Identification of oxidative stress signatures of lung adenocarcinoma and prediction of patient prognosis or treatment response with single-cell RNA sequencing and bulk RNA sequencing data.

Lung adenocarcinoma (LUAD), the most common subtype of lung cancer globally, has seen improved prognosis with advancements in diagnostic, surgical, radiotherapy, and molecular therapy techniques, while its 5-year survival rate remains low. Molecular biomarkers provide prognostic value. Oxidative stress factors, such as reactive nitrogen species and ROS, are crucial in various stages of tumor progression, influencing cell transformation, proliferation, angiogenesis, and metastasis. ROS demonstrate dual roles, affecting tumor cells, hypoxia sensitivity, and the microenvironment. Comprehensive analysis of oxidative stress in LUAD has not been conducted to date. Therefore, we systematically investigated the regulatory patterns of oxidative stress in LUAD based on oxidative stress-related genes and correlated these patterns with cellular infiltration characteristics of the tumor immune microenvironment. The model utilizes single-factor Cox analysis to screen key differential genes with prognostic value and employs least absolute shrinkage and selection operator (LASSO) penalized Cox regression analysis to construct a prognostic-related prediction model. Ten candidate genes were selected based on this model. The risk score was constructed using the coefficients and expression levels of these ten genes. Furthermore, the impact of this risk score on overall survival (OS) was determined. Two genes with the most significant differential expression, SFTPB and S100P, were selected through qRT-PCR. Cell experiments including CCK-8, Edu, transwell assays confirmed their effects on lung cancer cells growth, consistent with the results of bioinformatics analysis. These findings suggested that this model held potential clinical value for evaluating the prognosis of lung adenocarcinoma.

Spectroscopic analyses of particle and energy aggregations at the interface of silver nanoparticles and fluorescent carbon nanodots.

We study the change in the surface electromagnetic field provided by photoexcited silver nanoparticles as the field is disturbed by fluorescent carbon nanodots. Fluorescent carbon nanodots with an appropriate quantity and quality of surface functional groups are used to mediate the aggregation of silver nanoparticles of matching size and shape to form available nano-size conical structures. Carbon nanodots in the composite absorb and transfer additional photoenergy to the silver surface, resulting in energy aggregation within the cone structure and enhancement of the electromagnetic field in proximity to the silver surface. This elevated energy state is manifested in the strengthening of the SERS signal of the analytical probe 4-aminophenyl disulfide and the mechanism involved is elucidated by additional molecular spectroscopy studies.

The molecular mechanism of sepsis-induced diaphragm dysfunction.

Background: No effective drugs for the treatment of sepsis-induced diaphragm dysfunction are currently available. Therefore, it is particularly important to clarify the molecular regulatory mechanism of this condition and subsequently implement effective treatment and prevention of sepsis-induced diaphragm dysfunction. Methods: A mouse model of diaphragm dysfunction was established via injection of lipopolysaccharide (LPS). An RNA-sequencing (RNA-seq) technique was used to detect the differentially expressed genes (DEGs) in the diaphragms of mice. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed for functional analysis of DEGs. The protein-protein interaction network obtained from the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) website was imported into Cytoscape, the key molecular regulatory network was constructed with CytoNCA, the ClueGo plugin was further used to analyze the core regulatory pathways of key molecular, and finally, the iRegulon plugin was used to the identify key transcription factors. Results: The genes upregulated after LPS treatment were involved in biological processes and pathways related to immune response; the genes downregulated after LPS treatment were mainly correlated with the muscle contraction. The expressions of several inflammation-related genes were upregulated after LPS treatment, of which tumor necrosis factor (Tnf), interleukin (Il)-1ß, and Il-6 assumed a core regulatory role in the network; meanwhile, the downregulated key genes included Col1a1, Uqcrfs1, Sdhb, and ATP5a1, among others. These key regulatory factors participated in the activation of Toll-like receptor (TLR) signaling pathway, nuclear factor (NF)-κB signaling pathway, and TNF signaling pathway as well as the inhibition of oxidative phosphorylation pathway, cardiac muscle contraction pathway, and citrate cycle pathway. Finally, RelA, IRF1, and STAT3, were identified as the key regulators in the early stage of diaphragmatic inflammatory response. Conclusions: Sepsis-induced diaphragm dysfunction in mice is closely correlated with the activation of TLR signaling pathway, NF-κB signaling pathway, and TNF signaling pathway and the inhibition of oxidative phosphorylation pathway, cardiac muscle contraction pathway, and citrate cycle pathway. Our findings provide insight into the molecular mechanism of sepsis-induced diaphragm dysfunction in mice and provide a promising new strategy for targeted treatment of diaphragm dysfunction.

