Background: Hilar lymph nodes with dense adhesion to the bronchus and pulmonary artery (“doornail” nodes) can be encountered unexpectedly during robot-assisted pulmonary resection. We report our experience managing these nodes and associated factors. Methods: This retrospective single-center cohort study included 1,185 patients undergoing robot-assisted pulmonary resection (March 2021–September 2024). Preoperative factors were analyzed using Firth penalized logistic regression in a clinically selected model (age, maximal voluntary ventilation [MVV], and tumor diameter). Operative time and blood loss were compared using robust regression models. Perioperative outcomes were compared descriptively between forced dissection and en bloc stapling. Results: Doornail hilar lymph nodes occurred in 48 of 1,185 patients (4.05%; 95% CI, 3.07–5.33%). Older age remained associated with this finding after adjusting for MVV and tumor diameter (adjusted OR per 10 years, 2.316; 95% CI, 1.533–3.596; P<0.001). Operative time was longer unadjusted (105 vs 92 min; P=0.027) but not after adjustment. Among these 48 patients, 45 (93.8%) received en bloc stapling with no blood loss exceeding 200 mL, transfusion, or prespecified in-hospital complication, whereas all 3 (6.3%) who underwent forced dissection had substantial bleeding (700–2,400 mL), and 2 required transfusion. No conversion to thoracotomy occurred in either group. Conclusions: Doornail hilar lymph nodes occurred in about 4% of patients; older age remained associated with this finding after adjusting for MVV and tumor diameter. Because strategy selection was non-random and groups differed in resection extent, comparative safety cannot be established; en bloc stapling after tissue thinning is feasible when a node cannot be safely separated.

Abstract Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease with limited therapeutic options. Ferroptosis, an iron-dependent cell death, has been implicated in various fibrotic diseases, but its role in IPF remains unclear. This study integrates spatial transcriptomics, single-cell RNA sequencing, and bulk RNA-seq to explore ferroptosis in IPF. A ferroptosis scoring model and machine learning algorithms identified SERINC2 as a key gene upregulated across all datasets, with high expression in basal cells. Further analysis revealed that SERINC2⁺ basal cells are involved in key signaling pathways, such as Wnt and NT, and exhibit active intercellular communication. Animal experiments confirmed that SERINC2 protein levels are elevated in the lung tissues of BLM-induced mice, supporting its role in disease progression. Our findings suggest that SERINC2 may serve as a potential diagnostic biomarker and therapeutic target, providing new insights into the pathogenesis and potential treatment of IPF.

Background/Objectives: Prolonged air leak (PAL) remains a common complication after lung resection and may delay postoperative recovery and subsequent treatment. This study aimed to identify clinical factors associated with PAL after robot-assisted thoracic surgery (RATS) and to explore potential nonlinear relationships using restricted cubic spline (RCS) modeling. Methods: A retrospective cohort of 1185 patients who underwent RATS for primary lung cancer was analyzed. Multivariable Firth logistic regression was used to identify independent predictors of PAL (≥5 days). A nomogram was constructed based on the final model and internally validated using 1000 bootstrap resamples; its clinical utility was assessed using decision curve analysis. RCS analysis was performed to evaluate potential nonlinear associations. Results: A total of 98 patients (8.3%) developed PAL. Male sex was independently associated with increased PAL risk (OR 3.29, p < 0.001), whereas higher FEV1 was associated with reduced risk (OR 0.50 per 1-L increase, p < 0.001). BMI showed a modest protective effect (OR 0.91, p = 0.01). Age was not significant in the linear model (p = 0.86), but RCS analysis demonstrated a significant nonlinear association, with increased risk at older ages. The nomogram demonstrated moderate discrimination (apparent C-statistic 0.670, optimism-corrected 0.644) and good calibration, with decision curve analysis confirming net clinical benefit over treat-all and treat-none strategies. Conclusions: Male sex and impaired pulmonary function are key predictors of PAL after RATS. Nonlinear modeling revealed complex age-related risk patterns not captured by conventional approaches. The proposed nomogram may assist in preoperative risk stratification and perioperative decision-making.

