Cancer Cell

Background: Stomach adenocarcinoma is driven by heterogeneity, limiting therapeutic success. Although ROS acts as a continuous redox rheostat for tumor evolution, it is categorized based on binary models that are masked by tumor-microenvironment (TME) confounders. Here, we have defined a continuous, TME-independent ROS axis to help identify intrinsic vulnerabilities and improve patient stratification. Methods: Non-negative matrix factorization (NMF) defined a ROS-Axis in TCGA-STAD which was validated in ACRG Cohort. Multivariate regression model isolated intrinsic signatures via residual ROS scores by adjusting for TME confounders. Survival was assessed using Cox hazard models. Drug sensitivities were mapped using GDSC2/ElasticNet modeling with cross-cohort replication. Results: Our results define a reproducible ROS gradient, driven by effectors like NQO1 and SOD1, characterizing ROS-high tumors as proliferative, epithelial and immune -cold. High residual ROS score was associated with an improved prognosis, regardless of TNM stage and age. Pharmacogenomic mapping revealed an overlapping sensitivity to mTOR inhibitors in ROS-high gastric cancer tumors which persisted after TME confounder adjustment. Conclusion: The continuous ROS axis provides a functional readout of metabolic dependency that refines traditional anatomical staging. By identifying mTOR dependent cold tumors, our framework offers a precision strategy for immunotherapy-resistant patients like those affected by microsatellite-stable gastric cancer.

Effective predictive biomarkers for immune checkpoint inhibitor (ICI) therapy remain an unmet need across solid tumors. Here, we present an integrated spatial proteomics workflow that combines in situ proximity ligation assay with multiplexed immunofluorescence to directly resolve PD1/PDL1 signaling events at the level of defined cellular phenotypes and their spatial organization within intact tumor tissue. Applied as a proof of concept to tumor samples from patients with metastatic urothelial carcinoma treated with pembrolizumab, this approach reveals that PD1/PDL1 interactions specifically involving cytotoxic CD8CD3 T cells are significantly enriched in complete responders, while such interactions are rare in patients with progressive disease. This interaction defined T cell subset achieves superior discrimination of clinical response compared to single marker PDL1 expression or immune cell abundance alone. By integrating direct detection of protein protein interactions with high dimensional single cell phenotyping, our workflow provides a mechanistically informed, spatially resolved biomarker of functional immune engagement. Beyond urothelial carcinoma, this platform establishes a generalizable framework for translating spatial signaling biology into predictive tools for immunotherapy response across tumor types.

Classical and basal-like transcriptional subtypes of pancreatic ductal adenocarcinoma (PDAC) are prognostic and may predict response to different chemotherapy regimens and RAS inhibitors. Current subtyping methods rely on tissue biopsies and remain challenging to integrate into clinical workflows. Herein, we present a novel approach for non-invasive subtyping of PDAC based on epigenomic profiling of circulating tumor DNA (ctDNA). In a multi-omics cohort of patient-derived xenografts, we identify highly recurrent regulatory elements associated with classical and basal-like PDAC. We then demonstrate that these epigenomic signatures can identify PDAC subtype from plasma epigenomic profiling in a multi-institutional cohort of patients with metastatic PDAC and integrate information from circulating histone modifications and DNA methylation to develop the Pancreatic Integrated Epigenomic Score (PIES). PIES is concordant with tissue-based labels and captures transcriptional subtype heterogeneity observed within biopsies. Furthermore, it improves prognostication over tissue-based subtyping suggestive of the recovery of ground truth tumor biology from plasma ctDNA. Our work provides a proof-of-concept for a circulating biomarker that enables transcriptional subtyping and informs therapeutic decisions in pancreatic cancer.

