Citations

Abstract In a real-world analysis of brexucabtagene autoleucel recipients with relapsed/refractory B-cell acute lymphoblastic leukemia (N = 278), lack of response to prior blinatumomab correlates with significantly worse following chimeric antigen receptor T-cell therapy outcomes.

Objective: Orthobiologics are increasingly sought-after interventions in sports medicine for treatment of musculoskeletal injuries and conditions. Despite this trend, differences exist across sports medicine fellowship programs regarding foundational knowledge, educational curricula, and practical experience with orthobiologic therapies (eg, platelet-rich plasma, bone marrow aspirate concentrate, microfragmented adipose tissue). This represents an important educational gap for those training in sports medicine fellowships. To address this gap, an educational toolkit was envisioned with the sports medicine fellowship director and trainee in mind. Data Sources: Collective observations from physician experts in sports medicine education established the variations in curricula and expertise of graduating fellows. A literature review was conducted to source English-language peer reviewed articles from the online PubMed database. The scope of this project did not include an independent systematic analysis or statistical assessments. Main Results: An educational toolkit consisting of 12 adaptable modules was developed, each with a suggested reading list from the published literature. The modules may be rearranged to support each program's learning schedule. The information and lessons contained herein may be valuable to all healthcare providers interested in the evidence-based application of orthobiologics and insightful interpretation of related research. Conclusions: By implementing an educational toolkit, sports medicine fellowships may improve the quality of education on orthobiologics. This is intended to improve the knowledge and skill set of fellowship graduates, thus promoting the scientific, responsible use of orthobiologic interventions.

Background Fenestrated and branched endovascular aneurysm repair can be complicated by branch vessel occlusion in the absence of structural stenosis. We hypothesized that computational flow simulation could identify adverse hemodynamic features associated with postfenestrated and branched endovascular aneurysm repair branch occlusion. Methods Patients undergoing 4‐vessel fenestrated and branched endovascular aneurysm repair for Extent II to IV thoracoabdominal aortic aneurysms were retrospectively reviewed. Branches that occluded without identifiable kinking or stenosis on computed tomography were included, along with an equal cohort of anatomy‐matched patent controls. Patient‐specific pulsatile rigid‐wall simulations were performed using SimVascular with individualized geometries and boundary conditions. Abnormal time‐averaged wall shear stress (TAWSS) was defined as <10 or >70 dynes/cm 2 . Results Nine patients (36 target vessels) experienced 10 branch occlusions. Postoperative pressure and flow did not differ significantly between occluded and patent renal or mesenteric branches. However, occluded renal and mesenteric branches demonstrated significantly larger postoperative areas of abnormal TAWSS compared with controls (renal: 14.5% versus 5.9%, P =0.003; mesenteric: 17.7% versus 9.9%, P =0.035). Logistic generalized estimating equation modeling showed abnormal TAWSS to be a significant predictor of renal branch occlusion ( P =0.0085). Model estimates suggested occlusion probabilities of 1.1%, 31%, and 94% at 0%, 10%, and 20% abnormal TAWSS surface area, respectively. A cluster‐bootstrapped receiver operating characteristic curve (area under the curve, 0.876) identified a >10.2% threshold that correctly classified 92% of renal occlusions. Abnormal TAWSS frequently localized to distal stent–artery interfaces. Conclusions Elevated abnormal TAWSS within stented renal branches is associated with subsequent branch occlusion after fenestrated and branched endovascular aneurysm repair. Computational flow simulation‐derived TAWSS thresholds may help identify high‐risk branches before failure, warranting prospective validation.

