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Selective Identification of Secreted and Transmembrane Breast Cancer Markers using Escherichia coli Ampicillin Secretion Trap

¹ Center for Developmental Biology; ² Eugene McDermott Center for Human Growth and Development; Departments of ³ Medicine, ⁴ Pathology, ⁵ Obstetrics and Gynecology, and ⁶ Biochemistry, University of Texas Southwestern Medical Center; and ⁷ Reata Discovery, Inc., Dallas, Texas

Requests for reprints: Jonathan Graff, Center for Developmental Biology, University of Texas Southwestern Medical Center at Dallas, 6000 Harry Hines Boulevard, NB5.112, Dallas, TX, 75390-9039. Phone: 214-648-1481; E-mail: Deborah.Ferguson{at}UTSouthwestern.edu.

Secreted and cell surface proteins play important roles in cancer and are potential drug targets and tumor markers. Here, we describe a large-scale analysis of the genes encoding secreted and cell surface proteins in breast cancer. To identify these genes, we developed a novel signal sequence trap method called Escherichia coli ampicillin secretion trap (CAST). For CAST, we constructed a plasmid in which the signal sequence of ß-lactamase was deleted such that it does not confer ampicillin resistance. Eukaryotic cDNA libraries cloned into pCAST produced tens of thousands of ampicillin-resistant clones, 80% of which contained cDNA fragments encoding secreted and membrane spanning proteins. We identified 2,708 unique sequences from cDNA libraries made from surgical breast cancer specimens. We analyzed the expression of 1,287 of the 2,708 genes and found that 166 were overexpressed in breast cancers relative to normal breast tissues. Eighty-five percent of these genes had not been previously identified as markers of breast cancer. Twenty-three of the 166 genes (14%) were relatively tissue restricted, suggesting use as cancer-specific targets. We also identified several new markers of ovarian cancer. Our results indicate that CAST is a robust, rapid, and low cost method to identify cell surface and secreted proteins and is applicable to a variety of relevant biological questions.