Colon Cancer miRNA expression profiles
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Carella Massimo
PROVIDER: S-ECPF-MTAB-752 | biostudies-other |
REPOSITORIES: biostudies-other
Similar Datasets
Project description: Not available
| S-ECPF-MTAB-753 | biostudies-other
Project description: Not available
2011-08-01 | E-MTAB-752 | biostudies-arrayexpress
Project description:Changes in miRNA expression are a common feature in colon cancer. Those changes occurring in the transition from normal to adenoma and from adenoma to carcinoma, however, have not been well defined. Additionally, miRNA changes among tumor subgroups of colon cancer have also not been adequately evaluated. In this study, we examined the global miRNA expression in 315 samples that included 52 normal colonic mucosa, 41 tubulovillous adenomas, 158 adenocarcinomas with proficient DNA mismatch repair (pMMR) selected for stage and age of onset, and 64 adenocarcinomas with defective DNA mismatch repair (dMMR) selected for sporadic (n?=?53) and inherited colon cancer (n?=?11). Sporadic dMMR tumors all had MLH1 inactivation due to promoter hypermethylation. Unsupervised PCA and cluster analysis demonstrated that normal colon tissue, adenomas, pMMR carcinomas and dMMR carcinomas were all clearly discernable. The majority of miRNAs that were differentially expressed between normal and polyp were also differentially expressed with a similar magnitude in the comparison of normal to both the pMMR and dMMR tumor groups, suggesting a stepwise progression for transformation from normal colon to carcinoma. Among the miRNAs demonstrating the largest fold up- or down-regulated changes (?4), four novel (miR-31, miR-1, miR-9 and miR-99a) and two previously reported (miR-137 and miR-135b) miRNAs were identified in the normal/adenoma comparison. All but one of these (miR-99a) demonstrated similar expression differences in the two normal/carcinoma comparisons, suggesting that these early tumor changes are important in both the pMMR- and dMMR-derived cancers. The comparison between pMMR and dMMR tumors identified four miRNAs (miR-31, miR-552, miR-592 and miR-224) with statistically significant expression differences (?2-fold change).
| S-EPMC3111419 | 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).
| S-ECPF-GEOD-29352 | biostudies-other
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: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
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:A bunch of microRNAs (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 role 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. 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 many types of cancer such as prostate cancer, basal cell carcinoma, acute myeloid leukemia, and more.
| S-EPMC4033838 | biostudies-literature