Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1167935 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR30861100_1.fastq.gz | Fastqsanger.gz | |||
| SRR30861100_2.fastq.gz | Fastqsanger.gz | |||
| SRR30861101_1.fastq.gz | Fastqsanger.gz | |||
| SRR30861101_2.fastq.gz | Fastqsanger.gz | |||
| SRR30861102_1.fastq.gz | Fastqsanger.gz |
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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:Interventions: Group 1: Surgical patients undergoing surgery for colorectal cancer: immunophenotyping by PBMCs and metagenomic analyses from stool, mucosa, and saliva samples perioperatively and during oncologic follow-up.
Group 2: oncologic patients with chemo- / immune therapy without recent surgery:
Immunophenotyping by PBMCs and metagenomic analyses from stool, mucosa and saliva samples during therapy and oncological follow-up.
Group 3: healthy controls:
Immunophenotyping by PBMCs and metagenomic analyses from stool, mucosa, and saliva samples at the time of screening colonoscopy.
Primary outcome(s): Difference in the differential abundance of the colonic mucosa of patients with CRC vs. healthy controls for evaluation as diagnostic biomarkers based on metagenomic analyzes (microbial pattern)
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| 2439680 | ecrin-mdr-crc
Project description:The current treatment for Celiac Disease (CD) is adhering to a gluten-free diet (GFD), although its long-term molecular effects are still undescribed. New molecular features detectable in faecal samples may improve and facilitate non-invasive clinical management of CD on GFD. For this purpose, faecal small non-coding RNAs (sncRNAs) and gut microbiome profiles were concomitantly explored in CD subjects in relation to strict (or not) GFD adherence over time. In the present observational study, we performed small RNA and shotgun metagenomic sequencing in stool from 63 treated CD (tCD) subjects and 66 sex- and age-matched healthy controls. tCD included 51 individuals on strict GFD and with negative transglutaminase (TG) serology (tCD-TG-) and 12 symptomatic with not strict/short-time of GFD adherence and positive TG serology (tCD-TG+). Samples from additional 40 adult healthy individuals and from a cohort of 19 untreated paediatric CD subjects and 19 sex/age matched controls were analyzed to further test the outcomes. Several miRNA, other sncRNA (piRNA and tRNA) and microbiota profiles were altered in tCD subjects(adj.p<0.05). Findings were validated in one external group of controls. In tCD-TG-, GFD duration correlated with five miRNA levels (p<0.05): for miR-4533-3p and miR-2681-3p, the longer the diet adherence, the less the expression differed from controls. tCD-TG+ and untreated paediatric CD patients showed a similar miRNA dysregulation. Immune-response, trans-membrane transport and cell death pathways were enriched in targets of identified miRNAs. Bifidobacterium longum, Ruminococcus bicirculans and Haemophilus parainfluenzae abundances shifted (adj. p<0.05) with a progressive reduction of denitrification pathways with GFD length. Integrative analysis highlighted 121 miRNA-bacterial relationships (adj.p<0.05). Specific faecal sncRNA and microbial patterns characterise CD subjects on GFD, reflecting either the long-term effects or the gut inflammatory status, in case of a not strict/short-time adherence. Our findings suggest novel host-microbial interplays and could help the discovery of biomarkers for the clinical monitoring of GFD over time.
