Immune checkpoints are inhibitory proteins of the immune system that are crucial for controlling the duration and magnitude of the immune responses. These proteins are the key to minimizing collateral tissue damage during an immune response. Novel members of this class may be utilized as targets for cancer immunotherapy and as a basis for immunomodulatory therapeutics for autoimmune diseases.
Recently, the blockade of the immune checkpoints CTLA4 and PD-1 emerged as “game changers” in cancer therapy, leading to durable clinical responses in patients with advanced melanoma, lung and kidney cancers, thus forming the foundation for a new era of cancer immunotherapy. However, many patients and many types of cancers do not respond to these treatments, indicating that there are additional immune evasion mechanisms, mediated by unknown members of this protein family.
As this protein family shares very low sequence similarity, traditional sequence similarity analysis approaches are not effective. Therefore, our discovery platform was designed to specifically address this challenge by developing specialized algorithms designed to identify a set of the unique characteristics of this protein family at genomic and protein levels as well as unique gene expression profiles.
Our platform predicted multiple novel proteins as possible additional members of the B7/CD28 family. Our findings included, among others, the non-novel candidates VISTA and also TIGIT, for which two other groups published scientific papers disclosing the same immune checkpoint during 2009, the same year in which we published our experimental validation work on TIGIT (see Compugen’s PNAS publication from October 2009 titled “The interaction of TIGIT with PVR and PVRL2 inhibits human NK cell cytotoxicity”). These examples provided a strong validation of the predictive power of the model. Among this group of predicted novel immune checkpoints was also CGEN-15029/PVRIG. In 2016, we disclosed experimental validation of CGEN-15029/PVRIG, showing not only that it is a member of the B7/CD28 family but also linking it to the TIGIT pathway. CGEN-15029/PVRIG was chosen as our lead drug candidate, which is undergoing IND-enabling studies. Two other targets that were identified by our model are CGEN-15001T and CGEN-15022, which are the focus of our collaboration with Bayer.
Immunomodulatory proteins are proteins capable of modifying or regulating one or more immune functions. Immune checkpoints, including inhibitory receptors and ligands, are one type of immunomodulators.
The immunomodulatory platform models two distinct biological phenomena related to the role of the immune system that are conceptually different from those employed in the discovery of Compugen’s B7/CD28-like candidates.
The first biological phenomenon that was modeled exploits the interplay between the immune system and intruding pathogens. As a result of such interplay, some immune proteins tend to evolve differently. Compugen devised an evolutionary model to detect such immune proteins, and the predictive algorithm was incorporated into Compugen’s discovery infrastructure and integrated with its existing tools for the discovery of target candidates for cancer immunotherapy.
The modeling of the second biological phenomenon relies heavily on the Company’s MED Platform, which was employed to predict proteins that play a role in the biology of tumor-associated macrophages (TAMs).
TAMs are an important component of the tumor microenvironment and play a major role in creating the immunosuppressive environment that enables tumor development. Proteins having the potential to modulate the tumor microenvironment may serve as potential targets for cancer immunotherapy.
Myeloid biology is a critical component of immune suppression, and is an emerging and promising area within the field of immuno-oncology, with only a few known therapeutic targets. The myeloid lineage of the immune system includes macrophages, immune cells that are highly immune suppressive in the tumor microenvironment, and that can affect the anti-tumor immune response via multiple mechanisms-of-action. Myeloid immune checkpoint inhibition offers potential for efficacy in patients with cancers possessing a strong immune suppressive environment or that are refractory to available immune checkpoint inhibitors. Therefore, we have extended our predictive target discovery capabilities into myeloid biology, and have identified myeloid target candidates within tumor the microenvironment of multiple cancers. These can include both monotherapy and combination therapy, potentially with the combined use of other of candidates with our pipeline, thus providing the opportunity for multiple differentiated treatment options.