BackgroundLung adenocarcinoma (LUAD) exhibits marked heterogeneity. Organelle stress-adaptive programs that tumor cells develop under hypoxia, nutrient limitation, and proteostasis pressure may drive functional reprogramming of tumor biology, remodel the immune microenvironment, and ultimately influence the benefits of immunotherapy. Therefore, it is necessary to systematically characterize the coordinated changes across organelle stress-related pathways in LUAD, establish a subtyping and prognostic stratification framework, and identify key molecules as well as potential cell-cell communication axes.MethodsTranscriptomic profiles and clinical follow-up data from The Cancer Genome Atlas LUAD (TCGA-LUAD) cohort and public cohorts were collected. Pathway activities were quantified using organelle stress-related gene sets, and core stress programs associated with overall survival (OS) and progression-free survival (PFS) were screened by Cox regression and Kaplan-Meier analyses. Nonnegative matrix factorization (NMF) was used for unsupervised subtyping and stability evaluation. Functional enrichment, genomic features, and immune landscapes were compared between subtypes, and potential benefit from immune checkpoint blockade (ICB) was inferred using tumor immune dysfunction and exclusion (TIDE) and immunophenoscore (IPS). Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) were integrated to characterize malignant cell states, spatial niches, and cell-cell communication networks. In LUAD cell lines, the candidate gene was silenced by small interfering RNA (siRNA), and phenotypic assays were performed to validate its effects.ResultsThe organelle stress activity-based system robustly classified LUAD into two biologically distinct subtypes (the mitochondrial-ribosome biogenesis, MRB, subtype and the lysosomal catabolism, LC, subtype), which showed systematic differences in prognosis and functional programs. The MRB subtype exhibited enhanced stress and metabolic adaptation accompanied by immune exclusion features, whereas the LC subtype showed a relatively immune-active tumor microenvironment. Immunotherapy-related analyses suggested divergent trends in potential ICB benefit between the two subtypes. Multiscale evidence highlighted SLC16A14 (MCT14) as a key node linking stress heterogeneity to malignant progression. At the single-cell level, SLC16A14 was mainly expressed in malignant cells, and communication analyses suggested that CALCR-related signaling may mediate tumor-endothelial interactions and contribute to an immune-excluded microenvironment. In vitro, SLC16A14 silencing suppressed tumor cell proliferation, invasion, and migration, supporting its role as a key molecule connecting stress adaptation and tumor progression.ConclusionWe established an organelle stress program-based subtyping and prognostic framework for LUAD, revealed the coupling between stress adaptation and TME remodeling, and proposed SLC16A14 and its associated communication network as potential intervention targets, providing multiomics evidence for interpreting LUAD heterogeneity and for stratifying immunotherapy and combination strategies.

Hilar lymph nodes with dense adhesion to the bronchus and pulmonary artery (“doornail” nodes) can be encountered unexpectedly during robot-assisted pulmonary resection. We report our experience managing these nodes and associated factors. This retrospective single-center cohort study included 1,185 patients undergoing robot-assisted pulmonary resection (March 2021–September 2024). Preoperative factors were analyzed using Firth penalized logistic regression in a clinically selected model (age, maximal voluntary ventilation [MVV], and tumor diameter). Operative time and blood loss were compared using robust regression models. Perioperative outcomes were compared descriptively between attempted separate dissection and en bloc stapling. Doornail hilar lymph nodes occurred in 48 of 1,185 patients (4.05

