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Background: Airway remodelling is a feature of severe asthma with airway epithelial damage observed frequently. We evaluated the role of WNT5a and TGF-β 1 in asthmatic airway biopsies and in sputum and bronchial brushings assessed their role in remodelling., Methods: WNT5a and TGF-β 1 protein expression were assessed in the lamina propria epithelium of people with asthma (GINA 1-3, n-8 and GINA 4-5, n-14) and healthy subjects (n-9), alongside relevant remodelling markers. The effects of WNT5a and TGF-β 1 on BEAS-2B epithelial cell wound healing and differentiation were assessed in vitro. Replication was performed in the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) study in sputum (n = 120) and bronchial brushes (n = 147)., Results: WNT5a and TGF-β 1 protein expression were significantly increased in the airway epithelium and lamina propria in asthma patients with concurrent airflow limitation or severe disease. Furthermore, WNT5a protein expression in the lamina propria correlated with tissue eosinophils and vascular remodelling. Airway epithelial WNT5a was co-localised predominantly to airway basal cells and correlated with Th17 gene expression (r = 0.40, p = 0.025) and both the % intact (r s  = 0.54, p = 0.001) and % denuded epithelium (r s  = -0.39, p = 0.003). Experiments in BEAS-2B cells confirmed that WNT5a at maximal physiological concentrations (1 μg/mL), promoted epithelial wound healing, independently of TGF-β 1 , as well as induction of EMT-like morphology. WNT5a mRNA was associated with severe asthma, airflow limitation, sputum eosinophilia and Th2, and Th17 and neutrophil activation transcriptomes in sputum in U-BIOPRED., Conclusion: WNT5a is associated with both airway remodelling and severe asthma., Trial Registration: ClinicalTrials.gov identifier: NCT01982162., (© 2025 European Academy of Allergy and Clinical Immunology and John Wiley & Sons Ltd.)

Background: Lung quantitative computed tomography (qCT) severe asthma clusters have been reported, but their replication and underlying disease mechanisms are unknown. We identified and replicated qCT clusters of severe asthma in two independent asthma cohorts and determined their association with molecular pathways, using radiomultiomics, integrating qCT, multiomics and machine learning/artificial intelligence., Methods: We used consensus clustering on qCT measurements of airway and lung CT scans, performed in 105 severe asthmatic adults from the U-BIOPRED cohort. The same qCT measurements were used to replicate qCT clusters in a subsample of the ATLANTIS asthma cohort (n=97). We performed integrated enrichment analysis using blood, sputum, bronchial biopsies, bronchial brushings and nasal brushings transcriptomics and blood and sputum proteomics to characterise radiomultiomic-associated clusters (RACs)., Results: qCT clusters and clinical features in U-BIOPRED were replicated in the matched ATLANTIS cohort. In the U-BIOPRED cohort, RAC1 (n=30) was predominantly female with elevated body mass index, mild airflow limitation, decreased CT lung volume and increased lung density and upregulation of the complement pathway. RAC2 (n=34) subjects had airway wall thickness and a mild degree of airflow limitation, with upregulation of proliferative pathways including neurotrophic receptor tyrosine kinase 2/tyrosine kinase receptor B, and downregulation of semaphorin pathways. RAC3 (n=41) showed increased lung attenuation area and air trapping, severe airflow limitation, hyperinflation, and upregulation of cytokine signalling and signalling by interleukin pathways, and matrix metallopeptidase 1, 2 and 9., Conclusions: U-BIOPRED severe asthma qCT clusters were replicated in a matched independent asthmatic cohort and associated with specific molecular pathways. Radiomultiomics might represent a novel strategy to identify new molecular pathways in asthma pathobiology., Competing Interests: Conflict of interest: K.F. Chung reports grants from the MRC, EPSRC, GSK, Merck and NIEHS, payment or