Clinical Chemistry 56: 223-236, 2010. First published December 3, 2009; 10.1373/clinchem.2009.136333
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(Clinical Chemistry. 2010;56:223-236.)
© 2010 American Association for Clinical Chemistry, Inc.

Reviews

Sweetening the Pot: Adding Glycosylation to the Biomarker Discovery Equation

Penelope M. Drake1, Wonryeon Cho2, Bensheng Li3, Akraporn Prakobphol1, Eric Johansen1, N. Leigh Anderson4, Fred E. Regnier2, Bradford W. Gibson3 and Susan J. Fisher1,a

1 University of California San Francisco, San Francisco, CA; 2 Purdue University, West Lafayette, IN; 3 Buck Institute for Age Research, Novato, CA; 4 Plasma Proteome Institute, Washington, DC.

aAddress correspondence to this author at: 513 Parnassus Ave., Box 0556, San Francisco, CA 94143. Fax 415-502-7338; e-mail sfisher{at}cgl.ucsf.edu.

Background: Cancer has profound effects on gene expression, including a cell’s glycosylation machinery. Thus, tumors produce glycoproteins that carry oligosaccharides with structures that are markedly different from the same protein produced by a normal cell. A single protein can have many glycosylation sites that greatly amplify the signals they generate compared with their protein backbones.

Content: In this article, we survey clinical tests that target carbohydrate modifications for diagnosing and treating cancer. We present the biological relevance of glycosylation to disease progression by highlighting the role these structures play in adhesion, signaling, and metastasis and then address current methodological approaches to biomarker discovery that capitalize on selectively capturing tumor-associated glycoforms to enrich and identify disease-related candidate analytes. Finally, we discuss emerging technologies—multiple reaction monitoring and lectin-antibody arrays—as potential tools for biomarker validation studies in pursuit of clinically useful tests.

Summary: The future of carbohydrate-based biomarker studies has arrived. At all stages, from discovery through verification and deployment into clinics, glycosylation should be considered a primary readout or a way of increasing the sensitivity and specificity of protein-based analyses.