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.

Cellular and Molecular Biology

Somatic mutations in DCC are associated with genomic instability and favourable outcomes in melanoma patients treated with immune checkpoint inhibitors

Abstract

Background

Deleted in colorectal cancer (DCC) encodes a transmembrane dependence receptor and is frequently mutated in melanoma. The associations of DCC mutation with chromosomal instability and immunotherapeutic efficacy in melanoma are largely uncharacterised.

Methods

We performed an integrated study based on biological experiments and multi-dimensional data types, including genomic, transcriptomic and clinical immune checkpoint blockade (ICB)-treated melanoma cohorts from public databases.

Results

DCC mutation was significantly correlated with the tumour mutational burden (TMB) in The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and ICB-treated melanoma cohorts. DCC expression levels were correlated with DNA damage response and repair (DDR) pathways responsive to irradiation (IR) in the Malme-3M and SK-MEL-2 cell lines. In the TCGA cohort, DCC-mutated samples presented more neoantigens, higher proportions of infiltrating antitumour immunocytes and lower proportions of infiltrating pro-tumour immunocytes than DCC wild-type samples. DCC-mutated samples were significantly enriched in activated immune response and DDR pathways. Furthermore, patients harbouring mutated DCC treated with ICB showed remarkable clinical benefits in terms of the response rate and overall survival.

Conclusions

Somatic mutations in DCC are associated with improved clinical outcomes in ICB-treated melanoma patients. Once further validated, the DCC mutational status can improve patient selection for clinical practice and future study enrolment.

Your institute does not have access to this article

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Fig. 1: Mutation profile of DCC in relation to genes associated with genomic instability in the TCGA cohort containing 467 melanoma samples.
Fig. 2: Association of DCC mutation with a higher tumour mutational burden.
Fig. 3: Analysis of DDR activities response to irradiation in human melanoma cell lines.
Fig. 4: DCC expression is associated with the DNA damage repair signalling.
Fig. 5: DCC mutation correlated with more predicted neoantigens and a more activated immune infiltrate environment.
Fig. 6: Association of DCC mutation with better ICB therapeutic efficacy in the ICB-treated melanoma cohort.

Data availability

The datasets used in this study are available from the TCGA, ICGC and CCLE repositories. The ICB-treated melanoma datasets generated during the current study are available in six previous studies and their supplementary data files as described in the ‘Genomic and clinical data’ subsection. All data supporting the conclusions of this study have been included within the article and the Supplemental Data.

Code availability

The computer codes used to generate results that support the paper’s conclusions are available from the corresponding author upon reasonable request.

Materials availability

All materials supporting the conclusions of this study have been included in the article and the Supplemental Data.

References

  1. Larkin J, Chiarion-Sileni V, Gonzalez R, Grob JJ, Cowey CL, Lao CD, et al. Combined nivolumab and ipilimumab or monotherapy in untreated melanoma. N Engl J Med. 2015;373:23–34.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  2. Robert C, Schachter J, Long GV, Arance A, Grob JJ, Mortier L, et al. Pembrolizumab versus ipilimumab in advanced melanoma. N Engl J Med. 2015;372:2521–32.

    CAS  PubMed  Article  Google Scholar 

  3. Schadendorf D, Hodi FS, Robert C, Weber JS, Margolin K, Hamid O, et al. Pooled analysis of long-term survival data from phase II and phase III trials of ipilimumab in unresectable or metastatic melanoma. J Clin Oncol. 2015;33:1889–94.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  4. Wolchok JD, Chiarion-Sileni V, Gonzalez R, Rutkowski P, Grob J-J, Cowey CL, et al. Overall survival with combined nivolumab and ipilimumab in advanced melanoma. N Engl J Med. 2017;377:1345–56.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  5. Liu D, Schilling B, Liu D, Sucker A, Livingstone E, Jerby-Amon L, et al. Integrative molecular and clinical modeling of clinical outcomes to PD1 blockade in patients with metastatic melanoma. Nat Med. 2019;25:1916–27.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  6. Chan TA, Yarchoan M, Jaffee E, Swanton C, Quezada SA, Stenzinger A, et al. Development of tumor mutation burden as an immunotherapy biomarker: utility for the oncology clinic. Ann Oncol. 2019;30:44–56.

