The problem with neoantigen prediction

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2022-01-13 23:00:08

Nature Biotechnology volume  35, page 97 (2017 )Cite this article

Last December, the newly minted Parker Institute for Cancer Immunotherapy and its venerable East Coast counterpart, the Cancer Research Institute, announced the formation of the Tumor Neoantigen Selection Alliance. This initiative, involving researchers from 30 universities, non-profit institutions and companies, aims to identify software that can best predict mutation-associated cancer antigens, also known as neoantigens, from patient tumor DNA. The hope is that solving the shortcomings of current in silico methods for identifying neoantigens will galvanize a new wave of personalized cancer immunotherapies. But, for now, computational prediction of neoantigens capable of eliciting efficacious antitumor responses in patients remains a hit-or-miss affair.

Cancer vaccines have traditionally targeted tumor-associated self-antigens—proteins that may be aberrantly expressed in cancer cells. More recently, however, attention has shifted to neoantigens. Targeting an individual's tumor-specific mutations is attractive because these peptides are new to the immune system and are not found in normal tissues. Compared with tumor-associated self-antigens, neoantigens elicit T-cell responses not subject to host central tolerance in the thymus and also produce fewer toxicities arising from autoimmune reactions to non-malignant cells.

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