Cancer Cell

Regional lymph nodes (LNs) in the thoracic cavity serve as essential immunological hubs that coordinate humoral and cell-mediated responses against the development and progression of non-small cell lung cancer (NSCLC). To investigate immune dysregulation in the non-metastatic regional LNs of patients with aggressive NSCLC, we performed multimodal profiling on 36 LNs from 11 patients undergoing curative-intent resection including CITE-seq, scRNA-seq, and Imaging Mass Cytometry (IMC). Regional N1 LNs from patients with more aggressive disease (stage IB-IIIA) exhibited a significant enrichment of dysfunctional CD8 T cells and regulatory T cells (Tregs) compared to N2 LNs and LNs from patients with less aggressive disease (stage IA). These immune subsets were spatially co-localized with mature regulatory dendritic cells (mregDCs; CD1c, TIM3, LAMP3), forming an immunosuppressive niche uniquely enriched in the N1 LNs of higher-stage patients. Concurrently, higher-stage N1 LNs contained larger number of "decorticated" B-cell follicles characterized by decreased encapsulation of the mantle zone layer surrounding the germinal centers. This mantle zone disorganization was associated with increased spatial niches involving Tregs, CD68+ CD163 TIM3 Macrophages, CD163 TIM3dim Monocytic-Myeloid Derived Suppressor Cells (M-MDSC), plasma B cells, and a decrease in spatial niches involving CD4 T helper cells and fibroblastic reticular cells (FRCs). Together, our findings reveal parallel alterations in humoral and cell-mediated immunity within the regional LNs of patients with aggressive NSCLC.

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.

Clear cell renal cell carcinoma (ccRCC) is the leading cause of kidney cancer-related death, but how the tumor microenvironment shapes patient survival is not completely understood. Here, we describe the characterization of ccRCC tumor ecosystems from 498 patients using imaging mass cytometry with a focus on tumor, myeloid, and T cell landscapes. Data from more than 3 million single cells is analyzed using machine-learning to identify key ecosystem features that outperform basic clinical data for predicting patient survival. We define three survival ecotypes of ccRCC: Poor ecotypes, correlate with the worst survival, have high levels of ICAM1 and CD44 expression in tumor cells and are enriched in M2-like macrophages and interactions of exhausted CD8+ T cells with macrophages. Favorable ecotypes are characterized by high levels of VHL on tumor cells and of HLADR on myeloid cells and contain Th1-like CD4+ T cells. Medium ecotypes have the highest endothelial cell density and various immune-to-tumor interactions. Multi-omic characterization of these ecotypes using targeted genomic sequencing and metabolic imaging reveals distinct genomic and metabolic features, including BAP1 mutations in Poor and VHL monodriver/wild-type status in Favorable patients. We show that deep learning allows ecotype prediction directly from standard pathology H&E images. We validate the ecotypes and their associated molecular characteristics with orthogonal omics data across five clinical cohorts and more than 2,500 patients. These analyses highlight an overall survival benefit for Medium patients treated with immunotherapy. In summary, our study distills the survival-relevant information encoded in the ccRCC tumor microenvironment into prognostic survival ecotypes, which may inform clinical decision making in the future.

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.

Anti-CD19 chimeric antigen receptor (CAR) T-cell therapy can induce durable remissions in patients with large B-cell lymphoma (LBCL), yet outcomes remain variable. Reliable pre-treatment predictors of durable response remain limited, leaving a critical gap in patient management. To address this, we profiled pre-treatment plasma cell-free RNA (cfRNA) from 91 LBCL patients treated with axicabtagene ciloleucel (axi-cel, Yescarta) across three independent cohorts. We first demonstrated that signatures of "lymph node-like" tumor microenvironments (TMEs), previously identified in tumor biopsies and shown to correlate with favorable outcomes, are specifically elevated in the pre-treatment plasma cfRNA of responders, but not in matched peripheral blood mononuclear cells (PBMCs). These observations indicate that cfRNA captures TME tissue-derived signals not reflected in circulating immune cells. Next, using unbiased approaches, we identified additional cfRNA signatures associated with one-year clinical outcomes that capture the underlying biological landscape of treatment response. Collectively, these findings support pre-treatment plasma cfRNA as a minimally invasive surrogate of TME state to prospectively inform durable CAR T-cell therapy outcomes and guide risk stratification and TME-modulating adjunct therapies.

