A panel of eight-miRNA signature as a potential biomarker for predicting survival in bladder cancer.
ABSTRACT: There is increasing evidence to suggest that miRNAs play an important role in predicting cancer survival. To identify a panel of miRNA signature that can divided tumor from normal bladder using miRNA expression levels, and to assess the prognostic value of this specific miRNA markers in bladder cancer (BCa).A comprehensive meta-review of published miRNA expression profiles that compared BCa and adjacent normal tissues was performed to determine candidate miRNAs as prognostic biomarkers for BCa. Vote-counting strategy and Robust Rank Aggregation method were used to identify significant meta-signature miRNAs.We identified an eight-miRNA signature including three upregulated (miR-141, miR-200c, miR-21) and five downregulated (miR-145, miR-125, miR-199a, let-7c and miR-99a) miRNAs for the prediction of overall survival (OS) using TCGA dataset, and validated in our 48 BCa patients. X-tile plot was used to generate the optimum cut-off point and Kaplan-Meier method was used to calculate OS. A linear prognostic model of eight miRNAs was constructed and weighted by the importance scores from the supervised principal component method to divide patients into high- and low-risk groups. Patients assigned to the high-risk group were associated with poor OS compared with patients in the low-risk group (HR = 5.21, p < 0.001). Our validation cohort of 48 patients confirmed the panel of 8-miRNAs as a reliable prognostic tool for OS in patients with BCa (HR = 5.04, p < 0.001).The present meta-analysis identified eight highly significant and consistently dysregulated miRNAs from 19 datasets. We also constructed an eight-miRNA signature which provided predictive and prognostic value that complements traditional clinicopathological risk factors.
Project description:BACKGROUND: Lung adenocarcinoma is a heterogernous disease that creates challenges for classification and management. The purpose of this study is to identify specific miRNA markers closely associated with the survival of LUAD patients from a large dataset of significantly altered miRNAs, and to assess the prognostic value of this miRNA expression profile for OS in patients with LUAD. METHODS: We obtained miRNA expression profiles and corresponding clinical information for 372 LUAD patients from The Cancer Genome Atlas (TCGA), and identified the most significantly altered miRNAs between tumor and normal samples. Using survival analysis and supervised principal components method, we identified an eight-miRNA signature for the prediction of overall survival (OS) of LUAD patients. The relationship between OS and the identified miRNA signature was self-validated in the TCGA cohort (randomly classified into two subgroups: n?=?186 for the training set and n?=?186 for the testing set). Survival receiver operating characteristic (ROC) analysis was used to assess the performance of survival prediction. The biological relevance of putative miRNA targets was also analyzed using bioinformatics. RESULTS: Sixteen of the 111 most significantly altered miRNAs were associated with OS across different clinical subclasses of the TCGA-derived LUAD cohort. A linear prognostic model of eight miRNAs (miR-31, miR-196b, miR-766, miR-519a-1, miR-375, miR-187, miR-331 and miR-101-1) was constructed and weighted by the importance scores from the supervised principal component method to divide patients into high- and low-risk groups. Patients assigned to the high-risk group exhibited poor OS compared with patients in the low-risk group (hazard ratio [HR]?=?1.99, P <0.001). The eight-miRNA signature is an independent prognostic marker of OS of LUAD patients and demonstrates good performance for predicting 5-year OS (Area Under the respective ROC Curves [AUC]?=?0.626, P?=?0.003), especially for non-smokers (AUC?=?0.686, P?=?0.023). CONCLUSIONS: We identified an eight-miRNA signature that is prognostic of LUAD. The miRNA signature, if validated in other prospective studies, may have important implications in clinical practice, in particular identifying a subgroup of patients with LUAD who are at high risk of mortality.
