Urinary microRNA biomarkers for detecting the presence of esophageal cancer.
Ontology highlight
ABSTRACT:
SUBMITTER: Okuda Y
PROVIDER: S-EPMC8058072 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Purpose: Gastric cancer (GC) is one of the most common causes of cancer deaths worldwide; however, reliable and non-invasive screening methods for GC are not established. Therefore, we conducted this study to develop a biomarker for GC detection, consisting of urinary microRNAs (miRNAs). Experimental Design: We matched 306 participants by age and sex (153 pairs consisting of patients with GC and healthy controls [HCs]), then randomly divided them across three groups: (1) the discovery cohort (4 pairs); (2) the training cohort (95 pairs); (3) the validation cohort (54 pairs). Moreover, 64 participants (32 pairs) with serum samples were also enrolled in the serum cohort. Result: There were 22 urinary miRNAs with significantly aberrant expressions between the two groups in the discovery cohort. Upon multivariate analysis of the training cohort, urinary expression levels of miR-6807-5p and miR-6856-5p were significantly independent biomarkers for diagnosis of GC, in addition to Helicobacter pylori (H. pylori) status. A diagnostic panel that combined the aberrant miRNAs and H. pylori status distinguished between HC and GC samples with an area under the curve (AUC) = 0.736. In the validation cohort, urinary miR-6807-5p and miR-6856-5p showed significantly higher expression levels in the GC group, and the combination biomarker panel of miR-6807-5p, miR-6856-5p, and H. pylori status also showed excellent performance (AUC = 0.885). In addition, serum levels of miR-6807-5p and miR-6856-5p were significantly higher in the GC group. Conclusion: This novel biomarker panel enables early and non-invasive detection of GC.
2019-12-22 | GSE128720 | GEO
Project description:MicroRNA (miRNA) plays vital roles in biological processes like RNA splicing and regulation of gene expression. Studies have revealed that there might be possible links between oncogenesis and expression profiles of some miRNAs, due to their differential expression between normal and tumor tissues. However, the automatic classification of miRNAs into different categories by considering the similarity of their expression values has rarely been addressed. This article proposes a solution framework for solving some real-life classification problems related to cancer, miRNA, and mRNA expression datasets. In the first stage, a multiobjective optimization based framework, non-dominated sorting genetic algorithm II, is proposed to automatically determine the appropriate classifier type, along with its suitable parameter and feature combinations, pertinent for classifying a given dataset. In the second page, a stack-based ensemble technique is employed to get a single combinatorial solution from the set of solutions obtained in the first stage. The performance of the proposed two-stage approach is evaluated on several cancer and RNA expression profile datasets. Compared to several state-of-the-art approaches for classifying different datasets, our method shows supremacy in the accuracy of classification.
| S-EPMC5828659 | biostudies-literature
Project description:A novel urinary microRNA biomarker panel for detecting gastric cancer
| PRJNA528633 | ENA
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:BACKGROUND:MicroRNA (miR)s are promising diagnostic biomarkers of cancer. Recent next generation sequencer (NGS) studies have found that isoforms of micro RNA (isomiR) circulate in the bloodstream similarly to mature micro RNA (miR). We hypothesized that combination of circulating miR and isomiRs detected by NGS are potentially powerful cancer biomarker. The present study aimed to investigate their application in esophageal cancer. METHODS:Serum samples from patients with esophageal squamous cell carcinoma (ESCC) and age and sex matched healthy control (HC) individuals were investigated for the expression of miR/isomiRs using NGS. Candidate miR/isomiRs which met the criteria in the 1st group (ESCC = 18 and HC = 12) were validated in the 2nd group (ESCC = 30 and HC = 30). A diagnostic panel was generated using miR/isomiRs that were consistently confirmed in the 1st and 2nd groups. Accuracy of the panel was tested then in the 3rd group (ESCC = 18 and HC = 18). Their use was also investigated in 22 paired samples obtained pre- and post-treatment, and in patients with esophageal adenocarcinoma (EAD) and high-grade dysplasia (HGD). RESULTS:Twenty-four miR/isomiRs met the criteria for diagnostic biomarker in the 1st and 2nd group. A multiple regression model selected one mature miR (miR-30a-5p) and two isomiRs (isoform of miR-574-3p and miR-205-5p). The index calculated from the diagnostic panel was significantly higher in ESCC patients than in the HCs (13.3±8.9 vs. 3.1±1.3, p<0.001). The area under the receiver operating characteristics (ROC) curves of the panel index was 0.95. Sensitivity and specificity were 93.8%, and 81% in the 1st and 2nd groups, and 88.9% and 72.3% in the 3rd group, respectively. The panel index was significantly lower in patients with EAD (6.2±4.5) and HGD (4.2±1.7) than in those with ESCC and was significantly decreased at post-treatment compared with pre-treatment (6.2±5.6 vs 11.6±11.5, p = 0.03). CONCLUSION:Our diagnostic panel had high accuracy in the diagnosis of ESCC. MiR/isomiRs detected by NGS could serve as novel biomarkers of ESCC.
