Ultrasound-assisted complex enzyme extraction, structural characterization, and biological activity of polysaccharides from Ligustrum robustum.

Ligustrum robustum is one of the traditional teas in China with a long history of drinking and medicinal use. Through Response surface optimization, the yield of polysaccharides extracted by ultrasonic-assisted complex enzyme (UAE-EN) method was increased to 14.10 ±â€¯0.56 %. Neutral homogeneous polysaccharide (LRNP) and acidic homogeneous polysaccharide (LRAP-1, LRAP-2, LRAP-3) from L. robustum were purified. The molecular weights of them were 5894, 4256, 4621 and 3915 Da. LRNP was composed of glucose (Glc), galactose (Gal), arabinose (Ara) with molar percentage of 24.97, 42.38 and 30.80. Structure analysis revealed that the backbone of LRNP consisted of 1,5-linked α-Araf, 1,4-linked ß-Galp, 1,6-linked ß-Galp, and 1,4-linked ß-Glcp with the branches of 1,2-linked α-Araf, 1,3-linked α-Araf, 1,3-linked ß-Glcp and 1,6-linked ß-Galp residues, some terminal residues of α-Araf, ß-Glcp and α-Galp were also included. In vitro experiments showed that the four polysaccharides possessed excellent antioxidant, antitumor and hypoglycemic activities. LRNP possessed the protective effect against oxidative stress. The studies provide a basis for further exploitation of L. robustum.

Radiomics Features on Enhanced Computed Tomography Predict FOXP3 Expression and Clinical Prognosis in Patients with Head and Neck Squamous Cell Carcinoma.

Forkhead box P3 (FOXP3) has been identified as a novel molecular marker in various types of cancer. The present study assessed the expression of FOXP3 in patients with head and neck squamous cell carcinoma (HNSCC) and its potential as a clinical prognostic indicator, and developed a radiomics model based on enhanced computed tomography (CT) imaging. Data from 483 patients with HNSCC were downloaded from the Cancer Genome Atlas for FOXP3 prognostic analysis and enhanced CT images from 139 patients included in the Cancer Imaging Archives, which were subjected to the maximum relevance and minimum redundancy and recursive feature elimination algorithms for radiomics feature extraction and processing. Logistic regression was used to build a model for predicting FOXP3 expression. A prognostic scoring system for radiomics score (RS), FOXP3, and patient clinicopathological factors was established to predict patient survival. The area under the receiver operating characteristic (ROC) curve (AUC) and calibration curve and decision curve analysis (DCA) were used to evaluate model performance. Furthermore, the relationship between FOXP3 and the immune microenvironment, as well as the association between RS and immune checkpoint-related genes, was analyzed. Results of analysis revealed that patients with HNSCC and high FOXP3 mRNA expression exhibited better overall survival. Immune infiltration analysis revealed that FOXP3 had a positive correlation with CD4 + and CD8 + T cells and other immune cells. The 8 best radiomics features were selected to construct the radiomics model. In the FOXP3 expression prediction model, the AUC values were 0.707 and 0.702 for the training and validation sets, respectively. Additionally, the calibration curve and DCA demonstrated the positive diagnostic utility of the model. RS was correlated with immune checkpoint-related genes such as ICOS, CTLA4, and PDCD1. A predictive nomogram was established, the AUCs were 0.87, 0.787, and 0.801 at 12, 24, and 36 months, respectively, and DCA demonstrated the high clinical applicability of the nomogram. The enhanced CT radiomics model can predict expression of FOXP3 and prognosis in patients with HNSCC. As such, FOXP3 may be used as a novel prognostic marker to improve individualized clinical diagnosis and treatment decisions.

Causal associations between schizophrenia and cancers risk: a Mendelian randomization study.

