[Therapeutics in cystic fibrosis: Clinical revolution and new challenges]. / Traitements de la mucoviscidose - Révolution clinique et nouveaux défis.

Over time, cystic fibrosis has become a model of synergy between research in pathophysiology and cell biology, and clinical advances. Therapies targeting the CFTR protein, in particular CFTR modulators, have transformed the prognosis of patients, bringing the hope of a normal life with the possibility of starting a family and growing old, challenging established statistics. However, patients are not yet cured, and side effects remain insufficiently documented. Epidemiological changes create new challenges for the management of cystic fibrosis. Approximately 10 % of patients still lack a therapeutic option. The community of researchers, pharmaceutical industries, patient associations, and health authorities remains committed to monitor the long-term effects of these still poorly characterised treatments, and to explore new pharmacological approaches, such as gene therapies.

Title: Traitements de la mucoviscidose - Révolution clinique et nouveaux défis. Abstract: Avec le temps, la mucoviscidose est devenue un exemple de synergie entre la recherche en biologie cellulaire et les progrès cliniques. Les thérapies protéiques ont enfin apporté l'espoir d'une vie normale aux patients, bouleversant ainsi les statistiques épidémiologiques établies. Néanmoins, les patients ne guérissent pas, et l'évolution épidémiologique de la maladie ouvre de nouveaux défis pour la prise en charge des malades. Par ailleurs, environ 10 % des patients demeurent sans solution thérapeutique. De nouvelles stratégies sont ainsi envisagées et la communauté des chercheurs, industriels, patients et autorités de santé reste mobilisée pour suivre les effets à long terme de ces nouveaux traitements et explorer de nouvelles approches pharmacologiques.

Lumacaftor/Ivacaftor Population Pharmacokinetics in Pediatric Patients with Cystic Fibrosis: A First Step Toward Personalized Therapy.

BACKGROUND: A major breakthrough in cystic fibrosis (CF) therapy was achievedAQ1 with CFTR modulators. The lumacaftor/ivacaftor combination is indicated for the treatment of CF in pediatric patients above 6 years old. Pharmacokinetic (PK) studies of lumacaftor/ivacaftor in these vulnerable pediatric populations are AQ2crucial to optimize treatment protocols. OBJECTIVES AND METHODS: The objectives of this study were to describe the population PK (PPK) of lumacaftor and ivacaftor in children with CF, and to identify factors associated with interindividual variability. The association between drug exposure and clinical response was also investigated. RESULTS: A total of 75 children were included in this PPK study, with 191 concentrations available for each compound and known metabolites (lumacaftor, ivacaftor, ivacaftor-M1, and ivacaftor-M6). PPK analysis was performed using Monolix software. A large interindividual variability was observed. The main sources of interpatient variability identified were patient bodyweight and hepatic function (aspartate aminotransferase). Forced expiratory volume in the first second (FEV1) was statistically associated with the level of exposure to ivacaftor after 48 weeks of treatment. CONCLUSIONS: This study is the first analysis of lumacaftor/ivacaftor PPK in children with CF. These data suggest that dose adjustment is required after identifying variability factors to optimize efficacy. The use of therapeutic drug monitoring as a basis for dose adjustment in children with CF may be useful.

A benchmark study of data normalisation methods for PTR-TOF-MS exhaled breath metabolomics.

Volatilomics is the branch of metabolomics dedicated to the analysis of volatile organic compounds in exhaled breath for medical diagnostic or therapeutic monitoring purposes. Real-time mass spectrometry (MS) technologies such as proton transfer reaction (PTR) MS are commonly used, and data normalisation is an important step to discard unwanted variation from non-biological sources, as batch effects and loss of sensitivity over time may be observed. As normalisation methods for real-time breath analysis have been poorly investigated, we aimed to benchmark known metabolomic data normalisation methods and apply them to PTR-MS data analysis. We compared seven normalisation methods, five statistically based and two using multiple standard metabolites, on two datasets from clinical trials for COVID-19 diagnosis in patients from the emergency department or intensive care unit. We evaluated different means of feature selection to select the standard metabolites, as well as the use of multiple repeat measurements of ambient air to train the normalisation methods. We show that the normalisation tools can correct for time-dependent drift. The methods that provided the best corrections for both cohorts were probabilistic quotient normalisation and normalisation using optimal selection of multiple internal standards. Normalisation also improved the diagnostic performance of the machine learning models, significantly increasing sensitivity, specificity and area under the receiver operating characteristic (ROC) curve for the diagnosis of COVID-19. Our results highlight the importance of adding an appropriate normalisation step during the processing of PTR-MS data, which allows significant improvements in the predictive performance of statistical models.Clinical trials: VOC-COVID-Diag (EudraCT 2020-A02682-37); RECORDS trial (EudraCT 2020-000296-21).

Enhanced real-time mass spectrometry breath analysis for the diagnosis of COVID-19.

