Citations

Abstract The lung, one the largest branching organs in our body and vital for survival at first breath, is commonly known as the gas-exchange organ. Recent novel findings on lung sensing cells, molecules, and lung-brain crosstalk in the emerging discipline of interoception have highlighted the consideration of the lung as a sensory organ. Acknowledging the central importance of lung sensing to human health and disease, NHLBI convened a workshop to synthesize the past, current, and future of lung sensing research, with in-person presentations by ∼20 interdisciplinary experts and a large virtual audience. Here, we highlight the key topics discussed and summarize a blueprint for the future in this important field.

Objective Glaucoma and cancer are debilitating diseases with increasing global prevalence and morbidity. However, current literature lacks a systematic consolidation of their relationships and interactions. This systematic review aims to (A) summarize the association between intraocular/non-ocular cancers and their treatments with the prevalence and etiology of glaucoma, (B) explore glaucoma as a risk factor for complications or poor prognosis for intraocular cancer, and (C) explore the management of glaucoma secondary to cancer therapies. Methods A systematic search was performed from inception to July 2025 across three databases with variants of ‘cancer’ and ‘glaucoma’ as search terms. Findings were narratively synthesized. Results Of 8,103 identified studies, 44 were included in this review. Eighteen studies reported increased glaucoma prevalence amongst intraocular and non-ocular cancer patients. Fifteen studies suggested increased risk of regional invasion, metastases, and high-risk histopathologies when intraocular cancers co-occurred with glaucoma. Corticosteroids in cancer therapy have been linked to intraocular pressure (IOP) elevation, while androgen deprivation therapy was associated with lowered glaucoma risk. Conclusion Given the relationship between glaucoma and intraocular/non-ocular cancers, strategies to monitor and manage glaucoma risk following cancer diagnosis and/or therapy may be considered. Glaucoma may be an early sign of complications in intraocular cancers.

Abstract Interstitial cells of Cajal (ICC) regulate gastrointestinal motility by generating electrical slow waves that orchestrate downstream calcium (Ca 2 + ) waves and coordinate smooth muscle contractions. A reduced ICC number has been reported in diabetic gastroparesis patients and in mouse models of delayed gastric emptying (DGE). However, functional changes in ICC propagating across the gastric regions in intact stomach are not well understood. The aim of this study was to develop an imaging approach to visualize ICC Ca 2+ waves in mouse stomach and determine spatiotemporal changes in mice with DGE. Tamoxifen‐treated B6.GCaMP5‐KitCreERT2 female mice were used as non‐diabetic controls (Non‐Db), while mice treated with streptozocin to induce diabetes were categorized as having normal (Db‐NGE) or delayed (Db‐DGE) gastric emptying based on emptying of solids. The ICC Ca 2+ network was imaged from excised intact mouse stomachs and subsequently opened along the lesser curvature and pinned flat. ICC Ca 2+ waves typically propagated along the greater curvature from the fundus–corpus line toward the antrum. The propagation length of ICC Ca 2+ activity was significantly decreased in Db‐DGE compared to Non‐Db and Db‐NGE and correlated to longer GE times. There was also a decrease in frequency, and the velocity was significantly faster in stomachs from Db‐DGE compared to Non‐Db and Db‐NGE. All experimental groups exhibited similar proportions of aberrant Ca 2+ propagation patterns (e.g., retrograde waves), but ectopic initiation only occurred in Db‐DGE stomachs. Thus, DGE is possibly driven by dysfunction in Ca 2+ activity in the ICC network that propagates rapidly over short distances, resulting in uncoordinated, non‐phasic muscle activity. image Key points Dysfunction of the interstitial cells of Cajal (ICC) has been implicated in diabetic gastroparesis but the changes in spatiotemporal properties of ICC network activity are not known. We developed an ex vivo Ca 2+ imaging approach to visualize ICC network activity across the entire stomach and determined changes in ICC Ca 2+ activity in a diabetic mouse model of delayed gastric emptying (GE). Decreased frequency and increased velocity of ICC Ca 2+ activity was observed in stomachs of diabetic mice with delayed GE. Ectopic initiation was a key feature associated with delayed GE. The propagation length of ICC Ca 2+ activity was inversely correlated to GE times and significantly reduced in stomach preparations from diabetic mice with delayed GE.

