Citations

Cellular senescence is an irreversible stress response, which leads to loss of cellular function and remodeling of the cellular secretory profile. In humans, pancreatic β cells undergo cellular senescence during the progression to type 2 diabetes (T2D). However, the mechanism linking β cell senescence to islet dysfunction remains unknown, and thus the therapeutic potential of targeting senescent cells in T2D is not established. Herein, we identified a subpopulation of senescent β cells expressing p21, which emerged early in the progression of T2D in humans and mice. Spatial transcriptomics and proteomics analyses confirmed senescence and loss of cellular identity in this subpopulation in humans. Functional analysis revealed lack of glucose responsiveness, high basal insulin secretion, and transcription of senescence-associated secretory phenotype (SASP) factors. SASP factors from p21 + β cells induced secondary senescence in neighboring cells, characterized by dysfunction and loss of identity. JAK inhibitors counteracted the induction of secondary senescence and restored β cell function in islets from humans with T2D and in mice fed a high-fat diet. These findings reveal the critical role of p21 + β cells in T2D pathogenesis and the therapeutic potential of targeting this pathophysiological process.

ABSTRACT Biological aging greatly impacts the body’s ability to handle glucose, and represents a major risk factor the development and progression of type 2 diabetes (T2D). Nonetheless, despite advances in cellular senescence research and the development of new senolytic therapies, the heterogeneity of cellular senescence in the human endocrine pancreas, as well as its roles in normal aging, remains to be elucidated at the single-cell level. Here, we performed single-cell–resolved spatial proteomics and transcriptomics on intact pancreas from 26 donors (ages 20–80) and multiplexed single-cell RNA sequencing and functional assays on dispersed islets from 14 donors (ages 34–69). We identify two discrete SnC subpopulations distinguished by relative expression of CDKN1A and CDKN2A. CDKN1A ⁺ senescent cells (SnCs) exhibit loss of β-cell identity, impaired insulin secretion, and a proinflammatory SASP associated with increased islet immune infiltration. In contrast, CDKN2A ⁺ SnCs retain transcriptional identity and functional competence, with lower inflammatory signaling. Together, these findings identify heterogeneous and functionally divergent senotypes in the human pancreas, distinguishing an adaptive ( CDKN2A ⁺) from a maladaptive ( CDKN1A ⁺) senescence program, thus providing a mechanism-guided framework for senescence-targeted therapies in T2D.

3118 Background: Improved risk stratification is critically needed across multiple cancers to guide treatment decisions. This includes reducing overtreatment in Ductal Carcinoma in Situ (DCIS), addressing late recurrence risk in estrogen receptor-positive/lymph node-negative (ER+/LN-) breast cancer (BC), and refining prognosis in head & neck squamous cell carcinomas (HNSCC), and high-grade serous ovarian carcinoma (HGSOC). Tumor-infiltrating lymphocytes (TILs) reflect anti-tumor immunity, whereas tumor-associated macrophages (TAMs) polarize toward anti-tumor M1-like (CD68+) or immunosuppressive M2-like (CD163+) phenotypes. Integrating TILs with TAM polarization markers may better capture inflammatory balance and improve outcome prediction. We developed a hematoxylin and eosin (H&E)-only AI method (VAIP) to quantify TILs and virtual CD68/CD163 TAMs to develop multi-cancer based potential prognostic models. Methods: TILs were detected on H&E with HoVer-UNet, and virtual CD68 and CD163 macrophages were inferred with VISTA. In cancer regions, we computed cell densities and immune-balance ratios and trained cancer-specific Cox models with compact feature sets (DCIS 6; HGSOC 7; ER+ 4; HNSCC 4). Prognostic stratification used disease-free survival (DFS) for DCIS (N=273), HGSOC (training N=165, independent test N=220), and ER+ BC (training N=144, test N=622), and overall survival (OS) for HNSCC (N=77), reflecting clinical endpoints. Evaluation used cross-validation for cohorts without an external test set (DCIS, HNSCC) and independent training and testing when independent cohort was available (HGSOC, ER+). Results: Risk stratification performance across cancer types is in Table 1. The DCIS model used 6 features, largely TIL-macrophage contrast ratios (TIL/M2, TIL/M1). HGSOC used 7 features with a similar ratio-heavy immune-balance signature, plus macrophage-normalized density and polarization metrics (e.g., M1/N, M/N). In contrast, ER+ BC and HNSCC achieved best performance with 4 features dominated by macrophage measures, particularly M2 density and the M1/M2 ratio. Across sites, CD163-related macrophage metrics and immune-balance ratios were consistently informative. Conclusions: Integrating H&E-visible TILs with virtual CD68/CD163 TAMs enables fully automated, H&E-only prognostic biomarkers that stratify OS and DFS across multiple cancers, demonstrating consistent prognostic value in DCIS, ER+ BC, HGSOC, and HNSCC. These findings support further study of this histomorphometric risk classifier through broader external and prospective validation. Performance across cancer types. Cancer Type Cohort C-index HR [95% CI] p-value DCIS All 0.616 1.76 [1.20-2.59] <0.001 DCIS RT/No-treatment 0.624 1.94 [1.15-3.26] 0.003 HGSOC Test 0.553 1.38 [1.02-1.87] 0.030 ER+ BC Test 0.577 1.51 [1.00-2.28] 0.004 HNSCC All 0.603 1.92 [1.03-3.36] 0.012

