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.

Lymphoma

Genotyping circulating tumor DNA of pediatric Hodgkin lymphoma

Abstract

We used hybrid capture-targeted next-generation sequencing of circulating cell-free DNA (ccfDNA) of pediatric Hodgkin lymphoma (PHL) patients to determine pathogenic mechanisms and assess the clinical utility of this method. Hodgkin-Reed/Sternberg (HRS) cell-derived single nucleotide variants, insertions/deletions, translocations and VH-DH-JH rearrangements were detected in pretherapy ccfDNA of 72 of 96 patients. Number of variants per patient ranged from 1 to 21 with allele frequencies from 0.6 to 42%. Nine translocation breakpoints were detected. Genes involved in JAK/STAT, NFkB and PI3K signaling and antigen presentation were most frequently affected. SOCS1 variants, mainly deletions, were found in most circulating tumor (ct) DNAs, and seven of the nine translocation breakpoints involved SOCS1. Analysis of VH-DH-JH rearrangements revealed an origin of PHL HRS cells from partially selected germinal center B cells. Amounts of pretherapy ctDNA were correlated with metabolic tumor volumes. Furthermore, in all ccfDNA samples of 43 patients with early response assessment quantitative qPET < 3, indicative of a favorable clinical course, ctDNA was not detectable. In contrast, in five of six patients with qPET > 3, indicative of an unfavorable clinical course, ctDNA remained detectable. ccfDNA analysis of PHL is thus a suitable approach to determine pathogenic mechanisms and monitor therapy response.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

References

  1. 1.

    Mauz-Korholz C, Metzger ML, Kelly KM, Schwartz CL, Castellanos ME, Dieckmann K. et al. Pediatric Hodgkin lymphoma. J Clin Oncol. 2015;33:2975–85.

    PubMed  Google Scholar 

  2. 2.

    Castellino SM, Geiger AM, Mertens AC, Leisenring WM, Tooze JA, Goodman P, et al. Morbidity and mortality in long-term survivors of Hodgkin lymphoma: a report from the Childhood Cancer Survivor Study. Blood. 2011;117:1806–16.

    CAS  PubMed  PubMed Central  Google Scholar 

  3. 3.

    Dorffel W, Riepenhausenl M, Luders H, Bramswig J, Schellong G. Secondary malignancies following treatment for Hodgkin’s lymphoma in childhood and adolescence. Dtsch Arztebl Int. 2015;112:320–7. i

    PubMed  PubMed Central  Google Scholar 

  4. 4.

    Schaapveld M, Aleman BM, van Eggermond AM, Janus CP, Krol AD, van der Maazen RW, et al. Second cancer risk up to 40 years after treatment for Hodgkin’s lymphoma. N Engl J Med. 2015;373:2499–511.

    CAS  PubMed  Google Scholar 

  5. 5.

    Barros MH, Hassan R, Niedobitek G. Tumor-associated macrophages in pediatric classical Hodgkin lymphoma: association with Epstein−Barr virus, lymphocyte subsets, and prognostic impact. Clin Cancer Res. 2012;18:3762–71.

    CAS  PubMed  Google Scholar 

  6. 6.

    Barros MH, Vera-Lozada G, Soares FA, Niedobitek G, Hassan R. Tumor microenvironment composition in pediatric classical Hodgkin lymphoma is modulated by age and Epstein−Barr virus infection. Int J Cancer. 2012;131:1142–52.

    CAS  PubMed  Google Scholar 

  7. 7.

    Wan JCM, Massie C, Garcia-Corbacho J, Mouliere F, Brenton JD, Caldas C, et al. Liquid biopsies come of age: towards implementation of circulating tumour DNA. Nat Rev Cancer. 2017;17:223–38.

    CAS  PubMed  Google Scholar 

  8. 8.

    Kurtz DM, Green MR, Bratman SV, Scherer F, Liu CL, Kunder CA, et al. Noninvasive monitoring of diffuse large B-cell lymphoma by immunoglobulin high-throughput sequencing. Blood. 2015;125:3679–87.

    CAS  PubMed  PubMed Central  Google Scholar 

  9. 9.

