Daily Respiratory Research Analysis
Analyzed 54 papers and selected 3 impactful papers.
Summary
Analyzed 54 papers and selected 3 impactful articles.
Selected Articles
1. Proteomic profiling of early-stage non-small cell lung cancer identifies a high-performance protein signature associated with postoperative recurrence.
In 351 stage I NSCLC cases with external validation (n=103), a nine-protein panel significantly outperformed clinicopathologic models for disease-free survival prediction (AUC 0.898 vs 0.742), with validation AUC 0.810. Integrating proteomics with clinical features achieved robust 5-year recurrence prediction, supporting personalized postoperative surveillance and adjuvant therapy decisions.
Impact: Introduces a validated proteomic signature that materially improves recurrence prediction in early-stage NSCLC, offering a path toward precision postoperative management.
Clinical Implications: May guide intensified surveillance and selection for adjuvant therapy in ostensibly low-stage NSCLC after resection, pending prospective utility and cost-effectiveness studies.
Key Findings
- Identified 4,260 differentially expressed proteins associated with recurrence risk.
- Nine-protein model achieved AUC 0.898 vs 0.742 for DFS prediction over clinicopathologic model (P<0.001).
- Combined proteomic-clinical model showed AUC 0.896 (discovery) and 0.810 (external validation) for 5-year recurrence.
Methodological Strengths
- Discovery and external prospective validation cohorts with DIA-based LC-MS/MS.
- Robust statistical modeling (Cox regression, ROC analysis) and comparative benchmarking against clinicopathologic models.
Limitations
- Clinical data and outcomes were retrospectively collected, risking bias.
- Generalizability and clinical utility require prospective, multicenter impact and cost-effectiveness studies.
Future Directions: Prospective clinical utility trials to test risk-adapted adjuvant therapy and surveillance pathways based on the proteomic signature; assay standardization and health-economic evaluations.
BACKGROUND: The 5-year recurrence rate remains significantly high (∼30 %) in patients with early-stage Non-Small Cell Lung Cancer (NSCLC), even after complete tumor resection. Recurrence prediction primarily relies on pathological assessment and genomic abnormalities. However, proteins - the functional executors of genetic information - may offer additional prognostic value. In this study, we aimed to develop a model integrating proteomic and clinical features to improve recurrence prediction in early-stage NSCLC. METHODS: We recruited 351 stage Ⅰ NSCLC patients who underwent radical surgery in discovery corhort. An additional 103 participants from external prospective cohort were used for validation. Clinical data and follow-up outcomes were retrospectively collected. Tumor proteomics profiling was performed using liquid chromatography-mass spectrometry (LC-MS/MS). The proteomics data were acquired using a data-independent acquisition mode with a 150-minute gradient method and analyzed against the human UniProt database using DIA-NN (v1.8.1). We assessed the association between proteomic and clinicopathologic factors and disease-free survival (DFS) using Cox proportional hazards regression. A receiver operating characteristic (ROC) curve analysis was used to construct the predictive model. RESULTS: Of the 351 patients analyzed, 4260 differentially expressed proteins (DEPs) were identified as being associated with tumor recurrence. A nine-protein prediction model outperformed the clinicopathologic-based model (AUC, 0.898 vs. 0.742; P < 0.001) in predicting DFS. A combined model incorporating nine proteins and clinicopathological features demonstrated excellent predictive value for 5-year recurrence in the discovery cohort (AUC = 0.896). Nine proteins combined with clinicopathological features showed an AUC of 0.810 in the external validation cohort and an AUC of 0.844 in the combined cohort. CONCLUSION: Integrating tumor proteomics with clinicopathologic features enhances risk stratification and improves recurrence prediction after surgical resection of early-stage NSCLC. This approach may enable more personalized postoperative management through refined surveillance intervals and potential adjuvant therapies.
2. Calprotectin Is a Circulating Biomarker and Potential Therapeutic Target for Sarcopenia in Chronic Obstructive Pulmonary Disease.
In 235 stable COPD patients, serum calprotectin correlated with lower muscle strength and mass and accurately predicted sarcopenia (AUC 0.811 development; 0.805 validation). In cigarette smoke–exposed mice, the calprotectin inhibitor paquinimod mitigated muscle mass loss and increased cross-sectional area, positioning calprotectin as both a biomarker and actionable target.
Impact: Bridges clinical biomarker discovery with mechanistic validation, revealing a modifiable inflammatory pathway for COPD-related sarcopenia.
Clinical Implications: Supports serum calprotectin for sarcopenia risk stratification in COPD and motivates clinical trials of calprotectin pathway inhibitors to preserve muscle function.
Key Findings
- Serum calprotectin inversely correlated with handgrip and quadriceps strength and with rectus femoris thickness/CSA (all p<0.001).
- Calprotectin levels were higher in COPD patients with sarcopenia; predictive performance AUC 0.811 (development) and 0.805 (validation).
- Paquinimod (10 mg/kg/day) reduced smoke-induced muscle mass loss and increased muscle CSA in mice.
Methodological Strengths
- Independent development and validation patient cohorts with consistent AUCs.
- Translational in vivo testing of a calprotectin-specific inhibitor supporting causality.
Limitations
- Human analyses are observational; residual confounding is possible.
- Therapeutic evidence derives from a mouse model; human interventional data are lacking.
Future Directions: Prospective studies to validate clinical cutoffs and randomized trials of calprotectin inhibition (e.g., paquinimod) to prevent or reverse COPD-related sarcopenia.
