Mass spectrometry–driven exploration reveals nuances of neoepitope-driven tumor rejection

Ebrahimi-Nik, Hakimeh; Michaux, Justine; Corwin, William L.; Keller, Grant L.J.; Shcheglova, Tatiana; Pak, HuiSong; Coukos, George; Baker, Brian M.; Măndoiu, Ion; Bassani-Sternberg, Michal; Srivastava, Pramod K.

doi:10.1172/jci.insight.129152

Cited by 47 publications

(82 citation statements)

References 44 publications

(53 reference statements)

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“…S1 ). In line with a recent study ( Ebrahimi-Nik et al, 2019 ), these results clearly show that peptide binding ability to MHC-I is an insufficient predictor of immunogenicity.…”

Section: Resultssupporting

confidence: 90%

Mutation position is an important determinant for predicting cancer neoantigens

Capietto¹,

Jhunjhunwala²,

Pollock³

et al. 2020

Journal of Experimental Medicine

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Tumor-specific mutations can generate neoantigens that drive CD8 T cell responses against cancer. Next-generation sequencing and computational methods have been successfully applied to identify mutations and predict neoantigens. However, only a small fraction of predicted neoantigens are immunogenic. Currently, predicted peptide binding affinity for MHC-I is often the major criterion for prioritizing neoantigens, although little progress has been made toward understanding the precise functional relationship between affinity and immunogenicity. We therefore systematically assessed the immunogenicity of peptides containing single amino acid mutations in mouse tumor models and divided them into two classes of immunogenic mutations. The first comprises mutations at a nonanchor residue, for which we find that the predicted absolute binding affinity is predictive of immunogenicity. The second involves mutations at an anchor residue; here, predicted relative affinity (compared with the WT counterpart) is a better predictor. Incorporating these features into an immunogenicity model significantly improves neoantigen ranking. Importantly, these properties of neoantigens are also predictive in human datasets, suggesting that they can be used to prioritize neoantigens for individualized neoantigen-specific immunotherapies.

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“…S1 ). In line with a recent study ( Ebrahimi-Nik et al, 2019 ), these results clearly show that peptide binding ability to MHC-I is an insufficient predictor of immunogenicity.…”

Section: Resultssupporting

confidence: 90%

Mutation position is an important determinant for predicting cancer neoantigens

Capietto¹,

Jhunjhunwala²,

Pollock³

et al. 2020

Journal of Experimental Medicine

View full text Add to dashboard Cite

show abstract

“…Similarly, engagement of CD4+ T helper cells through HLA class II presentation might be limited as well. Nevertheless, tumor-specific non-canonical targets may still be valuable for cancer vaccines, even when no prior immune response against the targets has been detected ex vivo, as previously shown for neoantigens 4,67,68 . More research should be performed to thoroughly assess the ability of noncHLAp to augment protective immune response in vivo.…”

Section: Discussionmentioning

confidence: 98%

Integrated Proteogenomic Deep Sequencing and Analytics Accurately Identify Non-Canonical Peptides in Tumor Immunopeptidomes

Chong

Müller

Pak

et al. 2019

Preprint

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Efforts to precisely identify tumor human leukocyte antigen (HLA) bound peptides capable of mediating T cell-based tumor rejection still face important challenges. Recent studies suggest that non-canonical tumor-specific HLA peptides that derive from annotated non-coding regions could elicit anti-tumor immune responses. However, sensitive and accurate massspectrometry (MS)-based proteogenomics approaches are required to robustly identify these non-canonical peptides. We present an MS-based analytical approach that characterizes the non-canonical tumor HLA peptide repertoire, by incorporating whole exome sequencing, bulk and single cell transcriptomics, ribosome profiling, and a combination of two MS/MS search tools. This approach results in the accurate identification of hundreds of shared and tumorspecific non-canonical HLA peptides and of an immunogenic peptide from a downstream reading frame in the melanoma stem cell marker gene ABCB5. It holds great promise for the discovery of novel cancer antigens for cancer immunotherapy.

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“…Similarly, the engagement of CD4+ T helper cells through HLA class II presentation might also be limited. Nevertheless, tumorspecific non-canonical targets may still be valuable for immunotherapy, even when no prior immune response against the targets has been detected ex vivo, as was previously shown for neoantigens 3,4,67 . More research should be performed to thoroughly assess the ability of noncHLAp to augment protective immune responses in vivo.…”

Section: Discussionmentioning

confidence: 99%

Integrated proteogenomic deep sequencing and analytics accurately identify non-canonical peptides in tumor immunopeptidomes

et al. 2020

Self Cite

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Efforts to precisely identify tumor human leukocyte antigen (HLA) bound peptides capable of mediating T cell-based tumor rejection still face important challenges. Recent studies suggest that non-canonical tumor-specific HLA peptides derived from annotated non-coding regions could elicit anti-tumor immune responses. However, sensitive and accurate mass spectrometry (MS)-based proteogenomics approaches are required to robustly identify these noncanonical peptides. We present an MS-based analytical approach that characterizes the noncanonical tumor HLA peptide repertoire, by incorporating whole exome sequencing, bulk and single-cell transcriptomics, ribosome profiling, and two MS/MS search tools in combination. This approach results in the accurate identification of hundreds of shared and tumor-specific non-canonical HLA peptides, including an immunogenic peptide derived from an open reading frame downstream of the melanoma stem cell marker gene ABCB5. These findings hold great promise for the discovery of previously unknown tumor antigens for cancer immunotherapy.

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Mass spectrometry–driven exploration reveals nuances of neoepitope-driven tumor rejection

Cited by 47 publications

References 44 publications

Mutation position is an important determinant for predicting cancer neoantigens

Mutation position is an important determinant for predicting cancer neoantigens

Integrated Proteogenomic Deep Sequencing and Analytics Accurately Identify Non-Canonical Peptides in Tumor Immunopeptidomes

Integrated proteogenomic deep sequencing and analytics accurately identify non-canonical peptides in tumor immunopeptidomes

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