Citations

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.

3014 Background: Macrocyclic next-generation tyrosine kinase inhibitors (TKIs) have transformed outcomes in ALK- and ROS1-positive NSCLC; such creatively designed medicines are similarly needed to improve outcomes in EGFR-mutant NSCLC. Using a novel, mutant-selective macrocyclic structure, BH-30643 was designed for super-potency against driver EGFRm, largely sparing wildtype (WT) EGFR, and with unique invulnerability to resistance from C797S with or without T790M. Here we report emerging first-in-human dose-escalation data from the SOLARA trial (NCT06706076). Methods: Phase 1 dose escalation used a BOIN design with backfill at potentially efficacious doses. Expansion cohorts targeted populations of interest. Patients (pts) had advanced NSCLC with EGFR and/or HER2 mutations detected on local testing (tissue or plasma). Measurable disease was required; asymptomatic untreated brain metastases (BM) were permitted. Objectives included safety, PK, and RECIST response rate (ORR). Plasma NGS was performed at baseline and on treatment. Results: As of 01/05/2026, 72 pts enrolled into dose escalation and backfill across 7 dose levels at a total daily dose of 20mg -160mg, median age 62, 44% Asian, 65% with history of BM, median of 3 prior lines of treatment (range 1-12). EGFR mutations included classical (38 pts), exon20ins (14 pts) and other/atypical (18 pts) or HER2 mutations (2 pts). Plasma exposures at doses of 40mg BID and above achieved > 10x coverage over target EC90 and exceeded exposure levels of most contemporary EGFR TKIs. Common TRAE ( > 10%) were WT EGFR-associated, including diarrhea (38%), rash (28%), fatigue (15%), stomatitis (13%), and were predominantly grade 1. Bilirubin elevation was seen in 26 pts (36%) related to off-target UGT1A1 inhibition (Gilbert’s-like). Grade 3 TRAE were seen in 15 pts (18%), most commonly bilirubin (8/15); DLTs included bilirubin increase and mucositis, occurring at doses ≥ 60mg BID. No pneumonitis was observed. Responses were observed across diverse EGFRm subsets, including in CNS. Including expansion pts, 28 pts enrolled with C797S on their most recent informative molecular testing (6 with concurrent MET+ or KRAS+), with 23 still on therapy. Of 17 with on-treatment scans, partial responses (confirmed or ongoing) were seen in 10 (59%); ORR was comparable with (50%) or without (66%) T790M. Of 9 pts with baseline C797S detected in ctDNA (3 with T790M), 7 had > 99% reduction of C797S VAF on treatment. Conclusions: Leveraging a novel macrocyclic scaffold, BH-30643 is the first TKI monotherapy to demonstrate clinical responses against C797S both with or without T790M. High plasma exposures combined with super-potency, CNS activity, and favorable safety offers potential for deep and durable EGFR inhibition. Enrollment into backfill and expansion cohorts is ongoing to better characterize activity in both TKI-naïve and resistant pts. Clinical trial information: NCT06706076 .

ABSTRACT Reversion mutations (REVs) restore homologous recombination repair (HRR) and confer resistance to PARP inhibitors (PARPi) in HR-deficient cancers. Yet, their prevalence, mechanisms, and biological constraints remain undefined. We analyzed genomic profiling of 609,464 tissue and liquid biopsy samples across multiple cancer types to delineate the pan-cancer landscape of REVs. REVs were identified in eight HRR genes, most frequently BRCA2 and BRCA1 and notably never in ATM or CHEK2 . REVs exclusively impacted truncating pathogenic variants, predominantly through large in-frame and exon-level deletions, associated with repetitive sequences. Conserved functional domains are relatively depleted of REVs. Structural modeling and functional studies support that exon-level deletions preserve critical domain architecture and confer PARPi resistance. The study establishes HRR reversion as a structurally permissive, yet evolutionarily constrained, resistance mechanism with implications on response, monitoring, and therapeutic strategy. One Sentence Summary Homologous recombination reversion evolves through structurally tolerated, microhomology-driven alterations that restore DNA repair under therapeutic selection across cancers.

