Citations

Abstract Background and Aims Whether hemodynamic and symptomatic benefits of the APTURE left atrial-to-coronary sinus shunt translate into clinical outcome benefit in heart failure with left ventricular ejection fraction >40% remains unknown. Methods In this post hoc analysis of ALT-FLOW EFS patients undergoing APTURE implantation, Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) score-predicted 1-year all-cause mortality was compared with observed mortality by Kaplan-Meier analysis of adjudicated events. Heart failure hospitalization (HFH) rates were compared for the 12 months before vs after implantation. Additional analyses included stratification by baseline sodium-glucose cotransporter 2 inhibitor (SGLT2i) use and N-terminal pro-B-type natriuretic peptide (NT-proBNP), recurrent HFH cumulative hazard estimation (Nelson-Aalen), and H2FPEF score calculation. Results Among 95 patients (mean age 70.9 ± 8.5 years; 50% women; 93% New York Heart Association Class III; 85.9% with H2FPEF score >3), MAGGIC-predicted 1-year mortality was 13.0%. Observed 1-year survival was significantly higher than predicted (94.7% vs 87.0%; P=0.04), consistent across SGLT2i subgroups (log-rank P=0.59). The proportion of patients with HFH declined from 37.9% pre implantation to 9.6% post implantation (P<0.0001), with event rates falling from 0.61 to 0.21 per patient-year (P<0.001) and a 1-year cumulative hazard of recurrent HFH of 0.19 (95% confidence interval, 0.12-0.31). HFHs were evenly distributed across NT-proBNP strata. Conclusions In ALT-FLOW EFS, observed 1-year mortality was lower than MAGGIC-predicted mortality, and post implantation HFH rates were lower than pre implantation rates. These hypothesis-generating findings will require confirmation in the randomized, sham-controlled ALT-FLOW II trial.

Abstract 5-Fluorouracil (5-FU) is a widely prescribed chemotherapy for colorectal, breast, gastric, and head and neck cancers. The drug inhibits thymidylate synthase, blocking DNA synthesis and causing cytotoxic stress that halts tumor growth. However, patients carrying deleterious variants in DPYD, the gene encoding the rate-limiting enzyme in 5-FU metabolism (dihydropyrimidine dehydrogenase, DPD), can experience fatal toxicity due to impaired drug clearance and accumulation of 5-FU metabolites. Current pharmacogenetic screening guidelines in the U.S. recommend testing for few of the >2,000 nonsynonymous variants that have been reported for DPYD, leaving patients with rare, uncharacterized mutations at risk. To interpret expanded testing, however, a means to classify DPYD variants of unknown significance is needed. To address this, we developed MPACT-DPD, a random-forest-based classifier that accurately predicts the functional impact of DPYD missense variants. Our model was trained on in-vitro activity of 156 variants and leveraged a feature set of biochemical, evolutionary, and AlphaFold3-derived structural features. We optimized hyperparameters using ten-fold stratified cross-validation and evaluated model performance with Matthews correlation coefficient (MCC) to account for moderate class imbalance (7:3 neutral to deleterious). It achieved exceptional performance, with a Matthews correlation coeffient (MCC) of 0.906 and an accuracy of 95.1% on an independent validation set (n=43). Furthermore, a SHAP (SHapley Additive exPlanations)-based interpretability analysis revealed cofactor proximity and residue conservation as the key drivers of predictions. MPACT-DPD showed superior performance at variant classification against other tools, including a DPYD gene-specific variant classifier, and has the potential to expand pre-treatment genetic screening to improve the safety of personalized 5-FU-based chemotherapy. Citation Format: Lulu Jiang, Ryan Jonathan Swartz, Lauryn Allyn Hahn, Brianna Bembenek, Hannah Marie Krause, Kelly Bouchonville, Steven M. Offer. MPACT-DPD: An interpretable machine learning classifier for predicting the functional impact of DPYD missense variants [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 2712.