Adoptive cell therapy (ACT) in solid tumors is limited by tumor microenvironment (TME)-imposed resistance mechanisms that are inadequately addressed by conventional systems. We developed tissue-preserving patient-derived explants (PDEs) from lung and ovarian cancer to interrogate redirected T cell immunity in intact human tissue. Using mesothelin-targeting bispecific T cell engager (BiTE(R), Amgen trademark)-secreting T cells, we observed antigen-dependent but heterogeneous responses across lesions. An integrated ex vivo response score stratified responder and non-responder TMEs, revealing that resistance associates with reduced antigen density, stromal dominance, and limited myeloid licensing rather than baseline lymphocyte abundance. Elevated prostaglandin E2 (PGE2) inversely correlated with BiTE-induced T cell activation, identifying the COX/PGE2 axis as a tissue-imposed constraint. COX inhibition amplified interferon-driven immune programs enhanced intratumoral CD8 infiltration, and increased tumor-restricted apoptosis. Spatial transcriptomics localized these effects to tumor-proximal immune hubs in responders, whereas non-responders remained stromally insulated. These findings position PDEs as human-based new approach methodologies enabling combinatorial ACT pharmacodynamics and stratification. Statement of significancePatient-derived explants provide a human-based new approach methodology to interrogate adoptive immunotherapy pharmacodynamics within intact tumor microenvironments in NSCLC and HGSOC. We uncover a COX/PGE2-mediated tissue ceiling that limits BiTE-driven T cell function and demonstrate that COX inhibition reactivates tumor-proximal immune hubs to enhance intratumoral CD8 infiltration and tumor-restricted apoptosis, informing patient stratification and rational combinations.

Antibody-drug conjugates (ADCs) require high and homogeneous target expression for optimal efficacy, yet the spatial, temporal, and cellular heterogeneity of clinically approved ADC targets in high-grade serous ovarian cancer (HGSC) remains incompletely defined. We analyzed bulk RNA-sequencing, single-cell RNA-sequencing, and whole-genome sequencing data from 867 samples across 304 patients enrolled in the real-world DECIDER cohort to systematically evaluate 11 approved ADC targets. FOLR1, TACSTD2, and ERBB2 emerged as highly expressed candidates. Inter-patient variability exceeded intra-patient heterogeneity, which further decreased following neoadjuvant chemotherapy. Target expression was highly concordant across anatomical sites and largely stable from diagnosis to relapse. Single-cell RNA-sequencing results revealed that TACSTD2 and FOLR1 showed the most frequent cancer cell-restricted expression. In rare cases of gene amplification, ERBB2 and F3 emerged as potential targets alongside TACSTD2 and FOLR1. Overall, 80% of patients displayed homogeneous expression of at least one actionable target, with frequent co-expression of TACSTD2 and FOLR1. These findings indicate that ADC target expression in HGSC is broadly stable across space and time and support the prioritization and strategic integration of TACSTD2- and FOLR1-directed ADCs in this disease.

Intravesical Bacillus Calmette-Guerin (BCG) immunotherapy remains the standard treatment for intermediate and high-risk non-muscle invasive bladder cancer (NMIBC), yet more than half of the patients do not respond and experience recurrence or progression. BCG induced humoral immune responses remain poorly defined in patients with NMIBC. Building upon our previous findings showing the pathogenic role of atypical B cells (ABCs) in cancer progression, and following repeated intravesical treatment with BCG, in an aging murine model of bladder cancer, we conducted a longitudinal study to characterize B cell associated local and systemic responses in 45 patients (37 males and 8 females) with high-risk NMIBC who underwent treatment with BCG. Peripheral B cell immune phenotyping, B cell single-cell transcriptomics, spatial multi-omics, and systemic proteomics were performed. We identified expansion of circulating ABCs following the 4th BCG instillation, as a defining feature of patients who experienced early recurrence following BCG therapy. Spatial mapping of corresponding pre- and post-BCG recurrent tumors, at single cell transcriptomic and proteomic levels, revealed preferential enrichment of ABCs within tumor-adjacent stroma and tertiary lymphoid structures, where they co-localized with PD-1 B cells, regulatory T cells, and CD163 macrophages, forming immunosuppressive niches. BCG non-responders exhibited IgG skewed antibody responses at both local and systemic levels with expanded IgG autoantibody repertoires, progressive IgG reactivity against BCG antigens, and higher IgG deposition within the tumor microenvironment. Independent validation in tumors from two independent cohorts (total n = 409) of patients treated with BCG immunotherapy, revealed a significant association between high expression of the ABC specific transcript, FCRL5, and shorter recurrence and progression free survival. Findings from this study demonstrate that a BCG unresponsive state arises within a pre-existing ABC-dominated immune landscape that is further amplified during repeated BCG instillations. Our study identifies a novel role of ABCs as key regulators of local and systemic humoral immune dysfunction in high-risk NMIBC, and highlights ABC signatures as a potential predictive biomarker of response to BCG.