Background: Previous observational studies have reported inconsistent findings regarding the incidence of cancer in patients with schizophrenia compared to the general population. The causal relationship between schizophrenia and cancer remains unclear and requires further investigation. Objective: To investigate the causal relationship between schizophrenia and cancer. Methods: In this study, a two-sample Mendelian randomization (MR) analysis was conducted using publicly available genome-wide association studies to determine the causal relationship. The effect estimates were calculated using the random-effects inverse-variance-weighted method. Results: We determined a causal relationship between genetic predisposition to schizophrenia and cancer, with schizophrenia increasing lung cancer (odds ratio (OR) = 1.0007; 95% confidence interval (CI), 1.0001-1.0013; p = 0.0192), thyroid cancer (OR = 1.5482; CI, 1.1112-2.1569; p =0.0098),colorectal cancer (OR = 1.0009; CI, 1.0001-1.0018; p = 0.0344), ovarian cancer (OR = 1.0770; CI, 1.0352-1.1203; p = 0.0002), breast cancer (OR = 1.0011; CI, 1.0001- 1.0022; p =0.0352) and reduced the risk of malignant neoplasm of the stomach (OR = 0.8502; CI, 0.7230-0.9998; p = 0.0496). Conclusions: This study conducted a two-sample MR analysis and discovered a positive causal relationship between schizophrenia and breast, ovarian, thyroid, lung, and colorectal cancers. On the other hand, an inverse causal relationship was found between schizophrenia and malignant neoplasm of the stomach.

CDCA8 as an independent predictor for a poor prognosis in liver cancer.

BACKGROUND: Human cell division cycle associated 8 (CDCA8) a key regulator of mitosis, has been described as a potential prognostic biomarker for a variety of cancers, such as breast, colon and lung cancers. We aimed to evaluate the potential role of CDCA8 expression in the prognosis of liver cancer by analysing data from The Cancer Genome Atlas (TCGA). METHODS: The Wilcoxon rank-sum test was used to compare the difference in CDCA8 expression between liver cancer tissues and matched normal tissues. Then, we applied logistic regression and the Wilcoxon rank-sum test to identify the association between CDCA8 expression and clinicopathologic characteristics. Cox regression and the Kaplan-Meier method were used to examine the clinicopathologic features correlated with overall survival (OS) in patients from the TCGA. Gene set enrichment analysis (GSEA) was performed to explore possible mechanisms of CDCA8 according to the TCGA dataset. RESULTS: CDCA8 expression was higher in liver cancer tissues than in matched normal tissues. Logistic regression and the Wilcoxon rank-sum test revealed that the increased level of CDCA8 expression in liver cancer tissues was notably related to T stage (OR = 1.64 for T1/2 vs. T3/4), clinical stage (OR = 1.66 for I/II vs. III/IV), histologic grade (OR = 6.71 for G1 vs. G4) and histological type (OR = 0.24 for cholangiocarcinoma [CHOL] vs. hepatocellular carcinoma [LIHC]) (all P-values < 0.05). Kaplan-Meier survival analysis indicated that high CDCA8 expression was related to a poor prognosis in liver cancer (P = 2.456 × 10-6). Univariate analysis showed that high CDCA8 expression was associated with poor OS in liver cancer patients, with a hazard ratio (HR) of 1.85 (95% confidence interval [CI]: 1.47-2.32; P = 1.16 × 10-7). Multivariate analysis showed that CDCA8 expression was independently correlated with OS (HR = 1.74; CI: 1.25-12.64; P = 1.27 × 10-5). GSEA revealed that the apoptosis, cell cycle, ErbB, MAPK, mTOR, Notch, p53 and TGF-ß signaling pathways were differentially enriched in the CDCA8 high expression phenotype. CONCLUSIONS: High CDCA8 expression is a potential molecular predictor of a poor prognosis in liver cancer.

Small nucleolar RNA host gene 22 (SNHG22) promotes the progression of esophageal squamous cell carcinoma by miR-429/SESN3 axis.

