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.

e16159 Background: Pivotal trials established atezolizumab-bevacizumab and durvalumab-tremelimumab as first-line therapies for unresectable hepatocellular carcinoma (HCC). Atezolizumab plus bevacizumab demonstrated superior survival outcomes compared to sorafenib for unresectable HCC in the IMbrave150 trial in 2020, while durvalumab plus tremelimumab showed superior survival in the HIMALAYA trial in 2022. However, data on head-to-head comparison of these two combinations as first-line systemic therapy for the patient with decompensated HCC are limited. This study aims to compare survival outcomes between these two treatment regimens in decompensated HCC patients to address a critical gap in the current literature, as decompensated patients have largely been excluded from clinical trials. Methods: This retrospective study utilized electronic health records from 146 U.S. healthcare organizations within the TriNetX Network. Adults aged ≥21 years diagnosed with decompensated HCC receiving atezolizumab/bevacizumab and durvalumab/tremelimumab from 10/21/2022 to 8/20/2024 were included. The comparison group received atezolizumab/bevacizumab, and the control group received durvalumab/tremelimumab. The primary outcome was all-cause mortality. A 1:1 propensity score matching was conducted to balance baseline characteristics (age, gender, race/ethnicity, lab results including liver function tests, platelet counts, INR, gamma glutamyl transferase, alpha-fetoprotein, and underlying liver diseases). Kaplan–Meier survival analysis and Cox regression was used to estimate the mortality risk. Subgroup analysis was stratified by HCC etiology. Results: A total of 302 and 664 patients received durvalumab/tremelimumab, atezolizumab/bevacizumab, respectively. After propensity matching, 253 patients per group were included. Median OS was 283 days with durvalumab/tremelimumab and 391 days with atezolizumab/bevacizumab. The two treatment regimens showed no significant difference in survival (hazard ratio [HR]: 0.875, 95% confidence intervals [CI] 0.696–1.101, p=0.254). Subgroup analyses demonstrated no significant differences in survival between the two groups of patients in MASLD (HR: 0.698, 95% CI: 0.468–1.040), alcohol associated liver disease (HR: 0.821, 95% CI: 0.603–1.118), and chronic viral hepatitis (HR: 0.852, 95% CI: 0.596–1.219). Conclusions: There was no statistically significant difference in survival outcomes between atezolizumab plus bevacizumab and durvalumab plus tremelimumab in patients with decompensated advanced HCC. These results support current real-world practice in which both regimens may be considered viable first-line treatment options in this high-risk population with liver decompensation.

Abstract Background High‐resolution MRI is essential for accurate diagnosis and treatment planning, but its clinical acquisition is often constrained by long scanning times, which increase patient discomfort and reduce scanner throughput. While super‐resolution (SR) techniques offer a post‐acquisition solution to enhance resolution, existing deep learning approaches face trade‐offs between reconstruction fidelity and computational efficiency, limiting their clinical applicability. Purpose This study aims to develop an efficient and accurate deep learning framework for MRI SR that preserves fine anatomical detail while maintaining low computational overhead, enabling practical integration into clinical workflows. Materials and Methods We propose a novel SR framework based on multi‐head selective state‐space models (MHSSM) integrated with a lightweight channel multilayer perceptron (MLP). The model employs 2D patch extraction with hybrid scanning strategies (vertical, horizontal, and diagonal) to capture long‐range dependencies while mitigating pixel forgetting. Each MambaFormer block combines MHSSM, depthwise convolutions, and gated channel mixing to balance local and global feature representation. The framework was trained and evaluated on two distinct datasets: 7T brain T1 MP2RAGE maps (142 subjects) and 1.5T prostate T2w MRI (334 subjects). Performance was compared against multiple baselines including Bicubic interpolation, GAN‐based (CycleGAN, Pix2pix, SPSR), transformer‐based (SwinIR), Mamba‐based (MambaIR), and diffusion‐based (I 2 SB, Res‐SRDiff) methods. Results The proposed model demonstrated superior performance across all evaluation metrics while maintaining exceptional computational efficiency. On the 7T brain dataset, our method achieved the highest structural similarity (SSIM: ) and peak signal‐to‐noise ratio (PSNR: dB), along with the best perceptual quality scores (LPIPS: ; GMSD: ). These results represented statistically significant improvements over all baselines (), including a 2.1% SSIM gain over SPSR and a 2.4% PSNR improvement over Res‐SRDiff. For the prostate dataset, the model similarly outperformed competing approaches, achieving SSIM of , PSNR of dB, LPIPS of , and GMSD of . Notably, our framework accomplished these results with only 0.9 million parameters and 57 GFLOPs, representing reductions of 99.8% in parameters and 97.5% in computational operations compared to Res‐SRDiff, while also substantially outperforming SwinIR and MambaIR in both accuracy and efficiency metrics. Conclusion The proposed framework provides a computationally efficient yet accurate solution for MRI SR, delivering well‐defined anatomical details and improved perceptual fidelity across anatomically distinct datasets. By significantly reducing computational demands while maintaining state‐of‐the‐art performance, the model offers strong potential for feasibility toward clinical translation and scalable integration into future imaging workflows.

