Abstract Neuroblastoma (NB) accounts for 10% of pediatric cancer-related deaths. High-risk NB is frequently metastatic at diagnosis and has a poor 5-year survival rate (<50%) despite aggressive treatment. GD2, a disialoganglioside glycolipid that is expressed in nearly all NBs, has been validated as a promising immunotherapy target. Although GD2-CAR-T cells have been clinically evaluated, their efficacy has been limited by poor tumor infiltration and the immunosuppressive tumor microenvironment (TME), highlighting the need for alternative immune-based strategies. With inherent capacity of macrophages to infiltrate tumors, phagocytose cancer cells, and modulate TME, they represent a promising alternative strategy for immunotherapy in NB. In this study, we developed and evaluated GD2-CAR-macrophages (GD2-CAR-Ms) as a novel therapeutic approach for NB. GD2-specific CAR constructs were designed, validated, and introduced into multiple human and murine monocyte/macrophage cell lines via lentiviral transduction. Fluorescent microscopy and flow cytometry confirmed a significant enhancement in the phagocytosis of GD2-high NB cells by GD2-CAR-Ms containing Hu3F8 single-chain variable fragment (scFv). A strong positive correlation was observed between GD2 expression levels on the target cells and phagocytosis efficiency of GD2-CAR-Ms, indicating that the phagocytic activity of GD2-CAR-Ms is antigen-specific. Anti-tumor efficacy was further evaluated in vivo using an immunocompetent Mycn-expressing NB non-genetically engineered mouse model (MYCN-NGEMM). Mice treated with GD2-CAR-Ms exhibited significantly reduced tumor burden and prolonged survival compared to control groups. Notably, treatment of mice bearing GD2-high tumors resulted in markedly improved survival, including one complete remission among ten treated animals, underscoring the therapeutic potential of GD2-targeted macrophage therapy. Histological analysis showed increased deposition of connective tissues and decreased tumor cells density, suggesting TME remodeling. Furthermore, immunohistochemistry reveals increased immune cell infiltration, particularly of macrophages, neutrophils and T cells, indicating a favorable shift in the immune TME from “cold” to “hot” following GD2-CAR-M treatment. Additionally, inhibition of tumor growth was also observed in our zebrafish NB model after GD2-CAR-Ms treatment, further supporting their therapeutic potential. Together, our findings demonstrate that GD2-CAR-Ms exhibit potent antitumor activity and reshape the tumor immune microenvironment, supporting their translational potential as a therapeutic strategy for high-risk NB. Citation Format: Ke-En Tan, Kok Siong Yeo, Cheng Zhang, Caleb Baker, Shyang Hong Tan, Alexis M. Sosic, Yat-Yuen Lim, Choong-Yong Ung, Cristina Correia, Stephanie F. Polites, Yi Lin, William A. Weiss, Hu Li, Shizhen Zhu. Engineering macrophages as a novel therapeutic approach for high-risk neuroblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 7810.
Abstract 7903: MiR-362-3p enhances platinum response in breast cancer
Abstract The INFORM trial (NCT01670500) was a randomized, two-arm Phase II neoadjuvant study comparing the efficacy of a platinum-based regimen (cisplatin) versus an anthracycline (AC)-based regimen in participants with germline BRCA1/2 mutations and early-stage, HER2-negative breast cancer. MicroRNAs (miRNAs) are emerging as promising non-invasive biomarkers for disease detection and treatment monitoring. The initial aim of this study was to evaluate whether pretreatment plasma miRNA profiles were associated with treatment outcomes in the INFORM trial cohort. Pretreatment plasma samples from 97 INFORM participants (n=53 cisplatin and n=44 AC) were screened for 352 miRNAs commonly implicated in cancer using the qPCR-based ID3EALTM Cancer Panel. Twenty out of 53 participants achieved residual cancer burden (RCB) score of 0 or 1 with cisplatin and 20/44 with AC. Higher plasma miR-362-3p expression was associated with a favorable response to cisplatin (1.7-fold; p<0.01), but not to AC. MiR-362-3p expression in paired pretreatment tumor biopsies (n=79) did not significantly correlate with plasma expression and was not associated with RCB 0/1 (p>0.05). In TCGA, miR-362-3p expression was higher