Letter | Published:

Predicting immunogenic tumour mutations by combining mass spectrometry and exome sequencing

Nature volume 515, pages 572576 (27 November 2014) | Download Citation


Human tumours typically harbour a remarkable number of somatic mutations1. If presented on major histocompatibility complex class I molecules (MHCI), peptides containing these mutations could potentially be immunogenic as they should be recognized as ‘non-self’ neo-antigens by the adaptive immune system. Recent work has confirmed that mutant peptides can serve as T-cell epitopes2,3,4,5,6,7,8,9. However, few mutant epitopes have been described because their discovery required the laborious screening of patient tumour-infiltrating lymphocytes for their ability to recognize antigen libraries constructed following tumour exome sequencing. We sought to simplify the discovery of immunogenic mutant peptides by characterizing their general properties. We developed an approach that combines whole-exome and transcriptome sequencing analysis with mass spectrometry to identify neo-epitopes in two widely used murine tumour models. Of the >1,300 amino acid changes identified, 13% were predicted to bind MHCI, a small fraction of which were confirmed by mass spectrometry. The peptides were then structurally modelled bound to MHCI. Mutations that were solvent-exposed and therefore accessible to T-cell antigen receptors were predicted to be immunogenic. Vaccination of mice confirmed the approach, with each predicted immunogenic peptide yielding therapeutically active T-cell responses. The predictions also enabled the generation of peptide–MHCI dextramers that could be used to monitor the kinetics and distribution of the anti-tumour T-cell response before and after vaccination. These findings indicate that a suitable prediction algorithm may provide an approach for the pharmacodynamic monitoring of T-cell responses as well as for the development of personalized vaccines in cancer patients.

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The authors thank A. Bruce and J. Murphy for excellent assistance with artwork.

Author information

Author notes

    • Mahesh Yadav
    •  & Suchit Jhunjhunwala

    These authors contributed equally to this work.

    • Jennie R. Lill
    •  & Lélia Delamarre

    These authors jointly supervised this work.


  1. Genentech, South San Francisco, California 94080, USA

    • Mahesh Yadav
    • , Suchit Jhunjhunwala
    • , Qui T. Phung
    • , Patrick Lupardus
    • , Joshua Tanguay
    • , Stephanie Bumbaca
    • , Christian Franci
    • , Tommy K. Cheung
    • , Zora Modrusan
    • , Ira Mellman
    • , Jennie R. Lill
    •  & Lélia Delamarre
  2. Immatics Biotechnologies GmbH, 72076 Tubingen, Germany

    • Jens Fritsche
    •  & Toni Weinschenk


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M.Y. was involved in planning and performing in vivo experiments, analysing and interpreting data, and writing the manuscript. S.J. analysed and interpreted whole-exome sequencing and RNA sequencing data, generated translated FASTA database, searched for potential neo-epitopes. Q.T.P. and T.K.C. performed mass spectrometric data analysis and peptide validation. P.L. performed the structure prediction of the MHCI–peptide complexes. J.T. performed studies with tumour-bearing mice. S.B. performed and analysed FACS studies on tumour lines. C.F. performed and analysed immunizations experiments. Z.M. oversaw RNA sequencing experiments. I.M. assisted with the study design and the preparation of the manuscript. J.F. and T.W. performed MHCI peptide isolation and mass spectrometric analysis. L.D and J.R.L. oversaw all the work performed, planned experiments, interpreted data and wrote the manuscript.

Competing interests

Mahesh Yadav, Suchit Jhunjhunwala, Qui T. Phung, Patrick Lupardus, Joshua Tanguay, Stephanie Bumbaca, Christian Franci, Tommy K. Cheung, Zora Modrusan, Ira Mellman, Jennie R. Lill, and Lélia Delamarre were employees of Genentech at the time of the work. Jens Fritsche and Toni Weinschenk were employees of Immatics Biotechnologies GmbH at the time of the work. They hence declare competing financial interests.

Corresponding authors

Correspondence to Jennie R. Lill or Lélia Delamarre.

Extended data

Supplementary information

Excel files

  1. 1.

    Supplementary Table 1

    This table contains variant peptides (MC-38).

  2. 2.

    Supplementary Table 2

    This table contains variant peptides (TRAMP-C1).

  3. 3.

    Supplementary Table 3

    This table contains peptides identified by LC-MS.

  4. 4.

    Supplementary Table 4

    This table contains RNA-Seq-based expression data for all genes in MC-38 and TRAMP-C1.

  5. 5.

    Supplementary Table 5

    This table contains MHC Class I-presented variant peptides.

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