Citations

This case report describes a 65-year-old man who experienced complete remission of cavin-4 immunoglobulin G (IgG) rippling muscle disease after receiving rituximab therapy.

8524 Background: Teliso-V is a c-Met–directed antibody-drug conjugate comprising telisotuzumab and the microtubule polymerization inhibitor monomethyl auristatin E (MMAE) payload. In the Ph2 LUMINOSITY study (NCT03539536), Teliso-V showed durable responses and manageable safety (Camidge et al, JCO 2024;42:3000-11) resulting in its accelerated approval in locally advanced/metastatic NSQ NSCLC with high c-Met protein OE (3+, ≥50%), as determined by an FDA-approved test. MET amp is a negative prognostic risk factor in advanced NSCLC, frequently associated with recurrent disease. High levels of MET amp and c-Met OE are hallmarks of MET -addicted tumors. Here, we analyzed the effects of MET amp on clinical responses to Teliso-V in LUMINOSITY. Methods: MET amp was evaluated by FISH and ctDNA in baseline samples from 108 NSQ EGFR WT NSCLC pts with c-Met OE (3+, ≥25%). MET amp by FISH was defined as having focal MET amp (MET/CEP7 ≥2.0) with MET gene copy number (GCN) ≥4. MET amp (focal) by ctDNA was defined as having plasma MET GCN ≥4 with no co-amplification in CDK6 and EGFR. c-Met OE by Immunohistochemistry (IHC; SP44) was defined as 3+ tissue staining intensity in ≥25% tumor cells (high c-Met OE: 3+, ≥50%; intermediate [int] c-Met OE: 3+, 25% to 49%). Exploratory analysis of tumor response was assessed in 76 efficacy evaluable pts with c-Met OE and MET amp assay results. Results: MET amp was detected in 34% (37/108) of pts with c-Met OE (3+, ≥25%) and was enriched by c-Met levels: 22% (11/50) in pts with Int c-Met OE (3+, 25% to 49%) and 45% (26/58) in pts with high c-Met OE (3+, ≥50%). The effects of MET amp on tumor response in LUMINOSITY are shown in Table 1. The majority of c-Met OE pts (79%) with PFS ≥10 mo (n=14) had GCN ≥10 and/or c-Met IHC 3+ ≥50%. No new safety signals were reported in pts with c-Met OE and MET amp. Conclusions: MET amp is more common in pts with high c-Met OE in this retrospective subgroup analysis. Tumor activity with Teliso-V was observed regardless of MET amp status. The impact of MET amp in pts with c-Met OE will be further evaluated in ongoing Phase 3 study (NCT04928846). Teliso-V efficacy in NSQ EGFR -WT NSCLC pts with c-Met OE with or without MET amp in LUMINOSITY. Total c-Met OE(3+, ≥25%) Total c-Met OE(3+, ≥25%) Intermediate c-Met OE(3+, ≥25%-49%) Intermediate c-Met OE(3+, ≥25%-49%) High c-Met OE(3+, ≥50%) High c-Met OE(3+, ≥50%) MET amp(N) No (N=53) Yes (N=23) No (N=30) Yes (N=7) No (N=23) Yes (N=16) ORR %(95% CI) 28 (18.0, 41.6) 39 (22.2, 59.2) 23 (11.8, 40.9) 57 (25, 84.2) 35 (18.8, 55.1) 31 (14.2, 55.6) PFS,median, mo(95% CI) 5.26 (3.71, 8.11) 8.02 (4.47, 14.65) 5.32 (2.69, 8.11) 7.52 (4.47, NA) 4.17 (3.25, 8.87) 8.02 (3.06, 25.92) OS,median, mo(95% CI) 14.5 (8.18, 17.38) 13.86 (6.54, 22.24) 14.03 (3.65, 17.02) 9.79 (6.54, NA) 16.26 (5.59, 36.44) 13.86 (3.06, 30.29)

