Mining exomic sequencing data to identify mutated antigens recognized by adoptively transferred tumor-reactive T cells

Paul F. Robbins, Yong Chen Lu, Mona El-Gamil, Yong F. Li, Colin Gross, Jared Gartner, Jimmy C. Lin, Jamie K. Teer, Paul Cliften, Eric Tycksen, Yardena Samuels, Steven A. Rosenberg

Research output: Contribution to journalArticlepeer-review

Abstract

Substantial regressions of metastatic lesions have been observed in up to 70% of patients with melanoma who received adoptively transferred autologous tumor-infiltrating lymphocytes (TILs) in phase 2 clinical trials. In addition, 40% of patients treated in a recent trial experienced complete regressions of all measurable lesions for at least 5 years following TIL treatment. To evaluate the potential association between the ability of TILs to mediate durable regressions and their ability to recognize potent antigens that presumably include mutated gene products, we developed a new screening approach involving mining whole-exome sequence data to identify mutated proteins expressed in patient tumors. We then synthesized and evaluated candidate mutated T cell epitopes that were identified using a major histocompatibility complex-binding algorithm for recognition by TILs. Using this approach, we identified mutated antigens expressed on autologous tumor cells that were recognized by three bulk TIL lines from three individuals with melanoma that were associated with objective tumor regressions following adoptive transfer. This simplified approach for identifying mutated antigens recognized by T cells avoids the need to generate and laboriously screen cDNA libraries from tumors and may represent a generally applicable method for identifying mutated antigens expressed in a variety of tumor types.

Original languageEnglish (US)
Pages (from-to)747-752
Number of pages6
JournalNature medicine
Volume19
Issue number6
DOIs
StatePublished - Jun 2013

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)

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