Citations

Abstract Introduction E-cigarette use has risen dramatically in the past decade, accompanied by recognition of e-cigarette or vaping-use associated lung injury (EVALI). Although increasingly reported, the pathophysiology of EVALI remains poorly defined, and its clinical presentation and diagnostic evaluation are often nonspecific. Clinicians should maintain a high index of suspicion given its varied manifestations. We describe a young patient with EVALI complicated by histopathologic evidence of secondary pulmonary alveolar proteinosis (PAP), progressing to severe hypoxemic respiratory failure that ultimately required bilateral lung transplantation. Case Presentation A 28-year-old man with a nine-year history of vaping nicotine and THC-containing hash oil presented with chronic hypoxemic respiratory failure requiring BiPAP. One year earlier, he developed digital clubbing, followed by progressive cough and exertional dyspnea. Initial chest CT showed diffuse centrilobular ground-glass opacities without septal thickening, thought to represent hypersensitivity pneumonitis. Despite vaping cessation several months prior to presentation, his symptoms progressed rapidly, and he required high-flow supplemental oxygen (Fi02 80% at 50 L/min) within weeks of admission. Bronchoscopy with bronchoalveolar lavage and biopsy demonstrated focal organizing pneumonia, pigmented foamy macrophages, and eosinophilic acellular debris within alveoli, consistent with pulmonary alveolar proteinosis (PAP). Cultures and cytology were negative for infection or malignancy. Autoimmune serologies were unrevealing, and no alternative exposures were identified. Due to worsening hypoxemic respiratory failure and lack of response to vaping cessation, steroids, and nebulized sargramostim (recombinant human granulocyte-macrophage colony-stimulating factor), he underwent bilateral lung transplantation. Whole lung lavage was considered but not pursued due to concern for further deterioration. Explant pathology showed interstitial fibrosis with a nonspecific interstitial pneumonia pattern and extensive PAP-like reaction with cholesterol clefts and small airway injury. Discussion EVALI encompasses a broad spectrum of radiographic and histopathologic findings, but secondary pulmonary alveolar proteinosis (PAP) is rarely reported. Diagnostic criteria include e-cigarette use within 90 days and pulmonary infiltrates or ground-glass opacities, with exclusion of malignant, autoimmune, and infectious causes. Although most often associated with ground-glass opacities and organizing pneumonia with diffuse alveolar damage, the pathology of EVALI is variable and poorly understood, further complicated by heterogeneity in vaping exposures. This case highlights PAP as a potential manifestation of EVALI, raising the possibility that impaired alveolar macrophage function and surfactant clearance contribute to hypoxemia in severe disease. Clinicians should maintain a high index of suspicion for EVALI and be aware of its diverse histopathologic spectrum. Continued research is needed to clarify underlying mechanisms and guide management. This abstract is funded by: None

Abstract Background Older adults remain underrepresented in prospective trials of immunotherapy for advanced lung cancer. To estimate pembrolizumab adverse events, we conducted a multicenter, nonrandomized, open-label phase 2 trial of oncologist-choice first-line pembrolizumab with or without chemotherapy for older adults with advanced lung adenocarcinoma. Methods Alliance for Clinical Trials in Oncology A171901 enrolled patients aged 70 years and older with stage IV or recurrent lung adenocarcinoma starting oncologist’s choice of first-line pembrolizumab with or without carboplatin and pemetrexed. The primary endpoint was the proportion of patients experiencing a solicited grade 3 or greater adverse event within 6 months. Secondary endpoints included overall survival, quality of life, and association of a geriatric assessment toxicity risk score with severe adverse events. Results Among 95 evaluable patients, 43 (45.3%) received pembrolizumab and 52 (54.7%) received pembrolizumab plus chemotherapy. Median age was 77 years (range = 70-92 years); 11.6% had an E Performance Status of 2 or higher. During 6 months of treatment, 25.6% (95% CI = 13.5% to 41.2%) experienced a solicited grade 3 or greater adverse event in the monotherapy group and 42.3% (95% CI = 28.7% to 56.8%) in the combination group. Median overall survival was 16.4 months (95% CI = 10.1 to not estimable) with monotherapy and 29.9 months (95% CI = 16.4 to not estimable) with combination therapy. Quality of life worsened during treatment. The geriatric assessment toxicity risk score was not associated with severe adverse events with pembrolizumab with or without chemotherapy. Conclusions Older adults with advanced lung adenocarcinoma receiving pembrolizumab with or without chemotherapy had comparable adverse event rates to those in prior registration trials that excluded medically frail patients. These findings can inform shared decision making and support inclusion of older adults in future trials. Clinical Trial NCT04533451 (https://clinicaltrials.gov/study/NCT04533451)

