Human Breast Cell Index
Ontology highlight
ABSTRACT:
INSTRUMENT(S): LTQ Orbitrap
ORGANISM(S): Homo Sapiens (ncbitaxon:9606)
SUBMITTER: Dr Peter James
PROVIDER: MSV000079833 | MassIVE | Fri Jun 17 11:27:00 BST 2016
SECONDARY ACCESSION(S): PXD000691
REPOSITORIES: MassIVE
Publications
Molecular Portrait of Breast-Cancer-Derived Cell Lines Reveals Poor Similarity with Tumors.
Cifani Paolo P Kirik Ufuk U Waldemarson Sofia S James Peter P
Journal of proteome research 20150622 7
Breast-cancer-derived cell lines are an important sample source for cancer proteomics and can be classified on the basis of transcriptomic analysis into subgroups corresponding to the molecular subtypes observed in mammary tumors. This study describes a tridimensional fractionation method that allows high sequence coverage and proteome-wide estimation of protein expression levels. This workflow has been used to conduct an in-depth quantitative proteomic survey of five breast cancer cell lines ma ...[more]
Similar Datasets
Project description:The project consists of an In-depth analysis of seven breast (cancer)-derived cell lines, which represent different tumour types plus fibroblasts and adipocytes.
2015-05-06 | PXD000691 | Pride
Project description:Frozen tissue specimens from primary breast tumors were collected and profiled using Affymetrix U133 plus 2 expression microarrays. A publication describing the generation of these data is not yet available. However, these data can be used alongside other Affymetrix breast tumour data sets to form large meta-cohorts for breast cancer research, as was done in Lasham et. al. J Natl Cancer Inst. 2012 Jan 18;104(2):133-146.
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Project description:The efficacy of cancer treatments have improved constantly in the last decade. However, therapeutic resistance and the lack of curative treatments in metastatic disease, raises the question if conventional anticancer therapies target the right cells. Indeed, these treatments might miss cancer stem cells (CSCs), which might also represent a more chemoresistant and radioresistant subpopulation within cancer. In this view using vaccines in tertiary prevention of cancer, i.e. residual disease treatment, might be particularly effective if vaccine-elicited immune response is directed against CSC oncoantigens (OAs) — proteins required for the neoplastic process — the chance that the tumour will evade the vaccine should be reduced. An important task to devise effective CSC preventive vaccines is therefore the identification of CSC OAs. We used gene-level transcription profiling of TuBo epithelial cell and three mammosphere passages (P1, P2 and P3). This analysis allowed the identification of two new breast cancer CSC OAs: TMPRSS4 and xCT. Both genes are linked to invasion, migration and metastasis. These results were achieved integrating data derived by the analysis of transcription profile of CSCs derived by BALB-neuT mouse breast cancer model with meta-analyses of seven large independent breast tumour data sets.
2013-11-30 | GSE21451 | GEO
Project description:The breast tumour microenvironment (TME) includes fibroblasts, adipocytes, inflammatory and immune cells. While treatment of tumours with chemotherapeutic agents such as Docetaxel, leads to apoptosis of tumour cells, it can also have consequences for the cellular makeup and transcriptional profile of the TME and these, like increased epithelial mesenchymal transition can promote undesirable consequences, such as Cancer Stem Cell development. PKC-theta may have a role in these undesired effects. To be able to examine the effects of co-treatment of Docetaxel with an inhibitor of PKC-theta, we performed RNA-seq on tumours from mice injected with the human breast cancer cell line MDA-MB-231. We then separated reads mapped to the human and mouse genomes in silico, creating tumour and TME transcriptomes for control, Docetaxel, PKC-theta inhibitor and combination treated mice. Separation of the tumour and TME profiles illustrated a role for PKC-theta in the induction of a more basal-type transcriptome in the tumour, and of EMT in the TME.
2022-09-14 | GSE137467 | GEO
Project description:Frozen tissue specimens from primary breast tumors were collected and profiled using Affymetrix U133 plus 2 expression microarrays. A publication describing the generation of these data is not yet available. However, these data can be used alongside other Affymetrix breast tumour data sets to form large meta-cohorts for breast cancer research, as was done in Lasham et. al. J Natl Cancer Inst. 2012 Jan 18;104(2):133-146. Frozen tumor tissues comprising of >60% tumor cellularity were extracted for total RNA and hybridized on Affymetrix microarrays.
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Project description:Breast cancer is a heterogeneous disease for which prognosis and treatment strategies are largely governed by the receptor status (estrogen, progesterone and Her2-neu) of the tumor cells. Gene expression profiling of whole breast tumors further stratifies breast cancer into several molecular subtypes which also co-segregate with the receptor status of the tumor cells. We postulated that cancer associated fibroblasts (CAFs) within the tumor stroma may exhibit subtype specific gene expression profiles and thus contribute to the biology of the disease in a subtype specific manner. Several studies have reported gene expression profile differences between CAFs and normal breast fibroblasts but in none of these studies were the results stratified based on tumor subtypes. To address whether gene expression in breast cancer associated fibroblasts varies between breast cancer subtypes, we compared the gene expression profiles of early passage primary CAFs isolated from twenty human breast cancer samples representing three main subtypes; seven ER+, seven triple negative (TNBC) and six Her2+. We observed significant expression differences between CAFs derived from Her2+ breast cancer and CAFs from TNBC and ER+ cancers, particularly in pathways associated with cytoskeleton and integrin signaling. In the case of Her2+ breast cancer, the signaling pathways found to be selectively up regulated in CAFs may contribute to the more invasive properties and unfavorable prognosis of Her2+ breast cancer. These data demonstrate that in addition to the distinct molecular profiles that characterize the neoplastic cells, CAF gene expression is also differentially regulated in distinct subtypes of breast cancer.
