Characterization of dengue virus entry into HepG2 cells

<p>Abstract</p> <p>Background</p> <p>Despite infections by the dengue virus being a significant problem in tropical and sub-tropical countries, the mechanism by which the dengue virus enters into mammalian cells remains poorly described.</p> <p>Methods</p> <p>A combination of biochemical inhibition, dominant negative transfection of Eps15 and siRNA mediated gene silencing was used to explore the entry mechanism of dengue into HepG2 cells.</p> <p>Results</p> <p>Results were consistent with entry via multiple pathways, specifically via clathrin coated pit mediated endocytosis and macropinocytosis, with clathrin mediated endocytosis being the predominant pathway.</p> <p>Conclusion</p> <p>We propose that entry of the dengue virus to mammalian cells can occur by multiple pathways, and this opens the possibility of the virus being directed to multiple cellular compartments. This would have significant implications in understanding the interaction of the dengue virus with the host cell machinery.</p

Mathematical Model for Radial Expansion and Conflation of Intratumoral Infectious Centers Predicts Curative Oncolytic Virotherapy Parameters

<div><p>Simple, inductive mathematical models of oncolytic virotherapy are needed to guide protocol design and improve treatment outcomes. Analysis of plasmacytomas regressing after a single intravenous dose of oncolytic vesicular stomatitis virus in myeloma animal models revealed that intratumoral virus spread was spatially constrained, occurring almost exclusively through radial expansion of randomly distributed infectious centers. From these experimental observations we developed a simple model to calculate the probability of survival for any cell within a treated tumor. The model predicted that small changes to the density of initially infected cells or to the average maximum radius of infected centers would have a major impact on treatment outcome, and this was confirmed experimentally. The new model provides a useful and flexible tool for virotherapy protocol optimization.</p></div

Preclinical Development of Oncolytic Immunovirotherapy for Treatment of HPVPOS Cancers

Immunotherapy for HPVPOS malignancies is attractive because well-defined, viral, non-self tumor antigens exist as targets. Several approaches to vaccinate therapeutically against HPV E6 and E7 antigens have been adopted, including viral platforms such as VSV. A major advantage of VSV expressing these antigens is that VSV also acts as an oncolytic virus, leading to direct tumor cell killing and induction of effective anti-E6 and anti-E7 T cell responses. We have also shown that addition of immune adjuvant genes, such as IFNβ, further enhances safety and/or efficacy of VSV-based oncolytic immunovirotherapies. However, multiple designs of the viral vector are possible—with respect to levels of immunogen expression and method of virus attenuation—and optimal designs have not previously been tested head-to-head. Here, we tested three different VSV engineered to express a non-oncogenic HPV16 E7/6 fusion protein for their immunotherapeutic and oncolytic properties. We assessed their profiles of efficacy and toxicity against HPVPOS and HPVNEG murine tumor models and determined the optimal route of administration. Our data show that VSV is an excellent platform for the oncolytic immunovirotherapy of tumors expressing HPV target antigens, combining a balance of efficacy and safety suitable for evaluation in a first-in-human clinical trial. Keywords: VSV immunovirotherapy, HPV positive cancer, preclinica

Quantification of viable infected rim at the leading edge of infection to determine cell death rate.

<p>Immunofluorescence analysis of 5TGM1 tumors harvested 48-VSV administration, sectioned and stained to detect VSV (red), dying cells (TUNEL, green) and tumor cell nuclei (Hoescht, blue). Quantification of the mean viable rim width(n = 36 measurements), expressed in terms of cell diameters, at the leading edge of infection allows for the time from cellular infection by the VSV to cell death to be determined. Yellow bars indicate example locations of rim width determination.</p

Dose escalation in immunocompetent and immunocompromised myeloma tumor models validates model predictions.

