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Updated: Jul 26, 2026

Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing
Published on: September 25, 2011
Antibody-Protein L Functionalized Microparticles for Detection of Surface Markers in Heterogeneous Colorectal Lesions
Saleh Ramezani1,2,3, Niki M Zacharias4, William Norton5
1Department of Diagnostic and Biomedical Sciences, School of Dentistry, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Abstract:
Visualization of colorectal cancer (CRC) lesions is complicated by their location in the colon and tumor morphology. Reliance on a single surface biomarker for direct identification risks false negatives due to temporal changes and/or tumor heterogeneity. We developed a multiplexed system of complementary biomarker targets in an effort to capture a broader range of lesions with diverse temporal and/or phenotypic expression. We identified Mucin-1 (MUC1) and epithelial cell adhesion molecule (EPCAM) as useful targeting pairs by examining multiple colon tumor subtypes in a standard tissue array, and by surveying multiple CRC cell lines, both as 2D cultures and as 3D tumoroids, for the presence of the CRC surface biomarkers. We demonstrated the utility of a "universal" surface functionalization approach using Antibody-Protein L functionalized microparticles (APL-MPs) that enabled the simultaneous incorporation of antibodies recognizing MUC1 and EPCAM. Using CRC cell heterogeneous tumoroids expressing both MUC1 and EPCAM (HET-tumoroids) and orthotopic animal cancer models designed to express both surface antigens, we demonstrated that: 1) APL-MPs identified MUC1- and EPCAM-positive tumoroids in proportion to antigen expression; 2) APL-MPs detected CRC surface antigens on the luminal colon surface in vivo, and 3) concurrent targeting of multiple surface antigens enhanced the sensitivity of detection of heterogeneous CRC lesions. This approach opens the door for the use of antibody-protein L dual-targeting MPs in a variety of applications to detect heterogeneous cancer lesions.
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