Macrophage migration inhibitory factor promotes glucocorticoid resistance of neutrophilic inflammation in a murine model of severe asthma.

BACKGROUND: Severe neutrophilic asthma is resistant to treatment with glucocorticoids. The immunomodulatory protein macrophage migration inhibitory factor (MIF) promotes neutrophil recruitment to the lung and antagonises responses to glucocorticoids. We hypothesised that MIF promotes glucocorticoid resistance of neutrophilic inflammation in severe asthma. METHODS: We examined whether sputum MIF protein correlated with clinical and molecular characteristics of severe neutrophilic asthma in the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) cohort. We also investigated whether MIF regulates neutrophilic inflammation and glucocorticoid responsiveness in a murine model of severe asthma in vivo. RESULTS: MIF protein levels positively correlated with the number of exacerbations in the previous year, sputum neutrophils and oral corticosteroid use across all U-BIOPRED subjects. Further analysis of MIF protein expression according to U-BIOPRED-defined transcriptomic-associated clusters (TACs) revealed increased MIF protein and a corresponding decrease in annexin-A1 protein in TAC2, which is most closely associated with airway neutrophilia and NLRP3 inflammasome activation. In a murine model of severe asthma, treatment with the MIF antagonist ISO-1 significantly inhibited neutrophilic inflammation and increased glucocorticoid responsiveness. Coimmunoprecipitation studies using lung tissue lysates demonstrated that MIF directly interacts with and cleaves annexin-A1, potentially reducing its biological activity. CONCLUSION: Our data suggest that MIF promotes glucocorticoid-resistance of neutrophilic inflammation by reducing the biological activity of annexin-A1, a potent glucocorticoid-regulated protein that inhibits neutrophil accumulation at sites of inflammation. This represents a previously unrecognised role for MIF in the regulation of inflammation and points to MIF as a potential therapeutic target for the management of severe neutrophilic asthma.

Th2 high and mast cell gene signatures are associated with corticosteroid sensitivity in COPD.

RATIONALE: Severe asthma and chronic obstructive pulmonary disease (COPD) share common pathophysiological traits such as relative corticosteroid insensitivity. We recently published three transcriptome-associated clusters (TACs) using hierarchical analysis of the sputum transcriptome in asthmatics from the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) cohort comprising one Th2-high inflammatory signature (TAC1) and two Th2-low signatures (TAC2 and TAC3). OBJECTIVE: We examined whether gene expression signatures obtained in asthma can be used to identify the subgroup of patients with COPD with steroid sensitivity. METHODS: Using gene set variation analysis, we examined the distribution and enrichment scores (ES) of the 3 TACs in the transcriptome of bronchial biopsies from 46 patients who participated in the Groningen Leiden Universities Corticosteroids in Obstructive Lung Disease COPD study that received 30 months of treatment with inhaled corticosteroids (ICS) with and without an added long-acting ß-agonist (LABA). The identified signatures were then associated with longitudinal clinical variables after treatment. Differential gene expression and cellular convolution were used to define key regulated genes and cell types. MEASUREMENTS AND MAIN RESULTS: Bronchial biopsies in patients with COPD at baseline showed a wide range of expression of the 3 TAC signatures. After ICS±LABA treatment, the ES of TAC1 was significantly reduced at 30 months, but those of TAC2 and TAC3 were unaffected. A corticosteroid-sensitive TAC1 signature was developed from the TAC1 ICS-responsive genes. This signature consisted of mast cell-specific genes identified by single-cell RNA-sequencing and positively correlated with bronchial biopsy mast cell numbers following ICS±LABA. Baseline levels of gene transcription correlated with the change in RV/TLC %predicted following 30-month ICS±LABA. CONCLUSION: Sputum-derived transcriptomic signatures from an asthma cohort can be recapitulated in bronchial biopsies of patients with COPD and identified a signature of airway mast cells as a predictor of corticosteroid responsiveness.

Analyzing drop coalescence in microfluidic devices with a deep learning generative model.

