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Oral Surg Oral Med Oral Pathol Oral Radiol. 2017 Aug;124(2):157-164. doi: 10.1016/j.oooo.2017.05.474. Epub 2017 May 25.

Cell genomics and immunosuppressive biomarker expression influence PD-L1 immunotherapy treatment responses in HNSCC-a computational study.

Author information

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.

PMID:
28756882
PMCID:
PMC5539917
DOI:
10.1016/j.oooo.2017.05.474
[Indexed for MEDLINE]
Free PMC Article

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