    Oberle A, Brandt A, Voigtlaender M, Thiele B, Radloff J, Schulenkorf A, et al. Monitoring multiple myeloma by next-generation sequencing of V(D)J rearrangements from circulating myeloma cells and cell-free myeloma DNA. Haematologica. 2017;102:1105–11.

    CAS  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Roschewski M, Dunleavy K, Pittaluga S, Moorhead M, Pepin F, Kong K, et al. Circulating tumour DNA and CT monitoring in patients with untreated diffuse large B-cell lymphoma: a correlative biomarker study. Lancet Oncol. 2015;16:541–9.

    PubMed  PubMed Central  Google Scholar 

  11. 11.

    Rossi D, Diop F, Spaccarotella E, Monti S, Zanni M, Rasi S, et al. Diffuse large B-cell lymphoma genotyping on the liquid biopsy. Blood. 2017;129:1947–57.

    CAS  PubMed  Google Scholar 

  12. 12.

    Scherer F, Kurtz DM, Newman AM, Stehr H, Craig AF, Esfahani MS. et al. Distinct biological subtypes and patterns of genome evolution in lymphoma revealed by circulating tumor DNA. Sci Transl Med. 2016;8:364ra155

    PubMed  PubMed Central  Google Scholar 

  13. 13.

    Bessi L, Viailly PJ, Bohers E, Ruminy P, Maingonnat C, Bertrand P, et al. Somatic mutations of cell-free circulating DNA detected by targeted next-generation sequencing and digital droplet PCR in classical Hodgkin lymphoma. Leuk Lymphoma. 2019;60:498–502.

    Google Scholar 

  14. 14.

    Camus V, Stamatoullas A, Mareschal S, Viailly PJ, Sarafan-Vasseur N, Bohers E, et al. Detection and prognostic value of recurrent exportin 1 mutations in tumor and cell-free circulating DNA of patients with classical Hodgkin lymphoma. Haematologica. 2016;101:1094–101.

    CAS  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Oki Y, Neelapu SS, Fanale M, Kwak LW, Fayad L, Rodriguez MA, et al. Detection of classical Hodgkin lymphoma specific sequence in peripheral blood using a next-generation sequencing approach. Br J Haematol. 2015;169:689–93.

    CAS  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Spina V, Bruscaggin A, Cuccaro A, Martini M, Di Trani M, Forestieri G, et al. Circulating tumor DNA reveals genetics, clonal evolution and residual disease in classical Hodgkin lymphoma. Blood. 2018;131:2413–25.

    CAS  PubMed  Google Scholar 

  17. 17.

    Vandenberghe P, Wlodarska I, Tousseyn T, Dehaspe L, Dierickx D, Verheecke M, et al. Non-invasive detection of genomic imbalances in Hodgkin/Reed-Sternberg cells in early and advanced stage Hodgkin’s lymphoma by sequencing of circulating cell-free DNA: a technical proof-of-principle study. Lancet Haematol. 2015;2:e55–65.

    PubMed  Google Scholar 

  18. 18.

    Hasenclever D, Kurch L, Mauz-Korholz C, Elsner A, Georgi T, Wallace H, et al. qPET—a quantitative extension of the Deauville scale to assess response in interim FDG-PET scans in lymphoma. Eur J Nucl Med Mol Imaging. 2014;41:1301–8.

    PubMed  Google Scholar 

  19. 19.

    Bea S, Valdes-Mas R, Navarro A, Salaverria I, Martin-Garcia D, Jares P, et al. Landscape of somatic mutations and clonal evolution in mantle cell lymphoma. Proc Natl Acad Sci USA. 2013;110:18250–5.

    CAS  PubMed  Google Scholar 

  20. 20.

    Clipson A, Wang M, de Leval L, Ashton-Key M, Wotherspoon A, Vassiliou G, et al. KLF2 mutation is the most frequent somatic change in splenic marginal zone lymphoma and identifies a subset with distinct genotype. Leukemia. 2015;29:1177–85.

    CAS  PubMed  Google Scholar 

  21. 21.

    Green MR, Gentles AJ, Nair RV, Irish JM, Kihira S, Liu CL, et al. Hierarchy in somatic mutations arising during genomic evolution and progression of follicular lymphoma. Blood. 2013;121:1604–11.

