Identification of Transcriptional Markers and microRNA-mRNA Regulatory Networks in Colon Cancer by Integrative Analysis of mRNA and microRNA Expression Profiles in Colon Tumor Stroma.
ABSTRACT: The aberrant expression of microRNAs (miRNAs) and genes in tumor microenvironment (TME) has been associated with the pathogenesis of colon cancer. An integrative exploration of transcriptional markers (gene signatures) and miRNA-mRNA regulatory networks in colon tumor stroma (CTS) remains lacking. Using two datasets of mRNA and miRNA expression profiling in CTS, we identified differentially expressed miRNAs (DEmiRs) and differentially expressed genes (DEGs) between CTS and normal stroma. Furthermore, we identified the transcriptional markers which were both gene targets of DEmiRs and hub genes in the protein-protein interaction (PPI) network of DEGs. Moreover, we investigated the associations between the transcriptional markers and tumor immunity in colon cancer. We identified 17 upregulated and seven downregulated DEmiRs in CTS relative to normal stroma based on a miRNA expression profiling dataset. Pathway analysis revealed that the downregulated DEmiRs were significantly involved in 25 KEGG pathways (such as TGF-?, Wnt, cell adhesion molecules, and cytokine-cytokine receptor interaction), and the upregulated DEmiRs were involved in 10 pathways (such as extracellular matrix (ECM)-receptor interaction and proteoglycans in cancer). Moreover, we identified 460 DEGs in CTS versus normal stroma by a meta-analysis of two gene expression profiling datasets. Among them, eight upregulated DEGs were both hub genes in the PPI network of DEGs and target genes of the downregulated DEmiRs. We found that three of the eight DEGs were negative prognostic factors consistently in two colon cancer cohorts, including COL5A2, EDNRA, and OLR1. The identification of transcriptional markers and miRNA-mRNA regulatory networks in CTS may provide insights into the mechanism of tumor immune microenvironment regulation in colon cancer.
Project description:Background:The tumor stroma plays pivotal roles in influencing tumor growth, invasion, and metastasis. Transcriptional signatures of colon tumor stroma (CTS) are significantly associated with prognosis of colon cancer. Thus, identification of the CTS transcriptional features could be useful for colon cancer diagnosis and therapy. Methods:By a meta-analysis of three CTS gene expression profiles datasets, we identified differentially expressed genes (DEGs) between CTS and colon normal stroma. Furthermore, we identified the pathways, upstream regulators, and protein-protein interaction (PPI) network that were significantly associated with the DEGs. Moreover, we analyzed the enrichment levels of immune signatures in CTS. Finally, we identified CTS-associated gene signatures whose expression was significantly associated with prognosis in colon cancer. Results:We identified numerous significantly upregulated genes (such as CTHRC1, NFE2L3, SULF1, SOX9, ENC1, and CCND1) and significantly downregulated genes (such as MYOT, ASPA, KIAA2022, ARHGEF37, BCL-2, and PPARGC1A) in CTS versus colon normal stroma. Furthermore, we identified significantly upregulated pathways in CTS that were mainly involved in cellular development, immune regulation, and metabolism, as well as significantly downregulated pathways in CTS that were mostly metabolism-related. Moreover, we identified upstream TFs (such as SUZ12, NFE2L2, RUNX1, STAT3, and SOX2), kinases (such as MAPK14, CSNK2A1, CDK1, CDK2, and CDK4), and master metabolic transcriptional regulators (MMTRs) (such as HNF1A, NFKB1, ZBTB7A, GATA2, and GATA5) regulating the DEGs. We found that CD8+ T cells were more enriched in CTS than in colon normal stroma. Interestingly, we found that many of the DEGs and their regulators were prognostic markers for colon cancer, including CEBPB, PPARGC1, STAT3, MTOR, BCL2, JAK2, and CDK1. Conclusions:The identification of CTS-specific transcriptional signatures may provide insights into the tumor microenvironment that mediates the development of colon cancer and has potential clinical implications for colon cancer diagnosis and treatment.
