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

Area of Science:

• Biochemistry
• Molecular Biology
• Oncology

Background:

• Cancer heterogeneity complicates risk stratification and treatment decisions.
• Genomic and proteomic methods aim to identify biomarkers for improved therapeutic outcomes.
• Developing specific biomarkers for tumor subtypes is crucial for personalized medicine.

Purpose of the Study:

• To develop a generalizable strategy for creating tumor type-specific peptide ligand arrays.
• To identify peptides that specifically recognize and bind to breast tumor cell lines.
• To enable efficient tumor subtype classification and biomarker identification.

Main Methods:

• Utilized cell-displayed peptide libraries with fluorescent markers for sorting and quantitative flow cytometry.
• Achieved tumor cell specificity by depleting libraries of ligands that bind to normal mammary epithelial cells.
• Identified novel consensus motifs by screening with RGD competitors to enhance tumor specificity.

Main Results:

• Generated a peptide array with multiple consensus motifs showing similarity to breast tumor-associated proteins.
• Profiling breast cancer cell lines revealed receptor expression patterns distinguishing luminal and basal tumor subtypes.
• Demonstrated fluorescent labeling of tumor cells and tissue sections using peptide-functionalized bacteria and microparticles.

Conclusions:

• Cell surface profiling with specific breast tumor-binding ligands offers an efficient method for tumor subtype classification.
• This approach facilitates biomarker identification for targeted diagnostics and therapeutics.
• The developed peptide ligand arrays hold potential for advancing precision oncology.