Citations

Summary Chimeric antigen receptor T cells directed against CD‐19 are highly effective therapies for various subtypes of B‐cell non‐Hodgkin lymphoma (NHL). We have studied the impact of patient‐specific lymphocyte growth kinetics after lymphoid depletion chemotherapy on both long‐term outcomes and toxicity in patients with diffuse large B‐cell non‐Hodgkin lymphoma (DLBCL). The growth of the lymphocyte populations early after chimeric antigen receptor T‐cell (CAR‐T) therapy is well described by an exponential function and the growth rate of the cells appears to be one of the most critical determinants of overall survival in these patients. The maximum lymphocyte peak and the area under curve for lymphocytes within the first 4 weeks after CAR‐T therapy had no impact on survival. Receiver operator characteristic analysis determined that a replication rate ≥0.3876/day is associated with superior rates of complete response and durable responses. This threshold is associated with higher grades of cytokine release syndrome and the need for tocilizumab. However, patients with this threshold have a median overall survival of 3.04 years compared to 1.035 years for patients with slower lymphocyte replication ( p = 0.0206). The major determinant of depth of response and durability of response to CAR‐T in NHL is the speed of lymphocyte expansion.

Abstract Real-time, proactive detection has become a necessity as health systems face converging pressures that legacy tools cannot solve: rising acuity, workforce strain, and persistent quality gaps that erode margins, capacity, and reputation. Clinical decision support has historically lagged because rudimentary rules-based systems drown clinicians in false alerts, eroding trust without reliably changing outcomes at the bedside. Bayesian Health’s real-time clinical intelligence platform was built to close this gap by continuously synthesizing multimodal EHR data (vitals, labs, medications, procedures, and longitudinal history) to learn patient-specific baselines and surface only the most actionable, high-precision signals to care teams. Across diverse health systems, this platform has been used to enable earlier recognition and intervention for a range of high-impact conditions, improving both bedside care and system performance. This talk will focus on concrete, real-world applications of the platform for sepsis, clinical deterioration, and palliative care needs, illustrating how earlier detection and workflow-integrated interventions drive measurable gains in clinical outcomes and margins, and why the value of early, precise detection is amplified in high-risk populations such as oncology patients, whose higher baseline acuity and treatment-related toxicities both elevate their risk of harm and make emerging deterioration harder to recognize. Case Study: Detecting Sepsis within a Oncology Patient Subpopulation. Background: Sepsis remains one of the leading causes of in-hospital mortality, and traditional rules-based alerts have struggled to deliver timely, actionable detection without overwhelming clinicians with false alarms. Oncology patients experience an elevated risk for sepsis and septic shock, and those who experience sepsis are more likely to suffer in-hospital mortality than non-cancer patients with sepsis. Early recognition of sepsis onset is challenging due to the overlap between signs of sepsis and inflammation and tumor- and treatment-related toxicities. We investigated the ability of Bayesian Health’s real-time artificial intelligence-based computational algorithm to perform timely detection of sepsis onset in hospitalized patients with cancer. This algorithm ingests data directly from the electronic health record, such as vital signs, laboratory results, medications, procedures, and patient-specific historical results, processing it in a continuous manner to flag presence of sepsis as early as possible. Methods: Analysis included 7480 adult emergency and inpatient encounters from three tertiary and quaternary academic centers (Cleveland Clinic Main Campus, Sinai Hospital of Baltimore, and Strong Memorial Hospital) and one community hospital (Cleveland Clinic Fairview Hospital) with sufficient data for inclusion (age ≥ 18, presence in an emergency or inpatient care unit, and at least one measurement of a panel of vital signs). Patients with cancer (including subgroups of solid tumor and hematologic malignancy) were identified by current or past recorded diagnoses (ICD-10 codes). All included patient records underwent a multi-tiered retrospective adjudication process. An automated screen labeled records with no evidence of infection or organ dysfunction as non-sepsis, removing them from need for manual review. Two independent physicians then adjudicated a sample of the eliminated records in addition to each remaining record for both presence of sepsis and time of onset, with a third physician reconciling disagreements. Evaluation of the algorithm included all discrete flags generated by the system during a period of time it was not in clinical use and not visible to care teams. Results: In the overall population, 3.1% of all patients and 6.0% of cancer patients were adjudicated to have had sepsis, including zero from a sample of 200 of the records marked as non-sepsis in automated screening. The detection algorithm identified sepsis with high and consistent accuracy across all patients and across cancer patients, including those with solid tumors and with hematologic malignancies (Table). A flag for sepsis occurred in 85.8% of all sepsis patients and 86.1% of cancer patients with sepsis within 4 days of sepsis onset. Sepsis was present in 24.2% of all cancer patients flagged (22.9% of solid tumor patients and 27.9% of hematologic malignancy patients). Compared to patients who were never flagged, all patients who were flagged, whether they had sepsis or not, were more likely to experience in-hospital mortality (7.9% vs 0.3%, p < 0.001) or ICU transfer (38.2% vs 7.9%, p < 0.001). This was also true within oncology patients (in-hospital mortality: 8.8% vs 0.4%, p < 0.001; ICU transfer: 34.7% vs 9.7%, p < 0.001). Implementation of an automated sepsis detection system with high accuracy in populations such as cancer patients, who have elevated risk of poor outcomes following sepsis, provides an opportunity to meaningfully improve timely delivery of care and reduce subsequent morbidity and mortality while minimizing alert fatigue for clinicians. Citation Format: Suchi Saria, Varesh Prasad, Nicasia Beebe-Wang, Ellie Zhang, Neri Cohen, David Graham, Conrad Gleber, James Morrison, Jacob Strand, Alexandra Tallman. Real-time multimodal AI enables individualized care in challenging subpopulations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(8_Suppl):Abstract nr PL03-03.

