Ultrasound-Based Method for the Identification of Novel MicroRNA Biomarkers in Prostate Cancer.
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ABSTRACT:
SUBMITTER: Cornice J
PROVIDER: S-EPMC8619582 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:PurposeMicroRNAs (miRNAs), which could be stably preserved and detected in serum or plasma, could act as biomarkers in cancer diagnosis. Prostate cancer is the second cancer in males for incidence. This study aimed to establish a miRNA panel in peripheral serum which could act as a non-invasive biomarker helping diagnosing PC.MethodsA total of 86 PC patients and 86 normal control serum samples were analyzed through a four-stage experimental process using quantitative real-time polymerase chain reaction. Logistic regression method was used to construct a diagnostic model based on the differentially expressed miRNAs in serum. Receiver operating characteristic curves were constructed to evaluate the diagnostic accuracy. We also compared the 3-miRNA panel with previously reported biomarkers and verified in four public datasets. In addition, the expression characteristics of the identified miRNAs were further explored in tissue and serum exosomes samples.ResultsWe identified a 3-miRNA signature including up-regulated miR-146a-5p, miR-24-3p and miR-93-5p for PC detection. Areas under the receiver operating characteristic curve of the 3-miRNA panel for the training, testing and external validation phase were 0.819, 0.831 and 0.814, respectively. The identified signature has a very stable diagnostic performance in the large cohorts of four public datasets. Compared with previously identified miRNA biomarkers, the 3-miRNA signature in this study has superior performance in diagnosing PC. What's more, the expression level of miR-93-5p was also elevated in exosomes from PC samples. However, in PC tissues, none of the three miRNAs showed significantly dysregulated expression.ConclusionsWe established a three-miRNA panel (miR-146a-5p, miR-24-3p and miR-93-5p) in peripheral serum which could act as a non-invasive biomarker helping diagnosing PC.
| S-EPMC8141284 | biostudies-literature
Project description:BackgroundThe current methods adopted to screen for prostate cancer (PCa) can sometimes be misleading and inaccurate. Moreover, for advanced stages of PCa, the current effect of treatment is not satisfactory for some patients. Accordingly, we aimed to identify new biomarkers for the diagnosis and prognosis of PCa.MethodsA series of bioinformatic tools were utilized to search for potential new biomarkers of PCa and analyze their functions, expression, clinical relevance, prognostic value, and underlying mechanisms.ResultsAlthough ASPN was overexpressed in PCa, EDN3, PENK, MEIS2, IGF1, and CXCL12 were downregulated. The univariate Cox regression analysis showed that abnormally high expression of ASPN and low expression of other genes predicted worse prognosis. Moreover, the multivariate Cox regression analysis showed that ASPN, PENK, and MEIS2 were independently associated with the overall survival (OS) of patients, whereas other markers were not. The outcomes of gene ontology and gene set enrichment analysis showed that the expression levels of these genes might be associated with cell proliferation and infiltration of immune cells in PCa.ConclusionsWe demonstrated that ASPN, EDN3, PENK, MEIS2, IGF1, and CXCL12 are possibly novel diagnostic indicators for PCa, whereas ASPN, PENK, and MEIS2 show appealing potential to predict the prognosis of this disease.
| S-EPMC8421833 | biostudies-literature
Project description:BACKGROUND: MicroRNAs (miRNAs) are potential regulators that contribute to the pathogenesis of cancer. Microarray technologies have been widely used to characterize aberrant miRNA expression patterns in cancer. Nevertheless, the miRNAs expression signatures identified for a same cancer differs among laboratories due to the cancer heterogeneity. In addition, how the deregulated miRNAs coordinately contribute to the tumourigenic process of prostate cancer remains elusive. RESULTS: We evaluated five outlier detection algorithms that take into account the heterogeneity of cancer samples. ORT was selected as the best method and applied to four prostate cancer associated microRNA expression datasets. After microRNA target prediction and pathway enrichment mapping, 38 Gene Ontology terms, 16 KEGG pathways and 99 GeneGO pathways are found putative prostate cancer associated. Comparison with our previous studies, we identified two putative novel pathways important in prostate cancer. The two novel pathways are 1) ligand-independent activation of ESR1 and ESR2 and 2) membrane-bound ESR1: interaction with growth factors signalling. CONCLUSIONS: We proved that expression signatures of at the pathway level well address the cancer heterogeneity and are more consistent than at the miRNA/gene levels. Based on this observation, we identified putative novel microRNA regulatory pathways which will help us to elucidate the cooperative function of different microRNAs in prostate cancer.
