Idiopathic pulmonary fibrosis is characterized by loss of lung epithelial cells and inexorable progression of fibrosis with no effective and approved treatments. The distal airway stem/progenitor cells (DASCs) have been shown to have potent regenerative capacity after lung injury. In this work, we aimed to define the role of mouse DASCs (mDASCs) in response to bleomycin-induced lung fibrosis in mice. The mDASCs were isolated, expanded in vitro, and labeled with GFP by lentiviral infection. The labeled mDASCs were intratracheally instilled into bleomycin-induced pulmonary fibrosis mice on day 7. Pathological change, collagen content, α-SMA expression, lung function, and mortality rate were assessed at 7, 14, and 21 days after bleomycin administration. Tissue section and direct fluorescence staining was used to show the distribution and differentiation of mDASCs in lung. The transplanted mDASCs could incorporate, proliferate, and differentiate into type I pneumocytes in bleomycin-injured lung. They also inhibited fibrogenesis by attenuating the deposition of collagen and expression of α-SMA. In addition, mDASCs improved pulmonary function and reduce mortality in bleomycin-induced pulmonary fibrosis mice. The data strongly suggest that mDASCs could ameliorate bleomycin-induced pulmonary fibrosis by promotion of lung regeneration and inhibition of lung fibrogenesis.

In 2021, the fifth edition of the World Health Organization (WHO) classification of thoracic tumors introduced a new category, “Thoracic SMARCA4-deficient undifferentiated tumor”, highlighting SMARCA4 deficiency as a key molecular marker for classifying as “other pulmonary epithelial tumors”. SMARCA4 is a gene encoding a protein involved in chromatin remodeling, and approximately 8% of non-small cell lung cancer (NSCLC) patients exhibit SMARCA4 deletions. These patients are more prone to drug resistance, early recurrence, and unfavorable clinical outcomes. Moreover, NSCLC patients with concomitant SMARCA4 mutations may not benefit from currently available treatments, underscoring the distinctiveness of this subgroup. Thoracic SMARCA4-deficient undifferentiated tumors (SMARCA4-UT) represent distinct entities from SMARCA4-deficient non-small cell lung cancer (SMARCA4-dNSCLC). This distinction is supported by their divergent pathological characteristics, demographic profiles, and survival outcomes. NSCLC cases deficient in SMARCA4 exhibit high malignancy, yet the precise biological mechanisms underlying this phenomenon remain under intensive investigation. Pathological examination and immunohistochemistry can effectively differentiate SMARCA4-UT from SMARCA4-dNSCLC. SMARCA4-UT typically manifests as adenocarcinoma or, more rarely, as squamous cell carcinoma with undifferentiated rhabdomyoblastic morphology. Therefore, elucidating the mechanisms underlying SMARCA4 alterations in NSCLC and their regulatory roles in tumorigenesis and the microenvironment is crucial. This article aims to discuss the structure, biological functions, significance in NSCLC development, and emerging potential therapeutic strategies related to SMARCA4 while providing clinical practice guidance for NSCLC patients with SMARCA4 deletions.

Recent research highlights the significance of exosomes and long noncoding RNAs (lncRNAs) in cancer progression and drug resistance, but their role in lung adenocarcinoma (LUAD) is not fully understood. We analyzed 121 exosome-related (ER) mRNAs from the ExoBCD database, along with mRNA and lncRNA expression profiles of TCGA-LUAD using “DESeq2”, “survival,” “ConsensusClusterPlus,” “GSVA,” “estimate,” “glmnet,” “clusterProfiler,” “rms,” and “pRRophetic” R packages. This comprehensive approach included univariate cox regression, unsupervised consensus clustering, GSEA, functional enrichment analysis, and prognostic model construction. Our study identified 134 differentially expressed ER-lncRNAs, with 19 linked to LUAD prognosis. These ER-lncRNAs delineated two patient subtypes, one with poorer outcomes. Additionally, 286 differentially expressed genes were related to these ER-lncRNAs, 261 of which also correlated with LUAD prognosis. We constructed an ER-lncRNA-related prognostic model and calculated an ER-lncRNA-related risk score (ERS), revealing that a higher ERS correlates with poor overall survival in both the Meta cohort and two validation cohorts. The ERS potentially serves as an independent prognostic factor, and the prognostic model demonstrates superior predictive power. Notably, significant differences in the immune landscape were observed between the high- and low-ERS groups. Drug sensitivity analysis indicated varying responses to common chemotherapy drugs based on ERS stratification, with the high-ERS group showing greater sensitivity, except to rapamycin and erlotinib. Experimental validation confirmed that thymidine kinase 1 enhances lung cancer invasion, metastasis, and cell cycle progression. Our study pioneers an ER-lncRNA-related prognostic model for LUAD, proposing that ERS-based risk stratification could inform personalized treatment strategies to improve patient outcomes.

