Abstract 5656: Quantitative measurement of PDL1 expression across tumor types using laser capture microdissection and reverse phase protein microarray

Abstract

Abstract Background: The efficacy of immunotherapy, including therapeutic strategies capable of modulating innate/adaptive immune resistance, varies greatly across tumor types. As the number of available immunotherapies accelerates, the study of predictive markers by IHC (e.g. PDL1 expression) is under intense investigation. However, staining protocol inconsistency, variation across scoring systems, and subjective interpretation of the immunostaining have produced conflicting results thus far. This work explored the role of Laser Capture Microdissection (LCM) coupled with Reverse Phase Protein Microarray (RPPA) as an alternative high throughput, quantitative, operator independent platform for measuring PDL1 expression across tumor types. Material and Methods: Pure epithelial cells were isolated via LCM from 178 samples including: 72 ovarian cancers (OC), 57 lung adenocarcinomas (LC), 30 metastatic breast cancers (MBC), and 19 pancreatic cancers (PC). PDL1 expression was measured on a continuous scale using quantitative RPPA based analysis. Each tumor type was processed and arrayed independently. Experimental samples and reference standards used for inter-assay normalization were printed in triplicates. Results: PDL1 expression varied greatly across tumor types. LC were characterized by the greatest intra-tumor fold dynamic range (> 35-fold), followed by OC (< 13-fold), MBC (< 4-fold), and PC (< 2-fold). PDL1 expression of 46/57 (80.7%) LC, 17/30 (56.7%) MBC, 6/19 (31.5%) PC, and 20/72 (27.8%) OC was greater than the population median of all tumors combined. Within the LC samples with PDL1 expression equal to the top quartile of the population, 10 (71.4%) were KRAS mutant lesions and 4 (28.6%) were WT tumors. Finally, amongst LC and PC harboring a KRAS mutation, PC showed an overall lower expression of PDL1 with only 2/19 (10.5%) cases been above the population median and none within the top quartile of the population. Conclusions: The LCM-RPPA workflow has the unique ability to capture immune checkpoint expression on a continuous quantitative scale as well as capture its broad dynamic range. Because RPPA is unconstrained by antigen retrieval issues as well as subjectivity of IHC interpretation, this approach may generate more accurate cut-point of therapeutic response prediction. Overall the dynamic range of PDL1 was broader in LC compared to other solid tumors, and LC had a much higher proportion of patients with tumors expressing high levels of PDL1. These quantitative differences may explain therapeutic efficacy of PDL1 inhibition across tumor types. Such speculative hypothesis should be further validated in prospective clinical trials. Finally, these preliminary data suggest that organ specific microenvironments more than specific driving mutations (e.g. KRAS) may strongly influence PDL1 expression in malignant lesions. Citation Format: Elisa Baldelli, Valerie Calvert, K. Alex Hodge, Maria Isabella Sereni, Guido Gambara, Eric B. Haura, Lucio Crino', Bryant Dunetz, Sergio Pecorelli, David J. Perry, Stephen P. Anthony, Nicholas Robert, Donald W. Northfelt, Mohammad Jahanzeb, Emanuel F. Petricoin, Mariaelena Pierobon. Quantitative measurement of PDL1 expression across tumor types using laser capture microdissection and reverse phase protein microarray [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5656. doi:10.1158/1538-7445.AM2017-5656