Abstract Background: Immune checkpoint inhibitors (ICIs) have improved survival in non-small-cell lung cancer (NSCLC), yet only a subset of patients benefits, and biomarkers like PD-L1 remain limited. Here, we introduce a deep learning-based pathomics framework that utilizes routine H&E-stained slides to predict therapeutic response and survival outcomes in ICI-treated metastatic NSCLC. Methods: The study included 797 ICI-treated NSCLC patients from MD Anderson, with external validation in 280 patients from Mayo Clinic, Gustave Roussy, and the Phase III ICI-naïve LUSC Lung-MAP S1400I trial receiving nivolumab with or without ipilimumab. Path-IO (Pathology-Driven Immunotherapy Optimization) comprised of four major steps: (1) pathologist-verified tissue classifier segmented WSIs into eight compartments—Background, Bronchi, Immune, Lung, Necrosis, Stroma, Tumor, and Vessel—and was validated on TCGA and CPTAC dataset; (2) a survival prediction module generating patient-level risk scores in the MD Anderson cohort and validated across external datasets; (3) integration of Path-IO risk scores with radiomics and clinical features to improve prognostic accuracy; and (4) biological interpretability analyses correlating Path-IO risk immune contexture from multiplex immunofluorescence and transcriptomic signatures from NanoString profiling. Results: Path-IO effectively stratified patients into high and low-risk groups with significant survival differences. In the MD Anderson cohort, it achieved HR = 2.11 (p < 0.001) and HR = 2.51 (p < 0.001) for OS in the discovery and validation sets, and HR = 2.34 (p < 0.001) and HR = 1.87 (p < 0.001) for PFS, respectively. In the multicenter Phase III Lung-MAP S1400I trial, Path-IO achieved HR = 1.78 (p = 0.016) for OS and HR = 2.76 (p = 0.006) for PFS. In external validation, it predicted outcomes in the Gustave Roussy (OS = 1.97, p = 0.003; PFS = 1.51, p = 0.046) and Mayo Clinic (OS = 2.46, p = 0.007; PFS = 2.45, p = 0.027) cohorts. Path-IO outperformed PD-L1 and remained an independent predictor in multivariate analysis (p < 0.001). It enabled data-driven frontline selection between anti-PD-1 monotherapy and chemo-immunotherapy, offering guidance toward more personalized treatment decisions. Integration with radiomics and clinical features further improved predictive accuracy (OS 0.63→0.75; PFS C-index 0.58→0.70), while high Path-IO risk scores correlated with immune-cold phenotypes identified by multiplex immunofluorescence and NanoString transcriptomics. Conclusions: Path-IO demonstrates that deep learning models rooted in histopathologic architecture can generate interpretable and biologically informed survival predictions in NSCLC treated with ICIs. By integrating pathology, radiology, and clinical data, Path-IO provides complementary predictive value beyond established biomarkers such as PD-L1. Citation Format: Rukhmini Bandyopadhyay, Linghzi Hong, Mihaela Aldea, Shenduo Li, Lodovica Zullo, Frank R. Rojas, Maliazurina B. Saad, Maricel C. Marin, Muhammad Waqas, Jiexin Zhang, Eman Showkatian, Claudio A. Arrechedera, Xiaoyu Han, Yuliya Kitsel, Sherif Ismail, Muhammad Aminu, Bo Zhu, Carol C. Wu, Brett W. Carter, Joe Y Chang, Zhongxing Liao, Maria R. Ghigna, Davide Soldato, Hai T. Tran, Xiuning Le, Tina Cascone, Bingnan Zhang, Haniel A. Araujo, Mehmet Altan, Simon Heeke, David Jaffray, Don L. Gibbons, Ara Vaporciyan, J Jack Lee, Neda Kalhor, Cara Haymaker, Ignacio Wistuba, John V. Heymach, Yanyan Lou, Natalie Vokes, Luisa M. Solis Soto, Jianjun Zhang, Jia Wu. Path-IO: A deep learning pathomics framework for personalized immunotherapy selection and outcome prediction in metastatic non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4003.