Abstract Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal human malignancies due to its silent clinical onset, rapid progression, and limited responsiveness to current treatment options. These features underscore the urgent need for early detection strategies and for new molecular targets that can be exploited therapeutically. Epithelial Cell Transforming Sequence 2 (ECT2) is a Rho family guanine nucleotide exchange factor that was originally identified as an oncoprotein and later shown to regulate cytokinesis. In this study, we examined the clinical relevance of ECT2 expression in PDAC and determined its functional contribution to transformed growth and tumorigenicity. Our analyses revealed that ECT2 expression increases at the earliest stages of PDAC development, remains persistently elevated during disease progression, and associates with reduced overall patient survival. Furthermore, a substantial fraction of ECT2 is aberrantly localized to the cytoplasm of PDAC cells. Functional studies demonstrated that depletion of ECT2 suppresses three-dimensional growth, invasive behavior, and tumor formation in vivo, while having little impact on PDAC cell cytokinesis. Mechanistically, we found that ECT2 is required for activation of Rac1 and RhoA and downstream MEK/ERK and ROCK signaling, respectively. Consistent with these results, analyses of PDAC patient datasets revealed a strong positive association between ECT2 expression and Rho GTPase as well as MEK/ERK and ROCK pathway signatures. Together, our data identify ECT2 as an early driver of PDAC transformation and highlight it as a promising therapeutic target. Citation Format: Dania Al-Qasrawi, Nayya N. Murray, Ryan A. Argo, Alicia K. Fleming Martinez, Prita Pandya, Anaya Y. Clarke, Kayla C. Winter, Murli Krishna, Peter Storz, Nicole R. Murray, Verline Justilien, . The Rho-GEF ECT2 links Rho GTPases to MEK/ERK pathway activation in pancreatic ductal adenocarcinoma [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 5993.

Abstract Therapeutic resistance to chemotherapy is frequently the proximate cause of increased tumor burden, cancer treatment failure, and ultimately, patient mortality. The most successful therapy strategy derived from evolutionary practices to date, Adaptive Therapy (AT), leverages the fitness cost of developing therapeutic resistance. AT avoids treating cancer cells with the Maximum Tolerated Dose (MTD) of therapeutic drugs and instead incorporates a series of adaptive dosing schedules. Treatment-sensitive cells are bolstered by modulating or pausing treatment to out-compete and suppress treatment-resistant cell growth. We are evaluating AT for the first time in colorectal cancer, using a syngeneic orthotopic xenograft model. This work represents several key advances: it is the first to longitudinally and non-invasively track sensitive and resistant clones in vivo, to evaluate adaptive therapy in an immunocompetent mouse model, to incorporate multi-drug treatment regimens, and to integrate a targeted therapeutic agent. The dual-bioluminescent sensitive and resistant CT26 cell lines developed for this study allow real-time visualization and quantification of each population throughout tumor progression and treatment. Together, these advances establish a robust and clinically relevant platform for characterizing resistance dynamics and refining adaptive therapy strategies aimed at improving treatment outcomes in colorectal cancer. Citation Format: Harley I. Richker, Bailey Sierra Kane, Gissel Marquez Alcaraz, Ellie Pahl, Ryan Carr, Nagarajan Kannan, Carlo C. Maley. Harnessing clonal dynamics to overcome resistance: An adaptive therapy framework in colorectal 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 702.

