8e42b10f-eb70-4301-aa42-89efc8551b9e - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001007748 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Circulating plasma miRNAs profiling in platelets-free plasma samples from Behçet's disease patients compared with healthy subjects, aimed to both pathogenesis elucidation and candidate non-invasive biomarkers identification.
2020-04-01 | GSE145191 | GEO
Project description:This study aimed to explore circRNA expression profiles in the plasma of patients with early-stage lung adenocarcinoma compared to healthy controls. Using Agilent microarray technology, we profiled total RNA extracted from plasma samples of 4 patients with early-stage lung adenocarcinoma (stages IA–IIA) and 4 healthy individuals. All subjects provided peripheral blood samples, and cell-free RNA was isolated from plasma. The objective was to identify potential circRNA biomarkers that could distinguish lung cancer patients from healthy individuals at early stages.
2025-05-12 | GSE296415 | GEO
Project description:Improved biomarkers of treatment response are needed for patients with High-Grade Serous Ovarian Cancer (HGSC). A challenge is substantial anatomical site-to-site variation in expression. We completed Data Independent Acquisition – Mass Spectrometry (DIA-MS) analysis of over 404 fresh frozen and 78 formalin fixed, paraffin-embedded HGSC tissue samples from ovary (adnexal) and a common secondary site (omentum) in 11 patients. This was compared with mutation testing, gene expression and whole genome copy number profiling. Proteins with relatively stable intra-, and variable inter-individual expression (n=1,651), included a 52-protein module reflecting interferon mediated tissue inflammation indicative of a cGAS-STING pathway cytosolic double-stranded (ds) DNA response. The dsDNA sensing / inflammation (DSI) score was higher in omentum compared with ovary. Ovarian HGSC samples showed marked inter-individual differences in inflammatory and immune responses to DNA damage. Stable discriminative features of the HGSC proteome, a prerequisite for clinical predictive biomarkers, are detectable in ovary (adnexal) tissue samples.
2025-06-11 | GSE277107 | GEO
Project description:Most (70%) epithelial ovarian cancers (EOCs) are diagnosed late. Non-invasive biomarkers that facilitate disease detection and predict outcome are needed. The microRNAs (miRNAs) represent a new class of biomarkers. This study was to identify and validate plasma miRNAs as biomarkers in EOC. We evaluated plasma samples of 360 EOC patients and 200 healthy controls from two institutions. All samples were grouped into screening, training and validation sets. We scanned the circulating plasma miRNAs by TaqMan low-density array in the screening set and identified/validated miRNA markers by real-time polymerase chain reaction assay in the training set. Receiver operating characteristic and logistic regression analyses established the diagnostic miRNA panel, which were confirmed in the validationsets. We found higher plasma miR-205 and lower let-7f expression in cases than in controls. MiR-205 and let-7f together provided high diagnostic accuracy for EOC, especially in patients with stage I disease. The combination of these two miRNAs and carbohydrate antigen-125 (CA-125) further improved the accuracy of detection. MiR-483-5p expression was elevated in stages III and IV compared with in stages I and II, which was consistent with its expression pattern in tumor tissues. Furthermore, lower levels of let-7f were predictive of poor prognosis in EOC patients. Our findings indicate that plasma miR-205 and let-7f are biomarkers for ovarian cancer detection that complement CA-125; let-7f may be predictive of ovarian cancer prognosis.
2013-08-30 | GSE50472 | GEO
Project description:BAM files corresponding to the sequencing of 125 circulating cell-free DNA from 125 healthy patients. Each sample was sequenced twice.
