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Her2/Neu breast cancer mouse model transcriptome

ABSTRACT: Purpose: We generated extensive transcriptional and proteomic profiles from a Her2-driven mouse model of breast cancer that closely recapitulates human breast cancer. This report makes these data publicly available in raw and processed forms, as a resource to the community. Importantly, we previously made biospecimens from this same mouse model freely available through a sample repository, so researchers can obtain samples to test biological hypotheses without the need of breeding animals and collecting biospecimens. Experimental design: Twelve datasets are available, encompassing 841 LC-MS/MS experiments (plasma and tissues) and 255 microarray analyses of multiple tissues (thymus, spleen, liver, blood cells, and breast). Cases and controls were rigorously paired to avoid bias. Results: In total, 18,880 unique peptides were identified (PeptideProphet peptide error rate ≤1%), with 3884 and 1659 non-redundant protein groups identified in plasma and tissue datasets, respectively. Sixty-one of these protein groups overlapped between cancer plasma and cancer tissue. Conclusions and clinical relevance: These data are of use for advancing our understanding of cancer biology, for software and quality control tool development, investigations of analytical variation in MS/MS data, and selection of proteotypic peptides for MRM-MS. The availability of these datasets will contribute positively to clinical proteomics.

ORGANISM(S): Mus musculus

PROVIDER: GSE20280 | GEO | 2010/10/18

SECONDARY ACCESSION(S): PRJNA125363

REPOSITORIES: GEO

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Project description:Purpose: We generated extensive transcriptional and proteomic profiles from a Her2-driven mouse model of breast cancer that closely recapitulates human breast cancer. This report makes these data publicly available in raw and processed forms, as a resource to the community. Importantly, we previously made biospecimens from this same mouse model freely available through a sample repository, so researchers can obtain samples to test biological hypotheses without the need of breeding animals and collecting biospecimens. Experimental design: Twelve datasets are available, encompassing 841 LC-MS/MS experiments (plasma and tissues) and 255 microarray analyses of multiple tissues (thymus, spleen, liver, blood cells, and breast). Cases and controls were rigorously paired to avoid bias. Results: In total, 18,880 unique peptides were identified (PeptideProphet peptide error rate â¤1%), with 3884 and 1659 non-redundant protein groups identified in plasma and tissue datasets, respectively. Sixty-one of these protein groups overlapped between cancer plasma and cancer tissue. Conclusions and clinical relevance: These data are of use for advancing our understanding of cancer biology, for software and quality control tool development, investigations of analytical variation in MS/MS data, and selection of proteotypic peptides for MRM-MS. The availability of these datasets will contribute positively to clinical proteomics. Affymetrix GeneChip Mouse Genome 430 2.0 microarrays were used to profile whole tissues from 5 different tissue types of 25 tumor-bearing and 25 control mice of the Her2/Neu breast cancer mouse model. The 5 tissues tested were from breast, liver, spleen, blood cell, and thymus. The tumor-bearing mice were bitransgenic for MMTV-rtTA/TetO-NeuNT, and the control mice were transgenic for TetO-NeuNT only. The control mice were age- and cage-matched to the tumor-bearing mice. All samples were lysed and total RNA isolated and amplified prior to hybridization.

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Her2/Neu breast cancer mouse model transcriptome

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