Citations

Objectives Long-term symptoms following infection with acute respiratory syndrome coronavirus-2 (SARS-CoV-2), termed post-acute sequelae of SARS-CoV-2 infection (PASC) or Long COVID (LC), persist beyond 90 days and may impact at least 10% of patients with acute infection. The exact cause of LC remains unknown, but several theories include persistent viral particles, immune dysfunction, and autonomic nervous system (ANS) imbalance, particularly involving the vagus nerve. Given the role of the vagus nerve in inflammation regulation, vagal nerve stimulation (VNS) is being explored as a treatment option. The present study aimed to evaluate the feasibility, safety, and exploratory effects of a handheld external transcutaneous cervical non-invasive VNS (tcVNS) on the primary endpoint of Post-COVID Functional Status (PCFS) grade, alongside secondary outcomes such as LC-related fatigue and other symptoms. Methods Participants from our Post COVID Care Clinic were randomized into treatment (tcVNS treatments two minutes, three times a day) and control (no VNS) groups for a study period of 12 weeks. Participants completed validated questionnaires, PET-CT scans, and inflammatory cytokines at baseline and 12 weeks. Results All randomized patients (8 tcVNS, 10 control) completed the 12-week study. Participants randomized to tcVNS were observed to have improvements in PHQ-9, PROMIS-F, and COMPASS-31 when compared to controls, but these differences were not statistically significant. Cortisol and DHEA were also observed to increase less in the tcVNS group when compared to the control group, but these changes were also not statistically significant. Conclusions tcVNS was well tolerated and may be a promising therapeutic approach for LC, a chronic disease with no approved treatments and very low rates of complete recovery.

Abstract Background Breast cancer is etiologically heterogeneous, but which risk factors differ in their associations across tumor subtypes remains unclear. We conducted a large, pooled analysis to evaluate independent, dose-response associations between breast cancer risk factors and quantitative tumor features. Methods Analyses of 15,731 invasive breast cancers from 24 studies evaluated associations (p-trend) between reproductive and hormonal factors, body mass index (BMI), alcohol, smoking, and family history in relation to quantitative immunohistochemistry measures on tissue microarrays (ER, PR, HER2, KI67, TP53) and tumor grade. Analyses in a subset of 10 population-based studies estimated subtype-specific odds ratios (ORs) comparing cases to controls. A Bayesian False Discovery Probability (BFDP) <0.2 was used to identify associations with strong statistical evidence. Results Nulliparity and later age at menopause were associated with higher ER-positivity (p-trend=0.021 and 0.001, respectively), with corresponding OR[ER+] (95% CI) = 1.49 (1.16-1.90) for nulliparous vs. parous and 1.07 (1.03-1.11) per 5 years. Current combined menopausal hormone therapy (MHT) use was associated with lower grade (p-trend<0.001), with OR [grade1] = 3.37 (2.69-4.21) for current vs. never users. Higher BMI was associated with lower ER-positivity and higher grade in premenopausal women (p-trend<0.001 and <0.001), with OR[ER+] = 0.80 (0.74-0.87) and OR[grade1] = 0.75 (0.63-0.88) per 5 units, and with higher PR-positivity and higher grade in postmenopausal women (p-trend<0.001 and <0.001), with OR[PR+] = 1.08 (1.03-1.14) and OR[grade 3] = 1.10 (1.04-1.17) per 5 units. Conclusion This pooled analysis of 15,731 cases showed that nulliparity, age at menopause, MHT, and BMI have independent, dose-response associations with ER, PR, and grade, clarifying patterns of etiologic heterogeneity. Associations with HER2, KI67 and TP53, or other risk factors did not meet our threshold for strong evidence.

Abstract Polygenic risk scores (PRSs), which quantify inherited susceptibility to complex traits and diseases, have emerged as valuable tools for risk stratification and precision medicine. Despite their promise, PRS developed on European cohorts often demonstrate substantially reduced predictive accuracy in non-European populations, due to differences in genetic architecture. The disproportionate representation of European ancestry cohorts in genome-wide association studies (GWAS) leads to inequitable deployment of PRS technologies across diverse populations. Here, we introduce PRANA (Polygenic Risk Adaptation via Neural-network Architecture), a deep learning framework that adapts an existing PRS developed on one population to other ancestries. Unlike methods that require large-scale GWAS in the target population, PRANA leverages pre-trained PRS models derived from European cohorts and adapts them using modestly sized cohorts from the target population. We evaluated PRANA on seven complex traits in South Asian, East Asian and Ashkenazi Jewish populations, as well as in selected smaller East Asian subpopulations where the scarcity of training data poses a particular challenge. PRANA mostly improved predictive performance of the baseline PRS models by 5%-20% in terms of effect size (β) and Nagelkerke’s R², and, in most cases, outperformed existing cross-ancestry multi-PRS approaches. These results highlight PRANA as a scalable and practical strategy to reduce disparities in genomic risk prediction and advance the equitable application of PRS in diverse populations.

