and drug repurposing. To predict new therapeutics, LungChat implements Direction-Aware Repurposing and Targeting (DART) to distinguish perturbations that reverse disease transcriptional programs from those that reinforce them, at the cell-type level, for safety prediction. Controlled architecture ablations showed that hierarchical orchestration improved grounded abstention and token efficiency and preserved strong performance on complex multi-step tasks. In pulmonary disease case studies, LungChat independently prioritized saracatinib for IPF through drug-connectivity screening, followed by DART-based cell-type analysis; the same compound has been evaluated in the STOP-IPF clinical trial ( NCT04598919 ). The system also recovered fluticasone propionate, an established COPD therapy, through a single orchestrated analysis. This tissue-agnostic system provides a blueprint for verifiable agentic AI systems that support reproducible scientific discovery.

Fragile X syndrome (FXS), the leading genetic cause of intellectual disability, arises from FMR1 gene silencing and the subsequent loss of the RNA-binding protein FMRP. N6-methyladenosine (m ⁶ A) is a prevalent mRNA modification essential for post-transcriptional regulation. FMRP binds and regulates the stability of m ⁶ A-containing transcripts. However, how FMRP deficiency impacts transcriptome-wide m ⁶ A modifications in FXS remains unknown. To address this, we generated cortical neurons from induced pluripotent stem cells (iPSCs) derived from healthy individuals and FXS patients. Electrophysiology recordings revealed synaptic and neuronal network defects in FXS iPSC-derived neurons. Transcriptome-wide analysis revealed striking m ⁶ A hypermethylation predominantly affecting synapse-associated transcripts. Mechanistically, we demonstrated that FMRP deficiency drives the aberrant translational upregulation of core m ⁶ A writers, a causal relationship definitively validated using CGG-corrected isogenic control lines. Targeted genetic knockdown of the m ⁶ A writer METTL3 successfully rescued synaptic phenotypes in FXS neurons, whereas its overexpression in control neurons phenocopied these synaptic defects, confirming the causal role of m ⁶ A dysregulation in FXS pathology. Notably, pharmacological intervention with the METTL3 inhibitor STM-2457 normalized methylation on synapse-associated transcripts and restored synaptic transmission in FXS neurons. Together, our findings uncover an FMRP-dependent epitranscriptomic mechanism contributing to FXS pathogenesis and suggest a promising avenue for m ⁶ A-targeted therapies.

Acute myeloid leukemia (AML) is a multiclonal disease, existing as a milieu of clones with unique but related genotypes as initiating clones acquire subsequent mutations. However, bulk sequencing cannot fully capture AML clonal architecture or the clonal evolution that occurs as patients undergo therapy. To interrogate clonal evolution, we performed simultaneous single-cell molecular profiling and immunophenotyping on 43 samples from 32 patients with NPM1 (nucleophosmin 1)–mutated AML at different time points in disease progression. Here, we show that diagnosis and relapse AML samples display similar clonal architecture patterns, but signaling mutations drive increased clonal complexity, specifically at relapse, which correlates with overall survival. We uncovered unique genotype-immunophenotype relationships regardless of disease state, suggesting leukemic lineage trajectories can be hard-wired by the mutations present. Analysis of longitudinal samples from patients on front-line AML therapy identified dynamic clonal and immunophenotypic changes consistent with the genotype-immunophenotype relationships we identified.

Juvenile dermatomyositis (JDM) is a chronic multisystem vasculopathy and inflammatory myopathy characterized by proximal muscle weakness, distinct rash, and risk of complications such as calcinosis cutis, skin ulceration, and mortality. Molecular insight from diagnostic muscle biopsy histology is limited, and the mechanistic pathoetiology of JDM remains poorly defined. We used single nuclei transcriptomics to assess muscle samples from patients with newly diagnosed treatment-naïve JDM. As a control, we assessed muscle samples from patients with congenital (nemaline) myopathy (CM), a non-inflammatory disorder. A total of 25,794 high quality nuclei were analyzed and clustered into various muscle-resident or infiltrating cellular populations. JDM tissue was characterized by an enriched interferon (IFN) response signature across endothelial, stromal, and immune cell compartments. Endothelial and perivascular populations showed increased inflammatory and angiogenic programs. Intercellular communication inference analysis identified dysregulated vascular endothelial growth factor (VEGF)-related signaling involving endothelial, stromal, and myonuclear populations as a possible mechanism for myonuclear-driven modulation of the muscle microvasculature. Spatial RNA in situ hybridization supported increased expression of selected IFN responsive and angiogenesis signaling genes in JDM tissue. Collectively, these data provide a cell type-resolved view of treatment-naïve JDM muscle and highlight vascular and IFN pathways for follow-up in larger cohorts.

