Background Accurate malignancy-risk estimation is central to pulmonary nodule management. Existing approaches do not always jointly capture intranodular heterogeneity, global structural irregularity, and perinodular context from a single routine CT examination. We developed a multirepresentation TResNet-3D framework for malignancy-risk assessment and model-derived risk grouping at initial evaluation. Methods This retrospective single-center study included 18,914 pulmonary nodules from 3,172 patients. Multiscale three-dimensional patches centered on each nodule were used to characterize internal texture, overall morphology, and perinodular context. A Taylor-enhanced 3D residual network extracted deep features, which were fused with radiomics and low-dimensional morphological complexity features to generate malignancy probability and a continuous score. Malignancy was defined by pathology-confirmed primary lung cancer, and benignity by benign pathology or at least 24 months of imaging stability. Data were split at the patient level into training, validation, and independent test sets. Performance was evaluated primarily by area under the receiver operating characteristic curve (AUC), with accuracy, sensitivity, specificity, calibration, decision-curve analysis, ablation experiments, and gradient-based visualization as secondary assessments. Results In the independent test set, the model achieved an AUC of 0.9103, an accuracy of 0.8521, a specificity of 0.9318, and a sensitivity of 0.7059, outperforming the radiomics model and the single 3D CNN comparators. Model-derived low-, intermediate-, and high-risk groups showed stepwise increases in observed malignancy rates. Decision-curve, calibration, and gradient-based visualization analyses supported the clinical plausibility of the model output. Conclusion The TResNet-3D provided quantitative malignancy-risk estimation and model-derived score grouping from routine chest CT at initial evaluation. These findings support further investigation as an adjunctive decision-support tool, although multicenter external validation remains necessary.

ABSTRACTBackground: Administration of epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) has expanded from advanced disease to early-stage lung cancer. The widespread adoption of chest computed tomography (CT) has led to increasing detection of multifocal nodular lung cancers. The optimal management strategy for residual ground-glass opacities (GGOs) coexisting with surgically confirmed lung cancer remains undetermined. This study investigated the impact of postoperative EGFR-TKIs on residual GGOs in patients with resected lung adenocarcinoma.Materials and Methods: This single-center retrospective study enrolled patients who underwent initial surgery for non-small cell lung cancer (NSCLC) and had synchronous GGOs between 2021 and 2024. Patients who received postoperative targeted therapy were grouped as the treatment group, whereas those without any antitumor treatment constituted the control group. The primary end point was reduction in size of residual GGOs during EGFR-TKIs treatment or follow-up after the initial surgery. The secondary endpoint was objective response rate (ORR) in residual GGOs pathologically confirmed as lung adenocarcinoma.Results: 314 NSCLC patients with 582 residual lesions were enrolled in the study. Of these, 138 patients with 275 residual GGOs were treated with EGFR-TKIs and 176 patients with 307 residual GGOs were followed up. Among 275 lesions treated with EGFR-TKIs, 113 (41.1%) lesions exhibited regression, 159 (57.8%) lesions had no change in size, and 3 (1.1%) lesions increased in size. In the no EGFR-TKIs group, 12 (3.9%) lesions exhibited growth, 292 (95.1%) lesions showed no change in size, and 3 (1.0%) lesions decreased in size. In the multiple primary lung cancer (MPLC) subgroup, ORR was 43.3% (95%CI, 25.5-62.6).Conclusions: EGFR-TKIs reported promising efficacy for residual GGOs in patients with EGFR-mutated NSCLC. These results suggest that EGFR-TKIs could be an effective treatment option for GGOs in patients with multiple lesions when surgery cannot resect all.

