Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

MicroRNA expression profiles of distinct human mammary epithelial cell types

ABSTRACT: RNA samples were prepared from freshly sorted mammary cell subpopulations (MaSC/basal-enriched, luminal progenitor, mature luminal and stromal) from five human donors. High throughput RT-PCR was used to measure the global microRNA expression profiles of each cell subpopulation. The expression profiles were compared between cell subpopulations to gain insight into the regulation of lineage-restricted genes. High throughput RT-PCR profiling of microRNA expression in four mammary cell populations from five human donors.

ORGANISM(S): Homo sapiens

SUBMITTER: Gordon Smyth

PROVIDER: E-GEOD-67054 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Integration of microRNA signatures of distinct mammary epithelial cell types with their gene expression and epigenetic portraits.

Pal Bhupinder B Chen Yunshun Y Bert Andrew A Hu Yifang Y Sheridan Julie M JM Beck Tamara T Shi Wei W Satterley Keith K Jamieson Paul P Goodall Gregory J GJ Lindeman Geoffrey J GJ Smyth Gordon K GK Visvader Jane E JE

Breast cancer research : BCR 20150618

<h4>Introduction</h4>MicroRNAs (miRNAs) have been implicated in governing lineage specification and differentiation in multiple organs; however, little is known about their specific roles in mammopoiesis. We have determined the global miRNA expression profiles of functionally distinct epithelial subpopulations in mouse and human mammary tissue, and compared these to their cognate transcriptomes and epigenomes. Finally, the human miRNA signatures were used to interrogate the different subtypes of ...[more]

PMID: 26080807

Similar Datasets

Project description:Purpose: To identify tissue microRNAs predictive of sunitinib activity in patients with metastatic renal-cell carcinoma (MRCC) and to validate them in a cellular model. Selected microRNAs were studied in serum from MRCC patients and healthy individuals. Methods: We screened 673 microRNAs using TaqMan Low-density Arrays (TLDAs) in tumors from MRCC patients with extreme phenotypes of marked efficacy and resistance to sunitinib, selected from an identification cohort (n=41). Differentially expressed microRNAs were selected using bioinformatics-based target prediction analysis and quantified by qRT-PCR in tumors from patients presenting similar phenoytpes selected from an independent cohort (n=117). Results were validated in a cellular model of sunitinib resistance and studied in serum from healthy individuals and MRCC patients. Results: TLDAs identified 64 microRNAs differentially expressed in the identification cohort. Seven candidates were quantified by qRT-PCR in the independent series. MiR-942 was the most accurate predictor of sunitinib efficacy (p=0.0074). High expression of miR-942, miR-133a, miR484, and miR-628-5p was significantly associated with decreased time-to-progression and overall survival. These microRNAs were overexpressed in the sunitinib resistant cell line Caki-2 in comparison with the sensitive parental cell line. Serum levels of miR-942, miR-133a, miR-484, miR-146a-5p, miR-374a and miR-486-5p were significantly reduced in MRCC patients compared to healthy controls. Conclusions: Our strategy identified differentially expressed microRNAs in MRCC patients presenting marked sensitivity and resistance to sunitinib. Mir-942 was the best predictor of efficacy. Results were confirmed in a cellular model of sunitinib resistance. We also identified exosome derived serum microRNAs differentially expressed in MRCC patients and healthy individuals. Taqman Low Density Array for 6 FFPE tissues obtained from extreme phenotype MRCC patients, (n=3 marked resistance to sunitinib treatment patients and n=3 marked sensitivity to sunitinib treatment patients), was performanced to screen 667 microRNAs.

