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Abstract Plasma proteins are considered the most informative source of biomarkers for disease diagnosis and monitoring. Mass spectrometry (MS)-based proteomics has been applied to identify biomarkers in plasma, but the complexity of the plasma proteome and the extremely large dynamic range of protein abundances in plasma make the clinical application of plasma proteomics highly challenging. We designed and synthesized zeolite-based nanoparticles to deplete high-abundance plasma proteins. The resulting novel plasma proteomic assay can measure approximately 3000 plasma proteins in a 45 min chromatographic gradient. Compared to those in neat and depleted plasma, the plasma proteins identified by our assay exhibited distinct biological profiles, as validated in several public datasets. A pilot investigation of the proteomic profile of a hepatocellular carcinoma (HCC) cohort identified 15 promising protein features, highlighting the diagnostic value of the plasma proteome in distinguishing individuals with and without HCC. Furthermore, this assay can be easily integrated with all current downstream protein profiling methods and potentially extended to other biofluids. In conclusion, we established a robust and efficient plasma proteomic assay with unprecedented identification depth, paving the way for the translation of plasma proteomics into clinical applications. Graphical Abstract

Abstract Background There is no uniform standard for a strongly positive bronchodilation test (BDT) result. In addition, the role of bronchodilator response in differentiating between asthma, chronic obstructive pulmonary disease (COPD), and asthma–COPD overlap (ACO) in patients with a positive BDT result is unclear. We explored a simplified standard of a strongly positive BDT result and whether bronchodilator response combined with fractional exhaled nitric oxide (FeNO) can differentiate between asthma, COPD, and ACO in patients with a positive BDT result. Methods Three standards of a strongly positive BDT result, which were, respectively, defined as post-bronchodilator forced expiratory volume in 1-s responses (ΔFEV1) increasing by at least 400 mL + 15% (standard I), 400 mL (standard II), or 15% (standard III), were analyzed in asthma, COPD, and ACO patients with a positive BDT result. Receiver operating characteristic curves were used to determine the optimal values of ΔFEV1 and FeNO. Finally, the accuracy of prediction was verified by a validation study. Results The rates of a strongly positive BDT result and the characteristics between standards I and II were consistent; however, those for standard III was different. ΔFEV1 ≥ 345 mL could predict ACO diagnosis in COPD patients with a positive BDT result (area under the curve [AUC]: 0.881; 95% confidence interval [CI] 0.83–0.94), with a sensitivity and specificity of 90.0% and 91.2%, respectively, in the validation study. When ΔFEV1 was

Abstract Background Accurately distinguishing between pulmonary infection and colonization in patients with Acinetobacter baumannii is of utmost importance to optimize treatment and prevent antibiotic abuse or inadequate therapy. An efficient automated sorting tool could prompt individualized interventions and enhance overall patient outcomes. This study aims to develop a robust machine learning classification model using a combination of time-series chest radiographs and laboratory data to accurately classify pulmonary status caused by Acinetobacter baumannii. Methods We proposed nested logistic regression models based on different time-series data to automatically classify the pulmonary status of patients with Acinetobacter baumannii. Advanced features were extracted from the time-series data of hospitalized patients, encompassing dynamic pneumonia indicators observed on chest radiographs and laboratory indicator values recorded at three specific time points. Results Data of 152 patients with Acinetobacter baumannii cultured from sputum or alveolar lavage fluid were retrospectively analyzed. Our model with multiple time-series data demonstrated a higher performance of AUC (0.850, with a 95% confidence interval of [0.638–0.873]), an accuracy of 0.761, a sensitivity of 0.833. The model, which only incorporated a single time point feature, achieved an AUC of 0.741. The influential model variables included difference in the chest radiograph pneumonia score. Conclusion Dynamic assessment of time-series chest radiographs and laboratory data using machine learning allowed for accurate classification of colonization and infection with Acinetobacter baumannii. This demonstrates the potential to help clinicians provide individualized treatment through early detection.

