9525a77b-bf6a-459f-aa19-6742624f2fd0 - samples
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ABSTRACT:
PROVIDER: EGAD00001009337 | EGA |
REPOSITORIES: EGA
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Project description:As a non-invasive blood testing, the detection of cell-free DNA (cfDNA) methylation in plasma is raising increasing interest due to its diagnostic and biology applications. Although extensively used in cfDNA methylation analysis, bisulfite sequencing is less cost-effective. Through enriching methylated cfDNA fragments with MeDIP followed by deep sequencing, we aimed to characterize cfDNA methylome in cancer patients. In this study, we investigated the cfDNA methylation patterns in lung cancer patients by MeDIP-seq. MEDIPS package was used for the identification of differentially methylated regions (DMRs) between patients and normal ones. Overall, we identified 330 differentially methylated regions (DMRs) in gene promoter regions, 33 hypermethylation and 297 hypomethylation respectively, by comparing lung cancer patients and healthy individuals as controls. The 33 hypermethylation regions represent 32 genes. Some of the genes had been previously reported to be associated with lung cancers, such as GAS7, AQP10, HLF, CHRNA9 and HOPX. Taken together, our study provided an alternative method of cfDNA methylation analysis in lung cancer patients with potential clinical applications.
2019-03-31 | E-MTAB-7163 | biostudies-arrayexpress
Project description:The genome-wide analysis of cfDNA fragmentation patterns in DENQCMs and maternal plasma was performed by deep sequencing using Illumina Novaseq to confirm their biological characteristics. We first performed deep whole genome sequencing of the cfDNA extracted from DENQCMs and maternal plasma cfDNA. Then we analyzed the sequencing data and compared various characteristics of cfDNA fragmentation patterns, such as dinucleotide composition, nucleosome protection length, and nucleosome occupancy based on a windowed protection score (WPS), to the submitter-provided processed data from a healthy individual IH01 (GEO accession GSM1833276).
2019-01-05 | GSE124686 | GEO
Project description:Many concurrent arrays were run for different projects. All test conditions were tested in all animal models. Animal models were (i) healthy CD1 mice (abbreviation CN), or (ii) STZ-induced diabetic CD1 littermates (STZ). Treatment conditions were (i) untreated animals (no prefix), (ii) treatment with 30ul saline and electrotransfer ("e" prefix), (iii) treatment with 75ug noncoding parental plasmid pGG2-CMV ("p" prefix), or (iv) treatment with 37.5ug each (75ug net) of pGG2-CMV-hIns and pGG2-CMV-rGck expressing human insulin and rat glucokinase respectively ("t" prefix). All samples were harvested 7 days after treatment.
2009-06-07 | E-MEXP-2191 | biostudies-arrayexpress
Project description:We evaluated whether targeted next-generation sequencing (NGS) using the Ion Torrent Personal Genome Sequencer of cfDNA could identify prognostic or predictive factors for overall survival (OS) or progression free survival (PFS) within a large cohort of patients with advanced lung adenocarcinoma enrolled in the GALAXY-1 trial.
2018-01-10 | E-MTAB-5749 | biostudies-arrayexpress
Project description:Liquid biopsies hold significant potential for the non-invasive diagnostics of tumors and other diseases. While the clinical application of cell-free DNA (cfDNA) methodologies is emerging, the implementation of tumor-derived extracellular vesicles (EVs) as validated biomarkers is hindered by substantial pre-analytical variations. In this work, we are taking a step towards standardizing the pre-analytical procedures of blood collection for subsequent co-isolation of plasma cfDNA and EVs from a single blood collection tube. We compare effects of blood preservation tubes and storage to enable proteomic profiling of resulting EVs in addition to cfDNA extraction and sequencing. Following a stringent method of large EV (lEV) and small EV (sEV) isolation, consisting of differential ultracentrifugation and size exclusion chromatography, we evaluate protein concentration, particle number, quality and integrity of the isolated EVs. Subsequent proteomic analyses of EV isolates unravel the complexity of the respective tube proteomes allowing the interpretation of EV origins as well as contamination sources. While ACD-A and Citrate tubes demonstrate satisfying results in preservation of EV proteomes, only Streck RNA®, Norgen® and PAX® tubes can preserve high cfDNA purity for up to 7 days. When aiming for multi-omics analyses, Streck RNA® tubes show the most stable performance across tested parameters for both bioanalytes. Furthermore, we find more variability in protein composition in sEVs than in lEVs after 7 days of storage; thus, sEVs might be more susceptible to storage effects. Our clinically applicable workflow provides the basis for informed choice of liquid biopsy tubes along with a ready-to-use protocol to retrieve both genomic and EV proteomic biomarker information for multi-omics biomarker-based liquid biopsy studies.