honoraria for lectures, presentations, manuscript writing or educational events from GSK, Novartis and AstraZeneca, and participation on a data safety monitoring board or advisory board with GSK, AstraZeneca, Novartis, Roche, Merck, Trevi, Rickett-Beckinson, Nocion, Shionogi and Clean Breathing Institute supported by Haleon. C. Auffray reports support for the present study from the Innovative Medicines Initiative. Y. Badi reports support for the present study from the Innovative Medicines Initiative. P. Bakke reports payment or honoraria for lectures, presentations, manuscript writing or educational events from AstraZeneca, GSK and Sanofi. C. Brightling reports support for the present study from the ATLANTIS study (Chiesi grant) and Leicester NIHR BRC, grants from 4D Pharma, Areteia, AstraZeneca, Chiesi, Genentech, GSK, Mologic, Novartis, Regeneron Pharmaceuticals, Roche and Sanofi, and consultancy fees from 4D Pharma, Areteia, AstraZeneca, Chiesi, Genentech, GSK, Mologic, Novartis, Regeneron Pharmaceuticals, Roche and Sanofi. P. Chanez reports grants from ALK, AstraZeneca, Boehringer Ingelheim, Chiesi, GSK, Menarini, Novartis and Sanofi Aventis, consultancy fees from ALK, AstraZeneca, Boehringer Ingelheim, Chiesi, GSK, Menarini, Novartis and Sanofi Aventis, payment or honoraria for lectures, presentations, manuscript writing or educational events from ALK, AstraZeneca, Boehringer Ingelheim, Chiesi, GSK, Menarini, Novartis and Sanofi Aventis, and support for attending meetings from ALK, AstraZeneca, Boehringer Ingelheim, Chiesi, GSK, Menarini, Novartis and Sanofi Aventis. B. De Meulder reports support for the present study from the Innovative Medicines Initiative. R. Djukanovic reports consultancy fees from Synairgen plc, GSK, ZenasBio and Celltrion, leadership role as Chair of the European Respiratory Society's clinical research collaboration on severe asthma (SHARP), and stock (or stock options) with Synairgen plc. L. Fabbri reports consultancy fees from Chiesi Farmaceutici and AstraZeneca, payment or honoraria for lectures, presentations, manuscript writing or educational events from Chiesi Farmaceutici, AstraZeneca, GSK, Alfasigma and Novartis, support for attending meetings from Chiesi Farmaceutici, GSK and Novartis, and participation on a data safety monitoring board or advisory board with Novartis and Chiesi. S.J. Fowler reports grants from the NIHR, and payment or honoraria for lectures, presentations, manuscript writing or educational events from Boehringer Ingelheim. P. Howarth reports employment with GSK. J. Kolmert reports consultancy fees from Gesynta Pharma AB and Lipum AB. M. Kraft reports grants from the NIH, American Lung Association, Synairgen, Janssen, AstraZeneca and Sanofi, consultancy fees from AstraZeneca, Sanofi, Chiesi, GSK, Kinaset and Genentech, payment or honoraria for lectures, presentations, manuscript writing or educational events from Chiesi, support for attending meetings from the European Respiratory Society, one patent issued and tiled filed to development of therapeutics for inflammatory lung disease as CoFounder and Chief Medical Officer, RaeSedo, Inc., participation on a data safety monitoring board or advisory board with ALung, leadership role with the National Heart, Lung and Blood Advisory Council, stock (or stock options) with RaeSedo, Inc. (equity ownership), and the following financial (or non-financial) interests: Section Editor of UpToDate. A.H. Maitland-van der Zee reports grants from Health Holland, GSK, Boehringer Ingelheim and Vertex, consultancy fees from Boehringer Ingelheim and AstraZeneca, payment or honoraria for lectures, presentations, manuscript writing or educational events from GSK, and participation on a data safety monitoring board or advisory board for a study on BPD in neonates. A. Papi reports grants from Chiesi, AstraZeneca, GSK and Sanofi, consultancy fees from Chiesi, AstraZeneca, GSK, Novartis, Sanofi, Iqvia, Avillion, Elpen Pharmaceuticals, Moderna and Roche, payment or honoraria for lectures, presentations, manuscript writing or educational