Project description:Purpose:This research explores the aberrant expression of the long non-coding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) in pterygium. A competitive endogenous RNA (ceRNA) network was constructed to elucidate the molecular mechanisms in pterygium. Methods:We obtained the differentially expressed mRNAs based on three datasets (GSE2513, GSE51995, and GSE83627), and summarized the differentially expressed miRNAs (DEmiRs) and differentially expressed lncRNAs (DELs) data by published literature. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, protein-protein interaction (PPI), and gene set enrichment analysis (GSEA) analysis were performed. DEmiRs were verified in GSE21346, and the regulatory network of hub mRNAs, DELs, and DEmiRs were constructed. Results:Overall, 40 upregulated and 40 downregulated differentially expressed genes (DEGs) were obtained. The KEGG enrichment showed the DEGs mainly involved in extracellular matrix (ECM)-receptor interaction, focal adhesion, and PI3K-Akt signaling pathway. The GSEA results showed that cornification, keratinization, and cornified envelope were significantly enriched. The validation outcome confirmed six upregulated DEmiRs (miR-766-3p, miR-184, miR-143-3p, miR-138-5p, miR-518b, and miR-1236-3p) and two downregulated DEmiRs (miR-200b-3p and miR-200a-3p). Then, a ceRNA regulatory network was constructed with 22 upregulated and 15 downregulated DEmiRs, 4 downregulated DELs, and 26 upregulated and 33 downregulated DEGs. The network showed that lncRNA SNHG1/miR-766-3p/FOS and some miRNA-mRNA axes were dysregulated in pterygium. Conclusions:Our study provides a novel perspective on the regulatory mechanism of pterygium, and lncRNA SNHG1/miR-766-3p/FOS may contribute to pterygium development.
Project description:Hypertrophic cardiomyopathy (HCM) is a complex inherited cardiovascular disease. The present study investigated the long noncoding (lnc)RNA/microRNA (mi)RNA/mRNA expression pattern of patients with HCM and aimed to identify key molecules involved in the development of this condition. An integrated strategy was conducted to identify differentially expressed miRNAs (DEmiRs), differentially expressed lncRNAs (DElncs) and differentially expressed genes (DEGs) based on the GSE36961 (mRNA), GSE36946 (miRNA), GSE68316 (lncRNA/mRNA) and GSE32453 (mRNA) expression profiles downloaded from the Gene Expression Omnibus datasets. Bioinformatics tools were employed to perform function and pathway enrichment analysis, protein‑protein interaction, lncRNA‑miRNA‑mRNA and hub gene networks. Subsequently, DEGs were used as targets to predict drugs. The results indicated that a total of 2,234 DElncs (1,120 upregulated and 1,114 downregulated), 5 DEmiRs (2 upregulated and 3 downregulated) and 42 DEGs (35 upregulated and 7 downregulated) were identified in 4 microarray profiles. Gene ontology analysis revealed that DEGs were mainly involved in actin filament and stress fiber formation and in calcium ion binding, whereas Kyoto Encyclopedia of Genes and Genomes pathway analysis identified the hypoxia inducible factor‑1, transforming growth factor‑β and tumor necrosis factor signaling pathways as the main pathways involved in these processes. The hub genes were screened using cytoHubba. A total of 1,086 lncRNA‑miRNA‑mRNA interactions including 67 lncRNAs, 5 miRNAs and 25 mRNAs were mined in the present study based on prediction websites. Drug prediction indicated that the targeted drugs mainly included angiotensin converting enzyme inhibitors or β‑blockers. A comprehensive bioinformatics analysis of the molecular regulatory lncRNA‑miRNA‑mRNA network was performed and potential therapeutic applications of drugs were predicted in HCM patients. The data may unravel the future molecular mechanism of HCM.
