The influences of extraction methods on the chemical constituents of Lyonia ovalifolia (wall.) Drude and intracellular protective effects based on metabolomics analysis.

Lyonia ovalifolia (Wall.) Drude (LO) is mainly distributed in China with health benefits. In this study, LO buds (LOB) were extracted by ultrasonic extraction (UE) with or without ultra-high-pressure (UHP-UE), microwave (MW-UE), subcritical (SC-UE) techniques. The metabolomic result showed that a total of 960 chemical compounds and 117 differential compounds were identified from LOB extracts. The UHP-UE extract was rich in total polyphenol and flavonoid contents, followed by MW-UE, UE and SC-UE extracts, respectively. All LOB extracts increased superoxide dismutase (SOD) and catalase (CAT) activities, and glutathione (GSH) content, decreased reactive oxygen species (ROS) accumulation, levels of interleukin-6 (IL-6), interleukin-1ß (IL-1ß), tumor necrosis factor -α (TNF-α), and nitric oxide (NO), and alleviated apoptosis in cells. The cellular protective effect was UHP-UE > MW-UE > UE > SC-UE. This study revealed that higher pressure and lower temperature may be key factors for increasing bioactivities of LOB extracts.

Protective effect of hot-water and ethanol-aqueous extracts from Anneslea fragrans against acetaminophen-induced acute liver injury in mice.

Anneslea fragrans Wall. (AF) is an important medicinal and edible plant in China. The principal objectives of this study are to explore the hepatoprotective effect of ethanol-aqueous (AFE) and hot-water (AFW) extracts in vitro and in vivo. UPLC-ESI-MS/MS analysis showed that AFW and AFE are rich in dihydrochalcones. Both AFW and AFE significantly up-regulated the expressions of SOD, CAT and GSH, reduced the MDA content in acetaminophen (APAP)-induced HepG2 cells, and suppressed the expressions of NO, TNF-α, IL-1ß, and IL-6 in LPS-induced RAW246.7 cells. In APAP-induced mice, AFW and AFE administration significantly decreased the plasma levels of AST and ALT, and improved liver tissue damage, the collagen deposition and fibrosis formation. Moreover, AFW and AFE decreased the MDA and ROS accumulations via activating Nrf2 pathway to increase the hepatic GSH contents and activities of SOD, CAT, HO-1, and NQO-1, reduced the levels of NO, TNF-α, IL-1ß, and IL-6 by suppressing the JNK/p38/ERK/NF-κB pathways, and alleviated apoptosis via regulating Bcl-2, Bax, caspase-3/9 protein expressions. This study provides a new sight that AFW and AFE may have a potential natural resource for the treatment of liver injury.

DNA adduct formation and reduced EIF4A3expression contributes to benzo[a]pyrene-induced DNA damage in human bronchial epithelial BEAS-2B cells.

Benzo[a]pyrene(B[a]P) is a known human carcinogen. The ability of B[a]P to form stable DNA adducts has been repeatedly demonstrated. However, the relationship between DNA adduct formation and cell damage and its underlying molecular mechanisms are less well understood. In this study, we determined the cytotoxicity of benzo[a]pyrenediolepoxide, a metabolite of B[a]P, in human bronchial epithelial cells (BEAS-2B). The formation of BPDE-DNA adducts was quantified using a dot blot. DNA damage resulting from the formation of BPDE-DNA adducts was detected by chromatin immuneprecipitation sequencing (ChIP-Seq), with minor modifications, using specific antibodies against BPDE. In total, 1846 differentially expressed gene loci were detected between the treatment and control groups. The distribution of the BPDE-bound regions indicated that BPDE could covalently bind with both coding and non-coding regions to cause DNA damage. However, the majority of binding occurred at protein-coding genes. Furthermore, among the BPDE-bound genes, we found 16 protein-coding genes related to DNA damage repair. We explored the response to BPDE exposure at the transcriptional level using qRT-PCR and observed a strong inhibition of EIF4A3. We then established an EIF4A3 overexpression cell model and performed comet assays, which revealed that the levels of DNA damage in EIF4A3-overexpressing cells were lower than those in normal cells following BPDE exposure. This suggests that the BPDE-DNA adduct-induced reduction in EIF4A3 expression contributed to the DNA damage induced by BPDE exposure in BEAS-2B cells. These novel findings indicate that ChIP-Seq combined with BPDE specific antibody may be used for exploring the underlying mechanism of DNA adduct-induced genomic damage.

Exploration of the Associations of lncRNA Expression Patterns with Tumor Mutation Burden and Prognosis in Colon Cancer.

