Daily Respiratory Research Analysis
Three impactful studies advance respiratory medicine: a multicenter prospective PET/CT radiomics model accurately predicts invasiveness and high‑risk pathology in early lung adenocarcinoma; a nationwide cohort identifies modifiable risk predictors of mortality and hospitalized exacerbations in obstructive airway diseases; and a translational study uncovers α7 nicotinic acetylcholine receptor–driven vascular dysfunction in COPD, highlighting a new therapeutic target.
Summary
Three impactful studies advance respiratory medicine: a multicenter prospective PET/CT radiomics model accurately predicts invasiveness and high‑risk pathology in early lung adenocarcinoma; a nationwide cohort identifies modifiable risk predictors of mortality and hospitalized exacerbations in obstructive airway diseases; and a translational study uncovers α7 nicotinic acetylcholine receptor–driven vascular dysfunction in COPD, highlighting a new therapeutic target.
Research Themes
- AI-driven imaging biomarkers for surgical decision-making in early lung cancer
- Population-scale predictors of mortality and exacerbations in obstructive airway diseases
- Mechanistic vascular pathology and therapeutic targets in COPD
Selected Articles
1. Non-invasive prediction of invasive lung adenocarcinoma and high-risk histopathological characteristics in resectable early-stage adenocarcinoma by [18F]FDG PET/CT radiomics-based machine learning models: a prospective cohort Study.
A multicenter, prospectively validated PET/CT radiomics model distinguished invasive from preinvasive lung adenocarcinoma (AUC ~0.92–0.93) and predicted high-risk histopathology (AUC ~0.82–0.85). Decision-curve analysis showed greater net benefit than CT alone, and the model stratified survival, supporting surgical planning.
Impact: Provides externally validated, noninvasive biomarkers to tailor extent of resection and nodal management in early-stage lung adenocarcinoma.
Clinical Implications: Can inform limited versus anatomical resection decisions, prioritize nodal sampling, and triage patients for more extensive surgery when high-risk pathology is predicted.
Key Findings
- Hybrid [18F]FDG PET/CT radiomics + clinical model achieved AUC 0.93 (internal) and 0.92 (external) for IA vs AIS/MIA discrimination.
- High-risk histopathological features were predicted with AUC 0.82 (internal) and 0.85 (external).
- Decision curve analysis demonstrated higher net clinical benefit than CT-only models; the model stratified PFS (P=0.002) and OS (P=0.017).
Methodological Strengths
- Prospective internal and external multicenter validation
- Robust feature selection (mRMR, LASSO) and AutoML modeling with calibration and decision-curve analysis
Limitations
- Potential spectrum and center variability in imaging protocols may affect generalizability
- Thresholds and workflow integration for real-world surgical decision-making require prospective impact studies
Future Directions: Prospective clinical utility trials to test decision impact, integration with genomic/molecular markers, and harmonization across scanners and centers.
BACKGROUND: Precise preoperative discrimination of invasive lung adenocarcinoma (IA) from preinvasive lesions (adenocarcinoma in situ [AIS]/minimally invasive adenocarcinoma [MIA]) and prediction of high-risk histopathological features are critical for optimizing resection strategies in early-stage lung adenocarcinoma (LUAD). METHODS: In this multicenter study, 813 LUAD patients (tumors ≤3 cm) formed the training cohort. A total of 1,709 radiomic features were extracted from the PET/CT images. Feature selection was performed using the max-relevance and min-redundancy (mRMR) algorithm and least absolute shrinkage and selection operator (LASSO). Hybrid machine learning models integrating [18F]FDG PET/CT radiomics and clinical-radiological features were developed using H2O.ai AutoML. Models were validated in a prospective internal cohort (N = 256, 2021-2022) and external multicenter cohort (N = 418). Performance was assessed via AUC, calibration, decision curve analysis (DCA) and survival assessment. RESULTS: The hybrid model achieved AUCs of 0.93 (95% CI: 0.90-0.96) for distinguishing IA from AIS/MIA (internal test) and 0.92 (0.90-0.95) in external testing. For predicting high-risk histopathological features (grade-III, lymphatic/pleural/vascular/nerve invasion, STAS), AUCs were 0.82 (0.77-0.88) and 0.85 (0.81-0.89) in internal/external sets. DCA confirmed superior net benefit over CT model. The model stratified progression-free (P = 0.002) and overall survival (P = 0.017) in the TCIA cohort. CONCLUSION: PET/CT radiomics-based models enable accurate non-invasive prediction of invasiveness and high-risk pathology in early-stage LUAD, guiding optimal surgical resection.
2. Uncovering a novel role of nAChRs in oxidative stress-mediated vascular dysfunction in COPD.
Using human cells, mouse models, and human pulmonary arteries, the study identifies α7 nicotinic acetylcholine receptor activation as a driver of oxidative stress–linked pulmonary vascular dysfunction in COPD. Pharmacologic antagonism or genetic deletion mitigated damage, and α7 expression correlated with COPD severity, nominating nAChRs as therapeutic targets.
Impact: Reveals a previously underappreciated receptor-mediated mechanism of COPD vascular pathology with immediate translational relevance for drug development.
Clinical Implications: Targets such as α7 nAChR could be explored to prevent or treat COPD-associated pulmonary vascular dysfunction and hypertension alongside standard care.
Key Findings
- Cigarette smoke–induced oxidative stress, Ca2+ dysregulation, and contractile disruption in hPASMCs were driven by nAChR activation.
- nAChR antagonists or genetic deletion of α7 nAChR protected pulmonary artery function in mouse models.