e16535 Background: RMC is a rare and highly aggressive malignancy that predominantly affects young individuals with sickle hemoglobinopathies. Due to its rarity, no validated prognostic models exist to guide clinical decision-making. We aimed to develop and internally validate a prognostic model for patients with RMC using routinely available clinical and laboratory variables. Methods: We analyzed a single-institution cohort of patients with RMC. Candidate variables were identified based on biological plausibility and represented in a directed acyclic graph. Missing data were handled via multiple imputation by chained equations ( m = 50). Variables were ranked using elastic net Cox regression ( α = 0.5, λ = λ min ) with stability selection derived from 100 bootstrap resamples per imputed dataset. Predictors achieving > 60% selection frequency were retained for a nested parsimony analysis. Bootstrap internal validation ( B = 2000) estimated optimism-corrected discrimination and calibration performance, with the calibration slope applied as global shrinkage to penalize final coefficients for overfitting. Clinical utility was evaluated via decision curve analysis (DCA) at 18- and 24-month horizons. Results: Among 180 patients (median age 29; IQR 23–37), 142 deaths occurred with a median follow-up of 12.4 months. The final model included four predictors (Table). The optimism-corrected c-index was 0.667 (optimism = 0.009), and the calibration slope was 0.964, indicating minimal overfitting. Calibration plots showed excellent predicted-observed agreement at 12, 18, 24, and 36 months. DCA showed net benefit across threshold probabilities of 10%–75% at 18 months and 10%–80% at 24 months compared to default strategies. In sensitivity analysis, inclusion of TP53 mutation status improved discrimination ( c -index 0.686) and model fit ( ΔAIC −10.6). An interactive web-based risk calculator was developed to facilitate clinical implementation. Conclusions: This study presents the first internally validated prognostic model for RMC, demonstrating acceptable discrimination and excellent calibration using routinely available variables. By stratifying patients into distinct risk groups, this model may inform treatment intensity—guiding escalation to multi-agent regimens or sequential chemotherapy cycling in high-risk patients, while identifying lower-risk patients who may benefit from de-escalation strategies such as metastasis-directed therapy for oligometastatic disease or consideration of cytoreductive nephrectomy. External validation is warranted. Variable Time Ratio 95% CI p value ECOG performance status 0.64 0.53–0.77 <0.001 Distal (non-retroperitoneal) lymph node metastases 0.69 0.52–0.92 0.011 Neutrophil-to-lymphocyte ratio 0.98 0.94–1.02 0.25 Corrected calcium (mg/dL) 0.77 0.56–1.06 0.10 Sensitivity Analysis Only TP53 Mutation 0.63 0.36-1-10 0.10

