Selection and cloning of poly(rC)-binding protein 2 and Raf kinase inhibitor protein RNA activators of 2',5'-oligoadenylate synthetase from prostate cancer cells

The antiviral and antitumor functions of RNase L are enabled by binding to the allosteric effectors 5′-phosphorylated, 2′,5′-linked oligoadenylates (2-5A). 2-5A is produced by interferon-inducible 2′,5′-oligoadenylate synthetases (OAS) upon activation by viral double-stranded RNA (dsRNA). Because mutations in RNase L have been implicated as risk factors for prostate cancer, we sought to determine if OAS activators are present in prostate cancer cells. We show that prostate cancer cell lines (PC3, LNCaP and DU145), but not normal prostate epithelial cells (PrEC), contain RNA fractions capable of binding to and activating OAS. To identify the RNA activators, we developed a cDNA cloning strategy based on stringent affinity of RNAs for OAS. We thus identified mRNAs for Raf kinase inhibitor protein (RKIP) and poly(rC)-binding protein 2 (PCBP2) that bind and potently activate OAS. In addition, human endogenous retrovirus (hERV) envelope RNAs were present in PC3 cells that bind and activate OAS. Analysis of several gene expression profiling studies indicated that PCBP2 RNA was consistently elevated in metastatic prostate cancer. Results suggest that OAS activation may occur in prostate cancer cells in vivo stimulated by cellular mRNAs for RKIP and PCBP2.     

Probabilistic model of the human protein-protein interaction network

A catalog of all human protein-protein interactions would provide scientists with a framework to study protein deregulation in complex diseases such as cancer. Here we demonstrate that a probabilistic analysis integrating model organism interactome data, protein domain data, genome-wide gene expression data and functional annotation data predicts nearly 40,000 protein-protein interactions in humans-a result comparable to those obtained with experimental and computational approaches in model organisms. We validated the accuracy of the predictive model on an independent test set of known interactions and also experimentally confirmed two predicted interactions relevant to human cancer, implicating uncharacterized proteins into definitive pathways. We also applied the human interactome network to cancer genomics data and identified several interaction subnetworks activated in cancer. This integrative analysis provides a comprehensive framework for exploring the human protein interaction network.     

Amplified centrosomes may underlie aggressive disease course in pancreatic ductal adenocarcinoma

Centrosome amplification (CA), the presence of centrosomes that are abnormally numerous or enlarged, is a well-established driver of tumor initiation and progression associated with poor prognosis across a diversity of malignancies. Pancreatic ductal adenocarcinoma (PDAC) carries one of the most dismal prognoses of all cancer types. A majority of these tumors are characterized by numerical and structural centrosomal aberrations, but it is unknown how CA contributes to the disease and patient outcomes. In this study, we sought to determine whether CA was associated with worse clinical outcomes, poor prognostic indicators, markers of epithelial-mesenchymal transition (EMT), and ethnicity in PDAC. We also evaluated whether CA could precipitate more aggressive phenotypes in a panel of cultured PDAC cell lines. Using publicly available microarray data, we found that increased expression of genes whose dysregulation promotes CA was associated with worse overall survival and increased EMT marker expression in PDAC. Quantitative analysis of centrosomal profiles in PDAC cell lines and tissue sections uncovered varying levels of CA, and the expression of CA markers was associated with the expression of EMT markers. We induced CA in PDAC cells and found that CA empowered them with enhanced invasive and migratory capabilities. In addition, we discovered that PDACs from African American (AA) patients exhibited a greater extent of both numerical and structural CA than PDACs from European American (EA) patients. Taken together, these findings suggest that CA may fuel a more aggressive disease course in PDAC patients.     

Collagen modifying enzyme P4HA1 is overexpressed and plays a role in lung adenocarcinoma

Lung cancer is the leading cause of cancer-related deaths globally and is histologically defined as either small cell lung cancer (SCLC) or non-small cell lung cancer (NSCLC), with the latter accounting for 80% of all lung cancers. The 5-year overall survival rate for lung cancer patients is low as it is often discovered at advanced stages when potential cure by surgical resection is no longer an option. To identify a biomarker and target for lung cancer, we performed analysis of multiple datasets of lung cancer gene expression data. Our analyses indicated that the collagen-modifying enzyme Prolyl 4-Hydroxylase Subunit Alpha 1 (P4HA1) is overexpressed in NSCLC. Furthermore, our investigation found that overexpression of enzymes involved in this pathway predicts poor outcome for patients with lung adenocarcinoma. Our functional studies using knockdown strategies in lung cancer cell lines in vitro indicated that P4HA1 is critical for lung cancer growth, migration, and invasion. Additionally, diethyl pythiDC (PythiDC), a small molecule inhibitor, decreased the malignant phenotypes of lung cancer cells. Moreover, we found that miR-124 regulates and targets P4HA1 in lung cancer cells. Thus, our study suggests that collagen-modifying enzymes play an important role in lung cancer aggressiveness. Furthermore, our studies showed that P4HA1 is required for lung cancer cell growth and invasion, suggesting its potential as a valid therapeutic target in lung adenocarcinoma.