Circulating miRNA panels for specific and early detection in bladder cancer
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ABSTRACT:
PROVIDER: PRJNA451225 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:A serum miRNA combination could be a powerful classifier for the detection of patients with bladder cancer.
2018-11-06 | GSE113486 | GEO
Project description:Bladder cancer is the 9th leading cause of cancer death worldwide. The major problem in bladder cancer is primarily the high recurrence rate after drug treatment and resection. Although conventional screening methods, such as cystoscopy, urinary cytology and ultrasound sonography, have become widely used in clinical settings, the diagnostic performance of these modalities is unsatisfactory due to low accuracy or high invasiveness. Because circulating micro RNA (miRNA) profiles have recently been reported as an attractive tool for liquid biopsy in cancer screening, here, we performed global miRNA profiling of 392 serum samples of bladder cancer patients with 100 non-cancer samples and 480 samples of other types of cancer as controls. We randomly classified the bladder cancer and control samples into 2 cohorts, a training set (N = 486) and a validation set (N = 486). By comparing both controls, we identified specific miRNA, such as miR-6087, for diagnosing bladder cancer in the training and validation sets. Furthermore, we found that a combination of 7 miRNA (7-miRNA panel: miR-6087, miR-6724-5p, miR-3960, miR-1343-5p, miR-1185-1-3p, miR-6831-5p and miR-4695-5p) could discriminate bladder cancer from non-cancer and other types of tumors with the highest accuracy (AUC: .97; sensitivity: 95%; specificity: 87%). The diagnostic accuracy was high, regardless of the stage and grade of bladder cancer. Our data demonstrated that the 7-miRNA panel could be a biomarker for the specific and early detection of bladder cancer.
| S-EPMC6317958 | biostudies-literature
Project description:Plasma samples from 100 early stage (I to IIIA) non–small-cell lung cancer (NSCLC) patients and 100 non-cancer controls were screened for 754 circulating microRNAs via qRT-PCR, using TaqMan MicroRNA Arrays. Our objective was to identify a panel of circulating microRNAs in plasma that will contribute to early detection of lung cancer.
2015-12-31 | GSE64591 | GEO
Project description:Objective was to identify urine cell-free microRNAs enabling early non-invasive detection of bladder cancer. Total RNA enriched for fraction of short RNAs was isolated using Urine microRNA purification kit (Norgen corp.). miRNA profiles were determined using the Affymetrix GeneChip miRNA 3.0 array and analyzed to identify differentially deregulated miRNA in bladder cancer patients compared with helathy controls.
2017-10-29 | E-MTAB-6102 | biostudies-arrayexpress
Project description:The aim of this study was to examine the effect of intra-tumor heterogeneity (ITH) on detection of genes within gene expression panels (GEPs), and the subsequent ability to predict prognostic risk. Multiplexed barcoded RNA analysis was used to measure the expression of 141 genes from five GEPs (Oncotype Dx, MammaPrint, PAM50, EndoPredict, and BCI) in breast cancer tissue sections and tumor-rich cores from 71 ER positive node-negative tumors. Tumor regions with high Ki67 and/or low PR were also used to punch cores, potentially representing aggressive areas of a tumor. In addition to examining the effect of ITH on measurement of GEPs, the effect of ITH on prediction of prognosis in the Oncotype Dx assay was also assessed.