Background:The incidence of pulmonary nodules is rising. In the United States alone, approximately 1.57 million cases are detected annually via low-dose CT screening. This growing number has created an urgent need for accurately differentiating malignant lesions. The current standard methods rely on radiologist interpretation. However, these methods show variable accuracy, with a sensitivity range of 62%-79%. Invasive biopsies, which are often used for further diagnosis, carry complication risks ranging from 15% to 28%. Emerging technologies, such as artificial intelligence (AI) imaging analysis and liquid biopsy platforms, show promising capabilities in pulmonary nodule characterization. Nevertheless, there is a lack of a rigorous methodology for their comparative evaluation. Methods:We systematically evaluated 20 comparative studies that were published between 2015 and 2024. These studies assessed AI-based imaging methods, which included deep learning architectures and radiomics analysis, as well as liquid biopsy methods, such as ctDNA mutation profiling and methylation-based assays, for the characterization of pulmonary nodules. Bayesian hierarchical modeling was employed to account for the interdependencies among different tests. Evidence certainty was assessed via the GRADE framework. Results:The CT-Deep approach, when integrated with clinical information, demonstrated the highest sensitivity, with a value of 97.1% and a 90.8%-99.6% credible interval. However, it showed relatively lower specificity, with a value of 67.4% and a 74.4%-92.9% credible interval. Stand-alone liquid biopsy exhibited more balanced operating characteristics, with a sensitivity of 63.1% and a specificity of 82.8%. The hybrid clinical-liquid biopsy strategy showed optimal performance in the summary receiver operating characteristic analysis, with an area under the curve of 0.903. Substantial heterogeneity was observed across studies, with an I2 > 50%. Additionally, there were wide confidence intervals for some diagnostic odds ratio estimates, which means that the comparative performance should be interpreted with caution. Conclusions:AI-enhanced imaging techniques are particularly valuable for high-sensitivity screening applications, where the risk of false negatives is the greatest. On the other hand, liquid biopsy approaches or their combination with clinical assessment may be more suitable for situations that require high specificity. The findings highlight the need for standardized validation protocols and prospective evaluation of combined modality strategies to address the current limitations in pulmonary nodule characterization.

Background: Multiple primary lung cancers (MPLCs) present unique clinical difficulties because of their genetically diverse independent tumors, requiring genetic testing to distinguish synchronous primaries from intrapulmonary metastases. While circulating tumor DNA (ctDNA) analysis shows potential for detecting molecular residual disease (MRD), tumor heterogeneity hinders its application. Thus, there is an urgent need to develop specific biomarkers and standardize liquid biopsy protocols to improve monitoring and treatment. The aim of this study was to analyze the clinicopathological characteristics of postoperative MRD-positive stage I non-small cell lung cancer (NSCLC) patients, with a focus on the potential utility of ctDNA in detecting MRD and guiding therapeutic decisions. Methods: Twelve patients with pulmonary nodules were analyzed. Paired tissue and plasma samples underwent genomic profiling via next-generation sequencing (NGS) using validated extraction/library preparation kits, following ethical standards. Rigorous quality controls were implemented to ensure sensitive variant detection. Results: Both solitary (n=5) and multiple nodules (n=7) carried EGFR and TP53 mutations. Multiple nodules had significantly higher tumor mutational burden and clonal heterogeneity. Patients with positive MRD showed markedly elevated ctDNA levels, with clonal dynamics indicating increased shedding in multifocal disease. Conclusions: Multifocal lung disease exhibits greater genomic complexity and enhanced ctDNA shedding, supporting its use as a disease-tracking tool. The findings identify actionable signatures for MRD surveillance and guide personalized therapeutic interventions based on observed clonal architectures.

Chronic and complex wounds require materials capable of simultaneously regulating inflammation and promoting vascularized tissue regeneration. Here, we engineer a bioorthogonal vesicle-hydrogel that covalently integrates Lactobacillus casei-derived membrane vesicles (LCMVs) within a carboxymethyl chitosan/aldehydehyaluronic acid network to achieve sustained vesicle presentation and enhanced bioactivity. The resulting Gel-LCMVs composite exhibits an ECM-mimetic porous architecture, stable viscoelasticity, and controlled vesicle release, enabling marked stimulation of cell proliferation, migration, and endothelial tube formation while suppressing macrophage-derived pro-inflammatory signals. In a full-thickness excisional wound model, GelLCMVs achieved >50% closure by day 3 and nearly complete healing by day 10, with improved granulation tissue formation, thicker neo-dermis and enhanced collagen deposition, outperforming a commercial dressing (Tegaderm). Transcriptomic profiling reveals activation of PI3K-AKT, Wnt, and JAK-STAT pathways and suppression of inflammatory gene programs. This bioactive and cell-fre hydrogel platform demonstrates how precise materials-microbio-derived vesicle integration can synergetically steer wound microenvironment remodeling and enable scar-minimized wound repair.