Project description:MicroRNAs(miRNAs) are involved in the formation, maintenance, and metastasis of urologic cancer. Here, we aim to gather and evaluate all of the evidence regarding the potential role of miRNAs as novel predictors of urologic cancer survival.A systematic review was performed to identify and score all of the published studies that evaluated the prognostic effects of miRNAs in kidney (KCa), bladder (BCa) or prostate cancer (PCa). Where appropriate, the summary effects of miRNAs on urologic cancer were meta-analysed. The reliability of those results was then further validated by an integrated analysis of the TCGA cohort and miRNA panel.Of 151 datasets, 80 miRNAs were enrolled in this systematic review. A meta-analysis of the prognostic qualities of each miRNA identified an objective association between miRNA and prognosis. miR-21 was identified as an unfavourable miRNA with the overall survival (HR:2.699, 1.76-4.14, P?<?0.001) across various prognostic events. Our further meta-analyses, integrating a parallel TCGA analysis, confirmed these partial previous results and further revealed different summary effects, such as the moderate effect of miR-21 in BCa. The refined miRNA panel (KCa-6: miR-27b, -942, -497, -144, -141 and -27a) was more capable of predicting the overall survival than was any single miRNAs included in it (HR: 3.214, 1.971-5.240, P?<?0.01).A miRNA panel may be able to determine the prognosis of urologic tumour more effectively and compensate for the unreliability of individual miRNA in estimating prognosis. More large-scale studies are therefore required to evaluate the unbiased prognostic value of miRNAs in urologic cancer effectively.
Project description:Background Glioma is the most common form of primary malignant intracranial tumor. Methods In the current study, miRNA matrix were obtained from the Chinese Glioma Genome Atlas (CGGA), and then univariate Cox regression analysis and Lasso regression analysis were utilized to select candidate miRNAs and multivariate Cox regression analysis was applied to establish a miRNA signature for predicting overall survival (OS) of glioma. The signature was assessed with the area under the curve (AUC) of the receiver operating characteristic curve (ROC) and validated by data from Gene Expression Omnibus (GEO). Results Eight miRNAs (miR-1246, miR-148a, miR-150, miR-196a, miR-338-3p, miR-342-5p, miR-548h and miR-645) were included in the miRNA signature. The AUC of ROC analysis for 1- and 3-year OS in the CGGA dataset was 0.747 and 0.905, respectively. In the GEO dataset, The AUC for 1- and 3-year was 0.736 and 0.809, respectively. The AUC in both the CGGA and GEO datasets was similar to that based on WHO 2007 classification (0.736 and 0.799) and WHO 2016 classification (0.663 and 0.807). Additionally, Kaplan–Meier plot revealed that high-risk score patients had a poorer clinical outcome. Multivariate Cox regression analysis suggested that the miRNA signature was an independent prognosis-related factor [HR: 6.579, 95% CI [1.227?35.268], p = 0.028]. Conclusion On the whole, in the present study, based on eight miRNAs, a novel prognostic signature was developed for predicting the 1- and 3- year survival rate in glioma. The results may be conducive to predict the precise prognosis of glioma and to elucidate the underlying molecular mechanisms. However, further experimental researches of miRNAs are needed to validate the findings of this study.
Project description:Recent microRNA (miRNA) expression profiling studies suggest the clinical use of miRNAs as potential prognostic biomarkers in various malignancies. In this study, aiming to identify microRNAs with prognostic value for overall survival (OS) in stomach adenocarcinoma (STAD) patients, we analyzed the miRNA expression profiles and the associated clinical characteristics in 380 STAD samples from The Cancer Genome Atlas (TCGA) dataset. An eight-miRNA signature for predicting OS in STAD patients was identified and self-validated by survival analysis and semi-supervised principal components method. We developed a linear prognostic model composed of these miRNAs to divide patients into high- and low-risk groups according to the calculated prognostic scores. Kaplan-Meier analysis demonstrated that patients in the high-risk group had worse OS compared with patients in the low-risk group. Notably, this miRNA prognostic model showed prognostic significance to the STAD patients in early stages and the chemo-resistant patients, who would potentially benefit from additional medical interventions. Finally, this eight-miRNA signature is an independent prognostic biomarker and demonstrates a good predictive performance for 5-year survival. Thus, this signature may serve as a novel biomarker for predicting survival as well as chemotherapy response in STAD patients.
