Identification of tumor‐associated plasma biomarkers using proteomic techniques: From mouse to human
- 24 August 2004
- journal article
- research article
- Published by Wiley in Proteomics
- Vol. 4 (9) , 2766-2775
- https://doi.org/10.1002/pmic.200400785
Abstract
In an effort to identify tumor‐associated proteins from plasma of tumor‐bearing mice that may be used as diagnostic biomarkers, we developed a strategy that combines a tumor xenotransplantation model in nude mice with comparative proteomic technology. Five human cancer cell lines (SC‐M1, HONE‐1, CC‐M1, OECM1, GBM 8401) derived from stomach, nasopharyngeal, colon, oral and brain cancers were subcutaneously inoculated into nude mice and compared to control nude mice injected with phosphate‐buffered saline. One month later, plasma from mice inoculated with cancer cells was collected for proteomic analysis using two‐dimensional gel electrophoresis (2‐DE) and mass spectrometry (MS). Comparison of plasma 2‐DE maps from tumor‐bearing mice with those produced from control mice revealed the overexpression of several mouse acute phase proteins (APPs) such as haptoglobin. Another APP, serum amyloid A (SAA), was found only in mice bearing tumors induced by the stomach cancer cell line SC‐M1, which has not previously been demonstrated in xenotransplatation experiment. Furthermore, by using immunohistochemistry, SAA and haptoglobin were found to originate from the mouse hosts and not from the human cancer cell line donors. The protein alterations were further confirmed on patients with stomach cancers where up‐regulated levels of SAA were also observed. These results indicate that APPs may be used as nonspecific tumor‐associated serum markers. SAA in particular may serve as a potential marker for detecting stomach cancer. Taken together, the combination of the xenotransplatation model in nude mice and proteomics analysis provided a valuable impact for clinical applications in cancer diagnostics. In addition, our findings demonstrate that a panel of APPs might serve as screening biomarkers for early cancer detection.Keywords
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