| S-EPMC3852103 | biostudies-literature
Project description:Background: Therapy-related neuroendocrine prostate cancer (NEPC) is a lethal castration-resistant prostate cancer (CRPC) subtype that, at present, lacks well-characterized molecular biomarkers. The clinical diagnosis of this disease is dependent on biopsy and histological assessment: methods that are experience-based and easily misdiagnosed due to tumor heterogeneity. The development of robust diagnostic tools for NEPC may assist clinicians in making medical decisions on the choice of continuing anti-androgen receptor therapy or switching to platinum-based chemotherapy. Methods: Gene expression profiles and clinical characteristics data of 208 samples of metastatic CRPC, including castration-resistant prostate adenocarcinoma (CRPC-adeno) and castration-resistant neuroendocrine prostate adenocarcinoma (CRPC-NE), were obtained from the prad_su2c_2019 dataset. Weighted Gene Co-expression Network Analysis (WGCNA) was subsequently used to construct a free-scale gene co-expression network to study the interrelationship between the potential modules and clinical features of metastatic prostate adenocarcinoma and to identify hub genes in the modules. Furthermore, the least absolute shrinkage and selection operator (LASSO) regression analysis was used to build a model to predict the clinical characteristics of CRPC-NE. The findings were then verified in the nepc_wcm_2016 dataset. Results: A total of 51 co-expression modules were successfully constructed using WGCNA, of which three co-expression modules were found to be significantly associated with the neuroendocrine features and the NEPC score. In total, four novel genes, including NPTX1, PCSK1, ASXL3, and TRIM9, were all significantly upregulated in NEPC compared with the adenocarcinoma samples, and these genes were all associated with the neuroactive ligand receptor interaction pathway. Next, the expression levels of these four genes were used to construct an NEPC diagnosis model, which was successfully able to distinguish CRPC-NE from CRPC-adeno samples in both the training and the validation cohorts. Moreover, the values of the area under the receiver operating characteristic (AUC) were 0.995 and 0.833 for the training and validation cohorts, respectively. Conclusion: The present study identified four specific novel biomarkers for therapy-related NEPC, and these biomarkers may serve as an effective tool for the diagnosis of NEPC, thereby meriting further study.
| S-EPMC8503838 | biostudies-literature
Project description:Our recent study identified a list of differentially expressed microRNAs (miRNAs) in human prostate cancer (PCa) tissues compared to adjacent benign prostate tissues. In the current study, to identify the crucial miRNA-mRNA regulatory biomodule involved into prostate carcinogenesis based on the previous miRNA expression profile in PCa, we proposed an integrated systematic approach which combined miRNA-mediated gene expression regulatory network analysis, experimental validations in vitro and in vivo, as well as clinical significance evaluation. As a result, the CCND1-RNASEL-CDKN1A-TP73-MDM2-UBE2I axis was identified as a bottleneck in the miRNA-mediated gene expression regulatory network of PCa according to network topological analysis. The direct binding relationship between TP73 and PCa downregulated miR-193a-5p, and the direct binding relationship between UBE2I and PCa upregulated miR-188-5p were both experimentally validated. In addition, miR-193a-5p had a more significant regulatory effect on the tumor promoter isoform of TP73-deltaNp73 than on the tumor suppressive isoform of TP73-TAp73. Importantly, the deregulation of either the miR-193a-5p-TP73 or miR-188-5p-UBE2I axes was significantly associated with aggressive progression and poor prognosis in PCa patients. Gain- and loss-of-function experiments showed that miR-193a-5p efficiently inhibited in vitro PCa cell proliferation, migration, and invasion, and in vivo tumor growth, and markedly induced PCa cell apoptosis via regulating TP73 with a corresponding suppression of the CCND1-RNASEL-CDKN1A-MDM2 axis. In contrast, miR-188-5p exerted its tumor promoter roles through targeting UBE2I with a subsequent activation of the CCND1-RNASEL-CDKN1A-MDM2 axis. Taken together, this integrated analysis revealed the potential roles of the miR-193a-5p/TP73 and miR-188-5p/UBE2i negative regulation pairs in PCa. In addition to the significant clinical relevance, miR-193a-5p- and miR-188-5p-regulated CCND1-RNASEL-CDKN1A-TP73-MDM2-UBE2I signaling may be a novel regulatory biomodule in prostate carcinogenesis.
