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

Cancer Immunol Immunother. 2016 Dec;65(12):1511-1522. doi: 10.1007/s00262-016-1907-5. Epub 2016 Sep 29.


Purpose: 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.

Methods: 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.

Result: 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.

Conclusion: 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.

Keywords: Computational modeling; Multiple myeloma; Oral squamous cell carcinoma; PD-L1; Simulation modeling.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • B7-H1 Antigen / metabolism*
  • Carcinoma, Squamous Cell / genetics*
  • Carcinoma, Squamous Cell / pathology
  • Computer Simulation
  • Humans
  • Middle Aged
  • Models, Biological
  • Molecular Dynamics Simulation
  • Mouth Neoplasms / genetics*
  • Mouth Neoplasms / pathology
  • Multiple Myeloma / genetics*
  • Multiple Myeloma / pathology


  • B7-H1 Antigen
  • CD274 protein, human