ImmunoMap: A Novel Bioinformatics Tool for Immune Cell Repertoire Analysis

Identification: 3035


ImmunoMap: A Novel Bioinformatics Tool for Immune Cell Repertoire Analysis

J.W.Sidhom1, C.A. Bessell1, J. Havel2, T. Chan2, J.P.Schneck1

1Johns Hopkins University School of Medicine, 2 Memorial Sloan Kettering Cancer Center

There has been a dramatic increase in T-cell Receptor (TCR) sequencing spurred, in part, by the widespread adoption of this technology across academic medical centers and by the rapid commercialization of TCR sequencing. While the raw TCR sequencing data has increased, there has been little in the way of approaches to parse the data in a biologically meaningful fashion. The ability to parse this new type of ‘big data’ quickly and efficiently to understand the T-cell repertoire in a structurally relevant manner has the potential to open the way to new discoveries about how the immune system is able to respond to insults such as cancer and infectious diseases. Here we describe a novel method utilizing phylogenetic and sequencing analysis to visualize and quantify TCR repertoire diversity. To demonstrate the utility of the approach, we have applied it to understanding the shaping of the CD8 T Cell response to self (TRP2) and foreign (SIY) antigens in naïve and tumor bearing B6 mice. Additionally, this method was applied to tumor infiltrating lymphocytes (TIL’s) from patients undergoing Nivolumab (anti-PD1) therapy in a BMS-038 clinical trial for metastatic melanoma to understand TCR repertoire characteristics between responders and non-responders. Analysis of the naïve CD8 response demonstrated a more conserved and less clonal response to SIY whereas the response to TRP2 was highly clonal and less conserved, revealing effects of tolerance. Presence of tumor demonstrated differential immune pressure on the TRP2 vs SIY response. In patients undergoing anti-PD1 therapy, we identified signatures in their pre-treatment repertoire that correlated to response. In summary, we have developed and demonstrated a novel method to meaningfully parse and interpret TCR repertoire data and have applied it to yield a novel understanding of CD8 T Cell responses to different types of antigens as well as key characteristics in those who respond to anti-PD1 therapy.


Credits: None available.

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