Pancreatic Cyst Fluid Microbiota Profiling
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB31827 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR3244690_subreads.fastq.gz | Fastqsanger.gz | |||
| ERR3244700_subreads.fastq.gz | Fastqsanger.gz | |||
| ERR3244710_subreads.fastq.gz | Fastqsanger.gz | |||
| ERR3244720_subreads.fastq.gz | Fastqsanger.gz | |||
| ERR3244691_subreads.fastq.gz | Fastqsanger.gz |
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Project description:The increased number of pancreatic cyst lesions (PCLs) have been detected through the development of abdominal imaging techniques, such as computed tomography (CT), magnetic resonance imaging (MRI), and endoscopic ultrasound (EUS). However, accurate classification of cystic lesions is difficult because of the lack of standardized diagnostic methods, and thus potentially unnecessary surgical resection has been performed on pancreatic cyst patients. Among four most common types of cystic lesions of pancreas, intraductal papillary mucinous neoplasms (IPMNs), mucinous cystic neoplasms (MCN), serous cystic neoplasms (SCN), and solid pseudopapillary neoplasms (SPNs), IPMNs, the precursor lesion of pancreatic cancer, have been detected most frequently, and are subdivided into low-grade dysplasia (LGD), high-grade dysplasia (HGD), and invasive IPMN in accordance with their malignancy. To discover the potential biomarkers of the histological grades of IPMN, we investigated pancreatic cyst fluid proteins that are differentially expressed in accordance with the IPMN malignancy by LC-MS/MS analysis.
2020-09-06 | PXD016127 | Pride
Project description:Determination of pancreatic cyst fluids (PCF) peptidome and proteome in 5 distinct patient groups: malignant (CAs), intraductal papillary mucinous neoplasms (IPMNs), mucinous cystic neoplasms (MCNs), serous cystic neoplasms (SCNs), and pseudocysts (PCs). The PCF <5kDa fraction, referred as the degradome, and proteome profiles were determined using a LTQ-Orbitrap Elite mass spectrometer coupled with a nanoAcquity LC system. Qualitative LC-MS/MS analyses were ran on pooled samples from all patients.
2019-01-14 | PXD005248 | Pride
Project description:Intraductal papillary mucinous neoplasm (IPMN) is a benign tumor that grows within the pancreatic ducts characterized by the production of thick mucinous fluid by surrounding tumor cells. IPMN is the most important precursor lesion for pancreatic cancer that is the fourth most common cause of cancer deaths. Differentiating between low-grade dysplasia (LGD), high-grade dysplasia (HGD), and invasive intraductal papillary mucinous neoplasms (IPMNs) remains a diagnostic challenge with current biomarkers, necessitating the development of novel biomarkers that can distinguish IPMN malignancy. We investigated differentially expressed proteins among pancreatic cyst fluids consisted of LGD, HGD, and invasive IPMN patients by using our novel proteomic strategy, and finally we discovered pancreatic cyst fluid protein marker candidates that can predict the malignant potential of IPMNs.
2018-05-01 | PXD008302 | Pride
Project description:The pancreatic cyst fluids were collected using a syringe aspiration of the cyst fluid immediately after surgical resection of the lesion. The cyst fluid were then aliquoted and stored in -80C freezer until ready to use. We plan on performing untargeted metabolomics analysis and unknown lipid analysis and identification on these pancreatic cyst fluid to find potential biomarkers that correlate with histopathological assessment and clinical behavior of these cystic lesions and thus to guide clinical management of patients. Abbreviations: IPMN - Intraductal Pancreatic Mucinous Neoplasm; MCN - mucinous cystic neoplasm; SCA - serous cystadenoma.
2017-07-14 | ST000823 | MetabolomicsWorkbench
Project description:Intraductal papillary mucinous neoplasm (IPMN) is a duct-dilating precancerous lesion that grows in pancreatic ducts and is accompanied by the production of mucinous fluid. In recent years, its cystic fluid has been used molecularly for the differential diagnosis of other cystic tumors and malignancies. Thus, proteomic research of IPMN cyst fluid must be performed to identify an effective diagnostic biomarker. We examined the IPMN cyst fluid proteome using a novel proteomic strategy, combined with high-resolution LC-MS/MS. Although we did not deplete any high-abundance proteins, our dataset consistently detected thousands of proteins including pancreatic tumor markers, such as mucin family members, S100 proteins, and CEA-related proteins. In addition, we found 590 protein mutations through a variant sequence database search. Bioinformatics analyses were performed to determine biological functions and clinical meanings of canonical IPMN proteins and mutated proteins. Our proteomic platform and in-depth proteome dataset are valuable references that can be used in future studies.
2017-08-22 | PXD005671 | Pride
Project description:The pancreatic cyst fluids were collected using a syringe aspiration of the cyst fluid immediately after surgical resection of the lesion. The cyst fluid were then aliquoted and stored in -80C freezer until ready to use. We plan on performing untargeted metabolomics analysis on these pancreatic cyst fluid to find potential biomarkers that correlate with histopathological assessment and clinical behavior of these cystic lesions and thus to guide clinical management of patients.
