Citations

Abstract Background Progressive supranuclear palsy (PSP) is a tauopathy for which there is limited understanding of epidemiological risk factors. Objective The objective of this study was to identify premorbid nonmedical and medical risk factors for PSP diagnosis in a large prospective population‐based cohort. Methods We performed a matched nested case–control study using the UK Biobank (UKB) cohort consisting of >500,000 adults aged 37 to 73 years. PSP diagnoses were identified from 2007 to censor date (August 2025) and matched 1:10 by age and sex to control subjects without parkinsonism or dementia diagnoses. We derived risk factors using an iterative logistic regression approach. Results There were 240 incident PSP diagnoses in the UKB. In the fully adjusted model, premorbid depression (odds ratio [OR], 3.22; 95% confidence interval [CI], 2.30–4.50; P < 0.001), delirium (OR, 6.76; 95% CI, 4.08–11.19; P < 0.001), and functional gastrointestinal disorders (OR, 1.91; 95% CI, 1.39–2.63; P < 0.001) were associated with increased risk. Heavy alcohol consumption was associated with higher risk compared with moderate consumption (OR, 1.65; 95% CI: 1.21–2.26; P = 0.0017). Body mass index (BMI) and alcohol consumption had nonlinear risk profiles. Cancer diagnosis was inversely associated with PSP (OR, 0.56; 95% CI, 0.40–0.79; P < 0.001). Depression and delirium diagnoses remained significant 5 to 10 years before diagnosis. Conclusions In this large prospective cohort, PSP was associated with premorbid lifestyle practices and neuropsychiatric diagnoses years before diagnosis. This suggests a long premotor phase and highlights opportunities for earlier diagnosis and further mechanistic investigation. The inverse association with cancer mirrors the relationship seen in other neurodegenerative conditions and may point toward shared mechanisms. © 2026 International Parkinson and Movement Disorder Society.

Abstract In many cancers, a major barrier to effective immunotherapy is the dominance of tumor-associated myeloid cells (TAMs), which establish a profoundly immunosuppressive tumor microenvironment (TME). This challenge is particularly pronounced in glioblastoma (GBM), where myeloid cells represent the predominant immune population and actively suppress antitumor immunity. Identifying targets that can reprogram TAMs from an immunosuppressive state toward a pro-inflammatory, antigen-presenting phenotype remains a critical unmet need. Here, we identify the voltage-gated proton channel Hv1 as an immune-restricted regulator of glioma-associated macrophage function. Hv1 is notable not only for its immune-specific expression but also for its established roles in central nervous system (CNS) pathologies, where Hv1 depletion alters microglial and macrophage polarization, reduces myeloid accumulation, dampens inflammatory cytokine production, and limits secondary tissue damage. However, Hv1’s role in shaping the GBM immune landscape—particularly in vivo—has remained poorly understood due to low Hvcn1 transcript abundance and the lack of reliable antibodies and genetic tools. Given the dominance of myeloid cells in GBM and their central role in tumor immune regulation, we sought to define Hv1 function within this highly immunosuppressive brain TME. Analysis of patient datasets revealed that elevated Hv1 expression correlates with poor clinical prognosis. Consistently, Hv1 loss significantly prolonged survival in multiple murine glioma models. Using in vivo two-photon imaging and spectral flow cytometry, we show that Hv1 depletion reprograms TAMs toward an anti-tumor phenotype characterized by enhanced tumor cell phagocytosis, improved antigen presentation, and increased T cell infiltration. By generating new Hv1 reporter and conditional mouse lines, we further demonstrate that tumor-associated microglia and infiltrating macrophages are the principal sources of Hv1 and markedly upregulate its expression in response to glioma. Notably, selective deletion of Hv1 in infiltrating macrophages phenocopied the survival benefit observed with global Hv1 loss. Mechanistically, using mass spectrometry and genetic models, we identify the Stimulator of Interferon Genes (STING) as a previously unrecognized binding partner of Hv1, placing Hv1 within the STING signaling pathway, a central regulator of innate and adaptive immune responses. Together, these findings fill a critical gap in understanding myeloid Hv1 function in GBM and identify Hv1 as a promising target for reprogramming the tumor immune microenvironment. Citation Format: Jiaying Zheng, Lingxiao Wang, Shunyi Zhao, Katayoun Ayasoufi, Meijie Wang, Praveen N. Pallegar, Peter R. Strege, Langni Liu, Yushan Wan, Wenjing Zhang, Emma N. Goddery, Manling Xie, Arthur Beyder, Aaron J. Johnson, Long-Jun Wu. Myeloid Hv1-STING axis tunes glioma immunity [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Brain Cancer; 2026 Mar 23-25; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2026;86(6_Suppl):Abstract nr A016.

