Aptamer Candidate Development through ctDNA Fragments

Cancer deaths are largely attributable to late diagnosis and lack of recurrence surveillance, especially seen in low and middle income countries. Cell-free DNA (cfDNA) in plasma provides a minimally invasive window into tumor biology, making it a promising biomarker for cancer detection and monitoring due to distinctive end motif signatures. I hypothesize that ctDNA fragment-end motifs can be translated into stable aptamer candidates with higher binding specificity with suitable properties for a biosensor. Public cfDNA whole-genome sequencing for lung cancer and healthy plasma datasets were analyzed. K-mer frequency analysis and motif enrichment scanning was conducted, and custom motifs which were canonical transcription factor binding sites such as TATAAA, CCAAT, and GC-rich sequences were quantified between cancer and healthy datasets, with statistical validation to ensure accuracy. From these enriched motifs, aptamer candidates were designed and evaluated for GC content, melting temperature, and secondary structure stability using Biopython and RNAfold. Motif enrichment analysis identified 1 match for TATAAA in ctDNA, 11 matches for CCAAT (compared to 5 in healthy), and 6 matches for GC-rich motifs (compared to 3 in healthy). These motifs revealed five potential aptamer candidates with stability. Of these, secondary structure prediction for aptamer 1and 2 formed a weak stem-loop, with aptamer 1 also forming a tertiary structure. These findings suggest that CCAAT and GC-rich motifs are selectively enriched in cancer cfDNA. The modeling of aptamer 1 based on the enriched motifs demonstrates that fragmentomic signals can be translated into aptamer scaffolds with realistic folding potential.