Risk Stratification of Colorectal Adenomas and Cancer From Stool Microbiota
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB29239 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR2848630_1.fastq.gz | Fastqsanger.gz | |||
| ERR2848630_2.fastq.gz | Fastqsanger.gz | |||
| ERR2848640_1.fastq.gz | Fastqsanger.gz | |||
| ERR2848640_2.fastq.gz | Fastqsanger.gz | |||
| ERR2848650_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 2370 |
Similar Datasets
Project description:using fecal microbiota composition as a non-invasive diagnostic tool to classify colorectal carcinoma and adenoma.
| PRJEB35850 | ENA
Project description:Dysbiotic configurations of the human gut microbiota have been linked with colorectal cancer (CRC). Human small non-coding RNAs are also implicated in CRC and recent findings suggest that their release in the gut lumen contributes to shape the gut microbiota. Bacterial small RNAs (bsRNAs) may also play a role in carcinogenesis but their role is less explored. Here, we performed small RNA and shotgun sequencing on 80 stool specimens of patients with CRC, or adenomas, and healthy subjects collected in a cross-sectional study to evaluate their combined use as a predictive tool for disease detection. We reported a considerable overlap and correlation between metagenomic and bsRNA quantitative taxonomic profiles obtained from the two approaches. Furthermore, we identified a combined predictive signature composed by 32 features from human and microbial small RNAs and DNA-based microbiome able to accurately classify CRC from healthy and adenoma samples (AUC= 0.87). In summary we reported evidence that host-microbiome dysbiosis in CRC can be observed also by altered small RNA stool profiles. Integrated analyses of the microbiome and small RNAs in the human stool may provide insights for designing more accurate tools for diagnostic purposes.
2019-08-30 | GSE132236 | GEO
Project description:Background and Aims: RNA biomarkers derived from sloughed enterocytes would provide an ideal, non-invasive method for early detection of colorectal cancer (CRC) and precancerous adenomas. To realize this goal, a highly reliable method to isolate preserved human RNA from stool samples is needed. Here we develop a protocol to identify RNA biomarkers associated with CRC to assess the use of these biomarkers for noninvasive screening of disease. Methods: Stool samples were collected from 454 patients prior to a colonoscopy. A nucleic acid extraction protocol was developed to isolate human RNA from 330 stool samples and transcript abundances were estimated by microarray analysis. This 330-patient cohort was split into a training set of 265 individuals to develop a machine learning model and a testing set of 65 individuals to determine the model’s ability to detect colorectal neoplasms. Results: Analysis of the transcriptome from 265 individuals identified 200 transcript clusters as differentially expressed (p<0.03). These transcripts were used to build a Support Vector Machine (SVM) based model to classify 65 individuals within the testing set. This SVM algorithm attained a 95% sensitivity for precancerous adenomas and a 65% sensitivity for CRC (stage I-IV). The machine learning algorithm attained a specificity of 59% for healthy individuals and an overall accuracy of 72.3%. Conclusions: We developed an RNA-based neoplasm detection model that is sensitive for CRC and precancerous adenomas. The model allows for non-invasive assessment of tumors and could potentially be used to provide clinical guidance for individuals within the screening population for colorectal cancer.
2019-02-25 | GSE99573 | GEO
Project description:Background and Aims: Colorectal adenomas (CRAs) are precursor lesions that can progress to adenocarcinomas. Current clinical guidelines categorize patients into risk groups based on adenoma characteristics observed during index colonoscopy, but this may lead to overtreatment. Our aim was to establish a molecular feature-based risk allocation framework towards improved patient stratification. Methods: Deep Visual Proteomics (DVP) is a novel approach that combines image-based artificial intelligence with automated microdissection and ultra-high sensitive mass spectrometry. Here we used DVP on formalin-fixed, paraffin-embedded (FFPE) CRA tissues from nine patients. Immunohistological staining for Caudal-type homeobox 2 (CDX2), a gene implicated in colorectal cancer, enabled the characterization of cellular heterogeneity within distinct tissue regions and across patients. Results: DVP seamlessly integrated with current pathology workflows and equipment, identifying deleted in malignant brain tumors 1 (DMBT1), myristoylated alanine rich protein kinase C (MARCKS), and cluster of differentiation 99 (CD99) correlated with disease recurrence history, making them potential markers of risk stratification. The spatial and cell type specific capabilities of DVP uncovered a metabolic switch towards anaerobic glycolysis in areas of high dysplasia, which was specific for the cells with high CDX2 expression. Conclusion: The application of spatially resolved proteomics to CRA revealed three new potential markers for early-stage tumor development, and provided novel insights into metabolic reprogramming. Our findings underscore the potential of this technology to refine early-stage detection and contribute to personalized patient management strategies.
2024-08-04 | PXD046999 | Pride
Project description:We report the RNA-seq data of 40 advanced colorectal adenoma patients form Dongguk University Ilsan International Hospital. The polyps with a diameter of 1cm or greater were regarded as advenced colorectal adenoma and obtained through colonoscopy. The data consist of 22 tublar adenoma, 6 tublovillous adenoma, 5 sessile serrated adenoma/polyp, 1 traditional serrated adenoma, intramucosal adenocarcinoma, neuroendocrine tumor, hyperplastic polyp, inflammatory polyp, high grade dysplasia, and atypical glands with adjacent hyperplastic mucosa.
