Background The relationship between pancreatic cancer (PC) and type 2 diabetes mellitus (T2DM) has long been widely recognized, but the interaction mechanisms are still unknown. This study was aimed to investigate the shared gene signatures and molecular processes between PC and T2DM. Methods The Gene Expression Omnibus (GEO) database was used to retrieve the RNA sequence and patient information of PC and T2DM. Weighted gene co-expression network analysis (WGCNA) was performed to discover a co-expression network associated with PC and T2DM. Enrichment analysis of shared genes present in PC and T2DM was performed by ClueGO software. These results were validated in the other four cohorts based on differential gene analysis. The predictive significance of S100A6 in PC was evaluated using univariate and multivariate Cox analyses, as well as Kaplan–Meier plots. The biological process of S100A6 enrichment in PC was detected using Gene Set Enrichment Analysis (GSEA). The involvement of S100A6 in the tumor immune microenvironment (TIME) was assessed by CIBERSORT. In vitro assays were used to further confirm the function of S100A6 in PC. Results WGCNA recognized three major modules for T2DM and two major modules for PC. There were 44 shared genes identified for PC and T2DM, and Gene Ontology (GO) analysis showed that regulation of endodermal cell fate specification was primarily enriched. In addition, a key shared gene S100A6 was derived in the validation tests. S100A6 was shown to be highly expressed in PC compared to non-tumor tissues. PC patients with high S100A6 expression had worse overall survival (OS) than those with low expression. GSEA revealed that S100A6 is involved in cancer-related pathways and glycometabolism-related pathways. There is a strong relationship between S100A6 and TIME. In vitro functional assays showed that S100A6 helped to induce the PC cells’ proliferation and migration. We also proposed a diagram of common mechanisms of PC and T2DM. Conclusions This study firstly revealed that the regulation of endodermal cell fate specification may be common pathogenesis of PC and T2DM and identified S100A6 as a possible biomarker and therapeutic target for PC and T2DM patients.
Abstract Background: Epithelial ovarian cancer (EOC), and other solid tumors, contain a variable proportion of tumors characterized by global DNA hypomethylation. This phenotype is known to involve loss of DNA methylation at repetitive elements (RE) and at single copy gene promoters, including cancer-germline (a.k.a. cancer-testis) antigen genes. Global DNA hypomethylation in EOC coincides with tumor progression and reduced survival in EOC patients. Despite the clinical importance of global DNA hypomethylation, we currently have a limited understanding of the origin, the targets, and the consequences of this EOC phenotype. Objectives: The purpose of this study was to: i) examine global gene expression in globally hypomethylated EOC, ii) to identify the molecular pathways deregulated in these tumors, iii) to discover and validate novel and clinically relevant targets of DNA hypomethylation in EOC, iv) to conduct DNA methylome analysis to more precisely define the genomic locations effected by global DNA hypomethylation in EOC, and v) to determine whether global DNA hypomethylation impact RE gene expression in EOC. Methods: Global methylation status in EOC was determined using quantitative bisulfite pyrosequencing of the LINE1 RE. Affymetrix microarrays, RT-qPCR, and total RNAseq were used to measure gene expression in normal ovary (NO), LINE1 hypomethylated EOC, and LINE1 hypermethylated (i.e. normally methylated) EOC. Pathway analysis was conducted on differentially expressed genes (DEG) between NO and EOC and between the two EOC groups. Illumina Infinium 450K arrays and Agilent Sure Select methyl-seq were used to examine the DNA methylome of NO and EOC. Quantitative sodium bisulfite pyrosequencing was used to determine locus-specific DNA methylation in NO and EOC. Results: Global mRNA expression was distinct in LINE1 hypomethylated EOC, with ~70% of DEG upregulated, implicating DNA hypomethylation in gene activation. The most significantly altered pathway in LINE1 hypomethylated EOC was cell cycle, implicating enhanced proliferation in this phenotype. Cancer germline genes not previously known to be regulated by DNA methylation in EOC, including CT45 and PRAME, were identified and characterized. DNA methylome analysis of LINE1 hypomethylated EOC indicated that hypomethylation is not evenly dispersed across the genome, but rather is regionally localized, including at nuclear lamina associated domains (LAD). Preliminary analysis of RNAseq data indicated that specific RE are overexpressed in LINE1 hypomethylated tumors. Conclusions: Pathway analysis suggests that rapid cellular proliferation coupled with inherent inefficiencies of maintenance DNA methylation at specific genomic locations may contribute to global DNA hypomethylation in EOC. DNA hypomethylation is linked to gene activation in EOC, and important targets of this defect are cancer germline genes, which are likely to contribute to oncogenesis but may also be targeted by immunotherapy. Global DNA hypomethylation appears to be concentrated at specific genomic locations including LADs, and is connected not only to RE hypomethylation, but also to enhanced RE expression. Higher-order nuclear changes and enhanced RE expression are potential mechanisms driving genomic instability and/or poor prognosis in EOC patients displaying global DNA hypomethylation. Citation Format: Wa Zhang, David Klinkebiel, Sanjit Pandey, Dan Wang, Song Liu, Chittibabu Guda, Kunle Odunsi, Adam R. Karpf. Genomic and epigenomic characterization of global DNA hypomethylation in human epithelial ovarian cancer. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: From Concept to Clinic; Sep 18-21, 2013; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2013;19(19 Suppl):Abstract nr B12.
