Developmental co-exposure of TBBPA and titanium dioxide nanoparticle induced behavioral deficits in larval zebrafish.

Both tetrabromobisphenol A (TBBPA) and titanium dioxide nanoparticle (TiO2 NP) have widespread commercial applications, resulting in their ubiquitous co-presence in the environment and biota. Although environmental chemicals exist as mixtures, toxicity studies are nearly always conducted with single chemicals. Few studies explore potential interactions of different chemical mixtures. In this study, we employ the sensitive developing nerve system in zebrafish to assess the neurotoxicity of TBBPA/TiO2 NP mixtures. Specifically, zebrafish embryos were exposed to solvent control (0.1% DMSO), 2 µM TBBPA, 0.1 mg/L TiO2 NP, and their mixture from 8 to 120 h post fertilization (hpf), and motor/social behavioral assessments were conducted on embryos/larvae at different developmental stages. Our results showed that TBBPA/TiO2 NP single or co-exposures increased spontaneous movement, decreased touch response and swim speed, and affected social behaviors of light/dark preference, shoaling, mirror attack and social contact. In particular, many of these phenotypes were manifested with higher magnitude of changes from the mixture exposure. These behavioral deficits were also accompanied with increased cell death in olfactory region and neuromasts in the lateral line system, increased ROS in gallbladder, pancreas, liver, and intestine, as well as increased lipid peroxidation and decreased ATP levels in whole larval tissue homogenates. Further, genes coding for key cell apoptosis marker and antioxidant enzyme were significantly upregulated by these two chemicals, in particular to their mixture. Interestingly, the co-presence of TBBPA also increased the mean particle size of TiO2 NP in the exposure solutions and the TiO2 NP content in larval tissue. Together, our analysis suggests that TBBPA/TiO2 NP induced behavioral changes may be due to physical accumulation of these two chemicals in the target organs, and TiO2 NP may serve as carriers for increased accumulation of TBBPA. To conclude, we demonstrated that TBBPA/TiO2 NP together cause increased bioaccumulation of TiO2, and heightened responses in behavior, cell apoptosis and oxidative stress. Our findings also highlight the importance of toxicity assessment using chemical mixtures.

Analysis of clinical significance and molecular characteristics of methionine metabolism and macrophage-related patterns in hepatocellular carcinoma based on machine learning.

BACKGROUND: Increasing evidence has indicated that abnormal methionine metabolic activity and tumour-associated macrophage infiltration are correlated with hepatocarcinogenesis. However, the relationship between methionine metabolic activity and tumour-associated macrophage infiltration is unclear in hepatocellular carcinoma, and it contributes to the occurrence and clinical outcome of hepatocellular carcinoma (HCC). Thus, we systematically analysed the expression patterns of methionine metabolism and macrophage infiltration in hepatocellular carcinoma using bioinformatics and machine learning methods and constructed novel diagnostic and prognostic models of HCC. METHODS: In this study, we first mined the four largest HCC mRNA microarray datasets with patient clinical data in the GEO database, including 880 tissue mRNA expression datasets. Using GSVA analysis and the CIBERSORT and EPIC algorithms, we quantified the methionine metabolic activity and macrophage infiltration degree of each sample. WGCNA was used to identify the gene modules most related to methionine metabolism and tumour-associated macrophage infiltration in HCC. The KNN algorithm was used to cluster gene expression patterns in HCC. Random forest, logistic regression, Cox regression analysis and other algorithms were used to construct the diagnosis and prognosis model of HCC. The above bioinformatics analysis results were also verified by independent datasets (TCGA-LIHC, ICGC-JP and CPTAC datasets) and immunohistochemical fluorescence based on our external HCC panel. Furthermore, we carried out pancancer analysis to verify the specificity of the above model and screened a wide range of drug candidates. RESULTS: We identified two methionine metabolism and macrophage infiltration expression patterns, and their prognoses were different in hepatocellular carcinoma. We constructed novel diagnostic and prognostic models of hepatocellular carcinoma with good diagnostic efficacy and differentiation ability. CONCLUSIONS: Methionine metabolism is closely related to tumour-associated macrophage infiltration in hepatocellular carcinoma and can help in the clinical diagnosis and prognosis of HCC.

Construction and validation of a prediction model of extrahepatic metastasis for hepatocellular carcinoma based on common clinically available data.

Objective: This study aimed to investigate the clinical characteristics and risk factors of patients with hepatocellular carcinoma (HCC) with extrahepatic metastases (EHM) and to establish an effective predictive nomogram. Methods: Clinical and pathological data from 607 patients with hepatocellular carcinoma admitted to the Affiliated Hospital of Qinghai University between 1 January 2015 and 31 May 2018 were documented, as well as demographics, clinical pathological characteristics, and tumor-related parameters to clarify clinical risk factors for HCC EHM. These risks were selected to build an R-based clinical prediction model. The predictive accuracy and discriminating ability of the model were determined by the concordance index (C-index) and the calibration curve. The results were validated with a bootstrap resample and 151 patients from 1 June 2018 to 31 December 2019 at the same facility. Results: In multivariate analysis, independent factors for EHM were neutrophils, prothrombin time, tumor number, and size, all of which were selected in the model. The C-index in the EHM prediction model was 0.672 and in the validation cohort was 0.694. In the training cohort and the validation cohort, the calibration curve for the probability of EHM showed good agreement between the nomogram prediction and the actual observation. Conclusion: The extrahepatic metastasis prediction model of hepatocellular carcinoma constructed in this study has some evaluation capability.

