TY - JOUR
T1 - Explant Modeling of the Immune Environment of Head and Neck Cancer
AU - Sharon, Shay
AU - Duhen, Thomas
AU - Bambina, Shelly
AU - Baird, Jason
AU - Leidner, Rom
AU - Bell, Bryan
AU - Casap, Nardy
AU - Crittenden, Marka
AU - Vasudevan, Swetha
AU - Jubran, Maria
AU - Kravchenko-Balasha, Nataly
AU - Gough, Michael
N1 - Publisher Copyright:
© Copyright © 2021 Sharon, Duhen, Bambina, Baird, Leidner, Bell, Casap, Crittenden, Vasudevan, Jubran, Kravchenko-Balasha and Gough.
PY - 2021/6/17
Y1 - 2021/6/17
N2 - 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.
AB - 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.
KW - CTLA4
KW - OX40
KW - PD1
KW - cytokine
KW - explant
KW - head and neck cancer
KW - immunotherapy
KW - tumor
UR - http://www.scopus.com/inward/record.url?scp=85109148628&partnerID=8YFLogxK
U2 - 10.3389/fonc.2021.611365
DO - 10.3389/fonc.2021.611365
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AN - SCOPUS:85109148628
SN - 2234-943X
VL - 11
JO - Frontiers in Oncology
JF - Frontiers in Oncology
M1 - 611365
ER -