Abstract Despite growing interest in AI for pancreatic cyst management, no prior study has systematically investigated how lesion characteristics influence model behavior or provided a comprehensive explainability analysis in IPMN malignancy risk stratification. We present the first multi-center study integrating explainable AI with uncertainty quantification to evaluate how cyst type, size, and location affect deep learning performance in IPMN malignancy prediction. Our retrospective study analyzed 170 IPMNs from seven centers using a radiomics-deep learning fusion model. Cases were stratified by dysplasia grade, IPMN type, size, and location; with model interpretability assessed using SHAP, LIME, Grad-CAM, and uncertainty quantification. Overall accuracy was 67.1%, with model uncertainty lower for correct versus incorrect predictions (0.72 vs 0.78, p < 0.001). On subgroup analysis: Low-Risk lesion accuracy exceeded High-Risk (81.3% vs. 42.9%, p < 0.001), BD accuracy was inversely correlated with cyst size while MD remained stable, and body and whole-pancreas cysts stratified more accurately than tail cysts (77.8%, 76.6% vs. 47.8%). AI models face significant, previously uncharacterized performance drops when evaluating complex high-risk IPMNs. Our study shows that integrating uncertainty quantification can successfully flag unreliable predictions, enabling a selective-prediction framework where clinicians can confidently rely on AI for low-risk, low-uncertainty lesions while deferring high-uncertainty cases to expert review.

ABSTRACT Lactylation, a protein post-translational modification driven by lactate, plays crucial roles in various physiological and pathological processes. However, the function and underlying mechanisms of lactylation in infection and pathogenesis of influenza A virus (IAV) remain poorly understood. Here, we demonstrated that sirtuin 1 (SIRT1) suppressed IAV replication by mediating delactylation of viral proteins. We found that IAV infection significantly downregulated the expression of SIRT1. Functional studies revealed that depletion of SIRT1 markedly enhanced replication of IAV, whereas overexpression of SIRT1 attenuated the viral replication. Mechanistically, we observed that SIRT1 interacted with IAV NP, PA, PB1, and PB2 proteins, components of the viral ribonucleoprotein (vRNP) complex, and restrained the activity of the vRNP complex, thereby repressing transcription and replication of the IAV genome. Furthermore, we identified that viral NP, PA, PB1, and PB2 proteins underwent lactylation during IAV infection, and SIRT1 facilitated the delactylation of NP, PA, and PB2. Loss of SIRT1 enhanced the lactylation of NP, PA, and PB2, while overexpression of SIRT1 impaired lactylation of these viral proteins during IAV infection. Moreover, inhibition or depletion of lactate dehydrogenase A (LDHA) robustly reduced the lactylation of NP, PA, and PB2, thereby abolishing the promotion of IAV replication caused by SIRT1 deficiency, suggesting that SIRT1 repressed IAV replication via delactylation of viral NP, PA, and PB2 proteins. Together, these results uncover a mechanism that SIRT1 suppresses IAV replication via delactylation of the vRNP components and elicit a critical role for the lactylation of viral proteins in regulating IAV infection and pathogenesis. IMPORTANCE Lactylation plays vital roles in diverse pathological processes. However, the relationship between lactylation and influenza A virus (IAV) infection remains largely unexplored. Particularly, little information is available about the lactylation of viral proteins and their roles in the IAV pathogenesis. Here, viral proteins (NP, PA, PB1, and PB2) were identified to become lactylated during IAV infection. SIRT1 interacted with and promoted the delactylation of viral NP, PA, and PB2 proteins, thereby restraining the vRNP activity and inhibiting the viral transcription and replication. Interestingly, the expression of SIRT1 decreased following IAV infection, suggesting that IAV had evolved a mechanism to downregulate the SIRT1 expression, thereby ensuring appropriate lactylation of viral proteins and facilitating the IAV replication. Together, these findings reveal a critical role for the lactylation of viral proteins in regulating the replication of IAV and provide an important insight into the complicated interplay between the host and IAV.

