ABSTRACT
Immune checkpoint blockade (ICB) unleashes immune cells to attack tumors, thereby inducing durable clinical responses in many cancer types. The number of patients responding to ICB is modest, however, and combination treatments are likely needed to overcome the multifaceted suppressive pathways active in the tumor microenvironment (TME). The development of precision immuno-oncology (IO) strategies allowing to identify the optimal treatment of each patient upfront is therefore a pivotal question in the field of cancer immunotherapy. Although single-parameter biomarkers can enrich for response to ICB, their predictive capacity is far from perfect and their clinical utility is complicated by their continuous nature and the difficulty to determine cut-offs that reliably distinguish responding patients from those without clinical benefit. The antitumor immune response that is induced or reinvigorated by immunotherapy is a complex cascade of events requiring the interplay of multiple cell types. To move towards precision IO, it is therefore essential to understand for each individual patient at which level(s) the antitumor immune response failed and how it can be therapeutically restored. Holistic approaches to profile human tumor microenvironments and treatment-induced responses may help to identify critical rate-limiting factors of antitumor immunity. These factors need to be translated into clinically applicable multimodal predictors that allow for the selection of the best IO treatment. This review discusses strategies to (i) create such holistic views of antitumor immunity, (ii) identify measurable parameters capturing the complexity of a patient's immune status, and (iii) facilitate the incorporation of precision IO research in the clinic.
ABSTRACT
BACKGROUND: Cancer immunotherapy elicits functional activation and changes in immune cell distribution in cancer. Tumour heterogeneity is a reason for treatment failure but is difficult to capture in experimental settings. This proof-of-principle study describes the integrated functional and digital spatial profiling platform iPROFILER to capture in-situ immune activation patterns with high precision. MATERIALS AND METHODS: iPROFILER combines an algorithm-based image analysis approach for spatial profiling with functional analyses of patient-derived tumour fragments (PDTFs). This study utilized a folate receptor 1 (FOLR1)xCD3 bispecific antibody in dual-affinity re-targeting (DART) format as a tool for inducing T-cell responses in patient tumour samples, and an in-depth investigation of the immune perturbations induced in the tumour microenvironment was performed. RESULTS: Ex-vivo DART stimulation induces upregulation of multiple activation markers in CD4+ and CD8+ T-cell populations and secretion of pro-inflammatory cytokines in FOLR1-positive tumour specimens. This response was reduced or absent in tissue samples that did not express FOLR1. Immunological responses were driven by a strong induction of interferon gamma (IFNγ) and IFNγ-induced chemokines suggestive of activation of cytotoxic or Th1-like T cells. Ex-vivo DART treatment led to a numerical increase in effector T cells and an upregulation of immune activation markers in the tumour microenvironment as captured by digital image analysis. Analysis of immune activation in tumour and stromal regions further supported the potential of the platform to measure local differences in cell-type-specific activation patterns. CONCLUSIONS: iPROFILER effectively combines functional and spatial readouts to investigate immune responses ex vivo in human tumour samples.