Predicting drop coalescence based on process parameters is crucial for experimental design in chemical engineering. However, predictive models can suffer from the lack of training data and more importantly, the label imbalance problem. In this study, we propose the use of deep learning generative models to tackle this bottleneck by training the predictive models using generated synthetic data. A novel generative model, named double space conditional variational autoencoder (DSCVAE) is developed for labelled tabular data. By introducing label constraints in both the latent and the original space, DSCVAE is capable of generating consistent and realistic samples compared to the standard conditional variational autoencoder (CVAE). Two predictive models, namely random forest and gradient boosting classifiers, are enhanced on synthetic data and their performances are evaluated based on real experimental data. Numerical results show that a considerable improvement in prediction accuracy can be achieved by using synthetic data and the proposed DSCVAE clearly outperforms the standard CVAE. This research clearly provides more insights into handling imbalanced data for classification problems, especially in chemical engineering.

Relationship between type 2 cytokine and inflammasome responses in obesity-associated asthma.

BACKGROUND: Obesity is a risk factor for asthma, and obese asthmatic individuals are more likely to have severe, steroid-insensitive disease. How obesity affects the pathogenesis and severity of asthma is poorly understood. Roles for increased inflammasome-mediated neutrophilic responses, type 2 immunity, and eosinophilic inflammation have been described. OBJECTIVE: We investigated how obesity affects the pathogenesis and severity of asthma and identified effective therapies for obesity-associated disease. METHODS: We assessed associations between body mass index and inflammasome responses with type 2 (T2) immune responses in the sputum of 25 subjects with asthma. Functional roles for NLR family, pyrin domain-containing (NLRP) 3 inflammasome and T2 cytokine responses in driving key features of disease were examined in experimental high-fat diet-induced obesity and asthma. RESULTS: Body mass index and inflammasome responses positively correlated with increased IL-5 and IL-13 expression as well as C-C chemokine receptor type 3 expression in the sputum of subjects with asthma. High-fat diet-induced obesity resulted in steroid-insensitive airway hyperresponsiveness in both the presence and absence of experimental asthma. High-fat diet-induced obesity was also associated with increased NLRP3 inflammasome responses and eosinophilic inflammation in airway tissue, but not lumen, in experimental asthma. Inhibition of NLRP3 inflammasome responses reduced steroid-insensitive airway hyperresponsiveness but had no effect on IL-5 or IL-13 responses in experimental asthma. Depletion of IL-5 and IL-13 reduced obesity-induced NLRP3 inflammasome responses and steroid-insensitive airway hyperresponsiveness in experimental asthma. CONCLUSION: We found a relationship between T2 cytokine and NLRP3 inflammasome responses in obesity-associated asthma, highlighting the potential utility of T2 cytokine-targeted biologics and inflammasome inhibitors.

Mapping atopic dermatitis and anti-IL-22 response signatures to type 2-low severe neutrophilic asthma.

BACKGROUND: Transcriptomic changes in patients who respond clinically to biological therapies may identify responses in other tissues or diseases. OBJECTIVE: We sought to determine whether a disease signature identified in atopic dermatitis (AD) is seen in adults with severe asthma and whether a transcriptomic signature for patients with AD who respond clinically to anti-IL-22 (fezakinumab [FZ]) is enriched in severe asthma. METHODS: An AD disease signature was obtained from analysis of differentially expressed genes between AD lesional and nonlesional skin biopsies. Differentially expressed genes from lesional skin from therapeutic superresponders before and after 12 weeks of FZ treatment defined the FZ-response signature. Gene set variation analysis was used to produce enrichment scores of AD and FZ-response signatures in the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes asthma cohort. RESULTS: The AD disease signature (112 upregulated genes) encompassing inflammatory, T-cell, TH2, and TH17/TH22 pathways was enriched in the blood and sputum of patients with asthma with increasing severity. Patients with asthma with sputum neutrophilia and mixed granulocyte phenotypes were the most enriched (P < .05). The FZ-response signature (296 downregulated genes) was enriched in asthmatic blood (P < .05) and particularly in neutrophilic and mixed granulocytic sputum (P < .05). These data were confirmed in sputum of the Airway Disease Endotyping for Personalized Therapeutics cohort. IL-22 mRNA across tissues did not correlate with FZ-response enrichment scores, but this response signature correlated with TH22/IL-22 pathways. CONCLUSIONS: The FZ-response signature in AD identifies severe neutrophilic asthmatic patients as potential responders to FZ therapy. This approach will help identify patients for future asthma clinical trials of drugs used successfully in other chronic diseases.