2023-08-07 | GSE154548 | GEO
Project description:Traditional serrated adenoma (TSA) remains the least understood of all the colorectal adenomas although these lesions have been associated with a significant cancer risk- twice that of the conventional adenoma (CAD) and of the sessile serrated adenoma (SSA/P). This study was performed to investigate the proteomic profiles of the different colorectal adenomas to better assess the pathogenesis of TSA. We performed a global quantitative expression profile of 44 colorectal adenomas (12 TSA, 15 CAD, 17 SSA/Ps) and 17 normal colonic mucosa, conserved as formalin-fixed paraffin-embedded samples, by the label-free quantification (LFQ) method. Unsupervised consensus hierarchical clustering applied to the whole proteomic profile of the 44 colorectal adenomas identified four subtypes. The C1 and C2 were well-individualized clusters composed of most of the CAD (14/15) and most of the SSA (13/17) respectively. This is consistent with the fact that CAD and SSA/Ps are homogeneous but distinct colorectal adenoma entities. In contrast, TSA were subdivided into C3 and C4 clusters that also contained CAD and SSA/Ps, consistent with the more heterogeneous entity of TSA at the morphological and molecular levels. The comparison of the proteome expression profile between the adenoma subtypes and normal colonic mucosa further confirmed the heterogeneous nature of TSA that merged either on CAD or SSA, while CAD and TSA formed homogeneous and distinct entities. Furthermore, we identified LEFTY1 a new potential marker for TSA that may be relevant for the TSA pathogenesis. LEFTY1 is an inhibitor of the Nodal/TGFb pathway that we found to be one of the most overexpressed proteins specifically in the TSA and confirmed by immunohistochemistry. Taken together, our study confirms that CAD and SSA form homogenous but distinct colorectal adenoma entities while TSA are an heterogeneous entity and may arise from either SSA or from normal mucosa that will evolve along the conventional adenoma pathway.
2020-01-21 | PXD014511 | Pride
Project description:ObjectiveFor individuals with 1-2 small (<1 cm) low-risk colorectal adenomas, international guidelines range from no surveillance to offering surveillance colonoscopy in 5-10 years. We hypothesised that the risks for metachronous advanced neoplasia (AN) among patients with low-risk adenomas differ based on clinical factors distinct from those currently used.DesignWe pooled data from seven prospective studies to assess the risk of metachronous AN. Two groups with 1-2 small adenomas were defined based on guidelines from the UK (n=4516) or the European Union (EU)/US (n=2477).ResultsAbsolute risk of metachronous AN ranged from a low of 2.9% to a high of 12.2%, depending on specific risk factor and guideline used. For the UK group, the highest absolute risks for metachronous AN were found among individuals with a history of prior polyp (12.2%), villous histology (12.2%), age ≥70 years (10.9%), high-grade dysplasia (10.9%), any proximal adenoma (10.2%), distal and proximal adenoma (10.8%) or two adenomas (10.1%). For the EU/US group, the highest absolute risks for metachronous AN were among individuals with a history of prior polyp (11.5%) or the presence of both proximal and distal adenomas (11.0%). In multivariate analyses, strong associations for increasing age and history of prior polyps and odds of metachronous AN were observed, whereas more modest associations were shown for baseline proximal adenomas and those with villous features.ConclusionsRisks of metachronous AN among individuals with 1-2 small adenomas vary according to readily available clinical characteristics. These characteristics may be considered for recommending colonoscopy surveillance and require further investigation.
| S-EPMC8248523 | biostudies-literature
Project description:human blood plasma proteomes of colorectal adenoma, colorectal cancer and control patients
2019-10-01 | PXD007844 | JPOST Repository
Project description:We showed that some microRNAs could be characteristic of the progression from adenoma to adenocarcinoma in colorectal cancer.
2013-08-30 | GSE50194 | GEO
Project description:Colorectal cancer (CRC) develops from normal epithelium, through a benign precursor lesion called adenoma, by accumulation of genetic alterations affecting oncogenes and tumour suppressor genes. About 5% of colorectal adenomas are estimated to progress to CRC. However, it is important to identify which adenomas actually are at high-risk of progression, because these should serve as intermediate endpoints for e.g. CRC screening programs. In clinical practice, adenomas with a size of ≥10 mm, villous component and/or high-grade dysplasia, called advanced adenomas, are considered high-risk, although this classification lacks solid evidence. Specific DNA copy number changes are associated with adenoma-to-carcinoma progression.For this tissue dataset, we applied low-pass whole genome sequencing to 98 non-advanced and advanced adenomas. These adenomas were classified as lesions with low-risk or high-risk of progression, according to the presence of specific DNA copy number changes (Carvalho et al, CancerPrevRes, 2018).
| EGAS00001002953 | EGA