events from Chiesi, AstraZeneca, GSK, Menarini, Zambon, Mundipharma, Sanofi, Edmond Pharma, Iqvia, Avillion, Sanofi and Regeneron, participation on a data safety monitoring board or advisory board with Chiesi, AstraZeneca, GSK, Novartis, Sanofi, Iqvia, Avillion, Elpen Pharmaceuticals and Moderna, receipt of equipment, materials, drugs, medical writing, gifts or other services from Consorzio Futuro in Ricerca. K. Rabe reports payment or honoraria for lectures, presentations, manuscript writing or educational events from AstraZeneca, Boehringer Ingelheim, Chiesi Pharmaceuticals, Novartis, Sanofi/Regeneron, GSK, Berlin Chemie and Roche Pharma, participation on a data safety monitoring board or advisory board with AstraZeneca, Boehringer Ingelheim, Sanofi/Regeneron and CSL Behring, and leadership roles with the German Center for Lung Research (DZL), German Chest Society (DGP) and American Thoracic Society. D.E. Shaw reports consultancy fees from GSK, AstraZeneca and Novartis, payment or honoraria for lectures, presentations, manuscript writing or educational events from GSK and AstraZeneca, and support for attending meetings from GSK. D. Singh reports consultancy fees from Aerogen, AstraZeneca, Boehringer Ingelheim, Chiesi, Cipla, CSL Behring, EpiEndo, Genentech, GSK, Glenmark, Gossamer Bio, Kinaset Therapeutics, Menarini, Novartis, Orion, Pulmatrix, Sanofi, Synairgen, Teva, Theravance, Biopharma and Verona Pharma. M. van Den Berge reports grants from GSK, Roche, Genentech and Novartis. Y. Guo reports support for the present study from the Innovative Medicines Initiative. S. Wagers reports consultancy fees from King's College Hospital NHS Foundation Trust, Academic Medical Research, AMC Medical Research BV, Asthma UK, Athens Medical School, Boehringer Ingelheim International GmbH, CHU de Toulouse, CIRO, DS Biologicals Ltd, École Polytechnique Fédérale De Lausanne, European Respiratory Society, FISEVI, Fluidic Analytics Ltd, Fraunhofer IGB, Fraunhofer ITEM, GSK Research & Development Ltd, Holland & Knight, Karolinska Institutet Fakturor, KU Leuven, Longfonds, National Heart and Lung Institute, Novartis Pharma AG, Owlstone Medical Limited, PExA AB, UCB Biopharma SPRL, Umeå University, University Hospital Southampton NHS Foundation Trust, Università Campus Bio-Medico di Roma, Universita Cattolica Del Sacro Cuore, Universität Ulm, University of Bern, University of Edinburgh, University of Hull, University of Leicester, University of Loughborough, University of Luxembourg, University of Manchester, University of Nottingham, Vlaams Brabant, Dienst Europa, Imperial College London, Boehringer Ingelheim, Breathomix, Gossamer Bio, AstraZeneca, CIBER, OncoRadiomics, University of Leiden, University of Wurzburg, Chiesi Pharmaceutical, University of Liege, Teva Pharmaceuticals, Sanofi, Pulmonary Fibrosis Foundation and Three Lakes Foundation. P.J. Sterk reports consultancy fees from SME Breathomix, and stock (or stock options) with SME Breathomix. S-E. Dahlen reports grants from AstraZeneca, GSK and Sanofi, consultancy fees from AstraZeneca, Cayman Chemicals, GSK and Regeneron, and payment or honoraria for lectures, presentations, manuscript writing or educational events from AstraZeneca, GSK and Sanofi. I.M. Adcock reports support for the present study from the Innovative Medicines Initiative, grants from GSK, MRC, EPSRC and Sanofi, consultancy fees from GSK, Sanofi, Chiesi and Kinaset, payment or honoraria for lectures, presentations, manuscript writing or educational events from AstraZeneca, Sanofi, Eurodrug and Sunovion, and support for attending meetings from AstraZeneca. S. Siddiqui consultancy fees from AstraZeneca, GSK, CSL Behring, Areteia Therapeutics, ERT Medical, Chiesi and Roche, and payment or honoraria for lectures, presentations, manuscript writing or educational events from GSK, Chiesi and AstraZeneca. P. Montuschi reports support for the present study from the Innovative Medicines Initiative. The remaining authors have no potential conflicts of interest to disclose., (Copyright ©The authors 2024.)