The cellular mechanisms governing the change from pulmonary nodules to early-stage lung adenocarcinoma (LUAD) at single-cell resolution are not yet fully elucidated. In the present study, we employed single-nucleus RNA sequencing (snRNA-seq) on 44 pulmonary nodule and paired normal specimens to investigate this process. Within the epithelial compartment, alveolar type 2 (AT2) cells were categorized into high- and low-malignancy subclusters. Our differential expression analysis identified a significant upregulation of the transcription factor SMAD family member 3 (SMAD3) in the high-malignancy group, which was shown to enhance LUAD proliferation and migration. Mechanistically, intercellular adhesion molecule 1 (ICAM1) was established as a downstream target of SMAD3, playing a pivotal role in mediating intercellular crosstalk between malignant AT2 cells and lymphocytes. Specifically, the interaction between ICAM1 and immunosuppressive CD4+ T cells and immune-eliminating CD8+ T cells was found to dampen T cell-mediated antitumor response. In conclusion, these results reveal that the SMAD3-ICAM1 axis drives the malignant change from pulmonary nodules to early-stage LUAD, underscoring the potential of these molecules as biomarkers to inform diagnosis and surgical decision-making.

Background: Thymoma is an uncommon cancer of the thymus and postoperative radiotherapy (PORT) is often considered for selected patients with high-risk or locally advanced thymoma after resection. The effect of PORT on overall survival (OS) and cardiac-specific mortality in patients with thymoma is not well understood. The purpose of this study was to assess the impact of PORT on OS and cardiac-specific mortality in resected thymoma patients. Methods: We analyzed the data from Surveillance, Epidemiology, and End Results (SEER) database to identify patients with thymoma who had a cancer-directed operation alone or with PORT. A propensity score matching (PSM) was employed to adjust for imbalances in two groups. OS was analysed with Kaplan-Meier. Comparison of cumulative incidence curves for cardiac-specific mortality between the groups was performed using Fine and Gray's model. Results: There was a total of 3,434 patients with thymoma. After 1:1 matching, 1,078 patients remained in each group and PORT was independently correlated with better survival (P=0.004). The 5-year OS was 88.2% for the PORT group and 84.1% for the non-PORT group. With respect to cardiac-specific mortality, the cumulative incidence at 15 years for PORT vs. non-PORT patients following matching was PORT, 8.3% and non-PORT, 6.1%, with no difference in Gray's test (P=0.44). In a multivariable competing-risk model, PORT was not significantly associated with cardiac-specific mortality in a multivariable competing-risk analysis [hazard ratio (HR) =1.25, 95% confidence interval (CI): 0.84-1.86; P=0.28]. Conclusions: PORT was associated with improved long-term survival. No statistically significant increase in cardiac-specific mortality was observed; however, a moderate increase in risk cannot be excluded given the limited number of cardiac events. These findings suggest that PORT remains an appropriate part of thymoma management.

The coexistence of bronchial anatomical variations with bronchiectasis presents significant challenges for surgical intervention. Among these, an anomalous left apicoposterior segmental bronchus (B¹⁺²)—originating ectopically from the left main bronchus—is a highly uncommon variant that predisposes individuals to impaired mucociliary clearance and subsequent bronchiectasis. This case demonstrates the technical feasibility and considerations of performing a video- assisted thoracoscopic surgery (VATS) left apicoposterior segmentectomy in the presence of an displaced B1 + 2 bronchus, a rare anatomic variant that adds complexity to surgical planning. A 41-year-old male was admitted with a history of recurrent cough and purulent sputum. High-resolution computed tomography (HRCT) of the chest revealed localized cystic bronchiectasis with marked bronchial wall thickening in the left upper lobe apicoposterior segment. Preoperative three-dimensional computed tomography (3D-CT) reconstruction further identified an anatomical variation: the B¹⁺² bronchus originated directly from the left main bronchus, deviating from the conventional segmental branching pattern. Additionally, fusion was observed between the dorsal segment of the left lower lobe and the apicoposterior segment, further complicating the anatomical landscape. During video-assisted thoracoscopic surgery (VATS), the ectopic B¹⁺² bronchus and its accompanying arterial branch (A¹⁺²) were carefully dissected and transected via a posterior mediastinal pleural approach. The inflation-deflation technique was subsequently applied to delineate the intersegmental plane—a crucial step that enabled precise anatomical division under full thoracoscopic guidance. The total operative time was 115 min, with an estimated blood loss of 50 mL. The patient’s postoperative recovery was uneventful, and he was discharged on postoperative day 3. Histopathological examination confirmed the diagnosis of focal bronchiectasis with chronic inflammatory changes. No recurrence was observed at the six-month follow-up. In patients with bronchiectasis and a displaced B1+ 2 bronchus, preoperative 3D-CT reconstruction enables accurate delineation of complex anatomy and facilitates surgical planning (e.g., favoring a posterior mediastinal approach). The inflation-deflation technique effectively identifies the intersegmental plane. Together, these strategies are essential for achieving safe and precise thoracoscopic apicoposterior segmentectomy. This case offers a valuable reference for performing anatomical segmentectomy in patients with bronchial ectopia and benign lung disease.

