Ontology highlight
ABSTRACT:
PROVIDER: PRJNA924300 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Whole genome bisulphite sequencing of 2 human breast cancer cell lines representing a breast primary tumor and a matched lymph node metastasis. Sequencing of bisulfite converted DNA of cancer cell line samples.
2014-09-03 | E-GEOD-56763 | biostudies-arrayexpress
Project description:We studied genes, that are differentially expressed between malignant and normal breast tissue, to find weak spots for anti-cancer therapy development. RNA sequencing of three cell lines was performed: MCF-7 (epithelial breast cancer cell line), BCC (primary breast tumour cell line) and MCF-10A (epithelial breast cell line).
2023-01-30 | GSE223718 | GEO
Project description:We cultured the ER negative breast cancer cell line MDA-MB-231 and the ER positive breast cancer cell line MCF7 in serine-free media for 24h. RNA was extracted from the cells and submitted for RNA sequencing.
2023-08-01 | GSE222313 | GEO
Project description:breast cancer metastatic cell line
| PRJEB97884 | ENA
Project description:Breast cancer brain metastasis has been recognized as one of the central issues in breast cancer research. Elucidation of the process and pathway that mediate this step is expected to provide important clues for a better understanding of breast cancer metastasis. Increasing evidence suggests that the aberrant glycosylation patterns greatly contribute to the cell invasion and cancer metastasis. Herein, we combined next generation RNA sequencing with liquid chromatograph-tandem mass spectrometry based proteomic and N-glycomic analysis from five breast cancer cell lines and one brain cancer cell line to investigate the possible mechanism of breast cancer brain metastasis. 24763 genes were identified including 14551 differentially expressed genes across six cell lines while proteomic analysis allowed the quantitation of 1096 differentially expressed proteins with approximately 83.8% proteins’ regulation matching their gene expression change. The genes/proteins associated with cell movement were highlighted in the breast cancer brain metastasis. Integrin signaling pathway and the up-regulation of α-integrin (ITGA2, ITGA3) associated with the brain metastatic process was shown through Ingenuity Pathway Analysis (IPA). Overall 91 glycosylation genes were selected from transcriptomic data and all exhibited differential expression. 12 glycogenes showed unique expression in 231BR. The regulation of these genes could result in an activation prediction of sialylation function in 231BR by ingenuity pathway analysis. In agreement with the changes of glycogenes, 60 N-glycans out of 63 identified exhibited differential expression among cell lines. The correlation of glycogenes and glycans revealed the importance of sialylation and sialylated glycans in breast cancer brain metastasis. Highly sialylated glycans, which were up-regulated in brain seeking cell line 231BR, probably contributes to brain metastasis.
2020-05-26 | PXD010506 | Pride
Project description:RNA sequencing data from the T-47D breast cancer cell line
| PRJNA1093242 | 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