Proteome and transcriptome profiles of a Her2/Neu‐driven mouse model of breast cancer

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.

[1]  Daniel B. Martin,et al.  Circulating microRNAs as stable blood-based markers for cancer detection , 2008, Proceedings of the National Academy of Sciences.

[2]  Lukas N. Mueller,et al.  Halogenated Peptides as Internal Standards (H-PINS) , 2009, Molecular & Cellular Proteomics.

[3]  Adam Rauch,et al.  Computational Proteomics Analysis System (CPAS): an extensible, open-source analytic system for evaluating and publishing proteomic data and high throughput biological experiments. , 2006, Journal of proteome research.

[4]  G. Omenn,et al.  Proteomic characterization of novel alternative splice variant proteins in human epidermal growth factor receptor 2/neu-induced breast cancers. , 2010, Cancer research.

[5]  Alexey I Nesvizhskii,et al.  Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. , 2002, Analytical chemistry.

[6]  M. Mann,et al.  Exponentially Modified Protein Abundance Index (emPAI) for Estimation of Absolute Protein Amount in Proteomics by the Number of Sequenced Peptides per Protein*S , 2005, Molecular & Cellular Proteomics.

[7]  J. Yates,et al.  A model for random sampling and estimation of relative protein abundance in shotgun proteomics. , 2004, Analytical chemistry.

[8]  M. Girolami,et al.  Clinical proteomics: A need to define the field and to begin to set adequate standards , 2007, Proteomics. Clinical applications.

[9]  J. Rosen,et al.  Modelling breast cancer: one size does not fit all , 2007, Nature Reviews Cancer.

[10]  Vladislav A Petyuk,et al.  Region-specific protein abundance changes in the brain of MPTP-induced Parkinson's disease mouse model. , 2010, Journal of proteome research.

[11]  Phil Andrews,et al.  Recommendations from the 2008 International Summit on Proteomics Data Release and Sharing Policy: the Amsterdam principles. , 2009, Journal of proteome research.

[12]  Birgit Schilling,et al.  Repeatability and reproducibility in proteomic identifications by liquid chromatography-tandem mass spectrometry. , 2010, Journal of proteome research.

[13]  Mitchell D Schnall,et al.  Conditional activation of Neu in the mammary epithelium of transgenic mice results in reversible pulmonary metastasis. , 2002, Cancer cell.

[14]  David L. Tabb,et al.  Performance Metrics for Liquid Chromatography-Tandem Mass Spectrometry Systems in Proteomics Analyses* , 2009, Molecular & Cellular Proteomics.

[15]  Hua Xu,et al.  Automated diagnosis of LC-MS/MS performance , 2009, Bioinform..

[16]  Brendan MacLean,et al.  General framework for developing and evaluating database scoring algorithms using the TANDEM search engine , 2006, Bioinform..

[17]  J. Jonkers,et al.  Mouse models for BRCA1 associated tumorigenesis: From fundamental insights to preclinical utility , 2008, Cell cycle.

[18]  Richard D. Smith,et al.  Characterization of the mouse pancreatic islet proteome and comparative analysis with other mouse tissues. , 2008, Journal of proteome research.

[19]  Gordon A Anderson,et al.  High-throughput comparative proteome analysis using a quantitative cysteinyl-peptide enrichment technology. , 2004, Analytical chemistry.

[20]  Xu Shi,et al.  Quantification of Cardiovascular Biomarkers in Patient Plasma by Targeted Mass Spectrometry and Stable Isotope Dilution* , 2009, Molecular & Cellular Proteomics.

[21]  Birgit Schilling,et al.  Interlaboratory Study Characterizing a Yeast Performance Standard for Benchmarking LC-MS Platform Performance* , 2009, Molecular & Cellular Proteomics.

[22]  R. Beavis,et al.  A method for reducing the time required to match protein sequences with tandem mass spectra. , 2003, Rapid communications in mass spectrometry : RCM.

[23]  Robertson Craig,et al.  TANDEM: matching proteins with tandem mass spectra. , 2004, Bioinformatics.

[24]  Leroy Hood,et al.  A molecular correlate to the Gleason grading system for prostate adenocarcinoma. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[25]  C. Kemp,et al.  A mouse model repository for cancer biomarker discovery. , 2008, Journal of proteome research.

[26]  Werner Zolg,et al.  Quantification of C‐reactive protein in the serum of patients with rheumatoid arthritis using multiple reaction monitoring mass spectrometry and 13C‐labeled peptide standards , 2004, Proteomics.

[27]  Ronald J Moore,et al.  Fully automated four-column capillary LC-MS system for maximizing throughput in proteomic analyses. , 2008, Analytical chemistry.

[28]  Barbara Frewen,et al.  High quality catalog of proteotypic peptides from human heart. , 2008, Journal of proteome research.

[29]  R. Aebersold,et al.  A statistical model for identifying proteins by tandem mass spectrometry. , 2003, Analytical chemistry.

[30]  David A. Tuveson,et al.  Maximizing mouse cancer models , 2007, Nature Reviews Cancer.

[31]  Ronald J. Moore,et al.  Improved proteome coverage by using high efficiency cysteinyl peptide enrichment: The human mammary epithelial cell proteome , 2005, Proteomics.

[32]  Xu Yang,et al.  MRM screening/biomarker discovery with linear ion trap MS: a library of human cancer-specific peptides , 2009, BMC Cancer.

[33]  Heidi Zhang,et al.  Integrated pipeline for mass spectrometry-based discovery and confirmation of biomarkers demonstrated in a mouse model of breast cancer. , 2007, Journal of proteome research.

[34]  Pei Wang,et al.  Bioinformatics Original Paper a Suite of Algorithms for the Comprehensive Analysis of Complex Protein Mixtures Using High-resolution Lc-ms , 2022 .

[35]  G. Forni,et al.  ErbB2 transgenic mice: a tool for investigation of the immune prevention and treatment of mammary carcinomas. , 2008, Current protocols in immunology.