Cellular and molecular heterogeneity in the liver has been increasingly recognized to drive liver fibrosis progression, but the particular events that occur initially in response to liver injury and trigger immune cell recruitment remain unclear. Here, we identify epigenetically aberrant liver sinusoidal endothelial cells (LSECs) as key players in this process. Mechanistically, the epigenetic readers like bromodomain-containing protein 4–dependent (BRD4-dependent) super enhancers (SEs) activate proinflammatory genes, including promyelocytic leukemia (PML). The PML protein, in turn, binds BRD4 and amplifies proinflammatory angiocrine signaling through phase separation–dependent SE activation via PML/BRD4 condensate formation. In mouse models, LSEC-specific depletion of the PML/BRD4 complex mitigates liver inflammation and fibrosis. Single-cell RNA-seq reveals that epigenetically aberrant LSECs exhibit a reprogrammed proinflammatory angiocrine landscape in mouse fibrotic livers. TIMP1 + LSECs promote the recruitment of CD63 + monocyte–derived macrophages (MoMFs) during liver fibrosis progression. Thereby, PML/BRD4 in LSECs governs inflammatory immune cell recruitment in liver fibrosis. Pharmacological BRD4 inhibition or epigenetic PML-SE repression alleviates liver inflammation and fibrosis. In conclusion, PML/BRD4-mediated SE activation via phase separation drives proinflammatory angiocrine signaling in LSECs, initiating the inflammatory cascade and subsequent immune cell recruitment during liver fibrosis.

Background: Healing of the tendon-bone interface (TBI) after rotator cuff injury is limited, often leading to scar-mediated repair. Decellularized tendon fibrocartilage–bone composite (dTFBC) and bone marrow mesenchymal stem cell sheets (BMSCS) improve repair in preclinical models, but full scaffold encapsulation with mechanical preconditioning remains unexplored. Purpose: To evaluate TBI regeneration using mechanically preconditioned, BMSCS-encapsulated dTFBC scaffolds in a rabbit model. Study Design: Controlled laboratory study. Methods: A total of 48 male New Zealand White rabbits were randomized into 4 groups (n = 12 each): (1) standard repair (control); (2) repair with dTFBC; (3) repair with dTFBC-BMSCS; and (4) repair with mechanically preconditioned dTFBC-BMSCS (mdTFBC-BMSCS). Healing at 12 weeks was assessed via gross observation, histomorphological and immunohistochemical analyses, and biomechanical testing. Results: The mdTFBC-BMSCS group demonstrated a higher ultimate failure load (mean, 203.9 ± 65.6 N) than both the control (118 ± 37.4 N; P = .003) and dTFBC groups (127 ± 44.1 N; P = .008), with no significant difference between the 2 BMSCS-treated groups. Histological analysis revealed enhanced fibrocartilage formation, improved collagen fiber organization, and reduced inflammation infiltration at the TBI in the mdTFBC-BMSCS group. Immunohistochemical analysis showed greater collagen type 2 alpha 1 chain-, interleukin 10-, and arginase 1-positive areas in the mdTFBC-BMSCS group than in the control and dTFBC groups. Conclusion: Mechanically preconditioned, fully BMSCS-encapsulated dTFBC scaffolds promoted TBI regeneration, with enhanced cellular integration, fibrocartilage formation, and favorable biomechanical performance. Clinical Relevance: This biomimetic scaffold strategy may enhance biological healing and reduce the risk of retear after rotator cuff repair.

Abstract Motivation Intratumor heterogeneity arises from ongoing somatic evolution and complicates cancer diagnosis, prognosis, and treatment. Reconstructing evolutionary dynamics typically requires spatiotemporal samples, which are often unavailable in clinical settings. Computational approaches that can infer tumor evolutionary history from single-timepoint bulk sequencing data remain limited. Results We present estimating evolutionary events through single-timepoint sequencing (TEATIME), a novel computational framework that models tumors as mixtures of two competing cell populations: an ancestral clone with baseline fitness and a derived subclone with elevated fitness. Using cross-sectional bulk sequencing data, TEATIME estimates mutation rates, timing of subclone emergence, relative fitness, and number of generations of growth. To quantify intratumor fitness asymmetries, we introduce a novel metric—fitness diversity—which captures the imbalance between competing cell populations and serves as a measure of functional intratumor heterogeneity. Applying TEATIME to 33 tumor types from The Cancer Genome Atlas, we revealed divergent as well as convergent evolutionary patterns. Notably, we found that immune-hot microenvironments constraint subclonal expansion and limit fitness diversity. Moreover, we detected temporal dependencies in mutation acquisition, where early driver mutations in ancestral clones epistatically shape the fitness landscape, predisposing specific subclones to selective advantages. These findings underscore the importance of intratumor competition and tumor-microenvironment interactions in shaping evolutionary trajectories, driving intratumor heterogeneity. Lastly, we demonstrate that TEATIME-derived evolutionary parameters and fitness diversity offer novel prognostic insights across multiple cancer types. Availability and implementation R implementation of TEATIME is available on GitHub (https://github.com/liliulab/TEATIME) and Zenodo (https://zenodo.org/records/17422174).

