Citations

Abstract Objectives To implementation an automated multi-institutional pipeline that delivers breast-cancer risk integrated with polygenic risk scores, monogenic variants, family history, and clinical factors, emphasizing operational challenges and their solutions. Materials and Methods A five-stage process was executed at ten sites. Data streams from REDCap surveys, PRS and monogenic reports, and MeTree pedigrees were normalized and forwarded through a REDCap plug-in to the CanRisk API. Results Integrated risk was returned to >10 000 women; 3.6% were ≥25 % lifetime risk and 0.9% carried pathogenic variants. Pipeline generated score aligns well with manual generated ones. Major barriers such as heterogeneous pedigree formats, missing data, edge-case handling, and evolving model versions were identified and resolved through mapping rules, imputations, and iterative testing. Discussion Cross-platform data harmonization and stakeholder alignment were decisive for success. Borderline-risk communication and model-version drift remain open issues. Conclusion Large-scale PRS-integrated breast-cancer risk reporting is feasible but requires robust interoperability standards and iterative governance.

Abstract BRCA-associated homologous recombination deficiency (HRD) is present in ~ 50% of high-grade serous carcinomas (HGSC) and predicts sensitivity to platinum-based therapy. However, there is little understanding of why some patients with BRCA-deficient tumors experience unexpectedly poor outcomes. We profiled 154 tumors, enriched for patients with BRCA-deficient tumors that experienced short overall survival (≤ 3 years, n = 42), using whole-genome, transcriptome, and methylation analyses. All but one BRCA-deficient tumor exceeded an accepted HRD genomic scarring threshold. However, patients with BRCA1-deficient HGSC with a more elevated HRD score survived significantly longer. Patients with BRCA2-deficient HGSC and loss of NF1 survived twice as long as those without NF1 loss, whereas PIK3CA or RAD21 amplification defined BRCA2-deficient HGSC with exceptionally short survival. BRCA1-deficient tumors in short survivors had evidence of immunosuppressive c-kit signaling and EMT. In a large HGSC cohort (n = 1,389) including 282 individuals with pathogenic germline BRCA variants (gBRCApv), the location of the mutation within functional domains stratified clinical outcomes. Notably, residual disease after primary surgery had limited prognostic effect in gBRCApv-carriers compared to non-carriers. Our findings indicate that tumor HR proficiency in the context of therapy response and survival is not a binary property, and highlight genomic and immune modifiers of outcomes in BRCA-deficient HGSC.

Article Title: Colorectal Cancer Screening Based on Predicted Risk: A Randomized Controlled Trial.

Evaluation of T-cell receptor (TCR) β-chain constant region 1 (TRBC1) expression is an alternative T-cell clonality assessment method. However, evaluation of TRBC1 immunohistochemistry (IHC) for distinguishing mycosis fungoides (MF)/Sezary syndrome (SS) from reactive inflammatory infiltrates in skin is incomplete. We evaluated the utility of a novel dual TRBC1-CD3 IHC stain in skin biopsies with MF/SS (n=40), reactive (n=24), or atypical T-cell infiltrates indeterminant for MF/SS (n=9). Twenty of 24 reactive cases showed clear polytypic TRBC1 expression (median percent TRBC1 positivity among CD3-positive T cells [%TRBC1+] 50% in dermis, 42.5% in epidermis among all cases), while 34/40 MF/SS were clearly monotypic (%TRBC1+ either ≤20% or ≥85%) (sensitivity 85.0%, specificity 91.7%, positive predictive value 94.4%, negative predictive value 78.6%). Discordance between TRBC1 expression and diagnosis was associated with few neoplastic/monotypic T cells and/or lack of physical separation between neoplastic and non-neoplastic populations. Among patch/plaque MF/SS, TRBC1 showed similar diagnostic sensitivity (80.0% vs. 86.7%) and high categorical correlation (monotypic vs. not monotypic, 80%) with TCR gene rearrangement results. TRBC1 interpretation was reproducible, with ≥2/3 and 3/3 pathologists rendering identical interpretations in 100% and 86% of cases, respectively, after independent review and 100% agreement following collective review. Digital image analysis confirmed visual %TRBC1+ accuracy ( r =0.9749, P <0.0001). On the basis of these results, we propose %TRBC1+ cutoffs of <25% or >75% for establishing T-cell monotypia in skin. Considering such thresholds, TRBC1-CD3 evaluation facilitated diagnostic refinement in 7/9 (78%) atypical cases. Overall, TRBC1-CD3 IHC clearly and rapidly aids diagnosis of cutaneous T-cell proliferations.