2026-01-23 | PXD062837 | Pride
Project description:Targeted Multiplex PCR and Hybrid Capture of Reference cfDNA for Enhanced On-Target Ratio in Targeted Sequencing
| PRJNA1159908 | ENA
Project description:Single cell RNA sequencing data across seven samples of the Trypanosoma cruzi in vitro lifecycle. The samples have the following lifecycle stage compositions: Sample 1 (fastq file prefix = cycle_epimast) - Mix of exponential growth growth epimastigotes and amastigotes derived 120 hours post infection of Vero cells with trypomastigotes. Sample 2 (fastq file prefix = cycle_amast) - Mix of amastigotes derived 6 and 24 hours post infection of Vero cells with trypomastigotes. Sample 3 (fastq file prefix = cycle_metacyc1) - Mix of stationary growth phase epimastigotes and metacyclic trypomastigotes (first of two biological replicates). Sample 4 (fastq file prefix = cycle_metacyc2) - Mix of stationary growth phase epimastigotes and metacyclic trypomastigotes (second of two biological replicates). Sample 5 (fastq file prefix = cycle_trypomast)- Trypomastigotes harvested from culture 7 days post infection of Vero cells with trypomastigotes. Sample 6 (fastq file prefix = LifeCycleMix1) - A mix of amastigotes derived 6, 24 and 120 hours hours post infection of vera cells with trypomastigotes, exponential and stationary growth phase epimastigotes, metacyclic trypomastigotes and trypomastigotes harvested from culture 7 days post infection of Vero cells with trypomastigotes (first of two biological replicates). Sample 7 (fastq file prefix = LifeCycleMix2) - A mix of amastigotes derived 6, 24 and 120 hours hours post infection of Vero cells with trypomastigotes, exponential and stationary growth phase epimastigotes, metacyclic trypomastigotes and trypomastigotes harvested from culture 7 days post infection of Vero cells with trypomastigotes (first of two biological replicates). Sample 8 (fastq file prefix = A2, B2, C2 and D2) - Amastigotes derived 48 hours post infection of Vero cells
2025-08-27 | E-MTAB-14406 | biostudies-arrayexpress
Project description:Obesity-induced inflammation causes metabolic dysfunction, but the mechanisms remain elusive. Here we show that the innate immune transcription factor interferon regulatory factor (IRF3) adversely affects glucose homeostasis through induction of the endogenous FAHFA hydrolase androgen induced gene 1 (AIG1) in adipocytes. Adipocyte-specific knockout of IRF3 protects mice against high-fat diet-induced insulin resistance, whereas overexpression of IRF3 or AIG1 in adipocytes promotes insulin resistance on a high-fat diet. Furthermore, pharmacological inhibition of AIG1 reversed obesity-induced insulin resistance and restored glucose homeostasis in the setting of adipocyte IRF3 overexpression. We, therefore, identify the adipocyte IRF3/AIG1 axis as a crucial link between obesity-induced inflammation and insulin resistance and suggest an approach for limiting the metabolic dysfunction accompanying obesity. ## File Key ### MS-ABPP The following raw files were acquired on an Eclipse instrument in triplicate with two concentrations of inhibitor in both brain and kidney. These variables are encoded in the file names. Associated analysis pipeline files from CIMAGE are provided for each raw file (same file name, with a .raw_output_rt_10_sn_2.5.to_excel extension). - brain_conc1.0_rep1.raw - brain_conc1.0_rep2.raw - brain_conc1.0_rep3.raw - brain_conc10.0_rep1.raw - brain_conc10.0_rep2.raw - brain_conc10.0_rep3.raw - kidney_conc1.0_rep1.raw - kidney_conc1.0_rep2.raw - kidney_conc1.0_rep3.raw - kidney_conc10.0_rep1.raw - kidney_conc10.0_rep2.raw - kidney_conc10.0_rep3.raw ### TMT Dose Response The following raw files were acquired on an Eclipse instrument instrument in both brain and white adipose tissues: - brain_dose_response.raw - wat_dose_response.raw The TMT channels were organized as follows: - DMSO channels: 1, 3, 5 - ABD-110 @ 0.001 μM: 7, 9, 11 - ABD-110 @ 0.01 μM: 2, 4, 6 - ABD-110 @ 0.1 μM: 13, 15, 17 - ABD-110 @ 1 μM: 8, 10, 12 - ABD-110 @ 10 μM: 14, 16, 18 Associated analysis pipeline files after IDFilter run are provided for each file (same file name, with a _filtered_matches suffix and an .idXML extension). ### PRM AIG1 In Vivo Target Engagement The A prefix before the replicate number refers to treatment with ABD-110, whereas the V prefix refers to vehicle treatment. Diet and tissue type are also encoded in the filename. The following files were acquired on a Lumos instrument, with 5 replicates for each condition (as noted in square brackets). Associated pipeline analysis files are Skyline exports and are provided as two .csv files having names beginning with Skyline_PRM_export and ending with the tissue types contained. - Brain_Chow_A[1-5].raw - Brain_Chow_V[1-5].raw - Brain_HVD_A[1-5].raw - Brain_HVD_V[1-5].raw - eWAT_Chow_A[1-5].raw - eWAT_Chow_V[1-5].raw - eWAT_HVD_A[1-5].raw - eWAT_HVD_V[1-5].raw - iWAT_Chow_A[1-5].raw - iWAT_Chow_V[1-5].raw - iWAT_HVD_A[1-5].raw - iWAT_HVD_V[1-5].raw - Kindey_Chow_A[1-5].raw - Kindey_Chow_V[1-5].raw - Kindey_HVD_A[1-5].raw - Kindey_HVD_V[1-5].raw
2024-03-14 | PXD047864 | Pride