Abstract
BACKGROUND: Gastric cancer represents a significant global health concern with poor prognosis and limited early detection methods. Circulating tumor cells (CTCs) that express folate receptors (FRs) have emerged as promising biomarkers for cancer monitoring, as folate receptor-alpha is overexpressed in cancer tissues while remaining absent in normal cells. OBJECTIVE: This study aimed to develop and optimize a Folate-Ligand Targeted quantitative PCR (Folate-LT qPCR) method for the selective detection and quantification of FR+ CTCs in gastric cancer patients. METHODS: The methodology involved designing a folate-oligonucleotide conjugate with a 5' folate moiety, triethylene glycol spacer, and phosphorothioate bond for stability. A specific stem-loop primer was developed for complementary DNA synthesis, followed by qPCR optimization using four candidate primers (F1, F1.1, F1.2, F1.3). Validation was conducted through spiking experiments with HeLa cells in healthy donor blood samples, followed by CTCs enrichment using negative depletion, labelling with the folate-conjugate, and two-step PCR amplification. Performance was assessed through amplification efficiency, melt curve analysis, and gel electrophoresis. RESULTS: Among tested primers, F1.1 demonstrated superior performance with consistent amplification across all tested concentrations without non-specific binding. Optimal annealing temperature for stem-loop primers were established at 40-45°C. The standard curve showed strong linearity (R2 = 0.9970) between cycle threshold values and logarithmic CTCs concentrations. The assay demonstrated 104% amplification efficiency with a regression equation of y = -3.231x+29.69, confirming reliable quantification capability across a wide dynamic range. CONCLUSION: The optimized Folate-LT qPCR method provides a sensitive and specific approach for detecting FR-positive CTCs in gastric cancer. This technique addresses limitations of existing CTC detection methods by combining negative depletion with specific ligand targeting, requiring minimal blood volume, and avoiding size-based or epithelial marker-dependent limitations, and shows promise for early cancer detection, disease progression monitoring, and treatment response assessment, potentially improving clinical outcomes for gastric cancer patients.