Lung cancer has an extremely high mortality rate among malignant tumors, posing a significant threat to human health Among all lung cancer cases, non-small cell lung cancer (NSCLC) accounts for a significant proportion and has become a hot topic in clinical research and treatment. The Kirsten rat sarcoma viral oncogene homolog (KRAS) is one of the most common oncogenic drivers in NSCLC, closely associated with tumor initiation, treatment response, and prognosis. However, due to the relatively smooth surface of the KRAS protein and the lack of drug-binding pockets, it has long been regarded as an "undrugable target". With further research, recently, targeted drugs targeting the KRAS^G12C gene mutation have achieved significant breakthroughs in clinical trials, especially the application of KRAS^G12C-specific inhibitors adagrasib and sotorasib, which has changed the treatment landscape for NSCLC patients. To address challenges such as tumor heterogeneity, the complexity of the tumor microenvironment, interpatient variability, and acquired drug resistance mechanisms, combination therapy strategies involving KRAS^G12C inhibitors have emerged sequentially. This article systematically reviews the progress of targeted therapy for KRAS^G12C-mutant NSCLC and the results of related clinical trials, while exploring novel therapeutic strategies for patients with KRAS^G12C mutations, aiming to provide a reference for the selection of clinical treatment regimens.

Background: The prognosis of ABA-HAP patients is very poor. This study aimed to develop a scoring model to predict ABA-HAP in patients with GNB-HAP. Methods: A single center retrospective cohort study was performed among patients with HAP caused by GNB in our hospital during January 2019 to June 2019 (the derivation cohort, DC). The variables were assessed on the day when qualified respiratory specimens were obtained. A prediction score was formulated by using independent risk factors obtained from logistic regression analysis. It was prospectively validated with a subsequent cohort of GNB-HAP patients admitted to our hospital during July 2019 to Dec 2019 (the validation cohort, VC). Results: The final logistic regression model of DC included the following variables: transferred from other hospitals (3 points); blood purification (3 points); risk for aspiration (4 points); immunocompromised (3 points); pulmonary interstitial fibrosis (3 points); pleural effusion (1 points); heart failure (3 points); encephalitis (5 points); increased monocyte count (2 points); and increased neutrophils count (2 points). The AUROC of the scoring model was 0.845 (95% CI, 0.796 ∼ 0.895) in DC and 0.807 (95% CI, 0.759 ∼ 0.856) in VC. The scoring model clearly differentiated the low-risk patients (the score < 8 points), moderate-risk patients (8 ≤ the score < 12 points) and high-risk patients (the score ≥ 12 points), both in DC (P < 0.001) and in VC (P < 0.001). Conclusion: This simple scoring model could predict ABA-HAP with high predictive value and help clinicians to choose appropriate empirical antibiotic therapy.

Objective: To propose a refined CT-based phenotypic classification of pulmonary bullae and investigate the differences in demographic characteristics, morphological features, and pulmonary function among different subtypes. Methods: This retrospective study enrolled 467 patients diagnosed with pulmonary bullae who underwent chest CT at Tangdu Hospital from January 2023 to December 2024. Patients were classified into three phenotypes: bullous emphysema, intrapulmonary bullae, and subpleural bullae. Demographic data, smoking history, BMI, bulla morphology (size, number, internal septations, wall thickness, margin regularity), and pulmonary function parameters (FVC, FEV ₁ , FEV ₁ /FVC, DLCO) were collected and compared among groups. Subgroup analyses were performed based on smoking status, BMI level, and COPD status. Results: Significant intergroup differences were observed in age, BMI, and smoking history ( P < 0.05). Patients with bullous emphysema were older, had lower BMI, and higher smoking rates. Morphologically, the bullous emphysema group exhibited significantly greater maximum bulla length, width, and surface area compared to the other two groups ( P < 0.05). Smoking was associated with larger bullae, higher proportions of internal septations and thick walls, and fewer regular margins ( P < 0.05). Low BMI patients (BMI < 23.03 kg/m ² ) demonstrated larger bullae with more complex morphology compared to high BMI patients ( P < 0.05). Functionally, the bullous emphysema group had significantly lower FEV ₁ , FEV ₁ % predicted, FEV ₁ /FVC, and DLCO% predicted ( P < 0.05). Patients with COPD ( n = 83) showed larger bullae and lower proportions of regular margins and internal septations compared to non-COPD patients ( P < 0.05). Conclusion: CT-based phenotyping of pulmonary bullae reveals distinct demographic, morphological, and functional profiles. Bullous emphysema is associated with more severe morphological abnormalities and pulmonary function impairment. Smoking and low BMI are modifiable factors promoting bulla progression. This classification provides a foundation for personalized clinical surveillance and intervention strategies.