BACKGROUND: It has been observed that lncRNAs have been taking part in many cancer progressions, including non-small cell lung cancer and gastric cancer. Meanwhile, lncRNA small nucleolar RNA host gene 22 (SNHG22) has been studied, taking part in the progression of ovarian epithelial carcinoma. However, we know little about the function of SNHG22 in esophageal squamous cell carcinoma (ESCC). METHODS: In this study, we will explore the inner mechanism of SNHG22 in ESCC. Quantitative real-time PCR (qRT-PCR) assay was implemented in ESCC cells for detecting the expression of lncRNA, SNHG22, and miR-429. Also, functional experiments, including CCK8 and colony formation assay, were implemented to assess the growth of ESCC cells. Meanwhile, flow cytometry analysis was conducted to test the apoptosis of ESCC cells. The immunofluorescence (IF) assay and western blot were conducted to verify the autophagy of ESCC cells. RESULTS: Inhibition of SNHG22 was found that can inhibit the progression and promotes autophagy and apoptosis of ESCC cells. Meanwhile, as subcellular fraction assay and FISH assay found that SNHG22 mainly in the cytoplasm, miR-429 was found can bind to SNHG22 and SESN3 by RIP assay and luciferase reporter assay. SESN3 was found it can play the oncogene in ESCC cells. CONCLUSIONS: SNHG22 promotes the progression of ESCC by the miR-429/SESN3 axis.

Correction to: ATF5 involved in radioresistance in nasopharyngeal carcinoma by promoting epithelial-to-mesenchymal phenotype transition.

The article ATF5 involved in radioresistance in nasopharyngeal carcinoma by promoting epithelial-to-mesenchymal phenotype transition, written by Yu Shuai, Erxi Fan, Qiuyue Zhong, Guangyong Feng, Qiying Chen, Xiaoxia Gou, Guihai Zhang, was originally published.

ATF5 involved in radioresistance in nasopharyngeal carcinoma by promoting epithelial-to-mesenchymal phenotype transition.

PURPOSE: This study aimed to investigate the effects of activating transcription factor-5 (ATF5) on nasopharyngeal carcinoma (NPC) cell radioresistance. METHODS: HONE-1 nasopharyngeal carcinoma cells were irradiated by conventional fractionation to generate HONE-1R radiotherapy-resistant cells. Short hairpin RNA (shRNA) expression plasmids targeting the ATF5 gene were constructed and transfected into the HONE-1R cell line. The proliferation assay, colony formation analysis, Transwell Boyden chamber assay and other experimental methods were performed to verify changes in the radiosensitivity and other biological of NPC cells. RESULTS: X-ray irradiation significantly promoted the upregulation of ATF5 protein levels in HONE-1 cells, and the protein expression of ATF5 increased with the dose of X-ray irradiation (p < 0.05). The colony formation rate, cell survival rate and migration ability of HONE-1R cells were significantly higher than those of HONE-1 cells (p < 0.05). Simultaneously, X-ray could also promote the morphology of epithelial-mesenchymal transition (EMT) in HONE-1 cells, inducing a lower expression level of E-cadherin and a higher expression level of N-cadherin in a dose-dependent manner (p < 0.05). Inhibiting ATF5 significantly reduced the colony formation rate, cell survival rate, migration and invasiveness of HONE-1R cells (p < 0.05). Moreover, sensitizing HONE-1R cells to X-ray irradiation significantly upregulated the expression of E-cadherin and downregulated the expression of N-cadherin in these cells (p < 0.05). CONCLUSIONS: ATF5 may be a potential therapeutic target to improve radiosensitivity in NPC.

Five genes as a novel signature for predicting the prognosis of patients with laryngeal cancer.

In this study, we purpose to investigate a novel five-gene signature for predicting the prognosis of patients with laryngeal cancer. The laryngeal cancer datasets were obtained from The Cancer Genome Atlas (TCGA). Both univariate and multivariate Cox regression analysis was applied to screening for prognostic differential expressed genes (DEGs), and a novel gene signature was obtained. The performance of this Cox regression model was tested by receiver operating characteristic (ROC) curves and area under the curve (AUC). Further survival analysis for each of the five genes was carried out through the Kaplan-Meier curve and Log-rank test. Totally, 622 DEGs were screened from the TCGA datasets in this study. We construct a five-gene signature through Cox survival analysis. Patients were divided into low- and high-risk groups depending on the median risk score, and a significant difference of the 5-year overall survival was found between these two groups (P < .05). ROC curves verified that this five-gene signature had good performance to predict the prognosis of laryngeal cancer (AUC = 0.862, P < .05). In conclusion, the five-gene signature consist of EMP1, HOXB9, DPY19L2P1, MMP1, and KLHDC7B might be applied as an independent prognosis predictor of laryngeal cancer.

