Identification of novel markers that outperform EpCAM in quantifying circulating tumor cells

Cell Oncol (Dordr). 2014 Aug;37(4):235-43. doi: 10.1007/s13402-014-0178-4. Epub 2014 Jul 8.

Abstract

Background: Circulating tumor cells (CTCs) can be used to predict the spread of cancer to distant sites, to monitor the clinical response to therapy and to predict patient survival. The currently used EpCAM antibody-mediated identification of CTCs may lead to false negative results due to the low level or absence of EpCAM expression in several types of cancer, thus provoking a need to identify novel CTC markers.

Methods: The Cancer Cell Line Encyclopedia (CCLE) microarray dataset, storing 18,915 gene expression profiles across 967 cancer cell lines derived from 25 primary sites, was systematically analyzed. The results obtained were cross-validated using an independent microarray dataset generated from 1,911 clinical cancer specimens derived from 15 different cancers.

Results: Through bioinformatics analyses we identified, categorized and prioritized three classes of novel markers: pan-CTC markers (n = 45), EpCAM((-/low)) CTC markers (n = 16) and single cancer type-specific markers (n = 74). The pan-CTC markers were significantly, uniformly and constitutively over-expressed in most cancer types, except in cancers of hematopoietic and lymphoid origin. The EpCAM((-/low)) CTC markers were over-expressed in cancers with low or undetectable EpCAM expression levels. Among these, 22 markers were validated in an independent microarray dataset. In addition, 74 markers that were over-expressed in only single cancer types were categorized.

Conclusions: The combined use of these novel markers in conjunction with cancer type-specific markers should be able to quantify CTCs that are not captured by EpCAM antibodies, and to enhance the sensitivity and specificity of CTC detection among admixtures containing leucocytes or other types of contaminants.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antibodies / analysis
  • Antigens, Neoplasm / immunology
  • Antigens, Neoplasm / metabolism*
  • Biomarkers, Tumor / analysis*
  • Biomarkers, Tumor / metabolism*
  • Cell Adhesion Molecules / immunology
  • Cell Adhesion Molecules / metabolism*
  • Cell Line, Tumor
  • Computational Biology / methods
  • Databases, Genetic
  • Epithelial Cell Adhesion Molecule
  • Humans
  • Neoplastic Cells, Circulating / metabolism*

Substances

  • Antibodies
  • Antigens, Neoplasm
  • Biomarkers, Tumor
  • Cell Adhesion Molecules
  • EPCAM protein, human
  • Epithelial Cell Adhesion Molecule