Designing Optimal Probe Sequence for Breast Cancer Subtype Classification via Multiple MicroRNAs Recognition

Breast cancer is a heterogeneously manifested disease, categorized into several distinct molecular and pathological subtypes. Accurate subtype classification holds significant importance as it informs therapeutic strategies, thereby potentially improving patient prognosis. Current methodologies that employ biomarkers for breast cancer subtype classification encounter limitations: while the integration of a broader biomarker spectrum might enhance diagnostic accuracy, it simultaneously augments both diagnostic complexity and associated financial implications. Within this landscape, we introduce a Probe for Cancer Subtype Identification via MicroRNA Expression Profile Recognition (PRIMER). PRIMER represents a meticulously designed nucleotide probe aimed at discerning breast cancer subtypes through a comprehensive analysis of microRNA profiles. Leveraging a genetic algorithm predicated upon nucleic acid thermodynamics, we fine-tuned PRIMER’s diagnostic potential. Our theoretical evaluations highlight its potential, with a capacity to selectively identify breast cancer subtypes, exhibiting an AUC value exceeding 0.9. In addition to its usefulness in breast cancer subtyping, PRIMER’s conceptual approach suggests potential applicability in diagnosing numerous diseases through microRNA profiling analysis.