Genomics of NSCLC patients both affirm PD-L1 expression and predict their clinical responses to anti-PD-1 immunotherapy

BMC Cancer. 2018 Feb 27;18(1):225. doi: 10.1186/s12885-018-4134-y.


Background: Programmed Death Ligand 1 (PD-L1) is a co-stimulatory and immune checkpoint protein. PD-L1 expression in non-small cell lung cancers (NSCLC) is a hallmark of adaptive resistance and its expression is often used to predict the outcome of Programmed Death 1 (PD-1) and PD-L1 immunotherapy treatments. However, clinical benefits do not occur in all patients and new approaches are needed to assist in selecting patients for PD-1 or PD-L1 immunotherapies. Here, we hypothesized that patient tumor cell genomics influenced cell signaling and expression of PD-L1, chemokines, and immunosuppressive molecules and these profiles could be used to predict patient clinical responses.

Methods: We used a recent dataset from NSCLC patients treated with pembrolizumab. Deleterious gene mutational profiles in patient exomes were identified and annotated into a cancer network to create NSCLC patient-specific predictive computational simulation models. Validation checks were performed on the cancer network, simulation model predictions, and PD-1 match rates between patient-specific predicted and clinical responses.

Results: Expression profiles of these 24 chemokines and immunosuppressive molecules were used to identify patients who would or would not respond to PD-1 immunotherapy. PD-L1 expression alone was not sufficient to predict which patients would or would not respond to PD-1 immunotherapy. Adding chemokine and immunosuppressive molecule expression profiles allowed patient models to achieve a greater than 85.0% predictive correlation among predicted and reported patient clinical responses.

Conclusions: Our results suggested that chemokine and immunosuppressive molecule expression profiles can be used to accurately predict clinical responses thus differentiating among patients who would and would not benefit from PD-1 or PD-L1 immunotherapies.

Trial registration: NCT01295827.

Keywords: Computational modeling; Immunotherapy; NSCLC; PD-1; PD-L1.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Antibodies, Monoclonal, Humanized / pharmacology*
  • Antibodies, Monoclonal, Humanized / therapeutic use
  • Antineoplastic Agents, Immunological / pharmacology
  • Antineoplastic Agents, Immunological / therapeutic use
  • B7-H1 Antigen / genetics*
  • Carcinoma, Non-Small-Cell Lung / drug therapy*
  • Carcinoma, Non-Small-Cell Lung / genetics
  • Carcinoma, Non-Small-Cell Lung / metabolism
  • Chemokines / genetics
  • Computer Simulation*
  • Gene Expression Profiling
  • Gene Expression Regulation, Neoplastic
  • Humans
  • Immunotherapy*
  • Models, Biological
  • Mutation
  • Programmed Cell Death 1 Receptor / antagonists & inhibitors*
  • Programmed Cell Death 1 Receptor / metabolism
  • Signal Transduction / drug effects
  • Treatment Outcome


  • Antibodies, Monoclonal, Humanized
  • Antineoplastic Agents, Immunological
  • B7-H1 Antigen
  • CD274 protein, human
  • Chemokines
  • PDCD1 protein, human
  • Programmed Cell Death 1 Receptor
  • pembrolizumab

Associated data