in breast tumors than in adjacent normal tissue, and higher in triple negative breast cancers (TNBCs) compared with hormone receptor-positive tumors (both FDR<0.001), independent of BRCA mutation or Single Base Substitution Signature 3 (SBS3) status. The miR-362-3p findings in INFORM did not replicate in a sister trial, TBCRC 030 (NCT01982448; 11 out of 46 cisplatin-treated patients achieved RCB 0/1, p=0.46). These results suggest that while miR-362-3p is unsuitable as a circulating biomarker for cisplatin response, it may play an important biological role in mediating cisplatin sensitivity in TNBCs, independent of BRCA1/2 mutations. Functional studies demonstrated that miR-362-3p is expressed and secreted by TNBC cell lines, operates as a tumor suppressor, and generally correlates with cisplatin sensitivity. Overexpression of miR-362-3p rendered MDA-MB-231 and CAL-51 cells cisplatin sensitive, while knockdown induced resistance in MDA-MB-436 cells. Ongoing studies are testing whether these effects translate in xenograft models. In silico and functional assays identified BCLAF1, a DNA damage response (DDR) regulator, as a direct target of miR-362-3p. Overexpression of miR-362-3p suppresses BCLAF1 mRNA and protein levels. Our findings demonstrate that miR-362-3p enhances cisplatin responsiveness by targeting BCLAF1. A miR-362-3p-based therapeutic may be useful as a co-agent to enhance tumor responses to platinum-based chemotherapy. Citation Format: Zhaoji Liu, Shizhong Ke, Xiaohui Li, Catherine Wu, Madison M. Uyemura, Brian R. Sardella, Erica S. Massicott, Lin Wang, Emily K. Aronson, Dimitra Karagkouni, Nikolas Kalavros, Ioannis S. Vlachos, Felipe Batalini, Cristina S. Bogsan, Jit Kong Cheong, Lihan Zhou, He Cheng, Phillip Munson, Erica L. Mayer, Judy E. Garber, Stuart J. Schnitt, Nadine M. Tung, Andrea L. Kasinski, Frank J. Slack, Gerburg M. Wulf, Yujing J. Heng. MiR-362-3p enhances platinum response in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 7903.
Abstract 5516: Learning-based invariant feature engineering reveals symmetry-encoded fingerprints of cancers that facilitate drug discovery.
Abstract Background: Symmetry principles, a long foundational framework in physics and chemistry, have rarely been applied to understand biological phenotypes especially in cancers. Here we examine whether symmetric relationships in gene expression can characterize and differentiate healthy from disease conditions. Method: To test this concept, we built a hybrid machine-learning framework, Learning-Based Invariant Feature Engineering (LIFE), that applies two symmetric invariant feature functions, IFF1 and IFF2, to all possible gene pairs in bulk transcriptomic datasets to identify invariant feature genes (IFGs) - gene pairs whose transformed expression values by either IFF1 or IFF2 produce quasi-constant single-value outputs within a phenotype despite inter-individual variability. Results: Using bulk transcriptomes from 25 normal organs (GTEx) and 25 cancer types (TCGA), we computed IFF values for all normally distributed gene pairs, selected the 1000 most stable pairs per phenotype, and evaluated their performance in multiclass classification with five-fold cross-validation and independent hold-out testing. IFGs generated >70% accuracy across organs and cancers, establishing the existence of robust phenotype-specific symmetry “fingerprints.” Mapping approved and experimental drug targets onto networks construction from IFGs (IF-Nets) showed strong enrichment of hubs in cancer networks and highlighted the use of IF-Nets as drug discovery platforms in cancer treatment. Conclusion: Our findings demonstrate that gene-expression symmetry as a unifying organizing principle for phenotype definition and illustrate how IFGs and IF-Nets can guide biomarker design and symmetry-aware pharmacological intervention via “symmetry breaking.” Citation Format: Cristina Correia, Choong-Yong Ung, Cheng Zhang, Shizhen Zhu, Hu Li, . Learning-based invariant feature engineering reveals symmetry-encoded fingerprints of cancers that facilitate drug discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5516.
Abstract 899: Building a national network coordination center for clinical trials: Early implementation outcomes from the CP2CT DECC.
