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TPS5632 Background: Concurrent chemoradiation therapy (CCRT) is the standard of care for locally advanced cervical cancer (LACC); however, outcomes remain suboptimal in patients with high-risk disease. Recent studies suggest that integration of immunotherapy (IO) with definitive chemoradiation, or induction chemotherapy prior to CCRT improves outcomes. Whether treatment intensification with induction systemic therapy and IO prior to CCRT and IO further improves disease control remains unknown. Induction chemotherapy may reduce tumor burden, eradicate micrometastatic disease, and improve tumor immunogenicity prior to definitive CCRT. Preclinical and clinical data support synergy between systemic therapy or radiotherapy and immune checkpoint blockade, providing the rationale for evaluating an induction strategy incorporating chemotherapy and immunotherapy before standard CCRT with immunotherapy, followed by maintenance immunotherapy. Optional tumor tissue and blood samples will be collected for exploratory correlative analyses, including immune and molecular biomarkers associated with response, resistance, and patterns of failure. Methods: NRG-GY037 is a prospective, multi-institutional phase III randomized trial conducted through NRG Oncology. A total of 336 patients will be enrolled (168 per arm). Patients will be stratified by FIGO stage (III vs. IVA) and presence or absence of para-aortic lymph nodes (N2). The primary endpoint is progression free survival (PFS). The study has 90% power to detect PFS hazard ratio of 0.65 in the experimental arm. Treatment: Patients with previously untreated, high-risk LACC are randomized to receive either induction chemotherapy with pembrolizumab for 6 weeks followed by CCRT with pembrolizumab and pembrolizumab maintenance, or standard CCRT with pembrolizumab followed by pembrolizumab maintenance. Major Eligibility Criteria: Eligible patients have histologically confirmed cervical carcinoma (squamous, adenocarcinoma, or adenosquamous), TNM T3 and T4 disease, N0-2, ECOG performance status 0–1, and no prior definitive therapy for cervical cancer. Current Enrollment Status: The trial is actively accruing patients. No efficacy or safety data are available at the time of submission. Clinical Trial Registration: ClinicalTrials.gov identifier: NCT07061977. Clinical trial information: NCT07061977 .

Introduction To assess the within-class variation in kidney outcomes following initiation of sulfonylurea therapy. Research design and methods We used claims data of enrollees in commercial, Medicare Advantage, and traditional Medicare health plans between 2014 and 2021 to emulate a target trial including adults ≥21 years with type 2 diabetes at moderate cardiovascular risk to compare initiation of glimepiride, glipizide, or glyburide on the incidence of chronic kidney disease (CKD) stage 3 or worse, including initiation of kidney replacement therapy (primary outcome); secondary outcomes examined incident CKD stages 3-4, kidney failure (including kidney replacement therapy), all-cause mortality, and hypoglycemia requiring emergency department or hospital care. Random treatment assignment was emulated using propensity scores, estimated using the super learner ensemble method, and incorporated as inverse probability of treatment weights into proportional hazards models. Results The weighted study cohort included 295 092 individuals starting glimepiride (n=134 926), glipizide (n=145 984), and glyburide (n=14 182). One year after treatment initiation, stage 3 or worse CKD developed in 2.1% of patients in the glimepiride group, 2.2% in the glipizide group, and 1.8% in the glyburide group. Glyburide was associated with a lower risk of kidney complications compared with both glimepiride (HR 0.84, 95% CI 0.76 to 0.92) and glipizide (HR 0.81, 95% CI 0.73 to 0.89), despite a higher risk of severe hypoglycemia (HR 1.47, 95% CI 1.27 to 1.71 vs glipizide and HR 1.22, 95% CI 1.05 to 1.42 vs glimepiride). In contrast, the risk of kidney complications was modestly increased with glipizide compared with glimepiride use (HR 1.04, 95% CI 1.00 to 1.07). Conclusions Glyburide was associated with a modestly lower risk of kidney complications, despite a higher risk of hypoglycemia, while glipizide was associated with a higher risk of kidney complications. These hypothesis-generating findings suggest important within-class differences that warrant consideration in clinical decision-making and future research. Despite rigorous prespecified causal inference analytic methods, the risk of unmeasured confounding and bias by indication with the use of observational data remains. Trial registration number NCT05214573 .