Rationale: Volatile organic compounds (VOCs) in asthmatic breath may be associated with sputum eosinophilia. We developed a volatile biomarker signature to predict sputum eosinophilia in asthma. Methods: VOCs emitted into the space above sputum samples (headspace) from patients with severe asthma ( n  = 36) were collected onto sorbent tubes and analyzed using thermal desorption gas chromatography-mass spectrometry (GC-MS). Elastic net regression identified stable VOCs associated with sputum eosinophilia ⩾ 3% and generated a volatile biomarker signature. This VOC signature was validated in breath samples from: 1 ) patients with acute asthma according to blood eosinophilia ⩾0.3 × 10 9 cells/L or sputum eosinophilia of ⩾3% in the UK EMBER (East Midlands Breathomics Pathology Node) consortium ( n  = 65) and 2 ) U-BIOPRED-IMI (Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes Innovative Medicines Initiative) consortium ( n  = 42). Breath samples were collected onto sorbent tubes (EMBER) or Tedlar bags (U-BIOPRED) and analyzed by GC-MS (GC × GC-MS for EMBER or GC-MS for U-BIOPRED). Measurements and Main Results: The in vitro headspace identified 19 VOCs associated with sputum eosinophilia, and the derived VOC signature yielded good diagnostic accuracy for sputum eosinophilia ⩾3% in headspace (area under the receiver operating characteristic curve [AUROC] 0.90; 95% confidence interval [CI], 0.80-0.99; P  < 0.0001), correlated inversely with sputum eosinophil percentage ( r s  = -0.71; P  < 0.0001), and outperformed fractional exhaled nitric oxide (AUROC 0.61; 95% CI, 0.35-0.86). Analysis of exhaled breath in replication cohorts yielded a VOC signature AUROC (95% CI) for acute asthma exacerbations of 0.89 (0.76-1.0) (EMBER cohort) with sputum eosinophilia and 0.90 (0.75-1.0) in U-BIOPRED, again outperforming fractional exhaled nitric oxide in U-BIOPRED (0.62 [0.33-0.90]). Conclusions: We have discovered and provided early-stage clinical validation of a volatile biomarker signature associated with eosinophilic airway inflammation. Further work is needed to translate our discovery using point-of-care clinical sensors.

Background: Severe asthma (SA) encompasses several clinical phenotypes with a heterogeneous airway microbiome. We determined the phenotypes associated with a low α-diversity microbiome., Methods: Metagenomic sequencing was performed on sputum samples from SA participants. A threshold of 2 standard deviations below the mean of α-diversity of mild-moderate asthma and healthy control subjects was used to define those with an abnormal abundance threshold as relative dominant species (RDS)., Findings: Fifty-one out of 97 SA samples were classified as RDSs with Haemophilus influenzae RDS being most common (n = 16), followed by Actinobacillus unclassified (n = 10), Veillonella unclassified (n = 9), Haemophilus aegyptius (n = 9), Streptococcus pseudopneumoniae (n = 7), Propionibacterium acnes (n = 5), Moraxella catarrhalis (n = 5) and Tropheryma whipplei (n = 5). Haemophilus influenzae RDS had the highest duration of disease, more exacerbations in previous year and greatest number on daily oral corticosteroids. Hierarchical clustering of RDSs revealed a C2 cluster (n = 9) of highest relative abundance of exclusively Haemophilus influenzae RDSs with longer duration of disease and higher sputum neutrophil counts associated with enrichment pathways of MAPK, NF-κB, TNF, mTOR and necroptosis, compared to the only other cluster, C1, which consisted of 7 Haemophilus influenzae RDSs out of 42. Sputum transcriptomics of C2 cluster compared to C1 RDSs revealed higher expression of neutrophil extracellular trap pathway (NETosis), IL6-transignalling signature and neutrophil activation., Conclusion: We describe a Haemophilus influenzae cluster of the highest relative abundance associated with neutrophilic inflammation and NETosis indicating a host response to the bacteria. This phenotype of severe asthma may respond to specific antibiotics., (© 2024 The Author(s). Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.)