Since the late 1990s, the Chinese government has carried out several reforms on the primary health care, which is greatly improved but still left much to be desired, especially for the health workforces. The aim of this study was to analyze the number of health workforces and the trends in distribution of health workforces in Jiangsu province of eastern China from 2008 to 2012. The time trends in number and distribution of health professionals were compared in study period. Lorenz curves were plotted and Gini coefficient, Atkinson index and Theil index were calculated for inequalities in the distribution of health workforces to population and area. The number of health workforces increased every year and the inequality in the distribution of health workforces showed a decline trend from 2008 to 2012. After 2009, these trends changed more rapidly. There was the disproportionality between physicians and nurses. The values of three inequality indicators based on area were larger than those based on population. The health reform in 2009 might play an important role in increasing the number of health workforces and improving the distribution of health workforces in primary health care facilities. The disproportionality between physicians and nurses was related to the shortage of number of nurses.
Abstract Background: Some studies have revealed that immune regulation can delay Ischemic Stroke (IS) progression and improve neurological function and prognosis. Therefore, the molecular markers of immune cell infiltration in stroke deserves further investigation. Methods: The proportion of immune cells in the GSE58294 and GSE16561 datasets were calculated by Cell type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) algorithm. Then, Weighted Gene Coexpression Network Analysis (WGCNA) was performed to screen the key module genes related to immune cells. The overlapping differentially expressed genes (DEGs) between IS and healthy control (HC) samples were obtained from the GSE58294 and GSE16561 datasets. Differential immune cell-related DEGs were screened by overlapping DEGs and key module genes of WGCNA. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to investigate the functions of immune cell-related DEGs. Subsequently, machine learning algorithms were used to identify diagnostic genes. Then, GSE58294, GSE1656 and GSE54992 datasets were used to screen diagnostic genes by the Received Operating Characteristic (ROC) curves. Subsequently, the Pearson correlation between immune cells and diagnostic genes were analyzed. Moreover, Gene Set Enrichment Analysis (GSEA) was used to explore the functions of diagnostic genes, and the Comparative Toxicology Genomics (CTD) database was used to predict potential drugs for diagnostic genes. Finally, the quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR) was applied to explore the expression of diagnostic genes. Results: Three common differential immune cells in the GSE58294 and GSE16561 datasets were obtained, and 25 differential immune cell-related DEGs were obtained. Functional enrichment revealed that these genes were mainly associated with immune response activation and immunocytes. Moreover, 3 diagnostic genes (CD79B, ID3 and PLXDC2) with good diagnostic value were obtained. Subsequently, Pearson correlation analysis between immune cells and 3 diagnostic genes showed that the 3 genes were strong correlation with immune cells. Furthermore, GSEA revealed that CD79B, ID3 and PLXDC2 were mainly involved in immune response. Additionally, 20 CD79B-related, 73 ID3-related and 19 PLXDC2-related drugs were predicted. Finally, the mRNA expression of CD79B, ID3 and PLXDC2 were different in IS and HC. Conclusion: CD79B, ID3 and PLXDC2 were identified as biomarkers of IS, which might provide a research basis for further understanding the pathogenesis of IS and contribute to the treatment of IS.