BACKGROUND: Tumor mutation burden (TMB) is emerging as a new biomarker to monitor the response of cancer patients to immunotherapy. Long non-coding RNAs (lncRNAs) are critical in regulating gene expression and play a significant role in cancer-associated immune responses. However, the association between lncRNA expression patterns and TMB levels and survival outcomes remains unknown in colon cancer. METHODS: In colon cancer patients from The Cancer Genome Atlas Program (TCGA), a multi-lncRNAs based classifier for predicting TMB levels was established using the least absolute shrinkage and selection operator (LASSO) method. The association between classifier index and immune-related characteristics of patients was also investigated. Quantitative polymerase chain reaction (qPCR) was used to verify the expression levels of these lncRNAs in normal and CRC cell lines. RESULTS: The multi-lncRNAs based classifier had ability to predict TMB level of patients with accuracy (AUC= 0.70), and the general applicability of this classifier was proved in the validation set (AUC= 0.71) and the pooled set (AUC= 0.70). The classifier index was related to three immune checkpoints (PD1, PD-L1, and CTLA-4), the infiltration level of immune cells, and immune response-related score (IFN-γ score, gene expression profiles (GEP) score, cytolytic activity (CYT) score and MHC score). A nomogram, which integrates classifier and some common clinical information, was able to predict the overall survival of colon cancer patients accurately. CONCLUSION: LncRNA expression patterns are associated with TMB, which may serve as a classifier to predict the TMB in colon cancer patients. The nomogram could potentially evaluate survival outcomes and provide a reference to better manage colon cancer patients.

Antioxidant and Cytoprotective Effects of New Diarylheptanoids from Rhynchanthus beesianus.

Rhynchanthus beesianus (Zingiberaceae) has been an important food spice and vegetable in southern China. Fifteen phenolic compounds (1-15) including three new diarylheptanoids, rhynchanines A-C (1-3) and one new phenylpropanoid, 4-O-methylstroside B (9), were isolated from R. beesianus rhizomes. The structures of new compounds were elucidated by comprehensive analyses through NMR, HRMS technique, acid hydrolysis, and Mosher's reaction. Among them, compound 5 is the first isolated natural product and its NMR data are reported. Most of the isolated compounds, especially 3-6 and 8, showed significant antioxidant activities on DPPH, ABTS+ radical scavenging, and FRAP assays. Furthermore, the antioxidant phenolic compounds were evaluated for their cytoprotective capacity against H2O2-induced oxidative stress in HepG-2 cells. Compounds 3 and 5 could significantly inhibit reactive oxygen species production, and compounds 3, 5, and 6 could remarkably prevent the cell apoptosis. Then, the R. beesianus rhizome, which contained phenolic compounds, might serve as a functional food for potential application on preventing oxidative stress-connected diseases.

A genome-wide screen for differentially methylated long noncoding RNAs identified that lncAC007255.8 is regulated by promoter DNA methylation in Beas-2B cells malignantly transformed by NNK.

Tobacco exposure is well known to induce genetic and epigenetic changes that contribute to the pathogenesis of lung cancer. 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) is a significant tobacco-specific carcinogen, but the oncogenic mechanisms of NNK have not been thoroughly elucidated. In this study we found that DNA methyltransferase 1 (DNMT1) was overexpressed in malignantly transformed human bronchial epithelial Beas-2B cells induced by NNK (2B-NNK cells), by treatment with NNK (400 µg/mL) for 7 days. An Arraystar Human noncoding RNA Promoter Microarray was used to detect the DNA methylation status of the promoter region of long noncoding RNAs (lncRNAs). The result showed that 1010 differentially methylated fragments were present in the lncRNA promoter region. QRT-PCR revealed that the expression of lncRNA AC007255.8 was remarkably downregulated in 2B-NNK cells and lung cancer tissues. Furthermore, Methylation-specific PCR showed that the methylation of the lncRNA AC007255.8 promoter was increased in 2B-NNK cells and lung cancer tissues. The reduced expression of lncRNA AC007255.8 was significantly associated with hypermethylation of lncRNA AC007255.8 promoter region. LncRNA AC007255.8 overexpression could result in decreased cell proliferation and increased cell apoptosis in 2B-NNK cells. In conclusion, NNK induced lncRNA AC007255.8 promoter hypermethylation via upregulation of DNMT1 in Beas-2B cells, leading to downregulation of lncRNA AC007255.8, and ultimately the enhancement of cell proliferation and the inhibition of apoptosis. This research affords novel insights into the epigenetic mechanisms of lung cancer, and will stimulate further research into the involvement of aberrant DNA methylation of non-coding regions of the genome in the pathogenesis of lung cancer.

