Chronic lymphocytic leukemia

Clonal diversity predicts adverse outcome in chronic lymphocytic leukemia

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Abstract

Genomic analyses of chronic lymphocytic leukemia (CLL) identified somatic mutations and associations of clonal diversity with adverse outcomes. Clonal evolution likely has therapeutic implications but its dynamic is less well studied. We studied clonal composition and prognostic value of seven recurrently mutated driver genes using targeted next-generation sequencing in 643 CLL patients and found higher frequencies of mutations in TP53 (35 vs. 12%, p < 0.001) and SF3B1 (20 vs. 11%, p < 0.05) and increased number of (sub)clonal (p < 0.0001) mutations in treated patients. We next performed an in-depth evaluation of clonal evolution on untreated CLL patients (50 “progressors” and 17 matched “non-progressors”) using a 404 gene-sequencing panel and identified novel mutated genes such as AXIN1, SDHA, SUZ12, and FOXO3. Progressors carried more mutations at initial presentation (2.5 vs. 1, p < 0.0001). Mutations in specific genes were associated with increased (SF3B1, ATM, and FBXW7) or decreased progression risk (AXIN1 and MYD88). Mutations affecting specific signaling pathways, such as Notch and MAP kinase pathway were enriched in progressive relative to non-progressive patients. These data extend earlier findings that specific genomic alterations and diversity of subclones are associated with disease progression and persistence of disease in CLL and identify novel recurrently mutated genes and associated outcomes.

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References

  1. 1.

    Landau DA, Tausch E, Taylor-Weiner AN, Stewart C, Reiter JG, Bahlo J, et al. Mutations driving CLL and their evolution in progression and relapse. Nature. 2015;526:525–30.

  2. 2.

    Ljungstrom V, Cortese D, Young E, Pandzic T, Mansouri L, Plevova K, et al. Whole-exome sequencing in relapsing chronic lymphocytic leukemia: clinical impact of recurrent RPS15 mutations. Blood. 2016;127:1007–16.

  3. 3.

    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.

  4. 4.

    Nadeu F, Delgado J, Royo C, Baumann T, Stankovic T, Pinyol M, et al. Clinical impact of clonal and subclonal TP53, SF3B1, BIRC3, NOTCH1, and ATM mutations in chronic lymphocytic leukemia. Blood. 2016;127:2122–30.

  5. 5.

    Rose-Zerilli MJ, Gibson J, Wang J, Tapper W, Davis Z, Parker H, et al. Longitudinal copy number, whole exome and targeted deep sequencing of ‘good risk’ IGHV-mutated CLL patients with progressive disease. Leukemia. 2016;30:1301–10.

  6. 6.

    Quesada V, Conde L, Villamor N, Ordonez GR, Jares P, Bassaganyas L, et al. Exome sequencing identifies recurrent mutations of the splicing factor SF3B1 gene in chronic lymphocytic leukemia. Nat Genet. 2011;44:47–52.

  7. 7.

    Fabbri G, Rasi S, Rossi D, Trifonov V, Khiabanian H, Ma J, et al. Analysis of the chronic lymphocytic leukemia coding genome: role of NOTCH1 mutational activation. J Exp Med. 2011;208:1389–401.

  8. 8.

    Schuh A, Becq J, Humphray S, Alexa A, Burns A, Clifford R, et al. Monitoring chronic lymphocytic leukemia progression by whole genome sequencing reveals heterogeneous clonal evolution patterns. Blood. 2012;120:4191–6.

  9. 9.

    Puente XS, Pinyol M, Quesada V, Conde L, Ordonez GR, Villamor N, et al. Whole-genome sequencing identifies recurrent mutations in chronic lymphocytic leukaemia. Nature. 2011;475:101–5.

  10. 10.

    Burns A, Alsolami R, Becq J, Timbs A, Bruce D, Robbe P, et al. Whole-genome sequencing of chronic lymphocytic leukaemia reveals distinct differences in the mutational landscape between IgHV(mut) and IgHV(unmut) subgroups. Leukemia. 2017;3:332–42.

  11. 11.

    Kasar S, Kim J, Improgo R, Tiao G, Polak P, Haradhvala N, et al. Whole-genome sequencing reveals activation-induced cytidine deaminase signatures during indolent chronic lymphocytic leukaemia evolution. Nat Commun. 2015;6:8866.

  12. 12.

    Zhao Z, Goldin L, Liu S, Wu L, Zhou W, Lou H, et al. Evolution of multiple cell clones over a 29-year period of a CLL patient. Nat Commun. 2016;7:13765.

  13. 13.