| S-EPMC7135252 | biostudies-literature
Project description:MOTIVATION:Cancers arise as the result of somatically acquired changes in the DNA of cancer cells. However, in addition to the mutations that confer a growth advantage, cancer genomes accumulate a large number of somatic mutations resulting from normal DNA damage and repair processes as well as carcinogenic exposures or cancer related aberrations of DNA maintenance machinery. These mutagenic processes often produce characteristic mutational patterns called mutational signatures. The decomposition of a cancer genome's mutation catalog into mutations consistent with such signatures can provide valuable information about cancer etiology. However, the results from different decomposition methods are not always consistent. Hence, one needs to be able to not only decompose a patient's mutational profile into signatures but also establish the accuracy of such decomposition. RESULTS:We proposed two complementary ways of measuring confidence and stability of decomposition results and applied them to analyze mutational signatures in breast cancer genomes. We identified both very stable and highly unstable signatures, as well as signatures that previously have not been associated with breast cancer. We also provided additional support for the novel signatures. Our results emphasize the importance of assessing the confidence and stability of inferred signature contributions. AVAILABILITY AND IMPLEMENTATION:All tools developed in this paper have been implemented in an R package, called SignatureEstimation, which is available from https://www.ncbi.nlm.nih.gov/CBBresearch/Przytycka/index.cgi\#signatureestimation. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.
| S-EPMC5860213 | biostudies-literature
Project description:The steadily increasing incidence of kidney injury is a significant threat to human health. The current tools available for the early detection of kidney injury, however, have limited sensitivity or specificity. Thus, the development of novel biomarkers to detect early kidney injury is of high importance. Employing mouse renal ischemia-reperfusion and streptozotocin (STZ)-induced renal injury as acute and chronic kidney injury model, respectively, we assessed the alteration of microRNA (miRNA) in mouse urine, serum and kidney tissue by TaqMan probe-based qRT-PCR assay. Our results demonstrated that kidney-enriched microRNA-10a (miR-10a) and microRNA-30d (miR-30d) were readily detected in mouse urine and the levels of urinary miR-10a and miR-30d were positively correlated with the degree of kidney injury induced by renal ischemia-reperfusion or STZ diabetes. In contrast, no such alteration of miR-10a and miR-30d levels was observed in mouse serum after kidney injury. Compared with the blood urea nitrogen (BUN) assay, the test for urinary miR-10a and miR-30d levels was more sensitive for the detection of acute kidney injury. Furthermore, the substantial elevation of the urinary miR-10a and miR-30d levels was also observed in focal segmental glomerulosclerosis (FSGS) patients compared to healthy donors. In conclusion, the present study collectively demonstrates that urinary miR-10a and miR-30d represent a novel noninvasive, sensitive, specific and potentially high-throughput method for detecting renal injury.
| S-EPMC3521774 | biostudies-literature
Project description:BackgroundEsophageal adenocarcinoma (EAC) often presents at a late, incurable stage, and mortality has increased substantially, due to an increase in incidence of EAC arising out of Barrett's esophagus. When diagnosed early, however, the combination of surgery and adjuvant therapies is associated with high cure rates. Metabolomics provides a means for non- invasive screening of early tumor-associated perturbations in cellular metabolism.MethodsUrine samples from patients with esophageal carcinoma (n = 44), Barrett's esophagus (n = 31), and healthy controls (n = 75) were examined using (1)H-NMR spectroscopy. Targeted profiling of spectra using Chenomx software permitted quantification of 66 distinct metabolites. Unsupervised (principal component analysis) and supervised (orthogonal partial least-squares discriminant analysis OPLS-DA) multivariate pattern recognition techniques were applied to discriminate between samples using SIMCA-P(+) software. Model specificity was also confirmed through comparison with a pancreatic cancer cohort (n = 32).ResultsClear distinctions between esophageal cancer, Barrett's esophagus and healthy controls were noted when OPLS-DA was applied. Model validity was confirmed using two established methods of internal validation, cross-validation and response permutation. Sensitivity and specificity of the multivariate OPLS-DA models were summarized using a receiver operating characteristic curve analysis and revealed excellent predictive power (area under the curve = 0.9810 and 0.9627 for esophageal cancer and Barrett's esophagus, respectively). The metabolite expression profiles of esophageal cancer and pancreatic cancer were also clearly distinguishable with an area under the receiver operating characteristics curve (AUROC) = 0.8954.ConclusionsUrinary metabolomics identified discrete metabolic signatures that clearly distinguished both Barrett's esophagus and esophageal cancer from controls. The metabolite expression profile of esophageal cancer was also discrete from its precursor lesion, Barrett's esophagus. The cancer-specific nature of this profile was confirmed through comparison with pancreatic cancer. These preliminary results suggest that urinary metabolomics may have a future potential role in non-invasive screening in these conditions.