Project description:Background: Clear cell renal cell carcinoma (ccRCC) is the most prevalent histologic subtype of kidney cancers in adults, which could be divided into two distinct subgroups according to the BRCA1 associated protein-1 (BAP1) mutation status. In the current study, we comprehensively analyzed the genome-wide microRNA (miRNA) expression profiles in ccRCC, with the aim to identify the differentially expressed miRNAs between BAP1 mutant and wild-type tumors, and generate a BAP1 mutation-specific miRNA signature for ccRCC patients with wild-type BAP1. Methods: The BAP1 mutation status and miRNA profiles in BAP1 mutant and wild-type tumors were analyzed. Subsequently, the association of the differentially expressed miRNAs with patient survival was examined, and a BAP1 mutation-specific miRNA signature was generated and examined with Kaplan-Meier survival, univariate and multivariate Cox regression analyses. Finally, the bioinformatics methods were adopted for the target prediction of selected miRNAs and functional annotation analyses. Results: A total of 350 treatment-naïve primary ccRCC patients were selected from The Cancer Genome Atlas project, among which 35 (10.0%) subjects carried mutant BAP1 and had a shorter overall survival (OS) time. Furthermore, 33 miRNAs were found to be differentially expressed between BAP1 mutant and wild-type tumors, among which 11 (miR-149, miR-29b-2, miR-182, miR-183, miR-21, miR-365-2, miR-671, miR-365-1, miR-10b, miR-139, and miR-181a-2) were significantly associated with OS in ccRCC patients with wild-type BAP1. Finally, a BAP1 mutation-specific miRNA signature consisting of 11 miRNAs was generated and validated as an independent prognostic parameter. Conclusions: In summary, our study identified a total of 33 miRNAs differentially expressed between BAP1 mutant and wild-type tumors, and generated a BAP1 mutation-specific miRNA signature including eleven miRNAs, which could serve as a novel prognostic biomarker for ccRCC patients with wild-type BAP1.
Project description:Objective: Using genome-wide screening, this study was aimed at identifying prognostic microRNA (miRNA) in those patients suffering from stomach adenocarcinoma (STAD). Methods: A genome-wide miRNA sequencing dataset and relevant STAD clinical information was obtained via The Cancer Genome Atlas (TCGA). Prognostic miRNA selection was carried out through a whole genome multivariate Cox regression model in order to establish a prognostic STAD signature. Results: Eleven miRNAs (hsa-mir-509-2, hsa-mir-3917, hsa-mir-495, hsa-mir-653, hsa-mir-3605, hsa-mir-2115, hsa-mir-1292, hsa-mir-137, hsa-mir-6511b-1, hsa-mir-145, and hsa-mir-138-2) were recognized as prognostic and used for the construction of a STAD prognostic signature. This signature exhibited good performance in predicting prognosis (adjusted P<0.0001, adjusted hazard ratio= 3.047, and 95% confidence interval=2.148-4.323). The time-dependent receiver operating characteristic examination exhibited area under curve values of 0.711, 0.697, 0.716, 0.733, 0.805, and 0.805, for 1-, 2-, 3-, 4-, 5-, and 10-year overall survival (OS) estimation, respectively. Comprehensive survival analysis suggests that the 11-miRNA prognostic signature acts as an independent feature of STAD prognosis and exhibits superior performance in OS prediction when compared to traditional clinical parameters. Furthermore, fourteen miRNA target genes were linked to STAD OS. These included SERPINE1, MLEC, ANGPT2, C5orf38, FZD7, MARCKS, PDGFD, DUSP6, IRS1, PSAT1, TENM3, TMEM127, BLMH, and TIRAP. Functional and gene set enrichment analysis suggested that target genes and the 11-miRNA prognostic signature were both participate in various biological processes and pathways, including the growth factor beta, Wnt, and Notch signaling pathways. Conclusions: By means of a genome-wide analysis, an 11-miRNA expression signature that may serve as an underlying prognostic indicator for those patients suffering from STAD has been identified and described here.
Project description:MicroRNAs(miRNAs), as non-coding molecules, were proved to be correlated with gene expression in naspharyngeal carcinoma (NPC) development. In this research, a comprehensive meta-analysis of eight independent miRNA expression studies in NPC was preformed by using robust rank aggregation method (RRA), which contained a total of 775 tumor and 227 non-cancerous samples. There were 7 significant dysregulated miRNAs identified including three increased (miR-483-5p, miR-29c-3p and miR-205-5p) and four decreased (miR-29b-3p, let-7d-5p, miR-100- 5p and let-7g-5p) miRNAs. Subsequently, the miRNA target prediction and pathway enrichment analysis were carried out to find out the biological and functional relevant genes involved in the meta-signature miRNA regulation. Finally, several signaling and cancer pathogenesis pathways were suggested to be more frequently associated with the progression of NPC. In this research the meta-signature miRNA identified may be used to develop a series of diagnostic and prognostic biomarkers for NPC that serve specificity for use in clinics.