Abstract Background: Pyrimidine synthesis is a therapeutic vulnerability in cancer but inhibition results in toxicity to normal cells. Differential targeting of CTP synthase 1 (CTPS1), sparing the CTPS2 isoenzyme, is a therapeutic strategy in lymphoid cancers, supported by human genetic studies, that can potentially avoid toxicity; however, CTPS2 activity may compensate in epithelial tumours. Loss of CTPS2 protein expression characterises 25% of solid tumours and is predicted to expose a synthetic lethal vulnerability to CTPS1 inhibition. Dencatistat (STP938) is a first in class oral CTPS1 inhibitor showing >1,300-fold selectivity over CTPS2. In preclinical studies, CTPS2 expression was confirmed as a key modulator of response to CTPS1 inhibition, and dencatistat induced tumour regression in an in vivo model of CTPS2 negative ovarian cancer. Study design: The study comprises a standard 3+3 phase 1a dose escalation design, in which intra-patient dose escalation is encouraged, followed by a phase 1b safety expansion. The dose escalation study is recruiting participants with high grade advanced tumours who have exhausted standard of care therapy (excluding haematological cancers, salivary gland tumours and low grade tumours of any tissue). In addition, participants with high grade serous ovarian cancer whose tumours lack expression of CTPS2 (per central laboratory testing by immunohistochemistry) are eligible for backfill into cleared cohorts during dose escalation. The recommended phase 2 dose (RP2D) will be nominated based on safety, tolerability, target engagement and early signs of clinical efficacy. The phase 1b safety expansion study will recruit participants with CTPS2 negative ovarian, lung or endometrial cancer who will receive treatment at the RP2D. Standard inclusion criteria apply; patients with ECOG performance score >2 (>1 for phase 1a in France) or active/symptomatic CNS metastases are not eligible. The primary objectives of the study are to evaluate the safety and tolerability of single agent dencatistat and to determine the RP2D for further development. Secondary objectives comprise evaluation of pharmacokinetic properties and preliminary clinical activity. Exploratory endpoints include evaluation of target engagement, molecular features associated with response, and determination of drug metabolites. The study opened to enrolment in the UK, France and USA in September 2024 and is currently in dose escalation (NCT06297525). The phase 1b study is expected to commence mid-2026 and will include additional centres in Spain. Citation Format: Donna M. Graham, David Sommerhalder, Douglas Orr, Rowan Miller, Neeharika Makani, David O'Malley, Ira Winer, Philip A. Beer, Karen Smith, Maureen Higgins, John R. Hawse, Xiyin Wang, Saravut J. Weroha, Christophe Massard, Patricia Roxburgh. Lack of CTPS2 expression exposes synthetic lethal vulnerability to selective CTPS1 inhibition: A phase 1 dose escalation study of dencatistat (STP938) with safety expansion in biomarker selected cohorts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(8_Suppl):Abstract nr CT075.

