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JNCI Journal of the National Cancer Institute 2007 99(11):826-827; doi:10.1093/jnci/djk221
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© The Author 2007. Published by Oxford University Press.

EDITORIALS

Serum Proteomic Classifier for Predicting Response to Epidermal Growth Factor Receptor Inhibitor Therapy: Have We Built a Better Mousetrap?

Ming-Sound Tsao, Geoffrey Liu, Frances A. Shepherd

Affiliations of authors: Department of Pathology (MST), Division of Applied Molecular Oncology (MST, GL), and Division of Medical Oncology and Hematology (FAS), University Health Network, Princess Margaret Hospital and Ontario Cancer Institute, Toronto, ON, Canada; Department of Laboratory Medicine and Pathobiology (MST), Department of Medicine (GL, FAS), University of Toronto, Toronto, ON, Canada

Correspondence to: Ming-Sound Tsao, MD, FRCPC, 610 University Ave, Rm 7-613, Toronto, ON, Canada M5G 2M9 (e-mail: Ming.Tsao@uhn.on.ca).

The first 10% of the full text of this article appears below.

The ability to predict treatment response and clinical (survival) outcomes is one of the two "holy grails" of cancer biomarker development, the other being early detection or risk stratification by population screening (1). In advanced non–small-cell lung cancer (NSCLC), small-molecule tyrosine kinase inhibitors (TKIs) of the epidermal growth factor receptor (EGFR) represent a breakthrough for targeted therapy, yet only a small proportion of patients (especially among non–East Asians) appear to benefit from these expensive agents (2,3). Previous studies have shown that EGFR immunohistochemistry, tyrosine kinase domain mutations, and/or EGFR gene copy number by fluorescent in situ hybridization (FISH) are biomarkers that are potentially useful to select patients more likely to . . . [Full Text of this Article]


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The "Lazarus Response" in Treatment-Naive, Poor Performance Status Patients With Non-Small-Cell Lung Cancer and Epidermal Growth Factor Receptor Mutation
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