The adenosine-signaling axis has been recognized as an important immunomodulatory pathway in tumor immunity. However, the biological role of the adenosine-signaling axis in the remodeling of the tumor microenvironment (TME) in lung adenocarcinoma (LUAD) remains unclear. Here, we quantified adenosine signaling (ado_sig) in LUAD samples using the GSVA method and assessed the prognostic value of adenosine in LUAD. Afterward, we explored the heterogeneity of the tumor-immune microenvironment at different adenosine levels. In addition, we analyzed the potential biological pathways engaged by adenosine. Next, we established single-cell transcriptional profiles of LUAD and analyzed cellular composition and cell-cell communication analysis under different adenosine microenvironments. Moreover, we established adenosine-related prognostic signatures (ARS) based on comprehensive bioinformatics analysis and evaluated the efficacy of ARS in predicting immunotherapy. The results demonstrated that adenosine signaling adversely impacted the survival of immune-enriched LUAD. The high-adenosine microenvironment exhibited elevated pro-tumor-immune infiltration, including M2 macrophages and displayed notably increased epithelial-mesenchymal transition (EMT) transformation. Furthermore, adenosine signaling displayed significant associations with the expression patterns and prognostic value of immunomodulators within the TME. Single-cell sequencing data revealed increased fibroblast occupancy and a prominent activation of the SPP1 signaling pathway in the high adenosine-signaling microenvironment. The ARS exhibited promising effectiveness in prognostication and predicting immunotherapy response in LUAD. In summary, overexpression of adenosine can cause a worsened prognosis in the LUAD with abundant immune infiltration. Moreover, increased adenosine levels are associated with pro-tumor-immune infiltration, active EMT transformation, pro-tumor angiogenesis, and other factors promoting cancer progression, which collectively contribute to the formation of an immunosuppressive microenvironment. Importantly, the ARS developed in this study demonstrate high efficacy in evaluating the response to immunotherapy.

Objection Investigating the key genes and mechanisms that influence stemness in lung adenocarcinoma. Methods First, consistent clustering analysis was performed on lung adenocarcinoma patients using stemness scoring to classify them. Subsequently, WGCNA was utilized to identify key modules and hub genes. Then, machine learning methods were employed to screen and identify the key genes within these modules. Lastly, functional analysis of the key genes was conducted through cell scratch assays, colony formation assays, transwell migration assays, flow cytometry cell cycle analysis, and xenograft tumor models. Results First, two groups of patients with different stemness scores were obtained, where the high stemness score group exhibited poor prognosis and immunotherapy efficacy. Next, LASSO regression analysis and random forest regression were employed to identify genes (PBK, RACGAP1) associated with high stemness scores. RACGAP1 was significantly upregulated in the high stemness score group of lung adenocarcinoma and closely correlated with clinical pathological features, poor overall survival (OS), recurrence-free survival (RFS), and unfavorable prognosis in lung adenocarcinoma patients. Knockdown of RACGAP1 suppressed the migration, proliferation, and tumor growth of cancer cells. Conclusion RACGAP1 not only indicates poor prognosis and limited immunotherapy benefits but also serves as a potential targeted biomarker influencing tumor stemness.

OBJECTIVE:This study aimed to assess the functions of cell division cycle protein 45 (CDC45) in Non-small cell lung cancer (NSCLC) cancer and its effects on stemness and metastasis. METHODS:Firstly, differentially expressed genes related to lung cancer metastasis and stemness were screened by differential analysis and lasso regression. Then, in vitro, experiments such as colony formation assay, scratch assay, and transwell assay were conducted to evaluate the impact of CDC45 knockdown on the proliferation and migration abilities of lung cancer cells. Western blotting was used to measure the expression levels of related proteins and investigate the regulation of CDC45 on the cell cycle. Finally, in vivo model with subcutaneous injection of lung cancer cells was performed to verify the effect of CDC45 on tumor growth. RESULTS:This study identified CDC45 as a key gene potentially influencing tumor stemness and lymph node metastasis. Knockdown of CDC45 not only suppressed the proliferation and migration abilities of lung cancer cells but also caused cell cycle arrest at the G2/M phase. Further analysis revealed a negative correlation between CDC45 and cell cycle-related proteins, stemness-related markers, and tumor mutations. Mouse experiments confirmed that CDC45 knockdown inhibited tumor growth. CONCLUSION:As a novel regulator of stemness, CDC45 plays a role in regulating lung cancer cell proliferation, migration, and cell cycle. Therefore, CDC45 may serve as a potential target for lung cancer treatment and provide a reference for further mechanistic research and therapeutic development.

