Oncolytic Viruses: Do They Have a Role in Anti-Cancer Therapy?

Oncolytic viruses are replication competent, tumor selective and lyse cancer cells. Their potential for anti-cancer therapy is based upon the concept that selective intratumoral replication will produce a potent anti-tumor effect and possibly bystander or remote cell killing, whilst minimizing normal tissue toxicity. Viruses may be naturally oncolytic or be engineered for oncolytic activity, and possess a host of different mechanisms to provide tumor selectivity. Clinical use of live replicating viruses is associated with a unique set of safety issues. Clinical experience has so far provided evidence of limited efficacy and a favourable toxicity profile. The interaction with the host immune system is complex. An anti-viral immune response may limit efficacy by rapidly clearing the virus. However, virally-induced cell lysis releases tumor associated antigens in a ‘dangerous’ context, and limited evidence suggests that this can lead to the generation of a specific anti-tumor immune response. Combination therapy with chemotherapy or radiotherapy represents a promising avenue for ongoing translation of oncolytic viruses into clinical practice. Obstacles to therapy include highly effective non-specific host mechanisms to clear virus following systemic delivery, immune-mediated clearance, and intratumoral barriers limiting virus spread. A number of novel strategies are now under investigation to overcome these barriers. This review provides an overview of the potential role of oncolytic viruses, highlighting recent progress towards developing effective therapy and asks if they are a realistic therapeutic option at this stage

Do coder characteristics influence validity of ICD-10 hospital discharge data?

<p>Abstract</p> <p>Background</p> <p>Administrative data are widely used to study health systems and make important health policy decisions. Yet little is known about the influence of coder characteristics on administrative data validity in these studies. Our goal was to describe the relationship between several measures of validity in coded hospital discharge data and 1) coders' volume of coding (≥13,000 vs. <13,000 records), 2) coders' employment status (full- vs. part-time), and 3) hospital type.</p> <p>Methods</p> <p>This descriptive study examined 6 indicators of face validity in ICD-10 coded discharge records from 4 hospitals in Calgary, Canada between April 2002 and March 2007. Specifically, mean number of coded diagnoses, procedures, complications, Z-codes, and codes ending in 8 or 9 were compared by coding volume and employment status, as well as hospital type. The mean number of diagnoses was also compared across coder characteristics for 6 major conditions of varying complexity. Next, kappa statistics were computed to assess agreement between discharge data and linked chart data reabstracted by nursing chart reviewers. Kappas were compared across coder characteristics.</p> <p>Results</p> <p>422,618 discharge records were coded by 59 coders during the study period. The mean number of diagnoses per record decreased from 5.2 in 2002/2003 to 3.9 in 2006/2007, while the number of records coded annually increased from 69,613 to 102,842. Coders at the tertiary hospital coded the most diagnoses (5.0 compared with 3.9 and 3.8 at other sites). There was no variation by coder or site characteristics for any other face validity indicator. The mean number of diagnoses increased from 1.5 to 7.9 with increasing complexity of the major diagnosis, but did not vary with coder characteristics. Agreement (kappa) between coded data and chart review did not show any consistent pattern with respect to coder characteristics.</p> <p>Conclusions</p> <p>This large study suggests that coder characteristics do not influence the validity of hospital discharge data. Other jurisdictions might benefit from implementing similar employment programs to ours, e.g.: a requirement for a 2-year college training program, a single management structure across sites, and rotation of coders between sites. Limitations include few coder characteristics available for study due to privacy concerns.</p

PlantCV v2: Image analysis software for high-throughput plant phenotyping

Systems for collecting image data in conjunction with computer vision techniques are a powerful tool for increasing the temporal resolution at which plant phenotypes can be measured non-destructively. Computational tools that are flexible and extendable are needed to address the diversity of plant phenotyping problems. We previously described the Plant Computer Vision (PlantCV) software package, which is an image processing toolkit for plant phenotyping analysis. The goal of the PlantCV project is to develop a set of modular, reusable, and repurposable tools for plant image analysis that are open-source and community-developed. Here we present the details and rationale for major developments in the second major release of PlantCV. In addition to overall improvements in the organization of the PlantCV project, new functionality includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning

Pyrosequencing of the Camptotheca acuminata transcriptome reveals putative genes involved in camptothecin biosynthesis and transport

Background: Camptotheca acuminata is a Nyssaceae plant, often called the "happy tree", which is indigenous in Southern China. C. acuminata produces the terpenoid indole alkaloid, camptothecin (CPT), which exhibits clinical effects in various cancer treatments. Despite its importance, little is known about the transcriptome of C. acuminata and the mechanism of CPT biosynthesis, as only few nucleotide sequences are included in the GenBank database.Results: From a constructed cDNA library of young C. acuminata leaves, a total of 30,358 unigenes, with an average length of 403 bp, were obtained after assembly of 74,858 high quality reads using GS De Novo assembler software. Through functional annotation, a total of 21,213 unigenes were annotated at least once against the NCBI nucleotide (Nt), non-redundant protein (Nr), Uniprot/SwissProt, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Arabidopsis thaliana proteome (TAIR) databases. Further analysis identified 521 ESTs representing 20 enzyme genes that are involved in the backbone of the CPT biosynthetic pathway in the library. Three putative genes in the upstream pathway, including genes for geraniol-10-hydroxylase (CaPG10H), secologanin synthase (CaPSCS), and strictosidine synthase (CaPSTR) were cloned and analyzed. The expression level of the three genes was also detected using qRT-PCR in C. acuminata. With respect to the branch pathway of CPT synthesis, six cytochrome P450s transcripts were selected as candidate transcripts by detection of transcript expression in different tissues using qRT-PCR. In addition, one glucosidase gene was identified that might participate in CPT biosynthesis. For CPT transport, three of 21 transcripts for multidrug resistance protein (MDR) transporters were also screened from the dataset by their annotation result and gene expression analysis.Conclusion: This study produced a large amount of transcriptome data from C. acuminata by 454 pyrosequencing. According to EST annotation, catalytic features prediction, and expression analysis, novel putative transcripts involved in CPT biosynthesis and transport were discovered in C. acuminata. This study will facilitate further identification of key enzymes and transporter genes in C. acuminata

