ACE ImmunoID Platform for Reverse Translation
Laboratory models have been central to the fast evolving field of immuno-oncology and immunotherapy drug development. We continue to learn from in vitro cell cultures, animal models, patient-derived xenografts (PDX), organoids, and other highly sophisticated engineered systems. Indeed, evidence from murine experimental designs and pre-clinical studies successfully identified immune checkpoint inhibitory receptors as key players allowing tumors to prosper in an immunosuppressed environment. The first reported receptor shown to exhibit immune inhibitory functions was CTLA-4. Subsequently, evidence arising from murine studies modeling different cancer types supports blockade of CTLA-4 enough to warrant translation to the clinic. This has paved the way for discovery of PD1 immune checkpoint inhibitory receptor and the increased number of human PD1 antibody designs available today. Collectively, CTLA-4 and PD1 antibodies have dominated the world of immunotherapy for years, having also received FDA approvals for multiple indications at an unprecedented rate. However, while we can cure cancer in mice in many experimental settings, there remains lack of sufficient clinical drug response in humans. Despite having transformed the field of immunotherapy and many patients’ lives, successful treatment with immune checkpoint agents is limited to a small patient population that hovers around 15-20%.
How can clinical benefit extend further to the remaining 80%? The answer, albeit convoluted, might very well reside in reverse translation from human clinical samples.
There is agreement that laboratory model systems do not recapitulate the true biology of tumors in humans. In the context of immunotherapy, there is also consensus these models alone cannot fully elucidate the heterogeneity of resistance biology in a patient population, nor fully explain tumor-host dynamics, the complexity of the tumor microenvironment, and the multi-layered human immune response.
Immune checkpoint inhibitors are at the core of over a thousand clinical trials as monotherapy or in combination with other therapeutic approaches. As is the case with clinical trials, there is a wide margin of failure and therapeutics missing clinical trial phase III goals. This is partly because pre-clinical evidence of success generated in murine models does not coincide well with diverse patient populations. For this reason, biospecimens from successful and failed clinical trials are a valuable resource of information worth exploring. These clinical samples could provide a better understanding of cancer:immune system interaction, why some patients respond better than others, and why some patients don’t respond at all to immune checkpoint blockade. Many pharmaceutical companies are eager to leverage these biobanks for the discovery of new mechanisms of resistance to immunotherapy, identification of predictive biomarkers, improved patient stratification, design of mechanism-driven clinical trials and combinations, and measuring other factors impacting the success rate of their therapeutic approach. Often times we hear it is very cumbersome to consolidate data from multiple assays. Investigators send aliquots of one clinical sample to multiple sources for specialized testing and study each result in isolation. This creates additional hurdles for integration of results and making sense of the data. The cost of assaying hundreds and thousands of clinical samples can also be prohibitive.
Personalis ACE ImmunoID offers a comprehensive platform founded on the ACE Technology that helps answer multiple questions from one harmonized dataset. The platform is configured to explore the tumor as well as the immune compartment through insightful immunogenomics analytics derived from next generation sequencing of DNA and RNA simultaneously extracted from a single sample.
ACE ImmunoID platform analytics include:
• DNA Tumor mutational burden and list of somatic variants
• RNA Tumor mutational burden and expressed somatic variants
• Gene expression and fusion events
• Neoantigen load and characterization of peptides based on MHC binding affinity, expression, immunogenicity, similarity to self, and similarity to known antigens
• ImmunoGenomics profile based on key gene signatures including immune modulators, antigen processing machinery, DNA repair and replication, tumor associated antigens, chemokines and cytokines
Our goal is to enable and streamline reverse translational research from large cohorts of clinical trial samples from multiple trials to support immunotherapy drug development. In addition to analytically validated assays and informatics, Personalis has also implemented automated laboratory processes and significantly scaled operations with acquisition of NovaSeq instruments. Together, these elements place Personalis in a unique position to help drive the transformational immunotherapies being developed today.
Read more about our Biomarker Discovery Solutions.