Citations

Abstract Treatment resistance and metastases occur in 10–20% of patients with invasive lobular carcinoma (ILC), the most common special histological subtype of breast cancer. ILC metastasizes to the ovary more frequently than no special type (NST) tumors, also known as invasive ductal carcinoma (IDC). To characterize the genomic landscape of breast cancer ovarian metastases, we analyzed 15,613 local breast cancers, 22,010 non-ovarian metastases, and 246 ovarian metastases sequenced using FoundationOne®CDx or FoundationOne® assays. Ovarian metastases had enriched CDH1 , PIK3CA , and TBX3 mutations and depleted TP53 and MYC alterations relative to local breast cancers, with additional depletion of ESR1 mutations compared to non-ovarian metastases. CDH1 mutations were less frequent in ovarian metastases (47%) than local ILC (81.3%), with reduced 16q loss (64% vs 84%), indicating that ovarian metastases also arise from non-ILC tumors. We extended these findings to a UPMC cohort of 27 ovarian metastases (13 ILC, 8 IDC, 6 mixed ductal-lobular carcinoma) with patient-matched primary tumors in most cases. In both cohorts, patients with ovarian metastases were significantly younger than those with other metastatic sites. In the UPMC cohort, the most frequent mutations were in PIK3CA , CDH1 , KMT2C , FOXA1 , and RUNX1 . Transcriptomic analysis identified upregulated G protein-coupled receptor (GPCR) pathways, including metabotropic glutamate receptor signaling. Functional studies showed that calcium-sensing receptor (CaSR), a GPCR overexpressed in ovarian metastases, drives MEK/ERK-dependent migration and F-actin reorganization in ILC cell lines, enhanced by estrogen and blocked by calcilytic, MEK, or anti- estrogen treatment. Our findings inform future therapeutic targeting of ovarian metastasis.

ABSTRACT Purpose Despite 5‐year survival rates of over 90% among children and adolescents/young adults (CAYAs) with classic Hodgkin lymphoma (cHL), 15%–20% relapse after frontline therapy. Prior analysis of frontline Children's Oncology Group (COG) clinical trials demonstrated that, despite similar rates of relapse, non‐Hispanic Black (NHB) and Hispanic (vs. non‐Hispanic White [NHW]) patients experienced higher post‐relapse mortality. It is unknown whether post‐relapse disparities persist when second‐line treatment is delivered in a cooperative group trial setting. We examined overall survival (OS) by race and ethnicity in CAYAs enrolled in COG trials for relapsed/refractory (r/r) cHL. Methods A pooled analysis of individual‐level data from CAYAs (≤ 29 years) receiving therapy for r/r cHL on COG clinical trials (2001–2016) was conducted. The Kaplan–Meier method estimated 3‐year OS by racial and ethnic groups. Cox regression models examined associations of race and ethnicity and OS, adjusted for age, insurance, first versus ≥2 relapse, and time from initial diagnosis to relapse trial enrollment. Results Among 175 CAYAs treated on COG trials for r/r cHL (5.7% Asian or Pacific Islander, 14.9% Hispanic, 14.3% NHB, 61.7% NHW, 3.4% other), at median follow‐up of 4.9 years, 3‐year OS was 82.1% (95% confidence interval [CI], 75.3%–87.1%) and did not differ by race and ethnicity ( p = 0.36). In multivariable analyses, shorter time from diagnosis to relapse trial enrollment ( p = 0.01) and ≥2 relapses (vs. first, p = 0.004) conferred worse OS, with no significant effect of race and ethnicity ( p = 0.43). Conclusion Post‐relapse survival did not differ by race and ethnicity among CAYAs enrolled in COG trials for r/r cHL, suggesting access to clinical trials may mitigate OS disparities.