Abstract Purpose: Pancreatic ductal adenocarcinoma (PDAC) is typically detected too late for useful therapeutic interventions; hence, we sought blood biomarkers to detect early-stage disease. Experimental Design: Using mass spectrometry and ELISA on plasma pools from the University of Pennsylvania (Penn) and the Mayo Clinic (Mayo), we identified aminopeptidase N (ANPEP) and polymeric immunoglobulin receptor (PIGR) as increased in early-stage (stage I/II) PDAC plasma compared with controls. We tested ANPEP and PIGR, along with prior data for thrombospondin 2 (THBS2) and carbohydrate antigen 19-9 (CA19-9), in retrospective phase II studies using separate cohorts of PDAC plasmas at different stages versus healthy or nonmalignant disease controls (DC) from Penn (n = 135) and Mayo (n = 537). Results: Comparing healthy controls with stage I/II PDAC, we obtained area under the receiver-operating characteristic curves (AUC) of 0.78 [95% confidence interval (CI), 0.68–0.86]/0.80 (95% CI, 0.74–0.85; ANPEP) and 0.81 (95% CI, 0.70–0.88)/0.86 (95% CI, 0.82–0.90; PIGR) for the Penn/Mayo phase II studies, respectively. In multivariable models, CA19-9/THBS2/ANPEP, CA19-9/THBS2/PIGR, and CA19-9/THBS2/ANPEP/PIGR elicited AUC of 0.94 to 0.96 for Penn and 0.97 for Mayo. Notably, the four-marker panel elicited AUC of 0.87 for the Mayo stage I/II versus DC and 0.91 for stages I to IV versus DC. At a specificity of 95%, a plasma biomarker panel composed of CA19-9 (≥35 U/mL), THBS2 (≥42 ng/mL), ANPEP (≥2,995 ng/mL), and PIGR (≥1,800 ng/mL) yielded a sensitivity of 91.9% for PDAC stages I to IV and 87.5% for PDAC stage I/II. Conclusions: Adding ANPEP and PIGR to a plasma biomarker panel of CA19-9 and THBS2 enhances the detection of early-stage PDAC when comparing cancer versus healthy or nonmalignant DC. Given the concordance of our data in two retrospective phase II studies, assessments in prediagnostic cases are warranted.

Abstract Background Colonic strictures in Crohn’s disease (CD) present a complex and relatively underexplored clinical issue. Imaging modalities such as computed tomography (CT), magnetic resonance imaging (MRI), and intestinal ultrasound (IUS), have established criteria for evaluating small bowel CD strictures. However, radiologic definitions of benign colonic strictures and their diagnostic accuracy are not well-developed. Endoscopic definitions of colonic strictures are the most well-described. We conducted a systematic review to summarize definitions, diagnosis, and identification of inflammation and fibrosis of colonic strictures on endoscopy, CT, MR, and IUS. Methods A systematic review following PRISMA guidelines, from inception to October 6, 2024, was conducted using MEDLINE, Scopus, CINAHL, and CENTRAL databases to identify literature on diagnostic imaging of patients with colonic CD strictures. Only studies with comparison to endoscopy or imaging to a full-thickness histologic gold standard to differentiate fibrosis from inflammation were included. Two stage screening was completed in duplicate, and risk of bias was assessed using QUADAS-2. Results 46 studies were eligible for inclusion of 4623 abstracts screened. Definitions of colonic strictures on CT, MR, and IUS were highly variable with combinations of bowel wall thickness, luminal narrowing, and pre-stenotic dilation. Endoscopic definitions of colonic strictures were the most consistently reported as lack of passage of a colonoscope through a narrowed lumen. Diagnostic imaging definitions used various combinations of increased bowel wall thickness, luminal narrowing, and pre-stenotic dilation with no clear cutoffs. Few studies directly compared imaging features with histologic or endoscopic gold standards, limiting evaluation of diagnostic accuracy. Meta-analyses were not conducted due to methodological heterogeneity of grading fibrosis across studies. In addition, statistical heterogeneity of sensitivity, specificity, and accuracy of colonic stricture diagnoses was limited by pooling with small bowel strictures in the studies. Conclusion This systematic review highlighted the absence of standardized definitions for diagnosing colonic Crohn’s disease strictures, particularly on diagnostic imaging, and the limited data distinguishing inflammatory