Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Correspondence
  • Published:

Ultrasensitive detection of TCR hypervariable-region sequences in solid-tissue RNA–seq data

Nature Genetics volume 49, pages 482–483 (2017)Cite this article

Subjects

To the Editor:

Neoantigen-specific tumor-infiltrating T lymphocytes are immune effector cells for cancer elimination and are the primary focus of current cancer immunotherapies1,2,3,4. We previously published a novel method to assemble T cell receptor (TCR) complementarity-determining region 3 (CDR3) sequences using paired-end tumor RNA–seq data5. Extending this approach, we have developed 'TCR repertoire utilities for solid tissue', or TRUST, for ultrasensitive detection of tumor-infiltrating T cell CDR3 sequences (Supplementary Software). TRUST significantly outperforms our previous method, with a substantial increase in recall (Supplementary Fig. 1a), especially for libraries with deeper coverage and longer read length (Supplementary Fig. 1b). In addition to exhibiting improved performance, TRUST can also handle single-end RNA–seq data and has demonstrated utility for non-cancerous tissues.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Evaluation of the performance of TRUST in single-end mode.

References

  1. Fridman, W.H., Pages, F., Sautes-Fridman, C. & Galon, J. Nat. Rev. Cancer 12, 298–306 (2012).

    Article  CAS  PubMed  Google Scholar 

  2. Gajewski, T.F., Schreiber, H. & Fu, Y.X. Nat. Immunol. 14, 1014–1022 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Matsushita, H. et al. Nature 482, 400–404 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Snyder, A. et al. N. Engl. J. Med. 371, 2189–2199 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Li, B. et al. Nat. Genet. 48, 725–732 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Lefranc, M.P. Cold Spring Harb. Protoc. 2011, 595–603 (2011).

    PubMed  Google Scholar 

  7. Warren, R.L., Nelson, B.H. & Holt, R.A. Bioinformatics 25, 458–464 (2009).

    Article  CAS  PubMed  Google Scholar 

  8. Bolotin, D.A. et al. Nat. Methods 12, 380–381 (2015).

    Article  CAS  PubMed  Google Scholar 

  9. Thomas, N., Heather, J., Ndifon, W., Shawe-Taylor, J. & Chain, B. Bioinformatics 29, 542–550 (2013).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We acknowledge the following funding sources for supporting our work: NCI grant 1U01 CA180980 and National Natural Science Foundation of China grants 31329003 (to X.S.L.), 31601077 (to R.D.) and 81321002 (to T.L.).

Author information

Authors and Affiliations

  1. Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA

    Bo Li, Jian Zhang & X Shirley Liu

  2. Department of Statistics, Harvard University, Cambridge, Massachusetts, USA

    Bo Li, Jun S Liu & X Shirley Liu

  3. State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China

    Taiwen Li

  4. School of Life Science and Technology, Tongji University, Shanghai, China

    Binbin Wang & X Shirley Liu

  5. Department of Colorectal Surgery, Sixth Affiliated Hospital, Sun Yat-sen University, Guangdong, China

    Ruoxu Dou

Authors
  1. Bo Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Taiwen Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Binbin Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ruoxu Dou
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jian Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jun S Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. X Shirley Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Bo Li or X Shirley Liu.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Figures and Texts

Supplementary Figures 1–4 and Supplementary Note (PDF 647 kb)

Supplementary Software

Source code and support data. (ZIP 549 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, B., Li, T., Wang, B. et al. Ultrasensitive detection of TCR hypervariable-region sequences in solid-tissue RNA–seq data. Nat Genet 49, 482–483 (2017). https://doi.org/10.1038/ng.3820

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ng.3820

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer