December 16, 2015
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Significant heterogeneity observed among PD-L1 protein levels in non–small cell lung cancer samples

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Researchers found significant variability and discordance within assays analyzing non–small cell lung cancer tumors with programmed cell death protein 1 expression, and recommended a standardized diagnostic test to help account for the disparity, according to study results published in JAMA Oncology.

To detect programmed cell death 1 ligand 1 (PD-L1) proteins in tissue with non–small cell lung cancer (NSCLC), both immunohistochemistry (IHC) and quantitative immunofluorescence (QIF) methods were used, and then the results were compared with two PD-LI antibodies, according to the researchers.

“Future studies measuring PD-L1 protein quantitatively in patients treated with anti–PD-1 and anti–PD-L1 therapies may better address the prognostic and/or predictive value of these biomarkers,” Joseph McLaughlin, MD, from the department of medical oncology at Yale University School of Medicine, and colleagues wrote. “Determination of the optimal assay, PD-L1 antibody, and the best cut-point for PD-L1 positivity, will require further rigorous studies including tissues with known response to anti–PD-1 and anti–PD-L1 therapies.”

McLaughlin and colleagues used E1L3N and SP142 rabbit monoclonal antibodies to measure PD-L1 protein expression in 49 patients with NSCLC, according to the abstract. They found fair to poor concordance using chromogenic IHC (Cohen κ range, 0.12–0.34) and intra-assay results showed heterogeneity for both E1L3N (CV = 6.75% to 75.24%) and SP142 (CV = 12.17% to 109.61%) monoclonal antibodies.

Using QIF, McLaughlin and colleagues found significant discordance, with a frequency expression of 26.6%, “including 51 (8.6%) positive by SP142 and negative by E1L3N, and 106 (18.0%) positive by E1L3N and negative by SP142,” the researchers said. They noted both monoclonal antibodies showed PD-L1 expression was heterogeneous. When using the nonparametric paired test, the researchers found significantly different tumor scores for both E1L3N and SP142. Overall, there was a 25% frequency of discordance.

In a related editorial, Feriyl Bhaijee, MD, from AmeriPath Indiana in Indianapolis and Robert A. Anders, MD, PhD, from the department of pathology at Johns Hopkins University, wrote, “Identifying the subset of patients who are most likely to respond to anti–PD-L1 therapy is the first step toward individualized therapy. As a biomarker, however, PD-L1 immunohistochemistry offers poor sensitivity and reproducibility, and as a result, these patients may be unfairly excluded from clinical trials. To offer this potentially life-saving personalized immune-based therapy to as many patients as possible, we need to develop a multifaceted predictive biomarker system that integrates checkpoint inhibitors such as PD-L1, tumor mutations, and inflammatory cells.” – by Jeff Craven

Disclosure: One researcher reports consultant fees from Amgen, Applied Cellular Diagnostics, Biocept, BMS, Genoptix/Novartis, Metamark Genetics, Optrascan and Perkin Elmer. Anders reports research support from Bristol-Myers Squibb and Stand Up 2 Cancer.