    Nadeu F, Clot G, Delgado J, Martin-Garcia D, Baumann T, Salaverria I, et al. Clinical impact of the subclonal architecture and mutational complexity in chronic lymphocytic leukemia. Leukemia. 2017;32:645–53.

  14. 14.

    Burger JA, Landau DA, Taylor-Weiner A, Bozic I, Zhang H, Sarosiek K, et al. Clonal evolution in patients with chronic lymphocytic leukaemia developing resistance to BTK inhibition. Nat Commun. 2016;7:11589.

  15. 15.

    Landau DA, Sun C, Rosebrock D, Herman SEM, Fein J, Sivina M, et al. The evolutionary landscape of chronic lymphocytic leukemia treated with ibrutinib targeted therapy. Nat Commun. 2017;8:2185.

  16. 16.

    Jethwa A, Hullein J, Stolz T, Blume C, Sellner L, Jauch A, et al. Targeted resequencing for analysis of clonal composition of recurrent gene mutations in chronic lymphocytic leukaemia. Br J Haematol. 2013;163:496–500.

  17. 17.

    Lipson D, Capelletti M, Yelensky R, Otto G, Parker A, Jarosz M, et al. Identification of new ALK and RET gene fusions from colorectal and lung cancer biopsies. Nat Med. 2012;18:382–4.

  18. 18.

    He J, Abdel-Wahab O, Nahas MK, Wang K, Rampal RK, Intlekofer AM, et al. Integrated genomic DNA/RNA profiling of hematologic malignancies in the clinical setting. Blood. 2016;127:3004–14.

  19. 19.

    Forbes SA, Bindal N, Bamford S, Cole C, Kok CY, Beare D, et al. COSMIC: mining complete cancer genomes in the catalogue of somatic mutations in cancer. Nucleic Acids Res. 2011;39:D945–50.

  20. 20.

    Rossi D, Bruscaggin A, Spina V, Rasi S, Khiabanian H, Messina M, et al. Mutations of the SF3B1 splicing factor in chronic lymphocytic leukemia: association with progression and fludarabine-refractoriness. Blood. 2011;118:6904–8.

  21. 21.

    Baliakas P, Hadzidimitriou A, Sutton LA, Rossi D, Minga E, Villamor N, et al. Recurrent mutations refine prognosis in chronic lymphocytic leukemia. Leukemia. 2015;29:329–36.

  22. 22.

    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.

  23. 23.

    Hallek M, Cheson BD, Catovsky D, Caligaris-Cappio F, Dighiero G, Dohner H, et al. Guidelines for the diagnosis and treatment of chronic lymphocytic leukemia: a report from the International Workshop on Chronic Lymphocytic Leukemia updating the National Cancer Institute-Working Group 1996 guidelines. Blood. 2008;111:5446–56.

  24. 24.

    Martinez-Trillos A, Pinyol M, Navarro A, Aymerich M, Jares P, Juan M, et al. Mutations in TLR/MYD88 pathway identify a subset of young chronic lymphocytic leukemia patients with favorable outcome. Blood. 2014;123:3790–6.

  25. 25.

    Balatti V, Bottoni A, Palamarchuk A, Alder H, Rassenti LZ, Kipps TJ, et al. NOTCH1 mutations in CLL associated with trisomy 12. Blood. 2012;119:329–31.

  26. 26.

    Adachi M, Cossman J, Longo D, Croce CM, Tsujimoto Y. Variant translocation of the bcl-2 gene to immunoglobulin lambda light chain gene in chronic lymphocytic leukemia. Proc Natl Acad Sci USA. 1989;86:2771–4.

  27. 27.

    Dyer MJ, Zani VJ, Lu WZ, O’Byrne A, Mould S, Chapman R, et al. BCL2 translocations in leukemias of mature B cells. Blood. 1994;83:3682–8.

  28. 28.

    Ferreira PG, Jares P, Rico D, Gomez-Lopez G, Martinez-Trillos A, Villamor N, et al. Transcriptome characterization by RNA sequencing identifies a major molecular and clinical subdivision in chronic lymphocytic leukemia. Genome Res. 2014;24:212–26.

  29. 29.

    Stilgenbauer S, Schnaiter A, Paschka P, Zenz T, Rossi M, Dohner K, et al. Gene mutations and treatment outcome in chronic lymphocytic leukemia: results from the CLL8 trial. Blood. 2014;123:3247–54.

  30. 30.

    Del Giudice I, Rossi D, Chiaretti S, Marinelli M, Tavolaro S, Gabrielli S, et al. NOTCH1 mutations in +12 chronic lymphocytic leukemia (CLL) confer an unfavorable prognosis, induce a distinctive transcriptional profiling and refine the intermediate prognosis of +12 CLL. Haematologica. 2012;97:437–41.

