ABSTRACT
BACKGROUND AND AIMS: NAFLD is the most common form of liver disease worldwide, but only a subset of individuals with NAFLD may progress to NASH. While NASH is an important etiology of HCC, the underlying mechanisms responsible for the conversion of NAFLD to NASH and then to HCC are poorly understood. We aimed to identify genetic risk genes that drive NASH and NASH-related HCC. APPROACH AND RESULTS: We searched genetic alleles among the 24 most significant alleles associated with body fat distribution from a genome-wide association study of 344,369 individuals and validated the top allele in 3 independent cohorts of American and European patients (N=1380) with NAFLD/NASH/HCC. We identified an rs3747579-TT variant significantly associated with NASH-related HCC and demonstrated that rs3747579 is expression quantitative trait loci of a mitochondrial DnaJ Heat Shock Protein Family (Hsp40) Member A3 ( DNAJA3 ). We also found that rs3747579-TT and a previously identified PNPLA3 as a functional variant of NAFLD to have significant additional interactions with NASH/HCC risk. Patients with HCC with rs3747579-TT had a reduced expression of DNAJA3 and had an unfavorable prognosis. Furthermore, mice with hepatocyte-specific Dnaja3 depletion developed NASH-dependent HCC either spontaneously under a normal diet or enhanced by diethylnitrosamine. Dnaja3 -deficient mice developed NASH/HCC characterized by significant mitochondrial dysfunction, which was accompanied by excessive lipid accumulation and inflammatory responses. The molecular features of NASH/HCC in the Dnaja3 -deficient mice were closely associated with human NASH/HCC. CONCLUSIONS: We uncovered a genetic basis of DNAJA3 as a key player of NASH-related HCC.
ABSTRACT
BACKGROUND: MicroRNAs (miRNAs) play a key role in mediating the action of insulin on cell growth and the development of diabetes. However, few studies have been conducted to provide a comprehensive overview of the miRNA-mediated signaling network in response to glucose in pancreatic beta cells. In our study, we established a computational framework integrating multi-omics profiles analyses, including RNA sequencing (RNA-seq) and small RNA sequencing (sRNA-seq) data analysis, inverse expression pattern analysis, public data integration, and miRNA targets prediction to illustrate the miRNA-mediated regulatory network at different glucose concentrations in INS-1 pancreatic beta cells (INS-1), which display important characteristics of the pancreatic beta cells. RESULTS: We applied our computational framework to the expression profiles of miRNA/mRNA of INS-1, at different glucose concentrations. A total of 1437 differentially expressed genes (DEGs) and 153 differentially expressed miRNAs (DEmiRs) were identified from multi-omics profiles. In particular, 121 DEmiRs putatively regulated a total of 237 DEGs involved in glucose metabolism, fatty acid oxidation, ion channels, exocytosis, homeostasis, and insulin gene regulation. Moreover, Argonaute 2 immunoprecipitation sequencing, qRT-PCR, and luciferase assay identified Crem, Fn1, and Stc1 are direct targets of miR-146b and elucidated that miR-146b acted as a potential regulator and promising target to understand the insulin signaling network. CONCLUSIONS: In this study, the integration of experimentally verified data with system biology framework extracts the miRNA network for exploring potential insulin-associated miRNA and their target genes. The findings offer a potentially significant effect on the understanding of miRNA-mediated insulin signaling network in the development and progression of pancreatic diabetes.
Subject(s)
Gene Expression Regulation/genetics , Gene Regulatory Networks/genetics , Insulin/metabolism , MicroRNAs/genetics , Humans , Signal TransductionABSTRACT
MicroRNAs (miRNAs) are small non-coding RNAs of â¼ 22 nucleotides that are involved in negative regulation of mRNA at the post-transcriptional level. Previously, we developed miRTarBase which provides information about experimentally validated miRNA-target interactions (MTIs). Here, we describe an updated database containing 422 517 curated MTIs from 4076 miRNAs and 23 054 target genes collected from over 8500 articles. The number of MTIs curated by strong evidence has increased â¼1.4-fold since the last update in 2016. In this updated version, target sites validated by reporter assay that are available in the literature can be downloaded. The target site sequence can extract new features for analysis via a machine learning approach which can help to evaluate the performance of miRNA-target prediction tools. Furthermore, different ways of browsing enhance user browsing specific MTIs. With these improvements, miRTarBase serves as more comprehensively annotated, experimentally validated miRNA-target interactions databases in the field of miRNA related research. miRTarBase is available at http://miRTarBase.mbc.nctu.edu.tw/.