Afatinib treatment in a large real-world cohort of nonsmall cell lung cancer patients with common and uncommon epidermal growth factor receptor mutation.

The epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) afatinib improves survival in nonsmall cell lung cancer (NSCLC) patients with EGFR mutation. We analysed the outcome between EGFR mutation subtypes in a large afatinib-treated cohort in which 516 EGFR-mutated NSCLC patients receiving afatinib as front-line treatment. EGFR uncommon mutations include exon 20 insertion, de novo T790M of high or low allele frequency (dT790MHAF /dT790MLAF ), non-T790M compound mutation and others, where EGFR exon 20 insertion and dT790MHAF were defined as type-I and the rest as type-II uncommon mutation. Four hundred and sixty-one (89.3%) and 55 (10.7%) patients were common and uncommon mutation, respectively. Exon 20 insertion and dT790MHAF patients demonstrated a significantly shortened progression-free survival (PFS) (2.6 and 4.1 months) compared to EGFR common mutation, dT790MLAF and other uncommon mutation patients (15.1, 27.0 and 18.4 months; P = 3 × 10-8 ). Type-I uncommon mutation was an independent predictor of PFS (HR 4.46 [95% CI, 2.60-7.64]; P < .001) and OS (HR 2.56 [95% CI, 1.37-4.75]; P = .003). EGFR L858R patients demonstrated a significantly higher CNS progression (cause-specific HR, 3.16; 95% CI 1.24-8.08; P = .016), and type-I uncommon mutation patients exhibited a significantly higher systemic progression (cause-specific HR, 4.95; 95% CI 2.30-10.60; P = 4.3 × 10-5 ). Tendencies of higher CNS and lower systemic progression were observed in type-II uncommon mutation patients. A PFS ≥ 12 months (OR 2.38 [95% CI, 1.18-4.89]; P = .016) and uncommon EGFR mutation (OR 0.08 [95% CI, 0.01-0.48]; P = .021) were independent predictors of secondary T790M. Afatinib-treated NSCLC patients presented an EGFR genotype-specific pattern of disease progression and outcome.

Network-based visualisation reveals new insights into transposable element diversity.

Transposable elements (TEs) are widespread across eukaryotic genomes, yet their content varies widely between different species. Factors shaping the diversity of TEs are poorly understood. Understanding the evolution of TEs is difficult because their sequences diversify rapidly and TEs are often transferred through non-conventional means such as horizontal gene transfer. We developed a method to track TE evolution using network analysis to visualise TE sequence and TE content across different genomes. We illustrate our method by first using a monopartite network to study the sequence evolution of Tc1/mariner elements across focal species. We identify a connection between two subfamilies associated with convergent acquisition of a domain from a protein-coding gene. Second, we use a bipartite network to study how TE content across species is shaped by epigenetic silencing mechanisms. We show that the presence of Piwi-interacting RNAs is associated with differences in network topology after controlling for phylogenetic effects. Together, our method demonstrates how a network-based approach can identify hitherto unknown properties of TE evolution across species.

Navigating the disease landscape: knowledge representations for contextualizing molecular signatures.

Large amounts of data emerging from experiments in molecular medicine are leading to the identification of molecular signatures associated with disease subtypes. The contextualization of these patterns is important for obtaining mechanistic insight into the aberrant processes associated with a disease, and this typically involves the integration of multiple heterogeneous types of data. In this review, we discuss knowledge representations that can be useful to explore the biological context of molecular signatures, in particular three main approaches, namely, pathway mapping approaches, molecular network centric approaches and approaches that represent biological statements as knowledge graphs. We discuss the utility of each of these paradigms, illustrate how they can be leveraged with selected practical examples and identify ongoing challenges for this field of research.

Sputum macrophage diversity and activation in asthma: Role of severity and inflammatory phenotype.

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.

A retrospective study of alectinib versus ceritinib in patients with advanced non-small-cell lung cancer of anaplastic lymphoma kinase fusion in whom crizotinib treatment failed.

