miRNA analysis in pancreatic cancer: the Dartmouth experience

Pancreatic cancer is considered one of the most lethal cancers being the fourth leading cause of cancer deaths in adults in the United States because of the lack of early signs and symptoms and the lack of early detection. Pancreatic ductal adenocarcinoma (PDAC) is the most common histological type...

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Veröffentlicht in:Clinical chemistry and laboratory medicine 2017-05, Vol.55 (5), p.755-762
Hauptverfasser: Abreu, Francine B. de, Liu, Xiaoying, Tsongalis, Gregory J.
Format: Artikel
Sprache:eng
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Zusammenfassung:Pancreatic cancer is considered one of the most lethal cancers being the fourth leading cause of cancer deaths in adults in the United States because of the lack of early signs and symptoms and the lack of early detection. Pancreatic ductal adenocarcinoma (PDAC) is the most common histological type among pancreatic cancers, representing 80%–90% of all solid tumors of the pancreas. The majority of PDAC develops from three precursor lesions: pancreatic intraepithelial neoplasia, intraductual papillary mucinous neoplasm and mucinous cystic neoplasm. Although histologic tissue evaluation remains the gold standard for diagnosis, endoscopic ultrasound-guided fine needle aspiration has become the preferred modality for obtaining pathologic confirmation. At Dartmouth-Hitchcock Medical Center (DHMC),we have developed and validated a microRNA (miRNA) panel for patients with pancreatic diseases that can be used in association with the gold standard method for diagnosis. miRNAs have an important role in biological processes, such as apoptosis, metabolism, cell growth and differentiation. In cancer, miRNAs can be classified as either oncogenic or tumor suppressor according to their function in the carcinogenic process. In this study, we describe the expression of many miRNA in benign and malignant pancreatic tissues as well as their clinical significance. For this reason, miRNAs have been considered potential biomarkers of pancreatic diseases that could potentially contribute to an early diagnosis, predict disease progression, accurately monitor disease, contribute to better treatment strategies and reduce mortality by improving disease management.
ISSN:1434-6621
1437-4331
DOI:10.1515/cclm-2017-0046