Abstract 4430: Quantification of tumor-infiltrating immune cell populations with an augmented transcriptome
Authors: Levy Eric , Milani Pamela , Abbott Charles W. , Lee Manxia , Power Robert , West John , Chen Richard , Boyle Sean M. 
Published: September 2020

Abstract
Comprehensive characterization of the tumor and tumor microenvironment (TME) can improve our understanding of tumor progression and treatment outcomes. For example, quantification of the immune infiltrate can inform mechanisms of immune escape and predict response to checkpoint blockade. Standard experimental approaches exist to enumerate tumor-infiltrating immune cells, but they can have practical limitations of throughput, number of markers, or sample requirements. RNA sequencing can be used as a scalable solution to comprehensively profile the immune cell composition of the TME. However, care must be taken to ensure that the computational analysis accurately reflects the underlying immune cell composition. To address these challenges, we developed ImmunoID NeXT, an augmented, immuno-oncology-optimized exome/transcriptome platform designed to provide comprehensive information regarding the tumor and TME from a single FFPE tumor sample. This includes the quantification of tumor-infiltrating immune cells using RNA-seq analysis, which we compare to quantification by orthogonal methods.
To generate our reference data, we profiled the transcriptomes of eight purified immune cell types using ImmunoID NeXT. Then, we analyzed multiple sample types and orthogonally quantified immune cells in each. These include profiling of healthy donor PBMCs with cytometry by time of flight (CyTOF), and immunofluorescence (IF) characterization of FFPE tumor samples. We also used ImmunoID NeXT to profile the immune infiltrate of over 500 tumor samples across 13 cancer types. Finally, we created a set of in vitro cell mixtures and profiled them by flow cytometry.
We utilized the transcriptome profiles of eight purified immune cell types to develop reference expression signatures specific for each cell type. Then, we compared ImmunoID NeXT's transcriptome-based approach to CyTOF results of healthy donor PBMCs, showing accuracy in real samples with diverse immune populations. We also compared to FFPE tumor samples with IF, ensuring that our approach is able to profile the immune composition in tumor samples. Next, we highlight the diversity of immune populations across cancer types by applying ImmunoID NeXT to over 500 tumor samples. Finally, to demonstrate concordance across the eight cell types, we compared to flow cytometry results of in vitro cell mixtures.
Analysis of the immune infiltrate of tumor samples can add to our understanding of the tumor-immune interaction, with potential applications including studies of response to immunotherapy. RNA sequencing can be utilized as a scalable approach for such analysis. Here, we test the accuracy of our approach using multiple sample sets with orthogonal profiling. We demonstrate that ImmunoID NeXT can accurately evaluate the composition of infiltrating immune cells in tumor samples.
Citation Format: Eric Levy, Pamela Milani, Charles W. Abbott, Manxia Lee, Robert Power, John West, Richard Chen, Sean M. Boyle. Quantification of tumor-infiltrating immune cell populations with an augmented transcriptome [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4430.