Project description:Clear cell renal cell carcinoma (ccRCC) still remains a higher mortality rate in worldwide. Obtaining promising biomakers is very crucial for improving the diagnosis and prognosis of ccRCC patients. Herein, we firstly identified eight potentially prognostic miRNAs (hsa-miR-144-5p, hsa-miR-223-3p, hsa-miR-365b-3p, hsa-miR-3613-5p, hsa-miR-9-5p, hsa-miR-183-5p, hsa-miR-335-3p, hsa-miR-1269a). Secondly, we found that a signature containing these eight miRNAs showed obviously superior to a single miRNA in the prognostic effect and credibility for predicting the survival of ccRCC patients. Thirdly, we discovered that twenty-two transcription factors (TFs) interact with these eight miRNAs, and a signature combining nine TFs (TFAP2A, KLF5, IRF1, RUNX1, RARA, GATA3, IKZF1, POU2F2, and FOXM1) could promote the prognosis of ccRCC patients. Finally, we further identified eleven genes (hsa-miR-365b-3p, hsa-miR-223-3p, hsa-miR-1269a, hsa-miR-144-5p, hsa-miR-183-5p, hsa-miR-335-3p, TFAP2A, KLF5, IRF1, MYC, IKZF1) that could combine as a signature to improve the prognosis effect of ccRCC patients, which distinctly outperformed the eight-miRNA signature and the nine-TF signature. Overall, we identified several new prognosis factors for ccRCC, and revealed a potential mechanism that TFs and miRNAs interplay cooperatively or oppositely regulate a certain number of tumor suppressors, driver genes, and oncogenes to facilitate the survival of ccRCC patients.
Project description:Malignant pleural mesothelioma (MPM) is an aggressive tumor with a dismal overall survival (OS) and to date no molecular markers are available to guide patient management. This study aimed to identify a prognostic miRNA signature in MPM patients who did not undergo tumor resection. Whole miRNA profiling using a microarray platform was performed using biopsies on 27 unresected MPM patients with distinct clinical outcome: 15 patients had short survival (OS<12 months) and 12 patients had long survival (OS>36 months). Three prognostic miRNAs (mir-99a, let-7c, and miR-125b) encoded at the same cluster (21q21) were selected for further validation and tested on publicly available miRNA sequencing data from 72 MPM patients with survival data. A risk model was built based on these 3 miRNAs that was validated by quantitative PCR in an independent set of 30 MPM patients. High-risk patients had shorter median OS (7.6 months) as compared with low-risk patients (median not reached). In the multivariate Cox model, a high-risk score was independently associated with shorter OS (HR=3.14; 95% CI, 1.18-8.34; P=0.022). Our study identified that the downregulation of the miR-99a/let-7/miR-125b miRNA cluster predicts poor outcome in unresected MPM.
Project description:Novel biomarkers for pancreatic adenocarcinoma are urgently needed because of its poor prognosis. Here, by using The Cancer Genome Atlas (TCGA) RNA-seq data, we evaluated the prognostic values of the differentially expressed miRNAs and constructed a five-miRNA signature that could effectively predict patient overall survival (OS). The Kaplan-Meier overall survival curves of two groups based on the five miRNAs were notably different, showing overall survival in 10.2% and 47.8% at five years for patients in high-risk and low-risk groups, respectively. The ROC curve analysis achieved AUC of 0.775, showing good sensitivity and specificity of the five-miRNA signature model in predicting pancreatic adenocarcinoma patient survival risk. The functional enrichment analysis suggested that the target genes of the miRNA signature may be involved in various pathways related to cancer, including PI3K-Akt, TGF-?, and pluripotent stem cell signaling pathways. Finally, we analyzed expression of the five specific miRNAs in the miRNA signature, and validated the reliability of the results in 20 newly diagnosed pancreatic adenocarcinoma patients using qRT-PCR. The expression results of qRT-PCR were consistent with the TCGA results. Taken together, these findings suggested that the five-miRNA signature (hsa-miR-203, hsa-miR-424, hsa-miR-1266 hsa-miR-1293, and hsa-miR-4772) could be used as a prognostic marker for pancreatic adenocarcinoma.