Fecal microbiome in pancreatic cancer.
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB42013 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR9190640_1.fastq.gz | Fastqsanger.gz | |||
| ERR9190640_2.fastq.gz | Fastqsanger.gz | |||
| ERR9190650_1.fastq.gz | Fastqsanger.gz | |||
| ERR9190650_2.fastq.gz | Fastqsanger.gz | |||
| ERR9190660_1.fastq.gz | Fastqsanger.gz |
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Project description:Currently, the majority of patients diagnosed with pancreatic ductal adenocarcinoma (PDAC) present with locally invasive and/or metastatic disease, resulting in five-year survival of less than 5%. The development of an early diagnostic test is, therefore, expected to significantly impact the patient’s prognosis. In this feasibility study, we demonstrate for the first time the utility of miRNA biomarkers for non-invasive, early detection of PDAC in urine specimens.
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Project description:Pancreatic ductal adenocarcinoma (PDAC) has a high fatality rate, mainly due to its asymptomatic nature until late-stage disease and therefore delayed diagnosis that leads to a lack of timely treatment intervention. Consequently, there is a significant need for better methods to screen populations that are at high risk of developing PDAC. Such advances would result in earlier diagnosis, more treatment options, and ultimately better outcomes for patients. Several recent studies have applied the concept of liquid biopsy, which is the sampling of a biofluid (such as blood plasma) for the presence of disease biomarkers, to develop screening approaches for PDAC; several of these studies have focused on analysis of extracellular vesicles (EVs) and their cargoes. While these studies have identified many potential biomarkers for PDAC that are present within EVs, their application to clinical practice is hindered by the lack of a robust, reproducible method for EV isolation and analysis that is amenable to a clinical setting. Our previous research has shown that the Vn96 synthetic peptide is indeed a robust and reproducible method for EV isolation that has the potential to be used in a clinical setting. We have therefore chosen to investigate the utility of the Vn96 synthetic peptide for this isolation of EVs from human plasma and the subsequent detection of small RNA biomarkers of PDAC by Next-generation sequencing (NGS) analysis. We find that analysis of small RNA from Vn96-isolated EVs permits the robust discrimination of PDAC patients from non-affected individuals. Moreover, analyses of all small RNA species, miRNAs, and lncRNAs are most effective at segregating PDAC patients from non-affected individuals. We further identified 34 chromosomal regions that encode small RNAs whose differential expression in Vn96-isolated EVs strongly distinguishes PDAC patients from non-affected individuals. Several of the identified small RNA biomarkers have been previously associated with and/or characterized in PDAC, indicating the validity of our findings, whereas other identified small RNA biomarkers may have novel roles in PDAC or cancer in general. Overall, our results provide a basis for a clinically-amendable detection and/or screening strategy for PDAC using a liquid biopsy approach that relies on Vn96-mediated isolation of EVs from plasma.
2023-06-08 | GSE221185 | GEO
Project description:Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancer types, partly because it is frequently identified at an advanced stage, when surgery is no longer feasible. Therefore, early detection using minimally invasive methods such as blood tests may improve outcomes. However, studies to discover molecular signatures for the early detection of PDAC using blood tests have only been marginally successful. In the current study, a quantitative glycoproteomic approach via data-independent acquisition mass spectrometry (DIA-MS) was utilized to detect glycoproteins in 29 patient-matched PDAC tissues and sera. Total of 892 glycopeptides originated from 141 glycoproteins had PDAC associated changes beyond normal variation. We further evaluated the specificity of these serum detectable glycoproteins by comparing their abundance in 53 independent PDAC patient sera and 65 cancer-free controls. The PDAC tissue-associated glycoproteins we have identified represent an inventory of serum detectable PDAC glycoproteins as candidate biomarkers that can be potentially used for the detection of PDAC using blood tests.
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Project description:A metaproteomics analysis was conducted on the infant fecal microbiome to characterize global protein expression in 8 samples obtained from infants with a range of early-life experiences. Samples included breast-, formula- or mixed-fed, mode of delivery, and antibiotic treatment and one set of monozygotic twins. Although label-free mass spectrometry-based proteomics is routinely used for the identification and quantification of thousands of proteins in complex samples, the metaproteomic analysis of the gut microbiome presents particular technical challenges. Among them: the extreme complexity and dynamic range of member taxa/species, the need for matched, well-annotated metagenomics databases, and the high inter-protein sequence redundancy/similarity between related members. In this study, a metaproteomic approach was developed for assessment of the biological phenotype and functioning, as a complement to 16S rRNA sequencing analysis to identify constituent taxa. A sample preparation method was developed for recovery and lysis of bacterial cells, followed by trypsin digestion, and pre-fractionation using Strong Cation Exchange chromatography. Samples were then subjected to high performance LC-MS/MS. Data was searched against the Human Microbiome Project database, and a homology-based meta-clustering strategy was used to combine peptides from multiple species into representative proteins. Bacterial taxonomies were also identified, based on species-specific protein sequences, and protein metaclusters were assigned to pathways and functional groups. The results obtained demonstrate the applicability of this approach for performing qualitative comparisons of human fecal microbiome composition, physiology and metabolism, and also provided a more detailed assessment of microbial composition in comparison to 16S rRNA.