ABSTRACT Ciltacabtagene autoleucel (cilta‐cel) has demonstrated excellent efficacy and long‐term disease control in patients with relapsed/refractory multiple myeloma (RRMM). However, a proportion of patients experience early treatment failures. We investigated clinical factors associated with early progression or death (within 12 months) in patients with RRMM receiving standard‐of‐care cilta‐cel across the three Mayo clinic centers. Patients with a follow‐up of at least 12 months or progression or death within 12 months from infusion were included. Of the patients with early treatment failure ( n = 52), 69% had progressive disease and 31% had a non‐relapse mortality (NRM) event. In patients without early treatment failure ( n = 164), 13% of events were NRM. Among pretreatment factors, prior BCMA‐directed therapy, presence of extramedullary disease and a CAR‐HEMATOTOX score of ≥ 2 were independent predictors of early progression or death. The utilization of cilta‐cel in earlier lines of treatment (1–3 vs. 4 or more) demonstrated comparable PFS (12‐month PFS 73% vs. 77%, p = 0.94). Measurable residual disease positivity in the bone marrow at 3 months (11/197 patients) identified a small but high‐risk group with an increased risk of early treatment failure (OR 5.68; p = 0.012). Patients with less than a complete response on a FDG PET/CT at 3 months also had an increased risk of early treatment failure (OR 11.8; p < 0.0001). Our findings may help identify patients at high‐risk for early adverse outcomes despite receiving highly effective therapy, and support consideration of novel therapeutic strategies within a clinical trial setting.

Abstract Background New-onset atrial fibrillation (AF) is common in patients who are hospitalized with acute illness and is associated with overall poor outcomes. Current clinical and demographic predictors of new-onset AF have limitations. Electrocardiogram (ECG) waveforms, combined with these factors as part of multimodal approach could help improve prediction of new-onset AF. Purpose The purpose of our study was to develop a multimodal, deep-learning system that combines ECG waveforms with clinical data for prediction of new-onset AF in hospitalized patients. Methods We developed and compared two separate 1-dimensional models with a fusion model for prediction of new-onset AF. (a): one-dimensional convolutional neural network (1D-CNN) that learns patterns from the raw ECG waveforms. (b): a Multi-Layer Perceptron (MLP), unsupervised machine learning model which utilizes data from structured variables such as: age, heart rate, routinely obtained laboratory data and medications. The two modules each produce latent feature vectors, which are then placed end-to-end and fed into a final Multi- MLP head that outputs the probability of New-onset AF during hospitalization. We then compared this fused MLP model with the two simpler unimodal models based solely on ECG waveforms and clinical data respectively. Results On the held-out test set data, the feature-level fused model achieved an Area Under the Curve (AUC) of 0.81. This significantly outperformed both the ECG-alone model (0.77) and the clinical-alone model (0.74). By adjusting the threshold, we can fine-tune the tool at a threshold of 0.5, it flags 83% of patients who later develop AF (207 of 248) with a precision of 10%, a setting that could be useful for wider screening. By adjusting the threshold of 0.98 for a high-precision alert configuration, it has the ability to predict 46% of future occurrence of AF cases (113 of 248) while reducing false alarms by 81% (from 1,797 to 328), increasing precision to 26% and achieving an overall accuracy of 89%, a setting useful when resources for follow-up are limited. Conclusions Combining ECG signals with clinical data significantly enhances the model’s ability to detect new-onset AF in hospitalized patients as compared to a uni-dimensional CNN model. The dynamic nature of ML model also allows for adjustment of its decision threshold which can aid in broader screening and improving adverse outcomes related to occurrence of AF.ROC Curve for Fusion model