Periareolar incisions improve cosmesis in video-assisted thoracoscopic surgery, but their use as an assistant port in robotic-assisted thoracoscopic surgery (RATS) has not been formally described. We characterized the learning curve of this approach and compared perioperative outcomes with conventional-portal RATS. We retrospectively analyzed 117 consecutive malignant RATS resections performed with a periareolar assistant port (December 2025–June 2026) and 285 conventional-portal cases (January 2024–September 2025) at a single center. Learning curve analysis used cumulative sum analysis, moving-average smoothing, and case-sequence quartile comparison. Outcomes were compared using 1:1 propensity-score matching (100 pairs) and multivariable regression. No monotonic improvement in unadjusted operative time was detected (r = 0.099, P = 0.287), and operative time did not differ between matched groups (80.0 vs. 75.0 min, P = 0.503). The periareolar approach had less blood loss (20.0 vs. 30.0 mL, P < 0.001) but fewer lymph node stations (6.0 vs. 7.0, P < 0.001) and nodes dissected (10.0 vs. 12.5, P = 0.025), and a higher complication rate (15.0

BACKGROUND:Current guidelines recommend lobectomy for tumors > 20 mm on CT, yet systematic CT-pathology size discordance may contribute to size-threshold-driven surgical decisions. We hypothesized that CT-based tumor diameter differs from pathological size near the 20 mm surgical boundary, potentially leading a proportion of patients to undergo more extensive resection than pathology would indicate under a size-only rule. METHODS:We retrospectively analyzed 1096 patients undergoing thoracoscopic surgery for clinical stage I non-small cell lung cancer at a single center (2020-2024). CT-pathology agreement was assessed via Bland-Altman analysis. Optimal CT cut-off was identified using restricted cubic spline (RCS) modeling, internally validated with bootstrap resampling (B = 2000), and evaluated by decision curve analysis (DCA). RESULTS:CT showed size-dependent bias: overestimation in small tumors (T1a: +4.21 mm) transitioning to underestimation in larger lesions (≥T2: -7.49 mm). At the 20 mm threshold, 15.8% of patients (n = 173) underwent lobectomy despite pathological size ≤ 20 mm (potential overtreatment). RCS modeling and bootstrap-optimized DCA identified 23 mm as the candidate revised threshold. Adopting CT > 23 mm would reclassify 108 patients from lobectomy to sublobar resection, reducing size-threshold-defined potential overtreatment by 51.4% while maintaining sensitivity for true ≥ T2 tumors. CONCLUSIONS:CT demonstrates size-dependent discordance with pathological size; this discordance likely reflects both CT measurement inaccuracy and specimen shrinkage after fixation, and the relative contributions cannot be separated from these data. A candidate 23 mm CT threshold, supported by DCA and internal bootstrap validation, could reduce size-threshold-defined potential overtreatment by 51% in this cohort. Prospective multicenter validation is required before clinical implementation.

Lung cancer (LC) has the highest cancer-related mortality rate. Even though genome-wide association studies (GWAS) have identified numerous loci linked to LC risk, the underlying causal genes and biological processes are still mostly unknown. The LC GWAS summary data comprised 29,863 cases and 55,586 controls of European ancestry. The weight file and related files of plasma protein, multi-tissue, and single-cell were obtained from Zhang’s study, Mancuso lab, and Thompson’s study, respectively. We conducted transcriptome association studies (TWAS) employing functional Summary-based Imputation (FUSION) from two levels, which were multiple tissues and single cell. We conducted proteome-wide association studies (PWAS) from plasma protein. Conditional and joint (COJO) analysis and multi-marker analysis of genomic annotation (MAGMA) analysis were used to further screen the PWAS/TWAS results. Summary-data-based Mendelian randomization (SMR) and colocalization analysis were utilized to explain the causal association between variables and results. A total of 13, 251, and 16 genes were calculated from the three dimensions, which were plasma protein, multiple tissues, and single cell, respectively. RNASET2 and IREB2 were obtained through intersecting these three sets of genes. COJO analysis and MAGMA analysis were replicated the two genes successfully. Then, RNASET2 was replicated in both eQTL-SMR and mQTL-SMR and following colocalization analysis. In summary, we conducted a multi-omic studies, which integrated three levels to investigate the novel targets for LC. Through a series of verifications, RNASET2 was identified as the key gene for LC in the current research.

