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Measuring tissue-based biomarkers by immunochromatography coupled with reverse-phase lysate microarray.

Martin J Romeo1, John Wunderlich, Lien Ngo

  • 1Laboratory of Pathology, Surgery Branch, and Biostatistics and Data Management Section, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA.

Clinical Cancer Research : an Official Journal of the American Association for Cancer Research
|April 28, 2006
PubMed
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A new method, immunochromatography coupled with reverse-phase lysate microarrays (I-RPM), offers reproducible tissue biomarker quantification. I-RPM shows strong correlations with other methods for gp100 and MART-1, validating its potential.

Area of Science:

  • Biomarker Discovery
  • Translational Research
  • Cancer Diagnostics

Background:

  • Immunohistochemistry (IHC) is limited by variability and bias.
  • Alternative technologies like RT-PCR, ICC, and RPM require validation.
  • RPM faces challenges with microdissection and low protein yield.

Purpose of the Study:

  • To validate and correlate novel biomarker technologies on patient tissues.
  • To assess the utility of immunochromatography coupled with RPM (I-RPM) for biomarker analysis.
  • To overcome limitations of current tissue biomarker assessment methods.

Main Methods:

  • Surgically excised metastatic melanoma from 30 patients.
  • Specimens processed for IHC, ICC, RT-PCR, and I-RPM.
  • I-RPM utilized immunochromatography for melanoma cell enrichment.

Related Experiment Videos

  • Expression of gp100 and MART-1 was measured and normalized to actin.
  • Main Results:

    • I-RPM demonstrated reproducibility (r ≥ 0.70).
    • I-RPM correlated strongly with IHC and ICC for gp100 (r=0.78, 0.76).
    • I-RPM showed moderate correlation with RT-PCR for gp100 (r=0.61).
    • I-RPM correlated strongly with RT-PCR for MART-1 (r=0.78).
    • Transcript levels showed moderate correlations with IHC/ICC (r=0.41-0.64).

    Conclusions:

    • I-RPM is a promising technology for quantitative biomarker grading.
    • The method overcomes limitations of traditional techniques.
    • Antigen-dependent correlations highlight the need for careful validation.