A gene expression-based study on immune cell subtypes and glioma prognosis.

OBJECT: Glioma is a common malignant tumours in the central nervous system (CNS), that exhibits high morbidity, a low cure rate, and a high recurrence rate. Currently, immune cells are increasingly known to play roles in the suppression of tumourigenesis, progression and tumour growth in many tumours. Therefore, given this increasing evidence, we explored the levels of some immune cell genes for predicting the prognosis of patients with glioma. METHODS: We extracted glioma data from The Cancer Genome Atlas (TCGA). Using the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm, the relative proportions of 22 types of infiltrating immune cells were determined. In addition, the relationships between the scales of some immune cells and sex/age were also calculated by a series of analyses. A P-value was derived for the deconvolution of each sample, providing credibility for the data analysis (P < 0.05). All analyses were conducted using R version 3.5.2. Five-year overall survival (OS) also showed the effectiveness and prognostic value of each proportion of immune cells in glioma; a bar plot, correlation-based heatmap (corheatmap), and heatmap were used to represent the proportions of immune cells in each glioma sample. RESULTS: In total, 703 transcriptomes from a clinical dataset of glioma patients were drawn from the TCGA database. The relative proportions of 22 types of infiltrating immune cells are presented in a bar plot and heatmap. In addition, we identified the levels of immune cells related to prognosis in patients with glioma. Activated dendritic cells (DCs), eosinophils, activated mast cells, monocytes and activated natural killer (NK) cells were positively related to prognosis in the patients with glioma; however, resting NK cells, CD8+ T cells, T follicular helper cells, gamma delta T cells and M0 macrophages were negatively related to prognosis in the patients with glioma. Specifically, the proportions of several immune cells were significantly related to patient age and sex. Furthermore, the level of M0 macrophages was significant in regard to interactions with other immune cells, including monocytes and gamma delta T cells, in glioma tissues through sample data analysis. CONCLUSION: We performed a novel gene expression-based study of the levels of immune cell subtypes and prognosis in glioma, which has potential clinical prognostic value for patients with glioma.

Identification and potential mechanisms of a 4-lncRNA signature that predicts prognosis in patients with laryngeal cancer.

PURPOSE: This study aimed to describe the use of a novel 4-lncRNA signature to predict prognosis in patients with laryngeal cancer and to explore its possible mechanisms. METHODS: We identified lncRNAs that were differentially expressed between 111 tumor tissue samples and 12 matched normal tissue samples from The Cancer Genome Atlas Database (TCGA). We used Cox regression analysis to identify lncRNAs that were correlated with prognosis. A 4-lncRNA signature was developed to predict the prognosis of patients with laryngeal cancer. The receiver operating characteristic (ROC) curves and area under the curve (AUC) were used to verify the validity of this Cox regression model, and an independent prognosis analysis was used to confirm that the 4-lncRNA signature was an independent prognostic factor. Furthermore, the function of these lncRNAs was inferred using related gene prediction and Gene ontology (GO) enrichment analysis in order to clarify the possible mechanisms underlying their predictive ability. RESULTS: In total, 214 differentially expressed lncRNAs were identified, and a 4-lncRNA signature was constructed using Cox survival analysis. The risk coefficients in the multivariate Cox analysis revealed that LINC02154 and MNX1-AS1 are risk factors for laryngeal cancer, whereas MYHAS and LINC01281 appear to be protective factors. The results of a functional annotation analysis suggested that the mechanisms by which these lncRNAs influence prognosis in laryngeal cancer may involve the extracellular exosome, the Notch signaling pathway, voltage-gated calcium channels, and the Wnt signaling pathway. CONCLUSION: We identified a novel 4-lncRNA signature that can predict the prognosis of patients with laryngeal cancer and that may influence the prognosis of laryngeal cancer by regulating immunity, tumor apoptosis, metastasis, invasion, and other characteristics through the Notch signaling pathway, voltage-gated calcium channels, and the Wnt signaling pathway.