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Project description:The presence of some malignancies, such as cancer, impacts on peripheral blood mononuclear cells (PBMCs) gene expression profiling, suggesting the potential suitability of these genes as diagnostic and prognostic markers. The objective of this study was to identify new markers in peripheral blood that differentiate between PDAC patients and healthy controls as a means of facilitating early detection of the disease. 18 patients with unresectable PDAC were recruited. The diagnosis of PDAC was based on a positive biopsy of the pancreatic mass during the surgery. 18 gender, age, and habits matched healthy controls were also included. Whole genome cDNA microarray hybridization of PBMC samples was performed to identify potential PDAC markers.
2013-08-12 | E-GEOD-49641 | biostudies-arrayexpress
Project description:Pancreatic ductal adenocarcinoma (PDAC) suffers from lack of an effective diagnostic method, limiting improvement in patient survival. Although the FDA-approved biomarker CA19-9 has been used for detection and surveillance of PDAC, its clinical utility is generally regarded to be limited due to its suboptimal diagnostic performance. Liquid chromatography-mass spectrometry (LC-MS) has emerged as a burgeoning technology in clinical proteomics, and identified a plethora of protein biomarker candidates for PDAC. Yet few if any has successfully transitioned into clinical practice. This translational standstill is owed partly to the limited considerations of practical needs and perspectives of clinical implementation in the course of a biomarker pipeline, such as demonstrating analytical validity of proposed biomarkers, which is critical to turning research-grade assays to clinical-grade tests. Here, we developed a fit-for-purpose multi-marker panel for PDAC diagnosis by consolidating analytically robust biomarkers as well as employing a relatively simple LC-MS method. In the discovery phase, we systematically collected putative biomarkers from both in-house proteomics data and the large volume of literature documenting PDAC biomarkers. In the verification phase, we developed a multiple-reaction monitoring (MRM)-MS-based proteomic assay using surrogate peptides that passed stringent analytical validation criteria. Given the intended use of our panel (i.e., primary screening), we adopted a high-throughput protocol including short gradient (<10 min) and simple sample preparation (no depletion or enrichment steps). To further facilitate clinical implementation, we performed verification of our panel on serum samples, which are usually the preferred biospecimen available in clinical settings. We developed a stacking ensemble model based on our final panel of 12 protein biomarkers combined with CA19-9, which showed improved diagnostic performance compared to using CA19-9 alone (AUC 0.919 and 0.830, respectively). A large-scale clinical validation study is underway to demonstrate the clinical validity of our panel.
2024-08-12 | PXD048034 | Pride
Project description:Pancreatic cancer (PC) is a leading cause of cancer-related death in developed countries, and since most patients have incurable disease at the time of diagnosis, developing a screening method for early detection is of high priority. Due to its metabolic importance, alterations in pancreatic functions may affect the composition of the gut microbiota, potentially yielding biomarkers for PC. However, the usefulness of these biomarkers may be limited if they are specific for advanced stages of disease, which may involve comorbidities such as biliary obstruction or diabetes. In this study we analyzed the fecal microbiota of 30 patients with pancreatic adenocarcinoma, 6 patients with pre-cancerous lesions, 13 healthy subjects and 16 with non-alcoholic fatty liver disease, using amplicon sequencing of the bacterial 16S rRNA gene. Fourteen bacterial features discriminated between PC and controls, and several were shared with findings from a recent Chinese cohort. A Random Forest model based on the microbiota classified PC and control samples with an AUC of 82.5%. However, inter-subject variability was high, and only a small part of the PC-associated microbial signals were also observed in patients with pre-cancerous pancreatic lesions, implying that microbiome-based early detection of such lesions will be challenging.
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Project description:human fecal microbiome Raw sequence reads
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Project description:Objective Crohn’s Disease (CD) and Ulcerative Colitis (UC) are chronic inflammatory diseases of the gastrointestinal tract. Reliable diagnosis of these diseases requires a comprehensive examination of the patient, which include invasive endoscopy. This study assesses whether non-invasive LC-MS/MS based analysis of microbial and human proteins from feces may support the diagnosis of the diseases. Design In order to mimic a representative clinical background for this study, we investigated 17 healthy controls, 11 CD patients, 14 UC patients, also 13 Irritable Bowel Disease (IBS) patients, 8 Colon Adenoma (CA) patients, and 8 Gastric Carcinoma (GCA) patients. The proteins were extracted from the fecal samples with liquid phenol in a ball mill. Subsequently, the proteins were digested tryptically to peptides and analyzed by liquid chromatography coupled to an Orbitrap MS/MS. For protein identification and interpretation of taxonomic and functional results, the MetaProteomeAnalyzer software and the UniProtKB/SwissProt database and several metagenomes from human fecal samples were used. Results Cluster analysis and ANOSIM show a separation of healthy controls from patients with CD and UC as well as from patients with GCA. Among others, UC and CD correlated with an increase of neutrophil extracellular traps and immunoglobulins G (IgG) as well as a decrease of IgA. A specific marker metaprotein for CD was an increase of the human enzyme sucrose-isomaltase. IBS and CA patient’s fecal metaproteome showed only minor alterations. Conclusion Metaproteome analysis distinguished between patients with UC, CD and healthy controls and is therefore useful as a non-invasive tool for routine diagnostics in hospitals.
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