Background: Conservative management is an option for prostate cancer (PCa) patients either with the objective of delaying or even avoiding curative therapy, or to wait until palliative treatment is needed. PIONEER, funded by the European Commission Innovative Medicines Initiative, aims at improving PCa care across Europe through the application of big data analytics., Objective: To describe the clinical characteristics and long-term outcomes of PCa patients on conservative management by using an international large network of real-world data., Design, Setting, and Participants: From an initial cohort of >100 000 000 adult individuals included in eight databases evaluated during a virtual study-a-thon hosted by PIONEER, we identified newly diagnosed PCa cases (n = 527 311). Among those, we selected patients who did not receive curative or palliative treatment within 6 mo from diagnosis (n = 123 146)., Outcome Measurements and Statistical Analysis: Patient and disease characteristics were reported. The number of patients who experienced the main study outcomes was quantified for each stratum and the overall cohort. Kaplan-Meier analyses were used to estimate the distribution of time to event data., Results and Limitations: The most common comorbidities were hypertension (35-73%), obesity (9.2-54%), and type 2 diabetes (11-28%). The rate of PCa-related symptomatic progression ranged between 2.6% and 6.2%. Hospitalization (12-25%) and emergency department visits (10-14%) were common events during the 1st year of follow-up. The probability of being free from both palliative and curative treatments decreased during follow-up. Limitations include a lack of information on patients and disease characteristics and on treatment intent., Conclusions: Our results allow us to better understand the current landscape of patients with PCa managed with conservative treatment. PIONEER offers a unique opportunity to characterize the baseline features and outcomes of PCa patients managed conservatively using real-world data., Patient Summary: Up to 25% of men with prostate cancer (PCa) managed conservatively experienced hospitalization and emergency department visits within the 1st year after diagnosis; 6% experienced PCa-related symptoms. The probability of receiving therapies for PCa decreased according to time elapsed after the diagnosis., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Eosinophilic and neutrophilic asthma defined by high levels of blood and sputum eosinophils and neutrophils exemplifies the inflammatory heterogeneity of asthma, particularly severe asthma. We analysed the serum and sputum proteome to identify biomarkers jointly associated with these different phenotypes., Methods: Proteomic profiles (N = 1129 proteins) were assayed in sputum (n = 182) and serum (n = 574) from two cohorts (U-BIOPRED and ADEPT) of mild-moderate and severe asthma by SOMAscan. Using least absolute shrinkage and selection operator (LASSO)-penalised logistic regression in a stability selection framework, we sought sparse sets of proteins associated with either eosinophilic or neutrophilic asthma with and without adjustment for established clinical factors including oral corticosteroid use and forced expiratory volume., Findings: We identified 13 serum proteins associated with eosinophilic asthma, including 7 (PAPP-A, TARC/CCL17, ALT/GPT, IgE, CCL28, CO8A1, and IL5-Rα) that were stably selected while adjusting for clinical factors yielding an AUC of 0.84 (95% CI: 0.83-0.84) compared to 0.62 (95% CI: 0.61-0.63) for clinical factors only. Sputum protein analysis selected only PAPP-A (AUC = 0.81 [95% CI: 0.80-0.81]). 12 serum proteins were associated with neutrophilic asthma, of which 5 (MMP-9, EDAR, GIIE/PLA2G2E, IL-1-R4/IL1RL1, and Elafin) complemented clinical factors increasing the AUC from 0.63 (95% CI: 0.58-0.67) for the model with clinical factors only to 0.89 (95% CI: 0.89-0.90). Our model did not select any sputum proteins associated with neutrophilic status., Interpretation: Targeted serum proteomic profiles are a non-invasive and scalable approach for subtyping of neutrophilic and eosinophilic asthma and for future functional understanding of these phenotypes., Funding: U-BIOPRED has received funding from the Innovative Medicines Initiative (IMI) Joint Undertaking under grant agreement no. 115010, resources