Preliminary qPCR-based assessment of BAT-25 and BAT-26 microsatellite instability in formalin-fixed paraffin-embedded colon cancer samples: A pilot study from Sri Lanka

Colorectal cancer (CRC) is one of the most common malignancies worldwide, and assessment of microsatellite instability (MSI) provides important prognostic and therapeutic information. However, conventional MSI detection methods often rely on qualitative evaluation of fragment length alterations and may be challenging to implement in resource-limited settings. This pilot study evaluated the feasibility and preliminary amplification patterns of a quantitative PCR (qPCR)-based approach targeting the BAT-25 and BAT-26 microsatellite markers in formalin-fixed paraffin-embedded (FFPE) colon tissue samples. A cross-sectional descriptive study was conducted using fifteen FFPE tissue samples comprising ten colon cancer cases and five non-neoplastic colonic controls. Genomic DNA was extracted using a commercial FFPE DNA extraction kit, and qPCR was performed using SYBR Green chemistry to determine cycle threshold (Ct) values. Relative amplification differences were assessed using ΔCt values, with β-actin used as the reference gene. Both BAT-25 and BAT-26 demonstrated significant differences in ΔCt values between colon cancer samples and controls (p < 0.05). Exploratory logistic regression and receiver operating characteristic analyses indicated potential discriminatory ability, with area under the curve values of 0.72 for BAT-25 and 0.80 for BAT-26. BAT-26 showed higher specificity within this dataset. These findings suggest that qPCR-based amplification profiles of BAT-25 and BAT-26 may reflect molecular differences associated with MSI status between colon cancer and non-neoplastic colonic tissues. However, the small sample size and exploratory nature of this study require cautious interpretation, and further validation using larger cohorts and established MSI testing methods is necessary. This pilot study demonstrates the technical feasibility of a qPCR-based approach for preliminary assessment of MSI-associated patterns in FFPE samples and highlights its potential applicability in low-resource laboratory settings.