Abstract Female mammalian cells have two X chromosomes, one of maternal origin and one of paternal origin. During development, one X chromosome randomly becomes inactivated 1–4 . This renders either the maternal X (X m ) chromosome or the paternal X (X p ) chromosome inactive, causing X mosaicism that varies between female individuals, with some showing considerable or complete skew of the X chromosome that remains active 5–7 . Parent-of-X origin can modify epigenetics through DNA methylation 8,9 and possibly gene expression; thus, mosaicism could buffer dysregulated processes in ageing and disease. However, whether X skew or its mosaicism alters functions in female individuals is largely unknown. Here we tested whether skew towards an active X m chromosome influences the brain and body—and then delineated unique features of X m neurons and X p neurons. An active X m chromosome impaired cognition in female mice throughout the lifespan and led to worsened cognition with age. Cognitive deficits were accompanied by X m -mediated acceleration of biological or epigenetic ageing of the hippocampus, a key centre for learning and memory, in female mice. Several genes were imprinted on the X m chromosome of hippocampal neurons, suggesting silenced cognitive loci. CRISPR-mediated activation of X m -imprinted genes improved cognition in ageing female mice. Thus, the X m chromosome impaired cognition, accelerated brain ageing and silenced genes that contribute to cognition in ageing. Understanding how X m impairs brain function could lead to an improved understanding of heterogeneity in cognitive health in female individuals and to X-chromosome-derived pathways that protect against cognitive deficits and brain ageing.
Expression of DAZ-like ( DAZL ) is a hallmark of vertebrate germ cells and essential for embryonic germ cell development and differentiation, yet gametogenic function of DAZL has not been fully characterized with most of its in vivo direct targets unknown. We showed that postnatal stage-specific deletion of Dazl in mouse germ cells did not affect female fertility, but caused complete male sterility with gradual loss of spermatogonial stem cells (SSCs), meiotic arrest and spermatid arrest respectively. Using the genome-wide HITS-CLIP and mass spectrometry approach, we found that DAZL bound to a large number of testicular mRNA transcripts (at least 3008) at 3′ UnTranslated Region (3′ UTR) and interacted with translation proteins including PABP. In the absence of DAZL, polysome-associated target transcripts, but not their total transcripts were significantly decreased, resulting in drastic reduction of an array of spermatogenic proteins and thus developmental arrest. Thus, DAZL is a master translational regulator essential for spermatogenesis.
Background. Glioma is the most common central nervous system (CNS) cancer with a short survival period and a poor prognosis. The S100 family gene, comprising 25 members, relates to diverse biological processes of human malignancies. Nonetheless, the significance of S100 genes in predicting the prognosis of glioma remains largely unclear. We aimed to build an S100 family-based signature for glioma prognosis. Methods. We downloaded 665 and 313 glioma patients, respectively, from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) database with RNAseq data and clinical information. This study established a prognostic signature based on the S100 family genes through multivariate COX and LASSO regression. The Kaplan–Meier curve was plotted to compare overall survival (OS) among groups, whereas Receiver Operating Characteristic (ROC) analysis was performed to evaluate model accuracy. A representative gene S100B was further verified by in vitro experiments. Results. An S100 family-based signature comprising 5 genes was constructed to predict the glioma that stratified TCGA-derived cases as a low- or high-risk group, whereas the significance of prognosis was verified based on CGGA-derived cases. Kaplan–Meier analysis revealed that the high-risk group was associated with the dismal prognosis. Furthermore, the S100 family-based signature was proved to be closely related to immune microenvironment. In vitro analysis showed S100B gene in the signature promoted glioblastoma (GBM) cell proliferation and migration. Conclusions. We constructed and verified a novel S100 family-based signature associated with tumor immune microenvironment (TIME), which may shed novel light on the glioma diagnosis and treatment.
At present, the participation rate in cancer screening is still not ideal, and the lack of screening information or misunderstanding of information is an important factor hindering cancer screening behaviour. Therefore, a systematic synthesis of information needs related to cancer screening is critical.
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