Cell Reports Medicine

GLP-1 receptor agonists have reshaped obesity therapeutics, but their impact on neuropsychiatric outcomes remains poorly characterized. From 29 million patients in a large federated data platform across the USA, including 489,785 semaglutide treated patients, we conducted an observational study integrating longitudinal neuropsychiatric outcomes. From this population, we assembled a cohort of 63,215 patients with baseline neuropsychiatric conditions before treatment initiation and evaluated 24 incident neuropsychiatric outcomes. In propensity-matched comparator analyses, during the 2 year time-period from treatment initiation, semaglutide was associated with broadly lower neuropsychiatric event risk than metformin, SGLT2 inhibitors, and DPP-4 inhibitors. Within the semaglutide-treated cohort, higher attained dose during the first two years after the first prescription ("pre-landmark period") was associated with significantly lower incidence during the following two years ("post-landmark period") of diagnostic codes associated with substance-related disorders (P<0.001), mood disorders (P<0.001), anxiety- and stress-related disorders (P<0.001), CNS atrophies (P<0.001), neuromuscular disorders (P=0.013), eating/sleep/behavioral disorders (P=0.022), and personality/impulse-control disorders (P=0.028). Consistent with previous clinical trials, the post-landmark incidence of dementia or CNS degenerative diseases was similar between the high-dose and low-dose semaglutide cohorts (P=0.15). For most neuropsychiatric diagnoses, post-landmark incidence was strongly associated with the maximum attained semaglutide dose during the pre-landmark period, but incident cognitive symptoms and speech/language symptoms were more closely linked to the pre-landmark weight-loss magnitude (p<0.001 and p<0.003, respectively). Bulk and single-cell transcriptomic analyses demonstrated GLP1R expression in CNS tissues (hypothalamus, caudate, putamen, nucleus accumbens, cerebellum) and peripheral nerves. Age-associated heterogeneity in GLP1R expression was evident in several of these compartments including the caudate nucleus, suggesting dynamic changes in the availability of the neurobiological substrate for semaglutide response. Together, these data support a model in which semaglutide confers a sustained, dose-dependent, weight loss-independent benefit across multiple neuropsychiatric conditions via direct CNS target engagement. This observational study motivates prospective clinical studies and mechanistic analyses to clarify the impact of GLP-1 receptor agonists on human neuropsychiatric pathways and disease processes.

High-grade serous ovarian carcinoma (HGSC) is an aggressive malignancy for which bulk transcriptomic subtypes are used to stratify tumors, interpret biology, and guide biomarker development. The four TCGA-derived subtypes, mesenchymal (C1.MES), immunoreactive (C2.IMM), proliferative (C5.PRO), and differentiated (C4.DIF), are consistently observed across cohorts. However, despite their prominence, these subtypes have not translated into therapeutic utility, and their biological basis remains unresolved. Here, we show that HGSC transcriptomic subtypes are largely determined by tumor cellular composition rather than intrinsic malignant transcriptional programs. By integrating controlled single-cell-derived pseudobulk simulations with deconvolution-based analysis of 1,834 primary HGSC tumors across RNA-seq and microarray cohorts, we demonstrate that subtype probabilities align along a composition-driven axis of stromal and immune variation. Cellular composition alone predicted subtype labels with high accuracy (ROC-AUC = 0.81-0.95) and explained a substantial fraction of subtype-associated transcriptomic variation, with the mesenchymal (C1.MES) subtype representing the most robust and reproducible example of composition-driven signal. Although a secondary, composition-independent expression signal is detectable, it does not define the dominant structure of subtype classification. These findings redefine HGSC transcriptomic subtypes as features of the tumor ecosystem rather than discrete malignant states. This reinterpretation has immediate implications for studies that use subtype labels to infer tumor-intrinsic biology and provides a generalizable framework for separating composition-driven and intrinsic signals in bulk tumor data. Significance StatementHGSC transcriptomic subtypes lack consistent clinical utility and remain biologically ambiguous. We show subtype assignments are largely driven by tumor cellular composition, and less so by distinct intrinsic tumor states.

