- Poster presentation
- Open Access
Computational discovery and experimental validation of novel drug targets in immuno-oncology
© Levy et al. 2015
- Published: 4 November 2015
- Experimental Data
- Predictive Model
- Drug Target
- Therapeutic Potential
- Experimental Validation
The past few years have witnessed a renaissance in the field of immuno-oncology largely due to the clinical success in targeting the immune checkpoints CTLA-4 and PD-1. Towards identification of novel immune checkpoint drug targets we developed a dedicated predictive discovery platform.
The B7/CD28 discovery platform is a predictive model based on genomic and protein features along with expression patterns of known B7/CD28 proteins. The platform has been tested and validated extensively and has demonstrated its validity by identifying non-novel immune checkpoints such as TIGIT and VISTA, which were not used in the design stage.
The B7/CD28 predictive platform was employed to identify several novel immune checkpoint candidates which are currently in different validation stages. In this poster, we will describe our discovery approach as well as our validation path. In addition, we will present experimental data demonstrating the immuno-modulatory function and expression patterns of several of our novel immune checkpoints. These experimental results serve as an additional confirmation to the accuracy of our B7/CD28 predictive discovery platform and shed light on the therapeutic potential of the novel immune checkpoints identified using this unique discovery approach.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.