| EGAD00001005463 | EGA
Project description:Rheumatoid arthritis (RA) is a systemic autoimmune and inflammatory disease. Plasma biomarkers are critical for understanding disease mechanisms, treatment effects, and diagnosis. Mass spectrometry-based proteomics is a powerful tool for unbiased biomarker discovery. However, plasma proteomics is significantly hampered by signal interference from high-abundance proteins, low overall protein coverage, and high levels of missing data from data-dependent acquisition (DDA). To achieve quantitative proteomic analysis for plasma samples with a balance of throughput, performance, and cost, we developed a workflow incorporating plate-based high abundance protein depletion and sample preparation, comprehensive peptide spectral library building, and data-independent acquisition (DIA) SWATH mass spectrometry-based methodology. In this study, we analyzed plasma samples from both RA patients and healthy donors. The results showed that the new workflow performance exceeded that of the current state-of-the-art depletion-based plasma proteomic platforms in terms of both data quality and proteome coverage. Proteins from biological processes related to the activation of systemic inflammation, suppression of platelet function, and loss of muscle mass were enriched and differentially expressed in RA. Some plasma proteins, particularly acute phase reactant proteins, showed great power to distinguish between RA patients and healthy donors. Moreover, protein isoforms in the plasma were also analyzed, providing even deeper proteome coverage. This workflow can serve as a basis for further application in discovering plasma biomarkers of other diseases.
2023-10-25 | PXD045171 | Pride
Project description:Here, we performed label-free liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) to profile the normal human proteome. In total, we analyzed 117 samples from 46 histologically normal tissues and organs at autopsy. Our high-resolution MS approach allowed for the quantification of 10,438 unique proteins. In order to expand our coverage of the human proteome, we combined our previously published biological fluid proteomic data from healthy individuals. We considered data from seven biological fluids, including urine, cerebrospinal fluid, synovial fluid, seminal plasma, sweat, cervical vaginal fluid, and nipple aspirate fluid. Overall, we generated tandem mass spectra corresponding to 13,028 unique human protein-coding genes.
2020-10-29 | PXD020192 | Pride
Project description:In this study, we evaluated the effect of preservation agent on the effect of the methylation pattern of cell-free DNA. The methylation pattern was assessed with cell-free reduced representation sequencing (cf-RRBS). Blood was drawn from three healthy individuals (male and females between 24 and 50 years old). 15 tubes were drawn per healthy volunteer: 3x BD Vacutainer K2E EDTA spray tubes (REF 367525), 3x Streck Cell-Free DNA BCT tubes (catalogue number 218962), 3x PAXgene Blood ccfDNA tubes (catalogue number 768115), 3x Roche Cell-Free DNA Collection tubes (catalogue number 07785674001) and 3x Biomatrica LBgard blood tubes (SKU 68021-001), resulting in 45 samples in total. All 45 samples were sequenced on a NovaSeq6000. Samples are given as bismark coverage files (GRCh37).
2020-04-03 | E-MTAB-8858 | biostudies-arrayexpress
Project description:Liquid biopsy profile which can screen for early CRC. We aimed to depict the profile of early stage CRC as well as for advanced adenomas by combination of current molecular knowledge with microarray technology, using efficient circulating free RNA purification from blood and RNA amplification technologies. Circulating free RNA profile of plasma from colorectal cancer patients, advanced adenomas and healthy colonoscopia subjects. Plasma was drawn from 3 healthy colonoscopia subjects, 4 adanced adenomas subjects and 3 colorectal cancer patients. Circulating free RNA was purified from plasma samples and applied on GeneChip human 1.0 ST Arrays. The 'HuGene_1_0_green_yelow_red_DATASET.xlsx' and 'probe_level_expression_matrix.txt' files contain the primary data that was used to draw the conclusions of the current study. Please note that exon-level' analysis was performed but NO probe summarization to probeset was performed, therefore both data matrices contains non-unique identifiers.
2016-06-15 | E-GEOD-83353 | biostudies-arrayexpress
Project description:We sequenced cell-free RNA (cfRNA) for five cancer types (colorectal cancer, stomach cancer, liver cancer, lung cancer and esophageal cancer) and healthy individuals in 230 plasma samples collected from 6 clinical centers in China. Cancer related signaling pathway and microbial genus were identified. Cancer detection and specific classification were achieved through combining both host and microbial cfRNA reads.
2022-07-12 | GSE174302 | GEO