Background Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer (BC) and lacks effective treatment options. Polyphyllin B (PB), a saponin extracted from Paris formosana Hayata, has shown potential in cancer therapy. However, its anti-TNBC effects and mechanisms are not well studied. This study investigated the effects and underlying mechanisms of PB in TNBC. Methods CCK8 assay, Wound healing assay, Transwell migration experiments, and clonogenic assay were performed to assess the effects of PB in three TNBC cells lines. Iron level, lipid ROS, and MDA levels were assessed as ferroptosis markers. Mechanistic studies were conducted using molecular docking, Western blot, immunofluorescence, RT-qPCR, Nrf2 overexpression assays and establishment of a TNBC mouse model. Results PB treatment resulted in significant cell death and inhibited the migration of TNBC cells. Accumulation of iron and MDA suggested that PB induces ferroptosis. In vitro and in vivo , PB downregulated the expression of nuclear factor E2-related factor 2 (NRF2) and sequestosome-1 (P62) and upregulated the expression of Kelch-like ECH-associated protein 1 (KEAP1). Furthermore, it modulated the expression of key ferroptosis regulators, including acyl-CoA synthetase long-chain family member 4 (ACSL4) and glutathione peroxidase 4 (GPX4). In a TNBC mouse model, PB suppressed tumor growth and increased malondialdehyde accumulation. Conclusion PB inhibits cell proliferation and migration and induces ferroptosis in TNBC through the inactivation of NRF2. PB is a promising candidate for TNBC treatment that warrants further investigation.

Abstract Rationale Propofol-based sedation in the intensive care unit (ICU) is associated with clinically significant hemodynamic instability, including hypotension. Previous studies have identified hypotension as a key predictor of adverse outcomes in critically ill patients. However, no validated tools currently exist to systematically predict this risk. Therefore, this study aimed to develop and externally validate machine-learning (ML) models for predicting the risk of hypotension in ICU patients receiving propofol sedation. Methods We developed ML models using retrospective data from adult, mechanically ventilated ICU patients who received propofol infusion for at least 24 hours across four Mayo Clinic sites between 2018 and 2024. The primary outcome was hypotension, defined as ≥ 2 consecutive MAP readings ≤60 mmHg within 15 minutes during the first 6 hours of propofol sedation. The MIMIC-IV dataset was used for external validation. Features were selected using a union of Boruta and LASSO-penalised logistic regression. Four algorithms (elastic net-penalised logistic regression, random forest, LightGBM, and multilayer perceptron) were tuned using Bayesian optimization to minimize cross-entropy loss during leave-one-site-out cross-validation (LOSO-CV). The algorithm with the lowest cross-entropy loss during LOSO-CV was chosen as the best-performing algorithm. Classification thresholds were selected to target sensitivity ≥80%. Model performance was evaluated using area under the receiver operating characteristic curve (AUC-ROC), calibration slope and intercept, sensitivity, and specificity. Feature importance was evaluated using SHapley Additive exPlanations (SHAP). Results The development cohort included 16,361 patients from Mayo Clinic, of whom 3,482 (21.3%) developed hypotension. The external validation cohort comprised 4,684 patients from MIMIC-IV, with 115 (2.5%) experiencing hypotension. Patient characteristics included age, admission Sequential Organ Failure Assessment (SOFA) scores, starting propofol dose, ICU admission source, and comorbidities. The best-performing algorithm was LightGBM. The average AUC-ROC during LOSO-CV was 0.70 (95% confidence interval [CI] 0.68-0.71), versus 0.64 during external validation. The average calibration slope and intercept during LOSO-CV was 1.08 (95% CI 0.89-1.27) and 0.08 (95% CI -0.25-0.41), respectively, versus 0.78 and -2.07 during external validation. The average sensitivity and specificity during LOSO-CV was 0.81 (95% CI 0.79-0.83) and 0.47 (95% CI 0.42-0.52), respectively, versus 0.54 and 0.65 during external validation. Conclusions We developed and externally validated an ML-based classifier that demonstrates moderate discrimination for predicting propofol-induced hypotension in mechanically ventilated ICU patients. This tool may facilitate early identification of high-risk patients and enable proactive hemodynamic management strategies. Further prospective validation and assessment of clinical impact are warranted. This abstract is funded by: None