BACKGROUND: Surgeons and ostomy nurses receive a high volume of stoma photos from patients. OBJECTIVE: This study aimed to develop and validate an automated and scalable artificial intelligence pipeline for identification and triage of patient-submitted intestinal ostomy photos. DESIGN: Retrospective derivation and validation study with stakeholder engagement to guide model design. Clinical teams reviewed photos in duplicate and categorized them into: (a) obstructed view, (b) healthy stoma, (c) suitable for conservative management, or (d) requiring in-person review. Pre-trained neural networks including MobileNetV4, ResNet50, ViT and CLIP-ViT were fine-tuned with 5-fold cross-validation. SETTINGS: Nine Mayo Clinic hospitals (2019–2022). PATIENTS: Adult patients (≥18 years) undergoing surgery who submitted images within 30 days after surgery. MAIN OUTCOME MEASURES: Model performance was evaluated with area under the receiver operator curve, precision, recall, and F1-scores. RESULTS: In this study, 538 photos of abdominal ostomies were sent in by 191 patients (median age 52 years, IQR 40–63; 60.4% female). Expert consensus triaged 236 (43.9%) photos as having an obstructed view, 30 (5.6%) as healthy, 177 (32.9%) for conservative management, and 95 (17.7%) for in-person review. All models achieved area under the receiver operator curve >0.97 for identifying stomas. The CLIP-ViT model performed best at triage (macro- area under the receiver operator curve 0.94 ± 0.06; F1 0.77 ± 0.10). End-to-end detection and triage using CLIP-ViT achieved area under the receiver operator curve of 0.99 ± 0.01, precision of 0.87 ± 0.08, recall of 0.93 ± 0.04, and F1 of 0.89 ± 0.07. Attention maps showed that models focused on stomas to determine classification. LIMITATIONS: Low sample size and lack of prospective validation. CONCLUSIONS: A vision language model pipeline accurately detected and triaged patient-submitted ostomy photos. Prospective evaluation is now needed to support integration into multidisciplinary digital workflows. See Video Abstract .

Most genetic variants associated with complex traits are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterized 14,324 RNA-sequencing samples from the Trans-Omics for Precision Medicine program and performed expression and splicing quantitative trait locus (e/sQTL) analyses in six tissues and cell types, including whole blood ( n = 6454) and lung ( n = 1291). We detected tens of thousands of secondary cis-e/sQTLs, showing that secondary cis-e/sQTL discovery remains unsaturated. We fine-mapped UK Biobank–derived genome-wide association study (GWAS) signals from 164 traits and identified e/sQTL colocalizations for 10,611 GWAS signals, including 7096 that colocalize with secondary e/sQTLs. Our results suggest that even larger e/sQTL analyses will uncover additional secondary e/sQTLs, further benefiting GWAS interpretation.

Abstract Background Failure to rescue (FTR) is a key driver of postoperative mortality and reflects a hospital’s ability to recognize, escalate, and treat complications. Although FTR varies substantially between hospitals, the hospital characteristics that underpin this variation are inconsistently described. The aim of this study was to synthesize evidence on hospital-level factors associated with FTR after postoperative complications across surgical populations and health systems. Methods A systematic review of observational studies evaluating associations between hospital-level characteristics and FTR in surgical patients was undertaken. MEDLINE, EMBASE, and Scopus were systematically searched on 17 July 2024 and updated to 31 December 2025. Hospital factors were classified into structural, staffing, and system domains. Where three or more non-overlapping studies reported adjusted estimates in comparable formats, random-effects meta-analyses were performed; otherwise, findings were summarized narratively. Methodological quality of included studies was assessed using the ROBINS-I tool (version 2). Results A total of 111 studies encompassing over 137 million patients and 301 hospital factors were included. Meta-analyses demonstrated lower FTR rates in larger hospitals (odds ratio 0.85, 95% confidence interval 0.74 to 0.97), hospitals with greater intensive care unit capacity (odds ratio 0.80, 0.71 to 0.90), and teaching hospitals (odds ratio 0.88, 0.83 to 0.93). Better nursing resources were consistently associated with lower FTR, including patient-to-nurse ratios (odds ratio 1.07, 1.03 to 1.10), higher nurse education (odds ratio 0.95, 0.91 to 0.99), and more favourable work environments (odds ratio 0.93, 0.90 to 0.95). Safety-net hospital status was associated with higher FTR (odds ratio 1.22, 1.03 to 1.45). Substantial heterogeneity was observed across most analyses. Conclusion Hospital-level structural, staffing, and system characteristics are associated with variation in FTR. Postoperative mortality is closely linked to institutional capacity to detect and manage complications, underscoring the importance of adequate resourcing and system organization to improve surgical outcomes.

