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Engineered vaccinia virus (VACV) strains are used extensively as vectors for the development of novel cancer vaccines and cancer therapeutics. In this study, we describe for the first time a high-throughput approach for both fluorescent rVACV generation and rapid viral titer measurement with the multi-well plate imaging system, IncuCyte\(^®\)S3. The isolation of a single, well-defined plaque is critical for the generation of novel recombinant vaccinia virus (rVACV) strains. Unfortunately, current methods of rVACV engineering via plaque isolation are time-consuming and laborious. Here, we present a modified fluorescent viral plaque screening and selection strategy that allows one to generally obtain novel fluorescent rVACV strains in six days, with a minimum of just four days. The standard plaque assay requires chemicals for fixing and staining cells. Manual plaque counting based on visual inspection of the cell culture plates is time-consuming. Here, we developed a fluorescence-based plaque assay for quantifying the vaccinia virus that does not require a cell staining step. This approach is less toxic to researchers and is reproducible; it is thus an improvement over the traditional assay. Lastly, plaque counting by virtue of a fluorescence-based image is very convenient, as it can be performed directly on the computer.
Background:
Pancreatic cancer is a fatal disease associated with resistance to conventional therapies. This study aimed to determine changes in gene expression patterns associated with infection and susceptibility of pancreatic cancer cells to an oncolyticvaccinia virus, GLV-1h153, carrying the human sodium iodide symporter for deep tissue imaging of virotherapy.
Methods:
Replication and susceptibility of pancreatic adenocarcinoma PANC-1 cells to GLV-1h153 was confirmed with replication and cytotoxicity assays. PANC-1 cells were then infected with GLV-1h153 and near-synchronous infection confirmed via flow cytometry of viral-induced green fluorescent protein (GFP) expression. Six and 24 hours after infection, three samples of each time point were harvested, and gene expression patterns assessed using HG-U133A cDNA microarray chips as compared to uninfected control. Differentially expressed genes were identified using Bioconductor LIMMA statistical analysis package. A fold change of 2.0 or above was used as a cutoff, with a P value of 0.01. The gene list was then analyzed using Ingenuity Pathways Analysis software.
Results:
Differential gene analysis revealed a total of 12,412 up- and 11,065 downregulated genes at 6 and 24 hours postinfection with GLV-1h153 as compared to control. At 6 hours postinfection. A total of 139 genes were either up or downregulated >twofold (false discovery rate < 0.05), of which 124 were mapped by Ingenuity Pathway Analysis (IPA). By 24 hours postinfection, a total of 5,698 genes were identified and 5,563 mapped by IPA. Microarray revealed gene expression changes, with gene networks demonstrating downregulation of processes such as cell death, cell cycle, and DNA repair, and upregulation of infection mechanisms (P < 0.01). Six hours after infection, gene changes involved pathways such as HMGB-1, interleukin (IL)-2, IL-6, IL-8, janus kinase/signal tranducer and activator of transcription (JAK/STAT), interferon, and ERK 5 signaling (P < 0.01). By 24 hours, prominent pathways included P53- and Myc-induced apoptotic processes, pancreatic adenocarcinoma signaling, and phosphoinositide 3-kinase/v-akt murine thymoma vial oncogene homolog 1 (PI3/AKT) pathways.
Conclusions:
Our study reveals the ability to assess time-dependent changes in gene expression patterns in pancreatic cancer cells associated with infection and susceptibility to vaccinia viruses. This suggests that molecular assays may be useful to develop safer and more efficacious oncolyticvirotherapies and support the idea that these treatments may target pathways implicated in pancreatic cancer resistance to conventional therapies.
Virotherapy on the basis of oncolytic vaccinia virus (VACV) strains is a promising approach for cancer therapy. Recently, we showed that the oncolytic vaccinia virus GLV-1h68 has a therapeutic potential in treating human prostate and hepatocellular carcinomas in xenografted mice. In this study, we describe the use of dynamic boolean modeling for tumor growth prediction of vaccinia virus-injected human tumors. Antigen profiling data of vaccinia virus GLV-1h68-injected human xenografted mice were obtained, analyzed and used to calculate differences in the tumor growth signaling network by tumor type and gender. Our model combines networks for apoptosis, MAPK, p53, WNT, Hedgehog, the T-killer cell mediated cell death, Interferon and Interleukin signaling networks. The in silico findings conform very well with in vivo findings of tumor growth. Similar to a previously published analysis of vaccinia virus-injected canine tumors, we were able to confirm the suitability of our boolean modeling for prediction of human tumor growth after virus infection in the current study as well. In summary, these findings indicate that our boolean models could be a useful tool for testing of the efficacy of VACV-mediated cancer therapy already before its use in human patients.