Exosomal MicroRNAs Signature Acts as Efficient Biomarker for Non-Invasive Diagnosis of Gallbladder Carcinoma
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ABSTRACT:
PROVIDER: PRJNA735198 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14730725.fastq.gz | Fastqsanger.gz | |||
| SRR14730726.fastq.gz | Fastqsanger.gz | |||
| SRR14730727.fastq.gz | Fastqsanger.gz | |||
| SRR14730728.fastq.gz | Fastqsanger.gz | |||
| SRR14730729.fastq.gz | Fastqsanger.gz |
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Project description:Gallbladder carcinoma (GBC) is the most common biliary tract malignant tumor. However, few diagnostic and prognostic biomarkers are available. Although the potential role of exosomes in the diagnosis of several tumor types has been repeatedly explored, the use of exosomal microRNAs (miRNAs) as specific biomarkers for GBC has not been systematically conducted. In this study, we identified a 5-exosomal miRNAs set that can be used to evaluate the risk of GBC through a three-step study that relies on biomarker discovery, training and validation. This biomarker set including the exosomal miR-552-3p, miR-581, miR-4433a-3p, miR-496, and miR-203b-3p.
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Project description:Through a three-step study that relies on biomarker discovery, training, and validation, we identified a set of five exosomal microRNAs (miRNAs) that can be used to evaluate the risk of gallbladder carcinoma (GBC), including miR-552-3p, miR-581, miR-4433a-3p, miR-496, and miR-203b-3p. When validated in 102 GBC patients and 112 chronic cholecystitis patients from multiple medical centers, the AUC of this combinatorial biomarker was 0.905, with a sensitivity of 81.37% and a specificity of 86.61%. The performance of this biomarker is superior to that of the standard biomarkers CA199 and CEA and is suited for GBC early diagnosis. The multi-clinicopathological features and prognosis of GBC patients were significantly associated with this biomarker. After building a miRNA-target gene regulation network, cell functions and signaling pathways regulated by these five miRNAs were examined. This biomarker signature can be used in the development of a noninvasive tool for GBC diagnosis, screening and prognosis prediction.
| S-EPMC9420508 | biostudies-literature
Project description:We report here an improved protocol to reprogram mouse gallbladder cells (GBCs) into pancreatic beta cells. To fully understand the extent of reprogramming, mRNA was extracted from FACS-purified MIP-GFP positive insulin-producing cells (namely rGBC2) for RNA-seq after 10-days of in vitro reprogramming. The global gene expression profile of rGBC2 was compared with that of primary gallbladder cells, GBC reprogrammed with the rGBC1 protocol (Hickey et al., 2013) and mouse pancreatic β cells (Benner et al., 2014). We show that rGBC2 from four independent cell batches showed a unique gene expression phenotype. Compared with the rGBC1 protocol, rGBC2 expressed many additional pancreatic β cell genes, suppressed many gallbladder genes and resulted in an expression profile closer to pancreatic β cells.
2017-01-01 | GSE87606 | GEO
Project description:Background: Safe and sensitive methods for glioblastoma diagnosis and disease monitoring are urgently needed. Exosomes are nano-sized extracellular vesicles that contain molecules characteristic of their cell-of-origin, including microRNA. Exosomes released by glioblastoma tumors cross the blood-brain-barrier ino the peripheral circulation. Methods: Serum exosomal-microRNA isolated from IDH-wildtype glioblastoma (n=12) and IDH-mutant glioma grades II-III (n=10) were analyzed using small-RNA next generation sequencing and compared to age- and gender-matched healthy controls. Differentially expressed miRNAs (|fold change|³2 and p-value ≤ 0.05 in three statistical tests, Fischer-exact, t-test, and Wilcoxon) were identified and the predictive power of individual and subsets of miRNAs were tested using univariate (logistic regression) and multivariate (Random Forest) analyses. Additional glioblastoma sera (n=4) and independent sets of healthy (n=9) and non-glioma (n=10) controls were used to further test the predictive power of our glioblastoma miRNA signature. Results: Twenty-six miRNAs were differentially expressed in glioblastoma relative to healthy controls. Seven miRNAs (miR-182-5p, miR-328-3p, miR-339-5p, miR-340-5p, miR-485-3p, miR-486-5p and miR-543) were the most stable for classifying glioblastoma, achieving a predictive power of 91.7%. Strikingly, the combined expressions of miR-182-5p, miR-328-3p miR-485-3p miR-486-5p distinguished glioblastoma patients