Abstract Background: Despite the decline in overall mortality and incidence of cancer in the US population, the burden of cancer is still high, especially in underserved and under-researched populations. A major contributor to poor cancer outcomes is the absence of dedicated efforts utilizing scientifically rigorous approaches and implementation strategies to optimize participant enrollment and accrual in clinical trials. The Connecting Patient Populations to Clinical Trials (CP2CT) program implements innovative multilevel interventions to enhance clinical trial awareness and optimize referral pathways that facilitate patient enrollment. The CP2CT Data, Evaluation, and Coordinating Center (DECC) supports its data and evaluation activities, and coordinates a learning collaborative towards mitigating the key barriers of cancer burden in all populations. Methods: Using an implementation science-informed approach, the DECC deployed coordinated strategies over three years: (1) administrative structuring through streamlined governance, centralized reporting, and stakeholder integration; (2) data standardization via Common Data Elements (CDEs), a cross-network REDCap system, and a multi-institution Data Transfer Agreement (DTA); (3) evaluation infrastructure through a Network Logic Model, evaluation plan, standardized constructs, and a Process Evaluation Plan with tools; (4) learning supports through an internal website and expanded Speaker Series; and (5) site-level implementation facilitation through structured visits. Results: In collaboration with the CP2CT Network and NCI, the DECC’s achievements span four domains: (1) Administrative: built infrastructure, deployed centralized reporting platforms, coordinated key meetings, and strengthened community integration. (2) Data: standardized collection, secured network-wide data sharing through the DTA, enabled harmonized multi-site reporting, and advanced groundwork for interoperability and scientific value. (3) Program Evaluation: linked CP2CT activities to measurable outcomes through a Network-wide Logic Model, guided evaluation, established shared evaluation language, and launched a transferable Process Evaluation framework. (4) Learning Collaborative: developed a centralized resource hub, expanded the Speaker Series, and advanced authorship transparency with the CP2CT Publication Policy. < Conclusion: The CP2CT DECC has established a sustainable, scalable infrastructure that integrates administrative coordination, standardized data collection, robust program evaluation, and a collaborative learning environment. These efforts enhance clinical trial awareness, optimize referral pathways, and provide a transferable model for improving participant enrollment and scientific rigor across national research networks, ultimately addressing disparities in cancer outcomes. Citation Format: Laura E. Lectora, Cristina J. Orozco, Holly A. Thorson, Timethia Bonner, Robert R. Freimuth, Jennifer G. Le-Rademacher, Folakemi T. Odedina. Building a national network coordination center for clinical trials: Early implementation outcomes from the CP2CT DECC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 899.
Abstract 860: Development of and consensus building towards shared metrics, measures and benchmarks for the connecting patient populations to clinical trials (CP2CT).
Abstract Background: Multidisciplinary research networks often face challenges in harmonizing metrics and measures across participating sites, limiting the ability to aggregate data and generate generalizable insights. To address this barrier within the Connecting Patient Populations to Clinical Trials (CP2CT) Network, the Data, Evaluation, and Coordinating Center (DECC) coordinated the establishment of a unified framework that supports comparable evaluation and enhances the scientific impact of network-wide activities. Methods: Consensus was developed through a structured, iterative, and collaborative process: (1) drafting initial constructs, metrics, measures, and benchmarks informed by Network site materials and relevant literature; (2) soliciting qualitative and quantitative feedback from Network sites via Basecamp, an innovative online collaborative workspace for construct development; (3) conducting open dialogue sessions followed by systematic review and integration of site feedback; and (4) refining all elements through repeated feedback cycles until no further modifications were requested. Each iteration strengthened the clarity, coherence, and scientific precision of the final constructs. Results: A total of seven constructs were incorporated into the consensus-development process: clinical trials referral, clinical trials accrual, participants’ awareness of clinical trials, participants’ knowledge of clinical trials, providers’ awareness of NCI-supported clinical trials, providers’ engagement with NCI-supported clinical trials, and providers’ referral to NCI-supported clinical trials. For each construct, the Network established a conceptual definition (broad description of the construct), an operational definition (specification of how the construct is measured or observed), benchmarks (standards for assessing performance), metrics (quantitative indicators of performance), and measures (tools used to quantify inputs, processes, or outcomes). Common measures were developed for two constructs—clinical trials accrual and participants’ knowledge of clinical trials. Although full consensus was not achieved across all four Network sites for every construct, at least three sites reached consensus for the remaining five constructs. Conclusion: This consensus-building initiative resulted in the development of a unified, scientifically grounded framework. By harmonizing key elements related to clinical trial referral, accrual, awareness, knowledge, and provider engagement, the Network has established foundational tools that enable cross-site data comparability and facilitate more rigorous assessment of efforts to connect diverse patient populations to clinical trials. This framework positions the Network to inform strategies that improve equitable clinical trial participation. Citation Format: Folakemi T. Odedina, Jennifer Le-Rademacher, Robert Freimuth, Cristina Orozco, Laura Lectora, Timethia Bonner, Holly Thorson, Connecting Patient Populations to Clinical Trials(CP2CT) Program Evaluation Work Group, Connecting Patient Populations to Clinical Trials(CP2CT) Steering Committee. Development of and consensus building towards shared metrics, measures and benchmarks for the connecting patient populations to clinical trials (CP2CT) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 860.
