Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA122111 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Molecular Characterization of Breast Cancer Subtypes Derived from Joint Analysis of High Throughput miRNA and mRNA Data
| PRJNA122257 | ENA
Project description:We used a genome-wide approach (High-throughput sequencing of RNA isolated by crosslinking immunoprecipitation, or HITS-CLIP) to define direct miRNA-mRNA interactions in three breast cancer subtypes (estrogen receptor positive, Her2 amplified and triple negative). Focusing on steroid receptor signaling, we identified two novel regulators of the ER pathway (miR-9-5p and miR-193a/b-3p), which together target multiple genes involved in ER signaling. Moreover, this approach enabled the definition of miR-9-5p as a global regulator of steroid receptor signaling in breast cancer. Finally, we show that miRNA targets and networks defined by our analysis are predictive of patient outcomes and provide global insight into miRNA regulation in breast cancer. Argonaute HITS-CLIP on three representative breast cancer cell lines (each in triplicate).
2014-08-04 | E-GEOD-57855 | biostudies-arrayexpress
Project description:We used a genome-wide approach (High-throughput sequencing of RNA isolated by crosslinking immunoprecipitation, or HITS-CLIP) to define direct miRNA-mRNA interactions in three breast cancer subtypes (estrogen receptor positive, Her2 amplified and triple negative). Focusing on steroid receptor signaling, we identified two novel regulators of the ER pathway (miR-9-5p and miR-193a/b-3p), which together target multiple genes involved in ER signaling. Moreover, this approach enabled the definition of miR-9-5p as a global regulator of steroid receptor signaling in breast cancer. Finally, we show that miRNA targets and networks defined by our analysis are predictive of patient outcomes and provide global insight into miRNA regulation in breast cancer.
2014-08-04 | GSE57855 | GEO
Project description:We descrive a joint model of transcriptional activation and mRNA accumulation, using estrogen receptor ERα activation in MCF-7 breast cancer cell line, which can be used for inference of transcription rate, RNA processing delay and degradation rate given data from high-throughput sequencing time course experiments.
2015-03-04 | GSE62789 | GEO
Project description:We descrive a joint model of transcriptional activation and mRNA accumulation, using estrogen receptor ERM-NM-1 activation in MCF-7 breast cancer cell line, which can be used for inference of transcription rate, RNA processing delay and degradation rate given data from high-throughput sequencing time course experiments. MCF-7 cells were mock treated or with 10nM 17b-E2 to nine time points (5', 10', 20', 40', 80', 160', 320', 640' and 1280'). Genome-wide identification of RNA polymerase II (RNAPII) occupancy and transcriptome profiling (RNA-seq) following E2 induction of MCF-7 cells Please note that the information in the wig.txt files is in gene-specific coordinates, not chromosomic coordinates, as this is the most sensible format for the associated project/paper.
2015-03-04 | E-GEOD-62789 | biostudies-arrayexpress
Project description:Accurate characterization and understanding of the breast cancer subtypes is of crucial clinical importance to the heterogeneity of this disease. Several layers of information, including immunohistochemical markers, mRNA and microRNA expression profiles, and pathway analysis have been used for such purpose in several studies. However, a comprehensively integrative approach is currently missing. This paper provides microRNA and mRNA expression profiles, characterizing four breast tumor subtypes, as defined by four immunohistochemical markers. The defined sets of features were validated in two independent data sets at multiple levels, including unsupervised clustering and supervised classification. Moreover, the gene expression signatures of the tumor subtypes were screened by in-depth analysis of 12 cancer core pathways. We successfully identified and validated a novel breast cancer subtypes gene expression signature composed of 976 mRNAs and 69 miRNAs. Luminal and non-luminal tumors are shown to significantly differ both at the mRNA and miRNA levels. HER2 positive tumors are more closely related to triple negative tumors by mRNA profiling than by miRNA expression. Closely related miRNAs sharing the same targets may exert opposite roles during tumor progression. Besides the core cancer pathways, other pathways such as those controling biomass synthesis are shown to be important to enable the core basal subtype with additional progressive nature compared with the other triple negative tumors. Some therapeutic strategies are proposed for breast cancer treatment, including the combined blockage of MAPK/ERK and PI3K/Pten signalings for tumors with poor clinical outcome, and targeting Wnt and JAK/STAT and/or Hedgehog, depending on tumor subtypes, together with conventional chemotherapy with the purpose of achieving an eradicative outcome. The pathway analysis also reveals that the clinical strategy and pivotal targets need to be tuned according to different tumor subtypes. This study is the first attempt to elucidate breast cancer subtypes by combining microRNA and mRNA expression, immunohistochemical markers, and cancer core pathways. The results can avail the functional studies of the etiology of breast cancer and translated for clinical use given their intrinsic link in terms of immunohistochemistry and survival. This submission consists of microRNA profiles of 115 breast cancer tumors of several subtypes only.
