Genome-wide identification of potential biomarkers in multiple myeloma using meta-analysis of mRNA and miRNA expression data.
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ABSTRACT:
SUBMITTER: Katiyar A
PROVIDER: S-EPMC8154993 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundMultiple myeloma is a cancer which has a high occurrence rate and causes great injury to people worldwide. In recent years, many studies reported the effects of miRNA on the appearance of multiple myeloma. However, due to the differences of samples and sequencing platforms, a large number of inconsistent results have been generated among these studies, which limited the cure of multiple myeloma at the miRNA level.MethodsWe performed meta-analyses to identify the key miRNA biomarkers which could be applied on the treatment of multiple myeloma. The key miRNAs were determined by overlap comparisons of seven datasets in multiple myeloma. Then, the target genes for key miRNAs were predicted by the software TargetScan. Additionally, functional enrichments and binding TFs were investigated by DAVID database and Tfacts database, respectively.ResultsFirstly, comparing the normal tissues, 13 miRNAs were differently expressed miRNAs (DEMs) for at least three datasets. They were considered as key miRNAs, with 12 up-regulated (hsa-miR-106b, hsa-miR-125b, hsa-miR-130b, hsa-miR-138, hsa-miR-15b, hsa-miR-181a, hsa-miR-183, hsa-miR-191, hsa-miR-19a, hsa-miR-20a, hsa-miR-221 and hsa-miR-25) and one down-regulated (hsa-miR-223). Secondly, functional enrichment analyses indicated that target genes of the upregulated miRNAs were mainly transcript factors and enriched in transcription regulation. Besides, these genes were enriched in multiple pathways: the cancer signal pathway, insulin signal metabolic pathway, cell binding molecules, melanin generation, long-term regression and P53 signaling pathway. However, no significant enrichment was found for target genes of the down-regulated genes. Due to the distinct regulation function, four miRNAs (hsa-miR-19a has-miR-221 has-miR25 and has-miR223) were ascertained as the potential prognostic and diagnostic markers in MM. Thirdly, transcript factors analysis unveiled that there were 148 TFs and 60 TFs which bind target genes of the up-regulated miRNAs and target genes of the down-regulated miRNAs, respectively. They respectively generated 652 and 139 reactions of TFs and target genes. Additionally, 50 (31.6%) TFs were shared, while higher specificity was found in TFs of target genes for the upregulated miRNAs.DiscussionsTogether, our findings provided the key miRNAs which affected occurrence of multiple myeloma and regulation function of these miRNAs. It is valuable for the prognosis and diagnosis of multiple myeloma.
| S-EPMC5289111 | biostudies-literature
Project description:Identification of miRNA-mRNA modules is an important step to elucidate their combinatorial effect on the pathogenesis and mechanisms underlying complex diseases. Current identification methods primarily are based upon miRNA-target information and matched miRNA and mRNA expression profiles. However, for heterogeneous diseases, the miRNA-mRNA regulatory mechanisms may differ between subtypes, leading to differences in clinical behavior. In order to explore the pathogenesis of each subtype, it is important to identify subtype specific miRNA-mRNA modules. In this study, we integrated the Ping-Pong algorithm and multiobjective genetic algorithm to identify subtype specific miRNA-mRNA functional regulatory modules (MFRMs) through integrative analysis of three biological data sets: GO biological processes, miRNA target information, and matched miRNA and mRNA expression data. We applied our method on a heterogeneous disease, multiple myeloma (MM), to identify MM subtype specific MFRMs. The constructed miRNA-mRNA regulatory networks provide modular outlook at subtype specific miRNA-mRNA interactions. Furthermore, clustering analysis demonstrated that heterogeneous MFRMs were able to separate corresponding MM subtypes. These subtype specific MFRMs may aid in the further elucidation of the pathogenesis of each subtype and may serve to guide MM subtype diagnosis and treatment.
| S-EPMC4385567 | biostudies-literature
Project description:Background:Ulcerative colitis (UC) is a chronic, relapsing and non-specific inflammatory disease, involving various genes and pathways in their pathogenesis. Increasing evidences have showed that microRNAs (miRNAs) act as key post-transcriptional regulators of gene expression in UC. This current study aimed to identify key miRNAs, potential target genes, and relevant pathways involved in UC to uncover their underlying molecular mechanisms by using bioinformatics analysis. Methods:The mRNA and miRNA expression profiles were retrieved and downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and miRNAs (DEMIs) were obtained by using the R software package. Results:A total of 79 DEGs and 47 DEMIs were obtained. And a panel of miRNAs and their target mRNAs were identified. It showed that miR-1231 may be a key regulator for DUOX2 and TFF1. CCL11 may be potentially targeted by miR-625. MMP1 may play vital roles in the development of UC by regulating the miR-1228/PPAR signaling pathway. In addition, we validated the most significantly up/down-expressed miRNAs (miR-92b, miR-625) and two of their corresponding target mRNAs (AQP8 and TAGAP, CCL11 and CHI3L1) in colon tissues of UC models preliminarily. The results were consistent with the microarray analysis. Conclusions:These findings may provide new insights into representing key mechanisms associated with the development of UC.
