Amber M Bates1, Emily A Lanzel2, Fang Qian3, Taher Abbasi4, Shireen Vali4, Kim A Brogden5. 1. Iowa Institute for Oral Health Research, College of Dentistry, University of Iowa, Iowa City, IA, USA. 2. Department of Oral Pathology, Radiology and Medicine, College of Dentistry, University of Iowa, Iowa City, IA, USA. 3. Iowa Institute for Oral Health Research, College of Dentistry, University of Iowa, Iowa City, IA, USA; Division of Biostatistics and Research Design, College of Dentistry, University of Iowa, Iowa City, IA, USA. 4. Cellworks Group, Inc., San Jose, CA, USA. 5. Iowa Institute for Oral Health Research, College of Dentistry, University of Iowa, Iowa City, IA, USA. Electronic address: Kim-brogden@uiowa.edu.
Abstract
OBJECTIVES: Programmed death-ligand 1 (PD-L1) expression is correlated with objective response rates to PD-1 and PD-L1 immunotherapies. However, both immunotherapies have only demonstrated 12%-24.8% objective response rates in patients with head and neck squamous cell carcinoma (HNSCC), demonstrating a need for a more accurate method to identify those who will respond before their therapy. Immunohistochemistry to detect PD-L1 reactivity in tumors can be challenging, and additional methods are needed to predict and confirm PD-L1 expression. Here, we hypothesized that HNSCC tumor cell genomics influences cell signaling and downstream effects on immunosuppressive biomarkers and that these profiles can predict patient clinical responses. STUDY DESIGN: We identified deleterious gene mutations in SCC4, SCC15, and SCC25 and created cell line-specific predictive computational simulation models. The expression of 24 immunosuppressive biomarkers were then predicted and used to sort cell lines into those that would respond to PD-L1 immunotherapy and those that would not. RESULTS: SCC15 and SCC25 were identified as cell lines that would respond to PD-L1 immunotherapy treatment and SCC4 was identified as a cell line that would not likely respond to PD-L1 immunotherapy treatment. CONCLUSIONS: This approach, when applied to HNSCC cells, has the ability to predict PD-L1 expression and predict PD-1- or PD-L1-targeted treatment responses in these patients.
OBJECTIVES:Programmed death-ligand 1 (PD-L1) expression is correlated with objective response rates to PD-1 and PD-L1 immunotherapies. However, both immunotherapies have only demonstrated 12%-24.8% objective response rates in patients with head and neck squamous cell carcinoma (HNSCC), demonstrating a need for a more accurate method to identify those who will respond before their therapy. Immunohistochemistry to detect PD-L1 reactivity in tumors can be challenging, and additional methods are needed to predict and confirm PD-L1 expression. Here, we hypothesized that HNSCC tumor cell genomics influences cell signaling and downstream effects on immunosuppressive biomarkers and that these profiles can predict patient clinical responses. STUDY DESIGN: We identified deleterious gene mutations in SCC4, SCC15, and SCC25 and created cell line-specific predictive computational simulation models. The expression of 24 immunosuppressive biomarkers were then predicted and used to sort cell lines into those that would respond to PD-L1 immunotherapy and those that would not. RESULTS: SCC15 and SCC25 were identified as cell lines that would respond to PD-L1 immunotherapy treatment and SCC4 was identified as a cell line that would not likely respond to PD-L1 immunotherapy treatment. CONCLUSIONS: This approach, when applied to HNSCC cells, has the ability to predict PD-L1 expression and predict PD-1- or PD-L1-targeted treatment responses in these patients.
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