    CAS  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Green MR, Kihira S, Liu CL, Nair RV, Salari R, Gentles AJ, et al. Mutations in early follicular lymphoma progenitors are associated with suppressed antigen presentation. Proc Natl Acad Sci USA. 2015;112:E1116–1125.

    CAS  PubMed  Google Scholar 

  23. 23.

    Guieze R, Robbe P, Clifford R, de Guibert S, Pereira B, Timbs A, et al. Presence of multiple recurrent mutations confers poor trial outcome of relapsed/refractory CLL. Blood. 2015;126:2110–7.

    CAS  PubMed  Google Scholar 

  24. 24.

    Kiel MJ, Velusamy T, Betz BL, Zhao L, Weigelin HG, Chiang MY, et al. Whole-genome sequencing identifies recurrent somatic NOTCH2 mutations in splenic marginal zone lymphoma. J Exp Med. 2012;209:1553–65.

    CAS  PubMed  PubMed Central  Google Scholar 

  25. 25.

    Kridel R, Meissner B, Rogic S, Boyle M, Telenius A, Woolcock B, et al. Whole transcriptome sequencing reveals recurrent NOTCH1 mutations in mantle cell lymphoma. Blood. 2012;119:1963–71.

    CAS  PubMed  Google Scholar 

  26. 26.

    Landau DA, Carter SL, Stojanov P, McKenna A, Stevenson K, Lawrence MS. et al. Evolution and impact of subclonal mutations in chronic lymphocytic leukemia. Cell. 2013;152:714–26.

    CAS  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Li H, Kaminski MS, Li Y, Yildiz M, Ouillette P, Jones S, et al. Mutations in linker histone genes HIST1H1 B, C, D, and E; OCT2 (POU2F2); IRF8; and ARID1A underlying the pathogenesis of follicular lymphoma. Blood. 2014;123:1487–98.

    CAS  PubMed  PubMed Central  Google Scholar 

  28. 28.

    Lohr JG, Stojanov P, Carter SL, Cruz-Gordillo P, Lawrence MS, Auclair D, et al. Widespread genetic heterogeneity in multiple myeloma: implications for targeted therapy. Cancer Cell. 2014;25:91–101.

    CAS  PubMed  PubMed Central  Google Scholar 

  29. 29.

    Lohr JG, Stojanov P, Lawrence MS, Auclair D, Chapuy B, Sougnez C, et al. Discovery and prioritization of somatic mutations in diffuse large B-cell lymphoma (DLBCL) by whole-exome sequencing. Proc Natl Acad Sci USA. 2012;109:3879–84.

    CAS  PubMed  Google Scholar 

  30. 30.

    Love C, Sun Z, Jima D, Li G, Zhang J, Miles R, et al. The genetic landscape of mutations in Burkitt lymphoma. Nat Genet. 2012;44:1321–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  31. 31.

    Morin RD, Mungall K, Pleasance E, Mungall AJ, Goya R, Huff RD, et al. Mutational and structural analysis of diffuse large B-cell lymphoma using whole-genome sequencing. Blood. 2013;122:1256–65.

    CAS  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Okosun J, Bodor C, Wang J, Araf S, Yang CY, Pan C, et al. Integrated genomic analysis identifies recurrent mutations and evolution patterns driving the initiation and progression of follicular lymphoma. Nat Genet. 2014;46:176–81.

    CAS  PubMed  Google Scholar 

  33. 33.

    Pasqualucci L, Trifonov V, Fabbri G, Ma J, Rossi D, Chiarenza A, et al. Analysis of the coding genome of diffuse large B-cell lymphoma. Nat Genet. 2011;43:830–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Quesada V, Ramsay AJ, Lopez-Otin C. Chronic lymphocytic leukemia with SF3B1 mutation. N Engl J Med. 2012;366:2530.

    CAS  PubMed  Google Scholar 

  35. 35.

    Richter J, Schlesner M, Hoffmann S, Kreuz M, Leich E, Burkhardt B, et al. Recurrent mutation of the ID3 gene in Burkitt lymphoma identified by integrated genome, exome and transcriptome sequencing. Nat Genet. 2012;44:1316–20.

    CAS  PubMed  Google Scholar 

  36. 36.

