Project description:In the present study through TLDA analysis we looked into the miRNA differential expression in peripheral blood of PCOS patients v/s control women. The results implicated that many signalling networks as MAPK pathway, Androgen signaling, Insulin signaling and Immune signaling are regulated in peripheral blood of PCOS patients. The data indicate that there is generic PCOS specific gene expression in peripheral blood of PCOS subjects which can reflect the same from other PCO tissues. Total RNA was extracted from peripheral blood of 4 PCOS patients and 4 control subjects and compared for miRNA diferential expression through TLDA
Project description:In the present study through microarray analysis we looked into the mRNA differential expression in peripheral blood of PCOS patients v/s control women. The results implicated that many signalling networks as MAPK pathway, Androgen signaling, Insulin signaling and Immune signaling are regulated in peripheral blood of PCOS patients. The data indicate that there is generic PCOS specific gene expression in peripheral blood of PCOS subjects which can reflect the same from other PCO tissues. Total RNA was extracted from peripheral blood of 4 PCOS patients and 4 control subjects and compared for mRNA diferential expression through microarray.
Project description:BACKGROUND: MicroRNA (miRNA) signatures are not only found in cancer tissue but also in blood of cancer patients. Specifically, miRNA detection in blood offers the prospect of a non-invasive analysis tool. METHODS: Using a microarray based approach we screened almost 900 human miRNAs to detect miRNAs that are deregulated in their expression in blood cells of melanoma patients. We analyzed 55 blood samples, including 20 samples of healthy individuals, 24 samples of melanoma patients as test set, and 11 samples of melanoma patients as independent validation set. RESULTS: A hypothesis test based approach detected 51 differentially regulated miRNAs, including 21 miRNAs that were downregulated in blood cells of melanoma patients and 30 miRNAs that were upregulated in blood cells of melanoma patients as compared to blood cells of healthy controls. The tets set and the independent validation set of the melanoma samples showed a high correlation of fold changes (0.81). Applying hierarchical clustering and principal component analysis we found that blood samples of melanoma patients and healthy individuals can be well differentiated from each other based on miRNA expression analysis. Using a subset of 16 significant deregulated miRNAs, we were able to reach a classification accuracy of 97.4%, a specificity of 95% and a sensitivity of 98.9% by supervised analysis. MiRNA microarray data were validated by qRT-PCR. CONCLUSIONS: Our study provides strong evidence for miRNA expression signatures of blood cells as useful biomarkers for melanoma.
Project description:This project aims at the detection of specific patterns of miRNAs in peripheral blood samples of lung cancer patients. As controls, blood of donors without known affection have been tested. Using the miRNA patterns we hope to detect a diagnostic pattern for the non-invasive diagnosis of non-small cell lung carcinoma. In this study, we compared 17 lung cancer samples to 19 control samples using the sanger miRBAse 12.0 miRNA biochip manufactured by febit. Samples were analyzed with the Geniom Realtime Analyzer (GRTA, febit gmbh, Heidelberg, Germany) using the Geniom Biochip miRNA Homo sapiens. Each array contains 7 replicates of 866 miRNAs and miRNA star sequences as annotated in the Sanger miRBase 12.0. To benchmark the platform, we tested technical replicates using bought total RNA of brain and liver samples (ambion), achieving a correlation of 0.97.
Project description:Ovarian cancer is one of the most common cancer types in women characterized by a high mortality rate due to lack of early diagnosis. Circulating miRNAs besides being important regulators of cancer development could be potential biomarkers to aid diagnosis. We performed the circulating miRNA expression analysis in plasma samples obtained from ovarian cancer patients stratified into FIGO I, FIGO III, and FIGO IV stages and from healthy females using the NanoString quantitative assay. Forty-five miRNAs were differentially expressed, out of these 17 miRNAs showed significantly different expression between controls and patients, 28 were expressed only in patients, among them 19 were expressed only in FIGO I patients. Differentially expressed miRNAs were ranked by the network-based analysis to assess their importance. Target genes of the differentially expressed miRNAs were identified then functional annotation of the target genes by the GO and KEGG-based enrichment analysis was carried out. A general and an ovary-specific protein-protein interaction network was constructed from target genes. Results of our network and the functional enrichment analysis suggest that besides HSP90AA1, MYC, SP1, BRCA1, RB1, CFTR, STAT3, E2F1, ERBB2, EZH2, and MET genes, additional genes which are enriched in cell cycle regulation, FOXO, TP53, PI-3AKT, AMPK, TGFβ, ERBB signaling pathways and in the regulation of gene expression, proliferation, cellular response to hypoxia, and negative regulation of the apoptotic process, the GO terms have central importance in ovarian cancer development. The aberrantly expressed miRNAs might be considered as potential biomarkers for the diagnosis of ovarian cancer after validation of these results in a larger cohort of ovarian cancer patients.