The adult chronic pancreatitis (CP) working group, formed at the inception of the Consortium for the Study of Chronic Pancreatitis, Diabetes, and Pancreatic Cancer (CPDPC), has developed a robust framework and infrastructure to conduct clinical, translational, and mechanistic studies of CP. At its core is PRO spective Evaluation of C hronic Pancreatitis for E pid E miologic and Translational Stu D ies (PROCEED), the first longitudinal cohort study of CP in US adults, launched in 2017. PROCEED has developed a well-annotated clinical data set of over 2000 deeply-phenotyped participants, a biorepository and an imaging repository. Investigators have published promising data on blood-based and imaging-based biomarkers of CP diagnosis and pain, which are awaiting validation. Clinical observations include classification of patients into mechanism-based pain phenotypes using responses to PROMIS questionnaires, prevalence and predictors of opioid use, prevalence of psychological comorbidity, and osteopathy in CP patients. Pilot clinical trials have evaluated the effect of oral indomethacin on pancreatic fluid prostaglandin E2 levels and Internet-based cognitive behavioral therapy (CBT) for chronic pain. Results of pilot trials have led to an ongoing definitive randomized clinical trial for CBT. The rich environment and resources have facilitated mentorship and academic development of many early-stage investigators. Investigators outside of the consortium have opportunities for collaboration. In the next 5 years, the working group plans to further strengthen the research platform, complete primary and key secondary analyses of PROCEED and ancillary studies, continue efforts to develop biomarkers for diagnosis and prognosis of CP, and complete ongoing clinical trials to address unanswered questions in the field.

Objective Long COVID (LC) refers to the long-term symptoms occurring after SARS-CoV-2 infection and resolution of the initial disease prodrome. While LC is increasingly recognized, knowledge about its biomarkers is still limited. This study examines imaging findings in 18 F-FDG PET-CT scans in 40 patients with LC from an academic LC Clinic, for potential imaging biomarkers. Methods This study included patients aged 18 and older with confirmed positive SARS-CoV-2 PCR test and at least 28 days post-symptom onset. 18 F-FDG PET-CT scans were performed, and brain metabolic activity was compared to a control database to generate Z-scores. Participants were grouped based on their clinical phenotype and Z-scores of different brain regions were analyzed using t-tests. Results The study group was mainly female (70%), with a median age of 53 years, and predominantly non-Hispanic White (90%). Most had pre-existing conditions such as gastrointestinal, cardiovascular, endocrine, and psychiatric disorders. The findings showed significant cerebral hypometabolism in 29 patients with fatigue and post-exertional malaise (PEM), particularly in the left sensorimotor cortex (p=0.0253) and bilateral primary visual cortex (right: p=0.0096, left: p=0.0016), which persisted up to two years after infection. Conclusions In summary, this study identified persistent cerebral hypometabolism in LC patients, especially those with fatigue with PEM, up to two years post-infection. These results suggest that 18 F-FDG PET-CT could be a valuable tool for diagnosing and managing LC. Further research is essential to confirm these findings and improve treatment strategies for patients with LC.

545 Background: ILC is characterized by loss of E-cadherin expression, with distinct biological and clinical features, and is often perceived to be less sensitive to chemotherapy compared with IDC. Oncologists and pts may face a treatment dilemma regarding the benefits of adjuvant chemotherapy in pts with lower biologic risk but higher anatomic risk (N2/N3), stage III ILC. In this study, we sought to compare the benefit of adjuvant chemotherapy in pN2/N3 ILC compared with IDC. Methods: We used the National Cancer Database (NCDB) to identify adults with primary, non-metastatic, ER-positive/HER2-negative invasive breast cancer diagnosed between 2010 and 2022 who underwent upfront surgery. Patients receiving neoadjuvant systemic therapy were excluded. Analyses were limited to pathologic stage I–III disease with known nodal involvement (N2–N3) and tumor category (T1–4). Propensity score matching (1:3, caliper 0.2; using R 4.5.1) was performed to balance age, sex, race, insurance status, grade, pathologic stage, nodal category, tumor category, Charlson-Deyo comorbidity score, and year of diagnosis. Overall survival (OS) was assessed using Kaplan–Meier methods and Cox proportional hazards models used to estimate hazard ratios (SPSS v28). Results: After propensity matching, we analyzed 28,115 pts with pN2/N3 disease (ILC 9,603 and IDC 18,512). Upstaging from cN0 to pN2/3 was higher for ILC than IDC (20.3% vs 13.3%, p<0.001). ILC pts were more likely to undergo mastectomy compared to IDC (80.2% vs 71.2%, p<0.001). Receipt of adjuvant chemotherapy for pN2/N3 disease was similar between IDC and ILC (78.0% vs 78.4%, p=0.37), as was use of adjuvant radiation and endocrine therapy. Among patients receiving chemotherapy, treatment was associated with a 65% reduction in death in ILC (HR 0.35, 95% CI 0.32–0.38, p<0.001) and a 73% reduction in IDC (HR 0.27, 95% CI 0.26–0.29, p<0.001), compared with no chemotherapy. 5-year OS among chemotherapy-treated patients was lower for ILC compared with IDC (HR 1.4, 95% CI 1.33-1.49; p<0.001, Table 1). In contrast, no OS difference was observed between ILC and IDC among patients who did not receive chemotherapy (HR 1.03, 95% CI 0.96-1.11; p=0.38). Chemotherapy was associated with higher 5-year OS in both IDC (87.7% vs 58.9%) and ILC (84.3% vs 59.2%). Conclusions: Adjuvant chemotherapy was associated with a substantial improvement in 5-year OS among patients with pN2/N3 disease in both IDC and ILC. Pts with ILC and extensive nodal involvement benefit from adjuvant chemotherapy. 5-year survival of IDC and ILC. IDC (18,512) ILC (9,603) No Chemotherapy (4,078) Adjuvant Chemotherapy (14,434) No Chemotherapy (2,071) Adjuvant Chemotherapy (7,532) pN2 (18,669) 62.8% 90.1% 64.4% 87.6% pN3 (9,446) 48.3% 82.2% 51.4% 79.4% pN2/pN3 Combined (28,115) 58.9% 87.7% 59.2% 84.3% P <0.001, log rank.