BACKGROUND: Sarcopenia, an important complication of chronic obstructive pulmonary disease (COPD), is significantly associated with increased mortality. Systemic inflammation is an important trigger of COPD-related skeletal muscle dysfunction. Calprotectin is a damage-associated molecular pattern involved in the inflammatory response, but its exact role and mode of action in COPD-related skeletal muscle dysfunction remain unclear. This study aimed to determine whether calprotectin is involved in COPD-related sarcopenia. METHODS: In this study, 235 patients with stable COPD were divided into the development (n = 117) and validation (n = 118) groups, and serum calprotectin concentrations were measured by enzyme-linked immunosorbent assays (ELISAs). Paquinimod, an oral calprotectin-specific inhibitor, was used to investigate the involvement of calprotectin in cigarette smoke (CS)-induced skeletal muscle dysfunction in vivo. RESULTS: Handgrip strength and quadriceps muscle strength, essential indicators of muscle strength, were negatively correlated with serum calprotectin levels (r = -0.367, p < 0.001; r = -0.409, p < 0.001). The 5-time sit-to-stand test results, which reflect endurance and physical strength, were positively correlated with serum calprotectin levels (r = 0.290, p = 0.006). Ultrasound measurement of the rectus femoris muscle revealed negative correlations of serum calprotectin levels with both muscle thickness (r = -0.448, p < 0.001) and cross-sectional area (r = -0.495, p < 0.001). Furthermore, serum calprotectin levels were significantly greater in patients with sarcopenia than in those without sarcopenia (90.09 ± 25.72 ng/mL vs. 59.56 ± 23.22 ng/mL, p < 0.001). Importantly, serum calprotectin levels could effectively predict sarcopenia in COPD patients in the development set (AUC = 0.811) and validation set (AUC = 0.805). In C57BL/6 mice with CS-induced muscle dysfunction, paquinimod (10 mg/kg/day) reduced CS-induced muscle mass loss (skeletal muscle weight 1.15% ± 0.09% vs. 1.33% ± 0.09%; p = 0.005) and increased the muscle cross-sectional area (1375 ± 536.9 μm CONCLUSIONS: Serum calprotectin levels can be used to accurately predict sarcopenia in patients with COPD, and the calprotectin inhibitor paquinimod is a potential treatment for CS-induced skeletal muscle dysfunction.
3. Diagnostic performance of nanopore-targeted sequencing for pulmonary infections in a tuberculosis-endemic setting: A prospective observational study.
In a prospective cohort (n=305; 312 respiratory specimens), nanopore-targeted sequencing identified adjudicated pathogens in 263/283 paired cases, outperforming culture (185/283) with strong sensitivity across M. tuberculosis, nontuberculous mycobacteria, and fungi. It delivered a 12.2% incremental diagnostic yield and detected more pathogens in polymicrobial disease, though bacterial specificity in non-sterile specimens was lower.
Impact: Demonstrates single-assay, multi-kingdom pathogen detection in TB-endemic pulmonary infections with prospective benchmarking, informing adoption pathways and interpretation caveats.
Clinical Implications: NTS can complement conventional microbiology to accelerate and broaden pathogen detection, particularly for mycobacteria and fungi; bacterial calls in non-sterile samples should be interpreted with clinical correlation.
Key Findings
- NTS identified adjudicated pathogens in 263/283 paired cases versus 185/283 by culture.
- Sensitivity/specificity: M. tuberculosis 83.0%/99.4%; NTM 89.8%/98.2%; fungi 92.9%/91.1%; bacteria 97.4%/57.8%.
- Overall incremental diagnostic yield of 12.2%; in polymicrobial infections, NTS detected all pathogens in 77.8% vs 62.5% for conventional testing (P=0.06).
Methodological Strengths
- Prospective design with parallel conventional testing and blinded clinical adjudication.
- Performance reported across pathogen classes including mycobacteria, fungi, and bacteria.
Limitations
- Lower bacterial specificity in non-sterile respiratory specimens necessitates careful clinical correlation.
- Single specialized TB center; generalizability, turnaround time, and cost-effectiveness require further study.
Future Directions: Multicenter implementation studies to refine interpretive criteria, assess turnaround/cost, and integrate NTS into diagnostic algorithms for TB-endemic settings.
BACKGROUND: Pulmonary infections in tuberculosis (TB)-endemic settings are heterogeneous and commonly polymicrobial. Nanopore-targeted sequencing (NTS) enables detection of mycobacteria, bacteria, and fungi in a single targeted assay. However, performance across pathogen classes in TB-endemic cohorts remains limited. METHODS: We conducted a prospective study at a specialized TB hospital, enrolling adults with suspected pulmonary infections across five predefined diagnostic categories: pulmonary TB, nontuberculous mycobacterial pulmonary disease, bacterial, fungal, and polymicrobial infection. Respiratory specimens (n=312) from 305 patients were tested in parallel by conventional microbiological testing (CMT) and NTS. Blinded clinical diagnoses served as the reference standard. RESULTS: Among 283 paired cases, NTS identified the adjudicated pathogens in 263 cases, whereas culture identified them in 185 cases. NTS showed a sensitivity/specificity of 83.0%/99.4% for Mycobacterium tuberculosis, 89.8%/98.2% for nontuberculous mycobacteria, 92.9%/91.1% for fungi, and 97.4%/57.8% for bacteria. In 72 polymicrobial infections, NTS detected all adjudicated pathogens in 77.8% versus 62.5% for CMT, a non-significant difference (P=0.06). Overall, NTS provided a 12.2% incremental diagnostic yield. CONCLUSIONS: NTS offers sensitive, single-assay detection of diverse pulmonary pathogens in TB-endemic settings. By streamlining workflows and improving detection of fastidious or co-infecting organisms, it may complement conventional methods. However, bacterial NTS findings in non-sterile respiratory specimens require clinical correlation.