Background : Lung adenocarcinoma (LUAD), accounting for 50% of non-small cell lung cancer cases, exhibits dismal survival rates due to therapy resistance and metabolic adaptation. While NIMA related kinase 2 (NEK2), a mitotic kinase, is implicated in tumor progression, its mechanistic role in LUAD-associated glycolysis remains elusive. Materials and Methods: Patient data were obtained from The Cancer Genome Atlas (TCGA). Tissue microarrays assessed NEK2 expression. Gene Set Enrichment Analysis (GSEA) and Gene Ontology (GO) were used to explore NEK2 functions. Protein levels of NEK2, heat shock transcription factor 1 (HSF1), and lactate dehydrogenase A (LDHA) were detected by Western blotting, and NEK2 mRNA by qPCR. Cell proliferation, invasion, migration and apoptosis were evaluated by CCK8, colony formation, Transwell, wound healing, and flow cytometry. Metabolic activity was assessed by glucose uptake, lactate secretion, ATP production, and Seahorse XF analysis of extracellular acidification rate (ECAR) and oxygen consumption rate (OCR). A murine xenograft tumor model was established to systematically evaluate the in vivo functional role of NEK2. Results : NEK2 overexpression in 68% of patients, correlating with advanced TNM stages and poor survival. NEK2 upregulation in tumors linked to lymphatic metastasis and Ki67 positivity. NEK2 knockdown in LUAD cells suppressed proliferation, migration, and invasion, while promoting apoptosis. NEK2 depletion attenuated aerobic glycolysis, characterized by reduced glucose uptake, lactate production, and ECAR, with 2-deoxy-D-glucose (2-DG) treatment reversing NEK2-driven malignancy. Mechanistically, NEK2 stabilized HSF1 to transcriptionally upregulate LDHA and hexokinase 2 (HK2), confirmed by ChIP-qPCR. In vivo , NEK2-silenced xenografts displayed reduced tumor growth and diminished Ki67/LDHA co-expression. Conclusion : This study elucidates a NEK2-HSF1 axis as a master regulator of glycolytic reprogramming in LUAD, providing a rationale for dual targeting strategies against NEK2 and aerobic glycolysis to combat therapy resistance.

Background:Lung adenocarcinoma (LUAD) patients have a poor overall survival rate. Sialylation is closely related to lung cancer progression, and long non-coding RNAs (lncRNAs) are crucial in tumorigenesis. However, how sialylation and lncRNAs affect LUAD is unclear. Methods:This study utilized the TCGA-LUAD dataset, GSE31210, GSE131907, and a set of 109 sialylation-related genes (SRGs). Differential expression analysis was performed on TCGA-LUAD tumor and control samples to identify differentially expressed lncRNAs (DE-lncRNAs). Spearman correlation analysis with SRGs was then conducted to screen for sialylation-related lncRNAs (SRDLs). Risk-signature models were constructed using univariate and multivariate Cox regression analyses, followed by a proportional hazards (PH) test. Independent prognostic factors were identified, and a nomogram was developed to predict 1-, 3-, and 5-year survival. Gene expression in key cell populations was examined using GSE131907, and GSEA, tumor immune microenvironment assessment, and drug sensitivity analyses were performed. Finally, prognostic genes were validated using RT-qPCR. Results:A total of 139 SRDLs were identified. A four-gene risk model (LINC00115, LINC00173, LINC00968, LINC01352) was constructed. Both the risk score and T stage were independent prognostic factors. Single-cell analysis of GSE131907 identified eight cell types, with myeloid cells emerging as key contributors. The high-risk group was associated with cell-cycle-related pathways, whereas the low-risk group was enriched in neuroactive ligand-receptor interaction pathways. Immune infiltration analysis revealed multiple significant correlations, and tumor mutation burden scores differed between the two groups. RT-qPCR validated the observed gene expression patterns. Discussion:The four-lncRNA sialylation signature predicted LUAD outcomes and pointed to myeloid cells as therapeutic targets. Prospective validation and mechanistic studies are, however, needed. Conclusion:Four sialylation-associated lncRNAs were identified in LUAD, enabling the construction of an effective risk model. Myeloid cells were highlighted as key contributors, offering valuable insights for personalized treatment and prognostic intervention.