Outcomes of soft-tissue reconstruction for isolated type III internal hemipelvectomy
Aims A type III internal hemipelvectomy includes resection of the pubic rami. Although bony reconstruction is not necessary, the integrity of the abdominal wall is deficient following resection. The aim of this study was to report the outcome of soft-tissue reconstruction following these resections. Methods We retrospectively reviewed all isolated type III internal hemipelvectomies which were undertaken at the Mayo Clinic (Rochester, USA) between January 2002 and December 2022. The group included 25 patients, of whom 14 (56%) were male. Their median age was 45 years (IQR 61 to 31) at the time of surgery. Most patients (n = 18; 72%) underwent resection for a sarcoma. Soft-tissue flaps were used in 21 patients (84%) and nine also had a mesh reconstruction. Results The five-year disease-specific survival was 65% following surgery, with significantly worse survival in patients with locally advanced tumour (35% (95% CI 12 to 100) vs 76% (95% CI 59 to 99); p = 0.036). Complications were common, with 21 patients (84%) having at least one complication, and 12 (48%) having several complications. Most commonly, this included seroma or haematoma (44%), wound dehiscence (40%), and infection (40%). The use of a soft-tissue flap did not significantly reduce the risk of infection (hazard ratio (HR) 0.68 (95% CI 0.14 to 3.28); p = 0.638) or seroma or haematoma (HR 0.31 (95% CI 0.30 to 4.14); p = 0.088), but patients who did not have a soft-tissue flap were significantly more likely to develop a hernia (odds ratio 9.0 (95% CI 1.14 to 71.03); p = 0.027). A total of three of 21 patients (14%) whose reconstruction involved a flap had donor site complications. Conclusion Soft-tissue reconstruction following a type III internal hemipelvectomy reduces the risk of postoperative hernia formation, with a low rate of donor site complications. This additional procedure should be considered for all patients undergoing this type of resection. Cite this article: Bone Joint J 2026;108-B(4):561–566.
Mini-Galaxy: Rethinking Complex Human Diseases Through the Lens of Systems Biology and Multilayered AI Network Perspectives
Human diseases are complex and arise from the coordinated action of multiple genes and their protein products. Genes’ behaviors extend beyond genetic variants, mutations, and differential expressions. Their coordinated activity across biological scales (molecules, cells, tissues, organs) produces emergent behaviors that shape health and disease. These emergent behaviors span time and space and are often hard to measure directly from observation when using standard experimental measurements. Yet these “hidden” or latent gene characteristics can be powerful drivers of disease. We propose a Mini-Galaxy Model (MGM), a systems-level AI-driven network framework that models cells as “mini-galaxies” composed of multilayered biological information, with each layer encoding a different dimension of genes’ behavior. Here, we delineate a strategy on how to construct and compare MGMs across health and disease and map their etiological relatedness. We also operationalize the MGM as a discovery platform for translational medicine, offering modules to allow target prioritization and editing. By reframing human diseases as the result of emergent behavior of multilayered multimode biological networks and their perturbations, the MGM yields actionable rules to streamline biomarker discovery, guide target selection and enable rational design of combinatorial interventions, and accelerate drug repurposing.
Stroke and systemic embolism following atrial fibrillation ablation: the EMBOL-AF Global Registry
Abstract Background and Aims Stroke and systemic embolism are recognized but poorly characterized complications of atrial fibrillation (AF) and left atrial flutter (AFL) catheter ablation. Their incidence, outcomes, and procedural associations remain insufficiently defined. Methods Retrospective global registry was initiated by the European Heart Rhythm Association Scientific Committee. A secure database captured data from ablation centres worldwide on general AF and left AFL ablation activity, as well as detailed information on patients with symptomatic embolic events between 2017 and 2024. Results Overall, 204 centres reported 335 743 ablation procedures and 550 embolic events (incidence 0.16%). Centre-level rate ranged from 0% to 3.1%. Most events were cerebral (94%), followed by peripheral (5%), and combined (1%). Coronary air embolism accounted for 62% of all peripheral events. Intraprocedural events occurred in 93 patients (17%), within 72 h in 357 (78%) and beyond 72 h in 100 (22%); 128 cases (23%) were diagnosed after hospital discharge. Nonparoxysmal AF (0.23% vs 0.15%; P < .001), centre experience, and ablation energy source (radiofrequency, 0.16%; cryoballoon, 0.16%; pulsed field ablation, 0.25%; laserballoon, 0.88%; P < .001) were associated with embolic risk. Median NIHSS score after stroke was 4 (interquartile range, 2–9). Three-month follow-up was available for 518 patients with embolism (95%): 181 (35%) had sequelae and 16 (3%) died. Conclusions Symptomatic embolic events are infrequent but associated with significant morbidity and mortality. Most events occur early, though a substantial proportion arise later. Higher event rates were observed with laser and possibly with pulsed field ablation. A greater centre experience was associated with a lower embolism incidence.
