COPD: systemic proteomic profiles in frequent and infrequent exacerbators.

Background: Some patients with COPD suffer frequent exacerbations (FE). We hypothesised that their systemic proteomic profile would be different from that of non-frequent exacerbators (NFE). The objective of the present study was to contrast the systemic proteomic profile in FE versus NFE. As a reference, we also determined the systemic proteomic profile of healthy controls (HC) and COPD patients during an actual episode of exacerbation (AE). Methods: In the analysis we included 40 clinically stable COPD patients (20 FE and 20 NFE), and 20 HC and 10 AE patients. Their plasma samples were analysed by combining two complementary proteomic approaches: label-free liquid chromatography-tandem mass spectrometry and multiplex immunoassays. Gene Ontology annotation, pathway enrichment and network analyses were used to investigate molecular pathways associated with differentially abundant proteins/peptides (DAPs). Results: Compared with HC, we identified 40 DAPs in FE, 10 in NFE and 63 in AE. Also compared to HC, pathway functional and protein-protein network analyses revealed dysregulation of inflammatory responses involving innate and antibody-mediated immunity in COPD, particularly in the FE group, as well as during an AE episode. Besides, we only identified alterations in the complement and coagulation cascades in AE. Conclusion: There are specific plasma proteome profiles associated with FE, which are partially shared with findings observed during AE, albeit others are uniquely present during the actual episode of AE.

Sleep apnoea increases biomarkers of immune evasion, lymphangiogenesis and tumour cell aggressiveness in high-risk patients and those with established lung cancer.

Background: Intermittent hypoxaemia and obstructive sleep apnoea (OSA) have been linked to lung cancer through as yet unidentified pathophysiological mechanisms. This study evaluates the effect of OSA on serum levels of biomarkers of immunosurveillance, lymphangiogenesis and intrinsic tumour cell aggressiveness in high-risk individuals screened for lung cancer and patients with established lung cancer. Methods: Serum samples from individuals participating in a lung cancer screening cohort (SAILS study) or with newly diagnosed lung cancer (SAIL study) were analysed. All patients underwent home sleep apnoea testing. Soluble levels of programmed cell death-1 (PD-1), programmed cell death ligand-1 (PD-L1), cytotoxic T-lymphocyte antigen-4, midkine (MDK), paraspeckle component-1 (PSPC1), transforming growth factor-ß1 (TGF-ß1), SMAD3, matrix metalloproteinase-2 and co-stimulus receptor of the tumour necrosis factor family of receptors (CD137) were determined by ELISA. Results: The presence of moderate-to-severe OSA was associated with increased levels of PSPC1, MDK, PD-L1 and PD-1 in screened individuals, and with higher values of PSPC1, TGF-ß1, PD-L1 and PD-1 in patients with established lung cancer. The findings correlated with nocturnal intermittent hypoxaemia indices. Conclusion: Moderate-to-severe OSA is associated with increased expression of serum biomarkers of immune evasion, lymphangiogenesis and tumour cell aggressiveness in high-risk individuals screened for lung cancer and those with established disease.

Impact of Applying the Global Lung Initiative Criteria for Airway Obstruction in GOLD Defined COPD Cohorts: The BODE and CHAIN Experience.

INTRODUCTION: The Global Lung Function Initiative (GLI) has proposed new criteria for airflow limitation (AL) and recommends using these to interpret spirometry. The objective of this study was to explore the impact of the application of the AL GLI criteria in two well characterized GOLD-defined COPD cohorts. METHODS: COPD patients from the BODE (n=360) and the COPD History Assessment In SpaiN (CHAIN) cohorts (n=722) were enrolled and followed. Age, gender, pack-years history, BMI, dyspnea, lung function measurements, exercise capacity, BODE index, history of exacerbations and survival were recorded. CT-detected comorbidities were registered in the BODE cohort. The proportion of subjects without AL by GLI criteria was determined in each cohort. The clinical, CT-detected comorbidity, and overall survival of these patients were evaluated. RESULTS: In total, 18% of the BODE and 15% of the CHAIN cohort did not meet GLI AL criteria. In the BODE and CHAIN cohorts respectively, these patients had a high clinical burden (BODE≥3: 9% and 20%; mMRC≥2: 16% and 45%; exacerbations in the previous year: 31% and 9%; 6MWD<350m: 15% and 19%, respectively), and a similar prevalence of CT-diagnosed comorbidities compared with those with GLI AL. They also had a higher rate of long-term mortality - 33% and 22% respectively. CONCLUSIONS: An important proportion of patients from 2 GOLD-defined COPD cohorts did not meet GLI AL criteria at enrolment, although they had a significant burden of disease. Caution must be taken when applying the GLI AL criteria in clinical practice.