AO_SCPLOWBSTRACTC_SCPLOWLung cancer is characterized by profound intratumoral and inter-patient heterogeneity, spanning histological subtypes, molecular landscapes, and the tumor microenvironment. While multi-omics integration is essential for capturing this complexity, leveraging these data to explicitly define survival-associated subpopulations remains a significant challenge. In this study, we developed NeuroMDAVIS-FS, an unsupervised deep learning framework designed to stratify lung cancer patients by survival risk, and identify molecular determinants underlying improved clinical outcomes. Using the CPTAC cohort, we integrated genomic (CNV), transcriptomic (RNA-seq), and proteomic profiles to extract modality-specific features. Candidate biomarkers were validated through Kaplan- Meier (KM) survival analysis and univariate Cox proportional hazards (CoxPH) regression. A final multivariate CoxPH model effectively stratified patients into high-risk and low-risk cohorts (Kaplan Meier p-value < 0.001). Notably, the integration of these molecular features with baseline clinical models significantly enhanced prognostic accuracy, improving the concordance index by 43.79% in LUAD, 31.05% in LSCC, and 23.76% across the pan-lung cancer cohort. These results demonstrate that NeuroMDAVIS-FS identifies robust, biologically relevant features that surpass traditional clinical variables in predicting patient outcomes, offering a scalable path for precision oncology.

Tumor heterogeneity plays a critical role in tumor relapse and the development of drug resistance. Current personalized strategies, based on genetic profiling or bulk tumor drug sensitivity testing, offer limited clinical value as they overlook clonal heterogeneity. Here, through establishing primary tumor cell cultures from multiple metastatic sites, we observed that tumor cells exhibit high morphological plasticity and readily form distinct clonal morphologies during monoclonal expansion. Moreover, these heterogeneous clones displayed distinct tumorigenic and histological traits in orthotopic models, which may imply their differing clinical relevance in tumor progression. We also found that clonal morphological heterogeneity was exhibited by both established cell lines and primary lines derived from chemically induced tumor models. Subsequently, we analyzed the drug sensitivity profiles of tumor clones and identified clone-specific sensitive drugs. Despite limited in vitro synergy in pairwise combinations, both in vitro and in vivo assays confirmed their potent, clone-selective inhibition, suggesting rational drug combinations can precisely target distinct clonal populations. Taken together, Collectively, our findings propose that a heterogeneity-informed drug selection paradigm, enabled by rapid clonal morphology analysis of patient-derived cells, can be used to prevent recurrence and overcome resistance. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/703021v1_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@1db607dorg.highwire.dtl.DTLVardef@19bbcd4org.highwire.dtl.DTLVardef@18a3355org.highwire.dtl.DTLVardef@304794_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LITumor cells develop distinct morphologies during clonal expansion. C_LIO_LIDistinct morphologies serve as simple markers of tumor heterogeneity. C_LIO_LIDistinct clonal morphology defines a unique drug-response profile. C_LIO_LIClone-selective drug combinations combat heterogeneity-driven resistance. C_LI

Resistance to systemic therapy is a major unmet challenge in pancreatic cancer. To identify potential mechanisms of resistance, we developed a novel 3D pipeline in clinical samples that uses deep learning to classify sensitive and persistent tumor cell populations based on morphological features, enabling subsequent molecular characterization of intratumoral heterogeneity. We applied this automated 3D pipeline to a cohort of human pancreatic cancer samples treated with neoadjuvant chemotherapy, identifying heterogeneity in response to therapy both between and within tumors. Application of spatial proteomics to these sensitive and persistent regions identified enhanced epithelial-to-mesenchymal transition and non-classical cell states in persistent cells, confirming our morphological classification. Integration of spatial transcriptomics in multiple pancreatic cancer cohorts associated fibroblast-cancer crosstalk via syndecans with resistance to cytotoxic therapy. Our validated 3D multi-omic pipeline is now poised for application to clinical trials, enabling discovery of resistance mechanisms and design of new therapeutic combinations to circumvent resistance. Statement of significanceWe developed a novel 3D multi-omic pipeline to identify mechanisms of resistance to chemotherapy in clinical samples. This approach associated fibroblast-cancer crosstalk via syndecans with resistance to cytotoxic therapy and is poised for broader application in neoadjuvant clinical trials.