BACKGROUND: Crizotinib is the approved treatment for advanced non-small cell lung cancers (NSCLCs) of anaplastic lymphoma kinase (ALK) fusion. Failure of crizotinib treatment frequently involves drug intolerance or resistance. Comparison of using second-generation ALK inhibitors in this setting remains lacking. METHODS: Sixty-five ALK-positive advanced NSCLC patients receiving second-generation ALK inhibitors following treatment failure of crizotinib were retrospectively analyzed for the therapeutic efficacy. RESULTS: Forty-three (66.2%) and 22 (33.8%) patients received alectinib and ceritinib, respectively. Comparing alectinib to ceritinib treatment: the 12-month progression-free survival (PFS) rate (61.0% [95% confidence interval, 47.1 to 78.9%] vs. 54.5% [95% CI, 37.3 to 79.9%]); the hazard ratio (HR) for disease progression or death, 0.61 (95% CI, 0.31-1.17; p = 0.135). Multivariate Cox regression showed ECOG PS (0-1 vs. 2-3 HR 0.09 [95% CI, 0.02-0.33]; p < 0.001) and cause of crizotinib treatment failure (resistance vs. intolerance HR 2.75 [95% CI, 1.26-5.99]; p = 0.011) were the independent predictors for the PFS of second-generation ALK inhibitors. Treatment of alectinib, compared to ceritinib, was associated with a lower incidence of CNS progression (cause-specific HR, 0.10; 95% CI 0.01-0.78; p = 0.029) and a higher efficacy in patients whose cause of crizotinib treatment failure was intolerance (HR 0.29 [95% CI, 0.08-1.06]; p = 0.050). The most commonly noted adverse events were elevated AST/ALT in 10 (23.3%) patients treated with alectinib and diarrhea in 8 (36.4%) patients treated with ceritinib. CONCLUSION: Second-generation ALK inhibitors in crizotinib-treated patients showed a satifactory efficacy. Alectinib treatment demonstrated a CNS protection activity and a higher PFS in selected patients failing crizotinib treatment.

Crucial role for lung iron level and regulation in the pathogenesis and severity of asthma.

Accumulating evidence highlights links between iron regulation and respiratory disease. Here, we assessed the relationship between iron levels and regulatory responses in clinical and experimental asthma.We show that cell-free iron levels are reduced in the bronchoalveolar lavage (BAL) supernatant of severe or mild-moderate asthma patients and correlate with lower forced expiratory volume in 1 s (FEV1). Conversely, iron-loaded cell numbers were increased in BAL in these patients and with lower FEV1/forced vital capacity (FVC) ratio. The airway tissue expression of the iron sequestration molecules divalent metal transporter 1 (DMT1) and transferrin receptor 1 (TFR1) are increased in asthma, with TFR1 expression correlating with reduced lung function and increased Type-2 (T2) inflammatory responses in the airways. Furthermore, pulmonary iron levels are increased in a house dust mite (HDM)-induced model of experimental asthma in association with augmented Tfr1 expression in airway tissue, similar to human disease. We show that macrophages are the predominant source of increased Tfr1 and Tfr1+ macrophages have increased Il13 expression. We also show that increased iron levels induce increased pro-inflammatory cytokine and/or extracellular matrix (ECM) responses in human airway smooth muscle (ASM) cells and fibroblasts ex vivo and induce key features of asthma in vivo, including airway hyper-responsiveness (AHR) and fibrosis, and T2 inflammatory responses.Together these complementary clinical and experimental data highlight the importance of altered pulmonary iron levels and regulation in asthma, and the need for a greater focus on the role and potential therapeutic targeting of iron in the pathogenesis and severity of disease.

CGDM: collaborative genomic data model for molecular profiling data using NoSQL.

MOTIVATION: High-throughput molecular profiling has greatly improved patient stratification and mechanistic understanding of diseases. With the increasing amount of data used in translational medicine studies in recent years, there is a need to improve the performance of data warehouses in terms of data retrieval and statistical processing. Both relational and Key Value models have been used for managing molecular profiling data. Key Value models such as SeqWare have been shown to be particularly advantageous in terms of query processing speed for large datasets. However, more improvement can be achieved, particularly through better indexing techniques of the Key Value models, taking advantage of the types of queries which are specific for the high-throughput molecular profiling data. RESULTS: In this article, we introduce a Collaborative Genomic Data Model (CGDM), aimed at significantly increasing the query processing speed for the main classes of queries on genomic databases. CGDM creates three Collaborative Global Clustering Index Tables (CGCITs) to solve the velocity and variety issues at the cost of limited extra volume. Several benchmarking experiments were carried out, comparing CGDM implemented on HBase to the traditional SQL data model (TDM) implemented on both HBase and MySQL Cluster, using large publicly available molecular profiling datasets taken from NCBI and HapMap. In the microarray case, CGDM on HBase performed up to 246 times faster than TDM on HBase and 7 times faster than TDM on MySQL Cluster. In single nucleotide polymorphism case, CGDM on HBase outperformed TDM on HBase by up to 351 times and TDM on MySQL Cluster by up to 9 times. AVAILABILITY AND IMPLEMENTATION: The CGDM source code is available at https://github.com/evanswang/CGDM. CONTACT: y.guo@imperial.ac.uk.