Abstract Background: Spatial cellular ecosystems in the tumor microenvironment (TME) form dynamic signaling hubs that critically influence cancer disease progression and response to therapy, including response to immune checkpoint inhibitors (ICIs). However, tumor sampling bias and the impracticality of acquiring serial tumor biopsies have made it challenging to profile the TME clinically. To address this challenge, we developed Liquid EcoTyper, a multi-analyte AI framework to quantify TME spatial cellular ecosystems—termed spatial ecotypes (SEs)—noninvasively from cell-free DNA (cfDNA) methylation data. Methods: In previous work, we discovered nine spatial ecotypes, including SEs associated with ICI response (e.g., SE7 with benefit, SE4 with resistance), and quantified them from 1,249 bulk tumor RNA-seq profiles of melanoma, non-small cell lung cancer (NSCLC), and bladder cancer (BC) patients (Cancer Res (2025) 85 (8_Supplement_1): 153). Here we trained Liquid EcoTyper, an interpretable deep learning model, to transfer SE profiling to cell-free DNA using CpG methylation profiles. Performance was quantified using simulated and real data, including methylation profiles (EM-seq) of plasma cfDNA paired with tumor biopsy-derived SE levels determined by EM-seq (n=20 pairs) or 10x Visium (n=15 pairs). Clinical outcome prediction was evaluated using pretreatment plasma from patients treated with ICI alone (n=78 melanoma pts), chemotherapy and ICI (n=25 NSCLC pts), and enfortumab vedotin and ICI (n=10 localized muscle-invasive BC (MIBC) pts). Tumor mutational burden (TMB), tumor PD-L1, or circulating tumor DNA (ctDNA) were profiled as a comparator where possible. Results: We observed striking concordance between plasma-derived SE levels and tumor biopsy-confirmed SE levels from the same patients, demonstrating that liquid biopsy analysis of cfDNA methylomes can recapitulate TME spatial biology. Underscoring specificity, no reliable SE signal was detectable from peripheral blood mononuclear cells. In pre-ICI plasma, liquid SE levels were significantly associated with ICI-based response (SE7) versus resistance (SE4) in patients with melanoma, NSCLC, and MIBC, with a mean cross-cancer area under the curve (AUC) of 0.87 for SE7 (range 0.8-0.97) and 0.81 for SE4 (range 0.76-0.85)—far surpassing TMB, tumor PD-L1, and ctDNA in evaluable patients, both in binary analyses of response and multivariable models of survival. Our results also showed potential to predict pathologic complete response in the neoadjuvant setting. Conclusion: Liquid EcoTyper is a scalable noninvasive AI-based framework for spatiotemporal assessment of the TME. By enabling TME-informed risk stratification without surgical biopsies, Liquid EcoTyper has potential to enable more precise and actionable decision making in patients with solid tumors. Citation Format: Erin L. Brown, Wubing Zhang, Abul Usmani, Noah Earland, Ayesha Hashmi, Chibuzor Olelewe, Anushka Viswanathan, Pradeep S. Chauhan, Minji Kang, Chloé B. Steen, Hyun Soo Jeon, Susanna Avagyan, Irfan Alahi, Nicholas P. Semenkovich, Matteo Bergsagel, Janella C. Schwab, Chloe M. Sachs, Faridi Qaium, Peter K. Harris, Antonella Bacchiocchi, Qingyuan Cai, Andrew J. Gentles, Rondell P. Graham, Peter C. Lucas, Ryan C. Fields, Jacob J. Orme, Aaron S. Mansfield, Mario Sznol, Ruth Halaban, David Y. Chen, Aaron M. Newman, Aadel A. Chaudhuri. Liquid biopsy profiling of the tumor microenvironment to determine response to immunotherapy regimens across solid tumors [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 94.

Abstract Adipose‐derived cellular therapies (AD‐CTs) are increasingly used in orthopedics, yet the field lacks a standardized framework for classifying these heterogeneous products. Although prior efforts have standardized platelet‐rich plasma and bone marrow‐derived mesenchymal stromal cells, AD preparations remain inconsistently defined and poorly characterized. AD‐CTs encompass a range of products including enzymatically derived stromal vascular fraction, culture‐expanded adipose‐derived mesenchymal stromal cells (AD‐MSCs), and mechanically processed adipose tissue (AD‐MPT),each with distinct regulatory, cellular, and structural profiles. Unlike stromal vascular fraction and AD‐MSCs, which can be quantified using conventional assays, the intact extracellular matrix in AD‐MPTs complicates objective characterization. This paper introduces the Mechanical Processing (Harvesting) of Adipose Tissue classification system as a novel framework for standardizing the reporting of AD‐MPT harvesting and processing techniques that provides a structured approach to nomenclature and reporting. The system aims to enhance study comparability, facilitate research replication, and support the responsible advancement of adipose‐based therapies in musculoskeletal medicine.

Background/Objective: Dietary, supplement, and activity exposures have only been studied in spondyloarthritis (SpA) with retrospective studies. We aimed to determine the association of diet, supplements, and physical activity with incident SpA. Patients and Methods: We performed a case-control study in the Mayo Clinic Biobank from 2009 through 2015, matching criteria-confirmed incident SpA cases to controls 1:5 on age, sex, recruitment year, and location. Questionnaires assessed 16 dietary, 29 supplement, and leisure-time/work activity exposures. Logistic regression models calculated adjusted odds ratios (aOR) with 95% CIs of SpA for each exposure, adjusting for covariates. Sensitivity analyses were conducted within HLA-B27-positive patients, and those with baseline questionnaires completed 5+ years before index. Results: We identified 73 cases of incident SpA matched with 365 controls (mean age: 60, 70% females). No dietary or activity exposures were associated with SpA overall. However, among HLA-B27-positive individuals, non-diet soft drink consumption was associated with increased risk of SpA (aOR: 4.82, 95% CI: 1.29-18.1), whereas caffeinated coffee was associated with decreased risk (aOR: 0.20, 95% CI: 0.04-0.89). Zinc was associated with increased risk of SpA (aOR: 4.16, 95% CI: 1.19-14.6), as were B vitamins in the HLA-B27-positive subgroup (aOR: 4.21, 95% CI: 1.04-17.1). In the 5-year sensitivity analysis, low leisure-time physical activity plus high work physical activity was associated with increased risk of SpA (relative excess risk due to interaction: 0.50, 95% CI: 0.03-0.98). Conclusions: Due to small sample size and multiple comparisons, the risk factors we identified (non-diet soft drinks, B vitamins, and zinc) should be considered hypothesis-generating and warrant further investigation.