Reliable non-invasive biomarkers for tumor grading and disease monitoring in pediatric brain tumors are an unmet clinical need. Circulating extracellular vesicles (EVs) carrying molecular cargo reflective of tumor biology, offer promise as liquid biopsy tools. We have previously discovered EV-associated Syndecan-1 (SDC1) to be overexpressed in malignant brain tumors, but its value as a biomarker in pediatric disease remains unclear. In this study, plasma EVs were isolated from pediatric brain tumor patients (n=60) by size-exclusion chromatography and characterized using cryo-electron microscopy, nanoflow cytometry, immunoblotting, and single-vesicle total internal reflection fluorescence imaging. EV-associated SDC1 (EV-SDC1) was quantified and analyzed in relation to tumor grade, subtype, surgical resection status, and tumor volume. EV-SDC1 levels were significantly elevated in high-grade (ependymoma, diffuse midline glioma, and atypical teratoid/rhabdoid tumor (AT/RT)) compared with low-grade pilocytic astrocytoma tumors and robustly discriminated grade 3 tumors from pilocytic astrocytoma (AUROC 1.00). Independent validation using transcriptomic data from the Open Pediatric Brain Tumor Atlas showed SDC1 mRNA levels to effectively distinguish high grade (ependymoma, medulloblastoma, diffuse midline glioma, and AT/RT) from pilocytic astrocytoma patients. Furthermore, EV-SDC1 levels decreased following complete tumor resection but remained elevated in patients with residual disease or recurrence. Collectively, circulating SDC1-positive EVs represents a clinically informative biomarker reflecting tumor aggressiveness and treatment response in pediatric brain tumors, supporting their potential for non-invasive disease stratification and monitoring.

Despite recent advances in immunotherapy for advanced malignancies, Pancreatic ductal adenocarcinoma (PDAC) remains largely refractory to current immunotherapy due to dense fibrosis, limited antigen presentation, and myeloid-driven immune suppression. Here we report the tumor-targeting, immune remodeling, and safety profiles of the attenuated Salmonella enterica serovar Typhimurium strain CRC2631, and of iSTORM, a next-generation derivative engineered for tumor-localized CMTM6 silencing. CRC2631 preferentially colonizes orthotopic and genetically engineered PDAC tumors, with enrichment in primary lesions and metastases. Tumor-localized CRC2631 induces chemokine and adhesion programs consistent with leukocyte recruitment, increases intratumoral activated T-cell fractions, and triggers transcriptional signatures aligned with innate sensing, interferon signaling, antigen-processing and presentation, and apoptosis programs. iSTORM extends this platform by delivering CMTM6-targeting shRNA to modulate a PD-L1-stabilizing, myeloid-associated immune-evasion programs within tumor-colonized tissue. Compared with CRC2631, iSTORM increases intratumoral CD8+ T cells, shifts T-cell state toward activation with reduced exhaustion-prone features, strengthens antigen-presentation programs, and achieves deeper tumor control. A lyophilized formulation preserves immune remodeling while improving deployability. Mechanistically, glycan arrays and functional studies support mannose-rich glycan-guided tumor engagement. iSTORM toxicity studies, including systemic cytokine, hematologic, blood chemistry, and lethality demonstrate a favorable safety profile. Collectively, these findings establish iSTORM as a safe, programmable, CMTM6-silencing microbial immunotherapy platform that selectively targets and penetrate PDAC tumors to unleash anti-tumor immune activities. What is already known on this topicPDAC is highly resistant to immune checkpoint blockade because dense stroma and myeloid-dominated suppression prevent effective T-cell infiltration; attenuated Salmonella strains can selectively colonize tumors but first-generation agents showed limited efficacy and safety concerns. What this study addsThis study defines CRC2631/iSTORM as a tumor-selective microbial immunotherapy that exploits surface-exposed, mannose-rich N-glycans to colonize PDAC, delivers CMTM6 silencing, and restores CD8+ T-cell activation and tumor control in models resistant to PD-1 blockade immunotherapy. How this study might affect research, practice or policyThese findings provide a mechanistic blueprint for glycan-guided, CMTM6-targeted bacterial "living drugs," support rational combination strategies for deepening therapeutic effect, and establish a lyophilized, biocontained platform that could be developed into scalable microbial immunotherapies for PDAC and other immunologically cold solid tumors.