Multiple sclerosis (MS) is an immune-mediated chronic inflammatory and degenerative disease of the central nervous system (CNS). Typically occurring in young and middle-aged individuals, untreated MS can have high rates of disability and recurrence, thereby imposing a significant burden on the patient, their family, and society. Many factors are implicated in the etiology of MS, with the relationship between Epstein-Barr Virus (EBV) infection and the development of MS being the subject of extensive research recently. When the human body experiences a decline in immune function, it may trigger reactivation of EBV, and this reactivation is also believed to increase the risk of onset or relapse of MS. Currently, the phenomenon of cross-reactivity resulting from molecular mimicry following EBV infection (including reactivation status) is theorized as a contributing etiology. EBV-mediated abnormalities in T cells and B cells also play a key role in the development of MS. However, the underlying mechanisms have not been thoroughly understood. Meanwhile, the limited availability of effective treatment options for MS, in particular MS progression, underscores the urgent need for novel therapeutic strategies. Here, we discuss the pathophysiological mechanisms underlying MS, specifically emphasizing the relationship between EBV infection and the disease pathology. Furthermore, we introduced relevant pharmacological targets in order to propose a broader range of therapeutic alternatives for individuals diagnosed with MS.

As an emerging tire wear-derived environmental contaminant, 6PPD-quinone (6PPDQ) has raised significant concerns regarding its neurotoxic potential, particularly for children exposed to recycled tire crumb rubber in playgrounds. However, the molecular mechanisms by which 6PPDQ influences neurological disorders such as epilepsy remain poorly understood. In this study, we employed an integrative framework combining network toxicology, bulk analysis of human epileptic brain tissues, Mendelian randomization, and molecular dynamics simulations to elucidate these mechanisms. Our findings, validated through CETSA-WB and SPR, identify 6PPDQ as a direct ligand that binds to and stabilizes neuronal TP53. Through a synergistic double-hit mechanism, 6PPDQ directly engages the TP53 pathway while simultaneously triggering microglial interleukin-6 secretion. These converging pathways lead to the suppression of the master antioxidant regulator Nrf2, resulting in glutathione depletion, excessive reactive oxygen species accumulation, and exacerbated neuronal damage under excitotoxic stress. Experimental validation using glutamate-induced HT22 cell models and microglia–neuron crosstalk systems confirmed that targeting the TP53/Nrf2 axis or scavenging ROS significantly attenuates 6PPDQ-induced neurotoxicity. Our findings highlight critical risks to pediatric neurological health posed by tire-derived contaminants and identify the TP53/Nrf2 axis as a promising therapeutic target. Furthermore, this work provides a robust scientific basis for refining risk assessment frameworks and developing regulatory strategies to mitigate environmental exposure to 6PPDQ.

