Timothy Looney

Haplotype Analysis of the TRB Locus by TCRB Repertoire Sequencing

Polymorphism within the T cell receptor beta variable gene (TRBV) has been implicated in autoimmune disease and immuneCrelated adverse events (IRAEs) during immunotherapy. Previous efforts to evaluate TRBV polymorphism by whole genome sequencing (WGS) have been hampered by the repetitive nature of the TCRB locus. We present a novel longCamplicon TCRB repertoire sequencing approach to evaluate TRBV polymorphism from peripheral blood, which we use to identify TRBV allele haplotypes in 81 Caucasians.

Abstract 4668: Evidence for antigen-driven TCRB chain convergence in the tumor infiltrating T cell repertoire of 85 research subjects with melanoma

Introduction T cell convergence refers to the phenomenon whereby antigen-driven selection enriches for T cell receptors having a shared antigen specificity but different amino acid or nucleotide sequence. T cell recruitment and expansion within the tumor microenvironment (TME) may be directed by responses to tumor neoantigen, suggesting that elevated T cell convergence could be a general feature of the tumor infiltrating T cell repertoire. Here we evaluate evidence for T cell convergence within tumor biopsy research samples from a set of 85 subjects with melanoma. Methods Total RNA from 85 tumor biopsy research samples (non-FFPE) was extracted for use in long-amplicon TCRB chain sequencing (mean amplicon length of 330bp covering CDR1, 2 and 3) via the Ion AmpliSeq Immune Repertoire Assay Plus, TCRB. To evaluate T cell convergence within each biopsy, we searched for instances where TCRB chains were identical in amino acid space (shared variable gene identity and CDR3 amino acid sequence) but had distinct nucleotide sequences owing to N-addition and exonucleotide chewback within the V-D and D-J junctions of the CDR3. To provide context, we evaluated evidence for T cell convergence with T cell repertoires derived from healthy donor peripheral blood leukocytes (PBL). Results Sequencing of melanoma biopsies yielded an average of 6029 clones per sample. 11 of 85 samples yielded fewer than 100 clones and were eliminated from downstream analysis. Convergent T cell receptors were identified in 68/74 (92%) of tumor infiltrating T cell repertoires having greater than 100 detected clones. The frequency of convergent rearrangements was approximately 50-fold greater in the melanoma-infiltrating T cell repertoire than healthy PBL samples (p Conclusions These data suggest that T cell convergence may be a common feature of the melanoma infiltrating T cell repertoire. Convergence was more frequently observed within the TME than T cell repertoires derived from healthy PBL, consistent with elevated antigen-driven T cell selection within the TME. The extent to which convergence is a feature of the TME in other cancers is not yet known. T cell receptor convergence may be driven by T cell responses to tumor neoantigen within the TME. In such case, in silico identification of convergent T cell receptors by long-amplicon sequencing may serve as an approach for rapid identification of antigen-specific T cell receptors for future therapeutic use. For research use only. Citation Format: Timothy J. Looney, Sean Glenn, Sarabjot Pabla, Jeff Conroy, Carl Morrison, Alice Zheng, Lauren Miller, Elizabeth Linch, Denise Topacio, Geoff Lowman, Fiona Hyland, Mark Anderson. Evidence for antigen-driven TCRB chain convergence in the tumor infiltrating T cell repertoire of 85 research subjects with melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4668.

Abstract B17: Validation of targeted gene expression profiling panel for identifying biomarker signatures of immunotherapy responders

Cancer immunotherapy has led to an unprecedented, long-lasting response in populations susceptible to the therapies. Despite the therapeutic potential, identifying biomarkers and stratifying populations that are likely to respond has been a challenge. Gene expression profiling has previously been successfully used to stratify individuals based on survival and treatment characteristics, but there exist limitations with the prevalent technologies. In particular, full transcriptome gene expression estimates use limited biological material to measure the concentrations of tens of thousands uninformative genes and often lack the depth required to accurately measure expression levels of lowly-expressed genes. These genes may be critical to the identification of a signature associated with immunotherapy responders. To efficiently measure the expression of the key genes potentially informative of an immunotherapy response, we developed a high-throughput targeted gene expression solution measured by our RNA Ion Oncomine Immune Response Profiling panel* containing 395 genes. This panel provides information about the expression of genes involved in tumor checkpoint inhibition (including CTLA4, PD-1, PD-L1, OX-40, 4-1BB, TIM3, LAG3) and other targets such as CSF1R, and IDO1, as well as additional markers of T cell signaling pathway, interferon signaling, and markers of tumor infiltrating lymphocytes (TIL). We used publicly available TCGA data to demonstrate the need and develop a solution for a new normalization procedure that allows for accurate comparisons of samples within various cancer types. Furthermore, we verified a linear and unbiased estimate of fold change in our assays across mixing concentrations of a cell-line titration experiment. Finally, by achieving a high correlation (r > .99) of technical replicates, along with robust expression estimation even at low input amounts (10 ng RNA), our panel offers a valuable solution for biomarker research in cancer immunotherapy. *For research use only. Not for use in diagnostic procedures. Citation Format: Aleksandr Pankov, Yongming Sun, Yuan-Chieh Ku, Warren Tom, Jianping Zheng, Timothy Looney, Janice Au-Yong, Fiona Hyland, Ann Mongan. Validation of targeted gene expression profiling panel for identifying biomarker signatures of immunotherapy responders. [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2016 Oct 20-23; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2017;5(3 Suppl):Abstract nr B17.