KIF18A inhibition has emerged as a therapeutic strategy for chromosomally unstable cancers, but clinical development is limited by the absence of a deployable predictive biomarker. Here we identify strong, diffuse p16INK4a expression, a well-established surrogate marker of Rb-pathway inactivation, as a predictive biomarker of response to KIF18A inhibition, and show that Rb-pathway inactivation marks a biologically distinct subset of cancers sensitive to this therapeutic approach. In sensitive models, low Rb activity is associated with robust spindle assembly checkpoint signaling and prolonged mitotic arrest following KIF18A inhibition. Weakening the spindle assembly checkpoint in this context is sufficient to confer resistance. Across three independent pan-cancer sensitivity datasets generated with distinct KIF18A inhibitors, Rb-pathway altered models were significantly more sensitive than histology-matched Rb-intact comparators, with the strongest association observed in cancers harboring direct RB1 loss or inactivating mutation. Guided by this mechanism, we retrospectively analyzed p16INK4a expression by immunohistochemistry (IHC) in pre-treatment tumor biopsies from 79 heavily pre-treated high-grade serous ovarian cancer patients across three dose-escalation or expansion cohorts and treated with two different KIF18A inhibitors (sovilnesib and VLS-1488) sharing a common mechanism of action. p16INK4a-high tumors showed substantially higher objective response rates than their p16INK4a-low counterparts (36.0% versus 2.2%; P = 0.0002) and markedly longer progression-free survival (median 24.3 versus 7.9 weeks; hazard ratio, 0.16; P < 0.0001). These findings establish p16INK4a as a mechanistically-based, clinically implementable biomarker of clinical response to KIF18A inhibition that is poised to support pan-cancer development of KIF18A inhibitors guided by Rb-pathway inactivation.

1.The ABACUS study was a single arm, phase II trial evaluating neoadjuvant atezolizumab in operable urothelial carcinoma (UC). Initial bulk transcriptomic and immunohistochemistry analyses suggested links between immune activation, tissue remodeling, and resistance pathways such as transforming growth factor {beta} (TGF{beta}) that were associated with clinical outcome. To further characterize spatial and phenotypic changes at high resolution, artificial intelligence-assisted digital image analysis of hematoxylin and eosin sections and spatial transcriptomics (10x Genomics Visium) were performed on paired tissue samples. In baseline samples, cells residing in lymphoid aggregates and tertiary lymphoid structures (LAs/TLSs) were more abundant in stable disease than in relapse and exhibited gene expression programs associated with improved survival in UC. Most spatial features reflected shared pharmacodynamic changes between stable disease and relapse; however, carcinoma-endothelial adjacency was reduced significantly following treatment and differed between groups, accompanied by distinct transcriptional programs. Together, these findings indicate that atezolizumab induces localized immune and stromal remodeling within the tumor microenvironment, while non-response despite immune expansion is associated with persistent spatial immune exclusion and carcinoma-endothelial adjacency. Spatial and phenotypic biomarkers identified here may inform rational combination strategies for immune checkpoint inhibitor-refractory urothelial carcinoma.

In a confirmatory study, we evaluated the immunogenicity and protective efficacy of a heterologous prime-boost vaccination strategy against respiratory syncytial virus (RSV) in non-human primates. Building on prior evidence of protective mucosal immunity induced by intramuscular DNA priming followed by an oropharyngeal adenoviral boost, we conducted a randomized, blinded, dual-centre study across two European primate research facilities. Rhesus macaques received a codon-optimized RSV-F DNA vaccine via electroporation, followed by two mucosal administrations of a recombinant adenovirus serotype 5 vector encoding the same antigen. Control groups included animals vaccinated with irrelevant influenza antigens and a comparator group mimicking natural immunity induced by primary RSV infection. Systemic and mucosal immune responses, including RSV-F-specific antibodies and tissue-resident memory T cells, were monitored longitudinally. Here, we detected robust immune responses, but with some variability between the two centres. However, following experimental RSV challenge performed 22 weeks after the final immunization, RSV-vaccinated animals demonstrated markedly reduced viral replication in both upper and lower respiratory tracts. However, unexpected RSV-specific immunity in the control group at one single study site prevented confirmation of the predefined primary endpoint. Overall, these results support the potential of mucosal adenoviral boosting following DNA priming to induce protective immunity against RSV, while highlighting challenges associated with multi-centre preclinical vaccine studies.