Background: Although rapid screening for and diagnosis of coronavirus disease 2019 (COVID-19) are still urgently needed, most current testing methods are long, costly or poorly specific. The objective of the present study was to determine whether or not artificial-intelligence-enhanced real-time mass spectrometry breath analysis is a reliable, safe, rapid means of screening ambulatory patients for COVID-19. Methods: In two prospective, open, interventional studies in a single university hospital, we used real-time, proton transfer reaction time-of-flight mass spectrometry to perform a metabolomic analysis of exhaled breath from adults requiring screening for COVID-19. Artificial intelligence and machine learning techniques were used to build mathematical models based on breath analysis data either alone or combined with patient metadata. Results: We obtained breath samples from 173 participants, of whom 67 had proven COVID-19. After using machine learning algorithms to process breath analysis data and further enhancing the model using patient metadata, our method was able to differentiate between COVID-19-positive and -negative participants with a sensitivity of 98%, a specificity of 74%, a negative predictive value of 98%, a positive predictive value of 72% and an area under the receiver operating characteristic curve of 0.961. The predictive performance was similar for asymptomatic, weakly symptomatic and symptomatic participants and was not biased by COVID-19 vaccination status. Conclusions: Real-time, noninvasive, artificial-intelligence-enhanced mass spectrometry breath analysis might be a reliable, safe, rapid, cost-effective, high-throughput method for COVID-19 screening.

Volatile metabolites differentiate air-liquid interface cultures after infection with Staphylococcus aureus.

Early detection of lung infection is critical to clinical diagnosis, treatment, and monitoring. Measuring volatile organic compounds (VOCs) in exhaled breath has shown promise as a rapid and accurate method of evaluating disease metabolism and phenotype. However, further investigations of the role and function of VOCs in bacterial-host-stress response is required and this can only be realised through representative in vitro models. In this study we sampled VOCs from the headspace of A549 cells at an air-liquid interface (ALI). We hypothesised VOC sampling from ALI cultures could be used to profile potential biomarkers of S. aureus lung infection. VOCs were collected using thin film microextraction (TFME) and were analysed by thermal desorption-gas chromatography-mass spectrometry. After optimising ALI cultures, we observed seven VOCs changed between A549 and media control samples. After infecting cells with S. aureus, supervised principal component-discriminant function analysis revealed 22 VOCs were found to be significantly changed in infected cells compared to uninfected cells (p < 0.05), five of which were also found in parallel axenic S. aureus cultures. We have demonstrated VOCs that could be used to identify S. aureus in ALI cultures, supporting further investigation of VOC analysis as a highly sensitive and specific test for S. aureus lung infection.

Therapeutic drug monitoring of corticosteroids/ß2-agonists in the hair of patients with asthma: an open-label feasibility study.

Background: Although adherence to inhaled medication is critically important for treatment efficiency, around half of patients taking these drugs are non-adherent or make critical errors when using their delivery device. Segmental hair analysis might be a valuable tool for therapeutic monitoring because hair concentrations reflect exposure from month to month. The objective of the present proof-of-concept study was to establish the feasibility of segmental hair analysis of inhaled budesonide and formoterol in asthma patients. Methods: We conducted a prospective, open-label, interventional study of adult patients being treated with budesonide/formoterol for controlled, moderate-to-severe asthma (CorticHair, NCT03691961). Asthma control, lung function, and medication adherence were recorded. Hair samples were taken 4 months after enrolment and cut into four 1 cm segments. Results: Samples were available from 21 patients (20 women; median age: 53; median budesonide dose: 600 µg/d). Budesonide and formoterol were detected in samples from 18 to 13 patients, respectively. The median hair concentrations were 6.25 pg/mg for budesonide and 0.9 pg/mg for formoterol. The intrapatient coefficient of variation between hair segments was 21% for budesonide and 40% for formoterol. Pearson's coefficients for the correlations between the hair concentration and the self-reported drug dose and the prescribed drug dose were respectively 0.42 (p = 0.08) and 0.29 (p = 0.25) for budesonide and 0.24 (p = 0.44) and 0.17 (p = 0.57) for formoterol. Conclusion: Segmental hair analysis of inhaled medications was feasible, with low intrapatient variability. This innovative, non-invasive means of assessing monthly drug exposure might help physicians to personalize drug regimens for patients with difficult-to-treat asthma.

"Il faut continuer à poser des questions" patient reported outcome measures in cystic fibrosis: An anthropological perspective.

BACKGROUND: People with cystic fibrosis (pwCF) are central in the development of patient-led assessment tools. Qualitative analysis of a frequently used CF-specific patient-reported outcome measure (PROM) sought patient recommendations for development of a new quality of life (QoL) tool. METHODS: We performed an inventory of PROMs, symptom-report and QoL tools used in clinical trials within the European Cystic Fibrosis Society Clinical Trial Network (ECFS-CTN) and in routine clinical practice among Cystic Fibrosis Europe and ECFS members. A qualitative study using cognitive interviews with pwCF and their caregivers reviewed the Cystic Fibrosis Questionnaire (CFQ), the French initial form of the Cystic Fibrosis Questionnaire-Revised (CFQ-R). RESULTS: Survey results from 33 countries revealed over 70 tools used in routine clinical practice, utilized by clinical specialists (n=124), pwCF/parents/carers (n=49) and other allied health professionals (n=60). The CFQ-R was the main PROM used in clinical trials. The qualitative study enrolled 99 pwCF, 6 to 11 years (n=31); 12 to 18 years (n=38); >18 years (n=30) and 26 parents. Inductive thematic analysis based on the CFQ, revealed 19 key themes. Themes common across all cohorts included burden of treatment, impact of disease on day-to-day life, relationships/family, stress/mood, and nutrition. Themes unique to individual groups included, treatment when not symptomatic for the paediatric group; education/studies and planning for the future for adolescents, impact of anxiety and depression on day-to-day life for adults, and for parents, questions addressing anxiety and their role as carers. CONCLUSIONS: Patient-centeredness is paramount in development of an up-to-date PROM in the era of novel therapies.