Project description:Breast cancer is a heterogeneous disease, characterized by molecularly and phenotypically distinct tumor subtypes, linked to disparate clinical outcomes. American women of African ancestry (AA) are more likely than those of European ancestry (EA) to be diagnosed with aggressive, estrogen receptor negative (ER-) or triple negative breast cancer, and to die of this disease. However, the underlying causes of AA predisposition to ER-/triple negative breast cancer are still largely unknown. In this study, we performed high-throughput whole-genome miRNA expression profiling in breast tissue samples from both AA and EA women. A number of differentially expressed miRNAs, i.e., DEmiRs defined as >2-fold change in expression and false discovery rate <0.05, were identified as up- or downregulated by tumor ER status or by ancestry. We found that among 102 ER-subtype-related DEmiRs identified in breast tumors, the majority of these DEmiRs were race specific, with only 23 DEmiRs shared in tumors from both AAs and EAs; this finding indicates that there are unique subsets of miRNAs differentially expressed between ER- and ER positive tumors within AAs versus EAs. Our overall results support the notion that miRNA expression patterns may differ not only by tumor subtype but by ancestry, indicating differences in tumor biology and heterogeneity of breast cancer between AAs and EAs. These results will provide the basis for further functional analysis to elucidate biological differences between AAs and EAs and to help develop targeted treatment strategies to reduce disparities in breast cancer.
Project description:Defective lysosomal acid ?-glucosidase (GCase) in Gaucher disease causes accumulation of glucosylceramide (GC) and glucosylsphingosine (GS) that distress cellular functions. To study novel pathological mechanisms in neuronopathic Gaucher disease (nGD), a mouse model (4L;C*), an analogue to subacute human nGD, was investigated for global profiles of differentially expressed brain mRNAs (DEGs) and miRNAs (DEmiRs). 4L;C* mice displayed accumulation of GC and GS, activated microglial cells, reduced number of neurons and aberrant mitochondrial function in the brain followed by deterioration in motor function. DEGs and DEmiRs were characterized from sequencing of mRNA and miRNA from cerebral cortex, brain stem, midbrain and cerebellum of 4L;C* mice. Gene ontology enrichment and pathway analysis showed preferential mitochondrial dysfunction in midbrain and uniform inflammatory response and identified novel pathways, axonal guidance signaling, synaptic transmission, eIF2 and mammalian target of rapamycin (mTOR) signaling potentially involved in nGD. Similar analyses were performed with mice treated with isofagomine (IFG), a pharmacologic chaperone for GCase. IFG treatment did not alter the GS and GC accumulation significantly but attenuated the progression of the disease and altered numerous DEmiRs and target DEGs to their respective normal levels in inflammation, mitochondrial function and axonal guidance pathways, suggesting its regulation on miRNA and the associated mRNA that underlie the neurodegeneration in nGD. These analyses demonstrate that the neurodegenerative phenotype in 4L;C* mice was associated with dysregulation of brain mRNAs and miRNAs in axonal guidance, synaptic plasticity, mitochondria function, eIF2 and mTOR signaling and inflammation and provides new insights for the nGD pathological mechanism.
Project description: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.
Project description:BACKGROUND:The aim of this study was to gain further investigation of non-small cell lung cancer (NSCLC) tumorigenesis and identify biomarkers for clinical management of patients through comprehensive bioinformatics analysis. METHODS:miRNA and mRNA microarray datasets were downloaded from GEO (Gene Expression Omnibus) database under the accession number GSE102286 and GSE101929, respectively. Genes and miRNAs with differential expression were identified in NSCLC samples compared with controls, respectively. The interaction between differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRs) was predicted, followed by functional enrichment analysis, and construction of miRNA-gene regulatory network, protein-protein interaction (PPI) network, and competing endogenous RNA (ceRNA) network. Through comprehensive bioinformatics analysis, we anticipate to find novel therapeutic targets and biomarkers for NSCLC. RESULTS:A total of 123 DEmiRs (5 up- and 118 down-regulated miRNAs) and 924 DEGs (309 up- and 615 down-regulated genes) were identified. These genes and miRNAs were significantly involved in different pathways including adherens junction, relaxin signaling pathway, and axon guidance. Furthermore, hsa-miR-9-5p, has-miR-196a-5p and hsa-miR-31-5p, as well as hsa-miR-1, hsa-miR-218-5p and hsa-miR-135a-5p were shown to have higher degree in the miRNA-gene regulatory network and ceRNA network, respectively. Furthermore, BIRC5 and FGF2, as well as RTKN2 and SLIT3 were hubs in the PPI network and ceRNA network, respectively. CONCLUSION:Several pathways (adherens junction, relaxin signaling pathway, and axon guidance) miRNAs (hsa-miR-9-5p, has-miR-196a-5p, hsa-miR-31-5p, hsa-miR-1, hsa-miR-218-5p and hsa-miR-135a-5p) and genes (BIRC5, FGF2, RTKN2 and SLIT3) may play important roles in the pathogenesis of NSCLC.