Meningiomas are the most common primary central nervous system tumors in adults, posing a significant burden to society. Although a large percentage of lower-grade meningiomas are curable by surgery or radiation alone, high-grade and a subset of low-grade meningiomas demonstrate recurrences and complications from treatment. Systemic therapies for meningioma remain ineffective, and no targeted treatments are approved. Despite the central role of YAP1/TAZ-TEAD signaling in NF2-deficient/mutant tumors, no studies have systematically examined TEAD inhibition across molecularly defined meningioma subtypes or investigated mechanisms of resistance in this disease. We have recently shown that YAP1/TAZ signaling is an oncogenic driver of meningioma. Here, using established and patient-derived meningioma cell lines, we demonstrate that genetic ablation of YAP1/TAZ suppresses growth in both NF2 mutant and NF2 wild type cell lines, establishing YAP1/TAZ-TEAD signaling as a shared oncogenic dependency. Pharmacologic TEAD inhibition suppressed growth of benign NF2 mutant and a subset of higher-grade NF2 mutant meningiomas, whereas NF2 wild type meningiomas were generally more resistant. RNA-Seq and Western Blot analysis identified compensatory activation of MEK-ERK, mTOR-S6, and FAK signaling in resistant lines exhibit. Importantly, co-targeting these pathways was able to overcome resistance to TEADi and was superior to MEK/mTOR/FAK inhibition alone. These studies provide a compelling proof-of-concept that TEADi represents a novel therapeutic vulnerability in meningioma and reveal adaptive signaling responses that can be therapeutically exploited.

HighlightsO_LIA pan-cancer proteomic atlas defines the UPS architecture across human cancers C_LIO_LIGenome-wide pQTLs reveal mutation-driven UPS remodeling C_LIO_LILineage- and genotype-specific vulnerabilities created by UPS rewiring C_LIO_LIE3 ligase specificity scores to guide rational design of targeted protein degradation C_LIO_LIAn interactive platform, UbiDash, enables UPS-focused proteogenomic exploration C_LI Components of the Ubiquitin Proteasome System (UPS) are attractive candidates for targeted protein degradation therapies owing to their key roles in maintaining protein homeostasis in healthy and malignant cells. How cancer driver mutations rewire UPS components to support tumor growth and survival remains incompletely understood. By mapping tissue- and cancer-specific expression of UPS components across more than 20 tissues and 10 tumor types using harmonized multiomic datasets, we present an integrated pan-cancer proteogenomic analysis focused on E3 ubiquitin ligases. These analyses uncovered (1) mutation-associated UPS protein level changes; (2) clinically actionable E3s based on recurrent alterations, tissue-enriched expression, and prognostic value; and (3) E3 regulatory networks based on co-expression, co-dependency, and protein-protein interactions. We also introduce UbiDash, an interactive platform for exploring UPS alterations across cancers. This study identifies clinically relevant E3s and mutation-defined proteostatic dependencies and provides resource for mechanistic insight and therapeutic prioritization of UPS components in cancer.