9524 Background: Unresectable melanoma in-transit metastases (ITM) can pose a significant clinical challenge. Our recently published data comparing first-line treatments for ITM, isolated limb infusion or perfusion (ILI/ILP), immune checkpoint inhibitors (ICI) and intralesional talimogene laherparepvec (TVEC), found superior outcomes with TVEC. However, TVEC was used more often in patients with lower disease burden and earlier stage (IIIB vs. IIIC/D). Therefore, we sought to better investigate these differences with a propensity score-matched (PSM) analysis. Methods: A multi-institutional, international IRB- approved retrospective analysis was conducted for unresectable melanoma ITM from 2016-2022. PSM analysis comparing first-line ILI/ILP, ICI, and TVEC for was performed. Patients were matched for stage, number of ITM, anatomical site, CLND status, gender and age. Kaplan-Meier curves (OS, PFS, DMFS) and Cumulative incidence function (MSS) were used to visualize time-to-event outcomes in the PSM cohort, though both methods do not account for the matched structure. Results: 274 patients were identified, 120 female/154 male; 96 treated with ILI/ILP, 111 with ICI, and 67 with TVEC. Median follow-up was 40 months (range, 1-80). PSM was performed and identified 36 TVEC–ICI pairs and 27 TVEC–ILI pairs. These were combined resulting in a final cohort of 108 observations (45 TVEC, 36 ICI and 27 ILI). The groups were well balanced. No statistical difference was found for metastasis-free survival (DMFS), progression-free survival (PFS), melanoma-specific survival (MSS), and overall survival (OS) between treatment modalities. TVEC was associated with significant improvement in local PFS (median was 2.2 years (y) for ILI/ILP, 1.5y for ICI and not reached for TVEC, p=0.048). While not statistically significant, a clinical benefit was seen in PFS being longer for TVEC (2.1y for TVEC vs. 1.2y for ILI/ILP and 1.1y for ICI; p=0.2) and OS (not reached vs 2.9y for ILI/ILP and 5.2y for ICI; p=0.2). On mixed effect Cox regression proportional hazard model using the matched data set, there were no significant differences in any of the survival and recurrence outcomes. Conclusions: When patients are propensity-matched, there were no significant differences in first-line treatment modalities for unresectable melanoma ITM. Treatment with TVEC did result in clinically meaningful improved overall and local PFS and OS. This supports that selection of ITM therapy should incorporate an individualized approach, incorporating disease distribution, stage, burden, treatment side effects and patient priorities.

8057 Background: The NCI Adjuvant Lung Cancer Enrichment Marker Identification and Sequencing Trials (ALCHEMIST) study tested resected stage II-IIIB(N2) NSCLC for targetable EGFR and ALK alterations and PD-L1 expression to screen patients for biomarker-driven adjuvant therapy trials (NCT02194738). Local lab results were requested when available for comparison to central lab results. Methods: We identified patients with both central and local PD-L1 results in the ALCHEMIST adjuvant immunotherapy study screening population. Discrepancies in tumor proportion score (TPS) between central and local PD-L1 were defined using prespecified cut-points (granular: <1%, 1-<5%, 5-<10%, 10-<20%, 20-<30%, 30-<40%, 40-<50%, 50-60%, 60-<70%, 70-<80%, 80-<90%, 90-<100%; clinical: <1%, 1-<50%, 50-100%). Large discrepancies were defined as ≥ 50 percentage point differences; for these cases, local PD-L1 and hematoxylin & eosin-stained slides were requested. These and all central slides were digitally scanned at 40X. Three expert pathologists reviewed the scanned slides in a blinded fashion. Differences between patient or tumor characteristics were assessed by Chi-square and Wilcoxon rank sum tests. Percent agreement was computed within and between the reviewers. Results: Central and local PD-L1 results were available for 497 patients. 177 cases (36%) had discrepancies that placed patients in different clinical TPS categories (<1%, 1-<50%, 50-100%). Among these, 43 cases had large TPS discrepancies; 14 had available local testing slides. 46 of the 320 cases without discrepancy were randomly selected as controls. No patient or tumor characteristics were associated with discrepancy, including tumor location, histology, grade or cancer stage (p > 0.05). Pairwise comparisons of TPS according to three pathologists re-reading the same scanned PD-L1 slides showed similar levels of disagreement in clinical TPS category whether there was initial discrepancy between central and local results (24%, 34%, and 23%; mean 27%) or not (33%, 30%, and 20%; mean 28%). Among the 14 cases with large initial discrepancies and local slides available, there was agreement in clinical TPS category when the anonymized central and local scanned slides were re-read by the pathologists in 54%, 38%, and 43% of cases, despite 100% non-agreement in initial reads. There were higher rates of agreement when the tested slides both originated from the same (100%) versus different (35%) blocks, when the same (48%) versus different (40%) PD-L1 antibodies were used, and when the cases were of non-squamous (52%) versus squamous (14%) cell carcinoma. Conclusions: There are substantial differences in PD-L1 TPS read by pathologists that can result in placement of patients in different categories commonly used for clinical management. These differences have clear implications in clinical trials and routine patient care.