Abstract Rationale Propofol sedation in mechanically ventilated patients often causes clinically significant hypotension. While we concurrently developed and validated a machine-learning (ML) classifier to predict hypotension risk, accurately estimating the timing of hemodynamic deterioration could enable more precise, proactive interventions. This study aimed to develop and externally validate ML models that predict not only whether hypotension will occur, but also when it is likely to develop after propofol initiation. Methods ML models were developed using retrospective data from adult, mechanically ventilated ICU patients who received propofol infusion for ≥24 hours across four Mayo Clinic sites from 2018 to 2024 and developed hypotension (≥2 consecutive MAP readings ≤60 mmHg within 15 minutes) during the first 6 hours of sedation. The MIMIC-IV dataset was used for external validation. Features were selected using a union of Boruta and LASSO-penalised quantile regression. Two quantile algorithms (LASSO-penalised quantile regression and LightGBM) were trialed to predict the conditional median and interquartile range (IQR) of time to hypotension. In addition, two probabilistic algorithms (NGBoost and Mixture Density Network) were trialed to predict the full conditional distribution. The quantile models were tuned via Bayesian optimisation to minimise pinball loss during leave-one-site-out cross-validation (LOSO-CV), whereas probabilistic models were tuned to minimise the Continuous Ranked Probability Score. The algorithm with the lowest average pinball loss was deemed the best-performing algorithm. Model performance was evaluated using median absolute error (MAE), IQR coverage, and IQR width. Feature importance was evaluated using SHapley Additive exPlanations (SHAP). Results We included 3482 patients from the Mayo Clinic for model development, with 115 patients from the MIMIC-IV dataset used for external validation. Patient characteristics in the modeling dataset included age, sex, admission SOFA scores, weight, ICU admission source, and initial propofol dose. The best-performing algorithm was LightGBM-based quantile regression. The average MAE during LOSO-CV was 4.11 hours (95% confidence interval [CI] 3.98-4.23), versus 4.83 hours during external validation. The average IQR coverage and width during LOSO-CV was 0.49 (95% CI 0.48-0.49) and 7.12 (6.89-7.35), respectively, versus 0.07 and 6.51 during external validation. Conclusions We developed and externally validated a quantile regression model that predicts both the timing and uncertainty of propofol-induced hypotension in mechanically ventilated ICU patients. This model provides clinicians with actionable time estimates that may facilitate preemptive hemodynamic interventions and optimize sedation management. Prospective validation, expanded predictors and clinical impact assessment are warranted. This abstract is funded by: None

Abstract Rationale Lung-protective ventilation protocols use predicted body weight (PBW) to set tidal volumes. However, biases exist in these formulas, with overestimation of lung capacity in older, shorter, female, and non-White patients—groups that experience higher mortality rates during invasive mechanical ventilation (IMV). This study investigated associations between pre-admission forced vital capacity (FVC), driving pressure, and patient outcomes. Methods This multicenter retrospective study included adults (18-95 years old) with pre-admission spirometry who required IMV between 01/01/2016 and 05/31/2025 across the Mayo Clinic, spanning 11 ICUs within 5 hospitals in 4 states. Patients were stratified by FVC/PBW ratio quartiles. The primary outcome was 28-day mortality. Trends were assessed using linear or logistic regression, with FVC/PBW as a continuous variable. Mediation analysis examined pathways between FVC/PBW and mortality, with driving pressure (cm H2O, standardized) as the mediator, and adjusted for covariates including age, sex, SOFA score, and BMI. Absolute risk differences and number needed to harm (NNH) were estimated for key thresholds (e.g. FVC/PBW ≥45 mL/kg, PFTs within 2 years). Results Among 4,839 patients (38.7% female, mean (±SD) age 64.5±13.5 years), FVC/PBW ratio demonstrated substantial individual variation, with a mean of 48.3 ± 13.4 mL/kg. There was systematic variation by demographics (Figure): females had significantly lower ratios than males (45.4 versus 50.2 mL/kg, P < 0.001), and ratios were lower with older age from 52.5 mL/kg in patients <65 to 43.2 mL/kg in those ≥85 years (P < 0.001 for trend). Patients in the lowest FVC/PBW quartile had higher 28-day mortality compared to the highest quartile (26.0% versus 17.0%, P < 0.001) and higher driving pressures (14.0 versus 10.0 cm H2O, P < 0.001; Figure). In mediation analysis (n = 4,147), driving pressure mediated the relationship between FVC and mortality. Each 1-SD increase in FVC/PBW was associated with 0.364-SD lower driving pressure (P < 0.001) and 2.4% lower mortality. The adjusted indirect effect through driving pressure was significant (ACME -0.024, 95% CI: -0.029 to -0.019), accounting for the mortality effect. Sensitivity analyses across binary thresholds, age quartiles, outlier exclusion, and obstructive pathology confirmed robust mediation. Patients with FVC/PBW <45 mL/kg (N = 1,644; 39.6%) had 28-day mortality of 17.8% versus 13.5% for ≥45 mL/kg (risk difference 4.3%, 95% CI 1.8-6.8%; NNH: 23 patients). Conclusions Pre-admission lung function was strongly associated with mortality in adults receiving IMV through driving pressure-mediated pathways. Driving pressure is a modifiable target, especially in patients with smaller lung capacities at highest risk for ventilator-induced lung injury. Further prospective investigation is needed to confirm these findings. This abstract is funded by: National Heart, Lung, and Blood Institute (NHLBI) of the National Institute of Health (NIH) Grant Number K23HL151671