of which are composed of financial contributions from the European Union's Seventh Framework Programme (FP7/2007-2013), and European Federation of Pharmaceutical Industries and Associations (EFPIA) companies' in-kind contributions (www.imi.europa.eu). ADEPT was funded by Johnson & Johnson/Janssen pharmaceutical Company., Competing Interests: Declaration of interests Prof M Chadeau-Hyam holds shares in the O-SMOSE company; consulting activities conducted by the company are independent of the present work. Prof Adcock reports consulting fees from GSK, Sanofi, Chiesi and Kinaset; speaker fees from AZ, Sanofi, Eurodrug and Sunovion; travel support from AZ; grants from GSK, MRC, EPSRC, Sanofi and NIEHS, which were independent of the present work. Dr. Dahlén reports consulting fees from Affiboby, AZ, Cayman Chemicals, GSK and Regeneron, and speaker fees from AZ, GSK and Sanofi, outside the submitted work. Prof Chung has received speaker fees from Novartis, AZ and Merck; honoraria for participating in Advisory Board meetings of GSK, Novartis, Roche, Merck, Trevi, Rickett-Beckinson, Nocion and Shionogi; and has received grants from MRC, EPSRC and GSK. Prof Chung is a member of the Scientific Advisory Board of the Clean Breathing Institute supported by Haleon. Dr Djukanovic declares consulting fees from Synairgen plc and lecture fees from GSK, ZenasBio and Celltrion. He holds shares from Synairgen and is Chair of the European Respiratory Society's Clinical collaboration on severe asthma (SHARP). The other authors have no conflict of interest to disclose., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Multi-omics data integration is a complex and challenging task in biomedical research. Consensus clustering, also known as meta-clustering or cluster ensembles, has become an increasingly popular downstream tool for phenotyping and endotyping using multiple omics and clinical data. However, current consensus clustering methods typically rely on ensembling clustering outputs with similar sample coverages (mathematical replicates), which may not reflect real-world data with varying sample coverages (biological replicates). To address this issue, we propose a new consensus clustering with missing labels (ccml) strategy termed ccml, an R protocol for two-step consensus clustering that can handle unequal missing labels (i.e. multiple predictive labels with different sample coverages). Initially, the regular consensus weights are adjusted (normalized) by sample coverage, then a regular consensus clustering is performed to predict the optimal final cluster. We applied the ccml method to predict molecularly distinct groups based on 9-omics integration in the Karolinska COSMIC cohort, which investigates chronic obstructive pulmonary disease, and 24-omics handprint integrative subgrouping of adult asthma patients of the U-BIOPRED cohort. We propose ccml as a downstream toolkit for multi-omics integration analysis algorithms such as Similarity Network Fusion and robust clustering of clinical data to overcome the limitations posed by missing data, which is inevitable in human cohorts consisting of multiple data modalities. The ccml tool is available in the R language (https://CRAN.R-project.org/package=ccml, https://github.com/pulmonomics-lab/ccml, or https://github.com/ZhoulabCPH/ccml)., (© The Author(s) 2024. Published by Oxford University Press.)

Rationale: Patients with severe asthma are dependent upon treatment with high doses of inhaled corticosteroids (ICS) and often also oral corticosteroids (OCS). The extent of endogenous androgenic anabolic steroid (EAAS) suppression in asthma has not previously been described in detail. The objective of the present study was to measure urinary concentrations of EAAS in relation to exogenous corticosteroid exposure., Methods: Urine collected at baseline in the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease outcomes) study of severe adult asthmatics (SA, n=408) was analysed by quantitative mass spectrometry. Data were compared to that of mild-to-moderate asthmatics (MMA, n=70) and healthy subjects (HC, n=98) from the same study., Measurements and Main Results: The concentrations of urinary endogenous steroid metabolites were substantially lower in SA than in MMA or HC. These differences were more pronounced in SA patients with detectable urinary