Highly efficient prevention of radiation dermatitis using a PEGylated superoxide dismutase dissolving microneedle patch.

PEGylated superoxide dismutase (PEG-SOD) is commonly used as a cytoprotective agent in radiotherapy. However, its effectiveness in preventing radiation dermatitis is limited owing to its poor skin permeability. To address this issue, a PEG-SOD-loaded dissolving microneedle (PSMN) patch was developed to effectively prevent radiation dermatitis. Initially, PSMN patches were fabricated using a template mold method with polyvinylpyrrolidone K90 as the matrix material. PSMNs exhibited a conical shape with adequate mechanical strength to penetrate the stratum corneum. More than 90 % of PEG-SOD was released from the PSMN patches within 30 min. Notably, the PSMN patches showed a significantly higher drug skin permeation than the PEG-SOD solutions, with a 500-fold increase. In silico simulations and experiments on skin pharmacokinetics confirmed that PSMN patches enhanced drug permeation and skin absorption, in contrast to PEG-SOD solutions. More importantly, PSMN patches efficiently mitigated ionizing radiation-induced skin damage, accelerated the healing process of radiation-affected skin tissues, and exhibited highly effective radioprotective activity for DNA in the skin tissue. Therefore, PSMN patches are promising topical remedy for the prevention of radiation dermatitis.

Thyroid hormones as biomarkers of lung cancer: a retrospective study.

BACKGROUND: Thyroid hormones are key regulators of several physiological processes, including differentiation, embryonic development, proliferation, and metabolism. Several prospective studies have shown a relationship between hyperthyroidism and cancer incidence; however, since the association between thyroid hormone levels and lung cancer remains controversial, this study aimed to determine the correlation between the same. METHODS: We retrospectively analyzed 289 patients, who were diagnosed with lung cancer at the Huzhou Central Hospital between January 2016 and January 2021, and 238 healthy subjects. The baseline clinical data of two groups were collected. The concentrations of thyroid hormones, tumor CEA, CYF, SCC, and NSE in both the lung cancer patient and healthy volunteer groups were analyzed. Student's t-test or Mann-Whitney test was used to compare continuous variables. A chi-square test was adopted to estimate the relationship between serum thyroid hormones level and clinical characteristics of lung cancer cases. ROC curve analyses were used to determine the characteristics of thyroid hormones for recognizing lung cancer. RESULTS: The results showed that serum thyroid stimulating hormone (TSH), total thyroxine, total triiodothyronine, and free triiodothyronine (FT3) levels were significantly decreased, while free thyroxine (FT4) levels were increased in patients with lung cancer. In addition, FT3 was identified as a potential diagnostic biomarker of stage I-IV lung cancer with the area under the curve values of 0.807. What's more, FT3 and FT4 were used in combination with CEA and were identified as potential diagnostic biomarkers of stage 0 lung cancer (Tis) with the area under the curve values of 0.774. CONCLUSIONS: Our study highlights the possibility of using thyroid hormones as innovative diagnostic markers for lung cancer.

Serum TSH, TT4, TT3, and FT3 levels were significantly decreased in patients with lung cancer.low TT3 concentration was positively associated with age (p < 0.05), sex (p < 0.05), tumor size (p < 0.05) and lymph node metastasis (p < 0.05). Moreover, the concentration of FT3 was dependent on age (p < 0.05) and tumor size (p < 0.05). The serum FT4 concentration was discernible with obviously higher concentration in stage IV patients compared with stage I­III patients (p < 0.05).When FT3 was used in combination with CEA and CYF, the sensitivity and specificity in the screening for stage I­IV lung cancer were markedly increased to 85.9% and 97.5%, respectively. When we included FT3, FT4, and CEA in the diagnosis, the AUC was 0.774. The sensitivity and specificity of screening for stage 0 lung cancer were increased to 70.2% and 75.2%, respectively.

Low Expression of ADCY4 Predicts Worse Survival of Lung Squamous Cell Carcinoma Based on Integrated Analysis and Immunohistochemical Verification.

PURPOSE: The molecular mechanism underlying the carcinogenesis and development of lung squamous cell carcinoma (LUSC) has not been sufficiently elucidated. This analysis was performed to find pivotal genes and explore their prognostic roles in LUSC. METHODS: A microarray dataset from GEO (GSE19188) and a TCGA-LUSC dataset were used to identify differentially co-expressed genes through Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis. We conducted functional enrichment analyses of differentially co-expressed genes and established a protein-protein interaction (PPI) network. Then, we identified the top 10 hub genes using the Maximal Clique Centrality (MCC) algorithm. We performed overall survival (OS) analysis of these hub genes among LUSC cases. GSEA analyses of survival-related hub genes were conducted. Ultimately, the GEO and The Human Protein Atlas (THPA) databases and immunohistochemistry (IHC) results from the real world were used to verify our findings. RESULTS: A list of 576 differentially co-expressed genes were selected. Functional enrichment analysis indicated that regulation of vasculature development, cell-cell junctions, actin binding and PPAR signaling pathways were mainly enriched. The top 10 hub genes were selected according to the ranking of MCC scores, and 5 genes were closely correlated with OS of LUSC. Additionally, GSEA analysis showed that spliceosome and cell adhesion molecules were associated with the expression of GNG11 and ADCY4, respectively. The GSE30219 and THPA databases and IHC results from the real world indicated that although GNG11 was not detected, ADCY4 was obviously downregulated in LUSC tissues at the mRNA and protein levels. CONCLUSIONS: This analysis showed that survival-related hub genes are highly correlated to the tumorigenesis and development of LUSC. Additionally, ADCY4 is a candidate therapeutic and prognostic biomarker of LUSC.