Background The primary objective of this analysis was to assess the association between non-invasive biomarker results within the first 2-years post-kidney transplant and 10-year All Cause Graft Loss (ACGL). Methods CTOT-08 was linked with the Scientific Registry of Transplant Recipients (SRTR) to assess 10-year ACGL. Cox Regression was used to determine the association between gene expression profile (GEP) and donor-derived cell-free DNA (dd-cfDNA) results and ACGL. A Cox Regression with time-varying covariates was used to test associations with ACGL with simultaneous and repeated biomarker results. Results The final landmarked Cox model included clinical acute rejection (aHR 2.58 (1,30,5.13) for 1 rejection, aHR 3.41 (1.07,10.85) for 2 rejections), diabetes (aHR 1.71 (0.99,2.96)), recipient age (aHR 1.02 (1.00,1.04)), the highest quartile of positive GEP (aHR 2.44 (1.45,4.10)) and the highest quartile of positive dd-cfDNA (aHR 2.91 (1.77,4.78)). In the time-varying model, having both biomarkers positive at the same time carried the greatest association with ACGL (aHR 4.29 (2.10,8.76)). Conclusions In this multicenter, prospective analysis of GEP and dd-cfDNA on patient and graft outcomes, an independent association with long-term ACGL was demonstrated. Further, a time-varying analysis demonstrated that two biomarkers with independent methodologies tested at the same time can provide more information than either one alone.

TPS277 Background: Recent advances in genomic sequencing have deepened our understanding of the molecular complexity of metastatic castration-resistant prostate cancer (mCRPC), revealing multiple actionable alterations that now inform biomarker-driven treatment strategies. Accordingly, germline and somatic tumor profiling is recommended for all patients with mCRPC. Beyond DNA aberrations, gene expression profiling can uncover additional therapeutic targets and pathway activations. The phase 2 PREDICT trial is leveraging both DNA and RNA alterations to guide rationally designed, biomarker-based therapeutic approaches for patients with mCRPC. Methods: This multi-center, multi-arm, biomarker-driven phase 2 umbrella trial is evaluating rationally selected therapies for patients with metastatic castration-resistant prostate cancer (mCRPC). The primary endpoint is objective response rate in patients with measurable disease, with secondary endpoints including radiographic progression-free survival, PSA response, time to first symptomatic skeletal event, overall survival, safety, and correlative biomarker analyses. Eligible patients must have progressive mCRPC of any histology, prior treatment with an androgen receptor pathway inhibitor (ARPI), and either prior or declined taxane chemotherapy, with both measurable and non-measurable disease permitted. Enrollment requires standard-of-care next-generation DNA sequencing from tissue or circulating tumor DNA performed in a CLIA-certified laboratory, and RNA-based allocation will use the CLIA-certified Caris MI Tumor Seek assay (whole exome and whole transcriptome sequencing) on tissue obtained within 12 months of study entry, with a real-time molecular tumor board reviewing results to confirm arm assignment. Patients with RB1 loss (DNA), an RB functional loss signature (RNA), or an NEPC signature (RNA) will receive the EZH1/2 inhibitor valemetostat; those with ≥2 of 3 tumor suppressor gene alterations (TP53, RB1, PTEN), FANC alterations (DNA), or SLFN11 overexpression (RNA) will receive cabazitaxel plus carboplatin; and those without study-defined alterations will receive physician’s choice of cabazitaxel, ARPI, or 177Lu-PSMA-617. The design permits incorporation of additional biomarker-defined arms, and up to 158 patients per arm (64 with measurable and 94 with non-measurable disease) will be accrued under a Simon two-stage minimax design, providing a one-sided type I error of 0.05 if the true response rate is 0.20 and 90% power if the response rate is 0.37 (Clinical trial information: NCT06632977). Clinical trial information: NCT06632977 .

Abstract Liver metastases from well-differentiated thyroid carcinomas are rare. We report 3 patients, 1 with follicular and 2 with oncocytic thyroid cancers, treated for liver metastases with yttrium-90 radioembolization. The 2 patients with oligometastatic disease received ablative radiation doses, while 1 patient with diffuse metastatic liver disease was treated palliatively with 2 sessions of reduced nonablative radiation dose due to a large hepatopulmonary shunt fraction diagnosed at work-up. The 2 cases of oligometastatic disease had a complete local response by imaging criteria, while the third case had a pronounced local partial response, without adverse events. Future guidelines should include radioembolization as a viable option for locoregional therapy of liver metastases of differentiated thyroid cancer not responsive to radioiodine in patients that do not qualify for or refuse hepatic surgery.