Abstract Background Ultra‐high‐field 7 Tesla (7T) magnetic resonance imaging (MRI) provides improved resolution and signal‐to‐noise ratio (SNR) over standard clinical field strengths (1.5T, 3T). However, 7T scanners are costly, scarce, and introduce additional challenges such as susceptibility artifacts. Purpose We propose an efficient transformer‐based model (7T‐Restormer) to synthesize 7T‐like MRI (quantitative T1 MP2RAGE maps) from routine 1.5T or 3T T1‐weighted (T1W) images. Methods The proposed method leverages an efficient restoration transformer backbone and spatial attention layers to capture long‐range dependencies and generate high‐quality 7T‐like images. Our model was validated on an institutional dataset, comprised of 35 1.5T and 108 3T T1w MRI paired with corresponding 7T T1 maps of patients with confirmed multiple sclerosis (MS). A total of 141 patient cases (32 128 slices) were randomly divided into 105 (25 1.5T and 80 3T) training cases (19 204 slices), 19 (5 1.5T and 14 3T) validation cases (3476 slices), and 17 (5 1.5T and 12 3T) test cases (3145 slices). The synthetic 7T T1 maps were evaluated by comparing their similarity to the ground truth volumes using peak signal‐to‐noise ratio (PSNR), structural similarity index measure (SSIM), and normalized mean squared error (NMSE), and were compared against ResViT and ResShift. In addition, a blinded reader study was performed in which three clinicians scored the diagnostic image quality of each method on a 5‐point Likert scale (1 = non‐acceptable, 5 = excellent). Statistical significance ( α = 0.05) was assessed using two‐sided paired t ‐tests with Holm correction for multiple comparisons and Wilcoxon signed‐rank tests with Holm correction for reader scores. Effect sizes (Cohen's for paired data) were also computed to quantify practical significance. We interpreted and as small, medium, and large effects. Results For 1.5T inputs, 7T‐Restormer achieved an NMSE of 0.018 ± 0.003, PSNR of 25.0 ± 0.6 dB, and SSIM of 0.870 ± 0.019; for 3T inputs, the corresponding values were 0.019 ± 0.006, 24.5 ± 1.2 dB, and 0.874 ± 0.027. Across both field strengths, 7T‐Restormer provided the lowest NMSE and highest PSNR and SSIM among the three methods, reducing NMSE by approximately 5% and 25% relative to ResShift and ResViT at 1.5T and by 14% and 24% at 3T, respectively, and increasing PSNR by 0.5–1.5 dB (Holm‐adjusted p < 0.05, paired Cohen's = 1.37–6.84). Training on mixed 1.5T+3T data improved performance for 1.5T inputs compared with 1.5T‐only training (e.g., NMSE 0.018 vs. 0.019; p = 0.001, ), without degrading performance for 3T inputs ( p = 0.630, for NMSE). In the blinded reader study, 7T‐Restormer received higher diagnostic quality scores (3.50 ± 0.28) than ResShift (3.00 ± 0.27) and ResViT (2.33 ± 0.27), corresponding to mean improvements of 0.5–1.2 points on the 5‐point scale (Holm‐adjusted p = 0.014 and 0.004; paired Cohen's and 3.24, respectively). Conclusion We propose a novel method for predicting quantitative 7T MP2RAGE maps from 1.5T and 3T T1W scans with higher quality than existing state‐of‐the‐art methods. Future development and application of our approach may enhance diagnostic accuracy, treatment planning, and facilitate downstream tasks by making the benefits of 7T MRI more accessible to standard clinical workflows.