from fibrotic components. Bowel wall thickening, luminal narrowing, and pre-stenotic dilation are key features of small bowel strictures, but their relevance to the colon requires further assessment. Establishing standardized definitions for colonic strictures that incorporate both endoscopic and imaging modalities is essential to advancing the field. Conflict of interest: Dr. Lu, Cathy: Advisory board - Abbvie, Johnson and Johnson, Takeda, Ferring, Merck, Celltrion, Lilly, Pfizer, Pendopharm, Agomab. Research Funding - Abbvie, Helmsley Charitable Trust, Alberta Innovates Dhaliwal, Ravdip: No conflict of interest Kellar, Amelia: No conflict of interest Rowan, Catherine: No conflict of interest St-Pierre, Joelle: Consultant for Pfizer, Abbvie, Eli Lilly and Pendopharm, and speaker for Takeda. Ernest-Suárez, Kenneth: Consulting/Advisory Board fees: Abbvie, AstraZeneca, Johnson & Johnson, Pfizer, Ferring, Sandoz, SatisfAI, Takeda O’Brien, Maureen: No conflict of interest Rosentreter, Ryan: No conflict of interest Gulhati, Vishrut: No conflict of interest Baker, Mark: No conflict of interest Bettenworth, Dominik: DB is on the advisory board or consultant for AbbVie, Amgen, Arena, Atheneum, BNG Service GmbH, Bristol Myers Squibb, CED-Service GmbH, Celltrion, Doctorflix, DGVS, Diaplan, Else Kröner-Fresenius Foundation, Falk Foundation, Galapagos, Guidepoint, Impulze, Ferring, Janssen Cilag, Lilly, Medical Tribune, MedTriX, MSD, Mylan, Onkowissen, Pharmacosmos, Pfizer, Roche, Sandoz, Takeda, Tetrameros, Thieme, Tillotts Pharma, UCB Biopiharma, Viatris and Vifor Pharma. Bruining, David: Advisory board fees from Janssen Bari, Dane: Grant from Helmsley Charitable Trust speaker honorarium from Siemens Healthineers support for attending meetings or travel from Siemens Healthineers member of the Olympus advisory board co-chair Society of Abdominal Radiology (SAR) Inflammatory Bowel Disease Disease Focused Panel (IBD DFP) and SAR Photon-Counting Detector CT Emerging Technology Commission and chair of the Society for Advanced Body Imaging Scientific Committee. Dillman, Jonathan: Grants from Philips Healthcare, GE HealthCare, Motilent, Perspectum, Guerbet, and Bracco. El Ouali, Sara: Speaker and/or consulting fees from Takeda, Eli Lilly, Janssen, Abbvie. Fletcher, John: Grant supports from Siemens Healthineers Gordon, Ilyssa: Grants to institution from Morphic Therapeutics, Alimentiv, Pliant Therapeutics, and UCB patent pending with Case Western Reserve University on radiomics signatures Jairath, Vipul: Consulting Fees: Abbvie, Alimentiv, Amgen, Anaptys Bio, Asahi Kasei, Asieris, Astra Zeneca, Attovia, Blackbird Labs, BMS, Boehringer Ingleheim, Biomebank, Caldera, Calluna, Catalytic Health, Celltrion, Ensho, Enthera, Exeliome Biosciences, Ferring, Fresenius Kabi, Gilead, Granite Bio, GSK, Janssen, Lilly, Merck, Mountainfield, MRM Health, Nxera, Organon, OSE Immunotherapeutics, Pendopharm, Pioneering Medicine, Pfizer, Prometheus, Roche/Genentech, Sanofi, SCOPE, Shattuck Labs, Sorriso, Spyre, Synedgen, Takeda, Teva, Tillotts, Union Therapeutics, Ventus, Ventyx, Vividion, Xencor, Zealand Pharma. Feagan, Brian Gordon: Consulting Fees: AbbVie, Abivax, Adaxion, Adiso, AgomAB Therapeutics, Akros, Alira Health, Ally Bridge Group, Apini Therapeutics, Argenx, Attovia Tx, Avoro Capital Advisors, Belmore Law, Biora Therapeutics, Blackbird Laboratories, Boehringer-Ingelheim, BMS, Boxer Capital, Celgene/BMS, Clarivate, Connect Biopharm, EcoR1, Eli Lilly, Ensho Therapeutics, Equillium, Evida, Enveda, Evommune Inc. Faes Farma, First Wave, Forbion, Galapagos, Genentech/Roche, General Atlantic, Genesis Therapeutics, Gerson Lehrman Group, Gilead, Guidepoint, Imhotex, ImiDomics, Immunic Therapeutics, Janssen, Japan Tobacco Inc., LifeMine Therapeutics, Mage Biologics, Merck, Mirador Therapeutics, Mobius Care, Monte Rosa Tx, Morphic Therapeutics, Nimbus Therapeutics, Novartis, Nxera, OncoC3, Palisade Bio, Pendopharm, Pfizer,Q32 Bio, REDX, Roche, Sanofi, Sobi, Sorriso, Spyre Therapeutics, Sun Pharma, Surrozen Inc., Synedgen, Takeda, Tegus Inc., Teva, Tillotts, Trex Bio, TR1X Inc. TVM Lifesciences, Ventyx Biosciences, Versant Ventures, Vida Ventures, Ysios Capital, Zagbio Stock Shareholder: Connect Biopharm, EnGene, Evida, SRT, Imidomics, Enveda Rieder, Florian: Personal Fees: Adiso, Adnovate, Agomab, Allergan, AbbVie, Arena, Astra Zeneca, Boehringer-Ingelheim, Celgene/BMS, Celltrion, CDISC, Celsius, Cowen, Ferring, Galapagos, Galmed, Genentech, Gilead, Gossamer, Granite, Guidepoint, Helmsley, Horizon Therapeutics, Image Analysis Limited, Index Pharma, Landos, Jannsen, Koutif, Mestag, Metacrine, Mopac, Morphic, Organovo, Origo, Palisade, Pfizer, Pliant, Prometheus Biosciences, Receptos, RedX, Roche, Samsung, Sanofi, Surmodics, Surrozen, Takeda, Techlab, Teva, Theravance, Thetis, UCB, Ysios, 89Bio