Multiple myeloma (MM) is a plasma cell malignancy shaped by dynamic interactions between MM cells and non-malignant cells in the immune microenvironment. To spatially profile the influence of cellular context on MM and immune cell expression, we developed a multimodal framework integrating 10x Genomics Visium HD, 10x Genomics Xenium, and clinically annotated single-cell RNA (scRNA-seq) sequencing datasets. Visium HD enabled unbiased, whole transcriptome, spatial discovery at 16 {micro}m resolution, Xenium provided orthogonal validation at single-cell resolution, and scRNA-seq extended findings by mapping spatial labels and leveraging the greater sequencing depth. We developed a custom framework for cell type annotation within Visium HD spatial bins. Our approach enabled identification of plasma cell-dense niches enriched for non-canonical Wnt signaling, associated with gene expression supporting cell adhesion mediated drug resistance, inferior progression-free survival, and extramedullary lesions. Immune cells within these neighborhoods exhibited suppressed transcriptional states, including increased inhibitory receptor expression such as LAG3. Utilizing the niche-driven transcriptional states in MM and immune cells, we were able to develop a 15-gene signature independently predictive of progression free survival (HR = 2.00, p < 0.0001). Collectively, this study demonstrates the potential of integrated spatial and single-cell transcriptomics to define niche-specific programs supporting MM progression.

PDAC exhibits rapid chemoresistance, yet how drug-tolerant states arise remains unclear. Existing approaches miss how network topology evolves across cell-state transitions under drug pressure. A 3D PANC-1 tissue model on decellularized intestinal matrix was used for scRNA-seq across four conditions (control, GEM, TGF-{beta}1, GEM+TGF-{beta}1). Pseudotime trajectory inference was combined with dynamic PPI network analysis. Findings were cross-examined in a PDAC atlas (726,107 cells, 231 patients; Loveless et al., 2025). GEM resistance involved E2F1, mTOR, CDK1, AURKA, TPX2, TOP2A, and BIRC5. TGF-{beta}1 drove EMT resistance via KRAS, glycolysis, and hypoxia, inducing SPOCK1, MBOAT2, COL5A1, ADAMTS6, THBS1, and FN1. Trajectory-coupled network analysis revealed an emergent bottleneck when G1[-&gt;]S and TGF-{beta}1-induced EMT co-occurred: CDK1 centrality spiked selectively, with CDKN1A as critical regulator. This CDK1-CDKN1A-WEE1 axis defines an "S-phase persistence" state enriched for GEM survivors. Atlas cross-examination confirmed 8.7-fold metastatic enrichment of triple-positive cells and EMT-cell-cycle coupling. Trajectory-coupled network topology analysis identifies CDK1-CDKN1A-WEE1 as a chemoresistance bottleneck corroborated in 726,107 patient cells. The framework generalizes to drug resistance across cancer types.

T cell lymphomas (TCL) are a heterogeneous collection of malignancies whose origins and pathogenesis are poorly understood and for which few efficacious therapeutic options exist. Here, we conduct single-cell transcriptomic profiling spanning eight TCL entities and describe entity-associated programmes. We predict the cell of origin for these tumours through an integrative analysis of transcriptome and T cell receptor (TCR) maturation states. By identifying tumours with TCR states ranging from the pre-TCR through non-productive and productive TCR alpha and beta chain rearrangements we shed new light on their developmental origins. Furthermore, we apply our drug2cell computational drug target predictions with drug screens using patient-derived cell models, systematically benchmarking the performance of drug2cell and validating compounds and targets. This process identifies SYK inhibitors as a therapeutic opportunity and prioritises TIM3 for immunotherapy based on combined spatial transcriptomics analysis. Overall, our data provide a resource for diagnostics and therapies for tumours of critical unmet need.

