Abstract
The identification of recurrent human leukocyte antigen (HLA) neoepitopes driving T cell responses against tumors poses a significant bottleneck in the development of approaches for precision cancer therapeutics. Here, we employ a bioinformatics method, Prediction of T Cell Epitopes for Cancer Therapy, to analyze sequencing data from neuroblastoma patients and identify a recurrent anaplastic lymphoma kinase mutation (ALK R1275Q) that leads to two high affinity neoepitopes when expressed in complex with common HLA alleles. Analysis of the X-ray structures of the two peptides bound to HLA-B*15:01 reveals drastically different conformations with measurable changes in the stability of the protein complexes, while the self-epitope is excluded from binding due to steric hindrance in the MHC groove. To evaluate the range of HLA alleles that could display the ALK neoepitopes, we used structure-based Rosetta comparative modeling calculations, which accurately predict several additional high affinity interactions and compare our results with commonly used prediction tools. Subsequent determination of the X-ray structure of an HLA-A*01:01 bound neoepitope validates atomic features seen in our Rosetta models with respect to key residues relevant for MHC stability and T cell receptor recognition. Finally, MHC tetramer staining of peripheral blood mononuclear cells from HLA-matched donors shows that the two neoepitopes are recognized by CD8+ T cells. This work provides a rational approach toward high-throughput identification and further optimization of putative neoantigen/HLA targets with desired recognition features for cancer immunotherapy.
Highlights
Cancer immunotherapy harnesses a patient’s CD4+ and CD8+ T cell responses toward peptide neoantigens, which are displayed on the surface of tumor cells by major histocompatibility complex molecules [MHC, termed human leukocyte antigen (HLA) in humans] [1]
To evaluate the potential of the two ALK neoepitopes to interact with additional HLA alleles and predict structural features relevant for recognition by T cell receptors (TCRs), we develop a high-throughput comparative modeling approach using the program Rosetta
We predicted two HLA-B*15:01-restricted decamer (MAQDIYRASY and AQDIYRASYY) and one nonamer (AQDIYRASY) neoepitopes arising from ALK R1275Q in sample TARGET-30-PARHAM
Summary
Cancer immunotherapy harnesses a patient’s CD4+ and CD8+ T cell responses toward peptide neoantigens, which are displayed on the surface of tumor cells by major histocompatibility complex molecules [MHC, termed human leukocyte antigen (HLA) in humans] [1]. The resulting peptide/MHC complexes (p/MHC) are further trafficked through the Golgi and eventually displayed on the cell surface, where they are surveilled by CD8+ cytotoxic T cells (CTLs) through specific interactions with αβ T cell receptors (TCRs) [3]. The display of high affinity peptides expressed exclusively by the tumor (i.e., neoepitopes) on MHC molecules can elicit specific CTL responses, which forms the basis of several established immunotherapies against cancers [5, 6]. One such therapy utilizes in vitro-activated, autologous CTLs to selectively target tumor cells [7]. Neoepitopes derived from commonly mutated oncogenic proteins are well-suited immunotherapy targets if they have high affinity interactions with MHC alleles that are prevalent in the population [9]
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