Persistent Respiratory Failure and Re-Admission in Patients with Chronic Obstructive Pulmonary Disease Following Hospitalization for COVID-19.

Background: Chronic obstructive pulmonary disease (COPD) has been associated with worse clinical evolution/survival during a hospitalization for SARS-CoV2 (COVID-19). The objective of this study was to learn the situation of these patients at discharge as well as the risk of re-admission/mortality in the following 12 months. Methods: We carried out a subanalysis of the RECOVID registry. A multicenter, observational study that retrospectively collected data on severe acute COVID-19 episodes and follow-up visits for up to a year in survivors. The data collection protocol includes general demographic data, smoking, comorbidities, pharmacological treatment, infection severity, complications during hospitalization and required treatment. At discharge, resting oxygen saturation (SpO2), dyspnea according to the mMRC (modified Medical Research Council) scale and long-term oxygen therapy prescription were recorded. The follow-up database included the clinical management visits at 6 and 12 months, where re-admission and mortality were recorded. Results: A total of 2047 patients were included (5.6% had a COPD diagnosis). At discharge, patients with COPD had greater dyspnea and a greater need for prescription home oxygen. After adjusting for age, sex and Charlson comorbidity index, patients with COPD had a greater risk of hospital re-admission due to respiratory causes (HR 2.57 [1.35-4.89], p = 0.004), with no significant differences in survival. Conclusion: Patients with COPD who overcome a serious SARS-CoV2 infection show a worse clinical situation at discharge and a greater risk of re-admission for respiratory causes.

Untargeted Metabolomic Study of Lung Cancer Patients after Surgery with Curative Intent.

Lung cancer (LC) is a leading cause of mortality, claiming more than 1.8 million deaths per year worldwide. Surgery is one of the most effective treatments when the disease is in its early stages. The study of metabolic alterations after surgical intervention with curative intent could be used to assess the response to treatment or the detection of cancer recurrence. In this study, we have evaluated the metabolomic profile of serum samples (n = 110) from preoperative (PRE) and postoperative (POST) LC patients collected at two different time points (1 month, A; 3-6 months, B) with respect to healthy people. An untargeted metabolomic platform based on reversed phase (RP) and hydrophilic interaction chromatography (HILIC), using ultra-high performance liquid chromatography (UHPLC) and mass spectrometry (MS), was applied (MassIVE ID MSV000092213). Twenty-two altered metabolites were annotated by comparing all the different studied groups. DG(14,0/22:1), stearamide, proline, and E,e-carotene-3,3'-dione were found altered in PRE, and their levels returned to those of a baseline control group 3-6 months after surgery. Furthermore, 3-galactosyllactose levels remained altered after intervention in some patients. This study provides unique insights into the metabolic profiles of LC patients after surgery at two different time points by combining complementary analytical methods.

Metallomic Signatures of Lung Cancer and Chronic Obstructive Pulmonary Disease.

Lung cancer (LC) is the leading cause of cancer deaths, and chronic obstructive pulmonary disease (COPD) can increase LC risk. Metallomics may provide insights into both of these tobacco-related diseases and their shared etiology. We conducted an observational study of 191 human serum samples, including those of healthy controls, LC patients, COPD patients, and patients with both COPD and LC. We found 18 elements (V, Al, As, Mn, Co, Cu, Zn, Cd, Se, W, Mo, Sb, Pb, Tl, Cr, Mg, Ni, and U) in these samples. In addition, we evaluated the elemental profiles of COPD cases of varying severity. The ratios and associations between the elements were also studied as possible signatures of the diseases. COPD severity and LC have a significant impact on the elemental composition of human serum. The severity of COPD was found to reduce the serum concentrations of As, Cd, and Tl and increased the serum concentrations of Mn and Sb compared with healthy control samples, while LC was found to increase Al, As, Mn, and Pb concentrations. This study provides new insights into the effects of LC and COPD on the human serum elemental profile that will pave the way for the potential use of elements as biomarkers for diagnosis and prognosis. It also sheds light on the potential link between the two diseases, i.e., the evolution of COPD to LC.

Residual pulmonary infiltrates, symptoms and diffusion impairment at 1-year after severe COVID-19 infection have different associated factors.