from controls with perfect accuracy. This miRNA panel was able to correctly classify all specimens in validation cohorts (n=23). An analogous approach was used to identify 23 dysregulated miRNAs in IDH-mutant gliomas, including a distinct subset of stable miRNAs for classifying patients with lower-grade IDH-mutant gliomas. Conclusions: Our serum exosomal-miRNA signature can accurately diagnose glioblastoma preoperatively. These findings have significant scope to revolutionize glioblastoma tumor diagnosis and disease monitoring. IMPORTANCE OF STUDY: There is a real need for accurate biomarkers that can measure glioblastoma disease activity and treatment response in a safe and timely manner. This study demonstrates that exosome-associated microRNAs have exceptional utility as blood-based biomarkers in glioma patients. This work also shows the potential for exosomal microRNA profiles to be used for glioma subtyping, grading and determining mutational states. The development of specific, sensitive and non-invasive screening tests would have significant clinical benefit by reducing costs of treatment monitoring, improving accessibility and quality-of-life measures. Moreover, such tests have the potential to provide objectively measured surrogate endpoints to allow clinical trial protocols to be more dynamic and adaptive.
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Project description:We determined the global microRNA expression profiles of primary human gallbladder cells and genetically reprogrammed human gallbladder cells and compared with pancreatic beta cells to ascertain the degree of cellular transdifferentatiation of insulin-producing human gallbladder cells to become beta-like cells. First, we cultured patient-derived gallbladder cells and then we transduced these with beta cell transcription factors to reprogram gallbladder cells to become beta-like cells. We used a pan-islet surface monoclonal antibody to enrich for insulin-producing reprogrammed human gallbladder cells using FACS.
2017-08-02 | E-MTAB-5554 | biostudies-arrayexpress
Project description:We determined the global gene expression profiles of primary human gallbladder cells and genetically reprogrammed human gallbladder cells and compared with pancreatic beta cells to ascertain the degree of cellular transdifferentatiation of insulin-producing human gallbladder cells to become beta-like cells. First, we cultured patient-derived gallbladder cells and then we transduced these with beta cell transcription factors to reprogram gallbladder cells to become beta-like cells. We used a pan-islet surface monoclonal antibody to enrich for insulin-producing reprogrammed human gallbladder cells using FACS.
2017-08-02 | E-MTAB-5556 | biostudies-arrayexpress
Project description:Epigenome-wide methylation levels were measured in patients from Chiel with gallstone disease, gallbladder dyplasia or gallbladder cancer using Illumina Infinium methylation arrays.
2020-12-12 | E-MTAB-9868 | biostudies-arrayexpress
Project description:We carried out an iTRAQ-based quantitative proteomic analysis of gallbladder cancer and adjacent non-tumor tissue to systematically identify differentially expressed proteins in gallbladder cancer. Ten gallbladder adenocarcinoma and ten adjacent non-tumor tissue samples were selected post pathological confirmation for the study. Samples were pooled and In-solution trypsin digestion was carried out. Post digestion, peptides were iTRAQ labeled with 114 and 115 (gallbladder adenocarcinoma) and 116 and 117 (adjacent non-tumor samples). LC-MS/MS analysis of SCX fractions was carried out using a reversed phase analytical C18 column connected to 1200 Series Nanoflow LC interfaced with LTQ-Orbitrap Velos. Data were acquired using Xcalibur 2.1. Proteome Discoverer (v 1.3) suite was used for quantitation and database searches. LC-MS/MS data were searched using Mascot and SEQUEST search algorithms against Human RefSeq 50 supplemented with frequently observed contaminants.
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Project description:Gallbladder cancer is a rare but highly malignant cancer. We performed the transcriptional profile sequencing to figure out the potential mechanisms, which might significantly affect gallbladder cancer progression.
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Project description:The complexity of transcriptome in human gallbladder has not been clarified quite clearly so far. Here we collect 20 pairs of gallbladder samples.High-throughput RNA sequecing data was generated for each sample.We characterize the linear and circular transcripts.
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