7546 Background: MRD assessment informs relapse risk in MM but is typically bone marrow-based and invasive. We therefore compared two minimally invasive MRD assays: BM-informed cfDNA whole-genome sequencing (cfWGS) and plasma proteomic MRD (EasyM). Methods: 71 longitudinal plasma samples (22 diagnosis, 49 follow-up) from 22 newly diagnosed MM patients across 8 Canadian sites (TFRIM4) had paired cfWGS and EasyM (Rapid Novor Inc). cfWGS MRD used patient-specific mutation lists from diagnostic BM WGS (Abelman et al., medRxiv 2025). EasyM used mass spectrometry to quantify residual M-protein from baseline. The primary endpoint was progression-free survival (PFS). Results: Among 22 MM patients (8 male, 14 female; median age at diagnosis 62 years), 8 progressed at a median follow-up of 52.6 months (range: 10-79 months). At 1-year maintenance (n = 18 available), cfWGS MRD+ (6/18) predicted inferior PFS (HR 20.12, 95% CI 2.23-181.60, p = 0.007). EasyM any-detect positivity was frequent (16/18, reflecting delayed clearance) and not prognostic (p = 0.99), with poor agreement vs cfWGS (44.4%, κ = 0.118). An exploratory EasyM clearance threshold of 0.93% (hypothesis-generating) classified 5/18 patients as MRD+ and stratified PFS (HR 8.78, 95% CI 1.55-49.82, p = 0.004), improving agreement with cfWGS (17/18, 94.4%, κ = 0.870). Progression clustered in cfWGS+/EasyM-high patients (EasyM >0.93%; 4/5; median 11.9 months post-collection [1.9–22.8]) and occurred once in cfWGS−/EasyM-low patients (1/12, 27.6 months). The only discordant case (cfWGS+/EasyM−) progressed 8.7 months after collection. Higher quantitative MRD burden was associated with inferior PFS (cfWGS: HR 2.92 per 1 SD, 95% CI 1.29-6.59, p = 0.01; EasyM: HR 5.48 per 1 SD, 95% CI 0.79-37.90, p = 0.085). At ~100 days post-autologous stem cell transplantation (ASCT; n = 16 available), EasyM was uniformly MRD+ (16/16) while cfWGS was MRD+ in 7/16 patients. Applying an EasyM clearance threshold (2.13%; 9 cleared vs 7 residual) improved agreement with cfWGS (14/16; 87.5%; κ = 0.746). Of two discordant cases, one cfWGS+/EasyM-cleared patient relapsed 38.6 months post-collection and one cfWGS−/EasyM-residual patient remained progression-free at last follow-up. At post-ASCT, both assays showed consistent but underpowered associations with PFS (cfWGS HR 6.32, 95% CI 0.70–56.76, p = 0.100; EasyM-clearance HR 2.36, 95% CI 0.39–14.18, p = 0.335). Across all post-treatment samples (n = 49), continuous cfWGS burden correlated with EasyM residual M-protein (rho = 0.535, p < 0.001). Conclusions: BM-informed cfWGS MRD strongly stratified PFS, whereas EasyM required a clearance definition due to near-universal early positivity. Concordant plasma burdens support complementary MRD information. Future work will validate these findings in larger cohorts and quantify the incremental value of combined cfWGS and proteomic MRD for early relapse prediction.

3022 Background: Pharmacological blockade of Aurora-A mitotic kinase (AURKA) oncogenic pathway represents a promising therapeutic strategy to inhibit breast cancer plasticity and progression. However, treatment with the selective AURKA inhibitor alisertib is followed by acquired on-target mutations in a subset of patients that are linked to alisertib resistance and tumor progression. Current resistance mechanisms are typically identified retrospectively after therapeutic failure. We evaluated whether Dynaptive, a structure- and evolution-aware artificial intelligence (AI) platform, could prospectively predict treatment-induced AURKA resistance mutations prior to experimental observation. Methods: We identified acquired on-target mutations in patients from the alisertib Phase-II clinical trial. These mutations were cross-matched against Dynaptive predictions that had been generated independently of any experimental resistance data. Dynaptive integrates protein conformational ensembles and evolutionary sequence constraints to predict mutational hotspots and assess their functional and drug-binding impact. Identified mutations were evaluated against large-scale population datasets to determine natural occurrence. Results: Several AURKA mutations observed in patients that showed resistance to alisertib were prospectively predicted by Dynaptive despite being entirely absent from prior population datasets. These mutations were not observed previously in either healthy or cancer cohorts described in the public domain. Significantly, the most frequently occurring AURKA resistance mutation occurred at a residue ranked second among predicted mutational hotspots and were predicted to reduce alisertib binding affinity by ≥10-fold. Across all variants, absence from population datasets and emergence only following treatment support a treatment-induced resistance mechanism. Conclusions: A structure-aware AI platform prospectively identified clinically relevant, treatment-induced AURKA resistance mutations prior to experimental detection. These findings demonstrate the feasibility of predictive modeling to anticipate resistance mechanisms and support the development of next-generation AURKA inhibitors optimized to overcome mutations-driven resistance and to improve therapeutic efficacy, safety and durability.