Background SGLT2 (sodium‐glucose cotransporter 2) inhibitors reduce major adverse cardiovascular events (MACE) in type 2 diabetes. However, no direct comparison of individual SGLT2 inhibitor drugs has been conducted, particularly among adults with moderate cardiovascular risk who comprise most people with type 2 diabetes. Methods We used data for commercial, Medicare Advantage, and Medicare fee‐for‐service beneficiaries to emulate a target trial of adults (≥21 years) with type 2 diabetes and moderate cardiovascular risk who started canagliflozin, dapagliflozin, or empagliflozin between 2015 and 2020. We estimated propensity scores using the super learner ensemble method and incorporated them as inverse probability of treatment weights into Cox models, estimating risk of MACE, expanded MACE, and hyperglycemic and hypoglycemic crises through December 31, 2022. Results The weighted cohort, balanced on all baseline covariates, included 137 232 patients (mean age 65.7 years [SD, 8.1], 75.3% non‐Hispanic White, 57.0% male, 81.9% on metformin, 11.4% on glucagon‐like peptide‐1 receptor agonists) starting canagliflozin (N=42 877), dapagliflozin (N=17 871), or empagliflozin (N=7648). The risk of MACE was lower among patients starting empagliflozin versus canagliflozin (hazard ratio [HR], 0.92 [95% CI, 0.87–0.97]), driven by reduced risk of all‐cause mortality (HR, 0.86 [95% CI, 0.80–0.94]). There was no difference in MACE between empagliflozin versus dapagliflozin or dapagliflozin versus canagliflozin therapy. There was no difference in remaining outcomes between the three drugs. Conclusions The 3 most used SGLT2 inhibitor medications demonstrate similar effectiveness on cardiovascular outcomes among patients with type 2 diabetes at moderate cardiovascular risk, with differences between these drugs small in magnitude. Clinicians and health systems should prioritize enhancing access to these cardioprotective therapies.

Common sex chromosome aneuploidies (SCAs) often present with cognitive and cardiovascular dysfunction in humans. To address SCA effects on gene expression and DNA methylation in relevant cell types, we differentiated neural precursor cells (NPCs) and cardiomyocytes (CMs) from human induced pluripotent stem cells (hiPSCs) with different numbers of sex chromosomes, including isogenic and independent lines. As expected, the expression of genes that escape X inactivation (escapees) mostly increases with the number of inactive X chromosomes (Xi). However, allelic analysis shows dampening of escapees specifically on the Xi in XXY compared to XX in both NPCs and CMs, revealing a novel type of dosage compensation in SCA. In contrast, Y-linked gene expression is higher in XXY versus XY NPCs, but the opposite is observed in CMs. This may explain the greater number of differentially expressed autosomal genes in NPCs versus CMs with an added Y chromosome, while effects of added X chromosomes are similar between cell types. Concordantly, changes in autosomal DNA methylation are mainly driven by the presence of a Y chromosome. These findings highlight the cell-type specificity of sex-linked and autosomal gene regulation in SCA conditions.