Severe asthma exists despite suppressed tissue inflammation: findings of the U-BIOPRED study.

The U-BIOPRED study is a multicentre European study aimed at a better understanding of severe asthma. It included three steroid-treated adult asthma groups (severe nonsmokers (SAn group), severe current/ex-smokers (SAs/ex group) and those with mild-moderate disease (MMA group)) and healthy controls (HC group). The aim of this cross-sectional, bronchoscopy substudy was to compare bronchial immunopathology between these groups.In 158 participants, bronchial biopsies and bronchial epithelial brushings were collected for immunopathologic and transcriptomic analysis. Immunohistochemical analysis of glycol methacrylate resin-embedded biopsies showed there were more mast cells in submucosa of the HC group (33.6 mm-2) compared with both severe asthma groups (SAn: 17.4 mm-2, p<0.001; SAs/ex: 22.2 mm-2, p=0.01) and with the MMA group (21.2 mm-2, p=0.01). The number of CD4+ lymphocytes was decreased in the SAs/ex group (4.7 mm-2) compared with the SAn (11.6 mm-2, p=0.002), MMA (10.1 mm-2, p=0.008) and HC (10.6 mm-2, p<0.001) groups. No other differences were observed.Affymetrix microarray analysis identified seven probe sets in the bronchial brushing samples that had a positive relationship with submucosal eosinophils. These mapped to COX-2 (cyclo-oxygenase-2), ADAM-7 (disintegrin and metalloproteinase domain-containing protein 7), SLCO1A2 (solute carrier organic anion transporter family member 1A2), TMEFF2 (transmembrane protein with epidermal growth factor like and two follistatin like domains 2) and TRPM-1 (transient receptor potential cation channel subfamily M member 1); the remaining two are unnamed.We conclude that in nonsmoking and smoking patients on currently recommended therapy, severe asthma exists despite suppressed tissue inflammation within the proximal airway wall.

Clinical and inflammatory characteristics of the European U-BIOPRED adult severe asthma cohort.

U-BIOPRED is a European Union consortium of 20 academic institutions, 11 pharmaceutical companies and six patient organisations with the objective of improving the understanding of asthma disease mechanisms using a systems biology approach.This cross-sectional assessment of adults with severe asthma, mild/moderate asthma and healthy controls from 11 European countries consisted of analyses of patient-reported outcomes, lung function, blood and airway inflammatory measurements.Patients with severe asthma (nonsmokers, n=311; smokers/ex-smokers, n=110) had more symptoms and exacerbations compared to patients with mild/moderate disease (n=88) (2.5 exacerbations versus 0.4 in the preceding 12 months; p<0.001), with worse quality of life, and higher levels of anxiety and depression. They also had a higher incidence of nasal polyps and gastro-oesophageal reflux with lower lung function. Sputum eosinophil count was higher in severe asthma compared to mild/moderate asthma (median count 2.99% versus 1.05%; p=0.004) despite treatment with higher doses of inhaled and/or oral corticosteroids.Consistent with other severe asthma cohorts, U-BIOPRED is characterised by poor symptom control, increased comorbidity and airway inflammation, despite high levels of treatment. It is well suited to identify asthma phenotypes using the array of "omic" datasets that are at the core of this systems medicine approach.

Differential prognostic value of tumor and plasma T790M mutations in EGFR TKI-treated advanced NSCLC.