Glioblastoma (GBM) is the most prevalent primary brain cancer, with poor prognosis and limited therapeutic options available. The genetic and cellular heterogeneity characteristic of GBM contributes to poor response rates. Activating mutations of the epidermal growth factor receptor (EGFR) gene are among the most frequent alterations in GBM, occurring in roughly half of cases. Despite the prevalence of EGFR mutations, EGFR inhibition has shown limited success in GBM. The transcription factor C/EBP{beta} is a master regulator of the mesenchymal transformation in GBM, an aggressive state characterized by increased invasiveness and resistance to chemotherapy. Lucicebtide is a C/EBP{beta} antagonist peptide with demonstrated single agent activity in patients with recurrent GBM that is currently being evaluated in a clinical trial in combination with radiation and temozolomide in patients with newly-diagnosed GBM (NCT04478279), with emerging data supporting clinical activity in that setting. Here we show that in the TCGA-GBM dataset, patients with EGFR mutations display significant enrichment of a high C/EBP{beta} activity signature. Functionally, genetic inactivation of EGFR by CRISPR results in synthetic lethality in the presence of lucicebtide in GBM cell lines, and synergistic in vitro cytotoxicity and suppression of C/EBP{beta} target gene expression was observed in combination experiments with lucicebtide and EGFR inhibitors. Finally, enhanced anti-tumor activity was demonstrated in vivo in the combination setting, as combined subpharmacologic dose levels of lucicebtide and the EGFR inhibitor osimertinib potently suppressed GBM xenograft growth. These data identify EGFR and C/EBP{beta} dependencies in GBM and support lucicebtide combination with EGFR inhibitors as a potential therapeutic option for a sizable fraction of GBM patients.

Protein arginine methyltransferase 5 (PRMT5) is a synthetic lethal target in methylthioadenosine phosphorylase-deleted (MTAP-null) cancers. Second-generation MTA-cooperative PRMT5 inhibitors preferentially target MTAP-null cells while largely sparing MTAP-wildtype (MTAP-WT) cells, thereby improving tumor selectivity over first-generation PRMT5 inhibitors. Despite encouraging efficacy and safety signals in early clinical studies, the modest objective response rates (ORRs) observed with these inhibitors suggest that intrinsic or acquired resistance may limit their clinical benefit. Here, we investigated mechanisms of acquired resistance to the MTA-cooperative PRMT5 inhibitor BMS-986504/MRTX1719 in MTAP-null non-small cell lung cancer (NSCLC) cells and sought to identify therapeutic vulnerabilities that emerge upon resistance. Using multiple in vitro-derived resistant models, we found that acquired resistance was not fully explained by alterations in PRMT5 activity or reduced MTA levels. Instead, resistance was associated with collateral sensitivity to MEK inhibition and enrichment of MAPK-related transcriptional programs. Together, these findings identify MEK inhibition as an actionable collateral vulnerability in MTAP-null NSCLC cells that acquire resistance to PRMT5 inhibition.

Cancer-associated fibroblasts (CAFs) contribute to immune exclusion and therapy resistance in solid tumors, limiting the efficacy of chimeric antigen receptor (CAR) T cell and immune cell therapy. To overcome this, we developed a transcription factor (TF)-based strategy to reprogram prostate-derived CAFs (pCAFs) into normal fibroblast-like cells (NFs). We prioritized TFs enriched in quiescent stellate cells--Vitamin D receptor (VDR), Peroxisome Proliferator-Activated Receptor gamma (PPAR{gamma}), and p53--and selected VDR for proof-of-concept studies. Lentiviral VDR expression in pCAFs produced VDR-reprogrammed NFs (VDR-rpNFs) with reduced CAF markers, increased ATP, and suppressed TGF-{beta} and IL6, indicating phenotypic and metabolic reversion. In both in vitro 3D co-cultures and in vivo, VDR-rpNFs disrupted tumor architecture, enhanced CAR T cell infiltration, and reduced necrosis. PPAR{gamma}- and p53-rpNFs showed similar reprogramming effects. These results suggest TF-guided fibroblast reprogramming as a viable strategy to remodel the tumor microenvironment and improve CAR T cell efficacy in solid tumors.

