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Updated: Feb 13, 2026

An Orthotopic Model of Serous Ovarian Cancer in Immunocompetent Mice for in vivo Tumor Imaging and Monitoring of Tumor Immune Responses
Published on: November 28, 2010
Characterization of the Ovarian Tumor Peptidome
Tao Liu1, Karin D Rodland1, Richard D Smith1
1Pacific Northwest National Laboratory, Richland, WA, United States.
Abstract:
Aberrant degradation of proteins is associated with many pathological states, including cancers. Mass spectrometric analysis of the tumor peptidome has the potential to provide biological insights on proteolytic processing in cancer. However, attempts to use the tumors peptidome information in cancer research have been fairly limited to date, largely due to the lack of effective approaches for robust peptidomics identification and quantification, and the prevalence of confounding factors and biases associated with sample handling and processing. To address this need, we have recently developed an effective and robust analytical platform as well as a novel informatics approach for comprehensive analyses of tissue peptidomes. The ability of this new peptidomics pipeline for high-throughput, comprehensive, and quantitative peptidomics analysis, as well as the suitability of clinical ovarian tumor samples with postexcision delay limited to less than 60min before freezing for peptidomics analysis, has been demonstrated. These initial analyses set a stage for further determination of molecular details and functional significance of the peptidomic activities in ovarian cancer.
Insights
Researchers developed a new platform for analyzing tumor peptidomes, improving cancer research. This method enhances the identification and quantification of proteins, offering new insights into ovarian cancer.
Area of Science:
- Biochemistry
- Oncology
- Proteomics
Background:
- Aberrant protein degradation is linked to various diseases, including cancer.
- Tumor peptidome analysis offers insights into cancer's proteolytic processing.
- Previous peptidomics research in cancer is limited by identification/quantification challenges and sample biases.
Purpose of the Study:
- To develop a robust analytical platform and informatics approach for comprehensive tissue peptidome analysis.
- To enable high-throughput, comprehensive, and quantitative peptidomics analysis.
- To assess the suitability of clinical ovarian tumor samples for peptidomics.
Main Methods:
- Development of a novel analytical platform for peptidomics.
- Implementation of a new informatics approach for data analysis.
- Analysis of clinical ovarian tumor samples with strict pre-processing controls.
Main Results:
- Demonstrated a high-throughput, comprehensive, and quantitative peptidomics pipeline.
- Confirmed the suitability of ovarian tumor samples processed within 60 minutes of excision.
- Established a foundation for detailed molecular and functional analyses of ovarian cancer peptidomics.
Conclusions:
- The developed peptidomics pipeline overcomes previous limitations in cancer research.
- This approach enables robust analysis of clinical tissue samples.
- Further studies can now explore the molecular details and functional significance of peptidomic activities in ovarian cancer.
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