<p>(<b>A</b>) Tumor volume monitored by serial caliper measurements in C57Bl6/KaLwRij mice bearing 5TGM1 tumors after single IV administration of sterile saline or VSV-mIFNβ-NIS at doses of 10⁵, 10⁶, 10⁷, or 10⁸ TCID₅₀ (top) and in CB17 ICR SCID mice bearing KAS 6/1 tumors after single IV administration of sterile saline or VSV-mIFNβ-NIS at doses of 10⁵, 10⁶, 10⁷, or 10⁸ TCID₅₀ (bottom) is plotted against time. Dotted line represents tumor volume sacrifice criteria. Dose escalation is used to model increasing <i>K</i>. Immunocompromised mice allow for extended periods of infectious foci expansion, increasing <i>r/R</i>. The model is validated by (B) dose-dependent tumor response, defined as proportion of mice with tumor regression at day 12 relative to baseline, and (C) partial remission, defined as tumor regression ≥50% compared to baseline after a single IV injection of VSV-IFNß-NIS in immunocompetent C57Bl6/KaLwRij or immunocompromised SCID mice bearing subcutaneous plasmacytomas.</p

Extravasation and spatially constrained spread of systemic oncolytic therapy.

<p>Immunofluorescence analysis and quantification of 5TGM1 tumors harvested following IV VSV administration, sectioned and stained to detect VSV (red), dying cells (TUNEL, green) and tumor cell nuclei (Hoescht, blue). (A) Seeds of infection established following virus extravasation 24 hr post-VSV(ΔG). (B) Expansion and conflation of intratumoral foci and destruction of tumor cells 48 hr post-VSV. (C) Radial expansion of infection and subsequent cell death of intratumoral focus in tumor harvested at 6, 12, 18, 24, and 48 hr post-VSV(i-v). (D) Quantification of mean infectious focus diameter (n = 7–9/interval) in tumors harvested at 6 hr intervals post-VSV. (E) Schematic representation of proposed model of systemic oncolytic therapy showing (i) extravasation and infection of tumor cells seeding randomly distributed infectious centers, (ii) spatially constrained expansion, and (iii) conflation of foci resulting in viral destruction of tumor cells, though voids of uninfected, surviving cells remain.</p

Tumor growth rates are negligible in comparison to growth of infectious foci.

<p>Kinetics of tumor growth. (A) Subcutaneous 5TGM1 or KAS 6/1 myeloma tumors were measured by serial caliper measurements following implantation in immunocompetent C57Bl6/KaLwRij or immunocompromised SCID mice respectively. Volume was calculated using the formula (l*h²/2). Tumor growth was fitted using the exponential growth equation Y = Y₀e^(kX), where tumor doubling time was approximately 3.2 and 5.3 days respectively. (B) Kinetics of intratumoral infectious foci expansion based on average infectious focus volume determined by the equation V =  where <i>d</i> is the focus diameter (Fig. 1D). Focus expansion was fitted using the exponential growth equation Y = Y₀e^(kX), where focus doubling time was approximately 3.2 hours. (C) Exponential growth rate, doubling time and goodness of fit for approximated growth curves of tumor models and infectious focus expansion. (D) Comparison of infectious foci expansion rate and subcutaneous 5TGM1 of KAS 6/1 myeloma tumor growth rates relative to size of tumor at time of virotherapy administration.</p

Math modeling of oncolytic tumor destruction and experimental validation.

<p>(<b>A</b>) Heatmap depicting average probability of tumor survival with respect to modeling parameters <i>r/R</i> and <i>K</i> determined using the spherical-cap approximation. Values of <i>r/R</i> and <i>K</i> have been converted to standard units of focus diameter (cell diameters) and percent of tumor cells infected at time zero of foci expansion respectively. Red = 0.00 probability of survival. Purple = 1.00 probability of survival. Sharp gradient from purple to red reveals drastic drop in survival upon small change in viral parameters. This gradient defines threshold of therapeutic efficacy. (B) Dose-response relationship: When the relative size of foci radius is kept constant, small changes in foci density, <i>K</i>, cause drastic changes in survivability beyond threshold dose. (C)When the density of foci is kept constant, small changes in the relative radius of infection foci cause changes in survivability. An increase in relative foci size achieves greater survivability at greater doses.</p