3109 Background: Poly(ADP-ribose) glycohydrolase (PARG) is an enzyme that catalyzes the removal of poly-ADP-ribose (PAR) chains from proteins during DNA damage repair. PARG inhibition leads to selective cell death in tumors with underlying replication fork defects, including BRCAm tumors, through a mechanism distinct from PARP inhibition. ETX-19477 is an oral, potent, and selective PARG inhibitor that shows robust preclinical activity in mouse models of ovarian, breast, and gastric cancers. Methods: ERADIC8 is an open-label, multicenter, Phase 1/2 study, consisting of two parts, dose escalation and dose expansion. A Bayesian Optimal Interval Design was used to enroll patients (pts) into dose escalation cohorts, with enrichment for pts with BRCAm high grade serous ovarian (HGSOC) and breast cancers. The primary objective is to assess safety/tolerability of ETX-19477 and define the maximum tolerated dose (MTD) and recommended Phase 2 dose(s). Secondary and exploratory objectives include pharmacokinetics, pharmacodynamics, and preliminary anti-tumor activity per RECIST v1.1. ETX-19477 is given orally once or twice daily in 21-day cycles. Results: As of Jan 6 2026, 45 pts were enrolled into the study across 11 dose levels (range: 80-750 mg QD, 190-350 mg BID). Tumor types included ovarian (n=24, BRCAm: 18), breast (n=8, BRCAm: 7), endometrial (n=6, BRCAm: 0), colorectal (CRC, n=3, BRCAm: 1), and other (n=4, BRCAm: 0) cancers. Treatment-related AEs (TRAEs; any grade) occurring in >20% of pts were nausea (53%), vomiting (38%), and fatigue (24%). The only Gr3 TRAE occurring in >5% of pts was neutropenia (16%). There was one Gr4 TRAE of neutropenia in 1 pt (2%) and no Gr5 TRAEs. ETX-19477 exposure is dose proportional, and the BID regimen achieves >85% PARG inhibition throughout the dosing interval in a blood-based PAR accumulation pharmacodynamic assay. As of the data cutoff, dose escalation is ongoing at 350 mg BID (MTD has not been defined) and dose expansion is ongoing at 200-300 mg BID. Among BRCAm, HGSOC pts enrolled at BID dose levels, there were 7 evaluable pts with a median of 4 prior lines of therapy (range 2–11): 2 pts achieved a partial response (PR, 29%) and 3 pts achieved stable disease (SD, 43%). Both pts with PRs were platinum-resistant and received prior PARP inhibitor treatment. 1 pt with BRCAm CRC remains on active therapy (250 mg BID) with SD for 7 months. Conclusions: ETX-19477 was well tolerated and showed anti-tumor activity in heavily pretreated pts with BRCAm, platinum-resistant HGSOC during dose escalation. These findings provide the first clinical proof-of-concept of PARG inhibition in HGSOC. ETX-19477 is being further evaluated in the dose expansion phase of the study. Clinical trial information: NCT06395519 .