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High Dynamic Range Quantitative Proteomic Profiling of Plasma Samples from Pre-diagnostic Colon Cancer Patients and Controls

David Camp, PNNL contact
Samir Hanash, Principal Investigator, Fred Hutchinson Cancer Research Center

Funding Agency: National Institutes of Health, National Cancer Institute

The High Dynamic Range Quantitative Proteomic Profiling of Plasma Samples from Pre-diagnostic Colon Cancer Patients and Controls research team at Pacific Northwest National Laboratory (PNNL) is conducting comparative studies between pre-diagnostic colon cancer and control plasma samples.  Their goal is to identify protein biomarkers for the early detection of colon cancer.  The team is using a global quantitative proteomic strategy that combines:

A dual-quantitation strategy facilitates high-throughput analyses and accurate quantitation.
A dual-quantitation strategy facilitates high-throughput analyses and accurate quantitation. Click for a larger version.
  • front-end immunoaffinity depletion
  • stable isotope 18O labeling
  • sub-proteome fractionation based on high-efficiency cysteinyl-peptide capture
  • high-resolution nano-flow liquid chromatography-Fourier transform-ion cyclotron resonance mass spectrometry (LC-FTICR)
  • the accurate mass and time (AMT) tag strategy for peptide and/or protein identification and quantitation. 

A total of 100 pre-diagnostic cancer samples and 100 control samples are being used for this study, with each group of 100 samples combined into a total of 10 pooled samples for comparative analyses.  This pooling strategy yields enough statistical power to confidently identify candidate biomarkers while allowing higher throughput to analyze samples from a larger number of patients.  To facilitate high-throughput analyses and accurate quantitation, we are applying a dual-quantitation strategy.  Because the two strategies have different sources of variation, using them together increases the overall confidence of the data.  Sophisticated data analysis is made possible by PNNL’s unique suite of in-house informatics tools for processing large quantities of proteomic data generated from LC-FTICR measurements and for high-confidence peptide identifications and relative abundance quantitation.  All the data generated from this study is being shared with the other laboratories participating in the collaboration to allow cross-validation and follow-up of the data.

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