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1.  Multiplexed quantification of estrogen receptor and HER2/Neu in tissue and cell lysates by peptide immunoaffinity enrichment mass spectrometry 
Proteomics  2012;12(8):1253-1260.
Access to a wider range of quantitative protein assays would significantly impact the number and use of tissue markers in guiding disease treatment. Quantitative mass spectrometry-based peptide and protein assays, such as immuno-SRM assays, have seen tremendous growth in recent years in application to protein quantification in biological fluids such as plasma or urine. Here, we extend the capability of the technique by demonstrating the application of a multiplexed immuno-SRM assay for quantification of estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2) levels in cell line lysates and human surgical specimens. The performance of the assay was characterized using peptide response curves, with linear ranges covering approximately 4 orders of magnitude and limits of detection in the low fmol/mg lysate range. Reproducibility was acceptable with median coefficients of variation of approximately 10%. We applied the assay to measurements of ER and HER2 in well-characterized cell line lysates with good discernment based on ER/HER2 status. Finally, the proteins were measured in surgically resected breast cancers, and the results showed good correlation with ER/HER2 status determined by clinical assays. This is the first implementation of the peptide-based immuno-SRM assay technology in cell lysates and human surgical specimens.
doi:10.1002/pmic.201100587
PMCID: PMC3418804  PMID: 22577026
Estrogen receptor; HER2/Neu; immunoaffinity; peptides; tissue
2.  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
3.  A targeted proteomics–based pipeline for verification of biomarkers in plasma 
Nature biotechnology  2011;29(7):625-634.
High-throughput technologies can now identify hundreds of candidate protein biomarkers for any disease with relative ease. However, because there are no assays for the majority of proteins and de novo immunoassay development is prohibitively expensive, few candidate biomarkers are tested in clinical studies. We tested whether the analytical performance of a biomarker identification pipeline based on targeted mass spectrometry would be sufficient for data-dependent prioritization of candidate biomarkers, de novo development of assays and multiplexed biomarker verification. We used a data-dependent triage process to prioritize a subset of putative plasma biomarkers from >1,000 candidates previously identified using a mouse model of breast cancer. Eighty-eight novel quantitative assays based on selected reaction monitoring mass spectrometry were developed, multiplexed and evaluated in 80 plasma samples. Thirty-six proteins were verified as being elevated in the plasma of tumor-bearing animals. The analytical performance of this pipeline suggests that it should support the use of an analogous approach with human samples.
doi:10.1038/nbt.1900
PMCID: PMC3232032  PMID: 21685906
4.  Automated screening of monoclonal antibodies for SISCAPA assays using a magnetic bead processor and liquid chromatography-selected reaction monitoring-mass spectrometry 
Journal of immunological methods  2009;353(1-2):49-61.
Stable Isotope Standards and Capture by Anti-Peptide Antibodies (SISCAPA) utilizes antibodies to enrich peptides from complex matrices for quantitation by stable isotope dilution mass spectrometry. SISCAPA improves sensitivity and limits the sample handling required for plasma-based analysis. Thus far, SISCAPA assays have been performed using polyclonal antibodies, yet monoclonal antibodies are an attractive alternative since they provide exquisite specificity, a renewable resource, and the potential for isolation of clones with very high affinities (10-9 M or better). The selection of a good monoclonal antibody out of hundreds-to-thousands of clones presents a challenge, since the screening assay should ideally be in the format of the final SISCAPA assay, but performing the assays manually is labor- and time-intensive. In this manuscript, we demonstrate that monoclonal antibodies can be used in SISCAPA assays, and we describe an automated high-throughput SISCAPA method that makes screening of large numbers of hybridomas feasible while conserving time and resources.
doi:10.1016/j.jim.2009.11.017
PMCID: PMC2839902  PMID: 19961853
SISCAPA; anti-peptide antibody; monoclonal antibody screening; selected reaction monitoring-mass spectrometry; automation; ELISA
5.  CE-microreactor-CE-MS/MS for protein analysis 
Analytical chemistry  2007;79(6):2230-2238.
We present a proof-of-principle for a fully automated bottom-up approach to protein characterization. Proteins are first separated by capillary electrophoresis. A pepsin microreactor is incorporated into the distal end of this capillary. Peptides formed in the reactor are transferred to a second capillary, where they are separated by capillary electrophoresis and characterized by mass spectrometry. While peptides generated from one digestion are being separated in the second capillary, the next protein fraction undergoes digestion in the microreactor. The migration time in the first dimension capillary is characteristic of the protein while migration time in the second dimension is characteristic of the peptide. Spot capacity for the two-dimensional separation is 590. A MS/MS analysis of a mixture of cytochrome C and myoglobin generated Mascot MOWSE scores of 107 for cytochrome C and 58 for myoglobin. The sequence coverages were 48% and 22%, respectively.
doi:10.1021/ac061638h
PMCID: PMC2553279  PMID: 17295444

Results 1-5 (5)