Rationale: Respiratory disease is a major cause of mortality in Down syndrome (DS; trisomy 21, T21). DS is considered a progeroid syndrome, with elevated cellular senescence (SEN) and oxidative stress. Because SEN shapes organogenesis, its dysregulation may impair lung morphogenesis. We previously found SEN/SASP (senescence-associated secretory phenotype) abnormalities in prenatal human T21 lungs. Here, we test whether these alterations persist and change after birth. Methods: We analyzed human lung single-nuclear RNA (snRNA-seq) datasets (prenatal and postnatal) to quantify epithelial and mesenchymal SEN/SASP signatures. Sex- and age-matched T21 and non-T21 prenatal and postnatal lungs were studied; fibroblasts were isolated as prenatal human lung fibroblasts (HFLF) and postnatal human lung fibroblasts (HLF). SEN/SASP were measured by RT-qPCR and immunofluorescence (IF) in tissue and HFLF/HLF. HFLF/HLF were assayed for SA-β-gal, oxidative stress (CellROX/MitoSOX), and Ca 2 + dynamics (Fura-2 AM). 48h treatments with tunicamycin (1µM, SEN inducer), 4-phenylbutyrate (4-PBA, 2 mM, ER Stress inhibitor), or pyrroloquinoline quinone (PQQ, 20 μM, antioxidant) were performed on T21 and non-T21 HFLF/HLF. Conditioned media (CM) were collected after 48h from untreated cultures and then applied to cells of the opposite genotype for 24, 48, and 72h. Results: Overall SEN profile was similar in epithelium and mesenchyme across ages, but pathway signatures differed. Epithelium shows an inflammatory SASP, while mesenchyme shows a less-inflammatory, remodeling/growth-factor SASP. These lineage patterns were more evident postnatally. Whole-tissue IF showed increased γ-H2AX and p21 in T21 vs non-T21 both prenatally and postnatally (p< 0.05). At baseline, T21 HFLF/HLF had higher CDKN1A, CDKN2A, TP53, CDKN2B, and SERPINE1 (p< 0.05; n=5–6), with increased γ-H2AX/p21 IF (p< 0.01; n=6), SA-β-gal (p< 0.05; n=5–6), and ER/mitochondrial stress (p< 0.05; n=5–6). Fura-2 AM showed greater Ca 2 + release in T21 HFLF/HLF at baseline and after acetylcholine (10 μM, p< 0.01; n=5). Mitochondrial-morphology genes (FIS1, DNM1L, MFN1) were elevated in T21 HFLF/HLF (p< 0.05; n=6). In T21 HFLF, 4-PBA and PQQ each reduced SA-β-gal (p< 0.01; n=6). In postnatal HLF, PQQ had the stronger effect (p< 0.05; n=5). T21 CM induced progressively greater SEN/SASP over 24/48/72h in non-T21 cells (p< 0.05; n=5-6), while non-T21 CM partially rescued T21-HLF phenotypes at 24h only (p< 0.05; n=5-6). Conclusion: These data indicate that lung senescence in T21 initiates in utero and intensifies after birth and reflects lineage-specific pathways. ER-stress-related mechanisms are more prominent prenatally, while mitochondrial/redox mechanisms are predominant postnatally. This evidence suggests age and lineage-dependent drivers of senescence that may help explain DS lung disease and highlight potential new mechanistic targets. This abstract was presented at the American Physiology Summit 2026 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.

Background/Objectives: Accurate detection of pulmonary nodules on chest CT is critical for lung cancer screening, yet training robust detectors remains challenging due to the high cost of reliable annotations. In this work, we present a systematic study of curriculum learning for CT-based lung nodule detection on the enhanced LUNA25 benchmark and propose a hybrid curriculum learning framework for data-efficient optimization. Methods: Our approach estimates sample difficulty by fusing clinically interpretable handcrafted factors such as nodule size and count with model-driven signals such as prediction confidence from a teacher model, and constructs a three-stage progressive training curriculum from easy to hard samples. Using YOLOv11s as a strong baseline, the proposed hybrid curriculum is compared against conventional training without curriculum learning and against single-source curricula. Results: On the held-out LUNA25 test set, hybrid curriculum learning increases mAP50 from 0.672 to 0.696, mAP50–95 from 0.369 to 0.385, recall from 0.588 to 0.634, and precision from 0.725 to 0.764. Extensive data-efficiency experiments with proportional reductions (1/2, 1/5, 1/10) and fixed training samples (5000–40,000 slices) further confirm consistent gains across limited-data regimes. Conclusions: These results demonstrate that jointly leveraging intrinsic image complexity and optimization-aware feedback provides effective sample scheduling for robust and data-efficient lung nodule detection.

