Similar Datasets
Project description:We used PIP-seq single cell RNA-sequencing to study single cells from dissociated breast tissue
2023-01-12 | GSE202913 | GEO
Project description:We used 10X Chromium single cell RNA-sequencing to study single cells from dissociated breast tissue
2023-03-02 | GSE226391 | GEO
Project description:We used PIP-seq single cell RNA-sequencing to study single cells from a standard set of healthy human PBMCs
2023-01-12 | GSE215063 | GEO
Project description:The use of single cell transcriptomics provides previously inaccessible insights into cellular heterogeneity and lineage dynamics of the mammary gland allowing for a better understanding of normal mammary gland function as well as breast cancer initiation and progression. Especially for human mammary gland research, limited tissue accessibility and restriction to ex vivo techniques reinforce the importance of reliable cross-study comparison of single-cell transcriptomic data. However, it is unclear to what extent differences in breast tissue dissociation influence composition and transcriptomic profiles of isolated cells. Here, we used single-cell RNA sequencing to compare human mammary cell populations isolated from a single mammoplasty patient by varying enzymatic dissociation protocols differing in duration (3 or 16 hours) and agitation speed (10 rpm or 100 rpm). Protocol A (3 hours, 100 rpm), protocol B (16 hours, 100 rpm) and protocol C (16 hours, 10 rpm) were used to extract cell fragments from tissue which were either frozen down directly or further dissociated into single cells prior to cryopreservation. Samples were then prepared together for 10x scRNA-sequencing, where the fragments were defrosted and freshly dissociated and were loaded together with the defrosted single cells. From each of the protocols we sequenced similar numbers of cells isolated from fragments (Protocol A: 3,586 cells, Protocol B: 2,809 cells and Protocol C: 4,796 cells), finding an average of 7,427 unique molecular identifiers and 2,445 genes detected per cell. Overall, we detected a greater abundance and heterogeneity of stromal cell types, such as fibroblasts and endothelial cells at a lower agitation speed. Moreover, an extended duration of tissue dissociation governed an overall cellular oxidative stress response together with a downregulation of breast cancer associated genes and a cell-type specific downregulation of lineage markers. Thus, our systematic analysis of dissociation-induced compositional and transcriptional bias in human breast tissue samples yields useful information to avoid misinterpretation of cellular heterogeneity and lineage composition.
2023-06-30 | E-MTAB-9844 | biostudies-arrayexpress
Project description:We aimed to assess breast tissue methylation in breast cancers (triple negative breast cancer) as well as control breast tissue and breast tissue from women with increased breast cancer risk. The dataset includes methylation data from triple negative breast cancer tissue, breast tissue from risk-reducing surgeries (BRCA1/2 mutation carriers), normal breast tissue (cosmetic surgeries) as well as normal tissue adjacent to breast cancers. This dataset also comprises methylation data from controls or BRCA1/2 mutation carriers before and after mifepristone or placebo treatment.
| EGAS00001005070 | EGA
Project description:Background The PIP (prolactin-inducible protein) gene has been shown to be expressed in breast cancers, with contradictory results concerning its implication. As both the physiological role and the molecular pathways in which PIP is involved are poorly understood, we conducted a combined gene expression profiling and network analysis studies on selected breast cancer cell lines presenting distinct PIP expression levels and hormonal receptor status, to explore the functional and regulatory network of PIP co-modulated genes. Results Microarray analysis allowed identification of genes co-modulated with PIP independently of modulations resulting from hormonal treatment or cell line heterogeneity. Relevant clusters of genes that can discriminate between [PIP+] and [PIP-] cells were identified. Functional and regulatory network analyses based on knowledge database revealed a master network of PIP co-modulated genes, including many interconnecting oncogenes and tumor suppressor genes, half of which were detected as differentially expressed through high-precision measurements. The networks identified appear associated with an inhibition of proliferation coupled with an increase of apoptosis and an enhancement of cell adhesion in breast cancer cell lines. Finally, the STAT5 motif was identified in promoters of an important part of genes belonging to the PIP networks. Conclusion Our global exploratory approach was found to be an effective strategy to identify the biological pathways modulated along with the PIP expression, thus supporting good prognostic value of disease-free survival time in breast cancer based on previous reports focusing on PIP’s favorable signature. Moreover, our data allowed us to provide the first insight in its regulatory subnetwork in which STAT5 appears as a potential key regulator.
2009-03-06 | GSE11627 | GEO
Project description:This is a single-arm, multi-center data collection study designed to collect WF-OCT imaging data of excised breast tissue margins with corresponding margin status from histopathology.
| 2328012 | ecrin-mdr-crc
Project description:Stromal-epithelial interactions play a fundamental role in tissue homeostasis, controlling cell proliferation and differentiation. The goals and objectives of this study were 1.) To generate gene expression profiles and identify signatures of freshly isolated, non-cultured, luminal epithelial or basal epithelial and CD10 positive or negative stromal cell populations from the human breast. 2.) Use the generated signatures to characterize and validate the molecular identity of human primary epithelial and stromal/mesenchymal breast cells maintained long-term in novel ex vivo culture conditions in serum free medium (previous study in our lab) Breast tissue from three different reduction mammoplasties was dissociated and single cells were labeled with antibodies against lineage markers (CD31, CD45 CD235ab), CD10, EpCAM, CD49f and DAPI. Different cell populations were identified, separated and sorted with a fluorescence activated cell sorter. Gene expression profiling of luminal epithelial (EpCAM+, CD49f+/-), basal epithelial (EPCAM-, CD49f+), CD10 negative and CD10 positive stromal cells was performed and distinct gene expression signatures for the four cell populations were identified.
2015-09-26 | GSE51200 | GEO
Project description:Microbiomes of human breast tissue
| PRJNA482181 | ENA
Project description:Breast cancer can classify molecular subtype, luminal A, B, and HER2-positive and triple-negative breast cancer. Especially TNBC, there is no therapeutic target compared to other molecular subtypes. To investigate dysregulated miRNAs in TNBC, we performed miRNA microarray using breast cancer tissue with matched normal tissue in each subtype.
2023-06-15 | GSE154255 | GEO