Subject(s)
Databases, Genetic , MicroRNAs/metabolism , RNA, Messenger/metabolism , Data Mining , Humans , RNA, Messenger/chemistry , User-Computer InterfaceABSTRACT
Gastric cancer (GC) is the second most frequent cause of cancer-related deaths worldwide. MicroRNAs are single-stranded RNA molecules of 21-23 nucleotides that regulate target gene expression through specific base-pairing interactions between miRNA and untranslated regions of targeted mRNAs. In this study, we generated a multistep approach for the integrated analysis of miRNA and mRNA expression. First, both miRNA and mRNA expression profiling datasets in gastric cancer from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) identified 79 and 1042 differentially expressed miRNAs and mRNAs, respectively, in gastric cancer. Second, inverse correlations between miRNA and mRNA expression levels identified 3206 miRNA-mRNA pairs combined with 79 dysregulated miRNAs and their 774 target mRNAs predicted by three prediction tools, miRanda, PITA, and RNAhybrid. Additionally, miR-204, which was found to be down-regulated in gastric cancer, was ectopically over-expressed in the AGS gastric cancer cell line and all down-regulated targets were identified by RNA sequencing (RNA-seq) analysis. Over-expression of miR-204 reduced the gastric cancer cell proliferation and suppressed the expression of three targets which were validated by qRT-PCR and luciferase assays. For the first time, we identified that CKS1B, CXCL1, and GPRC5A are putative targets of miR-204 and elucidated that miR-204 acted as potential tumor suppressor and, therefore, are useful as a promising therapeutic target for gastric cancer.
Subject(s)
CDC2-CDC28 Kinases/genetics , Chemokine CXCL1/genetics , Gene Expression Regulation, Neoplastic , MicroRNAs/genetics , Receptors, G-Protein-Coupled/genetics , Stomach Neoplasms/genetics , Atlases as Topic , Base Sequence , Binding Sites , CDC2-CDC28 Kinases/metabolism , Cell Line, Tumor , Cell Proliferation , Chemokine CXCL1/metabolism , Databases, Genetic , Gene Expression Profiling , Gene Regulatory Networks , Genes, Reporter , Humans , Luciferases/genetics , Luciferases/metabolism , MicroRNAs/metabolism , Receptors, G-Protein-Coupled/metabolism , Sequence Analysis, RNA , Signal Transduction , Stomach Neoplasms/metabolism , Stomach Neoplasms/pathologyABSTRACT
Differentiation of induced pluripotent stem cells (iPSCs) is an extremely complex process that has proven difficult to study. In this research, we utilized nanotopography to elucidate details regarding iPSC differentiation by developing a nanodot platform consisting of nanodot arrays of increasing diameter. Subjecting iPSCs cultured on the nanodot platform to a cardiomyocyte (CM) differentiation protocol revealed several significant gene expression profiles that were associated with poor differentiation. The observed expression trends were used to select existing small-molecule drugs capable of modulating differentiation efficiency. BRD K98 was repurposed to inhibit CM differentiation, while iPSCs treated with NSC-663284, carmofur, and KPT-330 all exhibited significant increases in not only CM marker expression but also spontaneous beating, suggesting improved CM differentiation. In addition, quantitative polymerase chain reaction was performed to determine the gene regulation responsible for modulating differentiation efficiency. Multiple genes involved in extracellular matrix remodeling were correlated with a CM differentiation efficiency, while genes involved in the cell cycle exhibited contrasting expression trends that warrant further studies. The results suggest that expression profiles determined via short time-series expression miner analysis of nanodot-cultured iPSC differentiation can not only reveal drugs capable of enhancing differentiation efficiency but also highlight crucial sets of genes related to processes such as extracellular matrix remodeling and the cell cycle that can be targeted for further investigation. Our findings confirm that the nanodot platform can be used to reveal complex mechanisms behind iPSC differentiation and could be an indispensable tool for optimizing iPSC technology for clinical applications.
Subject(s)
Cell Differentiation , Induced Pluripotent Stem Cells , Myocytes, Cardiac , Induced Pluripotent Stem Cells/cytology , Induced Pluripotent Stem Cells/drug effects , Induced Pluripotent Stem Cells/metabolism , Cell Differentiation/drug effects , Myocytes, Cardiac/cytology , Myocytes, Cardiac/metabolism , Myocytes, Cardiac/drug effects , Humans , Nanoparticles/chemistry , Cells, Cultured , Nanostructures/chemistryABSTRACT
During endoderm formation, cell identity and tissue morphogenesis are tightly controlled by cell-intrinsic and cell-extrinsic factors such as biochemical and physical inputs. While the effects of biochemical factors are well studied, the physical cues that regulate cell division and differentiation are poorly understood. RNA sequencing analysis demonstrated increases of endoderm-specific gene expression in hPSCs cultured on soft substrate (Young's modulus, 3 ± 0.45 kPa) in comparison with hard substrate (Young's modulus, 165 ± 6.39 kPa). Further analyses revealed that multiple long noncoding RNAs (lncRNAs) were up-regulated on soft substrate; among them, LINC00458 was identified as a stiffness-dependent lncRNA specifically required for hPSC differentiation toward an early endodermal lineage. Gain- and loss-of-function experiments confirmed that LINC00458 is functionally required for hPSC endodermal lineage specification induced by soft substrates. Our study provides evidence that mechanical cues regulate the expression of LINC00458 and induce differentiation of hPSC into hepatic lineage progenitors.