Background:Lung adenocarcinoma (LUAD) remains a leading cause of cancer mortality, with poor prognosis driven by metastasis and therapeutic resistance. Chromosome 1 open reading frame 112 (C1ORF112) encodes a nuclear protein involved in DNA replication and repair, but its role in LUAD is unclear. To systematically investigate the clinical relevance, functional impact, and transcriptional regulation of C1ORF112 in LUAD through integrative bioinformatic and experimental approaches. Methods:C1ORF112 expression and prognostic significance were analyzed using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Single-cell RNA sequencing defined cellular localization and communication patterns. Functional enrichment, protein-protein interaction (PPI), and transcription factor prediction analyses were performed. In vitro assays and xenograft models assessed biological functions and transcriptional regulation by E2F8. Results:C1ORF112 was significantly upregulated in LUAD and correlated with poor overall survival (OS). Single-cell analysis showed elevated expression in malignant cells, fibroblasts, endothelial cells, and mast cells, accompanied by increased communication with M2 macrophages and exhausted CD8+ T cells. Overexpression of C1ORF112 inhibited apoptosis and promoted proliferation in LUAD cells, while xenografts exhibited accelerated tumor growth and increased Ki67 expression. Mechanistically, E2F8 directly bound the C1ORF112 promoter, enhancing its transcription and inhibiting downstream p53 signaling. Conclusions:Our integrative analysis suggests that C1ORF112 exhibits oncogenic properties in LUAD by promoting tumor survival, proliferation, and potentially remodeling the tumor microenvironment. The transcriptional activation by E2F8 highlights the E2F8-C1ORF112 axis as a candidate prognostic biomarker and therapeutic vulnerability, though prospective clinical validation and drug sensitivity studies are warranted.

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Glutamine plays a critical role in the progression of LUAD. However, the function of pyrroline-5-carboxylate reductase 1 (PYCR1) and its regulatory role in glutamine metabolism remain unclear. Transcriptomic and clinical data for LUAD were obtained from The Cancer Genome Atlas (TCGA) and validated using Gene Expression Omnibus (GEO) datasets (GSE19188, GSE13213). Glutamine metabolism-related genes were analyzed for differential expression and prognostic significance. Functional enrichment was performed via gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) analyses. Single-cell RNA-seq data (GSE117570) were processed using Seurat, and cell-cell communication was inferred with CellChat. In vitro, lentiviral overexpression, Western blotting, EdU, CCK-8, and glutamine uptake assays were conducted. An orthotopic xenograft model was established in nude mice to assess tumor growth in vivo. Six glutamine-metabolism-related genes were found significantly overexpressed in LUAD tissues and associated with poor overall survival. Single-cell sequencing revealed predominant PYCR1 expression in malignant cells. Functional assays demonstrated that PYCR1 overexpression enhanced glutamine uptake, proliferation, and inhibited apoptosis in LUAD cells, effects mediated via suppression of the P53 pathway. PYCR1 promoted tumor growth in a xenograft model and was found to transcriptionally upregulate 5-oxoprolinase (OPLAH), which augmented its oncogenic effects. Our findings identify the PYCR1/OPLAH axis as a key driver of LUAD progression via p53 signaling, revealing a promising therapeutic target.