| S-EPMC6776810 | biostudies-literature
Project description:Multiple myeloma (MM) is an incurable cancer of terminally differentiated plasma cells that proliferate in the bone marrow. miRNAs are promising biomarkers for risk stratification in MM and several miRNAs are shown to have a function in disease pathogenesis. However, to date, surprisingly few miRNA-mRNA interactions have been described for and functionally validated in MM. In this study, we performed miRNA-seq and mRNA-seq on CD138 + cells isolated from bone marrow aspirates of 86 MM patients to identify novel interactions between sRNAs and mRNAs. We detected 9.8% significantly correlated miRNA-mRNA pairs of which 5.17% were positively correlated and 4.65% were negatively correlated. We found that miRNA-mRNA pairs that were predicted by in silico target-prediction algorithms were more negatively correlated than non-target pairs, indicating functional miRNA targeting and that correlation between miRNAs and mRNAs from patients can be used to identify miRNA-targets. mRNAs for negatively correlated miRNA-mRNA target pairs were associated with gene ontology terms such as autophagy, protein degradation and endoplasmic stress response, reflecting important processes in MM. Targets for two specific miRNAs, miR-125b-5p and miR-365b-3p, were functionally validated in MM cell line transfection experiments followed by RNA-sequencing and qPCR. In summary, we identified functional miRNA-mRNA target pairs by correlating miRNA and mRNA data from primary MM cells. We identified several target pairs that are of potential interest for further studies. The data presented here may serve as a hypothesis-generating knowledge base for other researchers in the miRNA/MM field. We also provide an interactive web application that can be used to exploit the miRNA-target interactions as well as clinical parameters associated to these target-pairs.
| S-EPMC9287335 | biostudies-literature
Project description:BackgroundDysregulated long non-coding RNAs (lncRNAs) have been found to have oncogenic and/or tumor suppressive roles in the development and progression of cancer, implying their potentials as novel independent biomarkers for cancer diagnosis and prognosis. However, the prognostic significance of expression profile-based lncRNA signature for outcome prediction in patients with multiple myeloma (MM) has not yet been investigated.MethodsLncRNA expression profiles of a large cohort of patients with MM were obtained and analyzed by repurposing the publically available microarray data. An lncRNA-focus risk score model was developed from the training dataset, and then validated in the testing and another two independent external datasets. The time-dependent receiver operating characteristic (ROC) curve was used to evaluate the prognostic performance for survival prediction. The biological function of prognostic lncRNAs was predicted using bioinformatics analysis.ResultsFour lncRNAs were identified to be significantly associated with overall survival (OS) of patients with MM in the training dataset, and were combined to develop a four-lncRNA prognostic signature to stratify patients into high-risk and low-risk groups. Patients of training dataset in the high-risk group exhibited shorter OS than those in the low-risk group (HR = 2.718, 95 % CI = 1.937-3.815, p <0.001). The similar prognostic values of four-lncRNA signature were observed in the testing dataset, entire GSE24080 dataset and another two independent external datasets. Multivariate Cox regression and stratified analysis showed that the prognostic power of four-lncRNA signature was independent of clinical features, including serum beta 2-microglobulin (Sβ2M), serum albumin (ALB) and lactate dehydrogenase (LDH). ROC analysis also demonstrated the better performance for predicting 3-year OS. Functional enrichment analysis suggested that these four lncRNAs may be involved in known genetic and epigenetic events linked to MM.ConclusionsOur results demonstrated potential application of lncRNAs as novel independent biomarkers for diagnosis and prognosis in MM. These lncRNA biomarkers may contribute to the understanding of underlying molecular basis of MM.