Abstract INTRODUCTION In multicenter Alzheimer's disease studies, amyloid positron emission tomography (PET) visual reads are typically performed centrally by a few experts. Incorporating a broader reader network enhances scalability and generalizability. METHODS Ten neuroimaging experts from eight Alzheimer's Disease Research Centers (ADRCs) visually read 180 amyloid PET scans (30 scans and 15 duplicate scans for each of four tracers, imaged across a wide variety of scanners), using preferred reading software without anatomical imaging or quantitation. Scans were classified as elevated or non‐elevated per tracer‐specific criteria. Inter‐ and intra‐rater agreement was assessed. RESULTS Inter‐rater agreement was substantial (Fleiss’ κ = 0.78), with full consensus on 69% of scans. Inter‐rater reliability was substantial to perfect across tracers (Fleiss’ κ = 0.70–0.87). Intra‐rater agreement was substantial to perfect (Cohen's κ = 0.79‐1). Scans with intermediate (10–40 Centiloid) quantitation had lower reader agreement. DISCUSSION A multicenter expert network achieved substantial agreement classifying amyloid PET scans. These scans provide a standard for reader training and reliability assurance in future studies. Highlights Calibration methods ensure reliable amyloid positron emission tomography (PET) visual reads across multiple raters. Substantial agreement is possible across readers using their preferred tools. Agreement is also substantial regardless of the amyloid PET tracer used. Scans with intermediate (10–40 Centiloid) quantitation have lower reader agreement. The calibration set will become a training tool for amyloid PET visual read studies.

Abstract Introduction: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease with limited treatment options and poor survival. This study explores how a medically supervised ketogenic diet (MSKD) impacts the gut microbiome and treatment response in patients with newly diagnosed metastatic PDAC receiving gemcitabine, nab-paclitaxel, and cisplatin chemotherapy. Methods: As part of a randomized Phase II trial, 32 evaluable patients (median age 65.9 years; 53% male), 16 were randomized to either MSKD or standard diet (SD) combined with chemotherapy. Stool samples were collected from 4 patients in the MSKD group (13 samples) and 8 patients in the SD group (23 samples). Deep shotgun metagenomic sequencing was conducted using NovaSeq (Illumina). Taxonomical and functional microbiome characterization was performed using MetaPhlAn 4.0 and HUMAnN 3.6 (The Huttenhower Lab, Harvard). Comprehensive bioinformatics analyses, using QIIME2, were performed to analyze microbiome composition and function over time. Results: Patients in the MSKD group showed better treatment responses overall. Microbiome profiles between the two groups remained distinct throughout therapy. Though not statistically significant due to sample size, MSKD patients showed lower alpha diversity (Shannon diversity; p-value=0.1339), likely reflecting reduced intake of fermentable fiber. Differential abundance analysis using the ANCOM-BC method revealed a significant enrichment of beneficial taxa in the MSKD group compared to the SD group (p&lt;0.05, log-fold change [lfc]≥2), including Akkermansia muciniphila (linked to improved response to immune checkpoint inhibitors; p=0.017931, q=1), Intestinimonas butyriciproducens (a short-chain fatty acid [SCFA] and butyrate producer; p=3.09E-05, q=0.017), and Streptococcus thermophilus (a supporter of gut mucosal health; p=1.15E-05, q=0.006). During the course of the study, only MSKD patients showed sustained increases in Roseburia hominis (SFCA/butyrate producer; p=3.94E-05, q=0.021) and Lacticaseibacillus rhamnosus (with anti-inflammatory and immune-modulating properties; p=7.28E-19, q=3.98E-16), along with a marked reduction in potentially pro-inflammatory Actinomyces spp.(p≤4.47E-05, q≤0.024). Functional profiling showed increased abundance of cancer-relevant microbial pathways in MSKD patients, including phosphatidate metabolism (PWY-7039; involved in lipid signaling and immune regulation; p=4.36E-04, q=0.20) and allantoin degradation (PWY-5705; linked to redox balance; p=9.16E-06, q=0.004). Conversely, L-ascorbate biosynthesis V (PWY-6415) was reduced (p=3.80E-04, q=0.17), likely due to decreased D-galacturonate substrate availability from fiber restriction. Conclusion: These findings suggest that an MSKD may beneficially modulate the gut microbiome in ways that support and enhance therapeutic response in patients with PDAC. Further validation in a larger cohort is warranted to confirm these results and improve analytical resolution. Citation Format: Keehoon Lee, Derek Cridebring, Gayle S. Jameson, Denis J. Roe, Erkut Borazanci, Diana L. Hanna, Caroline G.P. Roberts, Meredith S. Pelster, Richard C. Frank, Angela T. Alistar, Alan M. Miller, J. Erin Wiedmeier-Nutor, Sandra D. Algaze, Alison R. Zoller, Sarah J. Hallberg, Betsy C. Wertheim, Joshua D. Rabinowitz, Stephen Gately, Jennifer Keppler, Sunil Sharma, Drew W. Rasco, Daniel D. Von Hoff. Ketogenic Diet Modulates Gut Microbiome Composition and Enhances Treatment Response in Patients with Advanced Pancreatic Cancer: A Phase II Study [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research—Emerging Science Driving Transformative Solutions; Boston, MA; 2025 Sep 28-Oct 1; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl_3):Abstract nr B094.