| S-EPMC5833360 | biostudies-literature
Project description:MicroRNAs (miRNAs/miRs) regulate the expression of target genes and are considered to be associated with human cancer. The aim of the present study was to screen novel miRNA biomarkers in esophageal cancer (EC). The miRNA expression profile GSE41268 was extracted from Gene Expression Omnibus database, and differentially expressed miRNAs between whole saliva samples from patients with EC and healthy controls were identified using the Linear Models for Microarray Data package. Then, the targets of these miRNAs were screened using the miRecords database and used to construct the regulatory network. Gene ontology and pathway enrichment analyses were performed for the target genes of differentially expressed miRNAs to predict their potential functions. A total of 18 differentially expressed miRNAs were identified in saliva samples from patients with EC, and 43 validated target genes corresponding to 7 upregulated miRNAs were identified. Then, 6 miRNAs (miR-144, miR-451, miR-98, miR-10b, miR-486-5p and miR-363) and their target genes were used to construct a regulatory network. Within the network, miR-144 may target Notch homolog 1, fibrinogen α chain and fibrinogen β chain; miR-451 may regulate murine thymoma viral oncogene homolog 1, matrix metalloproteinase (MMP)9 and MMP2; miR-98 may directly target E2F transcription factor (E2F) 1, E2F2 and v-myc avian myelocytomatosis viral oncogene homolog (MYC); miR-10b may modulate peroxisome proliferator-activated receptor α and Kruppel-like factor 4; miR-485-5p and miR-363 may regulate TNF receptor superfamily member 5 and cyclin-dependent kinase inhibitor 1A. In addition, E2F1, E2F2 and MYC were associated with the cell cycle, which was the most significantly enriched function and pathway in EC. The results of the present study suggested that miR-144, miR-451, miR-98, miR-10b and miR-363 may be involved in EC by regulating their target genes, and may be used as biomarkers for EC.
| S-EPMC5529882 | biostudies-other
Project description:The clinical course of prostate cancer (PCa) is highly variable, demanding an individualized approach to therapy and robust prognostic markers for treatment decisions. We here present a random forest-based classification model to predict aggressive behaviour of PCa. DNA methylation changes between PCa cases with good or poor prognosis (discovery cohort with n=78) were used as input. The model was validated with data from two independent PCa cohorts from ICGC and TCGA. Ranking of cancer progression-related DNA methylation changes allowed selection of candidate genes for additional validation by immunohistochemistry. We identified loss of ZIC2 protein expression as a promising novel prognostic biomarker for PCa in >12,000 tissue micro-array tumors. The prognostic value of ZIC2 proved to be independent from established clinico-pathological variables including Gleason, stage, nodal stage and PSA. In summary, we have developed a PCa classification model which either directly or via expression analyses of the identified top ranked candidate genes might help in decision making related to the treatment of prostate cancer patients.
