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Clinical Proteomics Technologies for Cancer

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Mouse Proteomic Technologies Initiative

Program Description

Mouse models of human cancer offer many opportunities to optimize procedures for profiling major human cancers. The National Cancer Institute's Mouse Proteomic Technologies Initiative, designed to use these animal models to develop and standardize technologies to help improve the accurate measurement of proteins and peptides linked to cancer processes.  Launched in 2004 with funding to two consortia, the program was designed as a multidisciplinary and collaborative team science approach towards the development of standard tools and resources needed to accelerate protein biomarker discovery.  Major outputs from this initiative include several bioinformatic tools for proteomics research (http://proteomics.fhcrc.org/CPL/home.html).  Additionally, the consortium produced tetrabytes of publicly available data currently deposited to the research community at: https://proteomecommons.org/tranche/examples/nci-mouse-models/#east  

The goals of the Initiative were to use mouse models to: 

  • Standardize methods for protein and peptide detection and analysis.
  • Develop metrics  for benchmarking performance and supporting reagents for promising technologies.
  • Identify or characterize new biomarkers associated with cancer processes in mouse models of human cancer.
  • Enhance current technologies for the analysis of proteins and peptides in biological fluids.
  • Refine and standardize methods of specimen preparation and develop specimen reference standards.
  • Design common data elements and algorithms to facilitate data sharing amongst different laboratories.
  • Improve detection capabilities associated with current technologies, including sensitivity and resolution.

Program Structure

The Initiative funded two consortia of laboratories: the "Eastern Consortium" based at the University of Michigan (Ann Arbor, MI) and the "Western Consortium" based at the Fred Hutchinson Cancer Research Center (Seattle, WA), to develop and standardize technologies used to identify proteins and peptides in complex mixtures.

The "Eastern Consortium" based at the University of Michigan (Ann Arbor, MI) included:

  • Dana-Farber Cancer Institute (Boston, MA)
  • Fred Hutchinson Cancer Research Center (Seattle, WA)
  • Harvard-Partners Center for Genetics and Genomics (Cambridge, MA)
  • Massachusetts Institute of Technology (Cambridge, MA)
  • Memorial Sloan-Kettering Cancer Center (New York, NY)
  • Van Andel Research Institute (Grand Rapids, MI)

Samir M. Hanash, M.D., Ph.D., Program Head, Molecular Diagnostics, Fred Hutchinson Cancer Research Center was the lead investigator for the Eastern Consortium.

The "Western Consortium" based at the Fred Hutchinson Cancer Research Center (Seattle, WA) included:

  • Institute for Systems Biology (Seattle, WA)
  • Pacific Northwest National Laboratory (Richland, WA)
  • Plasma Proteome Institute (Washington, DC) 

Martin W. McIntosh, Ph.D., and Amanda Paulovich, M.D., Ph.D., Computational Proteomics Laboratory, Fred Hutchinson Cancer Research Center, were the lead investigators of the Western Consortium.

Key Research Outputs

The Mouse Model consortium produced several advances in the field of proteomics including a number of research tools available to the cancer research community.  These tools include: 

  • Computational Proteomics Analysis System (CPAS): An open-source, web-based proteomics data management software suite that combines laboratory information management systems (LIMS) and informatics modules for high-throughput liquid chromatography/tandem mass spectrometry (LC/MS/MS) experiments. CPAS enables the cancer proteomics community to store, analyze, and share clinical proteomics data.
  • msInspect: A suite of algorithms for spectral processing of high-resolution LC-MS data analysis.
  • Q3: A suite of algorithms to assist with quantitation using isotopic labeling and high-resolution mass spectrometry.
  • PETAL: A suite of software algorithms for spectral alignment of peptide arrays.
  • X!Tandem pluggable scoring and customizable score: A flexible architecture for X!Tandem to allow configurable scoring algorithm plus a customized scoring algorithm that is compatible with Peptide Prophet.
  • PepXML converter for X!Tandem: Methods for X!Tandem to write to a standardized file format.

 These software platforms and tools are available online at http://proteomics.fhcrc.org/CPL/home.html.

 Additionally, the consortium produced publicly available data deposited to the research community at: https://proteomecommons.org/tranche/examples/nci-mouse-models/#east