BACKGROUND:Neoadjuvant chemoimmunotherapy demonstrates favorable survival outcomes and high pathological complete response (pCR) rates, but its efficacy in resectable N1/N2 nonsmall cell lung cancer (NSCLC) remains unproven. Additionally, predictive biomarkers for treatment efficacy and the relationship between lymph node status postneoadjuvant therapy and survival are unclear. This prospective study evaluates the efficacy and safety of combining penpulimab with chemotherapy for resectable N1/N2 NSCLC. MATERIALS AND METHODS:This prospective cohort study enrolled patients aged ≥18 years with resectable N1/N2 NSCLC. Patients received penpulimab, carboplatin, and paclitaxel (for squamous cell carcinoma) or pemetrexed (for adenocarcinoma) every 21 days for three cycles, followed by surgery within 6 weeks. Primary endpoint: major pathological response (MPR). Secondary endpoints: pCR, objective response rate (ORR), R0 resection rate, disease-free survival (DFS), overall survival (OS), and treatment- and surgery-related adverse events. The study was Ethics Committee-approved. RESULTS:From August 2022 to August 2023, 32 patients were enrolled. The preoperative ORR was 75.0%. R0 resection was achieved in 96.9%. MPR and pCR were achieved in 51.6% and 22.6% of patients, respectively. Significant associations between pCR and Response Evaluation Criteria in Solid Tumors response categories ( P < 0.001), downstaging of nodal status ( P = 0.007), and tumor mutational burden (TMB) ( P = 0.037) were observed in our analysis. Multivariate regression analysis showed that no clinical factor other than TMB was predictive of the pCR. One-year DFS was 84.4%, and OS was 96.9%, with a median follow-up of 18 months. DFS was 100% in the MPR group versus 66.7% in the non-MPR group ( P < 0.001) and higher in the pCR group ( P = 0.0074). Nodal downstaging was observed in 50.0%, with superior survival in this group. Adverse events occurred in 93.8%, primarily fatigue, nausea, vomiting, and rashes. CONCLUSION:This is the first report of neoadjuvant penpulimab in N1/N2 NSCLC, demonstrating efficacy, feasibility, and survival benefits, especially in patients with high tumor mutational burden.

Background:The KRAS gene is a member of the Ras protein family. KRAS mutations are prevalent oncogenic drivers in non-small cell lung cancer (NSCLC), even in the Chinese populations, where they account for 10-15% of cases, and are correlated with aggressive disease and poor clinical outcomes. Despite recent breakthroughs in direct KRAS G12C inhibitors (e.g., sotorasib and adagrasib), the therapeutic efficacy of these inhibitors remains limited; the median progression-free survival of KRAS-mutated NSCLC patients rarely exceeds 6 months, and actionable therapies for non-G12C variants are lacking. Based on this foundation, the study aimed to identify novel potential targeted therapeutic strategies for patients with KRAS-mutant NSCLC through systematic target screening. Methods:The following three-step process and selection criteria were employed to identify the KRAS function-related genes: (I) the genes were differentially expressed in the NSCLC tissues compared to the normal tissues; (II) the differentially expressed genes were highly expressed in the KRAS-mutated tissues compared to the KRAS-wild-type NSCLC tissues in The Cancer Genome Atlas (TCGA) cohort; and (III) the genes had a dependency score of >0.9 in the KRAS-mutated NSCLC cell lines from the Cancer Cell Line Encyclopedia based on the dataset. We then examined the prognostic value of the KRAS function-related genes in TCGA cohort (504 lung adenocarcinoma samples) and validated their prognostic value in the GSE72094 dataset (398 lung adenocarcinoma samples). Additionally, we conducted a gene set enrichment analysis (GSEA) to investigate the potential mechanisms by which the candidate genes affected prognosis, and performed a drug sensitivity analysis to identify compounds exhibiting sensitivity to candidate gene expression levels in the KRAS-mutated NSCLC cell lines. Results:We identified four KRAS function-related genes and showed that ATR expression was significantly associated with overall survival (P=0.008). After adjusting for age, gender and TNM stage (Tumor-Node-Metastasis stage), high ATR expression remained an independent predictor of a worse prognosis in KRAS-mutated NSCLC [hazard ratio (HR) =2.192; P=0.01] in the TCGA cohort, and this prognostic significance was validated in the GSE72094 dataset (HR =2.06; P=0.02). The GSEA results showed that the enriched genes in the ATR high-expression group were significantly associated with ubiquitin mediated proteolysis, pathways in cancer, and the mitogen-activated protein kinase signaling pathway compared to the ATR low-expression group. Additionally, the drug sensitivity analysis identified two compounds (i.e., AZ20 and AZD6738) that were sensitive to ATR expression. Conclusions:ATR holds promise as both a prognostic marker and therapeutic target for KRAS-mutated NSCLC. Our findings may assist in the prediction of prognosis and the development of novel targeted therapies for this disease.

