36 Analysis of T-cell receptor sequences identifies signatures associated with neoantigen exposure in peripheral blood of lynch syndrome patients

BackgroundLynch Syndrome (LS) is the most common inherited colorectal cancer (CRC) syndrome. It constitutes the perfect model to understand DNA mismatch repair deficient (dMMR) carcinogenesis, which underlies 15% of early-stage CRC.1 LS patients develop dMMR tumors with high loads of shared neoantigens, which are recognized by the immune system2. Elucidating the role and molecular landscape of public T-cell receptors (TCRs), provides potential as a diagnostic strategy for exposure to viruses and other immune-related phenotypes3–5. This study aims to characterize the TCR beta chain (TCRB) landscape of LS patients and to identify the presence of cancer-specific TCRB clones in the peripheral blood of LS carriers.MethodsA total of 122 PBMCs and 29 colorectal tissue samples have been collected from patients enrolled during their routine screening colonoscopy to an ongoing IRB-approved biospecimen protocol (MDACC IRB# PA12–0327). All TCRB repertoires were sequenced using the Immunoseq TCRB assay (Adaptive Biotechnologies). Bioinformatics analyses were performed using the immunarch R package6,7 and the immuneML software8 by comparing the TCRB repertoires among LS cancer survivors, LS healthy carriers (with no cancer history), and controls with no cancer and no family history of LS. To validate some of the identified TCRBs, a viral peptide and a cancer neoantigen predicted to be recognized by these public TCRBs were used to isolate peripheral T-cells from healthy human donors using pMHC-tetramer assays and single-cell TCR sequencing.ResultsOur data show that LS cancer survivors have less diverse TCRB repertoires compared to LS healthy carriers due to the presence of hyper-expanded TCRBs in the group of survivors. Our results also show that a set of highly expanded cancer-specific public TCRBs is detectable in the peripheral blood of LS cancer survivors after annotation to the McPas-TCR database9. We observe an overlap of TCRBs between the tissue (precancers and cancers) and PBMCs in patients for which both types of samples were collected at the same timepoint. Finally, with our pMHC-tetramer assays, we are capable of isolating TCRBs that were initially identified with bulk-TCR sequencing.ConclusionsOverall, our data suggest that the T-cell response of LS patients against developing cancers is not entirely restricted to their tumor microenvironment, with expanded cancer-specific public TCRBs being detectable in the peripheral blood of LS cancer survivors. This is the first step toward identifying a TCR signature that serves as a biomarker of early cancer detection in LS patients.ReferencesLynch HT, Snyder CL, Shaw TG, Heinen CD, Hitchins MP. Milestones of Lynch syndrome: 1895–2015. Nat Rev Cancer [Internet]. 2015 Feb 12;15:181. Available from: https://doi.org/10.1038/nrc3878 Ballhausen A, Przybilla MJ, Jendrusch M, Haupt S, Pfaffendorf E, Seidler F, et al. The shared frameshift mutation landscape of microsatellite-unstable cancers suggests immunoediting during tumor evolution. Nat Commun [Internet]. 2020;11(1):4740. Available from: https://doi.org/10.1038/s41467-020-18514-5 Woodsworth DJ, Castellarin M, Holt RA. Sequence analysis of T-cell repertoires in health and disease. Genome Med. 2013;5(10). Emerson RO, DeWitt WS, Vignali M, Gravley J, Hu JK, Osborne EJ, et al. Immunosequencing identifies signatures of cytomegalovirus exposure history and HLA-mediated effects on the T cell repertoire. Nat Genet [Internet]. 2017;49(5):659–65. Available from: http://dx.doi.org/10.1038/ng.3822 Cui JH, Lin KR, Yuan SH, Jin Y Bin, Chen XP, Su XK, et al. TCR repertoire as a novel indicator for immune monitoring and prognosis assessment of patients with cervical cancer. Front Immunol. 2018;9(NOV):1–11. Nazarov V, immunarch.bot, Rumynskiy E. immunarch: An R Package for Painless Analysis of Large-Scale Immune Repertoire Data. Zenodo [Internet]. 2019 Jan 20 [cited 2020 Mar 30]; Available from: https://doi.org/10.5281/zenodo.3613560#.XoJ_oycykjI.mendeley Nazarov VI, Pogorelyy M V., Komech EA, Zvyagin I V., Bolotin DA, Shugay M, et al. tcR: An R package for T cell receptor repertoire advanced data analysis. BMC Bioinformatics [Internet]. 2015;16(1):1–5. Available from: ??? Pavlovic M, Scheffer L, Motwani K, Kanduri C, Kompova R, Vazov N, et al. The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires. Nat Mach Intell. 2021; Tickotsky N, Sagiv T, Prilusky J, Shifrut E, Friedman N. McPAS-TCR: a manually curated catalogue of pathology-associated T cell receptor sequences. Bioinformatics [Internet]. 2017 May 8;33(18):2924–9. Available from: https://doi.org/10.1093/bioinformatics/btx286Ethics ApprovalAll patients included in this study provided written informed consent at The University of Texas MD Anderson Cancer Center (MDACC). All samples were obtained from study participants through an Institutional Review Board (IRB) approved protocol at MDACC (Protocol PA12–0327).