10.3389/fimmu.2020.00373.s001 Ulla Kring Hansen Ulla Kring Hansen Sofie Ramskov Sofie Ramskov Anne-Mette Bjerregaard Anne-Mette Bjerregaard Annie Borch Annie Borch Rikke Andersen Rikke Andersen Arianna Draghi Arianna Draghi Marco Donia Marco Donia Amalie Kai Bentzen Amalie Kai Bentzen Andrea Marion Marquard Andrea Marion Marquard Zoltan Szallasi Zoltan Szallasi Aron Charles Eklund Aron Charles Eklund Inge Marie Svane Inge Marie Svane Sine Reker Hadrup Sine Reker Hadrup Image_1_Tumor-Infiltrating T Cells From Clear Cell Renal Cell Carcinoma Patients Recognize Neoepitopes Derived From Point and Frameshift Mutations.jpg Frontiers 2020 renal cell carcinoma neoepitopes neoantigens frameshift mutations T cell screening 2020-03-12 04:13:03 Figure https://frontiersin.figshare.com/articles/figure/Image_1_Tumor-Infiltrating_T_Cells_From_Clear_Cell_Renal_Cell_Carcinoma_Patients_Recognize_Neoepitopes_Derived_From_Point_and_Frameshift_Mutations_jpg/11972082 <p>Mutation-derived neoantigens are important targets for T cell-mediated reactivity toward tumors and, due to their unique tumor expression, an attractive target for immunotherapy. Neoepitope-specific T cells have been detected across a number of solid cancers with high mutational burden tumors, but neoepitopes have been mostly selected from single nucleotide variations (SNVs), and little focus has been given to neoepitopes derived from in-frame and frameshift indels, which might be equally important and potentially highly immunogenic. Clear cell renal cell carcinomas (ccRCCs) are medium-range mutational burden tumors with a high pan-cancer proportion of frameshift mutations. In this study, the mutational landscape of tumors from six RCC patients was analyzed by whole-exome sequencing (WES) of DNA from tumor fragments (TFs), autologous tumor cell lines (TCLs), and tumor-infiltrating lymphocytes (TILs, germline reference). Neopeptides were predicted using MuPeXI, and patient-specific peptide–MHC (pMHC) libraries were created for all neopeptides with a rank score < 2 for binding to the patient's HLAs. T cell recognition toward neoepitopes in TILs was evaluated using the high-throughput technology of DNA barcode-labeled pMHC multimers. The patient-specific libraries consisted of, on average, 258 putative neopeptides (range, 103–397, n = 6). In four patients, WES was performed on two different sources (TF and TCL), whereas in two patients, WES was performed only on TF. Most of the peptides were predicted from both sources. However, a fraction was predicted from one source only. Among the total predicted neopeptides, 16% were derived from frameshift indels. T cell recognition of 52 neoepitopes was detected across all patients (range, 4–18, n = 6) and spanning two to five HLA restrictions per patient. On average, 21% of the recognized neoepitopes were derived from frameshift indels (range, 0–43%, n = 6). Thus, frameshift indels are equally represented in the pool of immunogenic neoepitopes as SNV-derived neoepitopes. This suggests the importance of a broad neopeptide prediction strategy covering multiple sources of tumor material, and including different genetic alterations. This study, for the first time, describes the T cell recognition of frameshift-derived neoepitopes in RCC and determines their immunogenic profile.</p>