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Abstract Background The pregnant women with intrahepatic cholestasis were at high risk of fetal distress, preterm birth and unexpected stillbirth. Intrahepatic cholestasis of pregnancy (ICP) was mainly caused by disorder of bile acid metabolism, whereas the specific mechanism was obscure. Methods We performed proteomics analysis of 10 ICP specimens and 10 placenta specimens from patients without ICP through data-independent acquisition (DIA) technique to disclose differentially expressed proteins. We executed metabolomic analysis of 30 ICP specimens and 30 placenta specimens from patients without ICP through UPLC-MS/MS to identify differentially expressed metabolites. Enrichment and correlation analysis was used to obtain the direct molecular insights of ICP development. The ICP rat models were constructed to validate pathological features. Results The heatmap of proteomics analysis showed the top 30 up-regulated and 30 down-regulated proteins. The metabolomic analysis revealed 20 richer and 4 less abundant metabolites in ICP samples compared with placenta specimens from patients without ICP, and enrichment pathways by these metabolites included primary bile acid biosynthesis, cholesterol metabolism, bile secretion, nicotinate and nicotinamide metabolism, purine metabolism and metabolic pathways. Combined analysis of multiple omics results demonstrated that bile acids such as Glycohyocholic acid, Glycine deoxycholic acid, beta-Muricholic acid, Noncholic acid, cholic acid, Gamma-Mercholic Acid, alpha-Muricholic acid and Glycochenodeoxycholic Aicd were significantly associated with the expression of GLRX3, MYL1, MYH7, PGGT1B, ACTG1, SP3, LACTB2, C2CD5, APBB2, IPO9, MYH2, PPP3CC, PIN1, BLOC1S1, DNAJC7, RASAL2 and ATCN3 etc. The core protein ACAT2 was involved in lipid metabolic process and animal model showed that ACAT2 was up-regulated in placenta and liver of pregnant rats and fetal rats. The neonates had low birth weight and Safranin O-Fast green FCF staining of animal models showed that poor osteogenic and chondrogenic differentiation of fetal rats. Conclusion Multiple metabolites-alpha-Muricholic acid, beta-Muricholic acid, Glycine deoxycholic acid and Glycochenodeoxycholic Acid etc. were perfect biomarkers to predict occurrence of ICP. Bile acids were significantly associated with varieties of protein expression and these proteins were differentially expressed in ICP samples. Our study provided several biomarkers for ICP detection and potential therapeutic targets for ICP development.

Abstract Background To analyze the expression of TXLNA in brain gliomas and its clinical significance. Methods Gene Expression Profiling Interactive Analysis（GEPIA）and Chinese Glioma Genome Atlas（CGGA）databases were retrieved as the methods. To assess the disparity between TXLNA expression in glioma and normal brain tissue. The Kaplan-Meier survival curve was employed to preliminarily evaluate the survival curves of the high and low expression groups, this was done for investigate the correlation between TXLNA expression level and the survival and prognosis of glioma. A Cox proportional regression risk model of multivariate nature was employed to evaluate the elements impacting the survival and prognosis of glioma. Gene pool enrichment analysis（GSEA）was used to investigate the related function of TXLNA in glioma. A Pearson correlation test and co-expression analysis were employed to identify the genes most associated with TXLNA expression. Result The enrichment analysis results were observably enriched in signal pathways for instance the cell cycle and completion and coordination cascade pathways, and it is evident that high expression of TXLNA in gliomas is related to a poor survival and a bad patient prognosis, thus making it an independent prognostic factor for gliomas. Genes such as STK40 and R1MS1 are significantly correlated with TXLNA, playing a synergistic or antagonistic role. Conclusions The prognosis of GBM patients is strongly linked to the high expression of TXLNA, which may be a viable therapeutic target for curbing cancer progression and creating new immunotherapies for GBM.

