Pancreatic Cancer miRNA expression profiles
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Piepoli A
PROVIDER: S-ECPF-MTAB-753 | biostudies-other | 2012
REPOSITORIES: biostudies-other
Similar Datasets
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).
| S-ECPF-GEOD-29352 | biostudies-other
Project description:This project analyzes pancreatic tissue profiles of pancreatic cancer patients, pancreatitis patients, and controls. Since miRNAs are known to be valuable diagnostic markers, we asked whether respective patterns of pancreatic cancer patients can be detected in biopsies. The project aimed at an impoved understanding of complex profiles rather than single markers. Thus, a high-throughput technique was necessary, profiling all known miRNAs integratively. Three markers have been validated by using qPCR. n = 22 normal controls, n = 27 pancreatitis samples, and n = 136 pancreatic cancer samples have been screened for the complete miRNA repertoire. Please note that each miRNA has been measured in seven replicates and the median of the replica has been computed.
| S-ECPF-GEOD-24279 | biostudies-other
Project description: Not available
| S-ECPF-MTAB-752 | biostudies-other
Project description:Altered expression of microRNAs (miRNAs) hallmarks many cancer types. The study of the associations of miRNA expression profile and cancer phenotype could help identify the links between deregulation of miRNA expression and oncogenic pathways.Expression profiling of 866 human miRNAs in 19 colorectal and 17 pancreatic cancers and in matched adjacent normal tissues was investigated. Classical paired t-test and random forest analyses were applied to identify miRNAs associated with tissue-specific tumors. Network analysis based on a computational approach to mine associations between cancer types and miRNAs was performed.The merge between the two statistical methods used to intersect the miRNAs differentially expressed in colon and pancreatic cancers allowed the identification of cancer-specific miRNA alterations. By miRNA-network analysis, tissue-specific patterns of miRNA deregulation were traced: the driving miRNAs were miR-195, miR-1280, miR-140-3p and miR-1246 in colorectal tumors, and miR-103, miR-23a and miR-15b in pancreatic cancers.MiRNA expression profiles may identify cancer-specific signatures and potentially useful biomarkers for the diagnosis of tissue specific cancers. miRNA-network analysis help identify altered miRNA regulatory networks that could play a role in tumor pathogenesis.
| S-EPMC3316496 | biostudies-literature
Project description: Not available
2011-08-01 | E-MTAB-753 | biostudies-arrayexpress
Project description:This project analyzes peripheral blood profiles of melanoma cancer patients. Since miRNAs are known to be valuable diagnostic markers we asked whether respective patterns of melanoma patients can be detected in peripheral blood samples rather than in biopsies. The project aimed at an improved understanding of complex profiles rather than single markers. Thus, a high-throughput technique was necessary, profiling all known miRNAs integratively. Top markers have been validated by using qPCR. n = 22 normal controls and n = 35 melanoma cancer samples have been screened for the complete miRNA repertoire. The melanoma samples have been collected by two clinicians using the same procedure. Please note that each miRNA has been measured in seven replicates and the median of the replica has been computed.
| S-ECPF-GEOD-20994 | biostudies-other
Project description:Few studies have addressed the expression profiles associated with progression of pancreatic cancer to advanced disease. Towards this end, we performed expression profiling of a series of normal pancreas, pancreatitis and cancer tissues representing early stage resected pancreatic cancers (stages pT2/T3), late stage unresectable cancers (stage pT4) and matched metastases to a variety of organ sites. Microarray data was analyzed using linear modeling of microarray data (LIMMA), and differentially expressed genes were subjected to Gene Set Enrichment Analysis (GSEA). While robust differences were found in primary cancers as compared to normal pancreatic tissues, no differences were found between primary cancers and metastases, whether using matched or unmatched samples. When resected pancreatic cancers were specifically compared to advanced pancreatic cancers, significant differences in gene expression were found associated with growth at the primary site. These differentially expressed genes were most prominent in gene classes that related to MAPK and Wnt pathway, metabolism, immune regulation, cell-cell and cell-matrix interactions within the infiltrating carcinoma. One candidate upregulated gene (MXI1) was validated as having increased expression in advanced stage (T4) carcinomas by real-time PCR (p<0.05) and immunolabeling (p<0.003). We conclude that in addition to the robust changes in expression that accompany pancreatic carcinogenesis additional specific changes occur in association with growth at the primary site. By contrast, metastatic spread is not accompanied by reproducible changes in gene expression. These findings add to our understanding of pancreatic cancer and offer new topics for investigation into the aggressive nature of this deadly tumor type.
