The comprehensive analysis of total expression profiles in initial diagnosed multiple myeloma by genetic microarray
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE141260 | GEO | 2020/12/02
REPOSITORIES: GEO
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Project description:Despite the development of novel therapeutic agents, multiple myeloma (MM) remains incurable, owing mainly to inevitable relapse in almost all patients. Some relapses occur as extramedullary disease (EMD), which is rare but is the most aggressive event in MM patients. Extramedullary myeloma (EMM) has extraordinary heterogeneous biological and clinical features. Previous studies have shown that expression levels of LncRNAs and mRNAs in different stages of MM are different. This study analyzes the expression levels of LncRNAs and mRNAs in primary plasma cells (PCs) from MM and EMM patients.
2023-03-01 | GSE147841 | GEO
Project description:A few reports have implicated specific lncRNAs in cardiac development or failure, but precise details of lncRNAs expressed in hearts and how their expression may be altered during embryonic heart development or by adult heart disease is unknown. By comparing lncRNA profiles of normal embryonic (~E14), normal adult, and hypertrophied adult hearts we defined a distinct fetal lncRNA abundance signature that includes 157 lncRNAs differentially expressed compared to adults (fold-change ≥ 50%, FDR=0.02), and which was only poorly recapitulated in hypertrophied hearts (17 differentially expressed lncRNAs; 13 of these observed in embryonic hearts). Analysis of protein-coding mRNAs from the same samples identified 22 concordantly and 11 reciprocally regulated mRNAs within 10 kb of dynamically expressed lncRNAs, reciprocal relationships of lncRNA and mRNA levels was validated for the Mccc1 and Relb genes using in vitro lncRNA knockdown in C2C12 cells. Network analysis suggested a central role for lncRNAs in modulating NFkappaB- and CREB1-regulated genes during embryonic heart growth and identified multiple mRNAs within these pathways that are also regulated, but independently of lncRNAs. Cardiac polyadenylated RNA (mRNA and lncRNA) profiles were generated from C57BL/6J mouse hearts were generated on Illumina HiSeq 2000 instruments. 7 independent E13.5 hearts, 12 adult hearts (6 at 6 weeks of age, 6 at 16 weeks of age), 4 sham-operated hearts at 12 weeks of age, and 4 hearts after 4 weeks of pressure overload (TAC) at 12 weeks of age.
2014-06-14 | E-GEOD-58455 | biostudies-arrayexpress
Project description:Dysregulation of long non-coding RNAs (lncRNAs) has been proven to be involved in the pathogenesis of coronary artery disease (CAD). However, it remains to be extensively explored.Using microarray, we performed the transcriptome-wide lncRNA and mRNAs expression profile in peripheral blood mononuclear cells (PBMCs) of 93 CAD patients and 48 healthy controls. Gene Ontology (GO) and pathway analysis for differentially expressed mRNAs was used to investigate underlying biological associations of differentially expressed lncRNAs and create path-net to depict interactions of significant pathways. We identified 1,210 lncRNAs and 890 mRNAs differentially expressed from the expression profile and validated selected 7 lncRNAs. Two novel lncRNA biomarkers, ENST00000444488.1 and uc010yfd.1, together with CAD risk factors had the better predictive performance for discriminating CAD patients from healthy controls, and ENST00000444488.1 could diagnose acute myocardial infarction (AMI) patients from non-AMI patients.
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Project description:Bone marrow-derived mesenchymal stem cell (BMSC) is one crucial component of the multiple myeloma (MM) microenvironment and supports the malignant progression of MM. Whether BMSCs act on MM cells via exosomes has not been well characterized. Herein, we used microarrays to screen out differentially expressed miRNAs in BMSCs from patients with MM (MM-MSCs) or benign diseases (BD-MSCs).
