Global analysis of shared T cell specificities in human non-small cell lung cancer enables HLA inference and antigen discovery

Abstract

Summary To identify disease-relevant T cell receptors (TCRs) with shared antigen specificity, we analyzed 778,938 TCRβ chain sequences from 178 non-small cell lung cancer patients using the GLIPH2 (grouping of lymphocyte interactions with paratope hotspots 2) algorithm. We identified over 66,000 shared specificity groups, of which 435 were clonally expanded and enriched in tumors compared to adjacent lung. The antigenic epitopes of one such tumor-enriched specificity group were identified using a yeast peptide-HLA A ∗ 02:01 display library. These included a peptide from the epithelial protein TMEM161A, which is overexpressed in tumors and cross-reactive epitopes from Epstein-Barr virus and E. coli . Our findings suggest that this cross-reactivity may underlie the presence of virus-specific T cells in tumor infiltrates and that pathogen cross-reactivity may be a feature of multiple cancers. The approach and analytical pipelines generated in this work, as well as the specificity groups defined here, present a resource for understanding the T cell response in cancer.

Immunotherapy in the Treatment of Urothelial Bladder Cancer: Insights From Single-Cell Analysis

“…Oh et al applied scRNA-seq and paired scTCR-seq to characterize the immune milieu of 7 MIBC patients (87). Reminiscent of heterogeneous T cell infiltrates defined in previous studies (106)(107)(108), a diverse range of T cell subtypes also existed in UBC, including both CD4 + and CD8 + T cells that could be further clustered into different functional subgroups. However, in contrast to the canonical view, two cytotoxic CD4 + T cell populations were unexpectedly identified in bladder cancer that correlated with a significantly increased likelihood of clinical response to PD-L1 inhibition (87).…”

Geometric Network Analysis Provides Prognostic Information in Patients with High Grade Serous Carcinoma of the Ovary Treated with Immune Checkpoint Inhibitors

“…This permits the pairing and testing of the type of modeling presented here along with prediction of genes with high curvature with experimental tests in a mouse model to improve the choice of therapies depending upon the genotypes of the tumors. Interestingly, in non-small cell lung cancer a major tumor antigen, not genetically altered in sequence (not a neo-antigen), was found to be overexpressed in many di↵erent independent tumors [7,8]. This suggests that in serous OCs, like non-small cell lung cancers, the higher concentration of a non-genetically altered tumor antigen was an important variable in responsiveness to checkpoint therapy.…”

“…Biomarkers of response to immune checkpoint blockade in HGSOC remain largely unknown. Unlike non-small cell lung cancers and melanomas that exhibit increased immunogenicity due to high tumor mutational burden (TMB) [7,8,9,10,11], HGSOCs exhibit low TMB [12]. In virtually all cases, HGSOCs are a disorder of loss of function gene mutations (TP53) leading to CNAs, and subsequently resulting in over-expressed copy number in multiple genes including oncogenes (e.g., K-RAS, c-MYC, cyclin E and AKT protein kinase) commonly due to aneuploidy [13,14].…”

Biological controls for standardization and interpretation of adaptive immune receptor repertoire profiling

“…AIRR sequencing (AIRR-seq) provides insights into the immune status of an individual at steady-state or in altered conditions such as malignancy, autoimmune disease, immunodeficiency, infectious disease, or vaccination, and allows comparison of B- and T-cell populations between individuals and time points ( Benichou et al, 2012 ; Kirsch et al, 2015 ; Dziubianau et al, 2013 ; Hou et al, 2016 ; Ghraichy et al, 2018 ). AIRR-seq permits the description and quantification of global diversity and characteristics of AIRR, the identification of clonal expansions, the tracking of particular clonotypes, and the prediction of their specificities ( Miho et al, 2018 ; Zvyagin et al, 2020 ; Sidhom et al, 2018 ; Glanville et al, 2017 ; Huang et al, 2020 ; Jokinen et al, 2021 ; Akbar et al, 2021 ; Hayashi et al, 2021 ) as well as the antibody selection through phage display ( Rouet et al, 2018 ; Ravn et al, 2013 ), thereby providing opportunities for new biomarker identification ( Gittelman, 2021 ; Dines, 2020 ), therapeutic antibody discovery ( Akbar et al, 2021 ; Richardson et al, 2021 ), CAR-T cell bioengineering ( Sheih et al, 2020 ), vaccine development, cancer diagnostics and treatment ( Linette et al, 2019 ; Zhang et al, 2018 ; Lu et al, 2018 ), including neoantigen discovery ( Chiou et al, 2021 ; Richters et al, 2019 ) and immune intervention monitoring in diverse pathologies, such as stem cell transplantation ( Robinson, 2015 ; Fink, 2019 ; Jiang et al, 2019 ; Jacobsen et al, 2017 ; Theil, 2017 ; Link-Rachner et al, 2019 ; Rubelt et al, 2017 ; Parola et al, 2018 ; Georgiou et al, 2014 ; Arnaout et al, 2021 ; Anand et al, 2021 ).…”