Towards Predictive Computational Models of Oncolytic Virus Therapy: Basis for Experimental Validation and Model Selection

Oncolytic viruses are viruses that specifically infect cancer cells and kill them, while leaving healthy cells largely intact. Their ability to spread through the tumor makes them an attractive therapy approach. While promising results have been observed in clinical trials, solid success remains elusive since we lack understanding of the basic principles that govern the dynamical interactions between the virus and the cancer. In this respect, computational models can help experimental research at optimizing treatment regimes. Although preliminary mathematical work has been performed, this suffers from the fact that individual models are largely arbitrary and based on biologically uncertain assumptions. Here, we present a general framework to study the dynamics of oncolytic viruses that is independent of uncertain and arbitrary mathematical formulations. We find two categories of dynamics, depending on the assumptions about spatial constraints that govern that spread of the virus from cell to cell. If infected cells are mixed among uninfected cells, there exists a viral replication rate threshold beyond which tumor control is the only outcome. On the other hand, if infected cells are clustered together (e.g. in a solid tumor), then we observe more complicated dynamics in which the outcome of therapy might go either way, depending on the initial number of cells and viruses. We fit our models to previously published experimental data and discuss aspects of model validation, selection, and experimental design. This framework can be used as a basis for model selection and validation in the context of future, more detailed experimental studies. It can further serve as the basis for future, more complex models that take into account other clinically relevant factors such as immune responses

Microsecond Time-Resolved Absorption Spectroscopy Used to Study CO Compounds of Cytochrome bd from Escherichia coli

Cytochrome bd is a tri-heme (b558, b595, d) respiratory oxygen reductase that is found in many bacteria including pathogenic species. It couples the electron transfer from quinol to O2 with generation of an electrochemical proton gradient. We examined photolysis and subsequent recombination of CO with isolated cytochrome bd from Escherichia coli in oneelectron reduced (MV) and fully reduced (R) states by microsecond time-resolved absorption spectroscopy at 532-nm excitation. Both Soret and visible band regions were examined. CO photodissociation from MV enzyme possibly causes fast (t,1.5 ms) electron transfer from heme d to heme b595 in a small fraction of the protein, not reported earlier. Then the electron migrates to heme b558 (t,16 ms). It returns from the b-hemes to heme d with t,180 ms. Unlike cytochrome bd in the R state, in MV enzyme the apparent contribution of absorbance changes associated with CO dissociation from heme d is small, if any. Photodissociation of CO from heme d in MV enzyme is suggested to be accompanied by the binding of an internal ligand (L) at the opposite side of the heme. CO recombines with heme d (t,16 ms) yielding a transient hexacoordinate state (CO-Fe2+ -L). Then the ligand slowly (t,30 ms) dissociates from heme d. Recombination of CO with a reduced heme b in a fraction of the MV sample may also contribute to the 30-ms phase. In R enzyme, CO recombines to heme d (t,20 ms), some heme b558 (t,0.2–3 ms), and finally migrates from heme d to heme b595 (t,24 ms) in ,5% of the enzyme population. Data are consistent with the recent nanosecond study of Rappaport et al. conducted on the membranes at 640-nm excitation but limited to the Soret band. The additional phases were revealed due to differences in excitation and other experimental conditions

Ascorbate Biosynthesis during Early Fruit Development Is the Main Reason for Its Accumulation in Kiwi

Background: Ascorbic acid (AsA) is a unique antioxidant as well as an enzyme cofactor. Although it has multiple roles in plants, it is unclear how its accumulation is controlled at the expression level, especially in sink tissues. Kiwifruit (Actinidia) is well-known for its high ascorbate content. Our objective was to determine whether AsA accumulates in the fruits primarily through biosynthesis or because it is imported from the foliage. Methodology/Principal Findings: We systematically investigated AsA levels, biosynthetic capacity, and mRNA expression of genes involved in AsA biosynthesis in kiwi (A. deliciosa cv. Qinmei). Recycling and AsA localization were also monitored during fruit development and among different tissue types. Over time, the amount of AsA, with its capacity for higher biosynthesis and lower recycling, peaked at 30 days after anthesis (DAA), and then decreased markedly up to 60 DAA before declining more slowly. Expression of key genes showed similar patterns of change, except for L-galactono-1,4-lactone dehydrogenase and L-galactose-1-phosphate phosphatase (GPP). However, GPP had good correlation with the rate of AsA accumulation. The expression of these genes could be detected in phloem of stem as well as petiole of leaf and fruit. Additionally, fruit petioles had greater ascorbate amounts, although that was the site of lowest expression by most genes. Fruit microtubule tissues also had higher AsA. However, exogenous applications of AsA to those petioles did not lead to its transport into fruits, and distribution of ascorbate was cell-specific in the fruits, with more accumulation occurring in large