Aberrant neurotransmitter signaling and transcriptional dysregulation are hallmarks of gliomagenesis and represent potential therapeutic targets. Monoamine neurotransmitters such as dopamine and serotonin primarily activate GPCRs but can also function epigenetically as histone H3 modifications. Here, we uncover mechanisms of crosstalk between monoamine neurotransmitter signaling, H3 dopaminylation, and RNA polymerase II (Pol2) transcription in diffuse midline glioma (DMG). We find that co-treatment with Pol2-targeting CDK9 inhibitors (CDK9i) and FDA-approved neuropsychiatric drugs, including selective serotonin reuptake inhibitors (SSRIs), synergistically reduces DMG growth. Mechanistically, CDK9i+SSRI treatment alters H3 dopaminylation patterns and represses synaptic and neurodevelopmental gene transcription associated with CDK9i resistance. Further phospho-proteomic analyses show that CDK9i monotherapy activates pro-survival CaMKII signaling, which can be suppressed by co-treatment with neuromodulatory drugs. These studies establish roles for H3 dopaminylation and neurotransmitter signaling in DMG gene regulation and response to CDK9i, suggesting that monoamine neurotransmitter pathways may be exploited as a therapeutic strategy for DMG.

We previously developed synthetic Notch (synNotch)-chimeric antigen receptor (CAR)-T cells to improve the safety and efficacy of CAR-T therapy for glioblastoma. In this system, an anti-EphA2/IL13R2-dual-CAR is expressed only upon recognition of tumor- or brain-specific "priming" antigens, EGFRvIII (termed E-SYNC cells) or brevican (B-SYNC), respectively, with E-SYNC currently under phase I clinical evaluation (NCT06186401). However, tracking and profiling these engineered cells in vivo remain challenging, limiting our understanding of their activity and therapeutic potential. To address this gap, we developed a single-cell RNA-sequencing (scRNA-seq) workflow with custom spike-in probes for synNotch-CAR transcripts, enabling simultaneous detection of engineered cells and transcriptomic profiling. In vitro, integration of multiple probes using machine-learning-assisted classifiers detected 78.2% of E-SYNC cells and 60.0% of B-SYNC cells with 98.0% specificity. In a xenograft model, synNotch-positive cells were detected across the spleen, lung, and brain, with the highest frequency and most robust priming and activation observed in the brain. Single-cell transcriptomic analyses revealed tissue-specific differentiation programs, including cytotoxicity, proliferation, metabolic activity, and acquisition of tissue-resident memory phenotypes, shaped by both environmental cues and synNotch-mediated antigen recognition. In summary, this spike-in probe-enhanced scRNA-seq workflow enables robust detection and high-resolution characterization of synNotch-CAR-T cell dynamics and provides a broadly applicable platform for monitoring engineered immune cells in diverse clinical contexts. One Sentence SummaryOur spike-in probe-enhanced single-cell RNA-sequencing method enables analysis of tissue-dependent activation and transcriptional states of synNotch-CAR-T cells, providing a robust and scalable platform for in vivo tracking and transcriptomic profiling of engineered cell therapies.

Pancreatic ductal adenocarcinoma (PDAC) remains a lethal malignancy, with therapeutic resistance influenced by a dense desmoplastic stroma dominated by cancer-associated fibroblasts (CAF). Using single-cell RNA-sequencing and gene regulatory network modeling of 42 PDAC tumors, we identified a CAF subpopulation characterized by elevated NFATC2 expression that is enriched in patients with improved therapeutic response and survival. NFATC2+ CAFs exhibited tumor-suppressive features, including enhanced apoptotic signaling and suppression of ERBB pathway activity. Co-culture experiments demonstrated that NFATC2+ CAFs restrain pancreatic cancer cell growth and enhance chemotherapy-induced apoptosis, increasing sensitivity to standard-of-care chemotherapy regimens and synergizing with ERBB-targeted therapies. The favorable effect of NFATC2+ CAFs on chemotherapy response was validated in two other PDAC cohorts and in rectal cancer. Together, these findings identify NFATC2+ CAFs as a therapy-conditioned stromal state linked to improved treatment response and uncover a context-dependent vulnerability within the tumor microenvironment that may be exploited to rationally optimize combination therapies.