Abstract INTRODUCTION: Prostate cancer (PC) shows marked heterogeneity in clinical outcomes, from indolent to highly aggressive disease. Alterations in TP53, PTEN, RB1, and DNA damage repair genes are linked to poor patient outcomes, yet how the interaction and co-occurrence of these alterations impact prognosis remains unclear. We leveraged the AACR Project GENIE prostate cancer cohort to assess the prognostic impact of individual and concomitant gene alterations, focusing on key PC drivers (BRCA2, TP53, PTEN, RB1). METHODS: the study was conducted in two stages: (i) identification of candidate alterations at individual gene level through a systematic literature review, followed by analyzing the prevalence and co-occurrence of genes in the AACR Project GENIE Public Release (PR) dataset. (ii) Prognostic analysis of the pre-selected biomarkers in the AACR Project GENIE Biopharma Collaborative (BPC) cohort. Analyses were performed in three clinical settings (entire BPC cohort, n=1114; subgroup of patients with localized disease at diagnosis, n=837; and subgroup of patients with metastatic PC with a biopsy collected before or at the time of mPC, n=455) using two statistical approaches: univariate analysis (UA) and inverse probability weighting using propensity scores (PS). Cox models were applied to estimate overall survival hazard ratios (HRs). RESULTS: after integrating the findings from the systematic review with the analysis of the GENIE PR (n=5684), 107 individual genes and 122 co-occurring alterations were selected for study. In the GENIE BPC (n=1114 patients) 75% were M0 at diagnosis, and 67% presented metastatic PC at any time. Alteration prevalence was: TP53, 25%; PTEN, 15%; BRCA2, 4%; RB1, 4%; co-alterations included, PTEN-TP53 (6.4%), RB1-TP53 (2.1%), PTEN-RB1 (1.3%), and BRCA2-TP53 (1.2%). All four key genes showed a statistically significant prognostic impact in the entire cohort with UA (BRCA2, HR:1.9; TP53, HR:2.6; PTEN, HR:2.4; RB1, HR:4.1, all p&lt;0.001). Results were consistent in the subgroup analysis and when using PS. Additional genes such as FANCA, PIK3CA, and MYC were also associated with poor outcomes. Among co-alterations, BRCA2-TP53 (HR:2.0, p=0.05), RB1-TP53 (HR:3.6, p&lt;0.001), PTEN-TP53 (HR:2.4, p&lt;0.001); PTEN-RB1 (HR:5.5, p&lt;0.001), and PTEN-TP53-RB1 (HR:9.0, p&lt;0.001) were the strongest predictors of poor survival, with consistent effects across subgroups and analytical methods. Other combinations including MYC-TP53 (HR 2.2, p&lt;0.001) and PIK3CA-TP53 (HR 3.2, p&lt;0.001), also showed independent prognostic value. CONCLUSIONS: Genomic alterations in TP53, PTEN, RB1, and BRCA2, alone and in combination, independently associate with poor prognosis. Co-alteration patterns such as PTEN-TP53-RB1 define aggressive molecular subsets. This evidence supports integrating genomic interaction patterns for enhancing clinical risk models and guiding precision patient management. Furthermore, this study highlights the potential of AACR Project GENIE to enable data-driven development of biomarker-informed patient care strategies. Citation Format: Pablo Cresta Morgado, Victor Navarro, Guillermo Vilacampa, Haitham Alatoom, Manuel Ramos del Rio, Irbaz Riaz, Shawn Sweeney, Nikolaus Schultz, Ken Kehl, Gregory Riely, Wasim Abida, Katherine Panageas, Deborah Schrag, Philippe Bedard, Christine Micheel, Xindi Guo, Chelsea Nayan, Rodrigo Dientsmann, Joaquin Mateo. Genomic prognostic biomarkers in prostate cancer from the AACR GENIE cohort [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Innovations in Prostate Cancer Research and Treatment; 2026 Jan 20-22; Philadelphia PA. Philadelphia (PA): AACR; Cancer Res 2026;86(2_Suppl):Abstract nr A013.