Characterization of the fatty acid metabolism in colorectal cancer to guide clinical therapy.

Colorectal cancer (CRC) is one of the most common malignant tumors, with the second-highest mortality of all 36 cancers worldwide. The roles of fatty acid metabolism in CRC were investigated to explore potential therapeutic strategies. The data files were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were used to construct a prognostic risk score model with fatty acid metabolism-related genes for predicting prognosis in CRC. Patients with a high-risk score had a poorer prognosis in TCGA cohort than those with a low-risk score and were confirmed in the GEO cohort. Further analysis using the "pRRophetic" R package revealed that low-risk patients were more sensitive to 5-fluorouracil. A comprehensive evaluation of the association between prognostic risk score model and tumor microenvironment (TME) characteristics showed that high-risk patients were suitable for activating a type I/II interferon (IFN) response and inflammation-promoting function. Tumor Immune Dysfunction and Exclusion (TIDE) and SubMap algorithm results also demonstrated that high-risk patients are more suitable for anti-CTLA4 immunotherapy. Therefore, the evaluation of the fatty acid metabolism pattern promotes our comprehension of TME infiltration characteristics, thus guiding effective immunotherapy regimens.

Fine particulate matter exposure induces DNA damage by downregulating Rad51 expression in human bronchial epithelial Beas-2B cells in vitro.

Although an accumulating body of evidence suggests that fine particulate matter (PM2.5) can cause lung injury and lung cancer, the underlying mechanisms are not yet clear. In this study, multiple endpoints associated with the cellular response to PM2.5 exposure, including the cell proliferation rate, cell apoptosis, malondialdehyde (MDA) content and DNA damage, were evaluated in human bronchial epithelial Beas-2B cells. The mRNA expression profile in PM2.5-treated cells was analyzed by transcriptome sequencing. The DNA repair gene Rad51 was then selected for further analysis. We found that the viability and growth of Beas-2B cells decreased while cell apoptosis increased in a dose-dependent manner after PM2.5 exposure. The comet assay showed that PM2.5 exposure induced evident DNA damage in PM2.5-treated cells. The MDA content in the treated cells was increased, indicating that PM2.5 exposure promoted lipid peroxidation. Furthermore, Rad51 expression was downregulated in PM2.5-treated cells, which may have contributed to the PM2.5-induced DNA damage in Beas-2B cells. Upregulation of Rad51 expression could rescue the negative impact of PM2.5 exposure in Beas-2B cells. Taken together, our research demonstrates that PM2.5 exposure induces DNA damage and impairs the DNA repair process by downregulating Rad51 expression in Beas-2B cells. This finding is expected to provide new insight into the genotoxicity of PM2.5 exposure.

Machine learning-based radiomics analysis in predicting the meningioma grade using multiparametric MRI.

PURPOSE: To investigate the prediction performance of radiomic models based on multiparametric MRI in predicting the meningioma grade. METHOD: In all, 229 low-grade [Grade I] and 87 high-grade [Grade II/III] patients with pathologically diagnosed meningiomas were enrolled. Radiomic features from conventional MRI (cMRI), ADC maps and SWI were extracted based on the volume of entire tumor. Classification performance of different radiomic models (cMRI, ADC, SWI, cMRI + ADC, cMRI + SWI, ADC + SWI, and cMRI + ADC + SWI models) was evaluated by a nested LOOCV approach, combining the LASSO feature selection and RF classifier that was trained (1) without subsampling, and (2) with the synthetic minority over-sampling technique (SMOTE). The prediction performance of radiomic models was assessed using ROC curve and AUC of them was compared using Delong's test. RESULTS: The cMRI + ADC + SWI model demonstrated the best performance without or with subsampling, which AUCs were 0.84 and 0.81, respectively. Following the cMRI + ADC + SWI model, the AUC range of the other models was 0.75-0.80 without subsampling, and was 0.71-0.79 with subsampling. Although the cMRI + ADC model and cMRI + SWI model showed higher AUCs than the cMRI model without subsampling (0.77 vs 0.80, P = 0.037 and 0.77 vs 0.80, P = 0.009, respectively), there was no significant difference among these models with subsampling (0.78 vs 0.77, P = 0.552 and 0.78 vs 0.79, P = 0.246, respectively). CONCLUSIONS: Multiparametric radiomic model based on cMRI, ADC map and SWI yielded the best prediction performance in predicting the meningioma grade, which might offer potential guidance in clinical decision-making.

