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BioKnife, a uPA activity-dependent oncolytic Sendai virus, eliminates pleural spread of malignant mesothelioma via simultaneous stimulation of uPA expression.

ABSTRACT: Malignant pleural mesothelioma (MPM) is highly intractable and readily spreads throughout the surface of the pleural cavity, and these cells have been shown to express urokinase-type plasminogen activator receptor (uPAR). We here examined the potential of our new and powerful recombinant Sendai virus (rSeV), which shows uPAR-specific cell-to-cell fusion activity (rSeV/dMFct14 (uPA2), named "BioKnife"), for tumor cell killing in two independent orthotopic xenograft models of human. Multicycle treatment using BioKnife resulted in the efficient rescue of these models, in association with tumor-specific fusion and apoptosis. Such an effect was also seen on both MSTO-211H and H226 cells in vitro; however, we confirmed that the latter expressed uPAR but not uPA. Of interest, infection with BioKnife strongly facilitated the uPA release from H226 cells, and this effect was completely abolished by use of either pyrrolidine dithiocarbamate (PDTC) or BioKnife expressing the C-terminus-deleted dominant negative inhibitor for retinoic acid-inducible gene-I (RIG-IC), indicating that BioKnife-dependent expression of uPA was mediated by the RIG-I/nuclear factor-?B (NF-?B) axis, detecting RNA viral genome replication. Therefore, these results suggest a proof of concept that the tumor cell-killing mechanism via BioKnife may have significant potential to treat patients with MPM that is characterized by frequent uPAR expression in a clinical setting.

SUBMITTER: Morodomi Y

PROVIDER: S-EPMC3321599 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature

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BioKnife, a uPA activity-dependent oncolytic Sendai virus, eliminates pleural spread of malignant mesothelioma via simultaneous stimulation of uPA expression.

Morodomi Yosuke Y Yano Tokujiro T Kinoh Hiroaki H Harada Yui Y Saito Satoru S Kyuragi Ryoichi R Yoshida Kumi K Onimaru Mitsuho M Shoji Fumihiro F Yoshida Tsukihisa T Ito Kensaku K Shikada Yasunori Y Maruyama Riichiroh R Hasegawa Mamoru M Maehara Yoshihiko Y Yonemitsu Yoshikazu Y

Molecular therapy : the journal of the American Society of Gene Therapy 20120207 4

Malignant pleural mesothelioma (MPM) is highly intractable and readily spreads throughout the surface of the pleural cavity, and these cells have been shown to express urokinase-type plasminogen activator receptor (uPAR). We here examined the potential of our new and powerful recombinant Sendai virus (rSeV), which shows uPAR-specific cell-to-cell fusion activity (rSeV/dMFct14 (uPA2), named "BioKnife"), for tumor cell killing in two independent orthotopic xenograft models of human. Multicycle tre ...[more]

PMID: 22314292

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Project description:Malignant pleural mesothelioma (MPM) is a highly lethal, poorly understood neoplasm that is typically associated with asbestos exposure. We performed transcriptional profiling using high-density oligonucleotide microarrays containing approximately 22,000 genes to elucidate potential molecular and pathobiological pathways in MPM using discarded human MPM tumor specimens (n=40), normal lung specimens (n=4), normal pleura specimens (n=5), and MPM and SV40-immortalized mesothelial cell lines (n=5). In global expression analysis using unsupervised clustering techniques, we found two potential subclasses of mesothelioma which correlate loosely with tumor histology. We also identified sets of genes with expression levels that distinguish between multiple tumor subclasses, normal and tumor tissues, and tumors with different morphologies. Microarray gene expression data were confirmed using quantitative reverse transcriptase-polymerase chain reaction (RT-PCR) and protein analysis for three novel candidate oncogenes (NME2, CRI1, and PDGFC) and one candidate tumor suppressor (GSN). Finally, we used bioinformatics tools (i.e. software) to create and explore complex physiological pathways that may be relevant in mesothelioma tumorigenesis, pathobiology, or both. Tissues and cell lines profiled using microarrays. Discarded MPM surgical specimens (n=40), normal pleura specimens (n=5), and normal lung specimens (n=4) were freshly collected (and snap frozen) from patients who underwent surgery at Boston's Brigham and Women's Hospital (BWH) between October 1998 and August 2000. All of these patients underwent extrapleural pneumonectomy with heated intra-pleural cisplatin chemotherapy delivered after the specimens were removed. All normal specimens were obtained from patients who were never diagnosed with MPM. Two human MPM cell lines (MS589 and MS428) were kindly provided by Jonathan A. Fletcher, M.D., Department of Pathology, BWH. The JMN1B MPM cell line19,20 has been described previously. The SV40-immortalized, non-tumorigenic mesothelial cell line (Met-5A)21 and the MPM cell line MSTO-211H22 were purchased from the American Type Culture Collection. Normal tissues were obtained from additional consented patients undergoing treatment for diseases other than MPM. All MPM samples used in these studies contained relatively pure tumor (greater than 50% tumor cells per high power field examined in a section adjacent to the tissue used). The microscopic slides from the patients' resection specimens were reviewed by one of the authors (J.G.), and the diagnosis and histologic subclassification of MPM confirmed in all cases. Linked clinical and pathological data were obtained for all patients who contributed tumor specimens. Specimens and data were rendered anonymous to protect patient confidentiality. Studies utilizing human tissues were approved by and conducted in accordance with the policies of the Institutional Review Board at BWH.

Dataset Information

BioKnife, a uPA activity-dependent oncolytic Sendai virus, eliminates pleural spread of malignant mesothelioma via simultaneous stimulation of uPA expression.

Publications

BioKnife, a uPA activity-dependent oncolytic Sendai virus, eliminates pleural spread of malignant mesothelioma via simultaneous stimulation of uPA expression.

Similar Datasets

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