2022-03-23 | GSE196321 | GEO
Project description:LncRNA expression profiling for liver tissues of mice fed for NFD, LSF and HSF groups Summary: An abstract of the experiment and the data analysis. Experiment Workflow: A workflow of the experiment and the data analysis. Project Description: Sample and experiment information. Array Information: Mouse 8 x 60K LncRNA expression array information. Summary Table of Files for Data Delivery: Contains summary table of files for data delivery and the recommended software programs for viewing the data. Data Analysis for LncRNAs 1. Raw LncRNA data normalization and low intensity filtering: Raw signal intensities were normalized in quantile method by GeneSpring GX v11.5.1, and low intensity LncRNAs were filtered (LncRNAs that at least 6 out of 9 samples have flags in Present or Marginal were chosen for further analysis, these LncRNAs can be found from the LncRNA Expression Profiling Data.xls file). 2. Quality assessment of LncRNA data after filtering: Contains Box Plot and Scatter Plot for LncRNAs after filtering (This data can be found from the LncRNA Expression Profiling Data.xls file). 3. Differentially expressed LncRNAs screening: Contains differentially expressed genes with statistical significance that passed Volcano Plot filtering (Fold Change >= 2.0, P-value <= 0.05) (This data can be found from the Differentially Expressed LncRNAs.xls file). 4. Heat Map and Hierarchical Clustering: Hierarchical Clustering of Differentially Expressed LncRNAs (The heat map can be found from the LncRNA Expression Profiling Data.xls file). Data Analysis for mRNAs 1. Raw mRNA data normalization and low intensity filtering: Raw signal intensities were normalized in quantile method by GeneSpring GX v11.5.1, and low intensity mRNAs were filtered (mRNAs that at least 6 out of 9 samples have flags in Present or Marginal were chosen for further analysis, these mRNAs can be found from the mRNA Expression Profiling Data.xls file). 2. Quality assessment of mRNA data after filtering: Contains Box Plot and Scatter Plot for mRNAs after filtering (This data can be found from the mRNA Expression Profiling Data.xls file). 3. Differentially expressed mRNAs screening: Contains differentially expressed genes with statistical significance that passed Volcano Plot filtering (Fold Change >= 2.0, P-value <= 0.05) (This data can be found from the Differentially Expressed mRNAs.xls file). 4. Heat Map and Hierarchical Clustering: Hierarchical Clustering of Differentially Expressed mRNAs (The heat map can be found from the mRNA Expression Profiling Data.xls file). 5. Pathway analysis: Pathway analysis of the differentially expressed mRNAs. 6. GO analysis: GO term analysis of the differentially expressed mRNAs. LncRNA Classification and Subgroup Analysis 1. Rinn lincRNAs profiling: Contains profiling data of all lincRNAs based on John Rinn's papers (This data can be found from the Rinn lincRNAs profiling.xls file). 2. LincRNAs nearby coding gene data table: Contains the differentially expressed lincRNAs and nearby coding gene pairs (distance < 300 kb) (This data can be found from the LincRNAs nearby coding gene data table.xls file). Sample RNA Quality Control: Sample quality control data file from NanoDrop ND-1000 spectrophotometer and standard denaturing agarose gel electrophoresis. Methods: A brief introduction of methods for sample preparation, microarray design, experiment, and data analysis.
2022-11-24 | E-MTAB-9167 | biostudies-arrayexpress
Project description:The identification of deregulated microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in multiple myeloma (MM) has progressively added a further level of complexity to MM biology. In addition, the cross-regulation between lncRNAs and miRNAs has begun to emerge, and theoretical and experimental studies have demonstrated the competing endogenous RNAs (ceRNAs) activity of lncRNAs as natural miRNA decoys in pathophysiological conditions, including cancer. Currently, information concerning lncRNA and miRNA interplay in MM is virtually absent. Herein, we investigated in silico the lncRNA and miRNA relationship in a representative datasets encompassing 95 MM and 30 plasma cell leukemia patients at diagnosis and in four normal controls, whose expression profiles were generated by a custom annotation pipeline to detect specific lncRNAs. We applied target prediction analysis based on miRanda and RNA22 algorithms to 235 lncRNAs and 459 miRNAs selected with a potential pivotal role in the pathology of MM. Among pairs that showed significant correlation between lncRNA and miRNA expression levels, we identified 10 lncRNA-miRNA relationships suggestive of novel ceRNA network with relevance in MM.
2017-11-09 | GSE106745 | GEO
Project description:The identification of deregulated microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in multiple myeloma (MM) has progressively added a further level of complexity to MM biology. In addition, the cross-regulation between lncRNAs and miRNAs has begun to emerge, and theoretical and experimental studies have demonstrated the competing endogenous RNAs (ceRNAs) activity of lncRNAs as natural miRNA decoys in pathophysiological conditions, including cancer. Currently, information concerning lncRNA and miRNA interplay in MM is virtually absent. Herein, we investigated in silico the lncRNA and miRNA relationship in a representative datasets encompassing 95 MM and 30 plasma cell leukemia patients at diagnosis and in four normal controls, whose expression profiles were generated by a custom annotation pipeline to detect specific lncRNAs. We applied target prediction analysis based on miRanda and RNA22 algorithms to 235 lncRNAs and 459 miRNAs selected with a potential pivotal role in the pathology of MM. Among pairs that showed significant correlation between lncRNA and miRNA expression levels, we identified 10 lncRNA-miRNA relationships suggestive of novel ceRNA network with relevance in MM.
2017-11-09 | GSE106744 | GEO
Project description:The identification of deregulated microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in multiple myeloma (MM) has progressively added a further level of complexity to MM biology. In addition, the cross-regulation between lncRNAs and miRNAs has begun to emerge, and theoretical and experimental studies have demonstrated the competing endogenous RNAs (ceRNAs) activity of lncRNAs as natural miRNA decoys in pathophysiological conditions, including cancer. Currently, information concerning lncRNA and miRNA interplay in MM is virtually absent. Herein, we investigated in silico the lncRNA and miRNA relationship in a representative datasets encompassing 95 MM and 30 plasma cell leukemia patients at diagnosis and in four normal controls, whose expression profiles were generated by a custom annotation pipeline to detect specific lncRNAs. We applied target prediction analysis based on miRanda and RNA22 algorithms to 235 lncRNAs and 459 miRNAs selected with a potential pivotal role in the pathology of MM. Among pairs that showed significant correlation between lncRNA and miRNA expression levels, we identified 10 lncRNA-miRNA relationships suggestive of novel ceRNA network with relevance in MM.
