Explant Modeling of the Immune Environment of Head and Neck Cancer

Abstract

Patients exhibit distinct responses to immunotherapies that are thought to be linked to their tumor immune environment. However, wide variations in outcomes are also observed in patients with matched baseline tumor environments, indicating that the biological response to treatment is not currently predictable using a snapshot analysis. To investigate the relationship between the immune environment of tumors and the biological response to immunotherapies, we characterized four murine head and neck squamous cell carcinoma (HNSCC) models on two genetic backgrounds. Using tumor explants from those models, we identified correlations between the composition of infiltrating immune cells and baseline cytokine profiles prior to treatment. Following treatment with PD-1 blockade, CTLA-4 blockade, or OX40 stimulation, we observed inter-individual variability in the response to therapy between genetically identical animals bearing the same tumor. These distinct biological responses to treatment were not linked to the initial tumor immune environment, meaning that outcome would not be predictable from a baseline analysis of the tumor infiltrates. We similarly performed the explant assay on patient HNSCC tumors and found significant variability between the baseline environment of the tumors and their response to therapy. We propose that tumor explants provide a rapid biological assay to assess response to candidate immunotherapies that may allow matching therapies to individual patient tumors. Further development of explant approaches may allow screening and monitoring of treatment responses in HNSCC.

3D tumor explant as a novel platform to investigate therapeutic pathways and predictive biomarkers in cancer patients

“…In this setting, the secretion of cyto/chemokines, along with T cell activation levels measured in a PDE model of patient-derived tumor fragments (PDTF) from different tumor types embedded into an artificial extracellular matrix, could predict clinical response to PD-1 blockade ( 22 ). Similar observations were recorded following PD-1 inhibition in explant cultures of head and neck cancer, gastric and gastroesophageal adenocarcinoma ( 23 , 24 ). Importantly, the PDTF platform can be also applied to identify suitable neoadjuvant treatment strategies in patients with early-stage cancer, as recently described for anti-CTLA-4 plus anti-PD-1 combined with IL-2 in PDE of checkpoint inhibitor-resistant melanoma patients ( 25 ).…”

The paradox of radiation and T cells in tumors

“… [51] In this way, advanced immune monitoring can identify patients who are responding to treatment. However, this could also be used to idenitfy alternative treatment options for those who fail to respond, for example using tumor explants to identify agents that can make beneficial changes in the patient tumor, [52 , 53] or to identify additional therapies that may redirect outcomes in recalcitrant tumors. [54] …”

Fluorescence tracking demonstrates T cell recirculation is transiently impaired by radiation therapy to the tumor

“…2bi). Since Moc2 tumors are known to have a very limited infiltration of CD8 T cells into the tumor environment 19,20 and they have a very limited number of photoconverted cells moving from the tumor to the TdLN, we investigated whether the number of photoconverted CD8 cells in the TdLN was directly linked to the number of CD8 T cells in the tumor. By comparing the percentage of CD8 T cells in the tumor to the photoconverted CD8 T cells in the TdLN, we see a direct relationship between these proportions (Fig.…”