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Detection and Monitoring of Tumor Associated Circulating DNA in Patient Biofluids
Published on: June 8, 2019
Clinical Utility of Circulating Tumor DNA Analysis in Pancreatic Ductal Adenocarcinoma
Mirang Lee1, Ji-Young Lee2, In Ho Kang3
1Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Background:
Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with poor prognosis and limited early detection strategies. Circulating tumor DNA (ctDNA) offers a noninvasive method for tumor monitoring and prognostic prediction. We aimed to evaluate the clinical utility of ctDNA in PDAC, focusing on stage-dependent variations in ctDNA detection rate and its association with survival.
Methods:
The study included 35 patients with PDAC. Plasma and tissue samples were evaluated with next-generation sequencing to detect ctDNA and assess the concordance of mutations detected in ctDNA with those detected in tissue samples. The rates of ctDNA positivity and partial concordance were evaluated across disease stages. Demographics, clinicopathologic characteristics including neoadjuvant chemotherapy, and surgical outcomes were also evaluated.
Results:
Among the study population, 91.4% received neoadjuvant chemotherapy, and ctDNA was detected in 57.1% of the patients. KRAS mutations in ctDNA were identified in 11.4% of the patients, ranging from 0.0% in stage I PDAC to 28.6% in stage IV PDAC. The partial concordance rate between ctDNA and tumor tissue mutations increased from 0.0% in stage I to 66.7% in stage IV. Although the difference was not statistically significant, the two-year survival tended to be worse in patients with detectable ctDNA than in those without ctDNA (44.0% vs. 86.2%, p = 0.071).
Conclusions:
Our analysis demonstrates the potential clinical relevance of ctDNA analysis in patients with PDAC, especially those with advanced disease. However, its limited sensitivity in the detection of early-stage PDAC highlights the need for methodologic improvements. Our findings support the potential integration of ctDNA analysis into clinical workflows as a biomarker for disease monitoring and prognosis.
