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
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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: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:Cancer cells have wide variety of gene expression profile. The objective of the study is to reveal the cancer-associated gene expression profile. Microarray analysis was used to investigate gene expression of cancer cells. Both gastric and pancreatic cancer tissues were surgically resected and total RNA was purified from these tissues by a conventional method.
2014-04-15 | E-GEOD-42252 | biostudies-arrayexpress
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:We aimed to identify urinary exosomal miRNAs associated with PCa metastasis and develop a non-invasive risk-scoring model for PCa metastasis in this study. MiRNA profiles were examined using the Taqman low-density miRNA array (TLDA). Megaplex reverse transcription reactions and pre-amplification reactions were performed to increase the quantity of cDNA for miRNA expression analysis using the Megaplex PreAmp Primers Human Pool A and TaqMan PreAmp Master Mix (Thermo Fisher Scientific). MiRNA expression was evaluated via the TLDA panel A v2.0 (Thermo Fisher Scientific). Raw data were processed using the QuantStudio Real-Time PCR Software (Thermo Fisher Scientific) to determine a cycle threshold (Ct) value for each miRNA.
2021-06-07 | GSE173094 | GEO
Project description:This large-scale study focused on the discovery on urinary biomarker for ovarian cyst.
2015-07-30 | PXD002549 | Pride