| S-EPMC2480531 | biostudies-literature
Project description:BackgroundAccurate classification of breast cancer using gene expression profiles has contributed to a better understanding of the biological mechanisms behind the disease and has paved the way for better prognostication and treatment prediction.ResultsWe found that miRNA profiles largely recapitulate intrinsic subtypes. In the case of HER2-enriched tumors a small set of miRNAs including the HER2-encoded mir-4728 identifies the group with very high specificity. We also identified differential expression of the miR-99a/let-7c/miR-125b miRNA cluster as a marker for separation of the Luminal A and B subtypes. High expression of this miRNA cluster is linked to better overall survival among patients with Luminal A tumors. Correlation between the miRNA cluster and their precursor LINC00478 is highly significant suggesting that its expression could help improve the accuracy of present day's signatures.ConclusionsWe show here that miRNA expression can be translated into mRNA profiles and that the inclusion of miRNA information facilitates the molecular diagnosis of specific subtypes, in particular the clinically relevant sub-classification of luminal tumors.
| S-EPMC6580620 | biostudies-literature
Project description:BackgroundMicroRNAs (miRNAs) are important key regulators in multiple cellular functions, due to their a crucial role in different physiological processes. MiRNAs are differentially expressed in specific tissues, during specific cell status, or in different diseases as tumours. RNA sequencing (RNA-seq) is a Next Generation Sequencing (NGS) method for the analysis of differential gene expression. Using machine learning algorithms, it is possible to improve the functional significance interpretation of miRNA in the analysis and interpretation of data from RNA-seq. Furthermore, we tried to identify some patterns of deregulated miRNA in human breast cancer (BC), in order to give a contribution in the understanding of this type of cancer at the molecular level.ResultsWe adopted a biclustering approach, using the Iterative Signature Algorithm (ISA) algorithm, in order to evaluate miRNA deregulation in the context of miRNA abundance and tissue heterogeneity. These are important elements to identify miRNAs that would be useful as prognostic and diagnostic markers. Considering a real word breast cancer dataset, the evaluation of miRNA differential expressions in tumours versus healthy tissues evidenced 12 different miRNA clusters, associated to specific groups of patients. The identified miRNAs were deregulated in breast tumours compared to healthy controls. Our approach has shown the association between specific sub-class of tumour samples having the same immuno-histo-chemical and/or histological features. Biclusters have been validated by means of two online repositories, MetaMirClust database and UCSC Genome Browser, and using another biclustering algorithm.ConclusionsThe obtained results with biclustering algorithm aimed first of all to give a contribute in the differential expression analysis in a cohort of BC patients and secondly to support the potential role that these non-coding RNA molecules could play in the clinical practice, in terms of prognosis, evolution of tumour and treatment response.
| S-EPMC4347621 | biostudies-literature
Project description:We identified total 174 significantly differentially expressed miRNAs between tumors and the normal tissues, and 109 miRNAs between serum from patients and serum from healthy individuals. There are only 10 common miRNAs. This suggests that only a small portion of tumor miRNAs are released into serum selectively. Interestingly, the expression change pattern of 28 miRNAs is opposite between breast cancer tumors and serum. Functional analysis shows that the differentially expressed miRNAs and their target genes form a complex interaction network affecting many biological processes and involving in cancer-related pathways such as prostate, basal cell carcinoma, acute myeloid leukymia, and more. A bunch of miRNAs have been demonstrated to be aberrantly expressed in cancer tumor tissue and serum. The miRNA signatures identified from the serum samples could serve as potential noninvasive diagnostic markers for breast cancer. The roles of the miRNAs in cancerigenesis is unclear. In this study, we generated the expression profiles of miRNAs from the paired breast cancer tumors, normal, tissue, and serum samples from eight patients using small RNA-sequencing. Serum samples from eight healthy individuals were used as normal controls.
| S-ECPF-GEOD-56614 | biostudies-other