INTRODUCTION: After severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia, patients may show lung sequelae on radiology and functional impairment at the 1-year follow-up. We aimed to describe the persistence of symptoms, radiological alterations, or reduced diffusing capacity of the lung for carbon monoxide (DLCO ) at 1-year follow-up in patients from the Spanish Registry RECOVID. METHODS: RECOVID collected symptom and radiological and functional lung tests data on hospitalized patients with coronavirus disease 2019 during the acute phase and at the 6- and 12-month follow-up visits. RESULTS: Of the 2500 enrolled survivors (90% admitted to the ward), 1874 had follow-up visits for up to a year. Of these, 42% continued to present with symptoms, 27% had radiological sequelae and 31% had reduced DLCO . Independently associated factors included female sex, asthma and the requirement for invasive or non-invasive mechanical ventilation. Complete radiological resolution was 72.2% at 12 months; associated factors with incomplete recovery were age, male sex, oxygen or respiratory support, corticosteroids and an initial SpO2 /FiO2 <450 or CURB-65 ≥2. Reduced DLCO was observed in 31% of patients at 12 months; associated factors were older age, female sex, smoking habit, SpO2 /FiO2 <450 and CURB-65 ≥2 and the requirement of respiratory support.At 12 months, a proportion of the asymptomatic patients showed reduced DLCO (9.5%), radiological findings (25%) or both (11%). CONCLUSIONS: The factors associated with symptom persistence, incomplete radiological resolution and DLCO <80% differed according to age, sex, comorbidities and respiratory support. The burden of symptoms, reduced DLCO and incomplete radiological resolution were considerable in patients with SARS-CoV-2 pneumonia at the 1-year follow-up after hospitalisation.

Integration of longitudinal deep-radiomics and clinical data improves the prediction of durable benefits to anti-PD-1/PD-L1 immunotherapy in advanced NSCLC patients.

BACKGROUND: Identifying predictive non-invasive biomarkers of immunotherapy response is crucial to avoid premature treatment interruptions or ineffective prolongation. Our aim was to develop a non-invasive biomarker for predicting immunotherapy clinical durable benefit, based on the integration of radiomics and clinical data monitored through early anti-PD-1/PD-L1 monoclonal antibodies treatment in patients with advanced non-small cell lung cancer (NSCLC). METHODS: In this study, 264 patients with pathologically confirmed stage IV NSCLC treated with immunotherapy were retrospectively collected from two institutions. The cohort was randomly divided into a training (n = 221) and an independent test set (n = 43), ensuring the balanced availability of baseline and follow-up data for each patient. Clinical data corresponding to the start of treatment was retrieved from electronic patient records, and blood test variables after the first and third cycles of immunotherapy were also collected. Additionally, traditional radiomics and deep-radiomics features were extracted from the primary tumors of the computed tomography (CT) scans before treatment and during patient follow-up. Random Forest was used to implementing baseline and longitudinal models using clinical and radiomics data separately, and then an ensemble model was built integrating both sources of information. RESULTS: The integration of longitudinal clinical and deep-radiomics data significantly improved clinical durable benefit prediction at 6 and 9 months after treatment in the independent test set, achieving an area under the receiver operating characteristic curve of 0.824 (95% CI: [0.658,0.953]) and 0.753 (95% CI: [0.549,0.931]). The Kaplan-Meier survival analysis showed that, for both endpoints, the signatures significantly stratified high- and low-risk patients (p-value< 0.05) and were significantly correlated with progression-free survival (PFS6 model: C-index 0.723, p-value = 0.004; PFS9 model: C-index 0.685, p-value = 0.030) and overall survival (PFS6 models: C-index 0.768, p-value = 0.002; PFS9 model: C-index 0.736, p-value = 0.023). CONCLUSIONS: Integrating multidimensional and longitudinal data improved clinical durable benefit prediction to immunotherapy treatment of advanced non-small cell lung cancer patients. The selection of effective treatment and the appropriate evaluation of clinical benefit are important for better managing cancer patients with prolonged survival and preserving quality of life.

A longitudinal and multidesign epidemiological study to analyze the effect of the volcanic eruption of Tajogaite volcano (La Palma, Canary Islands). The ASHES study protocol.

