Ansuman Bagchi

Phase 1 studies of the safety and immunogenicity of electroporated HER2/CEA DNA vaccine followed by adenoviral boost immunization in patients with solid tumors

BackgroundDNA electroporation has been demonstrated in preclinical models to be a promising strategy to improve cancer immunity, especially when combined with other genetic vaccines in heterologous prime-boost protocols. We report the results of 2 multicenter phase 1 trials involving adult cancer patients (n=33) with stage II-IV disease.MethodsPatients were vaccinated with V930 alone, a DNA vaccine containing equal amounts of plasmids expressing the extracellular and trans-membrane domains of human HER2, and a plasmid expressing CEA fused to the B subunit of Escherichia coli heat labile toxin (Study 1), or a heterologous prime-boost vaccination approach with V930 followed by V932, a dicistronic adenovirus subtype-6 viral vector vaccine coding for the same antigens (Study 2).ResultsThe use of the V930 vaccination with electroporation alone or in combination with V932 was well-tolerated without any serious adverse events. In both studies, the most common vaccine-related side effects were injection site reactions and arthralgias. No measurable cell-mediated immune response (CMI) to CEA or HER2 was detected in patients by ELISPOT; however, a significant increase of both cell-mediated immunity and antibody titer against the bacterial heat labile toxin were observed upon vaccination.ConclusionV930 vaccination alone or in combination with V932 was well tolerated without any vaccine-related serious adverse effects, and was able to induce measurable immune responses against bacterial antigen. However, the prime-boost strategy did not appear to augment any detectable CMI responses against either CEA or HER2.Trial registrationStudy 1 – ClinicalTrials.gov, NCT00250419; Study 2 – ClinicalTrials.gov, NCT00647114.

Analysis of lipid nanoparticles by Cryo-EM for characterizing siRNA delivery vehicles

Lipid nanoparticles are self-assembling, dynamic structures commonly used as carriers of siRNA, DNA, and small molecular therapeutics. Quantitative analysis of particle characteristics such as morphological features can be very informative as biophysical properties are known to influence biological activity, biodistribution, and toxicity. However, accurate characterization of particle attributes and population distributions is difficult. Cryo-Electron Microscopy (Cryo-EM) is a leading characterization method and can reveal diversity in particle size, shape and lamellarity, however, this approach is traditionally used for qualitative review or low throughput image analysis due to inherent EM micrograph contrast characteristics and artifacts in the images which limit extraction of quantitative feature values. In this paper we describe the development of a semiautomatic image analysis framework to facilitate reliable image enhancement, object segmentation, and quantification of nanoparticle attributes in Cryo-EM micrographs. We apply this approach to characterize two formulations of siRNA-loaded lipid nanoparticles composed of cationic lipid, cholesterol, and poly(ethylene glycol)-lipid, where the formulations differ only by input component ratios. We found Cryo-EM image analysis provided reliable size and morphology information as well as the detection of smaller particle populations that were not detected by standard dynamic light scattering (DLS) analysis.

High-Potency Human Immunodeficiency Virus Vaccination Leads to Delayed and Reduced CD8+ T-Cell Expansion but Improved Virus Control

ABSTRACT CD8+ T lymphocytes are thought to play an important role in the control of acute and chronic human immunodeficiency virus infections. However, there is a significant delay between infection and the first observed increase in virus-specific CD8+ T-cell numbers. Prior to this time, viral kinetics are not significantly different between controls and vaccinees. Surprisingly, higher initial virus-specific CD8+ T-cell numbers lead to a longer delay prior to initial CD8+ T-cell expansion, and slower CD8+ T-cell increases. Nevertheless, higher initial CD8+ T-cell numbers were associated with reduced peak and chronic viral loads and reduced CD4+ T-cell depletion.