2013-12-20 | GSE37614 | GEO
Project description:The progression of noninvasive ductal carcinoma in situ to invasive ductal carcinoma for patients with breast cancer results in a significantly poorer prognosis and is the precursor to metastatic disease. In this work, we have identified insulin-like growth factor–binding protein 2 (IGFBP2) as a potent adipocrine factor secreted by healthy breast adipocytes that acts as a barrier against invasive progression. In line with this role, adipocytes differentiated from patient-derived stromal cells were found to secrete IGFBP2, which significantly inhibited breast cancer invasion. This occurred through binding and sequestration of cancer-derived IGF-II. Moreover, depletion of IGF-II in invading cancer cells using small interfering RNAs or an IGF-II–neutralizing antibody ablated breast cancer invasion, highlighting the importance of IGF-II autocrine signaling for breast cancer invasive progression. Given the abundance of adipocytes in the healthy breast, this work exposes the important role they play in suppressing cancer progression and may help expound upon the link between increased mammary density and poorer prognosis.
2023-07-13 | PXD036479 | Pride
Project description:Purpose: There is a quest for novel non-invasive diagnostic markers for the detection of breast cancer. The goal of this study is to identify circulating microRNA signatures using a cohort of Asian Chinese breast cancer patients, and to compare microRNA profiles between tumour and serum samples. Experimental design: MicroRNAs from paired breast cancer tumours, normal tissue and serum samples derived from 32 patients were comprehensively profiled using microarrays (1300 microRNAs against tumour and normal tissues) or LNA RT-PCR panels (742 microRNAs against serum samples). Serum samples from healthy individuals (n=22) were also employed as normal controls. Significant serum microRNAs, identified by logistic regression, were validated in an independent set of serum samples from patients (n=82) and healthy controls (n=53). Results: The 20 most significant microRNAs differentially expressed in breast cancer tumours included miR-21, miR-10b, and miR-145, previously shown to be dysregulated in breast cancer. Interestingly, 16 of the 20 most significant microRNAs differentially expressed in serum samples were novel. MiR-1, miR-92a, miR-133a and miR-133b were identified as the most important diagnostic markers, and were successfully validated; receiver operating characteristic curves derived from combinations of these microRNAs exhibited areas under the curves of 0.944-0.946. Only seven microRNAs were overexpressed in both tumours and serum, suggesting that microRNAs may be released into the serum selectively. Conclusion: The clinical employment of microRNA signatures as a non-invasive diagnostic strategy is promising, but should be further validated for different subtypes of breast cancers. "_A" and "_B" are two tissue sections of the same sample; "_1" and "_2" represents 2 runs of the same sample; na = not available All tissue samples were histologically confirmed by a pathologist using hematoxylin and eosin staining of cryosectioned specimens. One tumour sample was rejected due to failure to detect any tumour cells. Except for two samples (with 30% and 40% tumour cells), all tumour tissues employed had a minimum of 60% tumour cells, as estimated microscopically. Overall, the breast cancer tumour samples had an average of 71% tumour cells. The criteria for adjacent normal tissue were absence of tumour cells and presence of epithelial cells. Hence, after histological confirmation, 31 breast cancer tumours and 23 matched normal tissues were employed for microRNA extraction and profiling using microarray.
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Project description:Elevated production of collagen-rich extracellular matrix (ECM) is a hallmark of cancer associated fibroblasts (CAFs) and a central driver of cancer aggressiveness. How to target ECM production to oppose cancer is yet unclear, since targeting CAFs has been shown to restrain but also promote cancer progression. Metabolic rewiring is a second hallmark of CAFs. Here we find that proline, which is a highly abundant amino acid in collagen proteins, is newly synthesised from glutamine to make tumour collagen in breast cancer xenografts, and that its production is increased in breast cancer patient-derived CAFs compared to their matched normal fibroblasts in vitro. PYCR1 is the rate-limiting enzyme for proline synthesis and is highly expressed in the tumour stroma of breast cancer patients and in CAFs. Reducing PYCR1 levels in CAFs is sufficient to reduce collagen production, tumour growth and metastatic spread in vivo and cancer cell proliferation in vitro. Collagen and proline synthesis are enhanced by increased acetyl-CoA levels, which occurs through the epigenetic regulator EP300, and targeting PYCR1 overwrites this epigenetic reprogramming and decreases collagen production. Altogether, we present a previously uncharacterised pathway that supports pro-tumorigenic collagen production in CAFs. We show that PYCR1 and COL1A1 are overexpressed in patients with poor prognosis in several cancer types. PYCR1 is a recognised cancer cell vulnerability and potential target for therapy, hence, our work provides evidence that targeting PYCR1 in tumours may have the additional benefit of halting the production of pro-tumorigenic ECM. Finally, PYCR1 is highly expressed in collagen-producing fibroblasts derived from lungs of idiopathic pulmonary fibrosis patients, suggesting that PYCR1 may also offer therapeutic opportunities in fibrotic diseases.
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