Abstract Serological tests for Epstein–Barr virus (EBV) antibodies have been widely conducted for the screening of nasopharyngeal carcinoma (NPC) in endemic areas. Further risk stratification of NPC can be achieved through plasma lipoprotein and metabolic profiles. A total of 297 NPC patients and 149 EBV‐positive participants are enrolled from the NCT03919552 and NCT05682703 cohorts for plasma nuclear magnetic resonance (NMR) metabolomic analysis. Small, dense very low density lipoprotein particles (VLDL‐5) and large, buoyant low density lipoprotein particles (LDL‐1) are found to be closely associated with nasopharyngeal carcinogenesis. Herein, an NMR‐based risk score (NRS), which combines lipoprotein subfractions and metabolic biomarkers relevant to NPC, is developed and well validated within a multicenter cohort. Combining the median cutoff value of the NRS (N50) with that of the serological test for EBV antibodies, the risk stratification model achieves a satisfactory performance in which the area under the curve (AUC) is 0.841 (95% confidence interval: 0.811‐0.871), and the positive predictive value (PPV) reaches 70.08% in the combined cohort. These findings not only suggest that VLDL‐5 and LDL‐1 particles can serve as novel risk factors for NPC but also indicate that the NRS has significant potential in personalized risk prediction for NPC.

Abstract Background Lung cancer is the most common cancer‐related death worldwide. In 2022, the number of daily deaths of lung cancer was estimated to reach around 350 in the United States. Lung adenocarcinoma is the main subtype of lung cancer and patients with malignant pleural effusion (MPE) suffer from poor prognosis. Microbiota and its metabolites are associated with cancer progression. However, the effect of pleural microbiota on pleural metabolic profile of MPE in lung adenocarcinoma patients remains largely unknown. Methods Pleural effusion samples collected from lung adenocarcinoma patients with MPE (n = 14) and tuberculosis pleurisy patients with benign pleural effusion (BPE group, n = 10) were subjected to microbiome (16S rRNA gene sequencing) and metabolome (liquid chromatography tandem mass spectrometry [LC‐MS/MS]) analyses. The datasets were analyzed individually and integrated for combined analysis using various bioinformatic approaches. Results The metabolic profile of MPE in lung adenocarcinoma patients were clearly distinguished from BPE with 121 differential metabolites across six significantly enriched pathways identified. Glycerophospholipids, fatty and carboxylic acids, and derivatives were the most common differential metabolites. Sequencing of microbial data revealed nine significantly enriched genera (i.e., Staphylococcus, Streptococcus, Lactobacillus) and 26 enriched ASVs (i.e., species Lactobacillus_delbrueckii) in MPE. Integrated analysis correlated MPE‐associated microbes with metabolites, such as phosphatidylcholine and metabolites involved in the citrate cycle pathway. Conclusion Our results provide substantial evidence of a novel interplay between the pleural microbiota and metabolome, which was drastically perturbed in MPE in lung adenocarcinoma patients. Microbe‐associated metabolites can be used for further therapeutic explorations.

Abstract Background Up-regulation of aerobic glycolysis has been reported as a characterization of asthma and facilitates airway inflammation. We has been previously reported that short isoform thymic stromal lymphopoietin (sTSLP) could reduce inflammation in asthmatic airway epithelial cells. Here we wanted to investigate whether the inhibition of sTSLP on asthma is related to aerobic glycolysis. Methods Asthmatic model was established in challenging Male BALB/c mice and 16-HBE (human bronchial epithelial) cell line with house dust mite (HDM). Indicators of glycolysis were assessed to measure whether involve in sTSLP regulating airway epithelial cells inflammation in asthmatic model in vivo and in vitro. Results sTSLP decreased inflammation of asthmatic airway and aerobic glycolysis in mice. HDM or long isoform thymic stromal lymphopoietin (lTSLP) promoted HIF-1α expression and aerobic glycolysis by miR-223 to target and inhibit VHL (von Hippel-Lindau) expression 16-HBE. Inhibition of aerobic glycolysis restrained HDM- and lTSLP-induced inflammatory cytokines production. sTSLP along had almost no potential to alter aerobic glycolysis of 16-HBE. But sTSLP decreased LDHA (lactate dehydrogenase A) and LD (Lactic acid) levels in BALF, and HIF-1α and LDHA protein levels in airway epithelial cells of asthma mice model. lTSLP and sTSLP both induced formation of TSLPR and IL-7R receptor complex, and lTSLP obviously facilitated phosphorylation of JAK1, JAK2 and STAT5, while sTSLP induced a little phosphorylation of JAK1 and STAT5. Conclusion We identified a novel mechanism that lTSLP could promote inflammatory cytokines production by miR-223/VHL/HIF-1α pathway to upregulate aerobic glycolysis in airway epithelial cells in asthma. This pathway is suppressed by sTSLP through occupying binding site of lTSLP in TSLPR and IL-7R receptor complex.