Background: Substitution of methionine for threonine at codon 790 (T790M) of epidermal growth factor receptor (EGFR) represents the major mechanism of resistance to EGFR tyrosine kinase inhibitors (TKIs) in EGFR-mutant non-small-cell lung cancer. We determined the prognostic impact and association of secondary T790M mutations with the outcomes of osimertinib and chemotherapy. Methods: Patients (n = 460) progressing from first-line EGFR-TKI treatment were assessed. Tissue and/or liquid biopsies were used to determine T790M status; post-progression overall survival (OS) was analyzed. Results: Overall, 143 (31.1%) patients were T790M positive, 95 (20.7%) were T790M negative, and 222 (48.2%) had unknown T790M status. T790M status [T790M positive versus T790M negative: hazard ratio (HR) 0.48 (95% confidence interval (CI), 0.32-0.70); p < 0.001, T790M unknown versus T790M negative: HR 1.97 (95% CI, 1.47-2.64); p < 0.001] was significantly associated with post-progression OS. T790M positivity rates were similar for tissue (90/168, 53.6%) and liquid (53/90, 58.9%) biopsies (Fisher's exact test, p = 0.433). Tumor T790M-positive patients had significantly longer post-progression OS than tumor T790M-negative patients (34.1 versus 17.1 months; log-rank test, p = 8 × 10-5). Post-progression OS was similar between plasma T790M-positive and -negative patients (17.4 versus not reached; log-rank test, p = 0.600). In tumor T790M-positive patients, post-progression OS was similar after osimertinib and chemotherapy [34.1 versus 29.1 months; log-rank test, p = 0.900; HR 1.06 (95% CI, 0.44-2.57); p = 0.897]. Conclusion: T790M positivity predicts better post-progression OS than T790M negativity; tumor T790M positivity has a stronger prognostic impact than plasma T790M positivity. Osimertinib and chemotherapy provide similar OS benefits in patients with T790M-positive tumors.

Different prognostic meaning of tumor resistant gene detected from tumor or blood in patients with EGFR-mutant lung cancer The study demonstrates that patients with EGFR-mutant lung cancer who develop resistance due to a secondary T790M mutation, defined by tumor or blood T790M positivity, achieve better survival than patients without secondary T790M mutation; this association was mainly contributed by tumour T790M positivity. Oismertinib and chemotherapy led to similar survival in tumour T790M-positive patients. However, compared to osimertinib, chemotherapy was associated with longer survival in blood T790M-positive patients.

Real-time updating of dynamic social networks for COVID-19 vaccination strategies.

Vaccination strategy is crucial in fighting the COVID-19 pandemic. Since the supply is still limited in many countries, contact network-based interventions can be most powerful to set an efficient strategy by identifying high-risk individuals or communities. However, due to the high dimension, only partial and noisy network information can be available in practice, especially for dynamic systems where contact networks are highly time-variant. Furthermore, the numerous mutations of SARS-CoV-2 have a significant impact on the infectious probability, requiring real-time network updating algorithms. In this study, we propose a sequential network updating approach based on data assimilation techniques to combine different sources of temporal information. We then prioritise the individuals with high-degree or high-centrality, obtained from assimilated networks, for vaccination. The assimilation-based approach is compared with the standard method (based on partially observed networks) and a random selection strategy in terms of vaccination effectiveness in a SIR model. The numerical comparison is first carried out using real-world face-to-face dynamic networks collected in a high school, followed by sequential multi-layer networks generated relying on the Barabasi-Albert model emulating large-scale social networks with several communities.

Brain metastasis, EGFR mutation subtype and generation of EGFR-TKI jointly influence the treatment outcome of patient with EGFR-mutant NSCLC.