2019-10-29 | GSE127985 | GEO
Project description:The lack of efficient biomarkers is the main reason for the inaccurate early diagnosis and poor treatment outcomes of patients with metabolic syndrome (MetS). The current study aimed to identify several novel microRNA (miRNA) biomarkers for metabolic syndrome via high-throughput sequencing and comprehensive bioinformatics analysis. Through high-throughput sequencing and differentially expressed miRNA (DEM) analysis, we first identified two upregulated and 36 downregulated DEMs in the plasma samples of patients with MetS compared to the healthy volunteers. Additionally, we also predicted 379 potential target genes and subsequently carried out enrichment analysis and protein-protein interaction network analysis to investigate the signaling pathways and functions of the identified DEMs as well as the interactions between their target genes. Furthermore, we selected two upregulated and top 10 downregulated DEMs with the highest |log2FC| values as the key microRNAs, which may serve as potential biomarkers for MetS. RT-qPCR was performed to validated these result. Finally, hsa-miR-526b-5p, hsa-miR-6516-5p was identified as the novel biomarkers for MetS.
| S-EPMC8806888 | biostudies-literature
Project description:Accumulating evidence indicates that human circulating microRNAs (miRNAs) could serve as diagnostic and prognostic biomarkers in various cancers. We aimed to explore novel miRNA biomarkers in the blood of breast cancer patients based on miRNA profiling. A miRCURY™ LNA Array was used to identify differentially altered miRNAs in the whole blood of breast cancer patients (n = 6) and healthy controls (n = 6). Levels of candidate miRNAs were quantified by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) in whole blood specimens of 15 breast cancer patients and 13 age-matched healthy control individuals. The miRWalk database was used to predict miRNA targets and the DAVID tool was used to identify significant enrichment pathways. A total of 171 differentially expressed miRNAs were identified by microarray, including 169 up-regulated and 2 down-regulated miRNAs in breast cancer. Five upregulated miRNAs (miR-30b-5p, miR-96-5p, miR-182-5p, miR-374b-5p, and miR-942-5p) were confirmed by qRT-PCR. The areas under the receiver operating characteristic curve of miR-30b-5p, miR-96-5p, miR-182-5p, miR-374b-5p, and miR-942-5p were 0.9333, 0.7692, 0.7590, 0.8256, and 0.8128, respectively. A total of 855 genes were predicted to be targeted by the five miRNAs, and the one cut domain family member 2 gene (ONECUT2) was a shared target of the five miRNAs. Analysis of publicly available data revealed that these dysregulated miRNAs and target genes were associated with the survival of breast cancer patients. Furthermore, the five miRNAs were significantly enriched in numerous cancer-related pathways, including “MicroRNAs in cancer”, “Pathways in cancer”, “FoxO signaling pathway”, “Ras signaling pathway”, “Rap1 signaling pathway”, “MAPK signaling pathway”, and “PI3K-Akt signaling pathway”. Our data support the potential of the five identified miRNAs as novel biomarkers for the detection of breast cancer, and indicate that they may be involved in breast cancer development and progression.
2017-06-28 | GSE83270 | GEO
Project description:Introduction:Prostate cancer is a heterogeneous disease. Existing risk stratification tools based on standard clinlicopathologic variables (prostate specific antigen [PSA], Gleason score, and tumor stage) provide a modest degree of predictive ability. Advances in high-throughput sequencing has led to the development of several novel tissue-based biomarkers that can improve prognostication in prostate cancer management. Areas Covered:The authors review commercially-available, tissue-based biomarker assays that improve upon existing risk-stratification tools in several areas of prostate cancer management, including the appropriateness of active surveillance and aiding in decision making regarding the use of adjuvant therapy. Additionally, some of the obstacles to the widespread adoption of these biomarkers and discuss several investigational sources of new biomarkers are discussed. Expert Commentary:Work is ongoing to answer pertinent clinical questions in prostate cancer management including which patients should undergo biopsy, active surveillance, receive adjuvant therapy, and what systemic therapy is best in the first-line. Incorporation into novel biomarkers may allow for the incorporation of a 'personalized' approach to management. Further validation will be required and questions of cost must be considered before wide scale adoption of these biomarkers. Tumor heterogeneity may impose a ceiling on the prognostic ability of biomarkers using currently available techniques.
| S-EPMC5722240 | biostudies-literature