e16510 Background: Early-onset RCC may reflect distinct biology and hereditary predisposition, yet data on stage-specific clinical features and outcomes remain limited. We comprehensively evaluated age-stratified, stage-specific clinical features and survival outcomes using the National Cancer Database. Methods: Adults with histologically confirmed RCC diagnosed between 2004 and 2022 were analyzed. Patients were categorized into three groups by age at diagnosis: early-onset ( < 40 years), middle-aged (40–50 years), and late-onset ( > = 50 years). The sociodemographic and clinical characteristics, comorbidities, histology, and treatment patterns were compared using descriptive statistics. Overall survival (OS) was evaluated using Cox proportional hazards models, adjusting for the aforementioned variables. Stage-specific analyses were conducted, including a metastatic disease cohort. Results: Among 742,114 patients, 4.3% were classified as early-onset, 10.9% as middle-aged, and 84.8% as late-onset. Overall, 12.6% presented with metastatic disease. Compared with late-onset, early-onset patients were more likely to be from racial minority populations (non-White: 16.9 % vs. 20.2 % in late-onset), uninsured, and had fewer comorbidities (Charlson–Deyo score 0: 85.2% vs. 65.2%). Early-onset RCC was characterized by a lower proportion of papillary RCC (8.9% vs. 12.5%) and higher proportions of clear cell (54.9% vs. 50.8%) and chromophobe RCC (9.3% vs. 4.5%) than late-onset RCC and more likely to undergo partial nephrectomy (50.4% vs. 30.2%). They also presented with earlier-stage disease, with lower rates of stage III (7.4% vs. 10.2% vs. 13.4%) and stage IV disease (5.4% vs. 8.9% vs. 13.5%) compared with middle-aged and late-onset groups. Among patients with metastatic disease, early-onset RCC demonstrated higher minority representation (30.8% vs. 14.1%) and a higher prevalence of non-clear cell histology (70.6% vs. 58.1%). In multivariable analysis, compared with early-onset RCC, middle-aged (HR 1.44, 95% CI 1.39–1.50; P < 0.001) and late-onset patients (HR 2.83, 95% CI 2.74–2.93; P < 0.001) experienced significantly worse OS. However, among metastatic disease, this survival advantage was attenuated. Early-onset patients had similar OS to middle-aged patients (HR 0.99, 95% CI 0.93–1.05, p = 0.69) and late-onset patients only had a modestly worse OS than the early-onset group (HR 1.09, 95% CI 1.03–1.15 p = 0.003). Conclusions: Early-onset RCC was associated with more favorable baseline characteristics, earlier stage at diagnosis, and higher utilization of nephron-sparing nephrectomy, corresponding to improved OS. However, this survival advantage diminishes in metastatic disease despite better baseline health, highlighting stage-dependent differences in outcomes and suggesting distinct histologic patterns in advanced early-onset RCC.

e16017 Background: Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer and remains one of the deadliest malignancies worldwide, largely due to late-stage diagnosis. Early-stage PDAC is frequently asymptomatic, limiting opportunities for timely detection and intervention. We aimed to develop prognostic models using routinely acquired pre-diagnostic clinical data to identify individuals at high risk for PDAC prior to clinical manifestation. Methods: We conducted a retrospective study of patients treated at Mayo Clinic sites in Rochester, MN; Phoenix, AZ; and Jacksonville, FL between January 2011 and February 2023. The cohort included 1,151 patients with PDAC and 3,745 noncancer controls. CT scans were standardized to axial abdominal acquisitions with slice thickness between 0.8–3.0 mm. Radiology reports were de-identified, normalized, and parsed into structured sections (Indications, Findings, Impression), with an additional pancreas-specific section aggregating pancreas-related sentences. Demographic and clinical variables, e.g., age, sex, race, etc., were encoded using a templated sentence representation. All textual inputs were embedded using a Sentence-BERT model. A multimodal deep learning survival model was developed to integrate CT imaging, radiology report embeddings, and demographic features. The model was trained using a negative log-likelihood loss to estimate patient-specific PDAC risk scores. Model performance was assessed using the concordance index (C-index). Internal validation included patients from MN and AZ sites, while external validation used the FL cohort. Results: We evaluated unimodal (imaging, text, and demographics) and multimodal inputs. Fusion of imaging, radiology report, and demographic features achieved the highest performance, with internal and external validation C-indices of 0.885 (95% CI, 0.856–0.908) and 0.751 (95% CI, 0.719–0.783), respectively. Subgroup analysis by tumor location demonstrated differential performance. For pancreatic head tumors, internal and external C-indices were 0.916 (95% CI, 0.841–0.960) and 0.778 (95% CI, 0.730–0.823). For pancreatic body tumors, C-indices were 0.954 (95% CI, 0.897–0.997) internally and 0.929 (95% CI, 0.897–0.953) externally. For pancreatic tail tumors, internal and external C-indices were 0.903 (95% CI, 0.830–0.974) and 0.789 (95% CI, 0.689–0.874). Conclusions: A multimodal deep survival model leveraging pre-diagnostic CT imaging, radiology report embeddings, and demographic data can effectively identify individuals at high risk for PDAC prior to clinical diagnosis. Differences in performance were observed across pancreatic head, body, and tail tumors. This approach highlights the potential of opportunistic cancer risk stratification from routine imaging to enable earlier detection and targeted intervention strategies.