Most persistent ground glass nodules (GGNs) are eventually diagnosed as early-stage lung adenocarcinoma (LUAD). Delving into the molecular underpinnings of malignant transformation of GGNs will aid in the development of preventive and therapeutic strategies to interrupt the occurrence and progression of early-stage LUAD. Macrophages (Macs) are critical in the formation of immunosuppressive tumor microenvironment (TME). However, its role in triggering the advancement of early-stage LUAD with mixed ground glass nodule (mGGN) is yet to be clarified. Utilizing scRNA-seq analysis on normal lung tissues, ground glass regions, and solid regions of mGGNs, complemented by multicolor immunohistochemistry (mIHC) and flow cytometry, we found an increase and peri-tumoral aggregation of immunosuppressive SPP1+ alveolar Macs and monocyte-derived Macs (Mo-Macs), with a particular emphasis on the Mo-Macs. This accumulation at the tumor margin could obstruct the penetration of immune cells into the tumor’s core, thereby promoting the malignant transformation of GGNs. SPP1+ Macs not only display a senescent phenotype but also harbor the potential capacity to foster tumor metastasis and angiogenesis. Clinical data from LUAD tissue array and TCGA-LUAD database revealed a positive association between the tumoral SPP1+ Macs percentage and poor prognosis. Furthermore, SPP1+ Macs could reshape the TME into an immunosuppressive state through interactions with other immune cells. In vitro and in vivo assays revealed SPP1 knockout inhibited the immunosuppressive polarization and senescence of Macs, reversed the immunosuppressive status of TME and reduced the growth of LUAD xenograft tumors. Our findings propose an emerging therapeutic strategy aimed at suppressing SPP1+ Macs, which could potentially decelerate or halt the malignant conversion of GGNs to early-stage LUAD.

Cancer-associated fibroblasts (CAFs) play a crucial role in promoting the invasion and metastasis of lung adenocarcinoma (LUAD). The mechanism by which CAFs promote this process remains unclear. We employed glycoproteomics to investigate the dynamic changes in glycosylation between normal and early-stage LUAD tissues, and explore the roles of related glycoproteins and site-specific polysaccharides through in vitro and in vivo experiments. Using mass spectrometry-based glycoproteomics, we identified 242 N-glycosylated proteins with significantly increased expression and 17 with decreased expression in LUAD tissues. Sialylated modifications constitute the largest proportion of N-glycosylation and promote extracellular matrix (ECM) release by CAFs, enhancing their pro-cancer potential. Stage I LUAD patients with high levels of sialylation modifications have poor overall survival (OS) rates. Further findings revealed that ST3GAL4-mediated sialylation in CAFs is a key driver of ECM secretion, and that early-stage LUAD patients with high infiltration of ST3GAL4-positive CAFs have poor OS. Quantitative analysis of intact glycopeptides showed that core sialylation of SUSD2-Asn(N)162 was significantly upregulated and correlated with the ability of CAFs to secrete ECM. Sialylated SUSD2 binds to AKT and Smad2, enhancing their phosphorylation and ECM secretion, thereby increasing the pro-tumorigenic effects of CAFs. These findings offer new directions for developing glycosylation-centric therapies and biomarkers to treat early-stage LUAD, to improve patient outcomes by targeting CAF-driven drug resistance mechanisms.

The treatment of lung cancer with azacitidine (AZA) is urgently in need of a novel delivery material due to its limitations, including a short half-life, high cytotoxicity, and poor tumor targeting. To overcome these limitations, the coordination of Gallic acid-catechin-gallate with Fe3+ and its encapsulation on the surface of mPDA loaded with AZA (mA@EF) was prepared. mA@EF exhibited a uniform distribution of regular spherical particles with good stability and drug release properties. In cell experiments, mA@EF effectively inhibited cell viability, promoted cellular uptake, and downregulated the expression of DNA methyltransferases. Moreover, mA@EF demonstrated good biosafety. In animal experiments, mA@EF showed strong tumor-targeting and retention activity, and significantly inhibited the growth of tumor. This discovery provided a feasible dosing regimen for AZA treatment in lung cancer patients.

