The Indian journal of medical research · 2025
Diagnostic accuracy of cfDNA levels in gallbladder cancer: A study using qPCR & threshold evaluation.
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Jindal Arpita, Nijhawan Sandeep, Vijay Urvashi, Kaur Ashmeet, Dana Rohitashwa
Аннотация
Background & objectives Gallbladder cancer (GBC) is a highly aggressive malignancy with a poor prognosis, often due to late-stage diagnosis. Existing diagnostic methods are invasive and not always feasible in resource-limited settings. Circulating free DNA (cfDNA) has emerged as a potential non-invasive biomarker for malignancies, including GBC. This study aimed to evaluate the diagnostic accuracy of cfDNA levels in distinguishing GBC patients from healthy controls, considering its potential for early detection and personalised treatment. Methods This case-control study included 42 newly diagnosed GBC affected individuals and 15 age- and sex-matched healthy controls. Plasma cfDNA was extracted using a bead-based protocol and quantified through quantitative PCR (qPCR) targeting the β-globin gene. Diagnostic thresholds were identified using Receiver Operating Characteristics (ROC) and precision-recall curve analyses, assessing sensitivity, specificity, and predictive values. Results cfDNA levels were significantly elevated in GBC patients compared to controls (P<0.05), with a mean cfDNA level of 721 ng/ml. Four diagnostic offering distinct clinical thresholds were identified: 75.5 ng/ml, 130 ng/ml, 188 ng/ml, and 372.92 ng/ml. The ROC curve demonstrated an area under the curve (AUC) of 0.94, indicating high diagnostic accuracy. cfDNA achieved high sensitivity (97.6% at 75.5 ng/ml) and 100 per cent specificity at 188 ng/ml. Interpretation & conclusion cfDNA serves as a reliable, non-invasive biomarker for GBC diagnosis, providing high diagnostic accuracy and utility in early detection and disease monitoring. These findings highlight cfDNA's potential as both a standalone diagnostic tool and a complementary marker to traditional tumour markers, enhancing diagnostic precision and aiding in personalised medicine. Its integration into diagnostic protocols can be particularly valuable in resource-limited settings.