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Circulating tumor DNA: An alternative to tissue biopsy for detecting EGFR mutation in NSCLC

Soroar, M. K. I.; Roy, S.; Ara, H.; al-Nur, S.; Akanda, R. A.; Alam, M. M.

2025-09-21 oncology
10.1101/2025.09.19.25336178 medRxiv
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BackgroundNon-small cell lung cancer (NSCLC) patients who have mutations in their EGFR gene respond more favorably to Tyrosine Kinase Inhibitors (TKIs) than to standard chemotherapy. However, tissue biopsy-based EGFR testing is invasive, costly, and technically challenging. Plasma-derived circulating tumor DNA (ctDNA) offers a minimally invasive and cost-efficient alternative for mutation profiling. This study assessed the agreement between EGFR mutation detection in plasma-derived ctDNA and tissue biopsy in NSCLC patients from tertiary care hospitals in Bangladesh. MethodsIn this cross-sectional analytical study, we recruited 32 patients with NSCLC before EGFR-TKI treatment. EGFR mutations in ctDNA samples were identified using the Amplification Refractory Mutation System (ARMS) PCR method. Tissue biopsy results were obtained from routine diagnostic procedures. Agreement between ctDNA and tissue biopsy results was assessed using kappa statistics, and diagnostic performance metrics were calculated. ResultsMost of our study participants were male (75%) and had stage IV lung adenocarcinoma (72%). We observed substantial agreement between plasma-derived ctDNA samples and tissue biopsies (kappa, {kappa} = 0.683). This agreement was almost perfect ({kappa} = 0.826) when calculated for patients with stage IV disease. The overall concordance was 84.4%. Compared with tissue biopsy, ctDNA testing yielded a sensitivity of 73.3% and specificity of 94.1%. ConclusionPlasma-derived ctDNA demonstrates substantial agreement with tissue biopsy for EGFR mutation detection in patients with NSCLC, particularly those with advanced-stage disease. These findings support ctDNA as a viable alternative for molecular profiling in settings where tissue biopsy is limited or impractical.

Published in The International Journal of Biological Markers · not in our set (fewer than 10 published preprints to learn from) · training set

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