Abstract Background Exposure to toluene diisocyanate (TDI) is a significant pathogenic factor for asthma. We previously reported that the receptor for advanced glycation end products (RAGE) plays a key role in TDI-induced asthma. Histone deacetylase (HDAC) has been reported to be important in asthmatic pathogenesis. However, its effect on TDI-induced asthma is not known. The aim of this study was to determine the role of RAGE and HDAC in regulating airway inflammation using a TDI-induced murine asthma model. Methods BALB/c mice were sensitized and challenged with TDI to establish an asthma model. FPS-ZM1 (RAGE inhibitor), JNJ-26482585 and romidepsin (HDAC inhibitors) were administered intraperitoneally before each challenge. In vitro, the human bronchial epithelial cell line 16HBE was stimulated with TDI-human serum albumin (TDI-HSA). RAGE knockdown cells were constructed and evaluated, and MK2006 (AKT inhibitor) was also used in the experiments. Results In TDI-induced asthmatic mice, the expression of RAGE, HDAC1, and p-AKT/t-AKT was upregulated, and these expressions were attenuated by FPS-ZM1. Airway reactivity, Th2 cytokine levels in lymph supernatant, IgE, airway inflammation, and goblet cell metaplasia were significantly increased in the TDI-induced asthmatic mice. These increases were suppressed by JNJ-26482585 and romidepsin. In addition, JNJ-26482585 and romidepsin ameliorated the redistribution of E-cadherin and β-catenin in TDI-induced asthma. In TDI-HSA-stimulated 16HBE cells, knockdown of RAGE attenuated the upregulation of HDAC1 and phospho-AKT (p-AKT). Treatment with the AKT inhibitor MK2006 suppressed TDI-induced HDAC1 expression. Conclusions These findings indicate that RAGE modulates HDAC1 expression via the PI3K/AKT pathway, and that inhibition of HDAC prevents TDI-induced airway inflammation.

BackgroundClinically, only a minority of patients benefit from immunotherapy and few efficient biomarkers have been identified to distinguish patients who would respond to immunotherapy. The tumor microenvironment (TME) is reported to contribute to immunotherapy response, but details remain unknown. We aimed to construct a prognostic model based on the TME of lung adenocarcinoma (LUAD) to predict the prognosis and immunotherapy efficacy.MethodsWe integrated computational algorithms to describe the immune infiltrative landscape of LUAD patients. With the least absolute shrinkage and selection operator (LASSO) and Cox regression analyses, we developed a LUAD tumor microenvironment prognostic signature (LATPS). Subsequently, the immune characteristics and the benefit of immunotherapy in LATPS-defined subgroups were analyzed. RNA sequencing of tumor samples from 28 lung cancer patients treated with anti-PD-1 therapy was conducted to verify the predictive value of the LATPS.ResultsWe constructed the LATPS grounded on four genes, including UBE2T, KRT6A, IRX2, and CD3D. The LATPS-low subgroup had a better overall survival (OS) and tended to have a hot immune phenotype, which was characterized by an elevated abundance of immune cell infiltration and increased activity of immune-related pathways. Additionally, tumor immune dysfunction and exclusion (TIDE) score was markedly decreased in the LATPS-low subgroup, indicating an enhanced opportunity to benefit from immunotherapy. Survival analysis in 28 advanced lung cancer patients treated with an anti-PD-1 regimen at Nanfang hospital revealed that the LATPS-low subgroup had better immunotherapy benefit.ConclusionLATPS is an effective predictor to distinguish survival, immune characteristics, and immunotherapy benefit in LUAD patients.