Project description:In vitro generation of mature neutrophils from human induced pluripotent stem cells (iPSCs) requires hematopoietic progenitor development followed by myeloid differentiation. The purpose of our studies was to extensively characterize this process, focusing on the critical window of development between hemogenic endothelium, hematopoietic stem/progenitor cells (HSPCs), and myeloid commitment, to identify associated regulators and markers that might enable the stem cell field to improve the efficiency and efficacy of iPSC hematopoiesis. We utilized a 4-stage differentiation protocol involving: embryoid body (EB) formation (Stage-1); EB culture with hematopoietic cytokines (Stage-2); HSPC expansion (Stage-3); and neutrophil maturation (Stage-4). CD34+CD45- putative hemogenic endothelial cells were observed in Stage-3 cultures, and expressed VEGFR-2/Flk-1/KDR and VE-cadherin endothelial markers, GATA-2, AML1/RUNX1, and SCL/TAL1 transcription factors, and endothelial/HSPC-associated microRNAs miR-24, miR-125a-3p, miR-126/126*, and miR-155. Upon further culture, CD34+CD45- cells generated CD34+CD45+ HSPCs that produced hematopoietic CFUs. Mid-Stage-3 CD34+CD45+ HSPCs exhibited increased expression of GATA-2, AML1/RUNX1, SCL/TAL1, C/EBPÎ±, and PU.1 transcription factors, but exhibited decreased expression of HSPC-associated microRNAs, and failed to engraft in immune-deficient mice. Mid-stage-3 CD34-CD45+ cells maintained PU.1 expression and exhibited increased expression of hematopoiesis-associated miR-142-3p/5p and a trend towards increased miR-223 expression, indicating myeloid commitment. By late Stage-4, increased CD15, CD16b, and C/EBPÎµ expression were observed, with 25-65% of cells exhibiting morphology and functions of mature neutrophils. These studies demonstrate that hematopoiesis and neutrophil differentiation from human iPSCs recapitulates many features of embryonic hematopoiesis and neutrophil production in marrow, but reveals unexpected molecular signatures that may serve as a guide for enhancing iPSC hematopoiesis. miRNA expression profiles were analyzed in iNC-01-3 and iNC-01-4 induced pluripotent stem cell lines at day 0 (undifferentiated iPSCs), day 18 of differentiation (embryoid bodies), and in 3 FACS-sorted cell populations at day 22 of differentiation (CD34+CD45- cells, CD34+CD45+ cells, and CD34-CD45+ cells). Comparative CT analysis was normalized to U6 snRNA and RNU48 control RNAs relative to expression in undifferentiated iPSCs. Data includes 2 files for each sample, one for the card A array and one for the card B array. This includes a total of 32 data files consisting of: 5 replicates for undifferentiated iPSCs (10 files), 2 replicates for EB (4 files), 3 replicates for CD34+CD45- (6 files), 3 replicates for CD34+CD45+ (6 files), and 3 replicates for CD34-CD45+ (6 files).

Project description:Most (70%) epithelial ovarian cancers (EOCs) are diagnosed late. Non-invasive biomarkers that facilitate disease detection and predict outcome are needed. The microRNAs (miRNAs) represent a new class of biomarkers. This study was to identify and validate plasma miRNAs as biomarkers in EOC. We evaluated plasma samples of 360 EOC patients and 200 healthy controls from two institutions. All samples were grouped into screening, training and validation sets. We scanned the circulating plasma miRNAs by TaqMan low-density array in the screening set and identified/validated miRNA markers by real-time polymerase chain reaction assay in the training set. Receiver operating characteristic and logistic regression analyses established the diagnostic miRNA panel, which were confirmed in the validationsets. We found higher plasma miR-205 and lower let-7f expression in cases than in controls. MiR-205 and let-7f together provided high diagnostic accuracy for EOC, especially in patients with stage I disease. The combination of these two miRNAs and carbohydrate antigen-125 (CA-125) further improved the accuracy of detection. MiR-483-5p expression was elevated in stages III and IV compared with in stages I and II, which was consistent with its expression pattern in tumor tissues. Furthermore, lower levels of let-7f were predictive of poor prognosis in EOC patients. Our findings indicate that plasma miR-205 and let-7f are biomarkers for ovarian cancer detection that complement CA-125; let-7f may be predictive of ovarian cancer prognosis. We designed a multi-stage, retrospective, nested case-control study to determine whether serum miRNA profiles can be used to predict EOC development. All samples were grouped into screening, training, and validation sets. A total of 560 plasma samples (360 cases and 200 controls) were obtained from Tianjin Medical University Cancer Institute and Hospital (TCIH) and Cancer Center of Nanjing Medical University. The cases and controls were well matched for age. The International Federation of Gynaecology and Obstetrics (FIGO) staging system was used to stage cases. All patients and controls were genetically unrelated, ethnic Han Chinese women who were permanent residents of the urban area of Tianjin and Nanjing. Controls with cardiovascular, respiratory, digestive, urinary, reproductive, and endocrine diseases were excluded. The study protocols were approved by the Tianjin and Nanjing Center review committees. In screening set, to detect generalizable miRNA signatures, we pooled serum samples of 10 early-stage cases (stage I), 10 late-stage cases (stage IIIc-IV), and 10 healthy controls, respectively, and analyzed these three pool samples using a TaqMan low-density array (TLDA set 2.0, Applied Biosystems) chip screening in the discovery stage. In training set, the miRNAs identified in the screening set were validated using quantitative reverse transcription-polymerase chain reaction (qRT-PCR) on individual plasma samples of 76 EOC patients and 30 normal controls. In validation set, the validation set comprised a two-phase process. Promising associations from the screening and training set were evaluated in the validation phase I set, comprising 134 cases and 70 controls from Tianjin Center. The validation phase II set included samples of 77 EOC cases and 50 normal controls were from Tianjin Center and 73 EOC cases and 50 normal controls were from Nanjing Center.

Dataset Information

MicroRNA expression profiles of distinct human mammary epithelial cell types

Publications

Integration of microRNA signatures of distinct mammary epithelial cell types with their gene expression and epigenetic portraits.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets