Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Analysis of Intestinal Microflora Combined With DNA Methylation in Stool to Detect Colorectal Cancer

ABSTRACT: Introduction: Colorectal cancer (CRC) has the third highest incidence rate and the fourth mortality rate in the world. Traditional colonoscopy as an invasive examination method cannot be widely used in screening for colorectal neoplasia. The fecal immunochemical test has some limitations in sensitivity. Also, race and regional differences may affect results. Abnormality in the composition of the gut microbiota has been implicated as a potentially important etiologic factor in the initiation and progression of colorectal cancer. Analyzing fecal flora and exfoliated cell genes may represent a new screening tool for colorectal cancer.This research aims to use 16S rRNA to compare differences in fecal flora between colorectal cancer patients and healthy controls. These data combined with DNA findings of fecal exfoliated cells may further clarify this difference to build a model for screening early colorectal cancer in Chinese people. Methods and analysis: In total, 300 patients with positive colonoscopy results and 200 health controls will be recruited. All participants will complete an information form and questionnaires. Fecal samples will be examined by 16S rRNA analysis. Gene methylation levels will be detected in fecal exfoliated cells. Models of related intestinal microbiota and methylation genes will be built. Receiver operating characteristic (ROC) curve analysis will be used to select some models with appropriate sensitivity and specificity.The models will be further validated by multicenter studys.

DISEASE(S): Dna Methylation,Gastrointestinal Microbiome,Colorectal Neoplasms,Neoplasms

PROVIDER: 2332627 | ecrin-mdr-crc |

REPOSITORIES: ECRIN MDR

ACCESS DATA

Json Xml

Similar Datasets

Gut microbiota dysbiosis and neurological function recovery after intracerebral hemorrhage [16S rRNA-Seq]

Project description:We aimed to investigate the microbial community composition in patients with intracerebral hemorrhage (ICH) and its effect on prognosis. The relationship between changes in bacterial flora and the prognosis of spontaneous cerebral hemorrhage was studied in two cohort studies. Fecal samples from healthy volunteers and patients with intracerebral hemorrhage were subjected to 16S rRNA sequencing at three time points: T1 (within 24 hours of admission), T2 (3 days post-surgery), and T3 (7 days post-surgery) using Illumina high-throughput sequencing technology.

2024-08-22 | E-MTAB-14351 | biostudies-arrayexpress

Impact of fecal microbiota transplantation (FMT) in 3 days-ABX-treated recipient mice using feces from 6 NSCLC patients at diagnosis.

Project description:This study aimed to analyze changes in gut microbiota composition in mice after transplantation of fecal microbiota (FMT, N = 6) from the feces of NSCLC patients by analyzing fecal content using 16S rRNA sequencing, 10 days after transplantation. Specific-pathogen-free (SPF) mice were used for each experiments (N=4) as controls.

2023-07-01 | E-MTAB-12812 | biostudies-arrayexpress

Differences of gut mucosa gene expression between septic very low birth weight infants and their non-septic twins

Project description:This is a prospective observational case-control study conducted in septic VLBW dizygotic twins and their non-septic twin controls. Fecal samples were used for genome-wide expression analysis of exfoliated intestinal cells.

2017-07-05 | E-MTAB-3439 | biostudies-arrayexpress

Chronic Strongyloides stercoralis infection increases Ruminococcus torques group and alter microbiome proteome in ivermectin treatment

Project description:The impact of mono-chronic S. stercoralis infection on the gut microbiome and microbial activities in infected participants was explored. The 16S rRNA gene sequencing of a longitudinal study with 2 sets of human fecal was investigated. Set A, 42 samples were matched, and divided equally into positive (Pos) and negative (Neg) for S. stercoralis diagnoses. Set B, 20 samples of the same participant in before (Ss+PreT) and after (Ss+PostT) treatment was subjected for 16S rRNA sequences and LC-MS/MS to explore the effect of anti-helminthic treatment on microbiome proteomes.

2023-11-07 | PXD037975 | JPOST Repository

16S rRNA sequencing of fecal samples from Atg16l1 T300A and wildtype littermate mice that were either exposed or not to mainstream cigarette smoking for 6 weeks

Project description:We found that mainstream cigarette smoking (4 cigarettes/day, 5 days/week for 2 weeks using Kentucky Research Cigarettes 3R4F) resulted in >20% decrease in the percentage of normal Paneth cell population in Atg16l1 T300A mice but showed minimal effect in wildtype littermate control mice, indicating that Atg16l1 T300A polymorphism confers sensitivity to cigarette smoking-induced Paneth cell damage. We performed 16S rRNA sequencing to identify potential microbiota changes associated with Paneth cell defect in Atg16l1 T300A mice exposed to cigarette smoking. Female mice were used at 4-5 weeks of age. Cigarette smoking was performed using smoking chamber with the dosage and schedule as described above. The fecal samples from the mice were collected for 16S rRNA sequencing analysis after completing 6 weeks of smoking.