Abstract Background Intracranial mesenchymal tumors, FET::CREB fusion-positive (ICMT), show fusions involving FET RNA-binding protein family genes (EWSR1 or FUS) and CREB family of transcription factors (ATF1, CREB1, or CREM). The methylation signature(s), gene expression characteristics, and clinical behavior of this important tumor type require further characterization. Methods We study the methylation profiles of 81 ICMT cases (61 newly profiled cases and 20 cases from publicly available sources). Clinicopathologic and genomic data were recorded for each case when available. Results ICMT showed a relatively distinct methylation signature compared to related tumors. Among the 65 cases where fusion types were documented, the identified fusions included EWSR1::ATF1 (25 cases), EWSR1::CREB1 (12 cases), EWSR1::CREM (21 cases), FUS::CREM (3 cases), and SMARCA2::CREM (4 cases). We confirmed the prior description of 2 distinct subgroups of ICMT (subclasses A and B). The majority of the cases belonged to subclass A (n = 69; 85%), which showed a higher median age compared to subclass B patients (26 years vs. 15 years). Subclass B cases (n = 12; 15%) showed shorter progression-free survival (P &lt; 0.01). Gene expression analysis of ICMT showed key overexpressed markers in ICMT, with significant CREM overexpression regardless of fusion type, when compared to either meningioma alone or a larger group of CNS tumors. Conclusions This work provides further characterization of ICMT as an important CNS mesenchymal neoplasm that is prone to tumor recurrence, showing 2 prognostically relevant methylation subclasses and warranting diagnostic distinction from other epigenetically and histologically related tumors. ICMTs show substantial overexpression of the CREM gene, independent of fusion type.

Abstract Aims Coronary angiography might contain clinically relevant information, beyond its traditional role in delineating coronary artery disease. We sought to explore the role of deep learning (DL) in detecting right ventricular dysfunction from routinely acquired cine images during coronary angiography. Methods and results 3D-convolutional neural networks (CNN) were trained to identify right ventricle (RV) dysfunction from diagnostic angiography of the right coronary artery (RCA). The model’s input was two cine angiograms from LAO and RAO projections. The model’s output was normal vs. abnormal RV function. Ground truth on RV function was obtained from the nearest transthoracic echocardiogram to the coronary angiogram. Two analyses were performed to identify (i) any RV dysfunction (≥mild) and (ii) significant RV dysfunction (≥mild–moderate). A total of 10 336 coronary angiograms from 9849 patients (mean age 66, 36% women) were included. The cohort was split into training (70%), validation (15%), and testing (15%) sets. In the testing sets, the models attained an area under the ROC curve (AUC), sensitivity, and specificity of 0.82 (95% CI: 0.80–0.84), 0.75, and 0.74, for detecting any RV dysfunction, and 0.83 (95% CI: 0.80–0.86), 0.82, and 0.70 for detecting significant (≥mild–moderate) RV dysfunction. Combining an ECG-driven AI model with the angio-driven model improved the AUC values to 0.83 and 0.87 for detecting any or advanced RV dysfunction, respectively. Conclusion A novel deep learning algorithm yielded acceptable classification accuracy in detecting RV dysfunction from routine cine angiography of the RCA. The model’s performance improved further by adding ECG to its inputs.