Objectives: Electronic health records (EHR)-based triggers (eTriggers) have been used to study diagnostic errors in the emergency department (ED), often with suboptimal performance. Our objective was to investigate incremental value of multi-factor machine learning (ML) approaches to improve eTrigger performance. Methods: Patients presenting to an academic ED were categorized into trigger-positive and trigger-negative using standard trigger (T) definitions: (T1) ED return visits resulting in admission within 10 days; (T2) care escalation from the inpatient unit to the ICU within 24 hours; and (T3) deaths within 24 hours of admission. We trained and evaluated 6 supervised ML models. Results: A total of 124,053 consecutive encounters (5791 T-positive and 118,262 T-negative) were included. Among the T-positive, 4159 (72%) were associated with T1, 1415 (24%) with T2, and 217 (4%) with T3. The T-based positive predictive values (PPV) were 5.2% for T1, 8.2% for T2, and 6.5% for T3. ML models trained and evaluated on balanced training dataset and imbalanced test set had low classification performances (accuracy: 0.72–0.95; PPV: 0.00–0.16; F1-score: 0.00–0.23). Higher performances were observed in balanced test sets (accuracy: 0.80–0.97; PPV: 0.82–1.00; F1-score: 0.79–0.97). Comparing models trained on clinically annotated data with models trained on T-based labels identified other important factors. Conclusions: Utilizing machine learning to refine e-triggers slightly improves the identification of diagnostic errors, as evidenced by an increase in PPV values. We identified new potential factors contributing to ED diagnostic errors. These findings open new avenues to construct or modify more accurate e-triggers for diagnostic error identification.

Abstract BACKGROUND Tau‐derived cerebrospinal fluid (CSF) biomarkers correlate with amyloid‐beta (Aβ) plaques or tau tangles in Alzheimer's disease (AD). This study assessed the effects of long‐term anti‐Aβ antibodies on amyloid plaques, tau tangles, and CSF tau species to determine the relationships between them. METHODS A post‐hoc analysis of the DIAN‐TU‐001 trial (NCT01760005) examined 142 participants at risk for dominantly inherited AD randomized to solanezumab ( n = 50), gantenerumab ( n = 52), or placebo ( n = 40). High‐resolution mass spectrometry quantified CSF tau species over four years. RESULTS Phosphorylated tau (p‐tau) species (153, 181, 217, 231) increased early in preclinical AD but were reduced with gantenerumab‐mediated Aβ plaque reduction. Nearly a decade later, MTBR‐tau243 and p‐tau205 increased, showing no association with Aβ reduction, aligning with tau tangle pathology progression. DISCUSSION Initially changing soluble p‐tau species track Aβ plaque reduction, while ptau205 and MTBR‐243 reflect tau tangle pathology, informing different pathways of therapeutic strategies. Highlights p‐tau217 and p‐tau231 correlate with Aβ‐PET and respond to Aβ‐plaque lowering therapies. Aβ immunotherapy trials support a direct link between p‐tau changes and Aβ plaques Gantenerumab reduces Aβ plaques but does not affect tau NFT‐related biomarkers. Blood‐based p‐tau217 assays may provide a non‐invasive tool to monitor Aβ therapies. MTBR‐tau243 strongly correlates with tau PET and tracks NFT pathology progression. Further studies are needed to validate tau biomarkers for tracking NFT‐targeting therapies.

The FAITH! (Fostering African-American Improvement in Total Health) Cardiovascular Health and Wellness Program is more than a decade-long community-based participatory research initiative aimed at addressing cardiovascular health disparities among African-Americans in Minnesota. Founded in 2013, the program employs a culturally tailored, community-driven approach by partnering with African-American faith communities to promote cardiovascular health through education, digital health tools, and multilevel interventions targeting the social determinants of health. Grounded in community-based participatory research principles, FAITH! prioritizes equitable academic-community partnerships, co-learning, community capacity building, and shared ownership in all aspects of research and implementation. The program’s exemplary innovations include the NIH-funded FAITH! Trial, a randomized clinical trial, testing a mobile health intervention (the FAITH! App) co-created with the African-American community, and the Techquity by FAITH! study. Techquity by FAITH! evaluates the effectiveness of a culturally relevant, community-informed mHealth intervention supported by a Digital Health Advocate network to improve overall cardiovascular health and digital health literacy. During its evolution, FAITH! has addressed emergent public health crises, including the COVID-19 pandemic, by adapting programming to provide emergency preparedness resources, health education, and vaccine outreach. Key outcomes include sustainable church-based health ministries, increased research participation, and successful translation of research into practice. The program has also contributed to research workforce development by mentoring and training diverse early-career scholars and community leaders in community-based participatory research and cardiovascular health equity research. Lessons learned highlight the transformative impact of community-based participatory research in building trust, facilitating culturally relevant dissemination, and sustaining health equity initiatives. The FAITH! model demonstrates a scalable, community-led strategy for advancing cardiovascular health in underserved populations and provides a blueprint for future initiatives aiming to reduce racial health disparities.