Pediatric-type diffuse high-grade gliomas (pHGGs) are aggressive, heterogeneous brain tumors shaped by intricate cancer-microenvironment cell-cell interactions. Here, we present an integrative multimodal pHGGmap, encompassing over 800,000 cells from 136 patients profiled across transcriptomic, epigenomic, and spatial modalities. Its analysis delineated robust cancer-myeloid cell programs that structured the tumor ecosystem and identified ten distinct cancer cell states, including previously unrecognized developmental and context-responsive programs. Among these, radial glial-like (RG-like) cells exhibited dual stress-adapted and infiltrative phenotypes. Tumor-associated monocyte-derived macrophages and resident microglia engaged in four distinct immunomodulatory programs aligned with specific cancer states. Three conserved multicellular communities were maintained across treatment, including a stable, spatially and transcriptionally linked RG-like/complement-macrophage niche, indicative of cellular co-option and adaptation to support invasion. Longitudinal profiling of a metastatic diffuse midline glioma case showed that RG-like cells predominate during dissemination and remain associated with complement-enriched macrophages, whose reprogramming restores immune activation. pHGGmap establishes a landmark resource for translational discovery. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=183 SRC="FIGDIR/small/701142v1_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@7ae699org.highwire.dtl.DTLVardef@b95b92org.highwire.dtl.DTLVardef@12adcf9org.highwire.dtl.DTLVardef@1118703_HPS_FORMAT_FIGEXP M_FIG C_FIG

Prostate cancer remains a major health burden with limited success in immune-targeted therapies. To identify immune-cell-specific therapeutic targets, we integrated single-cell cis-eQTL data across 14 immune cell types, bulk eQTLs, GWAS summary statistics from PRACTICAL and FinnGen, and single-cell RNA-seq data from prostate tumors. Using Mendelian randomization and Bayesian colocalization, we prioritized 80 causal eGenes with shared genetic signals, especially in CD4 and CD8 T cells. Functional analyses revealed enrichment in immune-related pathways such as antigen processing and cytokine signaling. Meta-analysis validated 52 robust eGenes across cohorts. Single-cell transcriptomics confirmed cell-type-specific expression of key genes including HLA-DQA2, TXN, and COX6B1 within the tumor microenvironment. Drug repurposing analysis identified potential therapeutic targets such as IGF1R and FAAH, with known drug interactions mapped via DrugBank and STRING. Our integrative framework highlights immune-cell-specific genetic drivers and actionable targets in prostate cancer, offering a high-resolution resource for precision immunotherapy development.

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.