Subject(s)
Endoderm/cytology , Endoderm/metabolism , Gene Expression Regulation, Developmental , RNA, Long Noncoding/genetics , Smad2 Protein/genetics , Smad3 Protein/genetics , Animals , Cell Differentiation/genetics , Cell Line , Cell Lineage/genetics , Cells, Cultured , Extracellular Matrix , Gene Expression Profiling , Gene Knockdown Techniques , Humans , Mice , Models, Biological , Organ Specificity/genetics , RNA Interference , TranscriptomeABSTRACT
Globally, breast cancer is the most frequently diagnosed cancer in women, and it remains a substantial clinical challenge due to cancer relapse. The presence of a subpopulation of dormant breast cancer cells that survived chemotherapy and metastasized to distant organs may contribute to relapse. Tumor microenvironment (TME) plays a significant role as a niche in inducing cancer cells into dormancy as well as involves in the reversible epithelial-to-mesenchymal transition (EMT) into aggressive phenotype responsible for cancer-related mortality in patients. Mesenchymal stem cells (MSCs) are known to migrate to TME and interact with cancer cells via secretion of exosome- containing biomolecules, microRNA. Understanding of interaction between MSCs and cancer cells via exosomal miRNAs is important in determining the therapeutic role of MSC in treating breast cancer cells and relapse. In this study, exosomes were harvested from a medium of indirect co-culture of MCF7-luminal and MDA-MB-231-basal breast cancer cells (BCCs) subtypes with adipose MSCs. The interaction resulted in different exosomal miRNAs profiles that modulate essential signaling pathways and cell cycle arrest into dormancy via inhibition of metastasis and epithelial-to-mesenchymal transition (EMT). Overall, breast cancer cells displayed a change towards a more dormant-epithelial phenotype associated with lower rates of metastasis and higher chemoresistance. The study highlights the crucial roles of adipose MSCs in inducing dormancy and identifying miRNAs-dormancy related markers that could be used to identify the metastatic pattern, predict relapses in cancer patients and to be potential candidate targets for new targeted therapy.
ABSTRACT
Sudden cardiac death (SCD) is an important cause of mortality worldwide. It accounts for approximately half of all deaths from cardiovascular disease. While coronary artery disease and acute myocardial infarction account for the majority of SCD in the elderly population, inherited cardiac diseases (inherited CDs) comprise a substantial proportion of younger SCD victims with a significant genetic component. Currently, the use of next-generation sequencing enables the rapid analysis to investigate relationships between genetic variants and inherited CDs causing SCD. Genetic contribution to risk has been considered an alternate predictor of SCD. In the past years, large numbers of SCD susceptibility variants were reported, but these results are scattered in numerous publications. Here, we present the SCD-associated Variants Annotation Database (SVAD) to facilitate the interpretation of variants and to meet the needs of data integration. SVAD contains data from a broad screening of scientific literature. It was constructed to provide a comprehensive collection of genetic variants along with integrated information regarding their effects. At present, SVAD has accumulated 2,292 entries within 1,239 variants by manually surveying pertinent literature, and approximately one-third of the collected variants are pathogenic/likely-pathogenic following the ACMG guidelines. To the best of our knowledge, SVAD is the most comprehensive database that can provide integrated information on the associated variants in various types of inherited CDs. SVAD represents a valuable source of variant information based on scientific literature and benefits clinicians and researchers, and it is now available on http://svad.mbc.nctu.edu.tw/.
