Citations

Background: Multicellular programs in the tumor microenvironment (TME) drive cancer pathogenesis and response to therapy but remain challenging to identify and profile clinically. Here, we present Spatial EcoTyper, a multimodal machine learning framework for large-scale profiling of spatially dependent cell states and multicellular ecosystems, termed spatial ecotypes (SEs). Methods and Findings: By integrating five million single-cell and spot-level spatial transcriptomes from 10 diverse human neoplasms, including carcinomas and melanomas, we identified a rich tapestry of conserved regional plasticity across nine TME cell types. We then applied Spatial EcoTyper to deeply dissect these data, revealing nine novel SEs with broad conservation - each with unique biology, TME cell states, geospatial features, and clinical outcome associations. SEs were linked to specific biogeographic domains, including the tumor core, margin, and adjacent stroma, and were remarkably well-validated in 235 held-out tumor samples profiled by either single-cell RNA sequencing, sequencing-based spatial transcriptomics (10x Visium), or high-resolution imaging-based spatial transcriptomics (Vizgen MERSCOPE and NanoString CosMx). By deconvolving SEs from over 1,200 bulk tumor RNA-seq profiles, we discovered striking associations between SE levels and response to immune checkpoint inhibitors (ICIs), outperforming nearly 40 potential correlates of ICI response, including previously described signatures of tertiary lymphoid structures and tumor tissue PD-L1 expression. Notably, baseline levels of a proinflammatory SE - localized to the tumor core and defined by a hub of unique T cell, macrophage, fibroblast, and endothelial cell states - strongly forecasted ICI benefit, while another SE - localized to the tumor margin and defined by myofibroblast and hypoxia-associated endothelial cell states - portended ICI resistance. Conclusion: Our data reveal fundamental units of TME organization and demonstrate a platform for large-scale profiling of spatial cellular ecosystems in any tissue, with implications for improved forecasting of immunotherapy response and the development of novel therapeutic strategies. Citation Format: Wubing Zhang,Erin L. Brown,Abul Usmani,Noah Earland,Hyun Soo Jeon,Irfan Alahi,Nicholas P. Semenkovich,Janella C. Schwab,Chloé B. Steen,Chloe M. Sachs,Bilge Gungoren,Faridi Qaium,Peter K. Harris,Jacqueline Mudd,Qingyuan Cai,Antonella Bacchiocchi,Ryan C. Fields,Mario Sznol,Ruth Halaban,David Y. Chen,Aadel A. Chaudhuri,Aaron M. Newman. High-resolution profiling of the tumor microenvironment with spatial ecotypes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 153.

OBJECTIVE The objective of this study was to develop a deep learning model for automated pituitary adenoma segmentation in MRI scans for stereotactic radiosurgery planning and to assess its accuracy and efficiency in clinical settings. METHODS An nnU-Net–based model was trained on MRI scans with expert segmentations of 582 patients treated with Leksell Gamma Knife over the course of 12 years. The accuracy of the model was evaluated by a human expert on a separate dataset of 146 previously unseen patients. The primary outcome was the comparison of expert ratings between the predicted segmentations and a control group consisting of original manual segmentations. Secondary outcomes were the influence of tumor volume, previous surgery, previous stereotactic radiosurgery (SRS), and endocrinological status on expert ratings, performance in a subgroup of nonfunctioning macroadenomas (measuring 1000–4000 mm 3 ) without previous surgery and/or radiosurgery, and influence of using additional MRI modalities as model input and time cost reduction. RESULTS The model achieved Dice similarity coefficients of 82.3%, 63.9%, and 79.6% for tumor, normal gland, and optic nerve, respectively. A human expert rated 20.6% of the segmentations as applicable in treatment planning without any modifications, 52.7% as applicable with minor manual modifications, and 26.7% as inapplicable. The ratings for predicted segmentations were lower than for the control group of original segmentations (p < 0.001). Larger tumor volume, history of a previous radiosurgery, and nonfunctioning pituitary adenoma were associated with better expert ratings (p = 0.005, p = 0.007, and p < 0.001, respectively). In the subgroup without previous surgery, although expert ratings were more favorable, the association did not reach statistical significance (p = 0.074). In the subgroup of noncomplex cases (n = 9), 55.6% of the segmentations were rated as applicable without any manual modifications and no segmentations were rated as inapplicable. Manually improving inaccurate segmentations instead of creating them from scratch led to 53.6% reduction of the time cost (p < 0.001). CONCLUSIONS The results were applicable for treatment planning with either no or minor manual modifications, demonstrating a significant increase in the efficiency of the planning process. The predicted segmentations can be loaded into the planning software used in clinical practice for treatment planning. The authors discuss some considerations of the clinical utility of the automated segmentation models, as well as their integration within established clinical workflows, and outline directions for future research.