Objective: this study evaluates the prognostic relevance of gene subtypes and the role of kinesin family member 2C (KIF2C) in lung cancer progression. Methods: high-expression genes linked to overall survival (OS) and progression-free interval (PFI) were selected from the TCGA-LUAD dataset. Consensus clustering analysis categorized lung adenocarcinoma (LUAD) patients into two subtypes, C1 and C2, which were compared using clinical, drug sensitivity, and immunotherapy analyses. A random forest algorithm pinpointed KIF2C as a prognostic hub gene, and its functional impact was assessed through various assays and in vivo experiments. Results: The study identified 163 key genes and distinguished two LUAD subtypes with differing OS, PFI, pathological stages, drug sensitivity, and immunotherapy response. KIF2C, highly expressed in the C2 subtype, was associated with poor prognosis, promoting cancer cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT), with knockdown reducing tumor growth in mice. Conclusion: The research delineates distinct LUAD subtypes with significant clinical implications and highlights KIF2C as a potential therapeutic target for personalized treatment in LUAD. This study evaluates the prognostic relevance of gene subtypes and the role of kinesin family member 2C (KIF2C) in lung cancer progression.

ObjectiveBy utilizing machine learning, we can identify genes that are associated with recurrence, invasion, and tumor stemness, thus uncovering new therapeutic targets.MethodsTo begin, we obtained a gene set related to recurrence and invasion from the GEO database, a comprehensive gene expression database. We then employed the Weighted Gene Co-expression Network Analysis (WGCNA) to identify core gene modules and perform functional enrichment analysis on them. Next, we utilized the random forest and random survival forest algorithms to calculate the genes within the key modules, resulting in the identification of three crucial genes. Subsequently, one of these key genes was selected for prognosis analysis and potential drug screening using the Kaplan-Meier tool. Finally, in order to examine the role of CDC20 in lung adenocarcinoma (LUAD), we conducted a variety of in vitro and in vivo experiments, including wound healing assay, colony formation assays, Transwell migration assays, flow cytometric cell cycle analysis, western blotting, and a mouse tumor model experiment.ResultsFirst, we collected a total of 279 samples from two datasets, GSE166722 and GSE31210, to identify 91 differentially expressed genes associated with recurrence, invasion, and stemness in lung adenocarcinoma. Functional enrichment analysis revealed that these key gene clusters were primarily involved in microtubule binding, spindle, chromosomal region, organelle fission, and nuclear division. Next, using machine learning, we identified and validated three hub genes (CDC45, CDC20, TPX2), with CDC20 showing the highest correlation with tumor stemness and limited previous research. Furthermore, we found a close association between CDC20 and clinical pathological features, poor overall survival (OS), progression-free interval (PFI), progression-free survival (PFS), and adverse prognosis in lung adenocarcinoma patients. Lastly, our functional research demonstrated that knocking down CDC20 could inhibit cancer cell migration, invasion, proliferation, cell cycle progression, and tumor growth possibly through the MAPK signaling pathway.ConclusionCDC20 has emerged as a novel biomarker for monitoring treatment response, recurrence, and disease progression in patients with lung adenocarcinoma. Due to its significance, further research studying CDC20 as a potential therapeutic target is warranted. Investigating the role of CDC20 could lead to valuable insights for developing new treatments and improving patient outcomes.

Silicosis, a highly lethal occupational respiratory disease characterized by irreversible pulmonary fibrosis, remains challenging to treat due to its unclear pathogenesis. In this study, bioinformatics, network pharmacology, and experimental validation were combined to explore potential mechanisms and therapeutic drugs for silicosis. First, the differentially expressed genes（DEGs）and pathway enrichment in pulmonary fibrosis were identified by GO and KEGG analysis. Next, the differential genes were submitted to cMap database for drug prediction and celastrol stood out as the most promising candidate drug. Then, network pharmacology analysis identified pharmacological targets of celastrol and demonstrated that celastrol could regulate JAK-STAT, MAPK, and Toll-like receptor signaling pathways. Finally, we verified the therapeutic role and mechanism of celastrol on silicosis. In vivo, celastrol significantly ameliorated CS-induced inflammation and fibrosis in silicosis mice, including inflammatory cell infiltration, collagen fiber and extracellular matrix deposition, fibroblast activation and related factor expression. Moreover, it dramatically improved lung respiratory function of silicosis mice. In vitro, celastrol suppressed CS-induced cytokine expression, apoptosis of macrophages and activation of Stat3 and Erk1/2 signals. Overall, our research identified and verified celastrol as a novel and promising candidate drug for silicosis.