An efficient T-cell epitope discovery strategy using in silico prediction and the iTopia assay platform

Functional T-cell epitope discovery is a key process for the development of novel immunotherapies, particularly for cancer immunology. In silico epitope prediction is a common strategy to try to achieve this objective. However, this approach suffers from a significant rate of false-negative results and epitope ranking lists that often are not validated by practical experience. A high-throughput platform for the identification and prioritization of potential T-cell epitopes is the iTopiaTM Epitope Discovery SystemTM, which allows measuring binding and stability of selected peptides to MHC Class I molecules. So far, the value of iTopia combined with in silico epitope prediction has not been investigated systematically. In this study, we have developed a novel in silico selection strategy based on three criteria: (1) predicted binding to one out of five common MHC Class I alleles; (2) uniqueness to the antigen of interest; and (3) increased likelihood of natural processing. We predicted in silico and characterized by iTopia 225 candidate T-cell epitopes and fixed-anchor analogs from three human tumor-associated antigens: CEA, HER2 and TERT. HLA-A2-restricted fragments were further screened for their ability to induce cell-mediated responses in HLA-A2 transgenic mice. The iTopia binding assay was only marginally informative while the stability assay proved to be a valuable experimental screening method complementary to in silico prediction. Thirteen novel T-cell epitopes and analogs were characterized and additional potential epitopes identified, providing the basis for novel anticancer immunotherapies. In conclusion, we show that combination of in silico prediction and an iTopia-based assay may be an accurate and efficient method for MHC Class I epitope discovery among tumor-associated antigens.

The CRASSS plug-in for integrating annotation data with hierarchical clustering results

We describe an algorithm for finding the most statistically significant non-overlapping subtrees of a hierarchical clustering of gene expression data with respect to a set of secondary data labels on genes. The method is implemented as a Java plug-in for a commercial gene expression analysis program (GeneSpring).

Modeling Effect of a γ-Secretase Inhibitor on Amyloid-β Dynamics Reveals Significant Role of an Amyloid Clearance Mechanism

Aggregation of the small peptide amyloid beta (Aβ) into oligomers and fibrils in the brain is believed to be a precursor to Alzheimer’s disease. Aβ is produced via multiple proteolytic cleavages of amyloid precursor protein (APP), mediated by the enzymes β- and γ-secretase. In this study, we examine the temporal dynamics of soluble (unaggregated) Aβ in the plasma and cerebral-spinal fluid (CSF) of rhesus monkeys treated with different oral doses of a γ-secretase inhibitor. A dose-dependent reduction of Aβ concentration was observed within hours of drug ingestion, for all doses tested. Aβ concentration in the CSF returned to its predrug level over the monitoring period. In contrast, Aβ concentration in the plasma exhibited an unexpected overshoot to as high as 200% of the predrug concentration, and this overshoot persisted as late as 72 hours post-drug ingestion. To account for these observations, we proposed and analyzed a minimal physiological model for Aβ dynamics that could fit the data. Our analysis suggests that the overshoot arises from the attenuation of an Aβ clearance mechanism, possibly due to the inhibitor. Our model predicts that the efficacy of Aβ clearance recovers to its basal (pretreatment) value with a characteristic time of >48 hours, matching the time-scale of the overshoot. These results point to the need for a more detailed investigation of soluble Aβ clearance mechanisms and their interaction with Aβ-reducing drugs.

A novel minigene scaffold for therapeutic cancer vaccines.

Genetic vaccines are emerging as a powerful modality to induce T-cell responses to target tumor associated antigens (TAA). Viral or plasmid DNA or RNA vectors harbor an expression cassette encoding the antigen of choice delivered in vivo by vaccination. In this context, immunizations with minigenes containing selected, highly antigenic, T-cell epitopes of TAAs may have several advantages relative to full-length proteins. The objective of this study was to identify an optimal scaffold for minigene construction. We generated a number of minigenes containing epitopes from the carcinoembryonic antigen (CEA) model TAA and utilized muscle DNA electro-gene-transfer (DNA-EGT) to vaccinate HLA-A*0201 (HHD) and CEA/HHD double transgenic mice. The components utilized to construct the minigenes included CD8+ T cell epitopes and (or) anchor modified analogs that were selected on the basis of their predicted binding to HLA-*A0201, their uniqueness in the human proteome, and the likelihood of cancer cell natural processing and presentation via MHC-I. Other candidate components comparatively tested included: helper CD4+ T-cell epitopes, flanking regions for optimal epitope processing (including both proteasome-dependent and furin-dependent polypeptide processing mechanisms), and immunoenhancing moieties. Through a series of comparative studies and iterations we have identified an optimal minigene scaffold comprising the following elements: human tissue plasminogen activator (TPA) signal peptide, T-cell epitopes connected by furin sensitive linkers, and the E. Coli enterotoxin B subunit. The selected epitope modified minigenes (EMM) delivered by DNA-EGT were able to break immune tolerance in CEA/HHD mice and induce a strong immune response against all epitopes tested, independently of their relative positions within the scaffold. Furthermore, the optimized EMMs delivered via DNA-EGT were more immunogenic and exerted more powerful antitumor effects in a B16-CEA/HHD metastatic melanoma model than a DNA vector encoding the full-length protein or a mixture of the same peptides injected subcutaneously. Our data may shed light on the optimal design of a universal vehicle for epitope-targeted, genetic cancer vaccines.