Robotic-assisted thoracic surgery (RATS) is increasingly acknowledged for its efficacy in managing early-stage non-small cell lung cancer (NSCLC), owing to its distinct technical advantages. Nevertheless, individuals with pronounced incomplete interlobar fissures often face higher rates of conversion to alternative procedures and an increased likelihood of postoperative complications. This retrospective study introduces a novel robotic surgical technique tailored to the challenges posed by incomplete fissures, evaluating both its safety and therapeutic outcomes. A retrospective analysis was performed on the clinical data of individuals who received robotic-assisted lobectomy for NSCLC at our center from March 2021 to September 2024. Altogether, 554 cases were incorporated and divided into two cohorts—those with fully developed fissures and those with partially developed fissures—based on the anatomical features of their lung fissures. Among the 554 patients analyzed, 302 were categorized as having complete fissures, while 252 were identified with incomplete fissures. Comparative evaluation revealed no statistically significant differences between these groups in terms of operative duration (p = 0.411), intraoperative blood loss (p = 0.822), chest tube retention time (p = 0.733), rate of prolonged air leakage (PAL, p = 0.805), or postoperative hospital stay (p = 0.962). Importantly, neither group exhibited cases of bronchopleural fistula, pneumonia, or perioperative death. Incomplete fissures do not increase the procedural difficulty of lobectomy when employing this robotic surgical approach. This newly developed, robot-specific technique ensures both safety and efficacy for patients with incomplete fissures.

PurposeNon-small cell lung cancer (NSCLC) is the most common type of lung cancer, and about half of the patients had mutations in the epidermal growth factor receptor (EGFR) gene. Changes in the tumor microenvironment after EGFR mutation are closely related to tumor progression and treatment efficacy.Materials and methodsWe searched the Web of Science Core Collection database to select the articles related to tumor microenvironment in non-small cell lung cancer with epidermal growth factor receptor mutation. The countries/regions, institutes, authors, journals, references, and keywords were visualized and analyzed.Results227 relevant studies were obtained from WoSCC. These articles came from 102 countries and 1179 institutions. After network analysis, it was found that the intensity of USA cooperation with China was the greatest (LS=13), followed by cooperation with South Korea (LS=3) and with Japan (LS=3). A total of 2267 authors participated the all 227 articles. 112 journals were covered, and Frontiers in Oncology published most papers (n=16, 14.3%). A total of 7964 co-cited references are related to TME in NSCLC with EGFR mutation. “EGFR” is the keyword with the highest centrality (C=0.31) and first appeared. The keywords that burst in the last 1 year (2022-2023) are “immunotherapy”, “mechanism”, “lung neoplasms”, “T cells”, and “multicenter”.ConclusionEffective drug treatment of advanced NSCLC with EGFR mutations after failure of first-line chemotherapy is one of the hotspots, in which the efficacy of immune checkpoint inhibitors may be the direction of the current and future studies that need to find a breakthrough.