Type 2 diabetes (T2D) is a heterogeneous disease shaped by genetic pathways related to insulin resistance and beta cell dysfunction, but how this heterogeneity is reflected molecularly remains unclear. We integrated partitioned polygenic scores (pPS) with proteomic and metabolomic profiling to define molecular signatures of T2D and their clinical relevance. We analyzed UK Biobank participants with genomic, proteomic, and metabolomic data. In a disease-free training subset, we used LASSO regression to identify multi-omic signatures associated with each pPS by jointly modeling proteins and metabolites. In an independent testing set, we constructed multi-omic scores and examined their associations with clinical traits and diabetes-related outcomes. Mediation analyses were used to investigate putative causal pathways. Key findings were evaluated in the Multi-Ethnic Study of Atherosclerosis (MESA). We identified distinct multi-omic signatures that capture the molecular architecture of T2D genetic risk across physiological subtypes. Compared with genetic scores alone, multi-omic pPS showed larger effect sizes and better disease discrimination. These scores recapitulated subtype-specific physiology and were associated with T2D risk. The Beta-Cell 2 multi-omic score showed marked stratification for insulin use, which was replicated in MESA, where it also predicted future insulin use. Mediation analyses implicated lipoprotein remodeling and fatty acid metabolism in the Lipodystrophy 1 cluster, accounting for up to 45% of the total effect of pPS on T2D risk. Integrating process-specific genetic risk with circulating multi-omic profiles reveals biologically distinct endotypes of T2D and supports a framework for improved patient stratification and risk assessment.

Background: Acute necrotizing encephalopathy (ANE) is a rare and severe neurologic complication of viral infection in children, thought to result from a hyperacute cytokine storm causing blood-brain barrier disruption and central nervous system injury. Despite characteristic clinical and radiologic features, ANE remains poorly understood at the molecular level, with no validated biomarkers or targeted therapies. We aimed to determine whether genetic predisposition to ANE due to RANBP2 variants is associated with a distinct immunologic signature. Methods: We conducted a prospective biological study of familial ANE (ANE1, NCT06731790). We included 23 heterozygous carriers of the RANBP2 c.1754C>T (p.Thr585Met) variant from 10 families, and 28 noncarriers (median age, 40 years [range, 4-72]). Soluble immune mediators, transcriptomic analyses, multiparameter flow cytometry, and cellular imaging were analysed in peripheral blood mononuclear cells (PBMCs) and monocytes. Baseline and resiquimod stimulated immune responses were analysed within the same statistical model, with genetic status as the primary predictor. Findings: The RANBP2 Thr585Met mutation was associated with a dysregulated inflammatory phenotype characterized by reduced basal mediator production and exaggerated TNF- responses following stimulation (estimated difference, +2,098 pg/mL; 95% CI, 1,121 to 3,076; P=0.0001). Transcriptomic and flow cytometry analyses showed broad reprogramming of myeloid cells with enrichment of CXCR3-high CD14-high subsets. Expansion of these populations was associated with increased long-term disease burden. The RANBP2 variant was the only independent factor associated this inflammatory phenotype. Interpretation: RANBP2-associated ANE is characterised by a distinct immunological signature that can inform disease stratification and support the development of targeted immunotherapeutic approaches.

Desmoid fibromatosis (DF) is a rare mesenchymal neoplasm with an unpredictable clinical course, where spontaneous regression or progression occurs in a significant subset of patients through largely undefined mechanisms. The use of active surveillance (AS) offers the opportunity to investigate whether tumor- or host-driven systemic and local immune features may explain these divergent outcomes, improving patient management. A prospective observational study enrolled 55 patients with primary sporadic DF managed with AS. Clinical evolution was categorized as progression, regression, or stable disease according to RECIST 1.1. Immunomonitoring with multicolor flow cytometry identified distinct systemic T-helper polarization states stratifying clinical trajectories: regressors showed a Th2-skewed profile, while progressors displayed activated T-helper cells and Th1/Th9/Th17 subsets. Higher baseline Th2 levels associated with regression and longer progression-free survival. Plasma proteomic and whole-blood transcriptomic analyses confirmed coordinated IL-4/IL-13-linked pro-resolving programs in regressors and inflammatory, early T-cell activation signatures in progressors. Tumor transcriptomics revealed adaptive, antigen-presentation and restrained immune programs in regressing lesions versus innate inflammatory, interferon and TGF-{beta}-driven fibrotic pathways in progressing tumors. These findings identify systemic T-helper polarization as a biomarker of DF behavior and highlight coordinated systemic-tumoral immune programs underlying clinical outcomes, supporting more precise clinical management.