| S-EPMC3579706 | biostudies-literature
Project description:Early detection of acute kidney injury is difficult due to lack of known biomarkers; previous studies have tried to identify new biomarkers for detecting acute kidney injury at an early stage. MicroRNA, a 21-23 nucleotide noncoding RNA molecule, has emerged as a desirable marker in the diagnosis and prognosis of various diseases. This study aims to identify the expression profile of microRNA in ischemia-reperfusion-induced kidney injury and determine the possibility of using the candidate microRNA as biomarker for the detection of I/R-induced kidney injury. Based on the established rat model of I/R-induced kidney injury, a microarray analysis of rat urine was performed at the beginning of operation (0?h) as well as 72?h post operation. To validate the results, urine samples from 71 patients who underwent cardiac surgery were collected, after which urinalysis was conducted to determine the microRNA concentration. An alternative expression profile of microRNAs was detected in rat urine. The quantitative validation of microRNA showed that the expression of miR-30c-5p, miR-192-5p, and miR-378a-3p was elevated significantly in urine post operation, which was consistent with those of the microarray analysis and earlier than kidney injury molecule-1 (KIM-1). In patients with acute kidney injury, increased levels of miR-30c-5p and miR-192-5p were also detected 2 h post operation, and miR-30c-5p showed preferable diagnostic value compared with protein-based biomarkers. In conclusion, an aberrant expression profile of microRNA was detected in rat urine based on the established ischemia-reperfusion animal model. Both miR-30c-5p and miR-192-5p served as important potential diagnostic markers for I/R-induced kidney injury. Impact statement Firstly, one differentiating factor in our study is that the candidate miRNAs were screened in a controlled animal model rather than in patients with acute kidney injury (AKI) to ensure the purity of the cause of disease and to avoid possible effects of comorbidities on the spectrum of urine miRNA. This ensured the presence of only the relevant candidate miRNA (that associated with I/R injury); and what's more, the alterative expression of miR-192-5p and miR-30c-5p in animal model, patients with AKI, and cell model was confirmed simultaneously, which is likely to be more convincing. Secondly, the candidate miRNAs were screened sequentially at regular time points, which covered the initiation, progression, and partial repair stages, thus ensuring that no significant miRNAs were omitted in the screening process, and miR-biomarkers in 2?h post operation showed preferable diagnostic performance.
| S-EPMC5685255 | biostudies-literature
Project description:This paper describes a straightforward electrochemical method for rapid and robust urinary microRNA (miRNA) quantification using disposable biosensors that can discriminate between urine from diabetic kidney disease (DKD) patients and control subjects. Aberrant miRNA expression has been observed in several major human disorders, and we have identified a urinary miRNA signature for DKD. MiRNAs therefore have considerable promise as disease biomarkers, and techniques to quantify these transcripts from clinical samples have significant clinical and commercial potential. Current RT-qPCR-based methods require technical expertise, and more straightforward methods such as electrochemical detection offer attractive alternatives. We describe a method to detect urinary miRNAs using diazo sulfonamide-modified screen printed carbon electrode-based biosensors that is amenable to parallel analysis. These sensors showed a linear response to buffered miR-21, with a 17 fM limit of detection, and successfully discriminated between urine samples (n = 6) from DKD patients and unaffected control subjects (n = 6) by differential miR-192 detection. Our technique for quantitative miRNA detection in liquid biopsies has potential for development as a platform for non-invasive high-throughput screening and/or to complement existing diagnostic procedures in disorders such as DKD.
| S-EPMC8144888 | biostudies-literature