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.

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.

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.

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.

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.

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.

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.

The different overall survival between single-agent EGFR-TKI treatment and with bevacizumab in non-small cell lung cancer patients with brain metastasis.

Comparison of epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) monotherapy or with bevacizumab in real-world non-small cell lung cancer (NSCLC) patients was lacking. 310 patients of advanced NSCLC with common EGFR mutation receiving first-generation EGFR-TKI monotherapy or with bevacizumab were included and propensity-score matched. Progression-free survival (PFS), overall survival (OS) and secondary T790M mutation were analysed. Patients receiving EGFR-TKI and bevacizumab were significantly younger, had better performance status and with high incidence of brain metastasis (55.8%). In the propensity-score matched cohort, PFS (13.5 vs. 13.7 months; log-rank p = 0.700) was similar between the two groups. The OS (61.3 vs. 34.2 months; log-rank p = 0.010) and risk reduction of death (HR 0.42 [95% CI 0.20-0.85]; p = 0.017) were significantly improved in EGFR-TKI plus bevacizumab group. Analysis of treatment by brain metastasis status demonstrated EGFR-TKI plus bevacizumab in patients with brain metastasis was associated with significant OS benefit compared to other groups (log-rank p = 0.030) and these patients had lower early-CNS and early-systemic progressions. The secondary T790M did not significantly differ between EGFR-TKI plus bevacizumab and EGFR-TKI monotherapy groups (66.7% vs. 75.0%, p = 0.460). Forty-one (31.1%) and 31 (23.5%) patients received subsequent osimertinib and chemotherapy, respectively. The post-progression OS of osimertinib and chemotherapy were 22.1 and 44.9 months in EGFR-TKI plus bevacizumab group and were 10.0 and 14.1 months in EGFR-TKI monotherpay group, respectively. First-generation EGFR-TKI with bevacizumab improved treatment efficacy in real-world patients of NSCLC with EGFR mutation. Patients with brain metastasis received additional OS benefit from this treatment.

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.

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.

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.

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.

First- or second-generation epidermal growth factor receptor tyrosine kinase inhibitors in a large, real-world cohort of patients with non-small cell lung cancer.

BACKGROUND: There are limited comparisons of first- and second-generation EGFR tyrosine kinase inhibitors (TKIs) in large, real-world cohorts of non-small cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) mutations. METHODS: Patients with advanced NSCLC (N = 612) with common EGFR mutations receiving first-line gefitinib/erlotinib and afatinib were grouped and propensity-score matched. Progression-free survival (PFS), overall survival (OS) and secondary T790M mutations were analyzed. RESULTS: The gefitinib/erlotinib and afatinib groups each contained 206 patients after matching. Compared with gefitinib/erlotinib, patients receiving afatinib achieved longer median PFS (16.3 versus 14.2 months; log-rank test p = 0.020) and had a lower risk of progression [hazard ratio (HR) 0.73 (95% confidence interval (CI), 0.57-0.94); p = 0.017]. Median OS (37.3 versus 34.2 months; log-rank test p = 0.500) and reduction in risk of death [HR 0.89 (95% CI, 0.65-1.23); p = 0.476] did not differ significantly between groups. T790M positivity was significantly higher in the gefitinib/erlotinib than afatinib group (70.9% versus 44.6%, p < 0.001). Multivariate analysis demonstrated that afatinib was independently associated with lower T790M positivity [odds ratio (OR) 0.27 (95% CI, 0.14-0.53); p < 0.001], whereas ⩾12 months PFS after EGFR-TKI treatment [OR 3.00 (95% CI, 1.56-5.98); p = 0.001] and brain metastasis [OR 2.12 (95% CI, 1.08-4.26); p = 0.030] were associated with higher T790M positivity. Sequential third-generation EGFR-TKI treatment was administered to 63 patients, in whom median OS after the second-third-generation and first-third-generation EGFR-TKI sequences were 38.8 and 29.1 months, respectively. CONCLUSION: Compared with gefitinib/erlotinib, afatinib had a higher treatment efficacy and a lower secondary T790M positivity in a large, real-world cohort of Asian patients with EGFR-mutated NSCLC.

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.

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.

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 data driven methodology for social science research with left-behind children as a case study.

For decades, traditional correlation analysis and regression models have been used in social science research. However, the development of machine learning algorithms makes it possible to apply machine learning techniques for social science research and social issues, which may outperform standard regression methods in some cases. Under the circumstances, this article proposes a methodological workflow for data analysis by machine learning techniques that have the possibility to be widely applied in social issues. Specifically, the workflow tries to uncover the natural mechanisms behind the social issues through a data-driven perspective from feature selection to model building. The advantage of data-driven techniques in feature selection is that the workflow can be built without so much restriction of related knowledge and theory in social science. The advantage of using machine learning techniques in modelling is to uncover non-linear and complex relationships behind social issues. The main purpose of our methodological workflow is to find important fields relevant to the target and provide appropriate predictions. However, to explain the result still needs theory and knowledge from social science. In this paper, we trained a methodological workflow with left-behind children as the social issue case, and all steps and full results are included.

Consolidation treatment of durvalumab after chemoradiation in real-world patients with stage III unresectable non-small cell lung cancer.

BACKGROUND: Treatment for stage III non-small cell lung cancer (NSCLC) of unresectable disease mainly involves concurrent chemoradiation (CRT). Post-CRT consolidation treatment with durvalumab is a major therapeutic advance that provides survival benefit in this group of patients. However, the performance of this treatment strategy remains to be studied in a real-world setting. METHODS: A total of 31 patients who had disease control post-CRT were included in the durvalumab early access program (EAP) as an intent-to-treat cohort and retrospectively reviewed for post-CRT progression-free survival (PFS) and time to metastatic disease or death (TMDD). The neutrophil-to-lymphocyte ratio (NLR) at the initiation of durvalumab was analyzed in 29 patients. RESULTS: The median time from the completion of concurrent CRT to the initiation of durvalumb was 2.8 months. The objective response was 25.8% and the 12 month PFS and TMDD-free rate were 56.4% and 66.9%, respectively. The low NLR patients showed a significantly longer post-CRT PFS (not reach vs. 12.0 months [95% CI: 5.5-not estimable]; P = 0.040; the hazard ratio for disease progression or death, 0.23 [95% CI: 0.05-1.00]; P = 0.048) and the 12 month post-CRT PFS rate (82.5 vs. 42.6%). The post-CRT TMDD (not reach vs. 12.6 months, [95% CI: 10.8-not estimable]; P = 0.010; the hazard ratio for distant metastasis or death, 0.11 [95% CI: 0.01-0.88]; P = 0.037) and 12 month post-CRT TMDD-free rate (90.9 vs. 57.1%) were also significantly higher in the low NLR patients. CONCLUSIONS: Durvalumab consolidation treatment in real-world patients showed substantial efficacy and the correlation with the NLR level warrants further investigation.

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.