INTRODUCTION: Volcanic eruptions emit gases and particulate matter into the atmosphere which, if inhaled, can have an impact on health. The eruption of the volcano situated in the Cumbre Vieja Nature Reserve (La Palma, Canary Islands, Spain) affords a unique opportunity to study the effect of such a phenomenon on health. The aim of the proposed study is to assess the short-, medium- and long-term respiratory health effects of exposure to volcanic emissions from the eruption in three different population groups. METHODS: We propose to undertake a multidesign study: an ambispective cohort study to analyze the effect of the eruption on the general population, the highly exposed population, and the childhood population; and a pre-post quasi-experimental study on subjects with previously diagnosed respiratory diseases. The information will be collected using a personal interview, biologic specimens, air pollution data, data from medical records, respiratory tests and imaging tests. The study has an envisaged follow-up of five years, to run from the date of initial recruitment, with annual data-collection. This study has been approved by the Santa Cruz de Tenerife Provincial Research Ethics Committee (Canary Island Health Service) on March 10, 2022. CONCLUSIONS: This study will make it possible to advance our knowledge of the effect a volcano eruption has on population health, both short- and long-term, and to assess the potential respiratory injury attributable to volcanic eruptions. It may serve as a model for future studies of new volcanic eruptions in the coming years.

N-acetylcysteine for prevention and treatment of COVID-19: Current state of evidence and future directions.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes coronavirus disease 2019 (COVID-19) and can be associated with serious complications, including acute respiratory distress syndrome. This condition is accompanied by a massive release of cytokines, also denominated cytokine storm, development of systemic oxidative stress and a prothrombotic state. In this context, it has been proposed a role for acetylcysteine (NAC) in the management of patients with COVID-19. NAC is a molecule classically known for its mucolytic effect, but it also has direct and indirect antioxidant activity as a precursor of reduced glutathione. Other effects of NAC have also been described, such as modulating the immune and inflammatory response, counteracting the thrombotic state, and having an antiviral effect. The pharmacological activities of NAC and its effects on the mechanisms of disease progression make it a potential therapeutic agent for COVID-19. NAC is safe, tolerable, affordable, and easily available. Moreover, the antioxidant effects of the molecule may even prevent infection and play an important role as a complement to vaccination. Although the clinical efficacy and dosing regimens of NAC have been evaluated in the clinical setting with small series of patients, the results are promising. In this article, we review the pathogenesis of SARS-CoV-2 infection and the current knowledge of the mechanisms of action of NAC across disease stages. We also propose NAC posology strategies to manage COVID-19 patients in different clinical scenarios.

Deep learning-based lesion subtyping and prediction of clinical outcomes in COVID-19 pneumonia using chest CT.

The main objective of this work is to develop and evaluate an artificial intelligence system based on deep learning capable of automatically identifying, quantifying, and characterizing COVID-19 pneumonia patterns in order to assess disease severity and predict clinical outcomes, and to compare the prediction performance with respect to human reader severity assessment and whole lung radiomics. We propose a deep learning based scheme to automatically segment the different lesion subtypes in nonenhanced CT scans. The automatic lesion quantification was used to predict clinical outcomes. The proposed technique has been independently tested in a multicentric cohort of 103 patients, retrospectively collected between March and July of 2020. Segmentation of lesion subtypes was evaluated using both overlapping (Dice) and distance-based (Hausdorff and average surface) metrics, while the proposed system to predict clinically relevant outcomes was assessed using the area under the curve (AUC). Additionally, other metrics including sensitivity, specificity, positive predictive value and negative predictive value were estimated. 95% confidence intervals were properly calculated. The agreement between the automatic estimate of parenchymal damage (%) and the radiologists' severity scoring was strong, with a Spearman correlation coefficient (R) of 0.83. The automatic quantification of lesion subtypes was able to predict patient mortality, admission to the Intensive Care Units (ICU) and need for mechanical ventilation with an AUC of 0.87, 0.73 and 0.68 respectively. The proposed artificial intelligence system enabled a better prediction of those clinically relevant outcomes when compared to the radiologists' interpretation and to whole lung radiomics. In conclusion, deep learning lesion subtyping in COVID-19 pneumonia from noncontrast chest CT enables quantitative assessment of disease severity and better prediction of clinical outcomes with respect to whole lung radiomics or radiologists' severity score.

IGF1R acts as a cancer-promoting factor in the tumor microenvironment facilitating lung metastasis implantation and progression.