Abstract The purpose of this study was to identify glioblastoma (GBM) proteins that contribute to the hijacking of the tumor microenvironment through extracellular vesicles (EVs). GBM is the most aggressive primary brain tumor in adults. It presents significant challenges due to its universal recurrence and limited survival rates, exacerbated when its located proximal to the lateral ventricles (LV). The cellular subpopulation of brain tumor-initiating cells (BTICs) plays a pivotal role in tumor initiation and invasiveness, interacting with the microenvironment, particularly the cellular components in the subventricular zone (SVZ) in the LV. We employed an integrated multi-omic strategy combining cell-specific proteomics of EV cargo and whole-cell transcriptomics of EV-treated neural progenitor cells (NPCs) to define mechanisms by which BTICs remodel the tumor microenvironment. Using the TurboID cell-specific protein labeling system, we identified a previously unrecognized repertoire of BTIC-derived proteins selectively packaged into EVs. Among these, DPYSL2 (CRMP2) emerged as a prominent EV cargo as it is implicated in cancer cell migration and invasion. Functionally, exposure of human NPCs to BTIC-derived EVs significantly increased NPC proliferation and migratory capacity in vitro, findings that were recapitulated in vivo following intracranial and intranasal delivery of GBM-derived EVs. To define the molecular basis of these phenotypic changes, we performed RNA sequencing of NPCs following EV treatment. Bioinformatic integration, including ontogenic and pathway enrichment analyses, revealed robust activation of oncogenic signaling pathways, notably JAK/STAT, mTOR, and WNT, accompanied by upregulation of downstream effector genes. Importantly, integrative proteomic-transcriptomic analyses identified DPYSL2 as a mechanistic link between EV cargo and NPC transcriptional reprogramming. Prior studies demonstrate that DPYSL2 can interact with JAK kinases, promoting STAT3 activation and transcription of genes such as Vimentin (VIM) and CALCA, consistent with the transcriptomic changes observed in EV-treated NPCs. Overall, we have identified DPYSL2 as a novel regulator of tumor microenvironment hijacking mediated by extracellular vesicles. This multi-omic approach is the first use of cell-specific proteomics to study extracellular vesicles and the first time pairing this method to identify upstream regulators of transcriptomic changes in neural progenitor cells. Collectively, these findings establish a direct molecular connection between BTIC-derived EV proteins and functional reprogramming of neural progenitor cells, providing mechanistic insight into how glioblastoma exploits developmental programs to promote tumor progression. Citation Format: Marissa Russo, Emily Norton, Weiwei Wang, Shreyartha Mukherjee, Daniel Wickland, TuKiet Lam, Hugo Guerrero-Cazares. DPYSL2 mediates extracellular vesicle-driven reprogramming of the glioblastoma tumor microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(8_Suppl):Abstract nr LB228.

INTRODUCTION: Immunoglobulin G4-related sclerosing cholangitis (IgG4-SC) and primary sclerosing cholangitis (PSC) are cholestatic disorders, which may be difficult to differentiate. Importantly, PSC is an untreatable progressive fibroinflammatory disease, whereas IgG4-SC responds to immunosuppression if recognized in a timely manner. This systematic review and meta-analysis aimed to identify and define the performance of clinical, biochemical, radiographic, and histologic features to differentiate between these 2 diseases. METHODS: A systematic search for comparative studies of IgG4-SC and PSC through November 2023 (with repeat evaluation for interval literature in December 2024) was performed and data extraction performed in duplicate. Pooled proportions, odds ratios, means, and standardized mean differences of pertinent diagnostic features were calculated using random-effects inverse-variance models. RESULTS: We identified 38 studies comparing patients with IgG4-SC and PSC. IgG4-SC patients were more likely to have pancreatic disease ( P < 0.001) but less likely to have inflammatory bowel disease ( P < 0.001) than those with PSC. Serum IgG4 was significantly higher in IgG4-SC ( P < 0.001), as anticipated. Radiographically, IgG4-SC demonstrated long distal strictures ( P = 0.02) and symmetric ductal thickening ( P < 0.001), whereas PSC showed a beaded appearance ( P = 0.038). With the exception of IgG4 staining, histologic features including periductal fibrosis were similar between these entities, although sample size was limited for these features. DISCUSSION: Our meta-analysis shows that IgG4-SC and PSC present with similar clinical and radiographic features and possibly comparable histology. A history of unusual pancreatitis and elevated IgG4 (serum or tissue) prompts assessment for more specific radiographic features which if present warrant a therapeutic treatment trial.