  31. 31.

    Rossi D, Khiabanian H, Spina V, Ciardullo C, Bruscaggin A, Fama R, et al. Clinical impact of small TP53 mutated subclones in chronic lymphocytic leukemia. Blood. 2014;123:2139–47.

  32. 32.

    Ojha J, Ayres J, Secreto C, Tschumper R, Rabe K, Van Dyke D, et al. Deep sequencing identifies genetic heterogeneity and recurrent convergent evolution in chronic lymphocytic leukemia. Blood. 2015;125:492–8.

  33. 33.

    Wang L, Shalek AK, Lawrence M, Ding R, Gaublomme JT, Pochet N, et al. Somatic mutation as a mechanism of Wnt/beta-catenin pathway activation in CLL. Blood. 2014;124:1089–98.

  34. 34.

    Messina M, Del Giudice I, Khiabanian H, Rossi D, Chiaretti S, Rasi S, et al. Genetic lesions associated with chronic lymphocytic leukemia chemo-refractoriness. Blood. 2014;123:2378–88.

  35. 35.

    Yao Z, Yaeger R, Rodrik-Outmezguine VS, Tao A, Torres NM, Chang MT, et al. Tumours with class 3 BRAF mutants are sensitive to the inhibition of activated RAS. Nature. 2017;548:234–8.

  36. 36.

    Heidorn SJ, Milagre C, Whittaker S, Nourry A, Niculescu-Duvas I, Dhomen N, et al. Kinase-dead BRAF and oncogenic RAS cooperate to drive tumor progression through CRAF. Cell. 2010;140:209–21.

  37. 37.

    Dahlman KB, Xia J, Hutchinson K, Ng C, Hucks D, Jia P, et al. BRAF(L597) mutations in melanoma are associated with sensitivity to MEK inhibitors. Cancer Discov. 2012;2:791–7.

  38. 38.

    Zhang C, Spevak W, Zhang Y, Burton EA, Ma Y, Habets G, et al. RAF inhibitors that evade paradoxical MAPK pathway activation. Nature. 2015;526:583–6.

  39. 39.

    Fama R, Bomben R, Rasi S, Dal Bo M, Ciardullo C, Monti S, et al. Ibrutinib-naive chronic lymphocytic leukemia lacks Bruton tyrosine kinase mutations associated with treatment resistance. Blood. 2014;124:3831–3.

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Acknowledgements

ACL is supported by the van der Laan foundation. JT is supported by an American Society of Hematology (ASH) Research Training Award for Fellows, an ASCO Young Investigator Award, and the ASH and Harold Amos Medical Faculty Development Program of the Robert Wood Johnson Foundation. JG was supported by the Vogelstein Fund at MSKCC. OAW is supported by NIH/NCI R01 (1R01HL128239-01 and 1R01 CA201247-01) and support from the Cycle for Survival. This work was also supported by the Peter Solomon Fund at MSKCC. TZ was supported by a Mildred Scheel Professorship, the “Monique Dornonville de la Cour Stiftung” and the Transcan project. Many thanks go to the participating patients and we would like to acknowledge all participating institutions in the HOVON68 CLL trial, the data managers and statisticians of the HOVON data center, as well as the HOVON68 CLL study funding sources, the participating German centers and MSKCC.

Author contributions

ACL, JT, BW, JRG, MN, JH, MG, OAW, TZ, and APK were responsible for conception and design of the study. ACL, BW, JT, JRG, RLL, VM, and TM were involved in analysis and interpretation of data. MN, JH, MH, DR, WGA, TW, JH, FB, KH, JD, NL, MGF, SD, RC, JD, CHG, MHJO, MLH, and AZ, TZ, OAW, and APK were involved in acquisition of patient materials. ACL, BW, JRG, and MG perfomed statistical analyses. ACL, BW, and JRG made the figures. ACL, JT, TZ, OAW, and APK wrote the first draft; and all authors were involved in revising the manuscript and approved the final version.

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Correspondence to Omar Abdel-Wahab or Arnon P. Kater.

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Conflict of interest

MN, JH, VM, and TM are employees of Foundation Medicine. RLL and OAW are consultants for Foundation Medicine. The remaining authors declare that they have no conflict of interest.

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Leeksma, A.C., Taylor, J., Wu, B. et al. Clonal diversity predicts adverse outcome in chronic lymphocytic leukemia. Leukemia 33, 390–402 (2019) doi:10.1038/s41375-018-0215-9

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