Gut microbiota are critical determinants of effective immune checkpoint therapy (ICT), yet the microbial mediators and host mechanisms that enhance antitumor immunity remain poorly understood. Here, we identify the microbiota-derived bile acid taurodeoxycholic acid (TDCA) as a metabolite associated with immune checkpoint therapy (ICT) response. TDCA administration alone is sufficient to overcome antibiotic-induced ICT hyporesponsiveness across multiple murine tumor models. Mechanistically, TDCA directly enhances CD8 T cell-mediated antitumor immunity, increasing cytotoxicity. These effects required signaling through the bile acid receptor TGR5. Together, these findings reveal TDCA as a gut microbial metabolite that restores ICT efficacy after antibiotic disruption by directly augmenting CD8 T cell anti-tumor activity. This work supports metabolite replacement as a therapeutic strategy to mitigate antibiotic-associated loss of cancer immunotherapy response. SignificanceTDCA is a microbiota-derived metabolite that restores immune checkpoint therapy efficacy after antibiotic disruption by directly enhancing CD8 T-cell-mediated anti-tumor immunity through bile acid receptor TGR5 signaling. Our findings suggest that supplementation with defined microbial metabolites can mitigate antibiotic-associated loss of immunotherapy response without requiring broader microbiome reconstitution.

Allogeneic hematopoietic stem cell transplantation (HSCT) is a life-saving treatment for hematologic malignancies, but long-term survivors present with lower muscle mass and functional capacity. In adult HSCT survivors 10-20 years after treatment, single nucleus RNA sequencing uncovered elevated XRRA1 expression levels in all muscle nuclei populations, which was retained in primary muscle stem cell cultures. HSCT survivors were characterized in vivo by impaired neuromuscular innervation that associated with muscle weakness, and lower muscle stem cell neurotrophic action. Despite these impairments, the molecular and physiological responses to heavy resistance training (HReT) were preserved in HSCT survivors, as demonstrated in a pre-registered clinical trial (ClinicalTrials.gov: NCT04922970). After 12 weeks of HReT, gains in muscle mass and strength were similar in HSCT survivors and healthy controls. In addition, we observed that [~]9% of muscle-resident immune cells persist into adulthood and that bone marrow derived cells do not adopt alternative cell fates in muscle tissue, resolving long-standing questions in human muscle biology. Together, these findings uncover molecular mechanisms of HSCT sequelae in muscle nuclei and muscle stem cells, which, importantly, can at least partly be overcome by mechanical loading. Given the growing population of HSCT survivors and the multitude of benefits of HReT for all organ systems, our findings support the importance of HReT in this population to promote healthspan.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent chronic liver disease and strongly linked to obesity and insulin resistance. We previously reported that the common nuclear envelope variant rs6461378 (g.842031C>T; SUN1 H118Y) associated with MASLD and related traits including insulin resistance. To gain insight into how wild-type (WT) and H118Y SUN1 might differentially impact insulin signaling, we performed affinity purification-mass spectrometry (AP-MS) in human liver-derived cells stably expressing WT or H118Y SUN1. Unbiased AP-MS revealed a novel SUN1-CUL3 interaction, with comparative analysis showing that WT SUN1 interacted robustly with CUL3, while CUL3 interaction was markedly diminished with H118Y SUN1. Cells in which SUN1 was silenced via siRNA, or in which H118Y SUN1 was ectopically expressed, showed increased CUL3 neddylation, which is required for cullin RING ligase (CRL)-mediated ubiquitination of insulin receptor substrate (IRS) proteins. Inhibition of neddylation restored IRS-1 levels and insulin signaling in H118Y SUN1-expressing cells. Together, our findings provide a potential mechanism of H118Y SUN1-driven insulin resistance and a viable therapeutic approach for its reversal.