Abstract Background We aimed to evaluate the effectiveness and safety of risankizumab (RZB) for Crohn’s disease (CD) in routine clinical practice. Methods We performed a retrospective review of a multicenter consortium of CD patients treated with RZB. Co-primary outcomes were week 12 clinical remission (Harvey Bradshaw Index [HBI] score of ≤4 or physician global assessment in those without HBI or with ileostomy) and 6-month endoscopic remission (Simplified Endoscopic Mucosal Assessment for Crohn’s Disease of 0-1 or absence of ulcers). Secondary outcomes included steroid-free clinical remission, clinical response, radiographic response, cumulative clinical and endoscopic remission rates at 6 and 12 months, and adverse events. Results A total of 309 patients were included (median disease duration 14 years [IQR, 6-24]; median follow-up 7.1 months [IQR, 4.1-10.3]). Most patients (85.8%) were advanced therapy (AT)-exposed, and 169 (54.7%) had prior ustekinumab (UST) exposure. Week 12 clinical remission rates were 49.7% (98/197) overall, and 44.2% (50/113) vs 57.1% (48/84) in UST-exposed vs naïve patients (P = .073). Among those with active disease on baseline endoscopy (n = 122) who had an available follow-up at 6 months, 52.4% (22/42) achieved endoscopic remission. Cumulative rates of clinical and endoscopic remission at 12 months were 65.0% and 49.5%, respectively. Cumulative 12-month endoscopic remission was 33.9% (19/56) in UST-exposed and 68.1% (32/47) in UST-naïve patients (P &lt; .001). Risankizumab was well-tolerated with no new safety signals identified. Conclusions In this large multicenter cohort of patients with CD, RZB was well-tolerated and effective in achieving favorable clinical and endoscopic outcomes in both AT-exposed and naïve populations, including those with exposure to UST.

ABSTRACT The rare human neuroendocrine tumors pheochromocytoma and paraganglioma (PPGL) can result from loss of mitochondrial succinate dehydrogenase. The resulting succinate accumulation is tumorigenic in certain neuroendocrine cells. Here, we explore two theoretical approaches to mitigate tumorigenic succinate accumulation in a cell culture model of PPGL. We first study a gene replacement strategy using transposition technology, and conclude that many of the changes in mitochondrial morphology, oxidative cell metabolism and succinate accumulation can be reversed by this process. We then investigate whether riboflavin supplementation has the potential to rescue succinate dehydrogenase activity in the intact SDHA catalytic subunit to suppress succinate accumulation even in the absence of SDHB. We show that this latter strategy is not successful.

Abstract INTRODUCTION Biomarkers play a crucial role in understanding Alzheimer's disease (AD) pathogenesis and treatment effects. However, comparing biomarker measures without standardization and appreciating their magnitude relative to the disease can be challenging. METHODS To address this issue, we propose the CentiMarker approach, similar to Centiloid, which provides a standardized scale between normal (0) and nearly maximum abnormal AD (100) ranges. We applied this scale to cerebrospinal fluid (CSF) biomarkers in dominantly inherited AD and sporadic AD cohorts. RESULTS CentiMarkers facilitated the interpretation of disease abnormality, demonstrating comparable changes and distributions of AD biomarkers across disease stages. CentiMarkers make the treatment effect more comparable than their original scales across various biomarkers. DISCUSSION The versatility of CentiMarkers makes it a valuable tool for standardized biomarker comparison in AD research, enabling informed cross‐study comparisons and contributing to accelerated therapeutic development. Adoption of the CentiMarker scale could enhance biomarker reporting and advance our understanding of AD. Highlights Comparing fluid biomarkers without appreciating their magnitude relative to the disease can be challenging. We propose a CentiMarker metric to standardize biomarker measures from normal (0) and nearly maximum abnormal AD (100) ranges. CentiMarkers make the treatment effect more comparable across various biomarkers than when using the original scales.