- α7 nAChR expression increased with COPD severity in human pulmonary arteries and inversely correlated with respiratory function.
Methodological Strengths
- Multi-system translational approach (in vitro human cells, in vivo mouse models, human vascular tissues)
- Mechanistic interrogation linking receptor activation to oxidative stress and vascular dysfunction with pharmacologic and genetic tools
Limitations
- No interventional clinical trial data to confirm therapeutic efficacy in patients
- Quantitative human sample sizes and longitudinal outcomes were not detailed
Future Directions: Early-phase clinical studies testing α7 nAChR antagonists in COPD-related pulmonary vascular dysfunction; biomarker-guided patient selection based on vascular α7 expression.
Tobacco smoke is the main risk factor for the development of chronic obstructive pulmonary disease (COPD). Despite current therapies alleviate symptoms there are limitations in the efficacy of treatments to curb its cardiovascular morbidities, particularly vascular dysfunction and the development of pulmonary hypertension. Our previous studies demonstrate that cigarette smoke directly contributes to pulmonary arterial dysfunction. Nevertheless, a further characterization of the molecular basis involved is needed for more effective targeted treatment. We have performed in vitro analysis with human pulmonary artery smooth muscle cells (hPASMC) challenged with cigarette smoke extract, and in vivo approaches of tobacco exposure in murine models and transgenic mice. Furthermore, we extended our analysis to include hPASMCs from COPD patients compared to non-COPD individuals, as well as pulmonary arteries from human tissue samples. These approaches allowed us to explore the molecular pathways contributing to the harmful effects from oxidative stress, calcium dysregulation and disruptions to the contractile machinery of pulmonary artery smooth muscle cells. Interestingly, these effects were triggered by the activation of nicotinic acetylcholine receptors (nAChRs) in these cells. Additionally, we demonstrated that nAChR antagonists or α7 nAChR deletion in a murine model effectively protected pulmonary artery function from damage. Most importantly, α7 nAChR expression in pulmonary arteries of COPD patients rose with disease severity and showed an inverse correlation with respiratory function. These findings have important clinical implications, indicating that nAChR-targeted tailored antagonists could be a promising therapeutic strategy for COPD-related vascular dysfunction.
3. Predictors of mortality and hospitalised exacerbations in obstructive airway diseases.
In a nationwide cohort of 1,006,968 adults with obstructive airway disease prescriptions, heavy short-acting bronchodilator overuse, current smoking, frailty, and prior exacerbations independently predicted mortality and hospitalized exacerbations. Findings emphasize modifiable targets for prevention and disease control.
Impact: Defines high-risk, modifiable predictors at population scale, guiding interventions to reduce mortality and exacerbation burden in asthma/COPD.
Clinical Implications: Prioritize smoking cessation, reduce SABA overuse by optimizing controller therapy, and address frailty to lower risk of death and hospitalizations.
Key Findings
- Among 1,006,968 adults, 14.4% died and 3.9% had a hospitalized exacerbation during follow-up.
- Mortality predictors included frailty (aHR 2.09), heavy SABA overuse (≥6 packages/year; aHR 1.81), current smoking (aHR 1.64), and ≥2 outpatient exacerbations in the prior year (aHR 1.52).
- Hospitalized exacerbation risk was highest with recent hospitalization (aHR 5.67), current smoking (aHR 3.69), and heavy SABA overuse (aHR 3.15).
Methodological Strengths
- Nationwide, very large sample with standardized claims data
- Multivariable Cox modeling to adjust for comorbidity and socioeconomic status
Limitations
- Claims-based definitions may misclassify disease and medication use
- Residual confounding and lack of granular clinical measures (spirometry, biomarkers)
Future Directions: Prospective interventions to curb SABA overuse, integrate frailty screening in primary care, and validate risk models with clinical data.
BACKGROUND: In Belgium, age-standardised hospital admission and mortality rates for asthma and COPD are higher than the European average. Understanding the factors that lead to a hospitalised exacerbation and/or mortality is needed to optimise patient management. METHODS: Patients ≥18 years old obtaining two claims for drugs for obstructive airway diseases (ATC code R03) in 1 year between 2017 and 2022 were identified in Belgian nationwide claims-based data. A multivariable Cox model was used to investigate predictors of all-cause mortality and hospitalised exacerbation. RESULTS: Among 1 006 968 patients included in this study, 39 214 patients (3.9%) had a hospitalised exacerbation during follow-up and 145 021 patients (14.4%) died. Next to age, sex, Charlson comorbidity index and socioeconomic status, significant predictors for mortality were being frail (adjusted hazard ratio (aHR) 2.09, 95% confidence interval (CI) 2.06-2.12), heavy overuse of short-acting bronchodilators (SABDs) (≥6 packages per year, aHR 1.81, 95% CI 1.78-1.84), current smoking (aHR 1.64, 95% CI 1.61-1.66) and a history of ≥2 outpatient exacerbations in the previous year (aHR 1.52, 95% CI 1.49-1.54). A recent hospitalised exacerbation (aHR 5.67, 95% CI 5.51-5.84), current smoking (aHR 3.69, 95% CI 3.60-3.78), heavy overuse of SABDs (aHR 3.15, 95%CI 3.08-3.23) and being frail (aHR 1.07, 95% CI 1.03-1.10) were important additional risk factors for hospitalised exacerbation. CONCLUSION: Previous exacerbations, current smoking, frailty and overuse of SABDs were significantly associated with hospitalised exacerbations and mortality in patients with asthma and/or COPD. The results of this nationwide cohort study highlight the importance of achieving disease control, smoking prevention and tackling frailty in primary care.