Citations

Objective We aimed to assess the occurrence of carpal tunnel syndrome (CTS) before and after rheumatoid arthritis (RA) incidence and by serologic status. Methods This population‐based study included residents of a geographically defined area meeting the 1987 American College of Rheumatology classification criteria for RA in 1980 to 2019 matched 1:1 with individuals without RA. At least two diagnosis codes ≥30 days apart were used to identify CTS. Cumulative incidence of CTS adjusting for competing risk of death was assessed. Logistic regression and Cox proportional hazard models were used, adjusting for age, sex, calendar year, smoking, obesity, diabetes mellitus, and hypothyroidism. Results We included 1,335 patients with RA and 1,331 individuals without RA. The overall prevalence of CTS before or on RA incidence or index was 179 patients with RA (13%) and 85 individuals without RA (6%), respectively (odds ratio [OR] 2.23; 95% confidence interval [CI] 1.69–2.94). Most previous incidences of CTS occurred ≥2 years before the index date (112 events in patients with RA and 75 events in individuals without RA, respectively). Following RA incidence or index, individuals with RA (vs those without RA) had ~80%‐higher risk of CTS (hazard ratio [HR] 1.78; 95% CI 1.38–2.30). The risk estimates of CTS in patients with seronegative (vs seropositive) RA were OR 1.33 (95% CI 0.96–1.84) before RA incidence and HR 1.37 (95% CI 0.99–1.88) after RA incidence. In RA, obesity (HR 1.42, 95% CI 1.02–1.99) and seronegative cyclic citrullinated peptide antibody status (HR 1.79, 95% CI 1.07–2.99), but not other risk factors, were associated with increased CTS risk. Conclusion We found a more than two‐fold increase in risk of CTS in the years preceding RA and a 1.8‐fold increased risk of incident CTS following RA onset. image

Abstract There are limited prospective data on whether established risk factors modify breast cancer risk in women with pathogenic variants (PV) in BRCA1/2 and virtually no risk modification data for ATM, CHEK2, or PALB2. We conducted a nested case–control study in the Women’s Health Initiative (WHI), randomly selecting women with and without breast cancer for DNA sequencing. We evaluated breast cancer odds associated with obesity, family cancer history, smoking, alcohol, parity, breastfeeding, oophorectomy, tubal ligation, neighborhood socioeconomic status, and menopausal hormone therapy (MHT) with estrogen and progestin or estrogen only in PV carriers and noncarriers. In exploratory analyses, we grouped genes by established predisposition for estrogen receptor (ER)-positive (ATM and CHEK2) or ER-negative (BRCA1 and PALB2) disease. Multivariable models with interaction terms were used to assess differential risk modification by PVs. Among 12,957 WHI participants, 287 carried PVs. Breastfeeding was modestly associated with reduced risk for PALB2 [OR = 0.08; 95% confidence interval (CI), 0.00–0.92; P value = 0.042]. With one-sided 95% CI, power was sufficient to exclude OR ≥2.0 with obesity for ATM and BRCA2; smoking and alcohol for CHEK2; no breastfeeding for ATM; no oophorectomy for BRCA2 and CHEK2; no tubal ligation for CHEK2; and neighborhood socioeconomic status for all genes. Estrogen + progestin MHT was modestly associated with increased risk for ER-positive PVs (OR = 7.31; 95% CI, 1.14–64.20; P = 0.036). PVs did not modify risk (interaction P ≥ 0.05). BRCA1/2, ATM, CHEK2, and PALB2 PV carriers do not have breast cancer OR ≥2.0 with many established risk factors. However, MHT warrants additional study in PV carriers. Significance: There is limited information on whether established risk factors increase breast cancer risk from PVs. In the WHI, PV carriers had no substantial (≥2-fold) increase with most risk factors, except potentially MHT in ATM or CHEK2 carriers. The results may inform counseling and research on MHT.