Diagnosing rare genetic diseases remains a major challenge despite widespread clinical testing. Long-read RNA sequencing (RNA-seq) offers a powerful approach to capturing the effects of genetic variants on the transcriptome, yet challenges with sequencing coverage, cost, tissue selection, and scalability have limited its clinical adoption. To address this, we developed STRIPE (Sequencing Targeted RNAs Identifies Pathogenic Events), a targeted long-read RNA-seq–based strategy for rare disease diagnosis and variant interpretation. STRIPE enables deep sequencing of full-length transcripts for any customized disease-specific gene panel such that a wide range of clinically informative readouts, including transcript aberrations and sequence variants, can be detected at haplotype-level resolution. Applying STRIPE to 88 individuals spanning two major rare disease groups, we accurately reidentified known pathogenic variants and revealed their transcript consequences, including many unexpected ones. For 8 of 15 splice site region variants, we observed more complex RNA processing defects beyond single exon skipping or cryptic splice site activation. Notably, we find that donor splice site variants frequently activate cryptic intronic polyadenylation sites, leading to premature transcript termination. Leveraging unique strengths of long-read RNA-seq, STRIPE also resolved variants of uncertain significance and uncovered disease-causing variants in five previously undiagnosed individuals. Overall, STRIPE is a powerful, adaptable, and scalable strategy with broad potential to improve clinical variant interpretation and advance genetic diagnosis of rare diseases.

ABSTRACT Background Visceral myopathy (VSCM) is an ultra‐rare life‐threatening condition characterized by severe impairment of gastrointestinal (GI), genitourinary, and uterine smooth muscle. This disorder represents a significant clinical challenge due to variable presentation and the lack of standardized diagnostic and therapeutic protocols. Methods To discuss advances in the field, scientists and clinicians with a special interest in VSCM met in Arenzano, Genova, Italy in October 2024 for the second International Forum on Visceral Myopathy 2024 (IFVM2024) ( https://ifvm2024.ge.ibf.cnr.it/ ). Key Results As in the previous edition of the event ( https://poic‐e‐dintorni.org/efvm‐2022/ ), attendees included clinicians and researchers from around the world who study this disease, representatives from support organizations, patients affected by VSCM and their families, and companies that co‐funded the event. The present manuscript aims to summarize knowledge shared during the IFVM2024 conference, thus providing an updated state‐of‐the‐art summary of VSCM biology and disease management. Conclusions Here, we pay particular attention to the epidemiology of the disease, histopathology, genetics, novel treatments, advances in molecular and cell biology, experimental models, and the lived experiences and impact of this disorder on families.

Abstract In both type 1 and type 2 diabetes (T1D and T2D), insulin-producing β cells undergo progressive dysfunction due to inflammation, leading to impaired glucose responsiveness, dedifferentiation, and cell loss. While bile acid (BA) dysregulation under diabetic conditions is known to influence metabolic and inflammatory pathways, its mechanistic role in β cell regulation remains incompletely defined 1–3 . Here we show that bile acid sensor Farnesoid X receptor (FXR) and Bromodomain and Extra-Terminal motif (BET) signaling cooperatively regulates β cell inflammatory response and β cell identity. We identified the physiological protein-protein interaction between FXR and the bromodomain-containing protein 4 (BRD4) as a regulatory axis that protects against β cell dysfunction. We show that FXR activation by Fexaramine (Fex) together with BRD4 inhibition by JQ1 synergistically suppressed IL-1β-induced inflammation while also improving β cell identity and insulin secretion in both db/db model and high-fat diet (HFD) plus multi low-dose streptozotocin (MLD-STZ) model of diabetes. Importantly, this cooperative effect is abolished in β cell–specific FXR knockout (βFXRKO) mice, establishing that FXR is required for the functional synergy between these pathways in vivo . Mechanistically, structure-guided modeling and mutational analyses identified a direct interaction between FXR and the BD2 domain of BRD4, depending on specific lysine acetylation sites. Additionally, inhibition of the BD2 domain of BET combined with FXR activation markedly improved β cell survival in human T1D and T2D models established from human pluripotent stem cell (hPSC)-derived islet-like organoids (HILOs). Collectively, these findings establish a BA–bromodomain axis as a transcriptional interface linking metabolic signaling and chromatin regulation, and highlight FXR–BET targeting as a promising strategy to counter progressive β cell failure in diabetes.

Abstract A short diagnosis-to-treatment interval independently predicts inferior outcomes in follicular lymphoma. Using international discovery and validation cohorts, we demonstrate its prognostic value beyond established prognostic indices, with implications for risk stratification, clinical trial design, and interpretation.