SUMMARY Neurodegenerative diseases are often accompanied by systemic comorbidities, including changes in bone health, but the molecular relationship between neurodegeneration, skeletal decline, and cellular senescence remains poorly understood. In this study, we investigated sex-specific changes in circulating bone- and senescence-related proteins across the spectrum of Alzheimer’s disease(AD), Lewbody dementia(LB) and Parkinson’s disease(PD). Plasma proteomic profiling was performed on samples from 408 participants deeply phenotyped for neurodegenerative diseases, followed by differential protein and pathway analyses. This study reveals sex-dependent alterations in bone and senescence-related circulating proteins in AD-related, PD and LB-related neurodegenerative diseases, providing insights into the complex relationship between neurodegeneration and bone health. Several candidate proteins were also associated with established plasma neurodegeneration biomarkers, particularly pTau181. Pathway analyses revealed shared mitochondrial and metabolic dysfunction across neurodegenerative diseases, with disease-specific features including vesicle trafficking disruption in AD and inflammatory-senescence pathways in LB, plus sex-divergent patterns in inflammatory signaling and bone-related pathways.

Abstract Functional magnetic resonance imaging (fMRI) data are inherently complex, characterized by high dimensionality, intricate inter-regional dependencies, and substantial individual variability across experimental paradigms. Traditional linear mixed models (LMMs) provide a principled framework that models population-level fixed effects while estimating variance components arising from subject-level random effects; however, they often fail to adequately capture nonlinear relationships inherent in neuroimaging data. To address these limitations, we introduce the nonlinear mixed model (NMM) approach, an innovative extension of the LMM framework that integrates neural networks to flexibly model complex fixed-effect relationships while preserving the random-effects structure to account for individual differences. NMM advances fMRI analysis by: (1) identifying robust functional connectivity (FC) patterns consistently observed across multiple paradigms; (2) leveraging SHapley Additive exPlanations (SHAP) analysis to provide post-hoc interpretability of the nonlinear fixed effects, quantifying how age, sex, and paradigm contribute to predicted FC and how these effects are distributed across large-scale brain networks; and (3) using subject-specific random effects as neural fingerprints that not only show systematic variability across attention and default mode systems but also predict standardized cognitive scores, demonstrating biological relevance. Applied to the Philadelphia Neurodevelopmental Cohort (PNC) across emotion, n-back, and resting-state paradigms, NMM achieved superior model fit relative to classical LMMs, as evidenced by lower mean squared error (MSE) in predicting FC. This framework offers a statistically rigorous and practically explainable approach for modeling large-scale FC from modest covariates while explicitly separating population-level effects from stable individual variability in functional brain organization.