Metabolic dysfunction is increasingly recognized as a risk factor for poor outcomes in breast cancer, but whether incretin-based therapies confer survival benefit beyond weight loss remains unresolved. Using a federated electronic health record platform spanning nearly 29 million patients, we evaluated breast cancer survival after semaglutide and tirzepatide initiation in routine care. In 1:1 propensity-matched pooled-comparator analyses, semaglutide was associated with improved overall survival versus metformin, sodium-glucose cotransporter 2 (SGLT2) inhibitor, and dipeptidyl peptidase 4 (DPP4) inhibitor users, with 54 deaths among 2,433 semaglutide users (2.2%) versus 395 deaths among 2,433 comparators (16.2%) over 24 months (log-rank P < 0.001). Tirzepatide showed a favorable survival association relative to pooled anti-diabetic comparators that did not meet statistical significance (P = 0.24), with 3 deaths among 220 users (1.4%) versus 64 deaths among 220 comparators (29.1%). In a head-to-head propensity-score-matched comparison, overall survival did not differ significantly between semaglutide and tirzepatide treated patients with pre-existing breast cancer (2,117 per arm; P = 0.12). In semaglutide-treated patients alive and observable at the 1-year landmark, higher maximum dose achieved was significantly associated with lower post-landmark mortality (P = 0.034), with an event rate of approximately 1.0% in the high-dose group (>=1.7 mg) versus approximately 4.5% in the low-dose group (0.25-1.0 mg). Despite a linear dose weight loss relationship for semaglutide, however, weight loss strata did not separate survival outcomes (global P = 0.22). In tirzepatide-treated patients alive and observable at the same landmark, neither maximum dose achieved nor weight loss strata separated post-landmark survival (P = 0.98 and P = 0.50, respectively). Structured EHR and AI-based clinical note analyses further showed significantly lower frequency of documented metastatic disease in semaglutide-treated patients relative to pooled anti-diabetic comparators, including any metastasis (7.0% versus 15.0%, rate ratio 0.5, P < 0.001), bone metastasis (1.0% versus 5.2%, rate ratio 0.2, P < 0.001), and liver, lung, or brain metastases (all P < 0.001). LLM-derived cause-of-death extraction further showed a 60% lower relative proportion of cancer-associated deaths in semaglutide-treated patients (19% of ascertainable deaths) than in matched pooled anti-diabetic comparators (47% of ascertainable deaths), with comparator deaths more often attributed to cancer progression involving metastatic breast cancer, leptomeningeal carcinomatosis, and cancer-driven organ failure. Overall, this study demonstrates that semaglutide use in patients with pre-existing breast cancer is associated with a dose correlated but weight loss independent improvement in overall survival. These findings motivate prospective trials of GLP-1 receptor agonists in breast cancer across various stages and treatment settings.

A substantial proportion of cancer patients fail to benefit from their prescribed combination regimens, yet identifying superior alternatives from the vast pharmacological space prior to treatment failure remains an unsolved clinical challenge. Existing computational approaches either rely on multi-omics profiles unavailable in standard oncological practice or reduce drug efficacy to scalar metrics that discard the dose-dependent resolution essential for therapeutic optimization. Here, we present XACT, a hierarchical deep learning framework that reconstructs full dose-dependent drug responses for both monotherapy and drug combinations using only clinically accessible transcriptomic profiles. By leveraging an asymmetric X-Linear Attention mechanism that models second-order interactions between molecular drug substructures and intracellular signaling pathway activities, XACT captures concentration-dependent pharmacodynamics with state-of-the-art accuracy and generalizability to unseen transcriptomic landscapes. When applied to the TCGA pan-cancer cohort, XACT-derived resistance scores were significantly associated with clinical treatment outcomes and stratified overall survival as the strongest independent prognostic factor after multivariate adjustment for tumor stage and cancer type. Systematic virtual screening revealed therapeutic vulnerabilities and nominated alternative regimens for treatment-refractory sarcoma and pancreatic adenocarcinoma. These results establish XACT as a scalable, interpretable, and clinically translatable framework that advances precision oncology from computational prediction toward data-driven therapeutic prescription.

Type 2 diabetes and prediabetes affect hundreds of millions of people globally, yet the metabolic networks underlying disease development remain poorly understood. Using untargeted liquid chromatography-mass spectrometry (LC-MS/MS), we profiled a total of 15,470 (900 known) serum metabolite features across the human diabetes spectrum (the most comprehensive coverage reported to date). Weighted coexpression network analysis of samples from people with normal glucose tolerance, prediabetes, and type 2 diabetes, collected at baseline and 2 hours after an oral glucose tolerance test, revealed tightly coregulated modules strongly associated with glycemic dysregulation, insulin resistance, and islet dysfunction. Notably, short-chain organic acids, particularly crotonic acid, emerged as hubs of the diabetes-associated networks, accumulating progressively with disease severity. Reanalysis of extracellular vesicle proteomics from the same cohort showed that 16.5% of circulating proteins were crotonylated, with 47.6% correlated with crotonic acid and other hub metabolites, establishing a metabolome-crotonylome axis as a novel mechanism in diabetes development.