Abstract Body surface gastric mapping (BSGM) enables non-invasive measurement of gastric electrophysiology, but the signals are approximately 100 times weaker than cardiac potentials and overlap spectrally with motion artifacts, necessitating labor-intensive manual review that limits clinical scalability. We present an uncertainty-aware deep learning framework combining a signal reconstruction network with a parallel uncertainty estimation network to automate artifact correction in high-resolution BSGM. Models were trained on 2,398 multihour, 64-channel recordings from 27 international clinical sites using weak supervision, a physiology-aware loss function, and uncertainty-gated quality control. In an independent cohort of 127 patients, the system achieved relative reductions of 39% in signal reconstruction error, 9% in total data removed, and 23% in amplitude–movement correlation compared with the industry-standard Wiener filter. Improved signal fidelity altered automated clinical phenotyping in 7% of patients by recovering previously obscured gastric rhythms. Uncertainty-aware deep learning enables reliable automated artifact correction in body-surface gastric mapping, improving signal fidelity and enabling scalable clinical interpretation. The system is FDA-cleared (510(k) K252504) and deployed in clinical practice, demonstrating that data-driven artifact correction can meet regulatory requirements for medical devices and reduce dependence on specialist manual review.

Background Irritable bowel syndrome (IBS) is a complex disorder of gut-brain interaction, with heterogeneous symptoms, no available biomarkers and limited pathogenetic insight. Objective To identify genetic risk factors and actionable mechanisms for future clinical translation in IBS. Design We conducted a genome-wide association study (GWAS) meta-analysis of IBS in 2 775 539 individuals from 22 biobanks. IBS genetics was studied across multiple ancestries, different case definitions and symptom-related subtypes. Heritability and genetic correlations with other traits were estimated, and Mendelian randomisation was used to test causal relationships. GWAS data were functionally annotated and fine-mapped to prioritise tissues, cell types, pathways, candidate genes, specific mechanisms and druggable targets. Results Significant heritability was only detected in individuals of European ancestry, with near-identical genetic architecture across case definitions. Genetic correlations with GI, psychiatric and cardiometabolic traits were observed, including causal relationships with triglyceride (TG) levels. Functional annotation of IBS risk loci highlighted cell types and pathways relevant to brain, enteric neuro-glial and cardiometabolic domains, as well as actionable targets like GCKR, a regulator of TG metabolism. Druggability analyses converged on cardiometabolic mechanisms, including TG modulation. IBS polygenic risk scores were derived and showed a significant association with case status in an independent case-control dataset, supporting further evaluation in external population-based and clinically ascertained cohorts. Conclusions This study provides the most comprehensive assessment of IBS genetics to date, demonstrating reproducible polygenic inheritance. We link IBS risk to convergent neurogastrointestinal and novel cardiometabolic mechanisms, highlight specific biological pathways and actionable mechanisms and outline translational opportunities emerging from integrated computational analyses.