    CAS  PubMed  Article  Google Scholar 

  7. Snyder A, Makarov V, Merghoub T, Yuan J, Zaretsky JM, Desrichard A, et al. Genetic basis for clinical response to CTLA-4 blockade in melanoma. N Engl J Med. 2014;371:2189–99.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  8. Van Allen EM, Miao D, Schilling B, Shukla SA, Blank C, Zimmer L, et al. Genomic correlates of response to CTLA-4 blockade in metastatic melanoma. Science. 2015;350:207–11.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  9. Mouw KW, Goldberg MS, Konstantinopoulos PA, D’Andrea AD. DNA damage and repair biomarkers of immunotherapy response. Cancer Discov. 2017;7:675–93.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  10. Tang H, Wang Y, Chlewicki LK, Zhang Y, Guo J, Liang W, et al. Facilitating T cell infiltration in tumor microenvironment overcomes resistance to PD-L1 blockade. Cancer Cell. 2016;29:285–96.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  11. Tumeh PC, Harview CL, Yearley JH, Shintaku IP, Taylor EJ, Robert L, et al. PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature. 2014;515:568–71.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  12. Topalian SL, Taube JM, Anders RA, Pardoll DM. Mechanism-driven biomarkers to guide immune checkpoint blockade in cancer therapy. Nat Rev Cancer. 2016;16:275–87.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  13. Fearon ER, Cho KR, Nigro JM, Kern SE, Simons JW, Ruppert JM, et al. Identification of a chromosome 18q gene that is altered in colorectal cancers. Science. 1990;247:49–56.

    CAS  PubMed  Article  Google Scholar 

  14. Shibata D, Reale MA, Lavin P, Silverman M, Fearon ER, Steele G Jr, et al. The DCC protein and prognosis in colorectal cancer. N Engl J Med. 1996;335:1727–32.

    CAS  PubMed  Article  Google Scholar 

  15. Mehlen P, Fearon ER. Role of the dependence receptor DCC in colorectal cancer pathogenesis. J Clin Oncol. 2004;22:3420–8.

    CAS  PubMed  Article  Google Scholar 

  16. Goldschneider D, Mehlen P. Dependence receptors: a new paradigm in cell signaling and cancer therapy. Oncogene. 2010;29:1865–82.

    CAS  PubMed  Article  Google Scholar 

  17. Mehlen P, Tauszig-Delamasure S. Dependence receptors and colorectal cancer. Gut. 2014;63:1821–9.

    CAS  PubMed  Article  Google Scholar 

  18. Gibert B, Mehlen P. Dependence receptors and cancer: addiction to trophic ligands. Cancer Res. 2015;75:5171–5.

    CAS  PubMed  Article  Google Scholar 

  19. Krauthammer M, Kong Y, Ha BH, Evans P, Bacchiocchi A, McCusker JP, et al. Exome sequencing identifies recurrent somatic RAC1 mutations in melanoma. Nat Genet. 2012;44:1006–14.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  20. Boussouar A, Tortereau A, Manceau A, Paradisi A, Gadot N, Vial J, et al. Netrin-1 and its receptor DCC are causally implicated in melanoma progression. Cancer Res. 2020;80:747–56.

    CAS  PubMed  Article  Google Scholar 

  21. Alexandrov LB, Nik-Zainal S, Wedge DC, Aparicio SAJR, Behjati S, Biankin AV, et al. Signatures of mutational processes in human cancer. Nature. 2013;500:415–21.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  22. Alexandrov LB, Kim J, Haradhvala NJ, Huang MN, Tian Ng AW, Wu Y, et al. The repertoire of mutational signatures in human cancer. Nature. 2020;578:94–101.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  23. Boland CR, Goel A. Microsatellite instability in colorectal cancer. Gastroenterology. 2010;138:2073–87.e3.

