Exploring the usefulness of urinary microRNA as a biomarker in pancreatic cancer and gastric cancer patients.
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE244347 | GEO | 2024/04/01
REPOSITORIES: GEO
Similar Datasets
Project description:Exploring the usefulness of urinary microRNA as a biomarker in pancreatic cancer and gastric cancer patients.
| PRJNA1022445 | ENA
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:A novel urinary microRNA biomarker panel for detecting gastric cancer
| PRJNA528633 | ENA
Project description:Although blood-based protein biomarkers have been described for diagnosis of some cancers, detection of tumor-derived peptides/proteins in urine provides an attractive and non-invasive alternative for diagnostic or screening purposes. For instance, bladder tumor antigen (BTA) assay is FDA approved urine-based biomarker assay to detect the bladder cancer. In this study, we decided to investigate the possibility of discovering proteins as biomarkers in urine from individuals diagnosed with gastric cancer. We carried out comprehensive quantitative profiling of urine samples using tandem mass tags (TMT)-based multiplexed mass spectrometry approach. Of the 1,504 total number of proteins identified, 246 proteins were differentially expressed in a gastric cancer cohort. Ephrin A1 (EFNA1), pepsinogen A3 (PGA3) and vitronectin (VTN) were among the upregulated proteins which are known to play crucial role in the progression of gastric cancer. Notably, our analysis also revealed other overexpressed proteins including shisa family member 5 (SHISA5), mucin like 1 (MUCL1) and leukocyte cell derived chemotaxin 2 (LECT2), which had not previously been linked to gastric cancer. We decided to deploy a recently developed targeted method, SureQuant, for validating a subset of potential proteins discovered in this study. We confirmed the overexpression of EFNA1, VTN and SORT1 in an independent set of urine samples. Our study demonstrates the potential of urinary proteomics to identify promising diagnostic biomarkers of cancers in a non-invasive fashion.
2024-08-10 | PXD040956 | Pride
Project description:Background: Metabolomics has shown promise in gastric cancer (GC) detection. This research sought to identify whether GC has a unique urinary metabolomic profile compared with benign gastric disease (BN) and healthy (HE) patients. Methods: Urine from 43 GC, 40 BN, and 40 matched HE patients was analysed using 1H nuclear magnetic resonance (1H-NMR) spectroscopy, generating 77 reproducible metabolites (QC-RSD <25%). Univariate and multivariate (MVA) statistics were employed. A parsimonious biomarker profile of GC vs HE was investigated using LASSO regularised logistic regression (LASSO-LR). Model performance was assessed using Receiver Operating Characteristic (ROC) curves. Results: GC displayed a clear discriminatory biomarker profile; the BN profile overlapped with GC and HE. LASSO-LR identified three discriminatory metabolites: 2-hydroxyisobutyrate, 3-indoxylsulfate, and alanine, which produced a discriminatory model with an area under the ROC of 0.95. Conclusions: GC patients have a distinct urinary metabolite profile. This study shows clinical potential for metabolic profiling for early GC diagnosis.
2018-09-03 | ST001047 | MetabolomicsWorkbench
Project description:Background: Renal cell carcinoma (RCC) accounts for about 2% of all cancers. Renal biopsy is the gold standard among the diagnostic tools, but it is invasive and not suitable for all patients. Therefore, new reliable and non-invasive biomarkers for ccRCC detection are required. Secretion of extracellular vesicles (EVs), containing RNA molecules that can be transferred between cells, seems to be a general characteristic of malignant transformation. Consistently, cancer-derived EVs are enriched in the blood, urine and various malignant effusions of cancer patients. Therefore, urinary samples can be a non-invasive approach for discovering diagnostic biomarkers. Methods: We enrolled 33 clear-cell RCC (ccRCC) patients and 22 healthy subjects (HS), age and sex-matched, for urine collection and extracellular vesicles isolation by differential centrifugation. Transcriptional profiles of urinary EVs from 12 patients with ccRCC and 11 HS were generated using the Illumina HumanHT-12 v4 BeadChip oligonucleotide arrays. Microarray analysis led to the identification of RNA that were then validated using RT-qPCR. Results: We showed for the first time that urinary exosomal shuttle RNA (esRNA) was significantly different in ccRCC patients compared to HS and we identified three EVs esRNA involved in the tumor biology that are potentially suitable as non-invasive biomarkers. GSTA1, CEBPA and PCBD1 RNA levels decreased in urinary EVs of patients compared to HS. After 1 month post-operation, the levels of RNA increased to reach the normal level. Conclusions: This study suggests, for the first time, the potential use of the RNA content of urinary EVs to provide a non-invasive first step to diagnose the ccRCC. Total RNA obtained from urinary extracellular vesicles isolated from ccRCC patients and healthy subjects.
2016-09-01 | E-GEOD-72922 | biostudies-arrayexpress
Project description:Primary outcome(s): Comparison of diagnostic accuracy of urinary protein fragments and carcinoembryonic antigen (CEA) for adenocarcinoma (gastric cancer, colorectal cancer, or bile duct cancer)
| 2653289 | ecrin-mdr-crc
Project description:Exercise could stimulate the release of exosomes into the circulation, transferring signals between the cells. Exosomes are also found in urine, which is an emerging biomarker of several diseases. However, the characteristics of urinary exosomes and their contents after exercise remain poorly understood. We used microarrays to identify the alteration of gene expression in urinary exosomes after exercise bout.
2022-01-09 | GSE193186 | GEO
Project description:Background: Renal cell carcinoma (RCC) accounts for about 2% of all cancers. Renal biopsy is the gold standard among the diagnostic tools, but it is invasive and not suitable for all patients. Therefore, new reliable and non-invasive biomarkers for ccRCC detection are required. Secretion of extracellular vesicles (EVs), containing RNA molecules that can be transferred between cells, seems to be a general characteristic of malignant transformation. Consistently, cancer-derived EVs are enriched in the blood, urine and various malignant effusions of cancer patients. Therefore, urinary samples can be a non-invasive approach for discovering diagnostic biomarkers. Methods: We enrolled 33 clear-cell RCC (ccRCC) patients and 22 healthy subjects (HS), age and sex-matched, for urine collection and extracellular vesicles isolation by differential centrifugation. Transcriptional profiles of urinary EVs from 12 patients with ccRCC and 11 HS were generated using the Illumina HumanHT-12 v4 BeadChip oligonucleotide arrays. Microarray analysis led to the identification of RNA that were then validated using RT-qPCR. Results: We showed for the first time that urinary exosomal shuttle RNA (esRNA) was significantly different in ccRCC patients compared to HS and we identified three EVs esRNA involved in the tumor biology that are potentially suitable as non-invasive biomarkers. GSTA1, CEBPA and PCBD1 RNA levels decreased in urinary EVs of patients compared to HS. After 1 month post-operation, the levels of RNA increased to reach the normal level. Conclusions: This study suggests, for the first time, the potential use of the RNA content of urinary EVs to provide a non-invasive first step to diagnose the ccRCC.
2016-09-01 | GSE72922 | GEO
Project description:This large-scale study focused on the discovery on urinary biomarker for ovarian cyst.
2015-07-30 | PXD002549 | Pride