Background:Idiopathic pulmonary fibrosis (IPF) is a chronic and fatal interstitial lung disease marked by progressive extracellular matrix accumulation and irreversible lung architecture remodeling. Oxidative stress (OS) plays a crucial role in IPF pathogenesis, yet its role across distinct cellular compartments and tissue microenvironments remains incompletely characterized. Methods:We integrated single-cell RNA sequencing (scRNA-seq), spatial transcriptomics (stRNA-seq), and bulk RNA-seq datasets to comprehensively characterize oxidative stress activity across cellular and tissue scales in IPF lungs. Oxidative stress scores were calculated using multiple enrichment algorithms, and machine learning models (LASSO, Random Forest, Boruta, Bayesian, LVQ, Treebag) were applied to identify robust OS-related diagnostic biomarkers. Expression patterns were validated in public datasets and a bleomycin-induced C57BL/6 mouse model. Cell-cell communication and gene regulatory pathways were further explored using CellChat and pseudotime trajectory analysis. Results:Oxidative stress activity was significantly elevated in IPF lung tissue and specifically enriched in basal cells. Among 71 candidate OS-related genes, SCPEP1 emerged as the most robust biomarker, consistently upregulated across multiple datasets and experimental validation, with an AUC of 0.857 in the training cohort. SCPEP1 expression was spatially confined to airway-adjacent regions and highly specific to basal cells. SCPEP1+ basal cells exhibited transcriptional reprogramming enriched in Wnt signaling and developmental pathways, dynamic expression during early pseudotime progression, and engaged in multifaceted interactions with immune and stromal cells through pro-fibrotic and inflammatory signaling axes such as MIF-CD74, MDK-NCL, and ICAM1-ITGAL. Translationally, these findings may help prioritize redox-sensitive pathways and ligand-receptor interactions for further investigation. While SCPEP1 appears to be a promising candidate, its potential for patient stratification or therapeutic intervention remains to be confirmed through functional studies. Conclusion:Our multi-omics integration revealed SCPEP1+ basal cells as central oxidative stress responders and communication hubs in IPF. These findings provide insights into ROS-driven epithelial remodeling and highlight SCPEP1 as a potential contributor to disease-associated pathways that warrants further exploration for its diagnostic or therapeutic relevance.

The aim of this study is to evaluate the perioperative results of patients who receive robot-assisted thoracoscopic (RATS) modified segmentectomy and to compare the effectiveness and safety of this approach with those of traditional segmentectomy methods. A retrospective analysis was conducted on perioperative data from 587 consecutive patients diagnosed with early stage lung cancer who underwent robot-assisted thoracoscopic segmentectomy between January 2020 and September 2024. Using a 1:1 propensity score matching approach, 326 patients were paired based on clinical variables, such as age, sex, body weight, height, pulmonary function test results, and tumor size as measured by CT. Comparative assessments of perioperative outcomes and oncological parameters were performed between the matched groups. Of the 587 individuals included in the study, 178 underwent conventional segmentectomy (CS), while 409 received modified segmentectomy (MS). After applying propensity score matching, a total of 328 patients were retained for the final comparative analysis. The MS group demonstrated a significantly shorter operative time (83.72 ± 25.46 min vs. 121.01 ± 35.74 min, P < 0.001), lower total postoperative drainage volume (359.66 ± 413.70 ml vs. 527.98 ± 381.32 ml, P < 0.001), and a reduced postoperative hospital stay (3.76 ± 2.08 days vs. 4.69 ± 1.45 days, P < 0.001).Although the MS group exhibited a higher mean estimated blood loss, this difference did not reach statistical significance (58.87 ± 77.57 ml vs. 44.27 ± 55.35 ml, P = 0.051). Additionally, tumor size was significantly smaller in the MS cohort (8.67 ± 2.82 mm vs. 10.41 ± 4.08 mm, P < 0.001). Complete (R0) resection was achieved in all cases. The modified RATS segmentectomy offers significant benefits compared to conventional segmentectomy, such as shorter operative duration, reduced postoperative drainage, and a shorter postoperative hospital stay. These findings demonstrate the technical feasibility and potential advantages of this approach. However, further studies are needed to evaluate long-term oncological outcomes.

