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MassARRAY-based KRAS and GNAS hotspot mutation analysis of cystic fluid enables accurate classification of pancreatic cystic lesions
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DOI：10.3748/wjg.v32.i13.115710.png)
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Abstract
En 中文
BACKGROUND Pancreatic cystic fluid analysis through mutation sequencing has proven to be a valuable approach for classifying pancreatic cystic lesions (PCLs). However, a rapid and cost-effective method for screening these lesions is still needed.AIM To evaluate the application of MassARRAY system in detecting hotspot mutation for the rapid diagnosis of PCLs. METHODS A total of 101 surgically resected PCLs were analyzed in this study. DNA was extracted from intraoperatively collected pancreatic cystic fluid. A custom panel targeting KRAS and GNAS hotspot mutations was developed, and the performance of MassARRAY-based mutation detection in classifying PCLs was evaluated. RESULTS Intraductal papillary mucinous neoplasms (IPMNs) exhibited GNAS mutations in 52.2% and KRAS mutations in 39.1% of cases, with 33.3% showing both mutations. KRAS mutations were detected in 30.6% of mucinous cystic neoplasms (MCNs), while serous cystadenomas and non-neoplastic neoplasms showed no detectable mutations. A logistic regression model integrating KRAS and GNAS mutations in pancreatic cystic fluid, along with serum tumor biomarkers and clinical features, achieved an area under the curve greater than 0.9 for identification of IPMNs and 0.795 for MCNs. CONCLUSION Targeted hotspot mutation analysis of KRAS and GNAS with MassARRAY technique in pancreatic cystic fluid offers a promising application for the molecular classification of PCLs. This method holds significant potential for improving preoperative diagnosis and assisting clinical decision-making in the management of PCLs.
Keywords:
Pancreatic cyst lesions
Cyst fluid analysis
KRAS
GNAS
MassARRAY
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