Open Access Research

A large, consistent plasma proteomics data set from prospectively collected breast cancer patient and healthy volunteer samples

Catherine P Riley1, Xiang Zhang2, Harikrishna Nakshatri3, Bryan Schneider4, Fred E Regnier1, Jiri Adamec1 and Charles Buck1*

Author Affiliations

1 Bindley Bioscience Center, Purdue University, West Lafayette, IN, USA

2 Department of Chemistry, University of Louisville, Louisville, KY, USA

3 Department of Surgery, Indiana University School of Medicine, Indianapolis, IN, USA

4 Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA

For all author emails, please log on.

Journal of Translational Medicine 2011, 9:80  doi:10.1186/1479-5876-9-80

Published: 27 May 2011

Abstract

Background

Variability of plasma sample collection and of proteomics technology platforms has been detrimental to generation of large proteomic profile datasets from human biospecimens.

Methods

We carried out a clinical trial-like protocol to standardize collection of plasma from 204 healthy and 216 breast cancer patient volunteers. The breast cancer patients provided follow up samples at 3 month intervals. We generated proteomics profiles from these samples with a stable and reproducible platform for differential proteomics that employs a highly consistent nanofabricated ChipCube™ chromatography system for peptide detection and quantification with fast, single dimension mass spectrometry (LC-MS). Protein identification is achieved with subsequent LC-MS/MS analysis employing the same ChipCube™ chromatography system.

Results

With this consistent platform, over 800 LC-MS plasma proteomic profiles from prospectively collected samples of 420 individuals were obtained. Using a web-based data analysis pipeline for LC-MS profiling data, analyses of all peptide peaks from these plasma LC-MS profiles reveals an average coefficient of variability of less than 15%. Protein identification of peptide peaks of interest has been achieved with subsequent LC-MS/MS analyses and by referring to a spectral library created from about 150 discrete LC-MS/MS runs. Verification of peptide quantity and identity is demonstrated with several Multiple Reaction Monitoring analyses. These plasma proteomic profiles are publicly available through ProteomeCommons.

Conclusion

From a large prospective cohort of healthy and breast cancer patient volunteers and using a nano-fabricated chromatography system, a consistent LC-MS proteomics dataset has been generated that includes more than 800 discrete human plasma profiles. This large proteomics dataset provides an important resource in support of breast cancer biomarker discovery and validation efforts.