Ramaswamy et al. recently reported in Nature Medicine that ChatGPT Health, a consumer-facing health AI tool, undertriaged 51.6% of true emergencies. It was also susceptible to social anchoring in a structured stress test of triage recommendations. We applied the same vignette-based benchmark to OpenEvidence, a widely used physician-facing AI platform for clinical decision support. The benchmark included 960 prompts across 21 clinical domains (Supplementary Table S3). OpenEvidence undertriaged 12.5% of emergencies, a four-fold reduction relative to ChatGPT Health. It also showed no anchoring effect. Its errors skewed in a safer direction, including 68.0% overtriage of Home presentations. In 65 of 960 responses (6.8%), it declined to assign a triage level. These refusals occurred only in symptom-only prompts and never in urgent or emergency cases. Performance improved when objective clinical data were provided. Under the same benchmark, a widely used physician-facing system showed a different safety profile from a consumer-facing one. This suggests that who a health AI is built for can shape how it fails.

Purpose: Limited CNS bioavailability and pharmacodynamics are obstacles to effective systemic therapies for glioblastoma. One strategy to overcome these challenges is drug combinations enhancing CNS penetration and/or tumor chemosensitivity. LP-184, a synthetic acylfulvene class alkylator, induces DNA damage and inhibits glioblastoma cell viability in pre-clinical models. LP-184 is a prodrug converted to active metabolites by intracellular prostaglandin reductase 1 (PTGR1) that is over-expressed in >70% of glioblastoma. DNA damage induced by LP-184 is MGMT agnostic and reversed by transcription-dependent NER. Patients: LP-184 was evaluated in a Phase 1a study (NCT05933265) in 63 adult patients with advanced malignancies including 16 patients with recurrent glioblastoma. All patients with glioblastoma received prior standard-of-care therapy and most had received 1 or more additional therapies before enrollment. Results: Patients with glioblastoma experienced more frequent transaminitis, Grade 1-2 nausea and a trend towards more frequent and severe thrombocytopenia compared to the non-glioblastoma cohort. Otherwise, overall toxicity profiles were similar. Clinical pharmacokinetic analysis combined with published pre-clinical intra-tumoral bioavailability data (~20% penetration) predicted that LP-184 at the recommended dose for expansion (RDE) would achieve cytotoxic levels if combined with spironolactone, a BBB permeable ERCC3 degrader and TC-NER inhibitor that sensitizes glioblastoma cells to LP-184 3-6-fold. We show that three daily doses of spironolactone deplete orthotopic glioblastoma PDX ERCC3 protein by ~ 80% and increases tumor LP-184 cytotoxicity 2-fold. Conclusions: LP-184 is well tolerated at the RDE, and we establish a clinically translatable scheme for dosing spironolactone in combination with LP-184 for a future Phase 1b clinical trial.

Abstract / SummarySurvival outcomes for pediatric Burkitt lymphoma (BL) substantially vary depending on geography (50-90%), which also serves as a proxy for the prevalence of Epstein-Barr virus (EBV) within the tumors. Although BL is considered an immunologically "cold" tumor with few tumor-infiltrating lymphocytes (TILs), their functional status has not been fully evaluated, especially for EBV-positive disease. Here, we characterize the exhaustion and activation profiles of T cells in the tumor microenvironment (TME) of EBV-positive BL using orthogonal methods, single-cell gene expression analysis, spectral flow cytometry, and immuno-histochemistry staining (IHC). We found that CD8+ TILs displayed a mosaic of immune inhibitory gene expression encoding, PD1, TIGIT, LAG3 and HAVCR2/TIM3. IHC validated the expression of PD1 and TIGIT on CD8+ TILs, as well as their respective ligands, PDL-1, PVR, and Nectin-2 on malignant B cells. Despite exhaustion-associated signatures, CD8+ TILs retain cytotoxic potential, expressing granules (i.e. Granzyme A, Perforin) and cytokines (i.e. IFN{gamma}) and demonstrate an increased uptake of metabolites such as glucose, arginine, and methionine. In peripheral blood, pediatric BL patients exhibited a significantly higher abundance of PD1+TIGIT+ CD8+ T cells compared to healthy children. Notably, these circulating T cells from BL patients express significantly lower levels of TOX, suggesting they are not irreversibly dysfunctional. Together, our results indicate that CD8+ T cells both in the TME and in circulation of children with BL are not terminally exhausted but remain poised for functional re-invigoration. These findings support the potential integration of immune checkpoint inhibitors into combination chemotherapeutic regimens to improve outcomes for these children. SignificanceEBV-positive BL tumors contain functional, metabolically active CD8+ T cells. Circulating PD1+TIGIT+CD8+ T cells found in BL patients blood are a biomarker for those in the tumor microenvironment.