Project description:MicroRNA sequencing (miRNA?seq) was performed in the present study to investigate miRNA expression profiles in infarcted brain areas following focal cerebral ischemia induced by middle cerebral artery occlusion in rats. In total, 20 miRNAs were identified to be upregulated and 17 to be downregulated in the infarct area. The expression levels of six differentially expressed miRNAs (DEmiRs), miR?211?5p, miR?183?5p, miR?10b?3p, miR?182, miR?217?5p and miR?96?5p, were examined by reverse transcription??quantitative polymerase chain reaction. Subsequently, a miRNA?mRNA network was constructed. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed to investigate the functions of the mRNAs targeted by these DEmiRs. The present study aimed to investigate the association between miRNAs and cerebral ischemia to provide potential insight into the molecular mechanisms underlying ischemic stroke.
Project description:Introduction:Circulation microRNAs (miRNAs) perform as potential diagnostic biomarkers of many kinds of cancers. This study is aimed at identifying circulation miRNAs as diagnostic biomarkers in colon cancer. Methods:We conducted a weighted gene coexpression network analysis (WGCNA) in miRNAs to find out the expression pattern among circulation miRNAs by using a "WGCNA" package in R. Correlation analysis was performed to find cancer-related modules. Differentially expressed miRNAs (DEmiRs) in colon cancer were identified by a "limma" package in R. Hub gene analysis was conducted for these DEmiRs in the cancer-related modules by the "closeness" method in cytoscape software. Then, logistic regression was performed to identify the independent risk factors, and a scoring system was constructed based on these independent risk factors. Then, we use data from the GEO database to confirm the reliability of this scoring system. Results:A total of 9 independent coexpression modules were constructed based on the expression levels of 848 miRNAs by WGCNA. After correlation analysis, green (cor = 0.77, p = 3 × 10-25) and yellow (cor = 0.65, p = 6 × 10-16) modules were strongly correlated with cancer development. 20 hub genes were found after hub gene analysis in these DEmiRs by cytoscape. Among all these hub genes, hsa-miR-23a-3p (OR = 2.6391, p = 6.23 × 10-5) and hsa-miR-663a (OR = 1.4220, p = 0.0069) were identified as an independent risk factor of colon cancer by multivariate regression. Furthermore, a scoring system was built to predict the probability of colon cancer based on both of these miRNAs, the area under the curve (AUC) of which was 0.828. Data from GSE106817 and GSE112264 was used to confirm this scoring system. And the AUC of them was 0.980 and 0.917, respectively. Conclusion:We built a scoring system based on circulation hub miRNAs found by WGCNA to predict the development of colon cancer.
Project description:MicroRNAs (miRNAs) are aberrantly expressed in virtually all cancer types, including digestive cancers. Herein, we aggregated and systematically analyzed miRNA expression profiles of 1765 tumor samples, including esophageal, gastric, liver, pancreatic, colon and rectal cancers, obtained through small RNA sequencing by The Cancer Genome Atlas. We found that digestive cancers of different tissue origins could be differentiated according to their miRNA expression profiles. In particular, esophageal squamous cell carcinoma and esophageal adenocarcinoma exhibited distinct miRNA expression patterns. Thirteen (e.g. miR-135b, miR-182) and sixteen (e.g. miR-139, miR-133a-1, miR-490) miRNAs were commonly upregulated and downregulated in more than four cancer types, respectively. Pertinent to pathological features, low miR-181d expression was associated with microsatellite instability in colon and gastric cancers whereas low miR-106a expression was associated with hepatitis B virus infection in hepatocellular carcinoma. Progression in colon cancer could also be predicted by low let-7f-2 and high miR-106a expression. Molecular subtypes with distinct prognostic outcomes independent of tumor-node-metastasis staging were identified in hepatocellular carcinoma and colon cancer. In total, 4 novel and 6 reported associations between specific miRNAs and patients' survival were identified. Collectively, novel miRNA markers were identified to stratify digestive cancers with different pathological features and survival outcomes.