INTRODUCTION:Idiopathic pulmonary fibrosis (IPF) is a kind of interstitial lung disease with a poor prognosis. Even though genome-wide association studies (GWAS) have identified numerous loci linked to IPF risk, the underlying causal genes and biological processes are still mostly unknown. METHODS:The IPF GWAS summary data included 4,125 cases, 20,464 controls from five cohorts. The weight file and related files for transcriptome association studies (TWAS) of plasma protein, multi-tissues, cross-tissue, and single-cell were obtained from Zhang's study, Mancuso lab, GTExV8 database, and Thompson's study, respectively. We conducted TWAS employing functional Summary-based Imputation (FUSION) from four levels, which were plasma protein, multiple tissues, cross-tissue, and single cell. Conditional and joint (COJO) analysis and multi-marker analysis of genomic annotation (MAGMA) analysis were used to validate the above results. Summary-data-based Mendelian randomization (SMR) and Bayesian co-localization analysis were utilized to explain the causal association between selected genes and the risk of IPF. RESULTS:A total of 12, 361, 1187, and 72 genes were calculated from the four dimensions of TWAS. TOLLIP, GCHFR, ZNF318 TALDO1, CD151, and AP4M1 were selected by intersecting the results of the four sets of genes. GCHFR, TALDO1, CD151, and AP4M1 were verified by COJO analysis and MAGMA analysis. SMR and colocalization analyses identified GCHFR as the most significant gene for IPF. DISCUSSION:We have applied the TWAS approach to identify novel therapeutic targets for IPF in multiple dimensions. Further biological testing will be required in future studies to validate our findings. CONCLUSION:In summary, we carried out an extensive TWAS that integrated four dimensions: plasma protein, multiple tissues, cross-tissue, and single cell. GCHFR was identified as the most significant gene for IPF in this study.

This study evaluated the safety and feasibility of robot-assisted thoracic surgery (RATS) thymectomy using right-sided, left-sided, and subxiphoid approaches, and explored methods for accurate preoperative diagnosis of thymic cysts to minimize unnecessary thymectomies for benign lesions. We retrospectively analyzed patients who underwent RATS thymectomy via different approaches from 2020 to 2025. Patient characteristics and perioperative outcomes were compared. Receiver operating characteristic analysis was used to determine the optimal cutoff value for diagnosing thymic cysts. A total of 240 patients were included. Operative time was shortest in the right-sided group (50.9 ± 26.9 min), followed by the left-sided (62.5 ± 28.3 min) and subxiphoid (70.2 ± 35.5 min) groups (p < 0.001). Intraoperative blood loss (p = 0.29), chest tube duration (p = 0.05), hospital stay (p = 0.81), and postoperative morbidity (p = 0.95) were comparable among groups. The optimal mean CT attenuation value for diagnosing thymic cysts was 54.33 HU, with 87.8

BackgroundWhether lymph node metastasis in non-small cell lung cancer is critical to clinical decision-making. This study was to develop a non-invasive predictive model for preoperative assessing lymph node metastasis in patients with non-small cell lung cancer (NSCLC) using radiomic features from chest CT images.Materials & methodsIn this retrospective study, 247 patients with resectable non-small cell lung cancer (NSCLC) were enrolled. These individuals underwent preoperative chest CT scans that identified lung nodules, followed by lobectomies and either lymph node sampling or dissection. We extracted both intratumoral and peritumoral radiomic features from the CT images, which were used as covariates to predict the lymph node metastasis status. By using ROC curves, Delong tests, Calibration curve, and DCA curves, intra-tumoral-peri-tumoral model performance were compared with models using only intratumoral features or clinical information. Finally, we constructed a model that combined clinical information and radiomic features to increase clinical applicability.ResultsThis study enrolled 247 patients (117 male and 130 females). In terms of predicting lymph node metastasis, the intra-tumoral-peri-tumoral model (0.953, 95%CI 0.9272-0.9792) has a higher AUC compared to the intratumoral radiomics model (0.898, 95%CI 0.8553-0.9402) and the clinical model (0.818, 95%CI 0.7653-0.8709). The DeLong test shows that the performance of the Intratumoral and Peritumoral radiomics models is superior to that of the Intratumoral or clinical feature model (p <0.001). In addition, to increase the clinical applicability of the model, we combined the intratumoral-peritumoral model and clinical information to construct a nomogram. Nomograms still have good predictive performance.ConclusionThe radiomics-based model incorporating both peritumoral and intratumoral features from CT images can more accurately predict lymph node metastasis in NSCLC than traditional methods.

