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Integrated Proteomic Analysis of Human Cancer Cells and Plasma from Tumor Bearing Mice for Ovarian Cancer Biomarker Discovery
Authors:Sharon J Pitteri  Lellean JeBailey  Vitor M Fa?a  Jason D Thorpe  Melissa A Silva  Reneé C Ireton  Marc B Horton  Hong Wang  Liese C Pruitt  Qing Zhang  Kuang H Cheng  Nicole Urban  Samir M Hanash  Daniela M Dinulescu
Institution:1. Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.; 2. Eugene Braunwald Research Center, Department of Pathology, Brigham and Women''s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.;University of Tuebingen, Germany
Abstract:

Background

The complexity of the human plasma proteome represents a substantial challenge for biomarker discovery. Proteomic analysis of genetically engineered mouse models of cancer and isolated cancer cells and cell lines provide alternative methods for identification of potential cancer markers that would be detectable in human blood using sensitive assays. The goal of this work is to evaluate the utility of an integrative strategy using these two approaches for biomarker discovery.

Methodology/Principal Findings

We investigated a strategy that combined quantitative plasma proteomics of an ovarian cancer mouse model with analysis of proteins secreted or shed by human ovarian cancer cells. Of 106 plasma proteins identified with increased levels in tumor bearing mice, 58 were also secreted or shed from ovarian cancer cells. The remainder consisted primarily of host-response proteins. Of 25 proteins identified in the study that were assayed, 8 mostly secreted proteins common to mouse plasma and human cancer cells were significantly upregulated in a set of plasmas from ovarian cancer patients. Five of the eight proteins were confirmed to be upregulated in a second independent set of ovarian cancer plasmas, including in early stage disease.

Conclusions/Significance

Integrated proteomic analysis of cancer mouse models and human cancer cell populations provides an effective approach to identify potential circulating protein biomarkers.
Keywords:
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