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1.  Proteome and Transcriptome Profiles of a Her2/Neu-driven Mouse Model of Breast Cancer 
Proteomics. Clinical applications  2011;5(3-4):179-188.
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.
doi:10.1002/prca.201000037
PMCID: PMC3069718  PMID: 21448875
Breast cancer; Her2; mouse; proteome; transcriptome
2.  The interface between biomarker discovery and clinical validation: The tar pit of the protein biomarker pipeline 
Proteomics. Clinical applications  2008;2(10-11):1386-1402.
The application of “omics” technologies to biological samples generates hundreds to thousands of biomarker candidates; however, a discouragingly small number make it through the pipeline to clinical use. This is in large part due to the incredible mismatch between the large numbers of biomarker candidates and the paucity of reliable assays and methods for validation studies. We desperately need a pipeline that relieves this bottleneck between biomarker discovery and validation. This paper reviews the requirements for technologies to adequately credential biomarker candidates for costly clinical validation and proposes methods and systems to verify biomarker candidates. Models involving pooling of clinical samples, where appropriate, are discussed. We conclude that current proteomic technologies are on the cusp of significantly affecting translation of molecular diagnostics into the clinic.
doi:10.1002/prca.200780174
PMCID: PMC2957839  PMID: 20976028
Biomarker verification; Multiple reaction monitoring; Targeted proteomics

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