Evaluation of Biomarkers Predictive of Benefit from the PD-1 Inhibitor MK-3475 in Patients with Non-Small Cell Lung Cancer and Brain Metastases
Technical Report,01 Jul 2015,30 Jun 2018
Yale University New Haven United States
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Immunotherapies inhibiting the Programmed Death-1 PD-1 axis can result in dramatic responses and durable benefit in patients with non-small cell lung cancer NSCLC. However, the overall response rate is only 20-30 and there is no clearly-defined biomarker that predicts which patients are most likely to benefit. Moreover, patients with NSCLC and brain metastases represent a population for which there are limited treatment options, and these patients are typically excluded from immunotherapy clinical trials or require local therapy prior to study enrollment. Therefore we conducted a trial of the PD-1 inhibitor pembrolizumab MK-3475 in patients with NSCLC and untreated brain metastases. The objective of this proposal was to study the immunophenotypic characteristics of primary lung tumors, brain metastases and extra-cerebral metastases with the goal of determining the variability across sites, and to study tumor- and blood-based biomarkers to establish predictors of immunotherapy benefit. We hypothesized that identifying biomarkers predictive of benefit to immunotherapy in patients with NSCLC and brain metastases would result in improved patient outcomes. Over the first two years of the grant, we optimized the assays to be used to study, compiled the cohort of paired tumor samples, constructed the tissue microarray, accrued patients with NSCLC and untreated brain metastases to the clinical trial with pembrolizumab, obtained both blood and tumor tissue samples from these patients, and began to analyze these samples. Additionally, the PI had the opportunity to learn the laboratory skills necessary to complete this project. Over the past year, we have completed accrual to the clinical trial and collected the final tissue and blood samples. We tested the tissue microarrayand trial patient samples for various immune biomarkers and analyzed them to determine whether they can predict for benefit from immunotherapy.
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