Machine-learning-based computed tomography radiomic analysis for histologic subtype classification of thymic epithelial tumours.

PURPOSE: To evaluate the performance of machine-learning-based computed tomography (CT) radiomic analysis to differentiate high-risk thymic epithelial tumours (TETs) from low-risk TETs according to the WHO classification. METHOD: This retrospective study included 155 patients with a histologic diagnosis of high-risk TET (n = 72) and low-risk TET (n = 83) who underwent unenhanced CT (UECT) and contrast-enhanced CT (CECT). The radiomic features were extracted from the UECT and CECT of each patient at the largest cross-section of the lesion. The classification performance was evaluated with a nested leave-one-out cross-validation approach combining the least absolute shrinkage and selection operator feature selection and four classifiers: generalised linear model (GLM), k-nearest neighbor (KNN), support vector machine (SVM) and random forest (RF). The receiver-operating characteristic curve (ROC) and the area under the curve (AUC) were used to evaluate the performance of the classifiers. RESULTS: The combination of UECT and CECT radiomic features demonstrated the best performance to differentiate high-risk TETs from low-risk TETs for all four classifiers. Among these classifiers, the RF had the highest AUC of 0.87, followed by GLM (AUC = 0.86), KNN (AUC = 0.86) and SVM (AUC = 0.84). CONCLUSIONS: Machine learning-based CT radiomic analysis allows for the differentiation of high-risk TETs and low-risk TETs with excellent performance, representing a promising tool to assist clinical decision making in patients with TETs.

High expression of Ras-related protein 1A promotes an aggressive phenotype in colorectal cancer via PTEN/FOXO3/CCND1 pathway.

BACKGROUND: Colorectal cancer (CRC) is a commonly diagnosed digestive malignancy worldwide. Ras-related protein 1A (RAP1A) is a member of the Ras superfamily of small GTPases and has been recently identified as a novel oncoprotein in several human malignancies. However, its specific role in CRC remains unclear. METHOD: In this study, we firstly analyzed its expression and clinical significance in a retrospective cohort of 144 CRC patients. Then, cellular assays in vitro and in vivo were performed to clarify its biological role in CRC cells. Finally, microarray analysis was utilized to investigate the molecular mechanisms regulated by RAP1A in CRC progression. RESULTS: Firstly, RAP1A expression was abnormally higher in CRC tissues as compared with adjacent normal tissues, and significantly correlated tumor invasion. High RAP1A expression was an independent unfavourable prognostic factor for CRC patients. Combining RAP1A expression and preoperative CEA level contributed to a more accurate prognostic stratification in CRC patients. Secondly, knockdown of RAP1A dramatically inhibited the growth of CRC cells, while it was opposite for RAP1A overexpression. Finally, the microarray analysis revealed RAP1A promoted CRC growth partly through phosphatase and tensin homolog (PTEN)/forkhead box O3(FOXO3)/cyclin D1(CCND1) signaling pathway. FOXO3 overexpression could partly mimic the inhibitory effect of RAP1A knockdown in CRC growth. Moreover, FOXO3 overexpression inhibited CCND1 expression, but had no impact on RAP1A and PTEN expression. CONCLUSION: RAP1A promotes CRC development partly through PTEN/FOXO3 /CCND1 signaling pathway. It has a great potential to be an effective clinical biomarker and therapeutic target for CRC patients.

Silencing of lncRNA AFAP1-AS1 suppressed lung cancer development by regulatory mechanism in cis and trans.

Although the long noncoding RNA AFAP1-AS1 has been shown to be involved in various types of cancer, its involvement in lung cancer remains poorly understood. In the current study, we found that AFAP1-AS1 was substantially over expressed in lung cancer tissues and cell lines. In addition, AFAP1-AS1 expression level was proven to be associated with the malignant features of lung cancer. Knockdown of AFAP1-AS1 significantly suppressed cell proliferation by increasing cell apoptosis and G0/G1 phase retardation of cell cycle in lung cancer cells. Furthermore, AFAP1-AS1 knockdown could suppress tumor growth of lung cancer in BALB/c nude mice. We also identified that AFAP1-AS1 silencing could influence the expression of AFAP1 and KRT1 on mRNA and protein level by cis and trans regulatory mechanism. Moreover, the oncogenic activities of AFAP1-AS1 on cell proliferation are partially mediated by KRT1. In summary, these findings demonstrate that AFAP1-AS1 plays an essential role in promoting lung cancer development in vitro and vivo. It indicated that AFAP1-AS1 is a promising prognostic predictor for patients with lung cancer.