    CAS  PubMed  Article  Google Scholar 

  24. Le DT, Durham JN, Smith KN, Wang H, Bartlett BR, Aulakh LK, et al. Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade. Science. 2017;357:409–13.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  25. Ghandi M, Huang FW, Jané-Valbuena J, Kryukov GV, Lo CC, McDonald ER, et al. Next-generation characterization of the Cancer Cell Line Encyclopedia. Nature. 2019;569:503–8.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  26. Hugo W, Zaretsky JM, Sun L, Song C, Moreno BH, Hu-Lieskovan S, et al. Genomic and transcriptomic features of response to anti-PD-1 therapy in metastatic melanoma. Cell. 2016;165:35–44.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  27. Zaretsky JM, Garcia-Diaz A, Shin DS, Escuin-Ordinas H, Hugo W, Hu-Lieskovan S, et al. Mutations associated with acquired resistance to PD-1 blockade in melanoma. N Engl J Med. 2016;375:819–29.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  28. Riaz N, Havel JJ, Makarov V, Desrichard A, Urba WJ, Sims JS, et al. Tumor and microenvironment evolution during immunotherapy with nivolumab. Cell. 2017;171:934–49.e16.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  29. Roh W, Chen P-L, Reuben A, Spencer CN, Prieto PA, Miller JP, et al. Integrated molecular analysis of tumor biopsies on sequential CTLA-4 and PD-1 blockade reveals markers of response and resistance. Sci Transl Med. 2017;9:eaah3560.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  30. Ramos AH, Lichtenstein L, Gupta M, Lawrence MS, Pugh TJ, Saksena G, et al. Oncotator: cancer variant annotation tool. Hum Mutat. 2015;36:E2423–9.

    PubMed  PubMed Central  Article  Google Scholar 

  31. Knijnenburg TA, Wang L, Zimmermann MT, Chambwe N, Gao GF, Cherniack AD, et al. Genomic and molecular landscape of DNA damage repair deficiency across The Cancer Genome Atlas. Cell Rep. 2018;23:239–54.e6.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  32. Wang H, Song M. Ckmeans.1d.dp: optimal k-means clustering in one dimension by dynamic programming. R J. 2011;3:29–33.

    PubMed  PubMed Central  Article  Google Scholar 

  33. Kim J, Mouw KW, Polak P, Braunstein LZ, Kamburov A, Kwiatkowski DJ, et al. Somatic ERCC2 mutations are associated with a distinct genomic signature in urothelial tumors. Nat Genet. 2016;48:600–6.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  34. Yarchoan M, Johnson BA 3rd, Lutz ER, Laheru DA, Jaffee EM. Targeting neoantigens to augment antitumour immunity. Nat Rev Cancer. 2017;17:209–22.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  35. Rooney MS, Shukla SA, Wu CJ, Getz G, Hacohen N. Molecular and genetic properties of tumors associated with local immune cytolytic activity. Cell. 2015;160:48–61.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  36. Shukla SA, Rooney MS, Rajasagi M, Tiao G, Dixon PM, Lawrence MS, et al. Comprehensive analysis of cancer-associated somatic mutations in class I HLA genes. Nat Biotechnol. 2015;33:1152–8.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  37. Charoentong P, Finotello F, Angelova M, Mayer C, Efremova M, Rieder D, et al. Pan-cancer immunogenomic analyses reveal genotype-immunophenotype relationships and predictors of response to checkpoint blockade. Cell Rep. 2017;18:248–62.

    CAS  PubMed  Article  Google Scholar 

  38. Newman AM, Liu CL, Green MR, Gentles AJ, Feng W, Xu Y, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015;12:453–7.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  39. Pardoll DM. The blockade of immune checkpoints in cancer immunotherapy. Nat Rev Cancer. 2012;12:252–64.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  40. Burugu S, Dancsok AR, Nielsen TO. Emerging targets in cancer immunotherapy. Semin Cancer Biol. 2018;52:39–52.

    CAS  PubMed  Article  Google Scholar 

  41. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA. 2005;102:15545–50.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  42. Liberzon A, Subramanian A, Pinchback R, Thorvaldsdottir H, Tamayo P, Mesirov JP. Molecular signatures database (MSigDB) 3.0. Bioinformatics. 2011;27:1739–40.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  43. Skidmore ZL, Wagner AH, Lesurf R, Campbell KM, Kunisaki J, Griffith OL, et al. GenVisR: genomic visualizations in R. Bioinformatics. 2016;32:3012–4.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  44. Lee JH, Paull TT. Direct activation of the ATM protein kinase by the Mre11/Rad50/Nbs1 complex. Science. 2004;304:93–6.