Immune checkpoint inhibitors (ICI) improved outcomes in metastatic urothelial carcinoma (mUC), but primary and acquired resistance remain poorly understood. We performed single-nuclei RNA sequencing on sequential metastatic biopsies from ICI-treated mUC patients. Tumor cells showed transcriptomic heterogeneity within individual lesions, basal cells being associated with increased immune infiltration and response. Myeloid and lymphoid compartments exhibited features of immune dysfunction in non-responders. Longitudinal analyses revealed convergent adaptive resistance mechanisms, dominated by polarization toward pro-tumoral macrophage states, but also including downregulation of the antigen presentation machinery in tumor cells, increased checkpoint expression with loss of cytotoxicity in T cells. Individual trajectories point to distinct evolutionary routes under ICI pressure. Across pivotal ICI trials, bulk expression of the M2-like macrophage marker HES1 predicted ICI resistance. Our study provides the first single-cell longitudinal atlas of ICI-treated mUC, revealing macrophage reprogramming as a dominant driver of resistance, establishing a framework for individualized immunotherapy strategies.

Oncolytic adenovirus (ADV) therapy faces heterogeneous responses, implying tumor-intrinsic resistance. We identify interleukin-17 (IL-17) signaling as a novel potential barrier associated with multi-modal cellular reprogramming. Transcriptomic analysis of ADV-treated 4T1 murine mammary carcinoma cells revealed specific upregulation of Il17rb, Il17rd, and Il17f, indicating viral induction of this inflammatory axis. The IL-17 signature correlates strongly with a cancer stemness phenotype. Metabolically, it associates with increased lipid metabolism and suppressed glycolysis, suggesting a state resistant to viral replication. Furthermore, it broadly negatively correlates with programmed cell death pathways (apoptosis, necrosis) while positively associating with pro-survival autophagy. IL-17 component expression effectively stratifies samples into distinct metastatic risk categories, underscoring its prognostic potential. Our findings reveal a previously unrecognized, tumor-intrinsic role for IL-17 signaling in ADV resistance, associated with enhanced stemness, altered metabolism, and impaired cell death. This nominates the IL-17 pathway as both a predictive biomarker and a therapeutic target for combination strategies. HighlightsO_LIOncolytic adenovirus infection selectively upregulates IL-17 receptor subunits (IL17RB, IL17RD) and IL17F ligand in 4T1 tumor cells C_LIO_LIIL-17 receptor expression strongly correlates with cancer stemness gene signatures, particularly through IL17RB and IL17RD C_LIO_LIThe IL-17 axis associates with broad suppression of lytic cell death pathways (apoptosis, necrosis, necroptosis) while positively correlating with autophagy C_LIO_LIIL-17 pathway activity correlates with metabolic reprogramming favoring lipid turnover over glycolysis C_LIO_LIIL-17 expression levels stratify samples into distinct metastatic risk categories, suggesting biomarker potential C_LI

Engineering macrophages with chimeric antigen receptors is emerging as a promising cancer therapeutic. Chimeric antigen receptor-expressing macrophages (CAR-Ms) engineered to recognize tumor-specific antigens have been shown to inhibit tumor growth and activate adaptive immune responses, leading to robust tumor control in animal studies. Based on this work, clinical trials have been initiated. While the trials have shown promise, challenges remain. The dynamic interactions between CAR-Ms and cancer cells and the exact mechanisms driving anti-tumor effects remain poorly defined. Defining the dynamic interactions between CAR-Ms and cancer cells will provide critical insights for optimizing future CAR-M design and improving therapeutic efficacy. We sought to directly visualize CAR-M interactions with glioblastoma cells at high-resolution and in real-time using CAR-Ms engineered to recognize Neural-Glial Antigen 2 (NG2), an antigen expressed on glioblastoma cells. Using patient-derived glioblastoma cells, we formed glioblastoma spheroids and embedded them in a 3D matrix together with CAR-Ms. Using time-lapse microscopy, as expected, we found that NG2-targeting CAR-Ms engulfed glioblastoma cells. However, excitingly, we found that NG2-targeting CAR-Ms blocked >85% of glioblastoma cell invasion in 3D. This inhibition of glioblastoma invasion was not due to a significant change in CAR-M polarization states. Together, these data suggest that NG2-targeting CAR-Ms both engulf glioblastoma cells and block glioblastoma invasive behavior.