| S-EPMC4567800 | biostudies-literature
Project description:Osteoporosis is a degenerative osteoarthropathy commonly found in old people and postmenopausal women. Many studies showed that microRNAs (miRNAs) can regulate the expression of osteoporosis-related genes and are abnormally expressed in patients with osteoporosis. miRNAs therefore have the potential to serve as biomarkers of osteoporosis. In this study, the limma package was used for the differential expression analysis of mRNA expression profiles and 357 significantly differentially expressed genes (DEGs) were obtained. Metascape was used for functional enrichment analysis of DEGs. The result revealed that DEGs were mainly enriched in signaling pathways like MAPK6/MAPK4. Based on the STRING database, the protein-protein interaction (PPI) network of DEGs was constructed. MCODE was used to analyze the functional subsets, and a key functional subset composed of 9 genes was screened out. In addition, the miRNA-mRNA regulatory interaction network (RegIN) was analyzed by the CyTargetLinker plugin, which generated 55 miRNA-mRNA regulatory interactions. Through literature searching, the osteoporosis-related gene FOXO1 in the key functional subset was determined to be the main object of the study. In qRT-PCR assay, the expression of the predicted miRNAs was tested in peripheral blood mononuclear cells of mice with osteoporosis, in which 13 miRNAs were remarkably highly expressed. All in all, this study, based on bioinformatics analysis and testing assay of miRNA expression, determined the potential biomarkers of osteoporosis.
| S-EPMC8579105 | biostudies-literature
Project description:N6-methyladenosine (m6A) regulators play an important role in tumorigenesis; however, their role in multiple myeloma (MM) remains unknown. This study aimed to create an m6A RNA regulators prognostic signature for MM patients. We integrated data from the Multiple Myeloma Research Foundation CoMMpass Study and the Genotype-Tissue Expression database to analyze gene expression profiles of 21 m6A regulators. Consistent clustering analysis was used to identify the clusters of patients with MM having different clinical outcomes. Gene distribution was analyzed using principal component analysis. Next, we generated an mRNA gene signature of m6A regulators using a multivariate logistic regression model with least absolute shrinkage and selection operator. The expressions of m6A regulators, except FMR1, were significantly different in MM samples compared with those in normal samples. The KIAA1429, HNRNPC, FTO, and WTAP expression levels were dramatically downregulated in tumor samples, whereas those of other signatures were remarkably upregulated. Three clusters of patients with MM were identified, and significant differences were found in terms of overall survival (p = .024). A prognostic two-gene signature (KIAA1429 and HNRNPA2B1) was constructed, which had a good prognostic significance using the ROC method (AUC = 0.792). Moreover, the risk score correlated with the infiltration immune cells. In addition, KEGG pathway analysis showed that 16 pathways were dramatically enriched. The m6A signature might be a novel biomarker for predicting the prognosis of patients with MM (p = .002). Our study is the first to explore the potential application value of m6A in MM. These findings may enhance the understanding of the functional organization of m6A in MM and provide new insights into the treatment of MM patients.
| S-EPMC10115423 | biostudies-literature
Project description:Abdominal aortic aneurysm (AAA) is a life-threatening disorder and, therefore, investigation into its underlying mechanisms in light of the competing endogenous RNAs (ceRNAs) hypothesis has gradually increased. However, there is still lacking systematic analysis on AAA-associated circular RNA (circRNA)-microRNA (miRNA/miR)-messenger RNA (mRNA) interaction networks based on bioinformatics methods. The present study attempted to identify novel molecular biomarkers for AAA by profiling circRNA-miRNA-mRNA networks using three public microarray datasets (GSE7084, GSE57691 and GSE144431). A total of 135 differentially expressed genes (DEGs) and 142 differentially expressed circRNAs were detected using the limma R package with the statistical threshold of P<0.05 and |log2fold change (FC)| >1.5. In addition, 12 circRNA-miRNA-mRNA axes were identified to construct upregulated and downregulated ceRNA networks using Cytoscape. Based on molecular complex detection algorithm, (hsa_circ_0057691/0092108/0006845/0082182)- miR-330-5p-calponin 1 (CNN1) and (hsa_circ_0061482/0011450/0008351/0004121)-miR-326-CD8a molecule (CD8A) were recognized as the center axes in ceRNA networks. Reverse transcription-quantitative PCR results verified the significant downregulation of CNN1 and upregulation of CD8A in human AAA tissues (P<0.05). In addition, four upregulated circRNA/mRNA axes, and five downregulated circRNA/mRNA axes were revealed to have possible biological functions in the pathogenesis of AAA using the Cytoscape software. Receiver operating characteristic analysis demonstrated the accuracy of these nine DEGs involved in these axes for AAA diagnosis with area under the curves >0.80. The present study revealed novel circRNA-miRNA-mRNA networks associated with AAA, especially for CNN1 and CD8A axes with the potential function of 'focal adhesion' and 'immune response', respectively. Overall, the present findings may provide evidence to explore the implicated ceRNAs in the molecular mechanisms and as novel biomarkers for AAA.