Abstract Objective The objective of this study was to examine the clinical outcomes during the implementation of a self-administered patient decision-aid (PtDA) for lupus. Methods We provided an effective computerized lupus PtDA in 15 rheumatology outpatient clinics 2019–2024 (including the COVID pandemic). We undertook Organizational Readiness to Implement Change Surveys (ORICs) and Team Learning and Psychological Safety Surveys (TLPSSs) at baseline. The primary study outcome objective measure, percent penetration/reach, was defined as the number of patients who viewed the lupus PtDA at the end of the study, divided by the total number of eligible patients (times 100). We used validated clinical personnel surveys to examine the perceived lupus PtDA appropriateness, acceptability, feasibility, success, and permanence, at 4 months, 12 months and 24 months post-PtDA implementation. Results Among the sites, the clinical personnels’ (n = 184) baseline ORIC commitment and efficacy scores (a 0–5 scale, higher = better) ranged from 3.5 to 4.2, and 3.4 to 4.4, respectively; the TLPSS scores (a 0–7 scale, higher = better) were 3.9–5.5 for internal learning, 3.7–5.6 for external learning, and 4.3–5.5 for psychological safety. The penetration (primary outcome) among 15 geographically diverse US rheumatology clinics ranged from 3% to 44%. We found that the total number of providers in the clinic was positively associated with higher penetration. Clinical personnel–perceived lupus PtDA outcomes were optimal at 4 months (all scale scores ranged from 1 to 5, higher = better): (i) appropriateness, 3.43 (s.d. 0.86); (ii) acceptability, 3.53 (s.d. 0.83); (iii) feasibility, 3.44 (s.d. 0.71); (iv) success, 3.41 (s.d. 0.73); and (v) permanence, 3.22 (s.d. 0.74). Conclusion We implemented a lupus PtDA with varied success rates during the COVID pandemic; more providers were associated with higher clinic penetration. Clinical personnel perceived high lupus PtDA appropriateness, acceptability, feasibility, success, and permanence that persisted up to 24 months. Trial Registration ClinicalTrials.gov, http://clinicaltrials.gov, NCT03735238.

Abstract ZUMA-8 evaluated the safety of brexucabtagene autoleucel (brexu-cel), a CD19-directed autologous chimeric antigen receptor (CAR) T-cell immunotherapy, for patients with relapsed/refractory chronic lymphocytic leukemia (R/R CLL). Patients with ≥2 prior lines of therapy (including a Bruton tyrosine kinase inhibitor) underwent leukapheresis, optional bridging therapy, and conditioning chemotherapy (fludarabine/cyclophosphamide) before infusion of 1 × 106 (cohort 1) or 2 × 106 (cohort 2) anti-CD19 CAR T cells per kg. Patients in cohort 3 (low tumor burden), and cohort 4A (postibrutinib) received 1 × 106 cells per kg. Fifteen patients, median age of 63 years (range, 52-79), were treated in cohorts 1 (n = 6), 2 (n = 3), 3 (n = 3), and 4A (n = 3). Median follow-up was 24.3 months. One dose-limiting toxicity was observed in cohort 3 (grade 4 cytokine release syndrome). Grade ≥3 neurologic events occurred in 3 patients (20%). Seven of 15 patients responded (overall response rate, 47%; complete response [CR], 7%), including all 3 patients in cohort 3 (1 with CR). CAR T-cell expansion occurred in 4 patients (27%), with an apparent weak inverse correlation with absolute lymphocyte count before apheresis. Brexu-cel had no new safety signals in R/R CLL. CAR T-cell expansion and responses occurred in patients with low tumor burden. This trial was registered at www.clinicaltrials.gov as #NCT03624036.

Abstract INTRODUCTION β‐synuclein is a promising blood marker to track synaptic degeneration in Alzheimer's disease (AD) but changes in preclinical AD are unclear. METHODS We investigated serum β‐synuclein in 69 cognitively unimpaired mutation non‐carriers, 78 cognitively unimpaired AD mutation carriers (asymptomatic AD), and 31 symptomatic mutation carriers from the Dominantly Inherited Alzheimer Network. RESULTS β‐synuclein levels were already higher in asymptomatic AD mutation carriers compared to non‐carriers and highest in symptomatic carriers. Longitudinal trajectories and correlation analyses indicated that β‐synuclein levels start to rise after amyloid deposition preceding axonal degeneration, brain atrophy and hypometabolism, and cognitive decline. β‐synuclein levels were associated with cognitive impairment and gradually increased with declining cognition. DISCUSSION Our study supports the use of blood β‐synuclein to track synaptic changes in preclinical AD and as a surrogate marker for cognitive impairment which might be used in early diagnosis and to support patient selection and monitoring of treatment effects in clinical trials. Highlights Blood β‐synuclein levels were already higher in asymptomatic Alzheimer's disease (AD) mutation carriers. Blood β‐synuclein levels were highest in symptomatic AD mutation carriers. Blood β‐synuclein levels start to rise 11 years before symptom onset. Rise of β‐synuclein precedes axonal degeneration, brain atrophy, and cognitive decline. β‐synuclein levels gradually increased with declining cognition.