Abstract Background: Savo is an oral, potent and highly selective MET-TKI. In the Phase 2 SAVANNAH study (NCT03778229), savo + osi had a high rate of durable responses in pts with EGFRm advanced NSCLC and high MET OverExp and/or Amp levels. Early clearance of plasma EGFRm may predict outcomes. We report an exploratory analysis of plasma EGFRm clearance and its association with MET tissue biomarker status, ORR and PFS. Methods: Pts with EGFRm advanced NSCLC and MET OverExp and/or Amp with PD on 1L+ osi received savo 300 mg QD, 300 mg BID or 600 mg QD + osi 80 mg QD. MET OverExp/Amp was centrally confirmed (by IHC [Roche], 3+ intensity in ≥50% of tumor cells [MET IHC3+/≥50%]; by FISH [Abbott Molecular], MET gene copy number ≥5 or MET:CEP7 ratio ≥2 [FISH5+], or at higher thresholds of MET IHC3+/≥90% or FISH10+). Baseline (BL) and Wk 3 plasma EGFRm (Ex19del/L858R) were analyzed by ddPCR (Biodesix) as an estimate of tumor burden. MET Amp was not monitored in ctDNA due to low detection sensitivity. Clearance was defined as undetected EGFRm ctDNA at Wk 3, when detected at BL. PFS was investigator-assessed (RECIST 1.1). DCO: Aug 23, 2024. Results: Of 344 pts with evaluable BL ctDNA, 259 (75%) had detected EGFRm ctDNA. Of these, 225 had evaluable ctDNA at Wk 3 (82 [36%] had EGFRm clearance at Wk 3). Confirmed ORR was higher in pts with EGFRm Wk 3 clearance (56/82; 68%) vs non-clearance (38/143; 27%). PFS was longer in pts with vs without EGFRm clearance at Wk 3 (Table). Across all pts evaluable for ctDNA at Wk 3, clearance rates were higher in pts with vs without high MET (69/162 [43%] vs 13/63 [21%]; odds ratio [95% CI] 0.35 [0.16, 0.72]). Similar results were seen in the savo 300 mg QD + osi subgroup. Conclusions: In SAVANNAH, among pts with detected EGFRm ctDNA at BL, clearance at Wk 3 was associated with improved ORR and PFS. Plasma EGFRm clearance at Wk 3 is enriched in pts with MET IHC3+/≥90% or FISH10+ status, consistent with improved efficacy in this biomarker subgroup. Citation Format: Jonathan W. Riess, Filippo de Marinis, Benjamin Levy, Tae Min Kim, Laura Bonanno, Quincy Chu, Marcello Tiseo, Adrian Sacher, Silvia Novello, Christina Baik, Lyudmila Bazhenova, Jacques Cadranel, Giulio Metro, Cheng-Ta Yang, Tsung-Ying Yang, Gee-Chen Chang, Konstantinos Leventakos, Lorenzo Livi, James Chih-Hsin Yang, Lecia V. Sequist, John Argue, Wanning Xu, Aleksandra Markovets, Ryan Hartmaier, Myung-Ju Ahn. SAVANNAH: Clearance of plasma EGFRm in patients with EGFRm MET-overexpressed (OverExp) and/or -amplified (Amp) NSCLC post-osimertinib (osi) treated with savolitinib (savo) + osi [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr LB416.

AbstractINTRODUCTIONHigher male prevalence in sporadic behavioral variant frontotemporal dementia (bvFTD) has been reported. We hypothesized differences in phenotypes between genetic and sporadic bvFTD females resulting in underdiagnosis of sporadic bvFTD females.METHODSWe included genetic and sporadic bvFTD patients from two multicenter cohorts. We compared behavioral and cognitive symptoms, and gray matter volumes, between genetic and sporadic cases in each sex.RESULTSFemales with sporadic bvFTD showed worse compulsive behavior (p = 0.026) and language impairments (p = 0.024) compared to females with genetic bvFTD (n = 152). Genetic bvFTD females had smaller gray matter volumes than sporadic bvFTD females, particularly in the parietal lobe.DISCUSSIONFemales with sporadic bvFTD exhibit a distinct clinical phenotype compared to females with genetic bvFTD. This difference may explain the discrepancy in prevalence between genetic and sporadic cases, as some females without genetic mutations may be misdiagnosed due to atypical bvFTD symptom presentation.Highlights Sex ratio is equal in genetic behavioral variant of frontotemporal dementia (bvFTD), whereas more males are present in sporadic bvFTD. Distinct neuropsychiatric phenotypes exist between sporadic and genetic bvFTD in females. Phenotype might explain the sex ratio difference between sporadic and genetic cases.

Abstract INTRODUCTION Sex differences are apparent in neurodegenerative diseases but have not been comprehensively characterized in frontotemporal dementia (FTD). METHODS Participants included 337 adults with autosomal dominant FTD enrolled in the ALLFTD Consortium. Clinical assessments and plasma were collected annually for up to 6 years. Linear mixed‐effects models investigated how sex and disease stage are associated with longitudinal trajectories of cognition, function, and neurofilament light chain (NfL). RESULTS While sex differences were not apparent at asymptomatic stages, females showed more rapid declines across all outcomes in symptomatic stages compared to males. In asymptomatic participants, the association between baseline NfL and clinical trajectories was weaker in females versus males, a difference that was not present in symptomatic participants. DISCUSSION In genetic FTD, females show cognitive resilience in early disease stages followed by steeper clinical declines later in the disease. Baseline NfL may be a less sensitive prognostic tool for clinical progression in females with FTD‐causing mutations. Highlights Females with genetic FTD exhibit overall steeper increases in plasma neurofilament light chain (NfL) than males. Females with genetic FTD outperform NfL levels in asymptomatic stages compared to males. Once symptomatic, females with genetic FTD decline more rapidly than males. Plasma NfL is a stronger prognostic marker in asymptomatic males than females.