Prior researches indicate that peripheral blood CD4 levels have an inverse correlation with distant tumor metastasis in non-small cell lung cancer (NSCLC). However, the linear relationship between CD4 and distant metastasis lacks clarity. Hence, the objective of this study was to ascertain the linear relationship between CD4 and distant metastasis in NSCLC patients. This retrospective study analyzed clinical and laboratory data of NSCLC patients between March 2016 and July 2022 at the Cancer Hospital of Anhui University of Technology. The study first applied a generalized summation model and smoothing curve fitting to determine if there was a linear relationship between CD4 and NSCLC metastasis. Secondarily, univariate logistic analysis and multiple linear regression were used to analyze the odds ratio (OR) of CD4 as a continuous variable, dichotomous variable, and trichotomous variable when predicting NSCLC metastasis. In addition, stratified and subgroup analyses were conducted to assess the reliability of CD4 in different NSCLC patient populations. The study included a total of 213 NSCLC patients, among which 122 had distant metastasis and 91 had no metastasis. The smoothing curve fitting analysis revealed a U-shaped relationship between CD4 and NSCLC metastasis with a threshold effect. The univariate logistic analysis indicated that continuous CD4 expression was not significantly associated with NSCLC metastasis (P = 0.051); however, high levels of CD4 expression (≥ 35.06

Background The occurrence of epithelial-mesenchymal transition (EMT) and immune evasion is considered to contribute to poor prognosis in lung adenocarcinoma (LUAD). Therefore, this study aims to explore the key oncogenes that promote EMT and immune evasion and reveal the expression patterns, prognostic value, and potential biological functions. Methods Firstly, we identified gene modules associated with EMT and Tumor Immune Dysfunction and Exclusion (TIDE) through weighted gene co-expression network analysis (WGCNA). Next, we utilized differential analysis and machine learning to identify the key genes and validate them. Moreover, we analyzed the correlation between key genes and tumor microenvironment remodeling, drug sensitivity, as well as mutation frequency. Furthermore, we explored and validated their malignant biological characteristics through in vitro experiments and clinical samples. Finally, potential drugs for LUAD were screened based on CMap and validated through experiments. Results Firstly, WGCNA analysis revealed that red and green modules were highly correlated with EMT and TIDE. Among them, upregulated expression of SPOCK1 was observed in lung adenocarcinoma tissues and was associated with poor prognosis. Additionally, patients in the high SPOCK1 group showed more activation of malignant oncogenic pathways, higher infiltration of immunosuppressive components, and a higher frequency of mutations. The knockdown of SPOCK1 suppressed invasion and metastasis capabilities of lung adenocarcinoma cells, and the high expression of SPOCK1 was associated with low infiltration of CD8 + T cells. Therapeutic aspects, SPOCK1 can be a candidate indicator for drug sensitivity and CMap showed that VER-155008 was the drug candidate with the largest perturbation effect on the SPOCK1 expression profile. In vitro and in vivo experiments validated the cancer-inhibitory effect of VER-155008 in LUAD. Conclusion This study revealed through comprehensive bioinformatics analysis and experimental analysis that SPOCK1 can promote EMT and immune escape in LUAD, and it may serve as a promising candidate prognostic biomarker and therapeutic target for LUAD.

Evidence suggests that interferon alpha (IFNα) plays an essential role in decreasing the HBsAg quantification and elevating the rate of clinical cure in chronic hepatitis B (CHB). However, the mechanisms underlying the effects of the exosomes on the expression of host genes in IFNα treatment remain unclear.CHB patients with IFNα treatment were divided into responders and non-responders according to the degree of HBsAg decline. Through microRNA sequencing and a series of molecular biology methods, the key microRNAs in serum exosomes associated with clinical antiviral response of Peg-IFNα treatment in nucleotide analogue-treated CHB patients were investigated. The roles of exosomal miRNAs on the IFNα signal pathway were explored in macrophages.MicroRNA sequencing and RT-qPCR assays confirmed six distinctly declined miRNAs in serum exosomes of responders at week 12 compared with levels at baseline. Exosomes with declined miR27b-3p in the serum of Peg-IFNα-treated responders activated phosphorylation of interferon regulatory factor 3/7 (IRF3/7) in IFNα synthesis pathway in macrophages. However, miR27b-3p overexpression in HepAD38 cells suppressed IFNα synthesis in macrophages, resulting in insufficient ability to eliminate HBV, whereas the inhibitory effect could be blocked by inhibitors of exosomes release. Luciferase assay showed miR-27b-3p directly suppressed retinoic acid-inducible gene I (RIG-I) and TANK-binding kinase 1 (TBK1) expressions, and these effects could be abrogated in mutation experiments.In IFNα treatment, exosomes with declined miR-27b-3p triggered activation of RIG-I/TBK1 signalling in macrophages against HBV. Serum exosomal miR-27-3p might represent a potential biomarker for patients with CHB.