Lung cancer is the leading cause of cancer related deaths in the United States (US) and the world, accounting for over 150,000 deaths per year in the US alone. Recently, understanding of the biology of non-small cell lung cancer (NSCLC) has increased. Although many patients are treated with agents targeting specific driver mutations in their tumor, such agents are unavailable for most patients, and resistance eventually emerges. Agents directed against the programmed cell death-1 (PD-1) immune checkpoint have recently shown great promise. Although associated with an objective response rate (ORR) of about 20% in unselected metastatic NSCLC patients, the quality and duration of responses can be profound, particularly in a field accustomed to progression of disease after six months with even the most effective therapies A substantial debate is based on the predictive nature of biomarkers to select patients for therapy. Many were surprised by the results of a study of 495 NSCLC patients I led suggesting an association between ORR and PD-L1 expression. In a training set, we found that staining for PD-L1 in at least half of the tumor cells predicted a greater ORR. When we looked to validate our results in independent patients, the ORR was 45.2% in those with staining in at least half of their tumor cells compared to 16.5% and 10.7% in those with lesser or absent staining respectively. Similar results were seen for progression free and overall survival. Further evidence has been generated looking at other potential biomarkers. We collaborated with others to show that the number of non-synonymous mutations correlated with durable clinical benefit (partial response or stable disease lasting at least 6 months). We also saw correlations with outcome and a history of current or prior cigarette smoking, pre-biopsy CD4+ and CD8+ T cells and expression of certain genes and miRNAs. Yet, no single factor predicts outcome at the level of precision that would be ideal for clinical practice. Further, despite the correlation of each factor with clinical-outcome, the different factors don't correlate with one another particularly strongly. We have banked specimens from well over 100 patients treated with a PD-1 inhibitor to date. In light of recent drug approvals, working with our affiliated satellite offices and a network of community oncologists with whom we collaborate, the TRIO-US network, we will rapidly bank additional high quality specimens that are associated with clinical data. With these specimens, we plan to be able to create models that can effectively predict which patients stand to benefit from PD-1 inhibitors.
The specific aims of this project are: 1. Define the clinical characteristics and the properties of the tumor and immune microenvironment that predict response to single agent PD-1 inhibition in a training set 2. Create models to identify the likelihood of benefit from PD-1 inhibition in NSCLC 3. Validate the models generated from the training set samples in an independent set of samples

Public Health Relevance

Although lung cancer is the world's leading cause of cancer related deaths, recent approvals of programmed cell death 1 (PD-1) inhibitors in metastatic non-small cell lung cancer (NSCLC) based on durable responses have caused tremendous enthusiasm. We have generated a large specimen bank, to which we will add substantially in light of recent drug approvals. We will evaluate clinical characteristics and properties of tumors and the immune microenvironment that predict benefit from PD-1 inhibition, create models to identify NSCLC patients likely to benefit from PD-1 inhibition, and validate those models in a set of independent samples.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project (R01)
Project #
Application #
Study Section
Cancer Biomarkers Study Section (CBSS)
Program Officer
Dey, Sumana Mukherjee
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of California Los Angeles
Internal Medicine/Medicine
Schools of Medicine
Los Angeles
United States
Zip Code
Williamson, Timothy J; Choi, Alyssa K; Kim, Julie C et al. (2018) A Longitudinal Investigation of Internalized Stigma, Constrained Disclosure, and Quality of Life Across 12 Weeks in Lung Cancer Patients on Active Oncologic Treatment. J Thorac Oncol 13:1284-1293
Aisner, Dara L; Sholl, Lynette M; Berry, Lynne D et al. (2018) The Impact of Smoking and TP53 Mutations in Lung Adenocarcinoma Patients with Targetable Mutations-The Lung Cancer Mutation Consortium (LCMC2). Clin Cancer Res 24:1038-1047
Dhar, Manjima; Wong, Jessica; Che, James et al. (2018) Evaluation of PD-L1 expression on vortex-isolated circulating tumor cells in metastatic lung cancer. Sci Rep 8:2592
Gaut, Daria; Sim, Myung Shin; Yue, Yuguang et al. (2018) Clinical Implications of the T790M Mutation in Disease Characteristics and Treatment Response in Patients With Epidermal Growth Factor Receptor (EGFR)-Mutated Non-Small-Cell Lung Cancer (NSCLC). Clin Lung Cancer 19:e19-e28
Lisberg, A; Cummings, A; Goldman, J W et al. (2018) A Phase II Study of Pembrolizumab in EGFR-Mutant, PD-L1+, Tyrosine Kinase Inhibitor Naïve Patients With Advanced NSCLC. J Thorac Oncol 13:1138-1145
Garcia-Gathright, Jean I; Matiasz, Nicholas J; Adame, Carlos et al. (2018) Evaluating Casama: Contextualized semantic maps for summarization of lung cancer studies. Comput Biol Med 92:55-63
Tsai, Emily B; Pomykala, Kelsey; Ruchalski, Kathleen et al. (2018) Feasibility and Safety of Intrathoracic Biopsy and Repeat Biopsy for Evaluation of Programmed Cell Death Ligand-1 Expression for Immunotherapy in Non-Small Cell Lung Cancer. Radiology 287:326-332
Chowell, Diego; Morris, Luc G T; Grigg, Claud M et al. (2018) Patient HLA class I genotype influences cancer response to checkpoint blockade immunotherapy. Science 359:582-587
Lisberg, Aaron; Tucker, D Andrew; Goldman, Jonathan W et al. (2018) Treatment-Related Adverse Events Predict Improved Clinical Outcome in NSCLC Patients on KEYNOTE-001 at a Single Center. Cancer Immunol Res :
Che, James; Yu, Victor; Garon, Edward B et al. (2017) Biophysical isolation and identification of circulating tumor cells. Lab Chip 17:1452-1461

Showing the most recent 10 out of 14 publications