    Rossi D, Trifonov V, Fangazio M, Bruscaggin A, Rasi S, Spina V, et al. The coding genome of splenic marginal zone lymphoma: activation of NOTCH2 and other pathways regulating marginal zone development. J Exp Med. 2012;209:1537–51.

    CAS  PubMed  PubMed Central  Google Scholar 

  37. 37.

    Schmitz R, Young RM, Ceribelli M, Jhavar S, Xiao W, Zhang M, et al. Burkitt lymphoma pathogenesis and therapeutic targets from structural and functional genomics. Nature. 2012;490:116–20.

    CAS  PubMed  PubMed Central  Google Scholar 

  38. 38.

    Wang L, Lawrence MS, Wan Y, Stojanov P, Sougnez C, Stevenson K, et al. SF3B1 and other novel cancer genes in chronic lymphocytic leukemia. N Engl J Med. 2011;365:2497–506.

    CAS  PubMed  PubMed Central  Google Scholar 

  39. 39.

    Zhang J, Grubor V, Love CL, Banerjee A, Richards KL, Mieczkowski PA, et al. Genetic heterogeneity of diffuse large B-cell lymphoma. Proc Natl Acad Sci USA. 2013;110:1398–403.

    CAS  PubMed  Google Scholar 

  40. 40.

    Zhang J, Jima D, Moffitt AB, Liu Q, Czader M, Hsi ED, et al. The genomic landscape of mantle cell lymphoma is related to the epigenetically determined chromatin state of normal B cells. Blood. 2014;123:2988–96.

    CAS  PubMed  PubMed Central  Google Scholar 

  41. 41.

    Reichel J, Chadburn A, Rubinstein PG, Giulino-Roth L, Tam W, Liu Y, et al. Flow sorting and exome sequencing reveal the oncogenome of primary Hodgkin and Reed-Sternberg cells. Blood. 2015;125:1061–72.

    CAS  PubMed  Google Scholar 

  42. 42.

    Tiacci E, Penson A, Schiavoni G, Ladewig E, Fortini E, Wang Y, et al. New recurrently mutated genes in classical Hodgkin lymphoma revealed by whole-exome sequencing os microdissected tumor cells. Blood. 2016;218:1088.

    Google Scholar 

  43. 43.

    Raczy C, Petrovski R, Saunders CT, Chorny I, Kruglyak S, Margulies EH, et al. Isaac: ultra-fast whole-genome secondary analysis on Illumina sequencing platforms. Bioinformatics. 2013;29:2041–3.

    CAS  PubMed  PubMed Central  Google Scholar 

  44. 44.

    Kuppers R, Dalla-Favera R. Mechanisms of chromosomal translocations in B cell lymphomas. Oncogene. 2001;20:5580–94.

    CAS  PubMed  Google Scholar 

  45. 45.

    Martin-Subero JI, Klapper W, Sotnikova A, Callet-Bauchu E, Harder L, Bastard C, et al. Chromosomal breakpoints affecting immunoglobulin loci are recurrent in Hodgkin and Reed-Sternberg cells of classical Hodgkin lymphoma. Cancer Res. 2006;66:10332–8.

    CAS  PubMed  Google Scholar 

  46. 46.

    Tiacci E, Ladewig E, Schiavoni G, Penson A, Fortini E, Pettirossi V, et al. Pervasive mutations of JAK-STAT pathway genes in classical Hodgkin lymphoma. Blood. 2018;131:2454–65.

    CAS  PubMed  PubMed Central  Google Scholar 

  47. 47.

    Mansouri L, Noerenberg D, Young E, Mylonas E, Abdulla M, Frick M, et al. Frequent NFKBIE deletions are associated with poor outcome in primary mediastinal B-cell lymphoma. Blood. 2016;128:2666–70.

    CAS  PubMed  Google Scholar 

  48. 48.

    Pasqualucci L, Neumeister P, Goossens T, Nanjangud G, Chaganti RS, Kuppers R, et al. Hypermutation of multiple proto-oncogenes in B-cell diffuse large-cell lymphomas. Nature. 2001;412:341–6.

    CAS  PubMed  Google Scholar 

  49. 49.

    Lennerz JK, Hoffmann K, Bubolz AM, Lessel D, Welke C, Ruther N, et al. Suppressor of cytokine signaling 1 gene mutation status as a prognostic biomarker in classical Hodgkin lymphoma. Oncotarget. 2015;6:29097–110.

