Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Prospective observational study of colorectal cancer examining diagnosis opportunity and risk factors, CRC-DR study

ABSTRACT: Primary outcome(s): Motivation and Symptoms of Colorectal Cancer Detection in Intramucosal vs. Invasive Cancer

DISEASE(S): Colorectal Cancer

PROVIDER: 112304 | ecrin-mdr-crc |

REPOSITORIES: ECRIN MDR

ACCESS DATA

Json Xml

Similar Datasets

Genetic lineage analysis in intramucosal gland-forming gastric neoplasms

Project description:To predict the progression risk of non-invasive gland-forming gastric neoplasms to invasive carcinoma, we assessed lineage continuity or discontinuity between the non-invasive and invasive neoplasms by applying hierarchical clustering analysis to the gene copy-number profiles of individual tumours. array-based Comparative Genomic Hybridization. Samples are including of 7 tumours of Vienna category 3, 12 tumours of Vienna category 4, 8 intramucosal cancers (Vienna category 5), 16 intramucosal lesions and 16 invasive parts (Vienna category 5); 40 reference for control, 19 control replicates

2014-08-06 | E-GEOD-60116 | biostudies-arrayexpress

SWATH-MS based protein quantification for diagnosis in systemic lupus erythematous

Project description:The gold standard for diagnosing lupus nephritis, one of the common symptoms of systemic lupus erythematosus, is an invasive procedure, a Renal biopsy. To overcome the risk of invasive methods, we constructed a spectral library using biological samples that can be obtained non-invasively and analyzed it using the SWATH-MS method, a quantitative proteomic analysis.

2023-10-24 | PXD040099 | Pride

Development of diagnosis method for LTBI with circulating miRNA

Project description:When exposed to M. tuberculosis, 25-50% become infected, of which 10-20% having several symptoms. Currently, there is no marker for judging the efficacy of M tuberculosis (Mtb) treatment, and it is judged based on the appearance of subjective symptoms and radiological findings. In this study, we attempted to establish a marker to distinguish patients who relapsed after TB treatment from patients who had recurrence after TB treatment using the information of circulating miRNA expression. Thirty two patients with tuberculosis infection aged 18 years or older were enrolled. 16 patients had onset or recurrence of TB and 16 patients with latent tuberculosis infection (LTBI) with positive test for Interferon gamma release assays (IGRA) and no chest X-ray examination. Total RNA from serum in exosome-rich fraction was extracted and then miRNA expression analysis was performed using a next-generation sequencer and NGS data analyzed using miRDeep2. Using expression information of nine miRNAs, TB and LTBI could be separated with 71.8% accuracy. The odds ratio also was 6.16, and the p-value was 3.20e-02, respectively. The expression of hsa-miR-122-5p was significantly different between TB and LTBI (p <0.05). Here we established a novel method to efficiently differentiate LTBI from patients with tuberculosis infection. Since this method can be performed in a low invasive manner such as blood sampling, it is promising tool for utilizing follow-up of TB treatment.

2021-03-18 | GSE149645 | GEO

Epigenetic array data of saliva samples in individiduals with esophageal cancer with controls

Project description:We took saliva samples from 89 people with oesophageal cancer (plus 9 with high grade dysplasia, also labelled here as cancer) and 167 controls. We took replicate samples on 6 cancer samples and 4 controls to assess reproducibility. The cancer groups comprise people with invasive adenocarcinoma (61 and also 6 replicates), 28 people with intramucosal adenocarcinoma, 9 people with high-grade dysplasia arising in Barrett's esophagus, 52 patients with non-dysplastic Barrett's esophagus, 42 people with no positive diagnosis after endoscopy (ie no Barrett's, + 1 replicate), and 73 self-reported healthy volunteers (with 3 duplicates)

2024-02-07 | GSE232332 | GEO

NMR-based Metabolomics for CRC Diagnosis

Project description: Not available

| ST000285 | MetabolomicsWorkbench

Epigenetic array data of saliva samples in individiduals with esophageal cancer (with controls)

Project description:We previously deposited a similar batch of data to the Gene Expression Omnibus (GEO) database under the accession code GSE232332. This dataset was to be a further validation of that study. Unlike the previous dataset, this has not, however, been submitted for publication. This dataset includes epigenetic data form 23 patients with invasive oesophageal adenocarcinoma, 25 with intramucosal oesophageal adenocarcinoma, 35 patients with non-dysplastic Barrett's esophagus and 32 controls who did not have Barrett's esophagus or cancer at endoscopy, performed within 2 weeks of the saliva sample which was obtained after fasting for at least 1 hour.

2025-05-31 | GSE232497 | GEO

Discovery of Novel Serum Peptide Biomarkers for Hepatobiliary Disease and Cholangiocarcinoma Staging Diagnosis Using MALDI-TOF MS and LC-MS/MS

Project description:Cholangiocarcinoma (CCA) is a highly aggressive malignancy often diagnosed at an advanced stage due to the absence of specific early symptoms, thereby limiting treatment options and resulting in a poor prognosis. Current cancer staging primarily depends on postoperative histopathological evaluation, requiring surgical resection for accurate staging. This reliance causes delays in staging and subsequently affects treatment planning. Given the challenges in early diagnosis and accurate staging of CCA, there is an urgent need for non-invasive and precise diagnostic tools to improve patient outcomes.

2026-02-24 | PXD061116 | JPOST Repository

Machine Learning-Based Diagnosis of Adenomyosis Uteri Using Serum and Urine miRNA Profiles

Project description:Background: Adenomyosis uteri is a chronic gynecological condition frequently coexisting with endometriosis, presenting significant diagnostic challenges due to overlapping symptoms and limitations in imaging techniques. There is a pressing need for reliable, non-invasive biomarkers to enhance diagnostic accuracy and improve patient care. Objective: This pilot study investigated the diagnostic potential of serum and urine microRNA (miRNA) profiles for adenomyosis using machine learning approaches. Methods: Serum and urine samples were collected from 59 patients undergoing surgery for chronic pelvic pain at the Endometriosis Center, RWTH Aachen University Hospital. Among them, 7 had isolated adenomyosis, 34 had histologically confirmed endometriosis, and 18 served as negative controls. miRNA profiling was conducted via next-generation sequencing. A comprehensive feature selection pipeline—including variance filtering, univariate testing, mutual information, and recursive feature elimination—was used to reduce dimensionality. Classification models (Logistic Regression, Random Forest, Support Vector Machine, and Decision Tree) were trained with cross-validation and evaluated using accuracy, precision, recall, F1 score, and ROC-AUC.

2026-05-27 | GSE298298 | GEO

Factors associated with seasonal influenza self-diagnosis: a prospective observational study in Japan.

Project description: Not available

| S-EPMC7090047 | biostudies-literature

circRNA expression files in invasive CRC cells

Project description:circRNA expression files in invasive CRC cells

| PRJNA803891 | ENA