Data from Cell surface profiling with peptide libraries yields ligand arrays that classify breast tumor subtypes

Abstract

<div>Abstract<p>Cancer heterogeneity renders risk stratification and therapy decisions challenging. Thus, genomic and proteomic methodologies have been used in an effort to identify biomarkers that can differentiate tumor subtypes to improve therapeutic outcome. Here, we report a generally applicable strategy to generate tumor type–specific peptide ligand arrays. Peptides that specifically recognize breast tumor-derived cell lines (MDA-MB-231, MCF-7, and T47-D) were identified using cell-displayed peptide libraries carrying an intrinsic fluorescent marker allowing for sorting and characterization with quantitative flow cytometry. Tumor cell specificity was achieved by depleting libraries of ligands binding to normal mammary epithelial cells (HMEC and MCF-10A). Although integrin binding RGD motifs were favored by some cell lines, screening with RGD competitors yielded several novel consensus motifs exhibiting improved tumor specificity. The resultant peptide array contained multiple consensus motifs exhibiting strong similarity to breast tumor–associated proteins. Profiling a panel of breast cancer cell lines with the peptide array revealed receptor expression patterns distinctive for luminal or basal tumor subtypes. In addition, peptide displaying bacteria and peptide functionalized microparticles enabled fluorescent labeling of tumor cells and frozen tumor tissue sections. Our results indicate that cell surface profiling using highly specific breast tumor cell binding ligands may provide an efficient route for tumor subtype classification, biomarker identification, and for the development of targeted diagnostics and therapeutics. [Mol Cancer Ther 2009;8(5):1312–8]</p></div>