Circulating Tumor Cells and Nucleic Acids for Tumor Diagnosis

  • Loren JosephEmail author
Part of the Molecular Pathology Library book series (MPLB, volume 7)


After decades of glacial progress, important clinical roles for circulating tumor cells (CTC) and circulating tumor nucleic acids (CNA) are coming into focus at an accelerating pace. Advances in immunohistochemistry, image cytometry, and molecular biology have converged to the point where circulating tumor cells can be analyzed by methods ranging from morphology through 10-color immunohistochemistry and FISH to whole genome/transcriptome analysis of single cells. Cell-free circulating tumor nucleic acids (genomic DNA, mRNA, miRNA) can also be quantified and comprehensively analyzed for changes like mutation and methylation. Circulating tumor cells and tumor nucleic acids can be found in most patients with gastrointestinal malignancy. One test for circulating tumor cells is already FDA approved for use in determining therapy in metastatic colon cancer. Exciting studies have shown the successful application of CTC and CNA analysis to monitor minimal residual disease by targeting tumor-specific mutations and gene rearrangements. This approach should expand dramatically as whole genome and whole transcriptome analysis of tumors becomes standard practice. MicroRNA profiling of plasma appears to be a promising way to screen for many epithelial malignancies. Measurement of circulating methylated DNA sequences has shown impressive specificity and sensitivity for detection of colon cancer. The role of circulating tumor cells in the cancer ecosystem (the primary, the stroma, the metastases, the disseminated tumor cells and immune cells) could remain elusive even as a clinical role is defined but the ability to fully characterize CTC and uncover detailed genomic relationships could also open a window onto tumor dormancy and metastasis.


Gastric Cancer Esophageal Cancer Circulate Tumor Cell Minimal Residual Disease Disseminate Tumor Cell 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Department of PathologyThe University of ChicagoChicagoUSA

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