Background: To determine the perioperative quality assessment results and learning curves for robot-assisted anatomical lung resection.Methods: We analyzed the data of the initial 400 patients who underwent lobectomies or segmentectomies by 1 surgeon from January 2020 to November 2021. The learning curve was analyzed using cumulative sum analysis.Results: The surgical experience was divided into an initial phase (1st-40th procedures), a transition phase (41st-131st procedures), and a proficient phase (132nd procedure onward). The operative time showed a conspicuously continuous improvement over the 400 consecutive patients. After the 120th procedure, there were significant improvements in the rate of persistent air leakage (11.7% versus 3.9%; P = .003), chest tube duration (3.92 +/- 1.91 versus 2.99 +/- 1.31, P = .00), and postoperative hospital stay (6.22 +/- 2.02 versus 4.93 +/- 1.44, P = .00).Conclusions: In conclusion, 40 patients were necessary to pass the learning curve, and technical proficiency with favorable perioperative outcomes was achieved after 120-130 patients.

BackgroundElevated PPP4C expression has been associated with poor prognostic implications for patients suffering from lung adenocarcinoma (LUAD). The extent to which PPP4C affects immune cell infiltration in LUAD, as well as the importance of associated genes in clinical scenarios, still requires thorough investigation.MethodsIn our investigation, we leveraged both single-cell and comprehensive RNA sequencing data, sourced from LUAD patients, in our analysis. This study also integrated datasets of immune-related genes from InnateDB into the framework. Our expansive evaluation employed various analytical techniques; these included pinpointing differentially expressed genes, constructing WGCNA, implementing Cox proportional hazards models. We utilized these methods to investigate the gene expression profiles of PPP4C within the context of LUAD and to clarify its potential prognostic value for patients. Subsequent steps involved validating the observed enhancement of PPP4C expression in LUAD samples through a series of experimental approaches. The array comprised immunohistochemistry staining, Western blotting, quantitative PCR, and a collection of cell-based assays aimed at evaluating the influence of PPP4C on the proliferative and migratory activities of LUAD cells.ResultsIn lung cancer, elevated expression levels of PPP4C were observed, correlating with poorer patient prognoses. Validation of increased PPP4C levels in LUAD specimens was achieved using immunohistochemical techniques. Experimental investigations have substantiated the role of PPP4C in facilitating cellular proliferation and migration in LUAD contexts. Furthermore, an association was identified between the expression of PPP4C and the infiltration of immune cells in these tumors. A prognostic framework, incorporating PPP4C and immune-related genes, was developed and recognized as an autonomous predictor of survival in individuals afflicted with LUAD. This prognostic tool has demonstrated considerable efficacy in forecasting patient survival and their response to immunotherapeutic interventions.ConclusionThe involvement of PPP4C in LUAD is deeply intertwined with the tumor’s immune microenvironment. PPP4C’s over-expression is associated with negative clinical outcomes, promoting both tumor proliferation and spread. A prognostic framework based on PPP4C levels may effectively predict patient prognoses in LUAD, as well as the efficacy of immunotherapy strategy. This research sheds light on the mechanisms of immune interaction in LUAD and proposes a new strategy for treatment.

ABSTRACT:This expert consensus reviews current literature and provides clinical practice guidelines for the diagnosis and treatment of multiple ground glass nodule-like lung cancer. The main contents of this review include the following: ① follow-up strategies, ② differential diagnosis, ③ diagnosis and staging, ④ treatment methods, and ⑤ post-treatment follow-up.