Identification of a Novel Four-Gene Signature Correlated With the Prognosis of Patients With Hepatocellular Carcinoma: A Comprehensive Analysis.

PURPOSE: Hepatocellular carcinoma (HCC) is a common solid-tumor malignancy with high heterogeneity, and accurate prognostic prediction in HCC remains difficult. This analysis was performed to find a novel prognostic multigene signature. METHODS: The TCGA-LIHC dataset was analyzed for differentially coexpressed genes through weighted gene coexpression network analysis (WGCNA) and differential gene expression analysis. A protein-protein interaction (PPI) network and univariate Cox regression analysis of overall survival (OS) were utilized to identify their prognostic value. Next, we used least absolute shrinkage and selection operator (LASSO) Cox regression to establish a prognostic module. Subsequently, the ICGC-LIRI-JP dataset was applied for further validation. Based on this module, HCC cases were stratified into high-risk and low-risk groups, and differentially expressed genes (DEGs) were identified. Functional enrichment analyses of these DEGs were conducted. Finally, single-sample gene set enrichment analysis (ssGSEA) was performed to explore the correlation between the prognostic signature and immune status. RESULTS: A total of 393 differentially coexpressed genes were obtained. Forty differentially coexpressed hub genes were identified using the CytoHubba plugin, and 38 of them were closely correlated with OS. Afterward, we established the four-gene prognostic signature with an acceptable accuracy (area under the curve [AUC] of 1-year survival: 0.739). The ICGC-LIRI-JP dataset also supported the acceptable accuracy (AUC of 1-year survival:0.752). Compared with low-risk cohort, HCC cases in the high-risk cohort had shorter OS, higher tumor grades, and higher T stages. The risk scores of this signature still act as independent predictors of OS (P<0.001). Functional enrichment analyses suggest that it was mainly organelle fission and nuclear division that were enriched. Finally, ssGSEA revealed that this signature is strongly associated with the immune status of HCC patients. CONCLUSIONS: The proposed prognostic signature of four differentially coexpressed hub genes has satisfactory prognostic ability, providing important insight into the prediction of HCC prognosis.

Identification of pivotal genes associated with the prognosis of gastric carcinoma through integrated analysis.

PURPOSE: Detecting and diagnosing gastric cancer (GC) during its early period remains greatly difficult. Our analysis was performed to detect core genes correlated with GC and explore their prognostic values. METHODS: Microarray datasets from the Gene Expression Omnibus (GEO) (GSE54129) and The Cancer Genome Atlas (TCGA)-stomach adenocarcinoma (STAD) datasets were applied for common differentially co-expressed genes using differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA). Functional enrichment analysis and protein-protein interaction (PPI) network analysis of differentially co-expressed genes were performed. We identified hub genes via the CytoHubba plugin. Prognostic values of hub genes were explored. Afterward, Gene Set Enrichment Analysis (GSEA) was used to analyze survival-related hub genes. Finally, the tumor-infiltrating immune cell (TIC) abundance profiles were estimated. RESULTS: Sixty common differentially co-expressed genes were found. Functional enrichment analysis implied that cell-cell junction organization and cell adhesion molecules were primarily enriched. Hub genes were identified using the degree, edge percolated component (EPC), maximal clique centrality (MCC), and maximum neighborhood component (MNC) algorithms, and serpin family E member 1 (SERPINE1) was highly associated with the prognosis of GC patients. Moreover, GSEA demonstrated that extracellular matrix (ECM) receptor interactions and pathways in cancers were correlated with SERPINE1 expression. CIBERSORT analysis of the proportion of TICs suggested that CD8+ T cell and T-cell regulation were negatively associated with SERPINE1 expression, showing that SERPINE1 may inhibit the immune-dominant status of the tumor microenvironment (TME) in GC. CONCLUSIONS: Our analysis shows that SERPINE1 is closely correlated with the tumorigenesis and progression of GC. Furthermore, SERPINE1 acts as a candidate therapeutic target and prognostic biomarker of GC.

Disulfur-bridged polyethyleneglycol/DOX nanoparticles for the encapsulation of photosensitive drugs: a case of computational simulations on the redox-responsive chemo-photodynamic drug delivery system.

Tumor redox stimulus-responsive nanoparticulate drug delivery systems (nano-DDSs) have attracted considerable attention due to their thermodynamically stable microstructures and well-controlled drug release properties. However, drug-loading nanoparticle conformation and redox-triggered drug release mechanisms at the molecular level remain unclear. Herein, doxorubicin-conjugated polymers were constructed using disulfide bonds as linkages (PEG-SS-DOX), which loaded photosensitizer chlorin e6 (Ce6). We integrated multiple scale dynamic simulations (density functional theory (DFT) calculation, atomistic molecular dynamics (MD) simulation and dissipative particle dynamics (DPD) simulations) to elucidate the assembly/drug release dynamic processing. First, it was revealed that the emergence of the calculated bond flexible angle of disulfide bonds facilitated the assembly behavior and improved the stability of conformation. Sorted by the binding model, hydrogen bonding accounted for the major interactions between polymers and photosensitive drugs. DPD simulations were further delved into to acquire knowledge regarding the drug-free self-aggregation and Ce6-loaded assembly mechanism. The results show that nano-assembly conformation not only depended on the concentration of polymers, but also were associated with the polymer-drug ratio. Different from dicarbon bond-bridging polymers, disulfide bonds would contribute to the breakage of the polymer and the rapid release of DOX and Ce6. Our findings provide deep insights into the influence of redox-responsive chemical linkages and offer theoretical guidance to the rational design of specific stimulus-responsive nano-DDSs for cancer therapy.