Subject(s)
Databases, Genetic/statistics & numerical data , Death, Sudden, Cardiac/etiology , Heart Diseases/genetics , Models, Genetic , Computer Simulation , Death, Sudden, Cardiac/epidemiology , Heart Diseases/mortality , Humans , Mutation , Polymorphism, Single Nucleotide , Risk Assessment/methodsABSTRACT
Introduction: In the United States and Europe, endometrial endometrioid carcinoma (EEC) is the most prevalent gynecologic malignancy. Lymph node metastasis (LNM) is the key determinant of the prognosis and treatment of EEC. A biomarker that predicts LNM in patients with EEC would be beneficial, enabling individualized treatment. Current preoperative assessment of LNM in EEC is not sufficiently accurate to predict LNM and prevent overtreatment. This pilot study established a biomarker signature for the prediction of LNM in early stage EEC. Methods: We performed RNA sequencing in 24 clinically early stage (T1) EEC tumors (lymph nodes positive and negative in 6 and 18, respectively) from Cathay General Hospital and analyzed the RNA sequencing data of 289 patients with EEC from The Cancer Genome Atlas (lymph node positive and negative in 33 and 256, respectively). We analyzed clinical data including tumor grade, depth of tumor invasion, and age to construct a sequencing-based prediction model using machine learning. For validation, we used another independent cohort of early stage EEC samples (n = 72) and performed quantitative real-time polymerase chain reaction (qRT-PCR). Finally, a PCR-based prediction model and risk score formula were established. Results: Eight genes (ASRGL1, ESR1, EYA2, MSX1, RHEX, SCGB2A1, SOX17, and STX18) plus one clinical parameter (depth of myometrial invasion) were identified for use in a sequencing-based prediction model. After qRT-PCR validation, five genes (ASRGL1, RHEX, SCGB2A1, SOX17, and STX18) were identified as predictive biomarkers. Receiver operating characteristic curve analysis revealed that these five genes can predict LNM. Combined use of these five genes resulted in higher diagnostic accuracy than use of any single gene, with an area under the curve of 0.898, sensitivity of 88.9%, and specificity of 84.1%. The accuracy, negative, and positive predictive values were 84.7, 98.1, and 44.4%, respectively. Conclusion: We developed a five-gene biomarker panel associated with LNM in early stage EEC. These five genes may represent novel targets for further mechanistic study. Our results, after corroboration by a prospective study, may have useful clinical implications and prevent unnecessary elective lymph node dissection while not adversely affecting the outcome of treatment for early stage EEC.
ABSTRACT
BACKGROUND: Radiotherapy (RT) is a common approach that accounts for nearly 50% of cancer patient treatment and has the potential for long-term tumor control. Recently, we published a research article on gene expression profiling of tumor-associated macrophages (TAM) that were exposed to ionizing radiation (IR). Single-dose irradiation of tumors could initiate differentially expressed genes in TAM as a time series from irradiated tumors that are associated with the immune response. It is also well known that human cancers are associated with microRNA (miRNA) alterations that are involved in cancer progression. However, the role of miRNA on TAM after exposure to irradiation remains unclear. RESULTS: In this study, miRNA expression profiles from microarrays were used to identify the key miRNAs and correlating pathways involved in the role of TAMs in tumor progression and recurrence after RT. Using a mouse tumor model, we identified miRNA pattern changes over time in response to irradiation. Based on our results, we hypothesize that miRNA expression in the irradiated tumor may be used as a distinguishing marker to indicate the best time for therapeutic intervention to prevent tumor recurrence after RT. CONCLUSIONS: We established a murine model irradiated with a single dose of 25â¯Gy that could initiate temporal changes in the expression of miRNAs associated with cell proliferation and the immune response, as evidenced by macrophages directly extracted from irradiated tumors after two weeks of IR. Statistical analyses were conducted by comparing the miRNA expression in macrophages from non-irradiated versus irradiated tumors. Thus, our study could lead to a better understanding of the function of miRNA expressions, which changed temporally in an irradiated tumor microenvironment.
Subject(s)
Gamma Rays , Gene Expression Profiling , Macrophages/metabolism , Macrophages/radiation effects , MicroRNAs/genetics , Neoplasms/radiotherapy , RNA, Messenger/genetics , Animals , Disease Models, Animal , Mice , Mice, Inbred C57BL , Neoplasms/genetics , Neoplasms/pathology , Tumor Cells, CulturedABSTRACT
Acute monocytic leukemia (AML-M5), a subtype of acute myeloid leukemia (AML), affects mostly young children and has poor prognosis. The mechanisms of treatment failure of AML-M5 are still unclear. In this study, we generated iPSC from THP-1 cells from a patient with AML-M5, using retroviruses encoding the pluripotency-associated genes (OCT3/4, SOX2, KLF4 and c-MYC). These AML-M5-derived iPSC showed features similar with those of human embryonic stem cells in terms of the morphology, gene expression, protein/antigen expression and differentiation capability. Parental-specific markers were down-regulated in these AML-M5-derived iPSCs. Expression of MLL-AF9 fusion gene (previously identified to be associated with pathogenesis of AML-M5) was observed in all iPSC clones as well as parental cells. We conclude that AML-M5-specific iPSC clones have been successfully developed. This disease model may provide a novel approach for future study of pathogenesis and therapeutic intervention of AML-M5.