CAR T cell therapy has changed the outlook for many blood cancers, but its promise in solid tumors remains largely unrealized. The barriers are steep: elusive targets, poor cell trafficking, and an aggressively immunosuppressive tumour microenvironment. Overcoming these challenges will require a deeper molecular understanding of CAR T function – and this is where analytical science is beginning to play a pivotal role. Mass spectrometry and proteomics are providing detailed insights into CAR design, target biology, and the complex cell states that determine therapeutic success or failure.
This interview is the first in a new series exploring how analytical science is shaping the future of cell therapies. Here, Joey Sheff of the National Research Council Canada discusses how his team is deploying advanced analytics to guide CAR T development – and why this data-driven approach could be key to conquering solid tumors.
What is the current state of CAR T cell therapy development?
Chimeric Antigen Receptor T-cell (CAR T) therapies, where an individual’s own T-cells are engineered to recognize and kill specific cancer cells, are rapidly emerging as powerful anti-cancer therapies. As it stands, there are currently seven approved therapies for hematological cancers along with hundreds of ongoing clinical trials. Excitingly, the first CAR T therapy for the treatment of solid tumours has been approved. These successes are enabled by significant momentum in the design of the CARs themselves, novel modes of CAR T delivery, and manufacturability. Finally, the applications of CAR T cell therapy are expanding beyond cancer, such as the treatment of autoimmune diseases or infections. All told, the field is poised for significant growth in the coming years.
What are some of the biggest scientific or technical challenges in advancing CAR T therapies for solid tumors?
Hematological cancers offer a sort of “goldilocks” environment for cell therapies. They harbor cell-surface targets that are exclusive to blood cancers, and malignant cells are readily accessible in the blood, and a setting that supports CAR T proliferation and activity. Solid cancers flip this paradigm on its head. CAR T cells often can’t survive, proliferate or kill within the tumour microenvironment, and cell trafficking and infiltration are limited by physical barriers. Further, unlike hematological cancers, they lack targets that are exclusive to cancer cells. As if this wasn’t enough, the tumour microenvironment is inherently immunosuppressive, which often results in T-cell exhaustion and death.
How can analytical science – and mass spectrometry and proteomics in particular – support the development of more effective and reliable CAR T therapies?
Mass spectrometry has an important role to play across all stages of CAR T development. In the discovery phase, proteomics enables cell surface target identification and validation with a sensitivity and flexibility that is unmatched by other technologies. This is going to be particularly valuable as the focus shifts from hematological to difficult-to-access solid tumours. Once a target is identified, mass spectrometry has the power to guide and enhance the development of therapies by providing readouts across all facets of the CAR T cells. At the level of the CAR itself, mass spectrometry-based analytics offer the ability to structurally characterize the antibodies that mediate cancer cell recognition and CAR activation. This informs on the manufacturability, integrity of candidate antibodies, and can inform the selection of candidates for integration into a CAR. By the same token, epitope mapping by mass spectrometry is a valuable tool to guide the selection of antibodies. For example, it may be useful to know if the epitope that you are targeting is membrane proximal or distal, or if it is even accessible in a cellular context, in order to fine tune CAR T activity.
Once a panel of candidate CAR T cells have been generated, proteomics analyses can be deployed to evaluate the dynamic cellular responses resulting from cell surface CAR expression/activation. Phosphoproteomics or cell-surface proteomics, for example, allow for comparisons of the unique cellular environments across multiple CAR constructs. When combined with functional readouts or therapeutic activity, these findings can be related to therapeutic outcomes to better predict the clinical efficacy of CAR T candidates.
Could you walk us through your own work in this area?
Mywork in this area focuses on using analytics to better understand and predict the function of CAR T therapies. We accomplish this through a multi-pronged mass spectrometry approach. First, we use a suite of complementary protein labelling strategies, namely hydrogen exchange and cross-linking mass spectrometry, to answer the question: how is my antibody binding to its target? The main objective here is to map the epitopes of candidate antibodies, and relate these findings to complementary functional assays. The spatial orientation of a bound antibody, or the strength of its binding can all drastically impact the therapeutic success of a CAR T therapy. Therefore, this layer of information is crucial for guiding the design of the CAR construct, as well as downstream engineering of the antibody/antigen interaction. Second, we deploy proximity labeling techniques to dig into and compare the local environment of a cell surface CAR. We are always looking to find out how the structure of a CAR influences the downstream cellular pathways that are engaged during CAR T proliferation and activation. Using the knowledge uncovered about these fundamental pathways, we aim to identify novel avenues for CAR receptor design to improve survivability, activity and toxicity profiles. In addition, this work has the potential to discover novel biomarkers for predicting CAR T activity, which we ultimately aim to incorporate into CAR design and development stages in order to improve the likelihood of therapeutic success.
What are the biggest analytical challenges that still need to be addressed to fully support CAR T development?
Mass spectrometers are becoming faster and more sensitive at an impressive rate. That said, there is a need for software platforms that allow for deeper mining of proteomics of the incredibly rich datasets that are being collected by the most sophisticated instruments. AI and machine learning has a role to play here, particularly when it comes to integrating multiomics datasets, and deciphering hidden patterns and trends within these incredibly complex datasets.
Further, there is a need to develop workflows that enable in process analytics for quality control during the manufacturing and production stage of cell therapies. What’s needed are rapid, targeted, and sensitive protocols that can reliably sample the complexity and heterogeneity of cell therapies.
How significant a role could analytical science play in shaping the future of cell therapies?
I think there is vast untapped potential for analytics to drive cell therapy development. For example, the ability to proteomics profiles of single cells, enabled by state-of-the-art sample handling protocols and ultra-sensitive instruments, will allow for unprecedented insights into heterogeneous protein expression in both CAR T cells (CAR expression) and cancer cells (antigen expression). Further, it will be the role of increasingly powerful proteomics platforms to unveil key cellular pathways that are fundamental to CAR T function, identify novel druggable targets, and profile engineered CAR T cells for biomarkers for product quality for tracking either with mass spectrometry or other, more streamlined analytical approaches. By combining functional datasets with the knowledge of which protein pathways correlate with strong proliferation, high therapeutic activity, and low toxicity (much more research is required here!) it may be possible to predict the therapeutic efficacy of patient-derived cell therapies.
Looking ahead, what do you see as the most exciting developments on the horizon for CAR T therapies over the next 5 to 10 years?
First and foremost, I am enthusiastic for the growth of made-in-Canada CAR T products, for which scientists at the NRC are playing a key role in collaboration with many Canadian and international partners. The recent success of cell therapy in solid tumors is promising, and I believe analytics will play a significant role in advancing these therapies, particularly for target identification and validation. In terms of analytics, I foresee a significant role of single-cell and deep-proteomics in driving the growth of patient-specific cell therapy deployment. And finally, I am looking forward to the advancement of off-the-shelf, universal cell therapies which will be integral to ensure widespread accessibility to these incredibly powerful therapies.
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