Abstract Background Irradiation has emerged as a valid tool for nasopharyngeal carcinoma (NPC) in situ treatment; however, NPC derived from tissues treated with irradiation is a main cause cancer-related death. The purpose of this study is to uncover the underlying mechanism regarding tumor growth after irradiation and provided potential therapeutic strategy. Methods Fibroblasts were extracted from fresh NPC tissue and normal nasopharyngeal mucosa. Immunohistochemistry was conducted to measure the expression of α-SMA and FAP. Cytokines were detected by protein array chip and identified by real-time PCR. CCK-8 assay was used to detect cell proliferation. Radiation-resistant (IRR) 5-8F cell line was established and colony assay was performed to evaluate tumor cell growth after irradiation. Signaling pathways were acquired via gene set enrichment analysis (GSEA). Comet assay and γ-H2AX foci assay were used to measure DNA damage level. Protein expression was detected by western blot assay. In vivo experiment was performed subcutaneously. Results We found that radiation-resistant NPC tissues were constantly infiltrated with a greater number of cancer-associated fibroblasts (CAFs) compared to radiosensitive NPC tissues. Further research revealed that CAFs induced the formation of radioresistance and promoted NPC cell survival following irradiation via the IL-8/NF-κB pathway to reduce irradiation-induced DNA damage. Treatment with Tranilast, a CAF inhibitor, restricted the survival of CAF-induced NPC cells and attenuated the of radioresistance properties. Conclusions Together, these data demonstrate that CAFs can promote the survival of irradiated NPC cells via the NF-κB pathway and induce radioresistance that can be interrupted by Tranilast, suggesting the potential value of Tranilast in sensitizing NPC cells to irradiation.

Purpose: This multi-center retrospective study determines whether the ΔCT value of the Amplified Refractory Mutation System (ARMS) predicts the efficacy of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) in EGFR-mutant advanced non–small-cell lung cancer (NSCLC).Patients and methods: Patients who harbored an exon 19 deletion (19Del) or L858R mutation detected by the ARMS and previously received treatment of EGFR-TKIs as a monotherapy were enrolled. A total of 108 NSCLC patients in four hospitals were enrolled. We divided the patients into a high ΔCT group (Group H) and a low ΔCT group (Group L) by the Martingale residuals analysis and log-rank test. The primary outcome was progression-free survival (PFS). Univariate analysis and multivariable regression were applied to compare the PFS between the groups.Result: The Martingale residuals analysis and log-rank test were applied to find the cutoff ΔCT value (0.8). In the 108 patients we enrolled, 59 were in group L and 49 were in group H. Patients’ demographics and clinical characteristics, including age, sex, smoking history, pathology, mutation sites, TNM stage, and line of TKIs therapy, were not significantly different between group L and group H. The median PFS was 11.1 months in group L and 6.9 months in group H, and the difference showed statistical significance (p < 0.001). Moreover, the objective response rates (ORRs) in group L was significantly higher than in group H (61.0 vs 34.7%, p = 0.002). The median OS was 25.0 months in group L and 20.0 months in group H (p = 0.046).Conclusion: The ΔCT value of ARMS could be an efficacy predictor for EGFR-TKI treatment in advanced EGFR-mutant NSCLC.

An amendment to this paper has been published and can be accessed via the original article.

We describe a 51-year-old woman who was admitted to hospital because of cough and expectoration accompanied with general fatigue and progressive dyspnea. Chest HRCT scan showed areas of ground glass attenuation, consolidation, and traction bronchiectasis in bilateral bases of lungs. BAL fluid test and transbronchial lung biopsy failed to offer insightful evidence for diagnosis. She was clinically diagnosed with acute interstitial pneumonia (AIP). Treatment with mechanical ventilation and intravenous application of methylprednisolone (80 mg/day) showed poor clinical response and thus was followed by steroid pulse therapy (500 mg/day, 3 days). However, she died of respiratory dysfunction eventually. Autopsy showed diffuse alveolar damage associated with hyaline membrane formation, pulmonary interstitial, immature collagen edema, and focal type II pneumocyte hyperplasia.