Non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutation is brain metastasis (BM)-prone. We determined the impact of this hallmark, along with EGFR subtype and generation of tyrosine kinase inhibitor (TKI) treatment, on patients' outcome. 553 metastatic EGFR-mutant NSCLC patients received front-line EGFR-TKI treatment. Progression-free survival (PFS), overall survival (OS) and secondary T790M rate were analysed. BM was observed in 211 (38.2%) patients. BM (HR 1.20 [95% CI 0.99-1.48]; p = 0.053), ECOG PS 0-1 (HR 0.71 [95% CI 0.54-0.93]; p = 0.014) and afatinib treatment (HR 0.81 [95% CI 0.66-0.99]; p = 0.045) were associated with PFS. Afatinib-treated patients without BM demonstrated a significantly longer PFS (16.3 months) compared to afatinib-treated patients with BM (13.7 months) and to gefitinib/erlotinib-treated patients with (11.1 months) or without BM (14.2 months; p < 0.001). CNS-only progression trended higher in afatinib-treated patients. ECOG PS 0-1 (HR 0.41 [95% CI 0.31-0.56]; p < 0.001) and EGFR L858R mutation (HR 1.46 [95% CI 1.13-1.88]; p = 0.003), but not BM, were the predictors for OS. BM (OR 2.02 [95% CI 1.02-4.08]; p = 0.040), afatinib treatment (OR 0.26 [95% CI 0.12-0.50]; p < 0.001) and EGFR L858R mutation (OR 0.55 [95% CI 0.28-1.05]; p = 0.070) were associated with secondary T790M rate. In BM patients, gefitinib/erlotinib-treated ones with 19 deletion mutation and afatinib-treated ones with L858R mutation had the highest and the lowest T790M rate (94.4% vs. 27.3%, p < 0.001), respectively. BM and generation of EGFR-TKI jointly impact PFS and secondary T790M rate in patients with EGFR-mutant NSCLC, whereas OS was mainly associated with EGFR subtype.

Ensemble latent assimilation with deep learning surrogate model: application to drop interaction in a microfluidics device.

A major challenge in the field of microfluidics is to predict and control drop interactions. This work develops an image-based data-driven model to forecast drop dynamics based on experiments performed on a microfluidics device. Reduced-order modelling techniques are applied to compress the recorded images into low-dimensional spaces and alleviate the computational cost. Recurrent neural networks are then employed to build a surrogate model of drop interactions by learning the dynamics of compressed variables in the reduced-order space. The surrogate model is integrated with real-time observations using data assimilation. In this paper we developed an ensemble-based latent assimilation algorithm scheme which shows an improvement in terms of accuracy with respect to the previous approaches. This work demonstrates the possibility to create a reliable data-driven model enabling a high fidelity prediction of drop interactions in microfluidics device. The performance of the developed system is evaluated against experimental data (i.e., recorded videos), which are excluded from the training of the surrogate model. The developed scheme is general and can be applied to other dynamical systems.

Afatinib Treatment Alone or with Bevacizumab in a Real-World Cohort of Non-Small Cell Lung Cancer Patients with Epidermal Growth Factor Receptor Mutation.

BACKGROUND: Treatment outcome between afatinib alone or with bevacizumab in non-small cell lung cancer (NSCLC) patient with epidermal growth factor receptor (EGFR) mutation remains insufficiently reported. METHODS: A total of 405 advanced NSCLC patients with sensitizing-EGFR mutation receiving first-line single-agent afatinib or with bevacizumab were grouped and propensity score-matched. Progression-free survival (PFS), overall survival (OS) and secondary T790M mutation were analyzed. RESULTS: In the original cohort, 367 (90.6%) patients received afatinib treatment alone and 38 (9.4%) patients received afatinib plus bevacizumab. Patients who received bevacizumab combination were significantly younger (54.6 ± 10.9 vs. 63.9 ± 11.5; p < 0.001) compared to the afatinib alone group. After propensity score matching, the afatinib alone and afatinib plus bevacizumab groups contained 118 and 34 patients, respectively. A non-significantly higher objective response was noted in the afatinib plus bevacizumab group (82.4% vs. 67.8%; p = 0.133). In the propensity score-matched cohort, a bevacizumab add-on offered no increased PFS (16.1 vs. 15.0 months; p = 0.500), risk reduction of progression (HR 0.85 [95% CI, 0.52-1.40]; p = 0.528), OS benefit (32.1 vs. 42.0 months; p = 0.700), nor risk reduction of death (HR 0.85 [95% CI, 0.42-1.74] p = 0.660) compared to the single-agent afatinib. The secondary T790M rate in afatinib plus bevacizumab and afatinib alone groups was similar (56.3% vs. 49.4%, p = 0.794). Multivariate analysis demonstrated that EGFR L858R (OR 0.51 [95% CI, 0.26-0.97]; p = 0.044), EGFR uncommon mutation (OR 0.14 [95% CI, 0.02-0.64]; p = 0.021), and PFS longer than 12 months (OR 2.71 [95% CI, 1.39-5.41]; p = 0.004) were independent predictors of secondary T790M positivity. CONCLUSION: Bevacizumab treatment showed moderate efficacy in real-world, afatinib-treated NSCLC patients with EGFR-sensitizing mutation.