| S-EPMC8561771 | biostudies-literature
Project description:BackgroundThe underlying circular RNAs (circRNAs)-related competitive endogenous RNA (ceRNA) mechanisms of pathogenesis and prognosis in non-small cell lung cancer (NSCLC) remain unclear.MethodsDifferentially expressed circRNAs (DECs) in two Gene Expression Omnibus datasets (GSE101684 and GSE112214) were identified by utilizing R package (Limma). Circinteractome and StarBase databases were used to predict circRNA associated-miRNAs and mRNAs, respectively. Then, protein-protein interaction (PPI) network of hub genes and ceRNA network were constructed by STRING and Cytoscape. Also, analyses of functional enrichment, genomic mutation and diagnostic ROC were performed. TIMER database was used to analyze the association between immune infiltration and target genes. Kaplan-Meier analysis, cox regression and the nomogram prediction model were used to evaluate the prognostic value of target genes. Finally, the expression of potential circRNAs and target genes was validated in cell lines and tissues by quantitative real-time PCR (qRT-PCR) and Human Protein Atlas (HPA) database.ResultsIn this study, 15 DECs were identified between NSCLC tissues and adjacent-normal tissues in two GEO datasets. Following the qRT-PCR corroboration, 7 DECs (hsa_circ_0002017, hsa_circ_0069244, hsa_circ_026337, hsa_circ_0002346, hsa_circ_0007386, hsa_circ_0008234, hsa_circ_0006857) were dramatically downregulated in A549 and SK-MES-1 compared with HFL-1 cells. Then, 12 circRNA-sponged miRNAs were screened by Circinteractome and StarBase, especially, hsa-miR-767-3p and hsa-miR-767-5p were significantly up-regulated and relevant to the prognosis. Utilizing the miRDB and Cytoscape, 12 miRNA-target genes were found. Functional enrichment, genomic mutation and diagnostic analyses were also performed. Among them, FNBP1, AKT3, HERC1, COL4A1, TOLLIP, ARRB1, FZD4 and PIK3R1 were related to the immune infiltration via TIMER database. The expression of ARRB1, FNBP1, FZD4, and HERC1 was correlated with poor overall survival (OS) in NSCLC patients by cox regression and nomogram. Furthermore, the hub-mRNAs were validated in cell lines and tissues.ConclusionWe constructed the circRNA-miRNA-mRNA network that might provide novel insights into the pathogenesis of NSCLC and reveal promising immune infiltration and prognostic biomarkers.
| S-EPMC8605517 | biostudies-literature
Project description:MicroRNAs (miRNAs), regulatory noncoding RNAs, are involved in gene regulation and may play a role in cancer development. The aim of this study was to identify miRNAs involved in lung adenocarcinoma (LUAD) using bioinformatics analysis. MiRNA (GSE135918), mRNA (GSE136043) and lncRNA (GSE130779) microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed miRNAs (DEMis), mRNAs (DEMs), and lncRNA (DELs) in LUAD. We used DEMs for functional enrichment analysis. MiRNA expression quantification from The Cancer Genome Atlas (TCGA) was used to validate DEMis. LncBase Predicted v.2, Targetscan, and MiRBase were used to predict lncRNAs and mRNAs. The LUAD data in TCGA were used for overall survival (OS) analysis. We screened the downregulation of 8 DEMis and upregulation of 6 DEMis, and found that 70 signal pathways changed. We chose 3 relevant signaling pathways in lung cancer development, WNT, PI3K-Akt, and Notch, and scanned for mRNAs involved in them that are potential targets of these miRNAs. Then a lncRNA-miRNA-mRNA network was constructed. We also found 7 miRNAs that were associated with poor OS in LUAD. Low expression level of hsa-miR-30a was highly associated with poor OS in LUAD (P < .001) and the target genes of hsa-miR-30a-3p were abundant in the Wnt and AKT signaling pathways. In addition, our results reported for the first time that hsa-miR-3944 and hsa-miR-3652 were highly expressed in LUAD. And the high expression level of hsa-miR-3944 was associated with poor OS (P < .05). Hsa-miR-30a-3p may suppress the occurrence and progression of lung cancer through Wnt and AKT signaling pathways and become a good biomarker in LUAD. Hsa-miR-3944 and hsa-miR-3652 may serve as new biomarkers in LUAD.
| S-EPMC10980501 | biostudies-literature