Automatic classification of squamosal abnormality in micro-CT images for the evaluation of rabbit fetal skull defects using active shape models

High-throughput micro-CT imaging has been used in our laboratory to evaluate fetal skeletal morphology in developmental toxicology studies. Currently, the volume-rendered skeletal images are visually inspected and observed abnormalities are reported for compounds in development. To improve the efficiency and reduce human error of the evaluation, we implemented a framework to automate the evaluation process. The framework starts by dividing the skull into regions of interest and then measuring various geometrical characteristics. Normal/abnormal classification on the bone segments is performed based on identifying statistical outliers. In pilot experiments using rabbit fetal skulls, the majority of the skeletal abnormalities can be detected successfully in this manner. However, there are shape-based abnormalities that are relatively subtle and thereby difficult to identify using the geometrical features. To address this problem, we introduced a model-based approach and applied this strategy on the squamosal bone. We will provide details on this active shape model (ASM) strategy for the identification of squamosal abnormalities and show that this method improved the sensitivity of detecting squamosal-related abnormalities from 0.48 to 0.92.

Automatic pose correction for image-guided nonhuman primate brain surgery planning

Intracranial delivery of recombinant DNA and neurochemical analysis in nonhuman primate (NHP) requires precise targeting of various brain structures via imaging derived coordinates in stereotactic surgeries. To attain targeting precision, the surgical planning needs to be done on preoperative three dimensional (3D) CT and/or MR images, in which the animals head is fixed in a pose identical to the pose during the stereotactic surgery. The matching of the image to the pose in the stereotactic frame can be done manually by detecting key anatomical landmarks on the 3D MR and CT images such as ear canal and ear bar zero position. This is not only time intensive but also prone to error due to the varying initial poses in the images which affects both the landmark detection and rotation estimation. We have introduced a fast, reproducible, and semi-automatic method to detect the stereotactic coordinate system in the image and correct the pose. The method begins with a rigid registration of the subject images to an atlas and proceeds to detect the anatomical landmarks through a sequence of optimization, deformable and multimodal registration algorithms. The results showed similar precision (maximum difference of 1.71 in average in-plane rotation) to a manual pose correction.

Quantification of Cy-5 siRNA signal in the intra-vital multi-photon microscopy images

Transgenic mice with Tie2- green fluorescent protein (GFP) are used as a model to study the kinetic distribution of the Cy5-siRNA delivered by lipid nanoparticles (LNP) into the liver. After the mouse is injected with the LNP, it undergoes a procedure of intra-vital multi-photon microscopy imaging over a period of two hours, during which the process for the nanoparticle to diffuse into the hepatocytes from the vasculature system is monitored. Since the images are obtained in-vivo, the quantification of Cy5 kinetics suffers from the moving field of view (FOV). A method is proposed to register the sequence of images through template matching. Based on the semi-automatic segmentations of the vessels in the common FOV, the registered images are segmented into three regions of interest (ROI) in which the Cy5 signals are quantified. Computation of the percentage signal strength in the ROIs over time allows for the analysis of the diffusion of Cy5-siRNA into the hepatocytes, and helps demonstrate the effectiveness of the Cy5-siRNA delivery vehicle.