Neoantigen prediction and computational perspectives towards clinical benefit: recommendations from the ESMO Precision Medicine Working Group
Por:
De Mattos-Arruda, L, Vazquez, M, Finotello, F, Lepore, R, Porta, E, Hundal, J, Amengual-Rigo, P, Ng, CKY, Valencia, A, Carrillo, J, Chan, TA, Guallar, V, McGranahan, N, Blanco, J and Griffith, M
Publicada:
1 ago 2020
Ahead of Print:
28 jun 2020
Resumen:
Background: The use of next-generation sequencing technologies has enabled the rapid identification of non-synonymous somatic mutations in cancer cells. Neoantigens are mutated peptides derived from somatic mutations not present in normal tissues that may result in the presentation of tumour-specific peptides capable of eliciting antitumour T-cell responses. Personalised neoantigen-based cancer vaccines and adoptive T-cell therapies have been shown to prime host immunity against tumour cells and are under clinical trial development. However, the optimisation and standardisation of neoantigen identification, as well as its delivery as immunotherapy are needed to increase tumour-specific T-cell responses and, thus, the clinical efficacy of current cancer immunotherapies.
Methods: In this recommendation article, launched by the European Society forMedical Oncology (ESMO), we outline and discuss the available framework for neoantigen prediction and present a systematic reviewof the current scientific evidence.
Results: A number of computational pipelines for neoantigen prediction are available. Most of them provide peptide major histocompatibility complex (MHC) binding affinity predictions, but more recent approaches incorporate additional features like variant allele fraction, gene expression, and clonality of mutations. Neoantigens can be predicted in all cancer types with high and low tumour mutation burden, in part by exploiting tumour-specific aberrations derived from mutational frameshifts, splice variants, gene fusions, endogenous retroelements and other tumour-specific processes that could yield more potently immunogenic tumour neoantigens. Ongoing clinical trials will highlight those cancer types and combinations of immune therapies that would derive the most benefit from neoantigen-based immunotherapies.
Conclusions: Improved identification, selection and prioritisation of tumour-specific neoantigens are needed to increase the scope of benefit from cancer vaccines and adoptive T-cell therapies. Novel pipelines are being developed to resolve the challenges posed by high-throughput sequencing and to predict immunogenic neoantigens.
Filiaciones:
:
Hosp Univ Trias & Pujol, IrsiCaixa, Badalona, Spain
Germans Trias & Pujol Res Inst IGTP, Badalona, Spain
Vazquez, M:
Barcelona Supercomp Ctr, Barcelona, Spain
Finotello, F:
Med Univ Innsbruck, Inst Bioinformat, Bioctr, Innsbruck, Austria
Lepore, R:
Barcelona Supercomp Ctr, Barcelona, Spain
:
Barcelona Supercomp Ctr, Barcelona, Spain
Josep Carreras Leukaemia Res Inst IJC, Badalona, Spain
Hundal, J:
Washington Univ, McDonnell Genome Inst, St Louis, MO 63110 USA
Amengual-Rigo, P:
Barcelona Supercomp Ctr, Barcelona, Spain
Ng, CKY:
Univ Bern, Dept BioMed Res, Bern, Switzerland
Valencia, A:
Barcelona Supercomp Ctr, Barcelona, Spain
Inst Catalana Recerca & Estudis Avancats ICREA, Barcelona, Spain
:
Hosp Univ Trias & Pujol, IrsiCaixa, Badalona, Spain
Germans Trias & Pujol Res Inst IGTP, Badalona, Spain
Chan, TA:
Cleveland Clin, Ctr Immunotherapy & Precis Immunooncol, Cleveland, OH 44106 USA
Guallar, V:
Barcelona Supercomp Ctr, Barcelona, Spain
Inst Catalana Recerca & Estudis Avancats ICREA, Barcelona, Spain
McGranahan, N:
Canc Res UK Lung Canc Ctr Excellence, London, England
UCL, Inst Canc, Canc Genome Evolut Res Grp, London, England
:
Hosp Univ Trias & Pujol, IrsiCaixa, Badalona, Spain
Germans Trias & Pujol Res Inst IGTP, Badalona, Spain
Univ Vic Univ Cent Catalunya UVIC UCC, Vic, Spain
Griffith, M:
Washington Univ, Sch Med, Dept Med, St Louis, MO 63110 USA
Bronze, Green Accepted
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