Introduction Gastroesophageal reflux disease (GERD) is a chronic inflammatory gastrointestinal disease, which has no thoroughly effective or safe treatment. Elevated oxidative stress is a common consequence of chronic inflammatory conditions.Methods We employed Summary-data based MR (SMR) analysis to assess the associations between gene molecular characteristics and GERD. Exposure data were the summary-level data on the levels of DNA methylation, gene expression, and protein expression, which obtained from related methylation, expression, and protein quantitative trait loci investigations (mQTL, eQTL, and pQTL). Outcome data, Genome-wide association study (GWAS) summary statistics of GERD, were extracted from the Ong's study (discovery), the D & ouml;nerta & scedil;'s study (replication), and the FinnGen study (replication). Colocalization analysis was performed to determine if the detected signal pairs shared a causative genetic mutation. Oxidative stress related genes and druggable genes were imported to explore oxidative stress mechanism underlying GERD and therapeutic targets of GERD. The Drugbank database was utilized to conduct druggability evaluation.Results After multi-omics SMR analysis and colocalization analysis, we identified seven key genes for GERD, which were SUOX and SERPING1, DUSP13, SULT1A1, LMOD1, UBE2L6, and PSCA. SUOX was screened out to be the mediator, which suggest that GERD is related to oxidative stress. SERPING1, SULT1A1, and PSCA were selected to be the druggable genes.Conclusions These findings offered strong support for the identification of GERD treatment targets in the future as well as for the study of the oxidative stress mechanism underlying GERD. Key Messages What is already known on this topic? - Worries about secondary hypergastrinemia and other side effects linked to long-term PPI usage for gastroesophageal reflux disease (GERD) remain, and ongoing therapy is often necessary. Elevated oxidative stress is a common consequence of many chronic inflammatory conditions. No Mendelian randomization (MR) study has explored the possible causative connection between multi-omics integration data and GERD risk. What this study adds? - The present MR research investigated the possible causal correlations between DNA methylation, gene expression, and protein expression with GERD. We identified a few prospective GERD therapeutic targets and explored the oxidative stress mechanism of GERD. How this study might affect research, practice, or policy? - These results offered strong support for the identification of GERD treatment targets in the future as well as for the study of the oxidative stress mechanism underlying GERD.

Background: Due to the high heterogeneity of lung adenocarcinoma (LUAD), which restricts the effectiveness of therapy, precise molecular subgrouping of LUAD is of great significance. Clinical research has demonstrated the significant potential of DNA methylation as a classification indicator for human malignancies. Methods: WGML framework (which was developed based on weighted gene correlation network analysis (WGCNA), Gene Ontology (GO), and machine learning) was developed to precisely subgroup molecular subtypes of LUAD. This framework included two parts: the WG algorithm and the machine learning part. The WG algorithm part was an original algorithm used to obtain a crucial module, which was characterized by weighted correlation network analysis, functional annotation, and mathematical algorithms. The machine learning part utilized the Boruta algorithm, random forest algorithm, and Gradient Boosting Regression Tree algorithm to select feature genes. Then, based on the results of the WGML framework, subtypes were computed by the hierarchical clustering algorithm. A series of analyses, including dimensionality reduction methods, survival analysis, clinical stage analysis, immune infiltration analysis, tumor environment analysis, immune checkpoints analysis, TIDE analysis, CYT analysis, somatic mutation analysis, and drug sensitivity analysis, were utilized to demonstrate the effectiveness of subgrouping. GEO datasets were used to externally validate the results. Meanwhile, another subgrouping method of LUAD from another study was employed to compare with the WGML framework. Result: By importing DNA methylation data into the WGML framework, nine genes were obtained to further subgroup LUAD. Three subtypes, the Carcinogenesis subtype, Immune-infiltration subtype, and Chemoresistance subtype, were identified. The dimensionality reduction method exhibited great distinctness between subtypes. A series of analyses were employed to exhibit the difference among the three subtypes and to demonstrate the accuracy of the definition of subtypes. Besides, the WGML framework was compared with a LUAD subgrouping method from another research, which demonstrated that WGML had better efficiency for subgrouping LUAD. Conclusion: This study provides a novel LUAD subgrouping framework named WGML for the accurate subgrouping of lung adenocarcinoma. result: By importing DNA methylation data into WGML framework, nine genes were obtained to further subgroup LUAD. Three subtypes, Carcinogenesis subtype, Immune-infiltration subtype, and Chemoresistance subtype were identified. Dimensionality reduction method exhibited great distinctness between subtypes. A series analyses were employed to exhibit the difference of three subtypes and to demonstrate accuracy of definition of subtypes. Besides, WGML framework was compared with a LUAD subgrouping method from another research, which demonstrated WGML had better efficiency for subgrouping LUAD.