2018-10-31 | E-MTAB-5717 | biostudies-arrayexpress

Effects of semaglutide on the gut microbiota of high-fat diet-fed mice lacking GLP-1Rs in T cells

Project description:Gut intraepithelial lymphocytes (IELs) are one of the few immune cell populations in the body that expresses glucagon-like 1 receptors (GLP-1R). To test the potential effects of GLP-1 on the gut microbiota through the gut IEL GLP-1R, we performed 16s rRNA seq on the DNA isolated from the fecal pellet of Lck-Cre; Glp1rfl/fl mice (Glp1rTcell-/-) or controls (Glp1rTcell+/+) fed a high-fat diet (HFD) for 12 weeks followed by 1 week of HFD plus semaglutide (10 ug/kg) or vehicle treatment. Fecal pellets from a group of age-matched, sex-matched control mice were included as a chow control group.

2022-08-29 | GSE202452 | GEO

a7bcbc51-217a-491f-808b-617da8eeca65 - samples

Project description:Fecal samples Illumina MiSeq 16S rRNA sequencing, V4 hypervariable region

| EGAD00001004106 | EGA

Whole rye consumption improves blood and liver n-3 fatty acid profile and gut microbiota composition in rats

Project description:This study in rats was designed to investigate whether whole rhye (WR) can influence the metabolism of n-3 and n-6 long-chain fatty acids (LCFA) and gut microbiota composition. For 12 weeks, rats were fed a diet containing either 50% WR or 50% refined rye (RR). Total bacterial DNA was extracted from fecal and cecal samples (n=5 per group). 16S PCR amplification was performed to assess the microbial diversity at the family level using the HuGChip. Amplified DNA was purified and labelled with either Cy3 or Cy5 dye and hybridized on the microarray. A 15 chip study was realized, each corresponding to hybridization with 250ng of labelled 16S rRNA gene amplicons from either mice fecal and cecal samples. Each probe (4441) was synthetized in three replicates.

2015-08-06 | E-GEOD-71726 | biostudies-arrayexpress

Microarray analysis of microbiota of gingival lesions in noma patients

Project description:We used phylogenetic low-density microarrays targeting the 16S rRNA gene to characterize the gingival flora of acute noma and acute necrotizing gingivitis lesions, and compared them to healthy control subjects of the same geographical and social background. Various types of samples were collected (column characteristics); patients from the same hospital without mouth infection (H), matched control populations (T), patients suffering gengivitis (Gengivitis), patient suffering NOMA (noma), patient suffering NOMA receiving antimicrobials (N-ATB). Sampled from patients were retrieved from both sides (column Description); healthy- or lesion-side of the mouth. All controls are matched with specific patients (see column patient category and number) We designed low-density 16S rDNA arrays representing 339 different phylotypes. We used an arbitrary cutoff of 1% of overall abundance to select from this dataset the most abundant sequences for probe design. Using this cutoff, the 132 most abundant 16S rRNA gene sequences were scanned for probes respecting defined physico-chemical properties (Tm = 65M-BM-15M-BM-0C; probe length = 23M-bM-^@M-^S50 nt; < -5.0 kcal/mol for hairpins; < -8.0 kcal/mol for self-dimers; and dinucleotide repeats shorter than 5 bp) using a commercial software (Array Designer TM 2.0 by Premier Biosoft). The 335 oligonucleotide probes were synthesized with a C6-linker with free primary amine (Sigma-Aldrich) and spotted on ArrayStrips microarrays (Clondiag GmbH, Jena, Germany).

2013-12-27 | E-GEOD-43612 | biostudies-arrayexpress

Microbial diversity of an uncontaminated and a 2,4,6-TNT contaminated soil sample with CodeLink microarrays

Project description:Comparison of probe-target dissociations of probe Eub338 and Gam42a with native RNA of P. putida, in vitro transcribed 16s rRNA of P. putida, in vitro transcribed 16S rRNA of a 2,4,6-trinitrotoluene contaminated soil and an uncontaminated soil sample. Functional ANOVA revealed no significant differences in the dissociation curves of probe Eub338 when hybridised to the different samples. On the opposite, the dissociation curve of probe Gam42a with native RNA of P. putida was significantly different than the dissociation curves obtained with in vitro transcribed 16S rRNA samples. Keywords: Microbial diversity, thermal dissociation analysis, CodeLink microarray

2005-11-05 | GSE3525 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data