2017-02-08 | GSE79378 | GEO
Project description:Biomarker studies for early stage or preclinical hepatocellular carcinomas (HCC) are hindered by the difficulties of obtaining samples from asymptomatic individuals. We established animal models using irradiated mice to investigate circulating miRNA as non-invasive markers for detection of early stage HCC. We hypothesized that certain miRNAs that play pivotal roles in molecular pathways are conserved across species and identification of these miRNAs will facilitate studying human markers in mice. To test the hypothesis, we performed weighted gene co-expression analysis by integrating circulating miRNA and tumor gene expression profiles from individual mice and discovered hub miRNAs in highly correlated expression modules. We validated the hub miRNAs using F2 hybrid mice derived from radiogenic HCC susceptible and resistant founders and identified 38 circulating miRNA markers associated with radiation-induced HCC. Through literacy search, we selected 10 human HCC-associated circulating miRNAs that had been validated in multiple independent patient cohorts. Nine of the 10 human markers overlapped with the mouse hub miRNAs, indicating the feasibility of using mouse model to study human circulating HCC markers. Using serially collected plasma samples from irradiated mice, we studied the kinetics of circulating miRNAs. We found that the mouse plasma levels of 4 human circulating markers, miR-122-5p, miR-100-5p, miR-34a-5p and miR-365-3p increased linearly as the time approaching towards HCC detection, indicating the correlations of the 4 miRNAs with oncogenic progression. Estimation of change points in the kinetics of the 4 circulating miRNAs suggested the changes started months before HCC detection, ranging from 17.5 to 6.8 months. Our data demonstrated that the 4 circulating miRNAs were sensitive biomarkers potentially valuable for the screening of early stage HCC.
2022-07-06 | GSE196193 | GEO
Project description:ObjectivesPancreatic ductal adenocarcinoma (PDAC) presents the lowest survival rate of all cancers because only 6% of patients reach five-year survival. Alterations in the expression of several microRNAs (miRNAs) occur in the tumor of PDAC and in preneoplastic lesions as the called intraductal papillary mucinous neoplasm (IPMN). Here, we aimed at identifying which miRNAs are significantly altered in liquid biopsies from patients with PDAC and IPMN to find new noninvasive biomarkers for early detection of PDAC.MethodsWe analyzed by real-time quantitative reverse transcription-PCR (qRT-PCR) the expression of 17 circulating miRNAs, previously found to be significantly overexpressed in tissue pancreatic neoplasms, in a set of 182 plasma samples (94 PDAC, 19 IPMN, 18 chronic pancreatitis, and 51 disease-free controls). Then, we analyzed CA19.9 levels in the same plasma set, and we assessed the diagnostic values of differentially expressed miRNAs, CA19.9, and all possible combinations.ResultsOf note, 16, 14, and 9 miRNAs were significantly increased in PDAC, IPMN, and chronic pancreatitis, respectively, compared with control plasmas. miR-21-5p, miR-33a-3p, miR-320a, and miR-93-5p showed the highest discriminating capacity for pancreatic neoplasia (PDAC or IPMN) with an area under the receiver operating characteristic curve (AUC) of 0.86, 0.85, 0.85, and 0.80, respectively. 2-miRNA combinations improved these performances reaching AUC = 0.90 for "miR-33a-3p+miR-320a." Addition of CA19.9 increased the diagnostic potential of miRNA signatures even further achieving an AUC of 0.95 (93% sensitivity and 85% specificity) for the combination of "miR-33a-3p+miR-320a+CA19.9."ConclusionsNovel signatures combining miRNAs and CA19.9 could be used as noninvasive biomarkers for early detection of PDAC.
| S-EPMC6602779 | biostudies-literature
Project description:We developed an enrichment-free, metabolic-based assay for rapid detection of tumor cells in the pleural effusion and peripheral blood samples. All nucleated cells are plated on microwell chips that contain 200,000 addressable microwells and then screened the chips. After candidate tumor cells were identified, retrieved single tumor cells with micromanipultor. To detection and analysis molecular characterization of these circulating tumor cells, we performed single cell whole genome amplification with multiple displacement amplification (MDA) technology and whole exome sequencing.
2017-02-17 | E-MTAB-4948 | biostudies-arrayexpress
Project description:A serum miRNA combination could be a powerful classifier for the detection of hepatocellular carcinoma. Keywords: Non-coding RNA profiling by array
2020-08-03 | GSE113740 | GEO