Molecular-Based Ecosystem to Improve Personalized Medicine in Chronic Myelomonocytic Leukemia
PURPOSE Chronic myelomonocytic leukemia (CMML) is a rare myeloid neoplasm characterized by clinical heterogeneity and is associated with poor outcomes. To date, limited molecular information has been incorporated into disease classification and risk stratification. We aimed to integrate genomic features into the clinical decision-making process for CMML. PATIENTS AND METHODS We analyzed a retrospective cohort of 3013 patients with CMML (training set) and a prospective population of 516 patients (validation set). Using an innovative framework for multimodal data analysis, we developed molecular-based disease taxonomy and prognostication. RESULTS Unsupervised clustering identified nine entities with distinct genomic features and outcomes ( P < .001), including splicing machinery, transcription factors, signal transduction and tyrosine kinase pathways aberrations, and high-risk molecular signatures. Notably, 15% of patients showed molecular/clinical overlap with other myeloid neoplasms. We integrated molecular and clinical information to build the international CMML Prognostic Scoring System (iCPSS), incorporating mutations in nine genes together with hematologic parameters and cytogenetic abnormalities. The iCPSS identified five groups with distinct probability of overall and leukemia-free survival in both training and validation cohorts ( P < .001), outperforming existing prognostic models. Importantly, 55% of patients were reassigned to higher or lower risk groups by the iCPSS. Decision analysis demonstrated that iCPSS could refine the optimal timing of allogeneic transplantation at the individual level; compared with conventional prognostic tools, iCPSS-based decision modeling changed transplantation strategy in 31% of cases, resulting in a significant gain-in-life expectancy for eligible patient population ( P < .001). A federated learning platform was implemented to enable continuous, privacy-preserving model update across multiple centers. CONCLUSION Molecular information improves CMML classification and prognostication, supports more effective clinical decision making, and potentially refines the design of clinical trials.
Mechanical dyssynchrony and septal–lateral perfusion heterogeneity predict adverse left ventricular remodelling beyond ECG-defined LBBB
Abstract Aims Left bundle branch block (LBBB) is associated with mechanical dyssynchrony, heterogeneous perfusion, and adverse left ventricular (LV) remodelling. However, not all patients with LBBB develop cardiomyopathy, and dyssynchrony can occur without conduction defects. The role of microvascular dysfunction remains uncertain. We aimed to assess how mechanical dyssynchrony and perfusion heterogeneity relate to LV remodelling and function in patients with and without LBBB. Methods and results We analysed 233 patients with LBBB and 932 matched controls who underwent PET myocardial perfusion imaging, assessing mechanical dyssynchrony (phase entropy), LV volumes, and ejection fraction (EF); coronary vascular resistance (CVR), myocardial blood flow (MBF), myocardial flow reserve (MFR) as markers of microvascular function; and septal-to-lateral MBF ratio (SLR) as a measure of regional perfusion heterogeneity. Compared with controls, LBBB patients had greater dyssynchrony (56% vs. 40%), larger LV volumes, and lower EF (54% vs. 67%) (all P < 0.001), as well as higher stress CVR (37 vs. 34 mmHg/mL·min−1·g−1), and lower MBF (2.4 vs. 2.6 mL/min/g), MFR (2.4 vs. 2.6), and SLR (0.95 vs. 1.00) (all P < 0.05). Among patients with dyssynchrony, SLR <1.0 identified greater remodelling. In multivariable regression, phase entropy and SLR independently predicted LV volumes and EF, with adverse effects of SLR reduction amplified in LBBB (interaction P < 0.01). In Cox analysis, phase entropy (HR:1.02, P = 0.01), MFR (HR:0.62, P < 0.001), and LVEF (HR:0.97, P < 0.001) were independently associated with death or heart failure hospitalization, whereas LBBB was not. Conclusion Mechanical dyssynchrony and perfusion heterogeneity independently predict adverse LV remodelling, irrespective of LBBB. Integrated imaging improves cardiomyopathy stratification.