Pancreatic ductal adenocarcinoma (PDAC) is refractory to immunotherapy due to its immunologically cold microenvironment and the scarcity of mutation-derived neoantigens. Here, we introduce NeoAPP, a computational tool designed to systematically decode neoantigens arising from tumor-specific transcripts (TSTs) generated by transcriptional dysregulation. Multi-cohort transcriptomic profiling of 413 PDAC samples using NeoAPP reveal a median of 351 neoantigens per sample derived from 56 neoantigen-encoding TSTs (neoTSTs), surpassing mutation-derived counterparts in both abundance and patient coverage. Mechanistic analyses show that non-canonical splicing junction and transposable element activation drive neoantigen generation, while FOXA2-regulated promoter usage constitutes a potential major source of neoTSTs. Tumor-derived neoTSTs are also detected in extracellular vesicles and cancer-associated fibroblasts, implicating stromal crosstalk in immune modulation. Vaccination with neoTSTs induce CD8+ T cell responses in HLA-A*02:01/A*11:01 transgenic mice and suppressed tumor growth in syngeneic PDAC models. Collectively, this work establishes TST-derived neoantigens as a dominant and therapeutically actionable antigen reservoir in PDAC, advancing a transcriptome-guided framework for neoantigen discovery with potential to overcome immune resistance in low-mutation cancers. Abstract Figure O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=196 SRC="FIGDIR/small/705024v1_ufig1.gif" ALT="Figure 1"> View larger version (71K): org.highwire.dtl.DTLVardef@82ff31org.highwire.dtl.DTLVardef@401342org.highwire.dtl.DTLVardef@b0771corg.highwire.dtl.DTLVardef@15c03ef_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundImmune checkpoint inhibition has transformed cancer therapy; however, many patients fail to respond to single-agent blockade, and combination strategies are often limited by toxicity. Central nervous system tumors exploit multiple immunosuppressive pathways, including the CD200 and PD-1/PD-L1 axis to evade anti-tumor immunity and support tumor aggressiveness. MethodsWe investigated ARL200, a peptide ligand targeting the CD200 activation receptor (CD200AR) using in vitro immune assays, murine syngeneic tumor models, phosphoproteomics, and correlative studies from a first-in-human trial in recurrent glioblastoma. ResultsARL200 exposure activated DAP10/12-dependent signaling and downregulated multiple inhibitory immune checkpoint receptors, including CD200R1, PD-1, and CTLA-4, and checkpoint ligands, CD200 protein and PD-L1, through suppression of the JAK1/3-SHP-STAT-IKK/{beta}-NF{kappa}B pathway. Distinct ARL200 variant peptides elicited unique immune responses. In patients with recurrent glioblastoma, ARL200 treatment was associated with immune activation, reduced inhibitory checkpoint expression, and evidence of antigen-specific memory responses without treatment-related toxicity. ConclusionsTargeting CD200AR enables coordinated modulation of multiple immune checkpoints with a single agent, representing a next-generation immunotherapeutic strategy opening a new pathway for treating aggressive malignancies. Key PointsO_LIARL200 elicits an active immune response for the development of a potent and durable anti-tumor response C_LIO_LIARL200 abolishes the suppressive effects of multiple immune checkpoint blockades C_LIO_LIDifferent ARL200 sequences drive alternative immune responses. C_LI Importance of the StudyTumors exploit multiple immune checkpoint pathways to suppress antitumor immunity, particularly within the immunosuppressive microenvironment of the central nervous system. Current immune checkpoint inhibitors often require combination therapy to achieve clinical efficacy, frequently at the cost of increased toxicity. In this study, we demonstrate that targeting the CD200 activation receptor (CD200AR) with a peptide ligand provides a novel strategy to simultaneously downregulate multiple inhibitory immune checkpoints, including CD200R1, PD-1, PD-L1, and CTLA-4, through a shared intracellular signaling pathway. ARL200 engagement activates DAP10/12-dependent signaling while suppressing the JAK1/3-SHP-STAT-IKK/{beta}-NF{kappa}B axis, thereby overriding tumor-mediated immunosuppression. Importantly, this multi-checkpoint modulation is achieved with a single therapeutic agent and translates to immune activation and clinical responses in patients with recurrent glioblastoma, with minimal treatment-related toxicity. These findings establish CD200AR targeting as a next-generation immunotherapeutic approach with the potential to improve the safety and efficacy of immune-based therapies for aggressive CNS malignancies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=179 SRC="FIGDIR/small/26345679v1_ufig1.gif" ALT="Figure 1"> View larger version (80K): org.highwire.dtl.DTLVardef@17a5010org.highwire.dtl.DTLVardef@11e67eborg.highwire.dtl.DTLVardef@1387c07org.highwire.dtl.DTLVardef@156d418_HPS_FORMAT_FIGEXP M_FIG C_FIG