Due to the complexity of tumor-immune interactions, comprehensive profiling of both the tumor and tumor microenvironment (TME) can help further our understanding of tumor progression and response to treatment. One significant application is quantification of the immune infiltrate, which has the potential to characterize response to checkpoint blockade therapy. While common experimental approaches exist to profile tumor-infiltrating immune cells, they can have significant practical limitations. Instead, RNA sequencing can be used to comprehensively profile the immune composition of the TME in a scalable way. To address this, we have developed an approach to quantify eight immune cell types in tumor samples, and compare it to quantification by orthogonal methods. This module adds to the ImmunoID NeXT Platform®, an augmented, immuno-oncology-optimized exome/transcriptome platform designed to provide comprehensive information regarding the tumor and TME from a single FFPE tumor sample.

To generate our reference data, we profiled the transcriptomes of eight purified immune cell types using ImmunoID NeXT™. Then, we utilized multiple methodologies and sample types to generate orthogonal quantification of immune cells for testing. These include creating in vitro cell mixtures and profiling by flow cytometry, profiling healthy donor PBMCs with cytometry by time of flight (CyTOF), profiling of dissociated tumor cells (DTCs) with FACS, and immunofluorescence (IF) characterization of FFPE tumor samples. We also used ImmunoID NeXT to profile the immune infiltrate of over 800 tumor samples across 13 cancer types.

We utilized the transcriptomes of the purified immune cells to develop reference expression signatures specific for each cell type. Then, we compared ImmunoID NeXT's transcriptome-based approach to the orthogonal quantification from the variety of samples. We observed a strong concordance of the quantification from our transcriptome-based approach to the flow cytometry results of the cell mixtures, demonstrating accuracy in purified immune cell populations. We also observed strong concordance to CyTOF results from healthy donor PBMC samples, showing accuracy in real samples with diverse immune populations. Further, we demonstrated strong concordance of our methodology to FACS results in DTCs and IF in FFPE tumor samples, ensuring that our approach is able to profile the immune composition in various tumor samples. Finally, we highlight the diversity of immune populations across cancer types by applying ImmunoID NeXT to over 800 tumor samples.

RNA sequencing can be used as a scalable approach to profile the immune infiltrate in tumors. Such analysis can add to our understanding of the tumor-immune interaction, including studies of response to immunotherapy. We show that the ImmunoID NeXT Platform is able to accurately evaluate the composition of tumor-infiltrating immune cells.

Citation Format: Eric Levy, Pamela Milani, Fabio Navarro, Charles W. Abbott, Robert Power, John West, John Lyle, Sean M. Boyle, Richard Chen. Profiling tumor-infiltrating immune cells using an augmented transcriptome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2241.