    CAS  PubMed  Article  Google Scholar 

  45. Carson CT, Schwartz RA, Stracker TH, Lilley CE, Lee DV, Weitzman MD. The Mre11 complex is required for ATM activation and the G2/M checkpoint. EMBO J. 2003;22:6610–20.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  46. Gatei M, Scott SP, Filippovitch I, Soronika N, Lavin MF, Weber B, et al. Role for ATM in DNA damage-induced phosphorylation of BRCA1. Cancer Res. 2000;60:3299–304.

    CAS  PubMed  Google Scholar 

  47. Prakash R, Zhang Y, Feng W, Jasin M. Homologous recombination and human health: the roles of BRCA1, BRCA2, and associated proteins. Cold Spring Harb Perspect Biol. 2015;7:a016600.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  48. Chen YQ, Hsieh JT, Yao F, Fang B, Pong RC, Cipriano SC, et al. Induction of apoptosis and G2/M cell cycle arrest by DCC. Oncogene. 1999;18:2747–54.

    CAS  PubMed  Article  Google Scholar 

  49. Castets M, Broutier L, Molin Y, Brevet M, Chazot G, Gadot N, et al. DCC constrains tumour progression via its dependence receptor activity. Nature. 2011;482:534–7.

    PubMed  Article  CAS  Google Scholar 

  50. Hedrick L, Cho KR, Fearon ER, Wu TC, Kinzler KW, Vogelstein B. The DCC gene product in cellular differentiation and colorectal tumorigenesis. Genes Dev. 1994;8:1174–83.

    CAS  PubMed  Article  Google Scholar 

  51. Bernet A, Fitamant J. Netrin-1 and its receptors in tumour growth promotion. Expert Opin Ther Targets. 2008;12:995–1007.

    CAS  PubMed  Article  Google Scholar 

  52. Yang L, Garbe DS, Bashaw GJ. A frazzled/DCC-dependent transcriptional switch regulates midline axon guidance. Science. 2009;324:944–7.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  53. Neuhaus-Follini A, Bashaw GJ. The intracellular domain of the Frazzled/DCC receptor is a transcription factor required for commissural axon guidance. Neuron. 2015;87:751–63.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  54. Fitamant J, Guenebeaud C, Coissieux M-M, Guix C, Treilleux I, Scoazec J-Y, et al. Netrin-1 expression confers a selective advantage for tumor cell survival in metastatic breast cancer. Proc Natl Acad Sci USA. 2008;105:4850–5.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  55. Grandin M, Mathot P, Devailly G, Bidet Y, Ghantous A, Favrot C, et al. Inhibition of DNA methylation promotes breast tumor sensitivity to netrin-1 interference. EMBO Mol Med. 2016;8:863–77.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  56. Paradisi A, Creveaux M, Gibert B, Devailly G, Redoulez E, Neves D, et al. Combining chemotherapeutic agents and netrin-1 interference potentiates cancer cell death. EMBO Mol Med. 2013;5:1821–34.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank all patients with melanoma who kindly donated samples for the TCGA and ICGC projects. The authors sincerely appreciated all of the data-sharing platforms, such as the TCGA, ICGC and CCLE. The authors would like to thank the colleagues from our department for their assistance.

Funding

This work was supported by the National Natural Science Foundation of China (81372429 to Lujun Zhao).

Author information

Authors and Affiliations

Authors

Contributions

YL had full access to perform experiments and statistical analysis in this study. LZ conceived and designed this study. All authors performed acquisition, analyses, or interpretation of data. YL drafted of the manuscript under close supervision and critical revision of LZ. All authors contributed paper writing and proofreading.

Corresponding author

Correspondence to Lujun Zhao.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

Not applicable.

Consent to publish

Not applicable.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Li, Y., Wang, Q., Chen, Y. et al. Somatic mutations in DCC are associated with genomic instability and favourable outcomes in melanoma patients treated with immune checkpoint inhibitors. Br J Cancer (2022). https://doi.org/10.1038/s41416-022-01921-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41416-022-01921-4

Search

Quick links