Identification of Biomarkers Related to Atrial Fibrillation With Mitral Regurgitation.

BACKGROUND: We aimed to explore the biomarkers associated with atrial fibrillation (AF) with mitral regurgitation (MR). METHODS: The gene expression profile data GSE115574 were downloaded from Gene Expression Omnibus database, which were obtained from patients with degenerative MR with AF and sinus rhythm (SR). The differentially expressed genes (DEGs) in samples of AF with MR compared with those of SR with MR were selected, followed by functional enrichment analysis, protein-protein interaction (PPI) network analysis, transcription factor (TF) prediction, and drug-gene interaction prediction. RESULTS: By comparing the genes' expression profiles between AF with MR and SR with MR, 379 DEGs were obtained. The upregulated genes, such as NMNAT2, LDHB, and hexosaminidase subunit beta (HEXB), were significantly enriched in metabolic pathways. Hub genes, such as amyloid beta precursor protein (APP), CDH2, SPP1, and STC2, were significantly associated with functions related to extracellular matrix organization and vitamin D response. Additionally, two TFs, PRDM3 and LSM6, were predicted for the key module genes. APP predicted the most drug molecules, that is, 22 molecules, and SPP1 predicted 10 drug molecules. CONCLUSIONS: Dysregulation of the metabolic pathway may play a critical role in AF with MR. Changes in functions related to the extracellular matrix and vitamin D response may also be associated with AF progression in patients with MR. Furthermore, APP, STC2, and SPP1 may serve as potential therapeutic targets of AF.

Metabolism-Relevant Molecular Classification Identifies Tumor Immune Microenvironment Characterization and Immunotherapeutic Effect in Cervical Cancer.

Cervical cancer (CESC) is a gynecologic malignant tumor associated with high incidence and mortality rates because of its distinctive management complexity. Herein, we characterized the molecular features of CESC based on the metabolic gene expression profile by establishing a novel classification system and a scoring system termed as METAscore. Integrative analysis was performed on human CESC samples from TCGA dataset. Unsupervised clustering of RNA sequencing data on 2,752 formerly described metabolic genes identified three METAclusters. These METAclusters for overall survival time, immune characteristics, metabolic features, transcriptome features, and immunotherapeutic effectiveness existed distinct differences. Then we analyzed 207 DEGs among the three METAclusters and as well identified three geneclusters. Correspondingly, these three geneclusters also differently expressed among the aforementioned features, supporting the reliability of the metabolism-relevant molecular classification. Finally METAscore was constructed which emerged as an independent prognostic biomarker, related to CESC transcriptome features, metabolic features, immune characteristics, and linked to the sensitivity of immunotherapy for individual patient. These findings depicted a new classification and a scoring system in CESC based on the metabolic pattern, thereby furthering the understanding of CESC genetic signatures and aiding in the prediction of the effectiveness to anticancer immunotherapies.

Characterization of murine mammary stem/progenitor cells in a D-galactose-induced aging model.

Aging plays an important role in many diseases, including breast cancer. Aged mammary stem/progenitor cells are perceived to be the cells of origin in breast tumorigenesis; however, the extensive use of mice who have aged naturally for research is hampered by cost, time, disease complications, and high mortality. In this study, we characterized murine mammary stem/progenitor cells in a D-galactose-induced accelerated aging model and compared them with findings from our earlier study on mice from natural aging. Our results showed that mammary glands in the D-galactose-induced aging model mimic natural aging in terms of pathological changes, epithelial cell composition, and mammary stem/progenitor cell function. These changes are accompanied by elevated inflammatory responses both systemically in the blood and locally in the mammary glands, which is similar in mice who age naturally. Our study for the first time evaluated the mammary glands and mammary stem/progenitor function in a D-galactose-induced aging model in rodents, and our findings suggest that D-galactose treatment can be used as a surrogate to study the role aged stem/progenitor cells play in breast tumorigenesis.

MT1JP-mediated miR-24-3p/BCL2L2 axis promotes Lenvatinib resistance in hepatocellular carcinoma cells by inhibiting apoptosis.

PURPOSE: Lenvatinib is a long-awaited alternative to Sorafenib for first-line targeted therapy of patients with advanced hepatocellular carcinoma (HCC). However, resistance to Lenvatinib results in tumor progression and has become a major obstacle to improving the prognosis of HCC patients. Exploring the mechanisms underlying Lenvatinib resistance is considered essential for the treatment of advanced HCC. METHODS: Lenvatinib resistant HCC (LR-HCC) cells were generated and potential long non-coding RNAs (Lnc-RNAs) upregulated in LR-HCC cells were identified by RNA sequencing. The effects of upregulated Lnc-RNAs were evaluated in vitro in cell models and in vivo in experimental animals using quantitative cell viability and apoptosis assays. RESULTS: We found that Lnc-RNA MT1JP (MT1JP) was upregulated in LR-HCC cells and inhibited the apoptosis signaling pathway. In addition, we found that sponging of microRNA-24-3p by MT1JP released Bcl-2 like 2 (BCL2L2), an anti-apoptotic protein, thereby forming a positive-feedback loop. The role of this feedback loop was validated using rescue assays. Additionally, we found that upregulation of MT1JP and BCL2L2 impaired the sensitivity of HCC cells to Lenvatinib both vitro and vivo. CONCLUSIONS: Our results suggest a novel molecular feedback loop between MT1JP and apoptosis signaling in Lenvatinib sensitive HCC cells.