Abstract Background Robotic left pancreatectomy (RLP) is increasingly adopted worldwide. Current guidelines suggest a learning curve of 21 cases, yet its impact on major morbidity and oncological quality remains uncertain. Methods A retrospective multicentre international study was undertaken across 10 centres in the UK, Spain, Germany, the USA, and Australia (2014–2025). Consecutive patients undergoing RLP were categorised into competency (first 21 cases per centre) or proficiency phase (>21). The primary outcome was major morbidity (Clavien–Dindo grade ≥ IIIa), and secondary outcome was the R1-margin rate. Mixed-effects logistic regression and risk-adjusted cumulative sum (RA-CUSUM) analyses were performed. Results 521 patients underwent RLP, including 200 (38.4%) in the competency phase and 321 (61.6%) in the proficiency phase. Median age was 63 years (IQR 54–73), and 56.4% were female. Rates of major morbidity were similar between phases (14.5% versus 14.0%, P = 0.981), as were R1 margin rates (21.6% versus 19.7%, P = 0.092). Independent predictors of major morbidity included male sex (OR 1.76, P = 0.037), preoperative pancreatitis (OR 2.23, P = 0.031), and multivisceral resection (OR 2.29, P = 0.034). Among patients with adenocarcinoma (n = 110), prolonged operative time (OR 1.39 per hour, P = 0.004) and nodal positivity (OR 2.62, P = 0.047) predicted R1 resection, while learning phase was not associated with margin status. RA-CUSUM demonstrated no excess morbidity over time in any centre. Conclusions In this first multicentre international analysis, the learning phase of RLP did not increase the risk of major morbidity or compromise oncological quality. These findings support the safe global adoption of RLP with appropriate training and case selection.

Objective Identifying eligible patients for precision oncology clinical trials is challenging, particularly for rare molecular subpopulations. To address this challenge, A2 Biotherapeutics developed BASECAMP-1 ( NCT04981119 ), a non-interventional master screening study to identify patients eligible for interventional studies of logic-gated Tmod chimeric antigen receptor T-cell therapies. Eligible patients for these interventional trials have an advanced solid malignancy and are germline human leucocyte antigen (HLA)-A*02 heterozygous, with tumour-associated HLA-A loss of heterozygosity (LOH). HLA-A LOH occurs in ~16% of advanced solid malignancies; therefore, an efficient screening strategy is required. This report describes BASECAMP-1; compares the efficiency of two screening methods; and discusses the broader advantages of BASECAMP-1 beyond efficient enrolment. Methods and analysis Patients are identified for BASECAMP-1 using two approaches. In the traditional approach, common for clinical trials, investigators consent and screen all patients who might be good candidates for cell therapy trials, with no prior knowledge of patient HLA-A type or LOH status. To further optimise our approach, we co-developed with Tempus AI (Tempus) the bioinformatic programme Aware, which identifies potentially eligible patients with tumour-associated HLA-A*02 LOH within a clinico-genomic database that includes linked genomic and transcriptomic sequencing and clinical data collected during routine care. Results Over 42 months of using a traditional approach to identify eligible patients, 1918 patients at 13 study sites were consented and screened for BASECAMP-1; of these, 30 patients with tumour-associated HLA-A*02 LOH were enrolled (~0.7 participants per month). Over the last 30 months of that same period, Tempus Aware screening was implemented and 55 patients with tumour-associated HLA-A*02 LOH were enrolled (~1.8 participants per month). The bioinformatic approach identified more patients than the traditional approach and used sequencing results produced as part of the standard clinical tumour sequencing workflow, reducing resource use and study staff burden. Additional advantages of using a screening study, such as BASECAMP-1, include manufacturing efficiencies and collection of a large dataset of molecular and clinical parameters that can be used to supplement trial analyses. Conclusions The BASECAMP-1 study demonstrates a clinico-genomic screening approach can more efficiently identify patients for precision oncology trials. Furthermore, precision oncology can be enhanced through collaborative data-sharing. Trial registration number NCT04981119 .