Abstract Rationale Asthma contributes substantially to healthcare burden and morbidity through frequent exacerbations. Emerging evidence suggests that genetic factors play a crucial role in modulating susceptibility to asthma exacerbations. To better understand the genetic architecture of exacerbations, we conducted a genome-wide association study (GWAS) in the Tapestry cohort. Methods The Tapestry Study, a large-scale, decentralized and clinical grade genomic sequencing study, conducted Exome+® sequencing at Helix, Inc. on 98,075 Mayo Clinic participants. After excluding patients with ≥10 pack-years of smoking and/or emphysema, we performed a GWAS of asthma exacerbations in 3,960 adults with asthma based on ICD codes. Cases (n = 1,059) were defined as individuals who experienced at least two exacerbations between 2020 and 2025; the remaining 2,901 individuals served as controls. Asthma exacerbations were defined by oral or systemic corticosteroid prescriptions with durations ranging from 3 days up to 28 days. Logistic regression models adjusted for age, sex, BMI, and the first six principal components of ancestry. Replication was performed in 1,273 asthma patients (439 African Americans and 834 non-Hispanic Whites) from the NHLBI-sponsored Severe Asthma Research Program (SARP 1-3), with adjustments for age, sex, BMI, and the first 10 principal components of ancestry. Results Based on a minor allele frequency (MAF) threshold of &gt; 0.05, we analyzed 5,256,135 genome-wide variants. Genome-wide significant associations for asthma exacerbations (p &lt; 5.0 × 10⁻8) included loci at a pseudogene in SMPD4P1 (rs680548, MAF = 0.39, OR = 1.37, p = 9.10 × 10⁻9). Additional variants showing suggestive associations included loci within ENDOD1 (rs638776, OR = 0.69, p = 1.20 × 10⁻6), PCSK2 (rs2206454, OR = 1.32, p = 3.53 × 10⁻6), RBFOX1 (rs17667084, OR = 0.60, p = 5.11 × 10⁻6), and CDC42EP3 (rs721660, OR = 1.29, p = 5.68 × 10⁻6). Subthreshold associations in Tapestry including loci at CDC42EP3 (rs4670213, OR = 1.27, p = 1.41x10-5, MAF = 0.36), and SDR39U1 (rs12587663,OR = 0.83, p = 5.86x10-4, MAF = 0.46) were replicated in the SARP longitudinal visit 5 with p-values of 8.523x10-3 (rs4670213, OR = 1.78), and 2.88x10-4 (rs12587663,OR=0.43), respectively. Conclusion Our GWAS for asthma exacerbations in the Tapestry cohort identified variant loci relevant to mitophagy mechanisms (CDC42EP3, PMID: 40783597), immune signaling and RNA splicing regulation (RBFOX1, PMID: 31301374), and neuromodulatory pathways (PCSK2, PMID: 32794589), all previously implicated in asthma pathophysiology. Collectively, these findings highlight potential novel genetic contributors to asthma exacerbations and provide a foundation for improving risk stratification and therapeutic targeting in asthma management. This abstract is funded by: This abstract is funded by: Mayo Clinic Funding: X01 from the NHLBI for TOPMed whole-genome sequencing and NIH grants R01 HL142992, HL69116, HL69167, HL69170, HL69174, U10 HL109164, U10 HL109257, U10 HL109146, U10 HL109172, U10 HL109250, U10 HL109250, U10 HL109250, U10 HL109168, U10 HL109152, U10 HL109086, U10 HL109046.

Background and Objectives: Roux-en-Y gastric bypass (RYGB) is one of the most commonly performed metabolic and bariatric surgeries worldwide. Marginal ulcers (MU) are a common complication following RYGB, yet their pathophysiology and the contributing risk factors to their development are not fully understood. Materials and Methods: This retrospective cohort study examined patients who underwent RYGB between January 2008 and December 2023, with 1 to 5 years of follow-up. Data collected included patient- and procedure-related risk factors, as well as postoperative MU events. Statistical analysis methods included the independent samples t-tests, multivariate regression, and Cox regression analyses. Results: Our final cohort included 2106 patients and was predominantly female (80.5%), with a mean age of 47.8 ± 12.1 years and body mass index (BMI) of 45.5 ± 7.5 kg/m2. MU occurred in 241 (11.4%) patients, with a mean time to occurrence of 4.5 ± 0.02 years. History of smoking (HR = 1.87, p < 0.001) and gastroesophageal reflux disease (HR = 2.36, p < 0.001) significantly increased hazard for MU, while proton pump inhibitor use (HR = 0.18, p < 0.001) was associated with reduced hazard. Aspirin exposure, regardless of dose and chronicity, did not impact MU. Conclusions: Our findings highlight the importance of preoperative assessment and counseling in patients planning to undergo RYGB. Patient-related factors should guide postoperative monitoring and prophylaxis of MU, as this remains a debated topic amongst experts.