MiR-202-3p inhibits the proliferation and metastasis of lung adenocarcinoma cells by targeting RRM2.

Background: Lung adenocarcinoma (LUAD) is the most common type of lung cancer, and its pathogenesis is still unclear. The present study aimed to investigate the role of miR-202-3p and its downstream target gene, ribonucleotide reductase regulatory subunit M2 (RRM2), in the occurrence and development of LUAD and elucidate the correlation between RRM2 and the clinicopathological stage and prognosis of LUAD. Methods: The expression of miR-202-3p was analyzed using the CancerMIRNome database and quantitative polymerase chain reaction (qPCR). The effects of miR-202-3p and RRM2 on the proliferation, migration, and invasion of A549 cells were analyzed. A dual luciferase reporter assay was used to verify the targeting of miR-202-3p and RRM2. Additionally, the correlation between RRM2 expression and clinicopathology was analyzed. Results: (I) MiR-202-3p was lowly expressed in LUAD and the LUAD cell lines. qPCR confirmed that microRNA (miRNA) transfection was effective and sufficient for subsequent experiments. (II) MiR-202-3p inhibited the proliferation, invasion, and migration of LUAD cells. (III) There was a targeting relationship between miR-202-3p and RRM2, and miR-202-3p affected the expression of the RRM2 protein. RRM2 was highly expressed in lung cancer tissue. (IV) RRM2 was associated with the clinicopathological staging of lung cancer. The prognosis of patients with low RRM2 expression was better, and the prognostic sensitivity of RRM2 to lung cancer was high. RRM2 may exert its effects via the Notch pathway. (V) Si-RRM2 inhibited the expression of the RRM2 protein. RRM2 promoted the proliferation, migration, and invasion of LUAD cells. A miR-202-3p inhibitor restored the inhibitory effect of si-RRM2 on LUAD cells. Conclusions: MiR-202-3p was lowly expressed in lung cancer tissue. MiR-202-3p overexpression inhibited the proliferation and metastasis of lung cancer cells. RRM2 was highly expressed in lung cancer tissue and promoted the proliferation and metastasis of lung cancer cells. MiR-202-3p targeted and inhibited RRM2, thereby reducing the proliferation and metastasis of LUAD cells. LUAD patients with low RRM2 expression had a better prognosis, and the expression level of RRM2 was correlated with the clinical characteristics of lung cancer patients.

The predictive prognostic values of CBFA2T3, STX3, DENR, EGLN1, FUT4, and PCDH7 in lung cancer.

BACKGROUND: Lung cancer is one of the most malignant tumors. However, neither the pathogenesis of lung cancer nor the prognosis markers are completely clear. The purpose of this study is to screen the diagnostic or prognostic markers of lung cancer. METHODS: TCGA and GEO datasets were used to analyze the relationship between lung cancer-related genes and lung cancer samples. Common differential genes were screened, and a univariate Cox regression analysis was used to screen survival related genes. A univariable Cox proportional hazards regression analysis was used to verify the genes and construct risk model. The key factors affecting the prognosis of lung cancer were determined by univariate and multivariate regression analyses. The ROC curve, AUC and the survival of each risk gene was analyzed. Finally, the biological functions of high- and low-risk patients were explored by GSEA and an immune-infiltration analysis. RESULTS: Based on the common differential genes, 13 genes significantly related to lung cancer survival were identified. Eight risk genes (CBFA2T3, DENR, EGLN1, FUT2, FUT4, PCDH7, PHF14, and STX3) were screened out. The results showed that risk status may be an independent prognostic factor, and the risk score predicted the prognosis of lung cancer. CBFA2T3 and STX3 are protective genes, while DENR, EGLN1, FUT4 and PCDH7 are dangerous genes. These 6 genes can be used as independent lung cancer prognosis markers. The corresponding biological functions of genes expressed in high-risk patients were mostly related to tumor proliferation and inflammatory infiltration. Neutrophil, CD8+T, Macrophage M0, Macrophage M1- and mDC-activated cells were high in high-risk status samples. CONCLUSIONS: CBFA2T3, STX3, DENR, EGLN1, FUT4, and PCDH7 are important participants in the occurrence and development of lung cancer. High-risk patients display serious inflammatory infiltration. This study not only provides insight into the mechanism of occurrence and development of lung cancer, but also provides potential targets for targeted therapy of lung cancer.