High mobility group protein B1 (HMGB1) has been implicated as an important mediator in the pathogenesis of asthma and chronic obstructive pulmonary disease (COPD). However, the expression of HMGB1 in plasma and sputum of patients with asthma and COPD across disease severity needs to be defined. The objective of the study was to examine the induced sputum and plasma concentrations of HMGB1 in COPD and asthmatic patients to determine differences in HMGB1 levels between these diseases and their relationship with airway obstruction and inflammatory patterns. A total of 147 participants were enrolled in this study. The participants included 34 control subjects, 61 patients with persistent asthma (according to the Global Initiative for Asthma [GINA] guidelines) and 47 patients with stable COPD (stratified by Global Initiative for Chronic Obstructive Lung Disease [GOLD] status). Spirometry was performed before sputum induction. HMGB1 levels in induced sputum and plasma were determined by enzyme-linked immunosorbent assay. Sputum and plasma concentrations of HMGB1 in patients with asthma and COPD were significantly higher than concentrations in control subjects and were significantly negatively correlated with forced expiratory volume in 1 s (FEV1), FEV1 (% predicted) in all 147 participants. The levels of HMGB1 in induced sputum of COPD patients were significantly higher than those of asthma patients and healthy controls (P < 0.001). This difference was present even after adjusting for sex, age, smoking status, daily dose of inhaled corticosteroids and disease severity. There were no significant differences in HMGB1 levels between patients with eosinophilic and noneosinophilic asthma. HMGB1 levels in asthmatic and COPD patients were positively correlated with neutrophil counts and percentage of neutrophils. In multivariate analysis, the two diseases (asthma and COPD) and disease severity were independent predictors of sputum HMGB1, but not smoking, age or use of inhaled corticosteroids. In conclusion, these data support a potential role for HMGB1 as a biomarker and diagnostic tool for the differential diagnosis of asthma and COPD. The importance of this observation on asthma and COPD mechanisms and outcomes should be further investigated in large prospective studies. [ABSTRACT FROM AUTHOR]

Damage-associated molecular pattern molecules such as high-mobility group box 1 protein (HMGB1) and heat shock protein 70 (HSP70) have been implicated in the pathogenesis of asthma. The aim of our study was to examine the induced sputum and plasma concentrations of HSP70 in asthmatic patients to determine their relationship with airway obstruction. Thirty-four healthy controls and 56 patients with persistent bronchial asthma matched for gender and age were enrolled in this study. Spirometry measurements were performed before sputum induction. HSP70 levels in induced sputum and plasma were measured using the ELISA Kit. Sputum and plasma concentrations of HSP70 in asthmatics patients were significantly higher than that in control subjects (sputum, (0.88 ng/ml (0.27-1.88 ng/ml) versus 0.42 ng/ml (0.18-0.85 ng/ml), p < 0.001); plasma, (0.46 ng/ml (0.20-0.98 ng/ml) versus 0.14 ng/ml (0.11-0.37 ng/ml), p < 0.001) and were significantly negatively correlated with forced expiratory volume in 1 s (FEV1), FEV1 (percent predicted), and FEV1/FVC in all 90 participants and 56 patients with asthma. There were no significant differences in HSP70 levels between patients with eosinophilic and non-eosinophilic asthma. HSP70 levels in plasma were positively correlated with neutrophil count, and HSP70 levels in induced sputum were positively correlated with lymphocyte count. In multivariate analysis, independent predictors of sputum HSP70 were diseases and disease severity but not smoking, age, or gender, and independent predictors of plasma HSP70 were also diseases and disease severity. In conclusion, this study indicates that induced sputum and plasma HSP70 could serve as a useful marker for assessing the degree of airway obstruction in patients with asthma. However, further investigation is needed to establish the role of circulating and sputum HSP70 in the pathogenesis of asthma.