2017-06-19 | ST000713 | MetabolomicsWorkbench
Project description:<h4><strong>BACKGROUND</strong> Increasing evidence implicates microbiome involvement in the development and progression of pancreatic ductal adenocarcinoma (PDAC). Studies suggest that reflux of gut or oral microbiota can lead to colonization in the pancreas, resulting in dysbiosis that culminates in release of microbial toxins and metabolites that potentiate an inflammatory response and increase susceptibility to PDAC. Moreover, microbe-derived metabolites can exert direct effector functions on precursors and cancer cells, as well as other cell types, to either promote or attenuate tumor development and modulate treatment response.</h4><p><strong>CONTENT</strong> The occurrence of microbial metabolites in biofluids thereby enables risk assessment and prognostication of PDAC, as well as having potential for design of interception strategies. In this review, we first highlight the relevance of the microbiome for progression of precancerous lesions in the pancreas and, using liquid chromatography-mass spectrometry, provide supporting evidence that microbe-derived metabolites manifest in pancreatic cystic fluid and are associated with malignant progression of intraductal papillary mucinous neoplasm(s). We secondly summarize the biomarker potential of microbe-derived metabolite signatures for (a) identifying individuals at high risk of developing or harboring PDAC and (b) predicting response to treatment and disease outcomes.</p><p><strong>SUMMARY</strong> The microbiome-derived metabolome holds considerable promise for risk assessment and prognostication of PDAC.</p>
2023-08-09 | MTBLS7260 | MetaboLights
Project description:Differentiation between mucinous and non-mucinous pancreatic cysts is exceedingly important and challenging, particularly as the former bears malignant transformation potential. Pancreatic cyst fluid (PCF)-based diagnostics, including analyses of biochemical markers, as well as cytology, has shown inadequate accuracy. Herein, a preliminary single-center study of 22 PCF samples, collected by endoscopic ultrasound-guided fine needle aspiration (EUS-FNA), assessed the rheological behavior of PCF and its correlation with lesion type. The dependence of PCF shear viscosity on shear rate was found to follow a power law and could be fitted using Ostwald-de Waele model. Three types of flow curves were identified, where two types correlated with non-mucinous cysts, differing by their power law exponent, and the third type corresponding to mucinous cysts. Viscosity measured at a high shear rate was shown to serve as an accurate and independent marker distinguishing between mucinous and non-mucinous cysts, with an optimal cutoff value of ?c?=?1.3?cP The accuracy of this novel technique proved superior to string-sign, cytology, carcinoembryonic antigen, and amylase assessments. Moreover, the combined predictive value of ?c and patient age provided for sensitivity and specificity of 100% and 95.5%, respectively. This simple and rapid diagnostic tool can be immediately implemented after EUS-FNA sampling.
| S-EPMC5372360 | biostudies-literature
Project description:MicroRNA (miRNA) expression profiles have been described in pancreatic ductal adenocarcinoma (PDAC), but these have not been compared with premalignant lesions. We wished to identify miRNA expression profiles in pancreatic cystic tumors with low malignant potential (serous microcystic adenomas) and high malignant potential (mucinous cystadenoma and intraductal papillary mucinous neoplasm (IPMN)) and compare these to PDAC and carcinoma-ex-IPMN (CEI). n= 20 samples Benign Pancreatic Cystic Tumour (n=7 Microcystic, n= 6 Mucinous, n= 7 IPMN) were compared with n= 9 samples of carcinoma ex IPMN and n= 14 samples of pancreatic cancer (adenocarcinoma) for known homo sapiens miRNAs (mirbase 13).
2011-05-18 | E-GEOD-29352 | biostudies-arrayexpress
Project description:It is clear that specific intestinal bacteria are involved in the development of different premalignant conditions along the gastrointestinal tract. An analysis of the microbial constituents in the context of pancreatic cystic lesions has, however, as yet not been performed. This consideration prompted us to explore whether endoscopically obtained pancreatic cyst fluids (PCF) contain bacterial DNA and to determine the genera of bacteria present in such material.Total DNA was isolated from 69 PCF samples. Bacterial 16S rRNA gene-specific PCR was performed followed by Sanger sequencing and de novo deep sequencing for the V3-V4 variable region of 16S rRNA gene.We observed that 98.2% of the samples were positive in conventional PCR, and that 100% of selected PCF samples (n = 33) were positive for bacterial microbiota as determined by next generation sequencing (NGS). Comprehensive NGS data analysis of PCF showed the presence of 408 genera of bacteria, of which 17 bacterial genera were uniquely abundant to PCF, when compared to the Human Microbiome Project (HMP) database and 15 bacterial microbiota were uniquely abundant in HMP only. Bacteroides spp., Escherichia/Shigella spp., and Acidaminococcus spp. which were predominant in PCF, while also a substantial Staphylococcus spp. and Fusobacterium spp. component was detected.These results reveal and characterize an apparently specific bacterial ecosystem in pancreatic cyst fluid samples and may reflect the local microbiota in the pancreas. Some taxa with potential deleterious functions are present in the bacterial abundance profiles, suggesting that the unique microbiome in this specific niche may contribute to neoplastic processes in the pancreas. Further studies are needed to explore the intricate relationship between pathophysiological status in the host pancreas and its microbiota.
| S-EPMC5680603 | biostudies-literature