OCS metabolites. Their dehydroepiandrosterone sulfate (DHEA-S) concentrations were <5% of those in HC, and cortisol concentrations were below the detection limit in 75% of females and 82% of males. The concentrations of EAAS in OCS-positive patients, as well as patients on high-dose ICS only, were more suppressed in females than males (p<0.05). Low levels of DHEA were associated with features of more severe disease and were more prevalent in females (p<0.05). The association between low EAAS and corticosteroid treatment was replicated in 289 of the SA patients at follow-up after 12-18 months., Conclusion: The pronounced suppression of endogenous anabolic androgens in females might contribute to sex differences regarding the prevalence of severe asthma., Competing Interests: Conflict of interest: V. Yasinska reports participation in advisory boards for AZ and GSK, and lecture honoraria from Sanofi and GSK. Conflict of interest: C. Gómez has nothing to disclose. Conflict of interest: J. Kolmert has nothing to disclose. Conflict of interest: M. Ericsson has nothing to disclose. Conflict of interest: A. Pohanka has nothing to disclose. Conflict of interest: A. James reports personal grant from Swedish Heart-Lung Foundation. Conflict of interest: L.I. Andersson has nothing to disclose. Conflict of interest: M. Sparreman-Mikus has nothing to disclose. Conflict of interest: A.R. Sousa reports employment and stocks or stock options from GSK. Conflict of interest: J.H. Riley has nothing to disclose. Conflict of interest: S. Bates has nothing to disclose. Conflict of interest: P.S. Bakke reports lecture honoraria from AstraZeneca and Boehringer Ingelheim. Conflict of interest: N. Zounemat Kermani has nothing to disclose. Conflict of interest: M. Caruso has nothing to disclose. Conflict of interest: P. Chanez reports participation in advisory boards, honoraria for consultancy, lectures fees and support for attending and/or travel from ALK, Almirall, AZ, Chiesi, GSK, Menarini, Novartis and Sanofi. Conflict of interest: S.J. Fowler has nothing to disclose. Conflict of interest: T. Geiser has nothing to disclose. Conflict of interest: P.H. Howarth reports employment and stocks or stock options from GSK. Conflict of interest: I. Horváth reports participation on an advisory board for AZ and Chiesi, honoraria for lectures from Chiesi and Roche, and support for attending and/or travel from Roche. Conflict of interest: N. Krug has nothing to disclose. Conflict of interest: P. Montuschi has nothing to disclose. Conflict of interest: M. Sanak has nothing to disclose. Conflict of interest: A. Behndig has nothing to disclose. Conflict of interest: D.E. Shaw has nothing to disclose. Conflict of interest: R.G. Knowles has nothing to disclose. Conflict of interest: B. Dahlén reports grant from GSK and Novartis. Conflict of interest: A-H. Maitland-van der Zee reports grants from BI, Vertex Innovation Award, Dutch Lung Foundation, Stichting Astma Bestrijding, IMI/3TR, EU grant ONELAB and EUROSTARS grant with Respiq, consulting fees from AZ and BI, and lecture honoraria from GSK. Conflict of interest: P.J. Sterk reports a grant from the Innovative Medicines Initiative. Conflict of interest: R. Djukanovic reports consulting fees from Synairgen, lecture honoraria from Regeneron, GSK and Kymab, and an advisory board for Synairgen. Conflict of interest: I.M. Adcock reports grant from EU-IMI, grants from GSK, MRK, EPSRC and Sanofi, consulting fees from GSK, Sanofi, Chiesi and Kinaset, lecture honoraria from AZ, Sanofi and Eurodrug, and payment for an educational event from Sunovion. Conflict of interest: K.F. Chung reports lectures honoraria from Novartis, AZ and Merck, advisory boards for GSK, AZ, Novartis, Roche, Merck, Rickett-Beckinson, Nocion and Shionogi, the Scientific Advisory Board of the Clean Breathing Institute supported by Haleon, grants from GSK, MRC and EPSRC, and support for travel from AZ. Conflict of interest: C.E. Wheelock has nothing to disclose. Conflict of interest: S-E. Dahlén reports research grants, consulting fees or lecture honoraria from AZ, Cayman Chemicals, GSK, Regeneron, Sanofi and Teva. Conflict of interest: E. Wikström Jonsson reports a research grant and expert assignment by Region Stockholm, and an expert appointment by the Swedish Medical Product Agency., (Copyright ©The authors 2023.)

