Temporally restricted activation of IFNß signaling underlies response to immune checkpoint therapy in mice.

The biological determinants of the response to immune checkpoint blockade (ICB) in cancer remain incompletely understood. Little is known about dynamic biological events that underpin therapeutic efficacy due to the inability to frequently sample tumours in patients. Here, we map the transcriptional profiles of 144 responding and non-responding tumours within two mouse models at four time points during ICB. We find that responding tumours display on/fast-off kinetics of type-I-interferon (IFN) signaling. Phenocopying of this kinetics using time-dependent sequential dosing of recombinant IFNs and neutralizing antibodies markedly improves ICB efficacy, but only when IFNß is targeted, not IFNα. We identify Ly6C+/CD11b+ inflammatory monocytes as the primary source of IFNß and find that active type-I-IFN signaling in tumour-infiltrating inflammatory monocytes is associated with T cell expansion in patients treated with ICB. Together, our results suggest that on/fast-off modulation of IFNß signaling is critical to the therapeutic response to ICB, which can be exploited to drive clinical outcomes towards response.

Bilateral murine tumor models for characterizing the response to immune checkpoint blockade.

The therapeutic response to immune checkpoint blockade (ICB) is highly variable, not only between different cancers but also between patients with the same cancer type. The biological mechanisms underlying these differences in response are incompletely understood. Identifying correlates in patient tumor samples is challenging because of genetic and environmental variability. Murine studies usually compare different tumor models or treatments, introducing potential confounding variables. This protocol describes bilateral murine tumor models, derived from syngeneic cancer cell lines, that display a symmetrical yet dichotomous response to ICB. These models enable detailed analysis of whole tumors in a highly homogeneous background, combined with knowledge of the therapeutic outcome within a few weeks, and could potentially be used for mechanistic studies using other (immuno-)therapies. We discuss key considerations and describe how to use two cell lines as fully optimized models. We discuss experimental details, including proper inoculation technique to achieve symmetry and one-sided surgical tumor removal, which takes only 5 min per mouse. Furthermore, we outline the preparation of bulk tissue or single-cell suspensions for downstream analyses such as bulk RNA-seq, immunohistochemistry, single-cell RNA-seq and flow cytometry.

Sensitization to immune checkpoint blockade through activation of a STAT1/NK axis in the tumor microenvironment.

Cancer immunotherapy using antibodies that target immune checkpoints has delivered outstanding results. However, responses only occur in a subset of patients, and it is not fully understood what biological processes determine an effective outcome. This lack of understanding hinders the development of rational combination treatments. We set out to define the pretreatment microenvironment associated with an effective outcome by using the fact that inbred mouse strains bearing monoclonal cancer cell line-derived tumors respond in a dichotomous manner to immune checkpoint blockade (ICB). We compared the cellular composition and gene expression profiles of responsive and nonresponsive tumors from mice before ICB and validated the findings in cohorts of patients with cancer treated with ICB antibodies. We found that responsive tumors were characterized by an inflammatory gene expression signature consistent with up-regulation of signal transducer and activator of transcription 1 (STAT1) and Toll-like receptor 3 (TLR3) signaling and down-regulation of interleukin-10 (IL-10) signaling. In addition, responsive tumors had more infiltrating-activated natural killer (NK) cells, which were necessary for response. Pretreatment of mice with large established tumors using the STAT1-activating cytokine interferon-γ (IFNγ), the TLR3 ligand poly(I:C), and an anti-IL-10 antibody sensitized tumors to ICB by attracting IFNγ-producing NK cells into the tumor, resulting in increased cure rates. Our results identify a pretreatment tumor microenvironment that predicts response to ICB, which can be therapeutically attained. These data suggest a biomarker-driven approach to patient management to establish whether a patient would benefit from treatment with sensitizing therapeutics before ICB.