Abstract 1675: Leveraging RNA sequencing for scalable tumor immune repertoire profiling

Abstract

Abstract Background: Therapeutic strategies that modulate the interaction between tumors and tumor-infiltrating lymphocytes (TILs), such as checkpoint blockade, have tremendous promise but yield clinical responses in only a subset of patients. Accumulating evidence indicates that better characterizing TILs using repertoire-sequencing (rep-seq) may aid in predicting immunotherapy outcomes. However, repertoire profiling of the immune infiltrate is often implemented as a stand-alone assay or via single-cell sequencing, which can be difficult to incorporate into diagnostic platforms at scale. We developed and optimized a method to integrate immune repertoire profiling into a high-volume RNA-seq pipeline. Our approach yields accurate quantification of abundant TIL receptors without diminishing the clinical value of the remaining transcriptome. Here, we demonstrate the capabilities of our method in 500 TCR/BCR repertoires from a diverse cohort of tumor samples. Methods: Hybrid capture probes tiling T-cell and B-cell receptor (TCR and BCR) genes were used to enrich immune receptor transcripts detected by the Tempus RNA-seq workflow. Receptor sequences were aligned, assembled, and annotated against IMGT reference sequences using the TRUST4 assembly tool. Shannon Entropy was calculated to evaluate repertoire evenness. Richness (productive clonotypes) and immune infiltration predictions were correlated with a one-tailed Pearson correlation coefficient (95% CI). Results: Immune repertoires were extracted from RNA-seq of 501 tumor samples across 38 different cancer types. TCR and BCR repertoires (including small gamma/delta TCR repertoires) were robustly assembled in our cohort, with over 1.2 million total clonotypes identified. The distribution of repertoire evenness demonstrated expected trends, including dominant monoclonal expansion (>70-90% total receptor reads) of putative tumor cell receptors in T-cell/B-cell-driven malignancies. Repertoire richness also followed tissue-specific expectations where TIL-low cancers (e.g., glioblastoma multiforme) typically exhibited low-richness repertoires, while TIL-high cancers (e.g., non-small cell lung cancer) often yielded thousands of productive clonotypes. Repertoire richness was significantly correlated with RNA-based cell-type-specific transcriptional profiles for T-cells (r = 0.43, P<5e-24) and B-cells (r = 0.2, P<3.6e-6). Benchmarking our method on co-extracted DNA with amplicon-based repertoire sequencing confirmed accurate detection of highly abundant TIL receptors using an orthogonal approach. Conclusions: Our repertoire profiling method effectively leveraged routine RNA-seq to profile TIL receptors, ultimately allowing for the seamless integration of repertoire-based biomarker evaluation and improved immune infiltrate estimation through a high-volume RNA-seq pipeline. Citation Format: Taylor S. Harding, Brittany Mineo, Jenna Malinauskas, Jason Perera, Aly A. Khan. Leveraging RNA sequencing for scalable tumor immune repertoire profiling [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 1675.