Given that antibody dependent cell mediated cytotoxicity (ADCC) and phagocytosis (ADCP) are thought to be the major mechanisms of action of Rituximab (R), increasing the activation levels of natural killer (NK) and macrophage (MP) cells may be one strategy for overcoming R resistance. We have developed and calibrated to ex-vivo literature data a quantitative systems pharmacology (QSP) model of ADCC/ADCP to interrogate which mechanisms of R resistance could be overcome by increased NK or MP activation, and how much effector cell activation would be required to overcome a given degree and mechanism of R resistance. This ADCC/ADCP model was then incorporated into an in-house QSP model built with ex-vivo and clinical data to support the development of a Takeda investigational drug which is being developed to restore R sensitivity in an R-resistant patient population.

Most preclinical in vivo efficacy models supporting drug discovery and development in immuno-oncology have not been proven to be translationally predictive. Successfully treating a preclinical immuno-oncology model does not predict for success in the clinic, in contrast to the situation for traditional oncology. This lack of translational relevance represents a significant (and often underappreciated) challenge for drug development in this field. In the absence of translational efficacy models, how do you rationally plan and execute a preclinical-to-clinical translation strategy? In this talk, we will discuss how to make that happen, relying in particular on ex vivo assays using human whole blood, PK/PD modeling for markers that are directly downstream of drug action (such as target occupancy), and Bayesian trial design approaches. This talk, which provides practical guidance for drug developers in immuno-oncology, will help attendees in the design of robust science-driven strategies for establishing clinical proof of concept for their assets.

The implantable microdevice (IMD) is a translational tool that allows us to systematically screen many individual and combination therapies in a small cohort of study animals.

This session explains how IMDs work, and how we use them to facilitate the collection of robust data for numerous applications, including: 

• Combination screening
• Testing of compounds that have no PK or toxicology data
• Candidate comparison
• Specific biology, e.g., candidate interaction with TME
• Clinical translation

We have developed syngeneic, engineered mouse lines which, when implanted into the left ventricle, result in disseminated metastases that can be visualized by bioluminescent imaging at very early stages of establishment. This model can be used in testing efficacy of immune therapies targeting metastatic tumors. In combination with sub-cutaneously implanted non-luminescent tumor cell line counterpart, we have successfully demonstrated treatment of primary tumor with experimental immune therapy agents resulting in abscopal effects on deep-seated metastases. We have also developed an in vitro patient-derived explant (PDE) model preserving the tumor immune microenvironment including the infiltrating immune cells in a viable and functional state for greater than a month. We have successfully demonstrated proof of concept and observe complete elimination of tumor cells following in vitro treatment with an immune checkpoint inhibitor. This platform could also eventually be used to perform real time multiplexed testing to enable personalized immuno-oncology therapy.

Anti-BCMA bispecific antibodies are very effective against relapse/refractory myeloma. However, patients inevitably relapse. Using the immunocompetent Vk*MYC mouse model of myeloma, we found that tumor burden and T cell exhaustion limit the efficacy of anti-BCMA/CD3 antibody. The addition of an IMiD only transiently deepened the response, but further exacerbated T cell exhaustion. Surprisingly, concurrent treatment with anti-BCMA/CD3 and cyclophosphamide proved very effective, prevented exhaustion and provided immunological protection against tumor reoccurrence.

Dr. Ptacek will provide an overview of how high-definition spatial proteomics, enabled by Multiplexed Ion Beam Imaging (MIBI), can be used to explore the tumor microenvironment with unprecedented depth. Examples of quantitative single-cell phenotype mapping in tissue analysis applications and the ability to generate actionable insights from this highly multiplexed, spatial proteomic data will be presented.

Current therapies, including conventional chemotherapy, targeted therapy, and immune therapy are typically tested in different types of preclinical models. Chemotherapy and targeted therapy are often analyzed using cancer cell lines and xenografts, patient-derived xenografts and more recently, patient-derived organoids. These models have the genetics of the human disease but lack a functional immune system/tumor microenvironment (TME). Immune-therapies have been tested primarily in "syngeneic tumor models" of unclear cell-of-origin and "irrelevant" genetics. Using mouse fallopian tube organoids, we engineered a suite of new, genetically defined models of high-grade serous ovarian cancer. I will discuss the use of these models to derive new combination therapies for this deadly disease.

3D human tissue organoids replicate native tissue structure and function and can be studied in vitro for several weeks to allow intensive investigations. We have used human tissue organoids to study cancer progression, metastasis and response to therapy. Patient-specific tumor organoids, consisting of tumor and stromal cells could replicate the patient’s own treatment response. We have recently improved the tumor organoids’ capabilities by adding immune cells to create immune-responsive tumor organoids.

Preclinical models that translate to human immunity are needed to assess novel cancer immunotherapy combinations. New approaches and model systems are needed to deprioritize ineffective strategies and to better understand mechanisms of response and resistance to promising approaches. To address this need, we have developed a system for ex vivo profiling of novel immunotherapy combinations using 3D microfluidic culture of murine- and patient-derived organotypic tumor spheroids (MDOTS/PDOTS). 

Innovative immuno-oncology therapeutics require focus on various underexplored mechanisms in the cancer immunity cycle. We are building a framework to identify the key determinant mechanisms and parameters that can be used to link patients with therapies. Allogeneic cell therapy platforms will be discussed in this context as an example with application to other therapeutic approaches. Attributes regarding patient population, cell platform, targets, and armoring options are taken into account.

CRISPR-Cas9 cell engineering is making great strides in driving novel immuno-medicines to the clinic. This talk will focus on how this technology is uncovering the mechanisms of immune resistance to checkpoint therapies and identifying next-generation IO targets and modalities.

Since PD-1 and GITR are co-expressed on recently activated antigen-specific T cells and on memory cells, a bispecific that targets both specificities is warranted. Anti-PD-1-GITR-L is a bispecific molecule that overcomes immune escape to PD-(L)1 blockade by enhancing and sustaining the activation, proliferation, and memory differentiation of primed antigen-specific T cells by inducing a PD-1 mediated GITR clustering. The MoA is independent of FcγR-mediated cross-linking, and ADCC-mediated Treg depletion.

Cancer cells evade clearance by macrophages through the overexpression of anti-phagocytic surface proteins called ‘don’t eat me’ signals. Here we report that CD24 is the dominant ‘don’t eat me’ signal in multiple solid tumors. In preclinical models, CD24 blockade leads to a macrophage-dependent reduction in tumor growth and extension of survival. Collectively, these data support the therapeutic potential for targeting CD24, and demonstrate the importance of assessing the global expression of innate immune checkpoints in order to inform therapeutic strategies with broad, durable responses.