Abstract Tumor microenvironments (TMEs) are spatially complex and dynamic systems shaped by evolutionary pressures, tissue architecture, and cellular interactions. To capture this complexity, we developed the Tumor Landscape Analysis (TLA) pipeline, a computational framework applying principles from landscape ecology and spatial statistics to quantitatively characterize tumor spatial heterogeneity. TLA integrates spatially resolved pathology data, including whole-cell, point-based, and region-level formats, and computes multiscale metrics to assess cell distributions, neighborhood relationships, and tissue-level organization. The framework leverages ecological indices such as the Morisita-Horn index, Ripley’s H function, and Shannon diversity to quantify intercellular proximity, spatial clustering, and cellular diversity. It also uses the concept of local microenvironments (LMEs), data-driven ecological niches defined by local cell-type abundance and spatial uniformity, enabling unsupervised and reproducible classification of tumor regions. The use of fragmentation metrics, including patch density, shape complexity, and interspersion, provide further insight into spatial disorganization and emergent tissue architecture. TLA is agnostic to imaging modality and biological context, supporting broad applicability across tumor types and sample formats. By translating complex tissue architectures into interpretable spatial metrics, the pipeline enables integrative analyses that link spatial ecology to clinical and molecular phenotypes. This approach facilitates a deeper understanding of how spatial features contribute to tumor progression, therapeutic resistance, and clinical outcomes, offering new opportunities for precision oncology rooted in spatial systems biology.

Abstract Introduction: We previously developed a urine liquid biopsy assay to measure urine tumor DNA (utDNA) levels in bladder cancer (BC) patients. Here, we extended this approach significantly by layering in cell-free DNA fragmentomic and cell-free RNA analysis, and extending the method to the full spectrum of genitourinary (GU) cancers, to enable both GU cancer detection and tumor tissue of origin prediction. Methods: A total of 155 GU cancer patients and 34 healthy adults were enrolled in this prospective study. Preoperative urine was collected from 94 bladder cancer (BC) patients, including 65 with muscle-invasive disease, all undergoing cystectomy. Additionally, urine samples were collected from 18 renal cell carcinoma (RCC) patients undergoing nephrectomy and 42 metastatic prostate cancer (mPC) patients. Urine cfDNA and cfRNA were isolated and sequenced, with cfRNA sequenced to 100 million reads per sample on an Illumina NovaSeq X and cfDNA sequenced at 5x genome-wide coverage on a Novoseq S4 flow cell. To identify malignant tissue of origin, we analyzed somatic copy number alterations (CNAs), genome-wide fragment length ratios, and 4-mer end motifs. Tumor fraction (TFx) was estimated using ichorCNA, while DELFI was employed for fragment length ratios in 5 megabase bins across the genome and chromosome arm-level z-scores. Individual logistic regression models were developed based on each fragmentomic feature, and validated using a training and held-out testing approach. Outputs from these models were combined into a single comprehensive model, also trained and held-out tested using the same approach. Urine cfRNA transcript isoform abundance was quantified using Salmon and normalized to Transcripts Per Million (TPM) to account for sequencing depth variations. Results: Bladder cancer (BC) showed the highest mean tumor fraction (TFx, 10.5%), followed by RCC (3.8%) and mPC (3.4%). Among 94 BC patients, 42% achieved a pCR, while 58% had residual disease and did not. Patients without pCR had significantly higher urine TFx compared to those with pCR (14.7% vs. 4.7%, p=0.0008). A machine learning model based on genome-wide fragment length ratios achieved an ROC AUC of 0.74, while models using genome-wide CNAs and end motifs achieved AUCs of 0.81 and 0.88, respectively. Combining all features into a single model yielded an AUC of 0.92, with classification accuracies of 89% for bladder cancer, 80% for RCC, and 60% for prostate cancer. Additionally, urine cfRNA analysis using the top 1, 000 coding transcripts achieved an AUC of 0.95, with classification accuracies of 100% for mPC, 87% for BC, and 78% for RCC. Conclusion: Fragmentomic features from urine cfDNA and transcriptomic features from urine cfRNA demonstrate strong potential for predicting tumor tissue-of-origin in GU cancers, underscoring the promise of non-invasive diagnosis across the spectrum of GU malignancies through urine liquid biopsy. Citation Format: Pradeep Singh Chauhan, Irfan Alahi, Jessica Linford, Arpit Panda, Nathan Colon, Ryan Mueller, Faridi Qaium, Peter K. Harris, John Sheng, Eric H. Kim, Melissa A. Reimers, Zachary L. Smith, Woodson W. Smelser, Aadel A. Chaudhuri. Predicting genitourinary cancer tissue-of-origin using urine cell-free DNA fragmentomics and cell-free RNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3258.