Abstract Heterogeneous treatment effects (HTE) are key to precision medicine, but most real-world studies lack the scale and diversity needed to detect them. While multi-site analyses offer a potential solution, data-sharing constraints often prevent access to patient-level information across institutions. We introduce POLARIS, a federated framework for time-to-event target trial emulation. POLARIS converts each site’s weighted Cox risk function into a compact tensor shared once with the coordinating center, enabling lossless reproduction of pooled estimates without sharing patient-level data. We applied POLARIS across five U.S. health systems to study risk of gastrointestinal outcomes after GLP-1 receptor agonist (GLP-1RAs) initiation versus sodium-glucose cotransporter 2 inhibitors (SGLT2is) and dipeptidyl peptidase 4 inhibitors (DPP4is). Results showed that GLP-1RAs were consistently associated with higher risks of nausea and vomiting, particularly among men, individuals with higher baseline HbA1c (≥ 8.5%), and lipid therapy. POLARIS provides a scalable solution for distributed target trial emulation and fine-grained assessment of HTE across diverse health systems.

Abstract Context Prior reports of plasma estradiol concentrations and their reference ranges in postmenopausal women identified marked variation, in part due to assay method and body mass index (BMI). Objective To develop an international reference range for plasma estradiol in postmenopausal women, support accurate assessment of concentrations during systemic and local (eg, vaginal) estradiol therapy, and improve risk prediction for diseases, including osteoporosis, breast, and endometrial cancers. Methodology Estradiol concentrations were measured using primarily liquid chromatography-tandem mass spectrometry (LC-MS/MS) assays in 5 international cohorts of community-dwelling, postmenopausal women of primarily European ancestry aged 38-100 years who were not using exogenous estrogens (n = 7206). Measurements were harmonized to the Centers for Disease Control and Prevention (CDC) reference measurement procedure (RMP) by re-assaying a subset of samples for each cohort and generating recalibration equations. Reference intervals were determined for all women, non-obese women, and specific BMI categories. Results Estradiol concentrations from separate LC-MS/MS assays correlated closely with the CDC RMP, and harmonization minimized inter-assay variability. Estradiol concentrations correlated with BMI but not with chronological age. The reference range (2.5th-97.5th percentile) was 1.1-18.2 pg/mL (4.0-66.8 pmol/L) with median of 4.9 pg/mL (18.0 pmol/L) for all postmenopausal women and 1.1-12.5 pg/mL (4.0-45.9 pmol/L) with median of 4.1 pg/mL (15.1 pmol/L) for non-obese women (BMI < 30). Reference ranges increased progressively with higher BMI categories. Conclusion Cross-calibration of estradiol measurements with the CDC RP enabled the development of harmonized plasma estradiol reference ranges for postmenopausal women who were not using exogenous estrogens, suitable for future studies to establish clinical utility. Increasing obesity in postmenopausal women was associated with increasing estradiol concentration and BMI category-specific reference ranges.