2022-11-14 | GSE217915 | GEO
Project description:Extracellular vesicles (EVs) are valuable sources for the discovery of useful cancer biomarkers. This study explores the potential usefulness of tumor cell-derived EV membrane proteins as plasma biomarkers for early detection of colorectal cancer (CRC). EVs were isolated from the culture supernatants of four CRC cell lines by ultracentrifugation, and their protein profiles were analyzed by LC-MS/MS. Bioinformatics analysis of identified proteins revealed 518 EV membrane proteins in common among at least three CRC cell lines. We next used accurate in-clusion mass screening (AIMS) in parallel with iTRAQ-based quantitative proteomic analysis to highlight candidate proteins and validated their presence in pooled plasma-generated EVs from 30 healthy controls and 30 CRC patients. From these, we chose 14 potential EV-derived targets for further quantification by targeted MS assay in a separate individual cohort comprising of 73 CRC and 80 healthy subjects. Quantitative analyses revealed significant increases in ADAM10, CD59 and TSPAN9 levels (2.19- to 5.26-fold, p <0.0001) in plasma EVs from CRC patients, with AUC values of 0.83, 0.95 and 0.87, respectively. Higher EV CD59 levels were significantly corre-lated with distant metastasis (p = 0.0475), and higher EV TSPAN9 levels were significantly asso-ciated with lymph node metastasis (p = 0.0011), distant metastasis at diagnosis (p = 0.0104) and higher TNM stage (p = 0.0065). A two-marker panel consisting of CD59 and TSPAN9 outper-formed the conventional marker CEA in discriminating CRC and stage I/II CRC patients from healthy controls, with AUC values of 0.98 and 0.99, respectively. Our results identify EV mem-brane proteins in common among CRC cell lines and altered plasma EV protein profiles in CRC patients, and suggest plasma EV CD59 and TSPAN9 as a novel biomarker panel for detecting early-stage CRC.
2023-03-11 | PXD038871 | Pride
Project description:Metagenomic shotgun sequencing of Irritable bowel syndrome patients and matched controls
| EGAD00001002668 | EGA
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:Stool samples from three patients with biliary atresia after Kasai portoenterostomy (BA-KPE) and four non-BA healthy controls (non-BA) were analyzed by overlapping DIA-MS.
2023-02-02 | PXD031394 | JPOST Repository
Project description:Background: Colorectal cancer (CRC) is one of the major causes of cancer-related death worldwide. Although commercial biomarkers of CRC are currently available, they are still lacking in terms of sensitivity and specificity; thus, searching for reliable blood-based biomarkers are important for the primary screening of CRC. Methods: Plasma samples of patients with non-metastatic (NM) and metastatic (M) CRC and healthy controls were fractionated using MARS-14 immunoaffinity chromatography. The flow-through and elute fractions representing low- and high-abundant proteins, respectively, were analyzed by label-free quantitative proteomics mass spectrometry. The functional analysis of the proteins with greater than 1.5-fold differential expression level between the CRC and the healthy control groups were analyzed for their biological processes and molecular functions. In addition, the levels of plasma proteins showing large alterations in CRC patients were confirmed by immunoblotting using two independent cohorts. Moreover, receiver operating characteristic (ROC) curve analysis was performed for individual and combinations of biomarker candidates so as to evaluate the diagnostic performance of biomarker candidates. Results: From 163 refined identifications, five proteins were up-regulated and two proteins were down-regulated in NM-CRC while eight proteins were up-regulated and three proteins were down-regulated in M-CRC, respectively. Altered plasma proteins in NM-CRC were mainly involved in complement activation, while those in M-CRC were clustered in acute-phase response, complement activation, and inflammatory response. Results from the study- and validation-cohorts indicate that the levels of LRG, C9, AGP1, and A1AT were statistically increased, while FN level was statistically decreased in CRC patients compared to healthy controls, with most alterations found in a metastatic stage-dependent manner. ROC analysis revealed that FN exhibited the best diagnostic performance to discriminate CRC patients and healthy controls while AGP1 showed the best discrimination between the disease stages in both cohorts. The combined biomarker candidates, FN+A1AT+AGP1, exhibited perfect discriminatory power to discriminate between the CRC population and healthy controls whereas LRG+A1AT+AGP1 was likely to be the best panel to discriminate the metastatic stages in both cohorts. Conclusions: This study identified and quantified distinct plasma proteome profiles of CRC patients. Selected CRC biomarker candidates including FN, LRG, C9, A1AT, and AGP1 may be further applied for screening larger cohorts.
2023-03-29 | PXD040999 | Pride