Modulators of CFTR. Updates on clinical development and future directions.

Cystic fibrosis (CF) is the most frequent life-limiting autosomal recessive disorder in the Caucasian population. It is due to mutations in the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) gene. Current symptomatic CF therapies, which treat the downstream consequences of CFTR mutations, have increased survival. Better knowledge of the CFTR protein has enabled pharmacologic therapy aiming to restore mutated CFTR expression and function. These CFTR "modulators" have revolutionised the CF therapeutic landscape, with the potential to transform prognosis for a considerable number of patients. This review provides a brief summary of their mechanism of action and presents a thorough review of the results obtained from clinical trials of CFTR modulators.

Metabolic Phenotyping and Strain Characterisation of Pseudomonas aeruginosa Isolates from Cystic Fibrosis Patients Using Rapid Evaporative Ionisation Mass Spectrometry.

Rapid evaporative ionisation mass spectrometry (REIMS) is a novel technique for the real-time analysis of biological material. It works by conducting an electrical current through a sample, causing it to rapidly heat and evaporate, with the analyte containing vapour channelled to a mass spectrometer. It was used to characterise the metabolome of 45 Pseudomonas aeruginosa (P. aeruginosa) isolates from cystic fibrosis (CF) patients and compared to 80 non-CF P. aeruginosa. Phospholipids gave the highest signal intensity; 17 rhamnolipids and 18 quorum sensing molecules were detected, demonstrating that REIMS has potential for the study of virulence-related metabolites. P. aeruginosa isolates obtained from respiratory samples showed a higher diversity, which was attributed to the chronic nature of most respiratory infections. The analytical sensitivity of REIMS allowed the detection of a metabolome that could be used to classify individual P. aeruginosa isolates after repeated culturing with 81% accuracy, and an average 83% concordance with multilocus sequence typing. This study underpins the capacities of REIMS as a tool with clinical applications, such as metabolic phenotyping of the important CF pathogen P. aeruginosa, and highlights the potential of metabolic fingerprinting for fine scale characterisation at a sub-species level.

Current and future therapies for Pseudomonas aeruginosa infection in patients with cystic fibrosis.

Pseudomonas aeruginosa opportunistically infects the airways of patients with cystic fibrosis and causes significant morbidity and mortality. Initial infection can often be eradicated though requires prompt detection and adequate treatment. Intermittent and then chronic infection occurs in the majority of patients. Better detection of P. aeruginosa infection using biomarkers may enable more successful eradication before chronic infection is established. In chronic infection P. aeruginosa adapts to avoid immune clearance and resist antibiotics via efflux pumps, ß-lactamase expression, reduced porins and switching to a biofilm lifestyle. The optimal treatment strategies for P. aeruginosa infection are still being established, and new antibiotic formulations such as liposomal amikacin, fosfomycin in combination with tobramycin and inhaled levofloxacin are being explored. Novel agents such as the alginate oligosaccharide OligoG, cysteamine, bacteriophage, nitric oxide, garlic oil and gallium may be useful as anti-pseudomonal strategies, and immunotherapy to prevent infection may have a role in the future. New treatments that target the primary defect in cystic fibrosis, recently licensed for use, have been associated with a fall in P. aeruginosa infection prevalence. Understanding the mechanisms for this could add further strategies for treating P. aeruginosa in future.

Pseudomonas aeruginosa infection in cystic fibrosis: pathophysiological mechanisms and therapeutic approaches.

Pseudomonas aeruginosa is a remarkably versatile environmental bacterium with an extraordinary capacity to infect the cystic fibrosis (CF) lung. Infection with P. aeruginosa occurs early, and although eradication can be achieved following early detection, chronic infection occurs in over 60% of adults with CF. Chronic infection is associated with accelerated disease progression and increased mortality. Extensive research has revealed complex mechanisms by which P. aeruginosa adapts to and persists within the CF airway. Yet knowledge gaps remain, and prevention and treatment strategies are limited by the lack of sensitive detection methods and by a narrow armoury of antibiotics. Further developments in this field are urgently needed in order to improve morbidity and mortality in people with CF. Here, we summarize current knowledge of pathophysiological mechanisms underlying P. aeruginosa infection in CF. Established treatments are discussed, and an overview is offered of novel detection methods and therapeutic strategies in development.