ABSTRACT Background and Purpose White matter hyperintensities (WMH) are a core neuroimaging marker of cerebral small vessel disease (CSVD). Sleep apnoea (SA) is a recognized vascular risk factor, but its associations with regional WMH burden, short‐interval WMH change and cognitive performance in population‐based cohorts remain incompletely defined. We examined these associations in the UK Biobank imaging cohort. Methods We conducted cross‐sectional analyses with an exploratory longitudinal subset in propensity score–matched cohorts excluding major neurologic and cerebrovascular disease before imaging. SA was identified from hospital records and self‐reports prior to brain magnetic resonance imaging (MRI). Head‐size–normalized WMH volumes were analysed on the log1p scale using multivariable linear regression with robust standard errors. Total WMH was the primary outcome; periventricular WMH (PWMH), deep WMH (DWMH) and cognitive measures were secondary outcomes. Mediation analyses evaluated WMH as a mediator of SA–cognition associations. Results In cross‐sectional analyses ( N = 12,890; mean age, 67.4 years; 27.2% women), SA was associated with greater WMH burden. Total WMH volume was 10.7% higher among participants with SA (95% CI, 5.0%–16.6%; p < 0.001). PWMH and DWMH volumes were 10.0% (95% CI, 4.7%–15.7%; q < 0.001) and 15.7% (95% CI, 7.1%–25.1%; q < 0.001) higher, respectively. SA was associated with modestly worse cognitive performance, with effect estimates attenuated after adjustment for WMH burden and cardiometabolic conditions. Mediation analyses indicated that WMH burden, particularly PWMH, mediated associations between SA and cognitive performance. In the longitudinal subset ( N = 698; median follow‐up, 2.26 years), no significant between‐group differences were observed in annualized WMH change. Conclusions In this large population‐based imaging cohort, SA was associated with higher WMH burden, a key neuroimaging marker of CSVD. Cognitive differences were modest, but WMH burden, particularly PWMH, consistently mediated associations between SA and cognitive performance. Longer term studies are needed to clarify temporal relationships and potential treatment effects.

Autoimmune diseases arise when B and T lymphocytes lose tolerance to self. Yet in most disorders, the underlying molecular determinants, including autoantibodies, epitopes and lymphocyte clones that drive tissue injury remain undefined. Rapid-onset obesity with hypothalamic dysfunction, hypoventilation and autonomic dysregulation (ROHHAD) is a rare and often fatal pediatric neuroendocrine syndrome with strong evidence of antigen-driven paraneoplastic autoimmunity, including association with the intracellular autoantigen ZSCAN1. However, the effector immune circuit and the epitope-level determinants operating within the hypothalamus and brainstem have remained unknown. To address this challenge in ROHHAD and more broadly in autoimmune disease, we developed the Autoimmune Epitope and immunoGlobulin/Immune-receptor identification System (AEGIS), an integrated framework that links immune repertoires to their cognate self-epitopes. AEGIS combines B cell and T cell receptor profiling from sites of tissue injury with high-resolution epitope mapping, direct sequencing of antigen-specific autoantibodies, in silico antibody-antigen folding, selection, and T cell antigen discovery. Applied to a deeply phenotyped child with ROHHAD, AEGIS revealed a compartmentalized, clonally restricted immune response in which brain-deposited IgG and expanded cerebrospinal fluid B cell and CD4 T cell clonotypes converged on shared ZSCAN1 epitopes, resolved to minimal determinants and peptide-MHC ligands. These findings provide a clone- and epitope-linked mechanistic map of ROHHAD autoimmunity and establish a generalizable framework for identifying candidate pathogenic clones and antigens across diverse autoimmune diseases.