The Ohio State University College of Medicine, Columbus, OH, 43210, USA.
Division of Surgical Oncology, Department of Surgery, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA.
J Gastrointest Surg. 2020 May;24(5):1201-1214. doi: 10.1007/s11605-020-04537-2. Epub 2020 Mar 3.
The prevalence of incidental pancreatic cystic neoplasms (PCNs) has increased dramatically with advancements in cross-sectional imaging. Diagnostic imaging is limited in differentiating between benign and malignant PCNs. The aim of this review is to provide an overview of biomarkers that can be used to distinguish PCNs.
A review of the literature on molecular diagnosis of cystic neoplasms of the pancreas was performed.
Pancreatic cysts can be categorized into inflammatory and non-inflammatory lesions. Inflammatory cysts include pancreatic pseudocysts. Noninflammatory lesions include both mucinous and non-mucinous lesions. Mucinous lesions include intraductal papillary mucinous neoplasm (IPMN) and mucinous cystic neoplasm. Non-mucinous lesions include serous cystadenoma and solid-pseudopapillary tumor of the pancreas. Imaging, cyst aspiration, and histologic findings, as well as carcinoembryonic antigen and amylase are commonly used to distinguish between cyst types. However, molecular techniques to detect differences in genetic mutations, protein expression, glycoproteomics, and metabolomic profiling are important developments in distinguishing between cyst types.
Nomograms incorporating common clinical, laboratory, and imaging findings have been developed in a better effort to predict malignant IPMN. The incorporation of top molecular biomarker candidates to nomograms may improve the predictive ability of current models to more accurately diagnose malignant PCNs.
随着影像学技术的进步,偶然发现的胰腺囊性肿瘤(PCN)的患病率显著增加。诊断影像学在鉴别良恶性 PCN 方面存在局限性。本综述的目的是概述可用于鉴别 PCN 的生物标志物。
对胰腺囊性肿瘤的分子诊断相关文献进行了回顾。
胰腺囊肿可分为炎症性和非炎症性病变。炎症性囊肿包括胰腺假性囊肿。非炎症性病变包括黏液性和非黏液性病变。黏液性病变包括导管内乳头状黏液性肿瘤(IPMN)和黏液性囊腺瘤。非黏液性病变包括浆液性囊腺瘤和胰腺实性假乳头状瘤。影像学、囊液抽吸和组织学发现以及癌胚抗原和淀粉酶常用于鉴别囊肿类型。然而,检测基因突变异质、蛋白表达、糖蛋白组学和代谢组学特征等分子技术对于鉴别囊肿类型非常重要。
已经开发了包含常见临床、实验室和影像学发现的列线图,以更好地预测恶性 IPMN。将最佳的分子生物标志物候选物纳入列线图可能会提高当前模型的预测能力,从而更准确地诊断恶性 PCN。