The high heterogeneity of pediatric cancers presents significant diagnostic challenges, underscoring the need for accurate classification. Although molecular profiling supports first-line diagnostics and guides treatment, it can delay final diagnosis. While Nanopore-based methylation analysis has enabled rapid CNS tumor diagnosis, its application to pediatric solid tumors and lymphomas has remained largely unexplored. We developed Tucan, a deep-learning classifier trained on 3,818 methylation array profiles representing 84 subtypes, designed to classify tumors from sparse Nanopore methylation data. In retrospective validation (n=514), Tucan generated confident predictions (CFT[&ge;] 0.7) within 30 minutes of sequencing in 385 cases, achieving 372 correct diagnoses (F1-score: 0.98). In prospective testing (n=74; 63 classifiable), 52 samples reached the confidence threshold with 96% accuracy, confirming the original diagnosis in 47 cases and correctly refining or revising it in three. Together, Tucan enables rapid, high-confidence molecular classification of pediatric solid tumors and lymphomas.

Well-differentiated and dedifferentiated liposarcoma (WDLPS and DDLPS) exhibit markedly different clinical behaviors, with DDLPS showing greater aggressiveness, higher recurrence and metastasis rates, and worse outcomes. Using single-nucleus multiome sequencing, epigenomic profiling, and spatial transcriptomics, we characterized cellular and epigenetic heterogeneity between these subtypes at single-cell and spatial resolution. We found distinct phenotypic states reflecting altered lineage differentiation and plasticity: DDLPS is dominated by early-differentiated progenitor-like cells, sclerotic WDLPS displays broader mesenchymal lineage plasticity, and adipocytic WDLPS contains abundant committed adipocytes. The DDLPS immune microenvironment was dominated by immunosuppressive macrophages, whereas WDLPS harbored more T cells and inflammatory macrophages. Notably, sclerotic WDLPS displayed intermediate cellular and molecular features, suggesting it may represent a distinct WDLPS subtype. Importantly, we identified novel gene regulatory circuits underlying each state, including FABP4/PPARG programs in adipocytic WDLPS, GLI2/TCF7L2/RBPJ/KLF7 programs in sclerotic WDLPS, and KLF7/FOSL2/SP3/GLI2/RBPJ programs in DDLPS. H3K27ac-marked enhancers were enriched near adipocytic marker genes in WDLPS and mesenchymal markers in DDLPS. Together, these findings reveal the cellular heterogeneity of tumor and immune compartments across liposarcoma subtypes and identify regulatory programs driving their differentiation states. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=155 SRC="FIGDIR/small/713651v1_ufig1.gif" ALT="Figure 1"> View larger version (73K): org.highwire.dtl.DTLVardef@1c84ee1org.highwire.dtl.DTLVardef@1b2ad42org.highwire.dtl.DTLVardef@18ce5a6org.highwire.dtl.DTLVardef@138f615_HPS_FORMAT_FIGEXP M_FIG C_FIG

Children with acute lymphoblastic leukemia (ALL) are treated with multiagent chemotherapy that causes profound changes to the immune system. There are limited data on how disease and therapy impact antigen-specific immune memory, leading to inconsistent guidelines on best practices for revaccination of this population. Here, to inform vaccine guidance, we investigated whether immunity derived from routine childhood measles and varicella zoster virus (VZV) vaccines is maintained during and after therapy for childhood ALL. We report that antibodies against measles and VZV were significantly reduced in children with ALL (n=45) compared to healthy controls (n=13), particularly in older children in whom a longer time had passed since their most recent vaccine dose. However, the avidity of the measles and VZV-specific antibodies was indistinguishable between groups. Despite changes to the composition of the T cell compartment, both overall and antigen-specific T cell function were preserved in children with ALL. These data provide compelling evidence for revaccination of children following ALL treatment. Intact T cell responses suggest that post-treatment revaccination would be effective.