0      0

eSymposia | Advances in Cancer Immunotherapy


Identifying tumor antigen-specific CD4+ T cell dysfunctional states by single cell transcriptomics in immunotherapy-treated cancer patients


Aug 17, 2020 12:00am ‐ Aug 17, 2020 12:00am

Description

Identifying tumor antigen-specific CD4+ T cell dysfunction Edgar E. Gonzalez-Kozlova, Shingo Eikawa, Naoko Imai, Sacha Gnjatic, Bojan Losic * Edgar.Gonzalez-Kozlova@mssm.edu , sacha.gnjatic@mssm.edu , bojan.losic@mssm.edu Icahn School of Medicine at Mount Sinai, New York, NY ABSTRACT Dysfunctional T cell states resulting from continuous exposure to self shared tumor antigens or neoantigens are key to understanding immune mechanisms that prevent proper antitumor immunity. We previously showed that repeated administration of recombinant tumor antigen vaccines without immunological adjuvant emulates a tolerized-like immune response that cannot be rescued even after in vivo re-challenge with adjuvant. We used bulk and single-cell RNA-seq of purified antigen-specific CD4+ T-cells (i.e., the orchestrator of immunity) from 12 ovarian and non-small cell lung cancer patients receiving NY-ESO-1 or MAGE-A3 vaccines with or without adjuvant, over a period of 13 weeks. First, using bulk RNA-seq data, we derived novel temporal, tolerization CD4+ T cell expression and clonotype evolution signatures using differential expression and VDJ-deconvolution analyses, highlighting significant association with cell cycle and immune activation. Then, we projected these signatures onto several recently published single-cell RNA-seq data profiling exhausted tumor-infiltrating and peripheral blood lymphocytes, finding reasonable predictive power (AUC~0.8) to classify dysfunctional T-cell states that could distinguish exhaustion from tolerance. Next, we characterized in depth the transcriptional profiles and heterogeneity of our antigen-specific CD4+ T-cells pre- and post-treatment at the single-cell level using combined scRNAseq and scTCRseq. Finally, we computationally inferred the regulatory axis of tolerized T-cells by deriving transcription factor signaling networks upstream of gene expression. In conclusion, we characterized transcriptional signatures of tumor antigen-specific CD4+ T-cells and derived a specific tolerization profile, distinguishable from exhaustion, and conserved across datasets. Through comprehensive identification of genes and pathways in a human experimental setting for induction of tolerization and exhaustion, these findings provide relevant and promising avenues to reverse dysfunctional CD4+ T cell states.

Speaker(s):

You must be logged in and own this session in order to post comments.

Print Certificate
Completed on: token-completed_on
Print Transcript
Please select the appropriate credit type:
/
test_id: 
credits: 
completed on: 
rendered in: 
* - Indicates answer is required.
token-content

token-speaker-name
token-index
token-content
token-index
token-content
token-index
token-content
token-index
token-content
token-index
token-content
token-index
token-content
/
/
token-index
token-content
token-index
token-content