2013-06-01 | E-GEOD-43040 | biostudies-arrayexpress
Project description:To investigate differentially expressed miRNAs in synovium of human temporomandibular joint osteoarthritis (TMJOA), we performed miRNA high-throughput sequencing in synovium of human TMJOA.
2022-06-10 | GSE205684 | GEO
Project description:Systems-wide profiling of breast cancer has so far built on RNA and DNA analysis by microarray and sequencing techniques. Dramatic developments in proteomic technologies now enable very deep profiling of clinical samples, with high identification and quantification accuracy. We analyzed 40 estrogen receptor positive (luminal), Her2 positive and triple negative breast tumors and reached a quantitative depth of more than 10,000 proteins. Comparison to mRNA classifiers revealed multiple discrepancies between proteins and mRNA markers of breast cancer subtypes. These proteomic profiles identified functional differences between breast cancer subtypes, related to energy metabolism, cell growth, mRNA translation and cell-cell communication. Furthermore, we derived a 19-protein predictive signature, which discriminates between the breast cancer subtypes, through Support Vector Machine (SVM)-based classification and feature selection. The deep proteome profiles also revealed novel features of breast cancer subtypes, which may be the basis for future development of subtype specific therapeutics.
2017-03-29 | MSV000080757 | MassIVE
Project description:Analysis of 143 formalin-fixed, paraffin-embedded (FFPE) primary breast tumors using a Custom Breast Cancer Panel and Human Cancer Panel for the DASL platform. Molecular markers between the pathology defined subtypes of breast cancer were assessed to hypothesize potential therapeutic targets specific to the subtypes Molecular Characterization of 143 primary breast carcinomas including 101 triple negative (TN: ER-, PR-, HER2-), 3 HER2-positive (HER2+: ER-, PR-, HER2+), and 39 hormone receptor-positive (HR+: ER+ and/or PR+)
2009-10-23 | E-GEOD-18539 | biostudies-arrayexpress
Project description:MicroRNAs (miRNAs), a class of short non-coding RNAs, often act post-transcriptionally to inhibit gene expression. We used a bead-based flow cytometric profiling method to obtain miRNA expression data for 93 primary human breast tumours, 21 cell lines and five normal breast samples. Of 309 human miRNAs assayed we identify 133 miRNAs expressed in human breast and breast tumours. We used mRNA expression profiling to classify the breast tumours into Luminal A, Luminal B, Basal-like, HER2+/ER- and Normal-like. A number of miRNAs are differentially expressed between these molecular tumour subtypes and individual miRNAs are associated with clinicopathological factors. Furthermore, we find that miRNAs could classify basal versus luminal tumour subtypes in an independent data set. Keywords = miRNA Keywords = microRNA Keywords = normal Keywords = tumour Keywords = cell line Keywords = breast Keywords = cancer Keywords: Bead-based flow cytometric profiling miRNA expression data for 93 primary human breast tumours, 21 cell lines and five normal breast samples
2007-10-09 | E-GEOD-7842 | biostudies-arrayexpress