2017-02-10 | GSE87829 | GEO
Project description:The identification of deregulated microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in multiple myeloma (MM) has progressively added a further level of complexity to MM biology. In addition, the cross-regulation between lncRNAs and miRNAs has begun to emerge, and theoretical and experimental studies have demonstrated the competing endogenous RNAs (ceRNAs) activity of lncRNAs as natural miRNA decoys in pathophysiological conditions, including cancer. Currently, information concerning lncRNA and miRNA interplay in MM is virtually absent. Herein, we investigated in silico the lncRNA and miRNA relationship in a representative datasets encompassing 95 MM and 30 plasma cell leukemia patients at diagnosis and in four normal controls, whose expression profiles were generated by a custom annotation pipeline to detect specific lncRNAs. We applied target prediction analysis based on miRanda and RNA22 algorithms to 235 lncRNAs and 459 miRNAs selected with a potential pivotal role in the pathology of MM. Among pairs that showed significant correlation between lncRNA and miRNA expression levels, we identified 10 lncRNA-miRNA relationships suggestive of novel ceRNA network with relevance in MM.
2017-02-10 | GSE87828 | GEO
Project description:LncRNA expression profiling for liver tissues of mice fed for a normal diet (NFD, 3mice) and a high-fat diet (HFD, 3mice) Summary: An abstract of the experiment and the data analysis. Experiment Workflow: A workflow of the experiment and the data analysis. Project Description: Sample and experiment information. Array Information: Mouse 8 x 60K LncRNA expression array information. Summary Table of Files for Data Delivery: Contains summary table of files for data delivery and the recommended software programs for viewing the data. Data Analysis for LncRNAs 1. Raw LncRNA data normalization and low intensity filtering: Raw signal intensities were normalized in quantile method by GeneSpring GX v11.5.1, and low intensity LncRNAs were filtered (LncRNAs that at least 6 out of 9 samples have flags in Present or Marginal were chosen for further analysis, these LncRNAs can be found from the LncRNA Expression Profiling Data.xls file). 2. Quality assessment of LncRNA data after filtering: Contains Box Plot and Scatter Plot for LncRNAs after filtering (This data can be found from the LncRNA Expression Profiling Data.xls file). 3. Differentially expressed LncRNAs screening: Contains differentially expressed genes with statistical significance that passed Volcano Plot filtering (Fold Change >= 2.0, P-value <= 0.05) (This data can be found from the Differentially Expressed LncRNAs.xls file). 4. Heat Map and Hierarchical Clustering: Hierarchical Clustering of Differentially Expressed LncRNAs (The heat map can be found from the LncRNA Expression Profiling Data.xls file). Data Analysis for mRNAs 1. Raw mRNA data normalization and low intensity filtering: Raw signal intensities were normalized in quantile method by GeneSpring GX v11.5.1, and low intensity mRNAs were filtered (mRNAs that at least 6 out of 9 samples have flags in Present or Marginal were chosen for further analysis, these mRNAs can be found from the mRNA Expression Profiling Data.xls file). 2. Quality assessment of mRNA data after filtering: Contains Box Plot and Scatter Plot for mRNAs after filtering (This data can be found from the mRNA Expression Profiling Data.xls file). 3. Differentially expressed mRNAs screening: Contains differentially expressed genes with statistical significance that passed Volcano Plot filtering (Fold Change >= 2.0, P-value <= 0.05) (This data can be found from the Differentially Expressed mRNAs.xls file). 4. Heat Map and Hierarchical Clustering: Hierarchical Clustering of Differentially Expressed mRNAs (The heat map can be found from the mRNA Expression Profiling Data.xls file). 5. Pathway analysis: Pathway analysis of the differentially expressed mRNAs. 6. GO analysis: GO term analysis of the differentially expressed mRNAs. LncRNA Classification and Subgroup Analysis 1. Rinn lincRNAs profiling: Contains profiling data of all lincRNAs based on John Rinn's papers (This data can be found from the Rinn lincRNAs profiling.xls file). 2. LincRNAs nearby coding gene data table: Contains the differentially expressed lincRNAs and nearby coding gene pairs (distance < 300 kb) (This data can be found from the LincRNAs nearby coding gene data table.xls file). Sample RNA Quality Control: Sample quality control data file from NanoDrop ND-1000 spectrophotometer and standard denaturing agarose gel electrophoresis. Methods: A brief introduction of methods for sample preparation, microarray design, experiment, and data analysis.
2022-11-23 | E-MTAB-8730 | biostudies-arrayexpress