Importance Current risk prediction guidelines for hypertrophic cardiomyopathy predict only sudden cardiac death and are imperfect, leading to avoidable deaths and unnecessary implantable cardioverter defibrillators. Objective To combine prospectively collected clinical history, imaging, genetic, and biomarker data to improve risk prediction of adverse events in hypertrophic cardiomyopathy. Design, Setting, and Participants A total of 2750 patients with hypertrophic cardiomyopathy were prospectively enrolled in the registry-based study from 44 sites in North America and Europe with expertise in hypertrophic cardiomyopathy and cardiac magnetic resonance (CMR) imaging. Participants were enrolled from April 1, 2014, to April 7, 2017. Exposures Patients underwent a health history questionnaire, blood sampling for biomarkers and genotyping, and contrast-enhanced CMR. Patients were followed up yearly by telephone and through records review regarding event documentation. Main Outcomes and Measures The predefined composite adjudicated primary end point was time to first event for hypertrophic cardiomyopathy–related deaths; nonfatal sustained ventricular arrhythmias (VAs) requiring cardioversion or defibrillation; and left ventricular (LV) assist device implant or heart transplant. A secondary end point was a composite of sudden cardiac death and nonfatal VA events. The elastic-net method identified the most important predictors. Cox proportional hazards regression assessed associations with time to the first end point. Results Of the 2750 prospectively enrolled patients, 2698 (98%) had analyzable data after 9 were excluded because they had hypertrophic cardiomyopathy phenocopies and 43 withdrew. Of these remaining patients, 1919 (71%) were male, mean age was 50 years (SD, 11 years), and 423 (16%) were from underrepresented racial and minority groups. The mean follow-up was 6.9 years (SD, 2.1 years). The primary event model in 104 patients included LV scar as a percentage of LV mass by late gadolinium enhancement (LGE%; hazard ratio [HR], 1.86; 95% CI, 1.58-2.20; P &amp;lt; .001), LV mass index (HR, 1.09; 95% CI, 1.01-1.17; P = .03), LV end-systolic volume index (HR, 1.28; 95% CI, 1.12-1.46; P &amp;lt; .001 ), all per 10-unit increase, history of heart failure at study entry (HR, 2.89; 95% CI, 1.75-4.77; P &amp;lt; .001), and log N-terminal pro–B-type natriuretic peptide (NT-proBNP; HR, 1.41; 95% CI, 1.17-1.70; P &amp;lt; .001) level per log unit, (C index for all, 0.77). An LGE percentage of the LV mass of 9% or higher substantially increased the primary composite event rate ( P = .001). The secondary sudden cardiac death and VA risk factor model (in 69 patients) included LGE%, LV mass index, LV ejection fraction, and log(NT-proBNP) (C index, 0.76). Conclusions and Relevance These results provide prospective evidence for incorporating cardiac magnetic resonance and NT-proBNP in the evaluation of patients with hypertrophic cardiomyopathy. Trial Registration ClinicalTrials.gov Identifier: NCT01915615

Abstract Background Lung cancer is the leading cause of cancer-related death, and the most common cancer diagnosed globally. Approximately 85% of lung cancer cases are non-small cell lung cancer (NSCLC). After initial surgical treatment, adjuvant therapy with conventional or targeted chemotherapy can help optimize survival. These treatments, however, must be tailored to each patients’ problematic situation, including cancer characteristics and goals of care. Shared decision making (SDM) is a method of care by which patients and clinicians work together to form plans of care that advance the patient’s problematic human situation. This method often requires evaluating alternative options, “trying them on” for fit given their practical demands and favorable and unfavorable effects. Tools used within the encounter can facilitate and support SDM conversations, yet none exist for considering care post-surgical treatment of NSCLC. Therefore, we aimed to evaluate the effectiveness of a novel encounter tool for SDM, NSCLC Choice, compared to usual care at improving SDM and reducing decisional conflict for patients with resected early-stage NSCLC considering adjuvant treatment. Methods We will conduct a parallel, patient-level randomized trial comparing NSCLC Choice with usual care. Patients will be eligible if they are adults with stage >1B NSCLC eligible for postsurgical adjuvant chemotherapy. Allocation will be central and post-consent. Patients will be blinded to our trial hypothesis, instead of being invited to evaluate an educational intervention. Our primary outcome is SDM quality, which we will assess using participant reported measures (patient SDM-Q-9) obtained immediately post-encounter and an observer measure estimated from video recording of trial encounters in both arms (OPTION12). With resources to conduct a 100-patient trial, we will have >80% power to detect a 12-point medium difference between arms in patient-reported SDM-Q-9. We will also assess the secondary outcomes of knowledge about the disease and the features of treatment options using an ad hoc questionnaire, decisional conflict using the Decisional Conflict Scale, and patient and clinician satisfaction using the metrics used in prior SDM intervention trials. We will also determine encounter length using video recordings. Discussion In testing NSCLC Choice, we seek to determine the extent to which this intervention can improve care for patients with NSCLC considering adjuvant therapy after surgery. In addition, we expect to determine whether this intervention is satisfactory to participants and feasible in practice. If successful, this study will result in an evidence-based tool for promoting patient-centered conversations around NSCLC and cancer care those fits. Trial Registration: NCT06122064 ClinicalTrials.gov

The present study provides novel physiological insights into aging by measuring airway compliance and residual volume via forced oscillation perturbations using a programmable mechanical ventilator (flexiVent—currently considered a gold standard for in vivo lung function measurements). In addition, dynamic measurements of lung inflation reported herein may serve as early indicators of altered elastic properties. Taken together, the findings offer a comprehensive assessment of age-related changes in lung structure and function.