Germinal center B cell responses are defined by many positive regulators of affinity maturation, but few components that restrain clonal dominance, notably Nr4a1, are known. We reveal an unsuspected role for BLIMP1 (Prdm1)-a plasma cell determinant-as a feedback regulator of affinity maturation. Single-cell RNA and B cell receptor (BCR) sequencing showed that B cell-specific Prdm1 loss drives an exaggerated germinal center reaction with larger clones, increased somatic hypermutation and greater clonal dominance, independent of Nr4a1. Single-cell chromatin profiling with base-resolution modeling indicated that Blimp-1 represses expression of BCR-signaling genes, gating chromatin accessibility at interferon-stimulated response elements, Ets-interferon regulatory factor composite elements, nuclear factor kappa B and Oct motifs. In the absence of BLIMP1, enhanced BCR-signaling augments activities of transcription factors that promote G1-S transition during light zone (LZ) selection and fuel dark zone (DZ) expansion. Thus, BLIMP1 attenuates BCR signaling and constrains the LZ to DZ transition, fine-tuning clonal competition, thereby maintaining repertoire diversity.

Background: Obesity-associated inflammation in white adipose tissue (WAT) worsens outcomes of influenza A virus (IAV) infection. A recently identified thoracic cavity WAT (tcWAT) supports IAV replication. However, tcWAT immune cell composition, functional properties, and role in IAV disease severity remain unclear. Methods: Using a mouse model of diet-induced obesity, flow cytometry, and single-cell RNA sequencing, we compared tcWAT with lung-distal visceral WAT assessing immune cell composition, transcriptomic profiles, inflammatory potential, and impact on IAV pathogenesis. Results: At baseline, tcWAT was uniquely enriched for immune cells with heightened proinflammatory capacity and exhibited a striking predominance of lymphocytic populations, including immature and Satb1+ T cells, the latter expressing gene signatures associated with elevated T-cell activation. Transfer of tcWAT immune cells into IAV-infected recipients accelerated IAV disease severity. IAV infection robustly reshaped tcWAT immune landscape, driving expansion of a B-cell population expressing Zbtb32 and upregulating genes involved in immune regulation and antiviral responses. Concurrently, IAV infection reduced immune populations linked to neutrophil regulation in tcWAT, while these same populations were expanded in the lung. Conclusions: These findings identify lung-proximal tcWAT as a distinct inflammatory tissue that may amplify pathogenic immune responses during IAV infection.

Large-scale, unbiased single-cell genomics studies of complex developmental compartments, such as hematopoiesis, have inferred novel cell states and trajectories; however, further characterization has been hampered by difficulty isolating cells corresponding to discrete genomic states. To address this, we present a framework that integrates multimodal single-cell analyses (RNA, surface protein and chromatin) with high-dimensional flow cytometry and enables semiautomated enrichment and functional characterization of diverse cell states. Our approach combines transcription factor expression with chromatin activity to uncover hierarchical gene regulatory networks driving these states. We delineated and isolated rare bone marrow Lin⁻Sca⁻CD117⁺CD27⁺ multilineage cell states (‘MultiLin’), validated predicted lineage trajectories and mapped differentiation potentials. Additionally, we used transcription factor activity on chromatin to trace and isolate multilineage progenitors undergoing multipotent to oligopotent lineage restriction. In the proposed model of steady-state hematopoiesis, discrete states governed developmental trajectories. This framework provides a scalable solution for isolating and characterizing novel cell states across different biological systems.