Abstract Background Low-grade gliomas (LGG) are WHO grade II tumors presenting as the most common primary malignant brain tumors in adults. Currently, LGG treatment involves either or a combination of surgery, radiation therapy, and chemotherapy. Despite the knowledge of constitutive genetic risk factors contributing to gliomas, the role of single genes as diagnostic and prognostic biomarkers is limited. The aim of the current study is to discover the predictive and prognostic genetic markers for LGG. Methods Transcriptome data and clinical data were obtained from The Cancer Genome Atlas (TCGA) database. We first performed the tumor microenvironment (TME) survival analysis using the Kaplan-Meier method. An analysis was undertaken to screen for differentially expressed genes. The function of these genes was studied by Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Following which a protein-protein interaction network (PPI) was constructed and visualized. Univariate and multivariate COX analyses were performed to obtain the probable prognostic genes. The key genes were selected by an intersection of core and prognostic genes. A clinical correlation analysis of single-gene expression was undertaken. GSEA enrichment analysis was performed to identify the function of key genes. Finally, a single gene-related correlation analysis was performed to identify the core immune cells involved in the development of LGG. Results A total of 529 transcriptome data and 515 clinical samples were obtained from the TCGA. Immune cells and stromal cells were found to be significantly increased in the LGG microenvironment. The top five core genes intersected with the top 38 prognostically relevant genes and two key genes were identified. Our analysis revealed that a high expression of HLA-DRA was associated with a poor prognosis of LGG. Correlation analysis of immune cells showed that HLA-DRA expression level was related to immune infiltration, positively related to macrophage M1 phenotype, and negatively related to activation of NK cells. Conclusions HLA-DRA may be an independent prognostic indicator and an important biomarker for diagnosing and predicting survival in LGG patients. It may also be associated with the immune infiltration phenotype in LGG.

Abstract Glioblastoma is the most common form of primary brain tumor. Glioblastoma stem cells play an important role in tumor formation by activation of several signaling pathways. Wnt signaling pathway is one such important pathway which helps cellular differentiation to promote tumor formation in the brain. Glioblastoma remains to be a highly destructive type of tumor despite availability of treatment strategies like surgery, chemotherapy, and radiation. Advances in the field of cancer biology have revolutionized therapy by allowing targeting of tumor-specific molecular deregulation. In this review, we discuss about the significance of glioblastoma stem cells in cancer progression through Wnt signaling pathway and highlight the clinical targets being potentially considered for therapy in glioblastoma.

Abstract Pancreatic cancer (PC) is one of the leading causes of cancer-related deaths worldwide. Due to the shortage of effective biomarkers for predicting survival and diagnosing PC, the underlying mechanism is still intensively investigated but poorly understood. Long noncoding RNAs (lncRNAs) provide biological functional diversity and complexity in protein regulatory networks. Scientific studies have revealed the emerging functions and regulatory roles of lncRNAs in PC behaviors. It is worth noting that some in-depth studies have revealed that lncRNAs are significantly associated with the initiation and progression of PC. As lncRNAs have good properties for both diagnostic and prognostic prediction due to their translation potential, we herein address the current understanding of the multifaceted roles of lncRNAs as regulators in the molecular mechanism of PC. We also discuss the possibility of using lncRNAs as survival biomarkers and their contributions to the development of targeted therapies based on the literature. The present review, based on what we know about current research findings, may help us better understand the roles of lncRNAs in PC.

Abstract Background SOX11 is a transcription factor that plays an important role in mantle cell lymphoma development. However, its functional role in head and neck squamous cell carcinoma (HNSCC) remains unknown. Methods Protein expression was measured with Western blotting, immunohistochemistry or quantitative proteomics, and gene expression was measured with quantitative RT-PCR. Functional role of SOX11 in HNSCC was evaluated with MTS/apoptosis, migration, invasion assays and a xenograft model. A SOX11-targeting gene, SDCCAG8, was confirmed with chromatin immunoprecipitation (ChIP), luciferase reporter and rescue assays. Results SOX11 was up-regulated in recurrent versus primary HNSCC and in highly invasive versus low invasive HNSCC cell lines. Silencing SOX11 in HNSCC cell lines significantly inhibited the cell proliferation, migration, invasion and resistance to Cisplatin, and vice versa. Quantitative proteomic analysis of SOX11-silencing HNSCC cells revealed a number of differentially expressed proteins, including a down-regulated tumor antigen SDCCAG8. Silencing of SDCCAG8 in HNSCC cells also significantly inhibited the cell proliferation, migration and invasion, and vice versa. ChIP assays demonstrated that endogenous SOX11 strongly bound to Sdccag8 gene promoter in highly invasive HNSCC cells. When over-expressed in low invasive HNSCC cells, wild type SOX11 but not mutant SOX11 induced the promoter activity of Sdccag8 and significantly induced the expression of SDCCAG8. However, exogenous mutant SOX11 abolished the expression of SDCCAG8 in highly invasive HNSCC cells. In addition, the inhibitory effects of SOX11 knockdown were partially rescued by over-expression of SDCCAG8 in HNSCC cells. Conclusion Collectively, our findings indicate SOX11 promotes HNSCC progression via the regulation of SDCCAG8.