Given the long-term ineffectiveness of current therapies and late-stage diagnoses, lung cancer is a leading cause of malignant diseases. Tumor progression is influenced by cancer cell interactions with the tumor microenvironment (TME). Insulin-like growth factor 1 receptor (IGF1R) was reported to affect the TME; however, the role of IGF1R in lung TME has not been investigated. First, we assessed IGF1R genomic alterations and expression in NSCLC patient tissue samples, as well as IGF1R serum levels. Next, we performed tumor heterotopic transplantation and pulmonary metastases in IGF1R-deficient mice using melanoma and Lewis lung carcinoma (LLC) cells. Herein we report increased amplification and mRNA expression, as well as increased protein expression (IGF1R/p-IGF1R) and IGF1R levels in tumor samples and serum from NSCLC patients, respectively. Moreover, IGF1R deficiency in mice reduced tumor growth, proliferation, inflammation and vascularization, and increased apoptosis after tumor heterotopic transplantation. Following induction of lung metastasis, IGF1R-deficient lungs also demonstrated a reduced tumor burden, and decreased expression of tumor progression markers, p-IGF1R and p-ERK1/2. Additionally, IGF1R-deficient lungs showed increased apoptosis and diminished proliferation, vascularization, EMT and fibrosis, along with attenuated inflammation and immunosuppression. Accordingly, IGF1R deficiency decreased expression of p-IGF1R in blood vessels, fibroblasts, tumor-associated macrophages and FOXP3+ tumor-infiltrating lymphocytes. Our results demonstrate that IGF1R promotes metastatic tumor initiation and progression in lung TME. Furthermore, our research indicates that IGF1R could be a potential biomarker for early prediction of drug response and clinical evolution in NSCLC patients.

A Social Return on Investment Analysis of Improving the Management of Chronic Obstructive Pulmonary Disease Within the Spanish National Healthcare System.

Purpose: To define a set of proposals that would improve the current management of chronic obstructive pulmonary disease (COPD) within the Spanish National Healthcare System (SNHS) from a comprehensive multidisciplinary perspective and to assess the impact of its implementation from clinical, healthcare, economic, and social perspectives. Patients and Methods: A group of 20 stakeholders related to COPD (healthcare professionals, patients, and informal caregivers, among others) participated in an online Delphi process to agree on a set of 15 proposals that would improve the current management of COPD within the SNHS in four areas: diagnosis, risk stratification, management of exacerbations, and management of stable COPD. A one-year forecast-type social return on investment (SROI) analysis was used to estimate the impact that implementing the set of proposals would have in relation to the investment required. A sensitivity analysis was used to test the strength of the model when varying assumption-based data-points. Results: The hypothetical implementation of the complete set of 15 proposals would require a €668 million investment and would generate a €2079 million social impact concerning savings for the SNHS and quality of life improvements for patients and their informal caregivers, among others. Accordingly, for every euro invested in the set of proposals, a social return of €3.11 would be generated (€2.71 in the worst-case scenario and €3.62 in the best-case scenario) of both tangible (32.56%) and intangible nature (67.44%). Conclusion: Altogether, implementing this set of 15 proposals would generate a positive social impact, threefold the required investment. The results may inform decisions relative to healthcare policy and practice regarding COPD management within the SNHS, further contributing to reduce the large burden of COPD.

La notoriedad de la salud respiratoria y de los profesionales sanitarios que la cuidan / Raising awareness of respiratory health and specialists in respiratory diseases

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[Translated article] Raising awareness of respiratory health and specialists in respiratory diseases / La notoriedad de la salud respiratoria y de los profesionales sanitarios que la cuidan

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Expression of Macrophage Scavenger Receptor (MSR1) in Peripheral Blood Cells from Patients with Different Respiratory Diseases: Beyond Monocytes.

BACKGROUND: Macrophage scavenger receptor 1 (MSR1) has mostly been described in macrophages, but we previously found a significant gene expression increase in peripheral blood mononuclear cells (PBMCs) of asthmatic patients. OBJECTIVE: To confirm those results and to define its cellular origin in PBMCs. METHODS: Four groups of subjects were studied: healthy controls (C), nonallergic asthmatic (NA), allergic asthmatic (AA), and chronic obstructive pulmonary disease (COPD) patients. RNA was extracted from PBMCs. MSR1 gene expression was analyzed by RT-qPCR. The presence of MSR1 on the cellular surface of PBMC cellular subtypes was analyzed by confocal microscopy and flow cytometry. RESULTS: MSR1 gene expression was significantly increased in the three clinical conditions compared to the healthy control group, with substantial variations according to disease type and severity. MSR1 expression on T cells (CD4+ and CD8+), B cells, and monocytes was confirmed by confocal microscopy and flow cytometry. In all clinical groups, the four immune cell subtypes studied expressed MSR1, with a greater expression on B lymphocytes and monocytes, exhibiting differences according to disease and severity. CONCLUSIONS: This is the first description of MSR1's presence on lymphocytes' surfaces and reinforces the potential role of MSR1 as a player in asthma and COPD.