Breast cancer (BC) is the most prevalent diagnosed cancer among women. Herceptin blocks the effects of Her-2 and tumour cell growth. Despite many achievements using Herceptin in Her-2 + invasive BC treatment, there are treatment failures and resistances. The signal transducer and activator of transcription 3 (STAT3) is persistently activated in BC and is associated with immune suppression and tumour cell proliferation. We evaluated whether STAT3 inhibition could increase Herceptin impact on in vitro reduction of immune checkpoint inhibitors and polarize T cells to a protective immune response. We treated SK-BR-3 cells with Herceptin and the STAT3-inhibitor (FLLL32) and assessed the apoptosis and expression of apoptosis-related proteins, VEGF, Her-2 and apoptosis targets of STAT3. PBMCs were isolated from healthy donors and co-cultured with SK-BR-3 cells in the presence or absence of Herceptin and FLLL32. PD-L1, CTLA-4, TIM-3 and T-cell intracellular cytokines were then evaluated. Our results demonstrated that STAT3 inhibition and Herceptin increased SK-BR-3 cell apoptosis, significantly. STAT3 inhibition through combination treatment had a more significant effect on regulating PD-1, TIM-3 and CTLA-4 expression on PBMCs. Alternatively, the combination of FLLL32 and Herceptin promoted T helper-1 protective immune response. The combination of FLLL32 and Herceptin suppress the expression of immune checkpoints and provoke the T-helper1 immune response in lymphocytes. Our analysis indicates STAT3 as a promising target that improves Herceptin's role in breast cancer cell apoptosis., (© 2023 The Scandinavian Foundation for Immunology.)

Background: Patients with asthma often suffer from frequent respiratory viral infections and reduced virus clearance. Lung resident memory T cells provide rapid protection against viral reinfections., Objective: Because the development of resident memory T cells relies on the lung microenvironment, we investigated the impact of allergen sensitization on the development of virus-specific lung resident memory T cells and viral clearance., Methods: Mice were sensitized with house dust mite extract followed by priming with X47 and a subsequent secondary influenza infection. Antiviral memory T-cell response and protection to viral infection was assessed before and after secondary influenza infection, respectively. Gene set variation analysis was performed on data sets from the U-BIOPRED asthma cohort using an IFN-γ-induced epithelial cell signature and a tissue resident memory T-cell signature., Results: Viral loads were higher in lungs of sensitized compared with nonsensitized mice after secondary infection, indicating reduced virus clearance. X47 priming induced fewer antiviral lung resident memory CD8 T cells and resulted in lower pulmonary IFN-γ levels in the lungs of sensitized as compared with nonsensitized mice. Using data from the U-BIOPRED cohort, we found that patients with enrichment of epithelial IFN-γ-induced genes in nasal brushings and bronchial biopsies were also enriched in resident memory T-cell-associated genes, had more epithelial CD8 T cells, and reported significantly fewer exacerbations., Conclusions: The allergen-sensitized lung microenvironment interferes with the formation of antiviral resident memory CD8 T cells in lungs and virus clearance. Defective antiviral memory response might contribute to increased susceptibility of patients with asthma to viral exacerbations., (Copyright © 2022 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.)

Background: Macrophages control innate and acquired immunity, but their role in severe asthma remains ill-defined. We investigated gene signatures of macrophage subtypes in the sputum of 104 asthmatics and 16 healthy volunteers from the U-BIOPRED cohort., Methods: Forty-nine gene signatures (modules) for differentially stimulated macrophages, one to assess lung tissue-resident cells (TR-Mφ) and two for their polarization (classically and alternatively activated macrophages: M1 and M2, respectively) were studied using gene set variation analysis. We calculated enrichment scores (ES) across severity and previously identified asthma transcriptome-associated clusters (TACs)., Results: Macrophage numbers were significantly decreased in severe asthma compared to mild-moderate asthma and healthy volunteers. The ES for most modules were also significantly reduced in severe asthma except for 3 associated with inflammatory responses driven by TNF and Toll-like receptors via NF-κB, eicosanoid biosynthesis via the lipoxygenase pathway and IL-2 biosynthesis (all P < .01). Sputum macrophage number and the ES for most macrophage signatures were higher in the TAC3 group compared to TAC1 and TAC2 asthmatics. However, a high enrichment was found in TAC1 for 3 modules showing inflammatory pathways linked to Toll-like and TNF receptor activation and arachidonic acid metabolism (P < .001) and in TAC2 for the inflammasome and interferon signalling pathways (P < .001). Data were validated in the ADEPT cohort. Module analysis provides additional information compared to conventional M1 and M2 classification. TR-Mφ were enriched in TAC3 and associated with mitochondrial function., Conclusions: Macrophage activation is attenuated in severe granulocytic asthma highlighting defective innate immunity except for specific subsets characterized by distinct inflammatory pathways., (© 2020 The Authors. Allergy published by European Academy of Allergy and Clinical Immunology and John Wiley & Sons Ltd.)