Abstract Prostate adenocarcinomas (PRAD) can acquire resistance to androgen receptor signaling inhibitors through lineage transition to a cell state known as neuroendocrine prostate cancer (NEPC). Using a panel of isogenic PRAD and NEPC mouse tumoroids, we show that NEPC cells acquire new transcription factor (TF) dependencies that function in a previously undefined network. Through selective perturbation of each TF, we identify ASCL1 as a key regulator of NE lineage fate whereas MYCL functions downstream to drive NEPC growth/survival by recruitment of the TIP60/KAT5 acetyltransferase. Interestingly, while dependencies on specific TF family paralogs can vary across NEPC models, all show markedly enhanced dependency on TIP60. Moreover, the H2A.Z-acetyltransferase activity of the TIP60 complex (TIP60-C) is required for NEPC as well as the acetyl-reader BRD8, which is newly incorporated as a TIP60-C subunit with the NEPC transition. Targeted degradation studies in isogenic tumoroids reveal increased dependence on MYCL in NEPC relative to its paralog MYC in PRAD. In addition to a paralog switch (MYC to MYCL), the MYC pathway-addicted NE state is accompanied by a chaperone switch (from TIP60-C to SRCAP) for H2A.Z histone exchange and a coactivator switch (to TIP60) for MYC target gene expression. The NE-specific coupling of MYCL with TIP60 reveals a previously unappreciated opportunity to target MYC-driven NE diseases through pharmacological inhibition of TIP60.

This multicenter, single-arm, phase 1/2 study evaluated the safety and efficacy of CD19-directed allogeneic chimeric-antigen-receptor (CAR) immunotherapy CTX110 in adult patients with relapsed/refractory (r/r) B-cell non-Hodgkin lymphoma (NHL). Patients received 1 or 2 treatment courses: standard lymphodepletion, followed by 1 CTX110 infusion at dose levels (DLs) 1-4 (3-60 × 107 CAR T-cells; dose escalation, N=32), or 2 infusions at DL4 on days 1 and 35 (cohort expansion, N=31). Primary endpoints in dose escalation and cohort expansion were incidence of dose-limiting toxicities and objective response rate, respectively. CTX110 was administered to 63 heavily pretreated patients: 59% primary refractory, 43% with ≥3 prior treatment lines. Among 57 patients whose first infusion was DL≥3, rates of objective and complete response (CR) were 65% and 39%, respectively. Among 22 patients achieving CR, 5 (23%) had ongoing CR at data cutoff, with 15-50 (median 34) months follow-up. The 2-infusion regimen appeared to prolong response duration compared to 1 infusion (hazard ratio 0.65). Cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) were reported in 54% and 13% of treated patients, respectively, including 2 grade ≥3 cases each. The most common grade ≥3 adverse events were neutropenia (59%), and anemia and thrombocytopenia (35% each). Serious adverse events occurred in 32% of treated patients, including CRS (14%), ICANS (8%), and febrile neutropenia (6%). In this r/r NHL population, CTX110 was well-tolerated, resulting in clinically meaningful responses at DL≥3, with a second infusion demonstrating evidence of further clinical benefit. This trial (NCT04035434) was registered at www.clinicaltrials.gov.

Abstract Spatial transcriptomics links gene expression to tissue architecture, providing a mechanistic view of cellular organization. Yet existing datasets cover few donors and miss the complexity of human disease. Experimental costs remain prohibitive, and large-scale profiling is impractically slow for population-level studies. Accurate computational methods are urgently needed. Predicting gene expression from standard histology, however, remains an open problem, as current approaches transfer poorly to unseen cohorts and diseases. Here, we present Phoenix, a (latent) flow matching generative model that infers pan-cancer spatially resolved single-cell gene expression with high accuracy. Phoenix analyzes treatment response in silico: Applied to 763 head and neck cancer patients, it identified three new spatial biomarkers that we validated across two cancers (breast cancer, n = 84; ovarian cancer, n = 157) and treatment regimens (platinum, trastuzumab). Phoenix generalizes beyond carcinomas: In a large sarcoma cohort (802 tissue microarray cores), it accurately predicted cell-type-specific signatures in held-out samples and captured chemotherapy-induced immune remodeling. Phoenix also extends across species: In a mouse model, it accurately predicted the expression of pancreatic cancer lineage markers and the mutant mKras^G12D allele in silico. In total, we evaluated Phoenix on over 10,000 patients. Our results establish virtual spatial transcriptomics as a scalable framework for studying tissue organization, therapeutic response, and disease mechanisms.