Gene expression profiling using Nanostring digital RNA counting to identify potential target antigens for melanoma immunotherapy

  • Beard R
  • Abate-Daga D
  • Rosati S
 et al. 
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PURPOSE: The success of immunotherapy for the treatment of metastatic cancer is contingent on the identification of appropriate target antigens. Potential targets must be expressed on tumors but show restricted expression on normal tissues. To maximize patient eligibility, ideal target antigens should be expressed on a high percentage of tumors within a histology and, potentially, in multiple different malignancies. Design: A Nanostring probeset was designed containing 97 genes, 72 of which are considered potential candidate genes for immunotherapy. Five established melanoma cell lines, 59 resected metastatic melanoma tumors, and 31 normal tissue samples were profiled and analyzed using Nanostring technology.

RESULTS: Of the 72 potential target genes, 33 were overexpressed in more than 20% of studied melanoma tumor samples. Twenty of those genes were identified as differentially expressed between normal tissues and tumor samples by ANOVA analysis. Analysis of normal tissue gene expression identified seven genes with limited normal tissue expression that warrant further consideration as potential immunotherapy target antigens: CSAG2, MAGEA3, MAGEC2, IL13RA2, PRAME, CSPG4, and SOX10. These genes were highly overexpressed on a large percentage of the studied tumor samples, with expression in a limited number of normal tissue samples at much lower levels.

CONCLUSION: The application of Nanostring RNA counting technology was used to directly quantitate the gene expression levels of multiple potential tumor antigens. Analysis of cell lines, 59 tumors, and normal tissues identified seven potential immunotherapy targets for the treatment of melanoma that could increase the number of patients potentially eligible for adoptive immunotherapy.

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  • Rachel E. Beard

  • Daniel Abate-Daga

  • Shannon F. Rosati

  • Zhili Zheng

  • John R. Wunderlich

  • Steven A. Rosenberg

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