Background:Globally, lung cancer is the most frequently diagnosed malignancy, for which solid pulmonary nodules (SPNs) are a common radiographic finding. Given the high false-positive rates of computed tomography (CT) screening, we aimed to develop a multimodal diagnostic model combining CT radiomics features and serum biomarkers via machine learning. Methods:This retrospective study included patients receiving both preoperative CT screening and serum biomarker testing. All pulmonary nodules (PNs) were divided into training and validation sets randomly at a ratio of 7:3. We developed a multimodal diagnosis model based on the CT radiomics and protein biomarkers of SPNs in the training cohort. The CT radiomics features were derived from the integration of traditional radiomics analysis methods and three-dimensional (3D) deep learning techniques. The accuracy of this multimodal diagnosis model for the prediction of SPNs was verified in the validation set. Model performances were evaluated in terms of the area under the curve (AUC), accuracy, positive predictive value (PPV), negative predictive value (NPV), decision curve analysis (DCA), and calibration curve. Results:Between February 2016 and December 2020, imaging data of 638 eligible PNs from CT scans of 633 different patients were collected. The multimodal model had satisfactory accuracy in differentiating benign and malignant SPNs in the training set [AUC =0.944; 95% confidence interval (CI): 0.924-0.964]. In the validation set, the multimodal model yielded an AUC of 0.926 (95% CI: 0.889-0.964), an accuracy of 0.885, an NPV of 0.812, and a PPV of 0.927. The multimodal model also significantly outperformed the single-modality diagnostic models, including the traditional radiomics CT model (AUC =0.843; 95% CI: 0.780-0.906), the serum biomarker model (AUC =0.783; 95% CI: 0.718-0.847), and the 3D deep learning model (AUC =0.820; 95% CI: 0.754-0.885) (all P values <0.01). Conclusions:This study developed a novel multimodal that demonstrated superior performance in classifying SPNs. It may thus enhance the diagnosis of benign and malignant lesions and provide support for clinical decision-making.

Lung adenocarcinoma (LUAD) remains a leading cause of cancer-related mortality worldwide, with limited response rates and resistance to targeted therapies and immunotherapies. Pin1, a phosphorylation-specific peptidyl-prolyl isomerase, has been implicated in multiple oncogenic pathways; however, its role in LUAD is not fully understood. We conducted an integrative analysis using public datasets (TCGA, GEO, HPA), LUAD tissue microarrays, malignant pulmonary nodule specimens, and cell line models to investigate the expression and function of PIN1 in LUAD. Functional assays, immunohistochemistry, and in vivo xenograft models were employed to validate the biological effects of PIN1 in LUAD progression and treatment response. PIN1 expression was significantly downregulated in LUAD tissues compared to adjacent normal lung tissues. High PIN1 expression was associated with improved overall survival, increased immune cell infiltration, and enhanced response to immunotherapy. Overexpression of PIN1 inhibited proliferation and migration while promoting apoptosis of LUAD cells in vitro and in vivo. Mechanistically, high PIN1 expression activated downstream pAKT and pMAPK signaling, potentially contributing to EGFR-TKI resistance despite unchanged pEGFR levels. Moreover, functional enrichment analysis and immune profiling revealed that PIN1 is positively associated with antitumor immune responses in LUAD, contrasting its immunosuppressive role in other cancers. PIN1 exhibits tumor-suppressive activity in LUAD and may serve as a promising biomarker for prognosis and therapeutic response. These findings underscore the context-dependent role of PIN1 and support further exploration of its mechanistic involvement in LUAD immunobiology and targeted therapy resistance.

Background:While sympathectomy remains the optimal surgical intervention for severe primary palmar hyperhidrosis (PPH), compensatory hyperhidrosis (CH) has emerged as the most significant factor contributing to postoperative patient regret. This retrospective study aimed to identify risk factors and develop a predictive model for moderate-to-severe compensatory hyperhidrosis (msCH) in patients with PPH. Methods:A total of 1,013 patients were retrieved from the institutional database between 2014 and 2024. Logistic regression modeling was utilized to identify risk factors for msCH. A nomogram for predicting msCH was developed accordingly. Results:Of the initial cohort, there were 903 patients included in the final analysis, among whom 182 (20.2%) developed msCH. The following factors were identified as independent risk factors for msCH: age >25 years [odds ratio (OR) 3.32, 95% confidence interval (CI): 2.23-4.95, P<0.01], smoking history (OR 6.46, 95% CI: 4.37-9.54, P<0.01), higher body mass index (BMI) (OR 1.68, 95% CI: 1.10-2.56, P=0.02), palmar-axillary hyperhidrosis (OR 2.37, 95% CI: 1.57-3.57, P<0.01), and T3 sympathectomy (OR 3.14, 95% CI: 2.03-4.85, P<0.01). A predictive nomogram for msCH was developed based on these factors. Receiver operating characteristic (ROC) curve analysis demonstrated an area under the curve (AUC) of 0.839, indicating good predictive performance. Conclusions:Age >25 years, smoking history, higher BMI, palmar-axillary hyperhidrosis, and T3 sympathectomy were independent risk factors for msCH. Based on these factors, a predictive model for msCH was developed and showed high predictive accuracy.