Year: 2021
Type: review
Abstract: Immunotherapy has revolutionised cancer treatment through restoration of host antitumour immune response. Immune checkpoint inhibitors (ICIs) confer durable responses in only a subset of patients. Mechanisms of ICI resistance to improve durable response rates and overall survival are an area of intense clinical research. Robust clinical development is ongoing to evaluate novel combination therapies to overcome ICI resistance, including targeting immunoregulatory pathways in the tumour microenvironment. Intratumoural (IT) immunotherapies such as toll-like receptor agonists, stimulator of interferon-induced gene agonists, retinoic-inducible gene I-like receptor agonists and oncolytic viruses may represent potential combination treatment options to overcome ICI resistance. Use of IT immunotherapies in combination with ICIs may alter the tumour microenvironment to address resistance mechanisms and improve antitumour response. Optimisation of IT immunotherapy clinical trials will elucidate resistance mechanisms, facilitate clinical trial design, define pharmacodynamic predictors that identify patients who may most benefit and inform clinical development of combination immunotherapy regimens. Here we provide an overview of IT immunotherapy principles, mechanisms of action, categories of IT immunotherapeutics, emerging data, clinical development strategies, response assessment, dose and schedule determination, clinical trial design and translational study design.
Source: European Journal of Cancer
Institutions: Merck & Co., Inc., Rahway, NJ, USA (United States), Icahn School of Medicine at Mount Sinai, University of Utah, Huntsman Cancer Institute, University of Pittsburgh, UPMC Hillman Cancer Center, The University of Texas MD Anderson Cancer Center, Université Paris-Saclay, Institut Gustave Roussy, Dana-Farber Cancer Institute, Dana-Farber/Harvard Cancer Center
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,800
OpenAlex ID: W3199310824