    PubMed  PubMed Central  Google Scholar 

  50. 50.

    Mottok A, Renne C, Willenbrock K, Hansmann ML, Brauninger A. Somatic hypermutation of SOCS1 in lymphocyte-predominant Hodgkin lymphoma is accompanied by high JAK2 expression and activation of STAT6. Blood. 2007;110:3387–90.

    CAS  PubMed  Google Scholar 

  51. 51.

    Schif B, Lennerz JK, Kohler CW, Bentink S, Kreuz M, Melzner I, et al. SOCS1 mutation subtypes predict divergent outcomes in diffuse large B-Cell lymphoma (DLBCL) patients. Oncotarget. 2013;4:35–47.

    PubMed  Google Scholar 

  52. 52.

    Klein U, Goossens T, Fischer M, Kanzler H, Braeuninger A, Rajewsky K, et al. Somatic hypermutation in normal and transformed human B cells. Immunol Rev. 1998;162:261–80.

    CAS  PubMed  Google Scholar 

  53. 53.

    Sasanelli M, Meignan M, Haioun C, Berriolo-Riedinger A, Casasnovas RO, Biggi A, et al. Pretherapy metabolic tumour volume is an independent predictor of outcome in patients with diffuse large B-cell lymphoma. Eur J Nucl Med Mol Imaging. 2014;41:2017–22.

    CAS  PubMed  Google Scholar 

  54. 54.

    Tout M, Casasnovas O, Meignan M, Lamy T, Morschhauser F, Salles G, et al. Rituximab exposure is influenced by baseline metabolic tumor volume and predicts outcome of DLBCL patients: a Lymphoma Study Association report. Blood. 2017;129:2616–23.

    CAS  PubMed  Google Scholar 

  55. 55.

    Dukers DF, Meijer CJ, ten Berge RL, Vos W, Ossenkoppele GJ, Oudejans JJ. High numbers of active caspase 3-positive Reed-Sternberg cells in pretreatment biopsy specimens of patients with Hodgkin disease predict favorable clinical outcome. Blood. 2002;100:36–42.

    CAS  PubMed  Google Scholar 

  56. 56.

    Georgiadi EC, Sachinis N, Dimtsas G, Vassilakopoulos TP, Kittas C, Doussis-Anagnostopoulou IA. Evaluation of apoptosis in classical Hodgkin’s lymphoma comparing different methods. J BUON. 2012;17:746–52.

    CAS  PubMed  Google Scholar 

  57. 57.

    Lorenzen J, Thiele J, Fischer R. The mummified Hodgkin cell: cell death in Hodgkin’s disease. J Pathol. 1997;182:288–98.

    CAS  PubMed  Google Scholar 

  58. 58.

    Kuppers R, Engert A, Hansmann ML. Hodgkin lymphoma. J Clin Invest. 2012;122:3439–47.

    PubMed  PubMed Central  Google Scholar 

  59. 59.

    Spina V, Bruscaggin A, Cuccaro A, Martini M, Di Trani M, Forestieri G, et al. Circulating tumor DNA reveals genetics, clonal evolution, and residual disease in classical Hodgkin lymphoma. Blood. 2018;131:2413–25.

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We like to thank Annika Habbaba, Sebastian Schäfer, Cindy Arnold, Katharina Sack and Stefanie Rudloff for excellent technical assistance and Stefanie Avondstondt and Dieter Hoffmann from the Pediatric Hodgkin Lymphoma reference center for providing the clinical data documentation. The EuroNet-PHL-C2 trial is supported by a grant from the Deutsche Krebshilfe (Grant No.110674). This study was supported by the Deutsche Krebshilfe (Grant no. 111711), the Rhön Klinikum AG (RKA FL_21), the Elternverein für leukämie- und krebskranke Kinder Gießen and the Kinderkrebshilfe Oldtimer Markt Mainz.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Andreas Bräuninger.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

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

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Desch, AK., Hartung, K., Botzen, A. et al. Genotyping circulating tumor DNA of pediatric Hodgkin lymphoma. Leukemia 34, 151–166 (2020). https://doi.org/10.1038/s41375-019-0541-6

Download citation

Further reading

Search

Quick links