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Nat Rev Clin Oncol . 2020 Jun 22

Towards new horizons: characterization, classification and implications of the tumour antigenic repertoire

Joel Selkrig, Nan Li, Annika Hausmann, Matthew S J Mangan, Matylda Zietek, André Mateus, Jacob Bobonis, Anna Sueki, Haruna Imamura, Bachir El Debs, Gianluca Sigismondo, Bogdan I Florea, Herman S Overkleeft, Nataša Kopitar-Jerala, Boris Turk, Pedro Beltrao, Mikhail M Savitski, Eicke Latz, Wolf-Dietrich Hardt, Jeroen Krijgsveld, Athanasios Typas, Sebastian P Haen, Markus W Löffler, Hans-Georg Rammensee, Peter Brossart

Immune-checkpoint inhibition provides an unmatched level of durable clinical efficacy in various malignancies. Such therapies promote the activation of antigen-specific T cells, although the precise targets of these T cells remain unknown. Exploiting these targets holds great potential to amplify responses to treatment, such as by combining immune-checkpoint inhibition with therapeutic vaccination or other antigen-directed treatments. In this scenario, the pivotal hurdle remains the definition of valid HLA-restricted tumour antigens, which requires several levels of evidence before targets can be established with sufficient confidence. Suitable antigens might include tumour-specific antigens with alternative or wild-type sequences, tumour-associated antigens and cryptic antigens that exceed exome boundaries. Comprehensive antigen classification is required to enable future clinical development and the definition of innovative treatment strategies. Furthermore, clinical development remains challenging with regard to drug manufacturing and regulation, as well as treatment feasibility. Despite these challenges, treatments based on diligently curated antigens combined with a suitable therapeutic platform have the potential to enable optimal antitumour efficacy in patients, either as monotherapies or in combination with other established immunotherapies. In this Review, we summarize the current state-of-the-art approaches for the identification of candidate tumour antigens and provide a structured terminology based on their underlying characteristics.

PMID: 32572208