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Tailoring chimeric ligands for studying and biasing ErbB receptor family interactions.

ABSTRACT: Described is the development and application of a versatile semisynthetic strategy, based on a combination of sortase-mediated coupling and tetrazine ligation chemistry, which can be exploited for the efficient incorporation of tunable functionality into chimeric recombinant proteins. To demonstrate the scope of the method, the assembly of a set of bivalent ligands, which integrate members of the epidermal growth factor (EGF) ligand family, is described. By using a series of bivalent EGFs with variable intraligand spacing, the differences in structure were correlated with the ability to bias signaling in the ErbB receptor family in a cell motility assay. Biasing away from EGFR-HER2 dimerization with a bivalent EGF was observed to reduce cell motility in an intraligand distance-dependent fashion, thus demonstrating the utility of the approach for acutely perturbing receptor-mediated cell signaling pathways.

SUBMITTER: Krueger AT

PROVIDER: S-EPMC4018821 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

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Tailoring chimeric ligands for studying and biasing ErbB receptor family interactions.

Krueger Andrew T AT Kroll Carsten C Sanchez Edgar E Griffith Linda G LG Imperiali Barbara B

Angewandte Chemie (International ed. in English) 20140131 10

Described is the development and application of a versatile semisynthetic strategy, based on a combination of sortase-mediated coupling and tetrazine ligation chemistry, which can be exploited for the efficient incorporation of tunable functionality into chimeric recombinant proteins. To demonstrate the scope of the method, the assembly of a set of bivalent ligands, which integrate members of the epidermal growth factor (EGF) ligand family, is described. By using a series of bivalent EGFs with v ...[more]

PMID: 24481645

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Project description:Pathway discovery from gene expression data can provide important insight into the relationship between signaling networks and cancer biology. Oncogenic signaling pathways are commonly inferred by comparison with signatures derived from cell lines. We use the Molecular Apocrine subtype of breast cancer to demonstrate our ability to infer pathways directly from patients' gene expression data with pattern analysis algorithms.We combine data from two studies that propose the existence of the Molecular Apocrine phenotype. We use quantile normalization and XPN to minimize institutional bias in the data. We use hierarchical clustering, principal components analysis, and comparison of gene signatures derived from Significance Analysis of Microarrays to establish the existence of the Molecular Apocrine subtype and the equivalence of its molecular phenotype across both institutions. Statistical significance was computed using the Fasano & Franceschini test for separation of principal components and the hypergeometric probability formula for significance of overlap in gene signatures. We perform pathway analysis using LeFEminer and Backward Chaining Rule Induction to identify a signaling network that differentiates the subset. We identify a larger cohort of samples in the public domain, and use Gene Shaving and Robust Bayesian Network Analysis to detect pathways that interact with the defining signal.We demonstrate that the two separately introduced ER- breast cancer subsets represent the same tumor type, called Molecular Apocrine breast cancer. LeFEminer and Backward Chaining Rule Induction support a role for AR signaling as a pathway that differentiates this subset from others. Gene Shaving and Robust Bayesian Network Analysis detect interactions between the AR pathway, EGFR trafficking signals, and ErbB2.We propose criteria for meta-analysis that are able to demonstrate statistical significance in establishing molecular equivalence of subsets across institutions. Data mining strategies used here provide an alternative method to comparison with cell lines for discovering seminal pathways and interactions between signaling networks. Analysis of Molecular Apocrine breast cancer implies that therapies targeting AR might be hampered if interactions with ErbB family members are not addressed.

Dataset Information

Tailoring chimeric ligands for studying and biasing ErbB receptor family interactions.

Publications

Tailoring chimeric ligands for studying and biasing ErbB receptor family interactions.

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