Homo sapiens
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ABSTRACT:
PROVIDER: PRJNA122257 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Molecular Characterization of Breast Cancer Subtypes from Joint Analysis of High Throughput miRNA and mRNA Data (II)
| PRJNA122111 | ENA
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:We performed quantitative proteomics of 60 human-derived breast cancer cell lines to a depth of ~13,000 proteins. The resulting high-throughput datasets were assessed for quality and reproducibility. We used the two omics datasets to identify and characterize the subtypes of breast cancer and showed that they conform with known transcriptional subtypes, revealing that molecular subtypes are preserved even in under-sampled molecular feature datasets. The datasets are made freely available as a public resource on the LINCS portal. We anticipate that these datasets, either in isolation or combination with measurements of complementary molecular features, can be mined for the purpose of predicting drug response, informing context in mathematical models of signaling pathways, inferring cell-type or subtype specific pathways activities of unperturbed cellular states, and identifying markers of sensitivity or resistance to therapeutics.
2023-03-15 | PXD026581 | Pride
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.
2016-01-05 | PXD002619 | Pride
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 performed quantitative proteomics and phosphoproteomics of 43 human-derived breast cancer cell lines to a depth of 11, 000 proteins and 45,000 phosphopeptides respectively. The resulting high-throughput datasets were assessed for quality and reproducibility. We used the two omics datasets to identify and characterize the subtypes of breast cancer and showed that they conform with known transcriptional subtypes, revealing that molecular subtypes are preserved even in under-sampled molecular feature datasets. The datasets are made freely available as a public resource on the LINCS portal. We anticipate that these datasets, either in isolation or combination with measurements of complementary molecular features, can be mined for the purpose of predicting drug response, informing context in mathematical models of signalling pathways, inferring cell-type or subtype specific pathways activities of unperturbed cellular states, and identifying markers of sensitivity or resistance to therapeutics.
2023-07-03 | PXD017494 | Pride
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 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: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: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