Context.— The diagnosis and characterization of well-differentiated neuroendocrine tumors (WDNETs) on cytology is challenging, with recognized pitfalls that may have therapeutic and prognostic implications. Objective.— To analyze data curated by the College of American Pathologists educational slide program for accuracy in the cytologic diagnosis of WDNET. The current state of cytologic diagnosis of WDNET is also reviewed for educational purposes. Design.— The study cohort included non-gynecologic cytology slides reviewed by participants in the College of American Pathologists Non-Gynecologic Cytopathology Education program. Individual responses for cytotechnologists or cytologists (CT) and pathologists were collated for WDNET. The data were analyzed for concordance with the correct general diagnosis and concordance with the correct reference diagnosis. The exact reference diagnosis available for each site was “pancreatic neuroendocrine tumor,” “liver, well/moderately differentiated neuroendocrine tumor,” and “lung, well/moderately differentiated neuroendocrine tumor.” Performance measures were assessed. Results.— The WDNET analysis includes 8941 responses from 1382 laboratories. The selection of the general diagnosis of “malignant” or “suspicious for malignancy” was greater than 90% in all body sites. Pathologists correctly identifying WDNET was highest in the pancreas (2501/2738, 91.3%) compared with the lung (805/1019, 79.0%) and liver (1444/1966, 73.4%). Pathologists had better concordance with the diagnosis of WDNET in all sites than CTs ( P < .001). Conclusions.— This large study, encompassing pathologists and CTs, confirms that although participants can identify WDNET on cytology, opportunities for greater accuracy and education persist. The most common incorrect response in the pancreas was adenocarcinoma, while the most common misdiagnosis was small cell carcinoma in the lung and liver.

Cercospora leaf spot (CLS) is a destructive disease of sugar beet (Beta vulgaris ssp. vulgaris L.) for which resistance conferred by the gene BvCR4 has been introgressed from sea beet (B. vulgaris ssp. maritima). BvCR4-mediated resistance has been broadly deployed to manage CLS globally in sugar beet; however, continuous implementation exerts strong selection pressure, increasing the risk of disease outbreaks due to resistance-breaking C. beticola populations. This study aimed to identify BvCR4 variants in public B. vulgaris spp. germplasm to assess their genetic and structural diversity. Polymerase chain reaction screening of 589 public B. vulgaris spp. germplasm detected BvCR4 homologs in 32 accessions with diverse responses to CLS including historically relevant sugar beet lines represented in breeding programs and Mediterranean sea beet populations of diverse genetic backgrounds. Analysis of the genomic sequences revealed higher diversity in sea beet compared to sugar beet. Additionally, population genetic analysis indicated that BvCR4 homologs in sugar beet likely originated from sea beet populations in Italy and Greece. We identified historical cultivated materials carrying full proteins encoded by BvCR4 alleles and delineated geographic regions where sea beet populations harbor BvCR4 homologs that may be useful in breeding programs. Structural variation was largely circumscribed within leucine-rich repeat domains, although CLS resistance phenotyping was not associated with specific polymorphisms, suggesting BvCR4-mediated resistance may rely on interactions with other co-receptors. This study provides resources for sugar beet improvement by enabling the identification of BvCR4 homologs in diverse germplasm and disclosing materials with potentially novel resistance.

Abstract Background Poor operating room (OR) ergonomics poses risk of injury to OR staff, worsening patient outcomes and threatening workforce wellness and sustainability. How OR staff navigate ergonomic barriers in the interdisciplinary team environment was examined in this qualitative study. Methods Semi-structured, open-ended interviews of surgeons, anaesthesiologists, and OR nurses were conducted at a single institution using a sociomaterial approach with interview-to-the-double. Transcripts were coded by two independent researchers. Themes in the data were outlined using the System Engineering Initiative for Patient Safety (SEIPS) 2.0 framework. Results Five major themes were identified. First, physical environment issues creating cognitive and physical frictions, such as tripping hazards and poor room layouts. Second, influence of social positionality, with hierarchy by role and experience and social dynamics leading to a differential capacity to adjust. Third, team collaboration, with lack of interdisciplinary work and communication and high staff turnover. Fourth, burden of self-initiated workarounds, outlining conflicts between system/organizational issues and individual solutions. Fifth, institutional support, with lack of leadership engagement. Participants suggested solutions including accommodations to foster a collaborative approach to managing discomfort in the OR and new team communication tools. Conclusion Ergonomic barriers were described within the work system of the SEIPS 2.0 framework. Social positionality and differential levels of agency, as well as lack of team collaboration and misperceptions of others’ roles, were central to ergonomic challenges. Conflicts between problems lying with the system/organization and solutions being left to individuals were also central to challenges to optimal OR ergonomics.