Abstract Introduction While Large Language Models (LLMs) offer generative capabilities, generic models often lack domain-specific grounding, leading to hallucinations in high-stakes contexts. However, LLMs can serve as clinical decision support tools if augmented with specific domain data. This study evaluates the utility of Retrieval-Augmented Generation (RAG) applied to open-source LLMs, utilizing a curated knowledge base of authoritative sleep medicine textbooks, to quantify improvement in performance. Methods We evaluated four open-source models—Llama-70B, Llama-8B, Qwen-14B, and Qwen-235B, linked to a RAG system indexing five standard textbooks, including ICSD-3 TR. Models were tested on sleep board–style MCQs and clinical vignettes diagnostic accuracy. Performance was assessed across nine configurations derived from three factors: RAG pipeline complexity (Plain vs. Complicated), textbook preprocessing (Uncleaned vs. Cleaned/TOC-aligned), and retriever type (Dense-only vs. Hybrid). Metrics included MCQ Accuracy and the rates at which the correct diagnosis appeared as the top result or within the top 5 differential diagnosis lists for vignettes. Results RAG consistently outperformed the no-RAG baseline, yielding absolute performance gains of 5.6%–10.7% for MCQs and 8.1%–10.2% for the top diagnosis in cases across all models. For MCQs, Qwen-235B achieved the highest accuracy of 87.3% (vs. 81.7% baseline) using the Plain RAG configuration with Cleaned (TOC-aligned) Hybrid retrieval. Llama-70B followed with 83.6% in the same configuration. For case vignettes, Qwen-235B achieved a correct top diagnosis rate of 66.3% and a correct diagnosis rate within the top 5 differential diagnosis lists of 90.8% using Cleaned Hybrid retrieval configurations. Hybrid retrieval (Dense + Sparse) consistently surpassed Dense-only methods. Notably, while larger models benefited from Cleaned text, smaller models (e.g., Qwen-14B) achieved higher top diagnosis rates with Uncleaned text (57.1% vs. 51.0%), suggesting a dependency on redundant context in lower-parameter settings. Conclusion RAG significantly enhances knowledge performance of open-source LLMs in sleep medicine. Hybrid retrieval and curated, TOC-aligned knowledge bases yield optimal results for large models, whereas smaller models benefit from the redundancy of uncleaned text. These findings suggest that RAG systems can augment LLMs in domain specific knowledge for clinical decision support. Support (if any)

Study objectives To evaluate and compare the performance of two proprietary frontier large language models (LLMs), ChatGPT-5 and Grok-4, on diagnostic reasoning and foundational knowledge tasks within the specialty domain of sleep medicine. Methods The models were evaluated on two tasks: case-based reasoning using 79 clinical vignettes from the AASM Case Book of Sleep Medicine and knowledge assessment using 897 multiple-choice questions (MCQs) from board review materials. For vignettes, final diagnosis was scored by concept-level exact match, and differential diagnosis (DDx) was scored on a fixed top-5 output using concept-level matching with synonym normalization to compute precision, recall, and F 1-score. MCQ performance was the proportion correct. Inter-model performance was compared using the Mann–Whitney U test. Results Both models achieved high accuracy for final diagnosis (92.4% for both; 95% CI 86.4, 98.4) and MCQs (ChatGPT-5: 93.0%; Grok-4: 92.8%). However, performance on generating a comprehensive differential diagnosis was suboptimal, with modest F 1-scores for both ChatGPT-5 (0.55 ± 0.20) and Grok-4 (0.59 ± 0.20). There were no statistically significant differences in performance between the two models across any metric ( p > 0.05). Conclusions Frontier LLMs demonstrated high accuracy in sleep medicine tasks requiring knowledge recall and direct pattern recognition but showed more limited performance in complex clinical reasoning tasks such as generating a comprehensive differential diagnosis. These findings suggest that current general-purpose models may be more reliable for focused knowledge support than for broad hypothesis generation. Future studies should evaluate whether domain-adapted models or clinician-in-the-loop workflows can improve real-world diagnostic usefulness and safety.

53BP1 nuclear bodies are dynamic structures with properties resembling biomolecular condensates, but the molecular determinants that govern 53BP1 higher-order assembly at DNA double-strand breaks (DSBs) remain to be established. Here, we show that 53BP1 condensation is stimulated by phosphatidylinositol 3-phosphate (PI(3)P) in vitro through a highly specific interaction with its C-terminal tandem BRCT domain (tBRCT). Consequently, mutational inactivation of the 53BP1 tBRCT domain compromised PI(3)P binding and suppressed 53BP1 optodroplet formation in vivo. We further show that rapid 53BP1 clustering following DNA damage precedes its stable assembly on DSB-flanking chromatin, requires its tBRCT, and is suppressed by sequestration of nuclear PI(3)P. Taken together, our findings identify PI(3)P binding as a mechanism that promotes the formation and maturation of 53BP1 condensate-like assemblies on damaged chromatin.