Predicting PD-L1 expression on human cancer cells using next-generation sequencing information in computational simulation models

Emily A Lanzel; M Paula Gomez Hernandez; Amber M Bates; Christopher N Treinen; Emily E Starman; Carol L Fischer; Deepak Parashar; Janet M Guthmiller; Georgia K Johnson; Taher Abbasi; Shireen Vali; Kim A Brogden

doi:10.1007/s00262-016-1907-5

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Predicting PD-L1 expression on human cancer cells using next-generation sequencing information in computational simulation models

Journal article

Peer reviewed

Predicting PD-L1 expression on human cancer cells using next-generation sequencing information in computational simulation models

Emily A Lanzel, M Paula Gomez Hernandez, Amber M Bates, Christopher N Treinen, Emily E Starman, Carol L Fischer, Deepak Parashar, Janet M Guthmiller, Georgia K Johnson, Taher Abbasi, …

Cancer immunology, immunotherapy, Vol.65(12), pp.1511-1522

12/2016

DOI: 10.1007/s00262-016-1907-5

PMCID: PMC5394567

PMID: 27688163

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Abstract

Interaction of the programmed death-1 (PD-1) co-receptor on T cells with the programmed death-ligand 1 (PD-L1) on tumor cells can lead to immunosuppression, a key event in the pathogenesis of many tumors. Thus, determining the amount of PD-L1 in tumors by immunohistochemistry (IHC) is important as both a diagnostic aid and a clinical predictor of immunotherapy treatment success. Because IHC reactivity can vary, we developed computational simulation models to accurately predict PD-L1 expression as a complementary assay to affirm IHC reactivity. Multiple myeloma (MM) and oral squamous cell carcinoma (SCC) cell lines were modeled as examples of our approach. Non-transformed cell models were first simulated to establish non-tumorigenic control baselines. Cell line genomic aberration profiles, from next-generation sequencing (NGS) information for MM.1S, U266B1, SCC4, SCC15, and SCC25 cell lines, were introduced into the workflow to create cancer cell line-specific simulation models. Percentage changes of PD-L1 expression with respect to control baselines were determined and verified against observed PD-L1 expression by ELISA, IHC, and flow cytometry on the same cells grown in culture. The observed PD-L1 expression matched the predicted PD-L1 expression for MM.1S, U266B1, SCC4, SCC15, and SCC25 cell lines and clearly demonstrated that cell genomics play an integral role by influencing cell signaling and downstream effects on PD-L1 expression. This concept can easily be extended to cancer patient cells where an accurate method to predict PD-L1 expression would affirm IHC results and improve its potential as a biomarker and a clinical predictor of treatment success.

Carcinoma, Squamous Cell - genetics

Carcinoma, Squamous Cell - pathology

Humans

Middle Aged

Molecular Dynamics Simulation

B7-H1 Antigen - metabolism

Multiple Myeloma - pathology

Models, Biological

Computer Simulation

Mouth Neoplasms - pathology

Adult

Mouth Neoplasms - genetics

Multiple Myeloma - genetics

Details

Title: Subtitle: Predicting PD-L1 expression on human cancer cells using next-generation sequencing information in computational simulation models
Creators: Emily A Lanzel - Department of Oral Pathology, Radiology and Medicine, College of Dentistry, University of Iowa, Iowa City, IA, USA
M Paula Gomez Hernandez - Iowa Institute for Oral Health Research, N423 DSB, College of Dentistry, The University of Iowa, 801 Newton Road, Iowa City, IA, 52242, USA
Amber M Bates - Iowa Institute for Oral Health Research, N423 DSB, College of Dentistry, The University of Iowa, 801 Newton Road, Iowa City, IA, 52242, USA
Christopher N Treinen - Iowa Institute for Oral Health Research, N423 DSB, College of Dentistry, The University of Iowa, 801 Newton Road, Iowa City, IA, 52242, USA
Emily E Starman - Iowa Institute for Oral Health Research, N423 DSB, College of Dentistry, The University of Iowa, 801 Newton Road, Iowa City, IA, 52242, USA
Carol L Fischer - Iowa Institute for Oral Health Research, N423 DSB, College of Dentistry, The University of Iowa, 801 Newton Road, Iowa City, IA, 52242, USA
Deepak Parashar - Cellworks Research India Ltd, Whitefield, Bangalore, India
Janet M Guthmiller - College of Dentistry, University of Nebraska Medical Center, 40th and Holdrege, Lincoln, NE, USA
Georgia K Johnson - Department of Periodontics, College of Dentistry, The University of Iowa, Iowa City, IA, USA
Taher Abbasi - Cellworks Group Inc, 2033 Gateway Place Suite 500, San Jose, CA, USA
Shireen Vali - Cellworks Group Inc, 2033 Gateway Place Suite 500, San Jose, CA, USA
Kim A Brogden - Department of Periodontics, College of Dentistry, The University of Iowa, Iowa City, IA, USA. kim-brogden@uiowa.edu
Resource Type: Journal article
Publication Details: Cancer immunology, immunotherapy, Vol.65(12), pp.1511-1522
DOI: 10.1007/s00262-016-1907-5
PMID: 27688163
PMCID: PMC5394567
NLM abbreviation: Cancer Immunol Immunother
ISSN: 0340-7004
eISSN: 1432-0851
Publisher: Springer Science and Business Media LLC; Germany
Grant note: R01 DE014390 / NIDCR NIH HHS\r\nT90 DE023520 / NIDCR NIH HHS
Language: English
Date published: 12/2016
Academic Unit: Oral Pathology, Radiology and Medicine; Periodontics
Record Identifier: 9984065814702771

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