Introduction Angina with no obstructive coronary artery disease (ANOCA) affects millions and is frequently under-recognised because diagnostic pathways and risk tools predominantly target obstructive coronary artery disease (CAD). This protocol describes shared methods for two machine-learning (ML) studies: (1) differentiating ANOCA from stable angina with obstructive CAD and (2) predicting long-term mortality among patients with ANOCA and obstructive CAD. Methods and analysis We will develop and cross-site validate ML classification models using a multicentre retrospective cohort drawn from the Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease registry and institutional datasets from the University of Ottawa Heart Institute and the University Health Network. Eligible participants are adults (≥18 years) undergoing initial cardiac catheterisation for chest pain/anginal equivalents since 1995, excluding prior revascularisation, major structural heart disease and predefined non-anginal indications. Outcomes are (1) ANOCA (0% to <50% stenosis) versus obstructive CAD (≥50% stenosis) and (2) 1, 3 and 5-year mortality, modelled separately for ANOCA and obstructive CAD. Model development will use nested cross-validation with stratified k-fold inner-loop tuning and leave-one-site-out cross-validation for repeated external validation. Candidate predictors will be harmonised across sites, filtered for missingness and refined using expert/directed acyclic graph-guided selection plus Boruta and Least Absolute Shrinkage and Selection Operator. Preprocessing includes appropriate encoding, missing-data imputation (multivariate imputation by chained equations) and feature scaling. Algorithms will include elastic-net logistic regression, random forest, LightGBM and multilayer perceptron models; hyperparameters will be optimised via Bayesian optimisation. Performance and threshold tuning will be reported. Explainability and subgroup fairness will be assessed using SHapley Additive exPlanations. Final models will be deployed as a web-based clinical risk calculator. Ethics and dissemination Ethics approval has been obtained from the University of Calgary and the University Health Network (#24-5916). Analyses will use deidentified data in secure environments; only aggregate results will be reported. Findings will be disseminated via peer-reviewed publications, conferences and a web-based calculator.

Abstract Background: Deletions in MTAP occur in 10-15% of cancers and are associated with poor prognosis. MTAP deletion (MTAPdel) leads to accumulation of MTA which causes partial inhibition of PRMT5, creating a synthetic lethality approach with PRMT5 inhibitors. Multiple investigational MTA-cooperative PRMT5 inhibitors have demonstrated early clinical efficacy in MTAPdel NSCLC and other cancers. MTAPdel, PRMT5 expression, and clinical outcomes to standard of care immune checkpoint inhibitors (ICI) and chemotherapy (chemo) have not been well characterized. Methods: The Tempus Lens Platform (Tempus AI, Inc., Chicago, IL) was used to query the Tempus multimodal de-identified database and establish and subsequently analyze a cohort of patients (pts)with NSCLC and DNA (Tempus xT) and RNA (Tempus xR) testing, treated with front-line (1L) ICI with or without chemo (N=3,676). PRMT5 expression was normalized as transcripts per million (TPM) and reported as log2(TPM + 1). Pts were classified into high vs low groups based on median PRMT5 expression and into MTAPdel vs intact (MTAPwt) based on MTAP biallelic loss. Immune infiltration was estimated using Quantiseq. Real-world overall survival (rwOS) was defined as the time from 1L start to death or last known follow-up. Real-world progression-free survival (rwPFS) was defined as the time from 1L start to death, progression or last known follow-up. Hazard ratios (HR) were calculated using Cox proportional hazards models and adjusted for age, sex, histology, smoking status and PDL1 status. Results: PRMT5 expression was moderately increased in pts with MTAPdel (6.65 v 6.70, p=0.012). Alterations in MYC, SMARCA4 and KEAP1 were enriched in PRMT5-high tumors in both MTAPdel and MTAPwt pts (p&lt;0.03). Pts with PRMT5-high tumors had decreased infiltrate of multiple immune cells, including B cells, macrophages (M1 and M2), NK cells, CD4 and CD8 T cells (p&lt;0.001). Pts with MTAPdel/PRMT5-high expression had shorter rwOS compared to MTAPwt/PRMT5-low when treated with ICI alone (HR 1.58, 95% CI 1.11-2.24, p=0.011) or with ICI + chemo (HR 1.65, 95% CI 1.34-2.03, p&lt;0.001). These associations persisted on multivariate analysis. Pts with MTAPdel/PRMT5-high expression were also associated with worse rwPFS when treated with ICI + chemo (HR 1.5, 95% CI 1.22-1.86, p&lt;0.001) on univariate and multivariate analysis, but did not associate with rwPFS in pts treated with ICI alone (HR=0.97, 95% CI 0.66-1.42, p=0.9). Conclusion: PRMT5 expression defines an immune suppressed subpopulation of pts with NSCLC. Pts with elevated PRMT5 expression and MTAPdel have poor outcomes with ICI+/- chemo, indicating PRMT5 RNA expression levels can be used to inform clinical trial designs, particularly those that are testing novel combinatorial strategies. Citation Format: Natalie Vokes, Stamatina Fragkogianni, Pooja A. Shah, Santiago G. Trevino, Konstantinos Leventakos, Lei Deng, Matthew Lee, Tali Azenkot, KAYLA LAYNG, JACOB MERCER, Jyoti Patel, Jordi Rodon Ahnert. High PRMT5 expression is associated with decreased immune infiltrate and worse outcomes to immune checkpoint inhibitors in non-small cell lung 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 2446.