Precision immunotherapy in human cancer

Over the last years, cancer immunotherapy, i.e. immune checkpoint inhibition (ICI), has truly transformed the therapeutic field in cancer and is now approved for the treatment of many tumor types. Nevertheless, the number of meaningful clinical responses is still rather low. Current available biomarkers do not allow to unambiguously identify patients who do or do not benefit from the therapy, exposing them to ineffective treatment and unnecessary toxicities. In order to improve patient selection and develop more personalized immunotherapy strategies, a better fundamental understanding is needed of how human cancers immunologically respond to treatment and how such responses relate to the immunological makeup of a tumor.

Spatio-temporal immune profiling and ICI response dynamics in human cancers.

It is well-established that tumors which lack a substantial immune infiltrate often also poorly respond to ICI. However, vice versa, the presence of infiltrating immune cells is no guarantee for susceptibility to ICI. This observation has fueled the interest in identifying immune components that are associated with responsiveness. To understand the diversity in immune activity in human cancers and its impact on therapy response, we combine immune profiling (such as by flow cytometry, digital spatial analyses, single-cell sequencing, etc.) with dynamic assays that enable functional analyses of human tumor microenvironments (Figure 1). We developed a human ex vivo tumor model, the patient-derived tumor fragment (PDTF) platform, that maintains cellular composition and spatial organization, but allows perturbation of this complex ecosystem by immunotherapies. Using the PDTF platform, we characterized immunological responses to PD-1 blockade in five different human cancer types and showed that these responses correlate with clinical response (Voabil, de Bruijn, Roelofsen et al, submitted). Further studies are ongoing to elucidate the role of spatial heterogeneity on anti-tumor immunity and to investigate ICI-induced immune responses at single cell level.

Reverse translation and development of precision immunotherapy trials.

ICI has led to spectacular clinical results over the last years, and many more types of immunotherapy drugs or drug combinations are currently in clinical trials and pre-clinical development. However, to select the right patient for the right treatment has proven to be challenging. By using our tumor immune profiling and ex vivo assays, we aim to identify new biomarker candidates indicative of a functional anti-tumor response. As an example, we previously identified a transcriptionally and functionally distinct intratumoral T cell pool, termed PD-1^T T cells that is enriched for tumor reactivity in lung cancer. The presence of PD-1^T T cells in the tumor correlated with clinical response and survival to PD-1 blockade, thus representing a potential biomarker to select patients for this treatment (Thommen et al, Nat Med, 2018). We developed an algorithm-based digital image analysis tool to quantify PD-1^T T cells in pre-treatment biopsies (Figure 2), and the validation of this new biomarker in larger study cohorts is currently ongoing. In addition, we are using the PDTF platform to test new treatment strategies in human tumor tissue samples outside of the patient. The possibility to compare multiple treatments in the same tumor and to directly link treatment responses to baseline tumor properties should provide new insights into response and resistance mechanisms. Moreover, in close collaboration with clinical investigators at NKI, we will use these preclinical analyses to inform the design of new precision immunotherapy trials in preselected patient groups which should contribute to the development of personalized cancer immunotherapy.

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