Abstract Background Meningiomas exhibit clinical heterogeneity. Radiotherapy (RT) remains the only adjuvant therapy, but tumor-control is variable, and biomarkers are limited. NRG/RTOG-0539 is the first prospective phase 2 trial to stratify meningioma patients for adjuvant RT based on clinical risk. Here, we apply modern molecular tools to this cohort and identify correlates of RT response. Methods Tumor tissue from 100 RTOG-0539 patients was profiled using DNA methylation arrays, RNA sequencing, and whole-exome sequencing. Recurrence scores, Molecular Groups, gene expression, and copy number alterations were compared across clinical groups and between RT responders and non-responders; non-response was defined as progression or death within 3 years. Results Modern grading criteria, including brain invasion, TERT mutation, CDKN2A/B deletion, and 1p/1q status, would reclassify 10% of tumors and alter treatment group assignment in 7%. Non-responders to RT exhibited more frequent 1p and 14q loss, and more copy number alterations. Transcriptomic and epigenetic profiling revealed immune-related signatures in responders and cell cycle–related pathways in non-responders, several of which overlapped with targets of vorinostat, a histone deacetylase inhibitor previously validated in aggressive meningioma models. The Proliferative Molecular Group was an independent predictor of post-RT recurrence in multivariable analysis, outperforming WHO grade. Conclusion Multi-omic analysis of the NRG/RTOG-0539 cohort shows that updated WHO grading criteria, incorporating molecular and cytogenetic features, improve risk stratification. However, molecular classification, particularly the Proliferative group, remains an independent and stronger predictor of RT response. These findings support integrating molecular biomarkers alongside modern grading frameworks to guide treatment and trial design in meningioma. Clinical Trial Information NCT00895622.

Abstract Neoadjuvant therapy (NAT) with HER2-targeted agents is the standard treatment for patients with HER2-positive early breast cancer (HER2 + EBC). Although high levels of tumor-infiltrating lymphocytes (TILs) are associated with higher pathologic complete response (pCR) rates and improved recurrence-free survival (RFS), the specific immune components responsible remain unclear. In this study, pretreatment tumor biopsies from 188 patients receiving HER2-targeted NAT were analyzed. Univariate analysis revealed that enrichment of TIL-B cells in tumors, high HER2 mRNA and low ESR1 mRNA expression were linked to pCR (both p < 0.01). Multivariate analysis confirmed TIL-B-cell enrichment as an independent predictor of pCR. Mature IgD/IgM-high B cells, but not immature RAG1 + B cells, independently predicted pCR. Transcriptomic profiling identified 265 upregulated genes in pCR tumors enriched in MHC class II antigen presentation pathways. Immunofluorescence demonstrated increased spatial interaction of mature B cells with CD4 + T cells in pCR tumors, consistent with active antigen presentation. The antigen presenting B-cell signature, integrated mature B-cell and MHC II profile, was the strongest independent predictor of pCR (OR = 3.008, 95% CI: 1.196–7.544, p = 0.019) and was also significantly associated with improved RFS (HR = 0.109, 95% CI: 0.014–0.872), highlighting B-cell–mediated antigen presentation as a clinically relevant biomarker in HER2 + EBC.

Background: Stable osteochondritis dissecans (OCD) lesions are primarily treated nonoperatively. Nonoperative treatment includes several recommendations, including the use of an unloader brace. However, little is known about the clinical effectiveness of unloader bracing and its influence on OCD healing, return to sports, and patient-reported outcomes (PROs). The purpose of this investigation was to evaluate the impact of unloader bracing on patients with stable medial femoral condyle (MFC) OCD lesions treated nonoperatively. Purpose: To investigate the influence of valgus unloader bracing on the success of treating stable MFC OCD with nonoperative treatment strategies. Study Design: Cohort study; Level of evidence, 2. Methods: The authors used a prospective cohort of patients receiving nonoperative care for stable MFC knee OCD lesions. The primary variable of interest was the efficacy of bracing. The primary outcomes were transition from nonoperative care to surgical intervention, return-to-play (RTP) clearance, and PROs. Bivariate testing was used to determine if there were differences between groups. Chi-square testing was used to determine if there were differences in rates of transition to surgery by group. The timing of the transition by each group was assessed using a Wilcoxon rank-sum test, given the nonparametric nature of the data. Kaplan-Meier survival analysis was used to calculate time at risk, incidence rate, and survival times for each group. Results: A total of 185 knees (bracing group: 123 [66.5%] knees; no-bracing group: 62 [33.5%] knees) were analyzed. Overall, 142 (76.8%) knees were successfully treated nonoperatively. Transition to surgery occurred in 43 (23.2%) knees. There were no differences in transition to surgery by groups, with no differences seen by group. Of the knees that did not transition to surgical care, 65 (71.4%) in the bracing group and 38 (74.5%) in the no-bracing group received RTP clearance ( P = .693). PRO scores were similar between the 2 groups at the time of RTP clearance. Conclusion: The inclusion of an unloader brace in the nonoperative treatment for stable MFC OCD lesions did not decrease the likelihood of patients undergoing surgical intervention or improve their PRO scores at the time of RTP clearance. Registration: NCT02771496 (ClinicalTrials.gov identifier).