Placenta-Specific 8 Is Overexpressed and Regulates Cell Proliferation in Low-Grade Human Pancreatic Neuroendocrine Tumors.

BACKGROUND/AIMS: Many aspects of the biology of pancreatic neuroendocrine tumors (PanNETs), including determinants of proliferative, invasive, and metastatic potential, remain poorly understood. Placenta-specific 8 (PLAC8), a gene with unknown molecular function, has been reported to have tumor-promoting roles in different human malignancies, including exocrine pancreatic cancer. Since preliminary data suggested deregulation of PLAC8 expression in PanNET, we have performed detailed analyses of PLAC8 expression and function in human PanNET. METHODS: Primary tissue from PanNET patients was immunohistochemically stained for PLAC8, and expression was correlated with clinicopathological data. In vitro, PLAC8 expression was inhibited by siRNA transfection in PanNET cell lines and effects were analyzed by qRT-PCR, Western blot, and proliferation assays. RESULTS: We report that PLAC8 is expressed in the majority of well-differentiated human PanNETs, predominantly in early-stage and low-grade tumors. SiRNA-mediated knockdown of PLAC8 in PanNET cells resulted in decreased proliferation and viability, while apoptosis was not induced. Mechanistically, these effects were mediated by attenuation of cell cycle progression, as Western blot analyses demonstrated upregulation of the tumor suppressor p21/CDKN2A and downregulation of the cell cycle regulator Cyclin D1 as well as reduced levels of phosphorylated ribosomal protein s6 and retinoblastoma protein. CONCLUSION: Our findings establish PLAC8 as a central mediator of cell growth in a subset of human PanNET, providing evidence for the existence of distinct molecular subtypes within this class of tumors.

Unraveling the Molecular Tumor-Promoting Regulation of Cofilin-1 in Pancreatic Cancer.

Cofilin-1 (CFL1) overexpression in pancreatic cancer correlates with high invasiveness and shorter survival. Besides a well-documented role in actin remodeling, additional cellular functions of CFL1 remain poorly understood. Here, we unraveled molecular tumor-promoting functions of CFL1 in pancreatic cancer. For this purpose, we first show that a knockdown of CFL1 results in reduced growth and proliferation rates in vitro and in vivo, while apoptosis is not induced. By mechanistic modeling we were able to predict the underlying regulation. Model simulations indicate that an imbalance in actin remodeling induces overexpression and activation of CFL1 by acting on transcription factor 7-like 2 (TCF7L2) and aurora kinase A (AURKA). Moreover, we could predict that CFL1 impacts proliferation and apoptosis via the signal transducer and activator of transcription 3 (STAT3). These initial model-based regulations could be substantiated by studying protein levels in pancreatic cancer cell lines and human datasets. Finally, we identified the surface protein CD44 as a promising therapeutic target for pancreatic cancer patients with high CFL1 expression.

Combined microRNA and mRNA microfluidic TaqMan array cards for the diagnosis of malignancy of multiple types of pancreatico-biliary tumors in fine-needle aspiration material.

Pancreatic ductal adenocarcinoma (PDAC) continues to carry the lowest survival rates among all solid tumors. A marked resistance against available therapies, late clinical presentation and insufficient means for early diagnosis contribute to the dismal prognosis. Novel biomarkers are thus required to aid treatment decisions and improve patient outcomes. We describe here a multi-omics molecular platform that allows for the first time to simultaneously analyze miRNA and mRNA expression patterns from minimal amounts of biopsy material on a single microfluidic TaqMan Array card. Expression profiles were generated from 113 prospectively collected fine needle aspiration biopsies (FNAB) from patients undergoing surgery for suspect masses in the pancreas. Molecular classifiers were constructed using support vector machines, and rigorously evaluated for diagnostic performance using 10×10fold cross validation. The final combined miRNA/mRNA classifier demonstrated a sensitivity of 91.7%, a specificity of 94.5%, and an overall diagnostic accuracy of 93.0% for the differentiation between PDAC and benign pancreatic masses, clearly outperfoming miRNA-only classifiers. The classification algorithm also performed very well in the diagnosis of other types of solid tumors (acinar cell carcinomas, ampullary cancer and distal bile duct carcinomas), but was less suited for the diagnostic analysis of cystic lesions. We thus demonstrate that simultaneous analysis of miRNA and mRNA biomarkers from FNAB samples using multi-omics TaqMan Array cards is suitable to differentiate suspect solid pancreatic masses with high precision.