Rapid and accessible detection of ovarian cancer biomarkers remains a major challenge for effective point-of- care diagnostics. Of these, CA125 is majorly used for disease diagnostics. However, current detection methods are constrained by cost, complexity, and limited portability. In the present study, we proposed an integrated methodology by combining bioinformatics-driven aptamer discovery with lateral flow assay (LFA) development. A huge library of ssDNA (~4.1 x 106 sequences) was thoroughly screened by using computational tools to identify high-affinity aptamer candidates, which resulted in the selection of a novel aptamer (P1) with superior predicted binding performance relative to existing sequences. The selected aptamer was subjected to conjugation with gold nanoparticles and incorporated into a Lateral Flow Assay platform for rapid detection. The developed assay showed clear and reproducible visual detection of CA125 antigen at 10 ng/mL. This study establishes a systematic pipeline which links in-silico aptamer design with practical diagnostic implementation, which offers a scalable and cost-effective approach for next-generation point-of- care cancer biosensors.
Tandasi et al. (Thu,) studied this question.