Myelodysplastic syndrome

Co-mutation pattern, clonal hierarchy, and clone size concur to determine disease phenotype of SRSF2P95-mutated neoplasms


Somatic mutations in splicing factor genes frequently occur in myeloid neoplasms. While SF3B1 mutations are associated with myelodysplastic syndromes (MDS) with ring sideroblasts, SRSF2P95 mutations are found in different disease categories, including MDS, myeloproliferative neoplasms (MPN), myelodysplastic/myeloproliferative neoplasms (MDS/MPN), and acute myeloid leukemia (AML). To identify molecular determinants of this phenotypic heterogeneity, we explored molecular and clinical features of a prospective cohort of 279 SRSF2P95-mutated cases selected from a population of 2663 patients with myeloid neoplasms. Median number of somatic mutations per subject was 3. Multivariate regression analysis showed associations between co-mutated genes and clinical phenotype, including JAK2 or MPL with myelofibrosis (OR = 26.9); TET2 with monocytosis (OR = 5.2); RAS-pathway genes with leukocytosis (OR = 5.1); and STAG2, RUNX1, or IDH1/2 with blast phenotype (MDS or AML) (OR = 3.4, 1.9, and 2.1, respectively). Within patients with SRSF2–JAK2 co-mutation, JAK2 dominance was invariably associated with clinical feature of MPN, whereas SRSF2 mutation was dominant in MDS/MPN. Within patients with SRSF2–TET2 co-mutation, clinical expressivity of monocytosis was positively associated with co-mutated clone size. This study provides evidence that co-mutation pattern, clone size, and hierarchy concur to determine clinical phenotype, tracing relevant genotype–phenotype associations across disease entities and giving insight on unaccountable clinical heterogeneity within current WHO classification categories.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Co-mutation plot for somatically mutated genes in SRSF2P95-mutated neoplasms.
Fig. 2: Associations between somatic mutations and clinical phenotype.
Fig. 3: Clinical phenotype of JAK2SRSF2-mutated myeloid neoplasms reflects the hierarchy of JAK2-mutated clone.
Fig. 4: Relationship between TET2–SRSF2 double-mutant clone and monocytosis.
Fig. 5: Relationship between WHO classification, co-mutation pattern, and clinical outcome in SRSF2-mutated neoplasms.


  1. 1.

    Papaemmanuil E, Cazzola M, Boultwood J, Malcovati L, Vyas P, Bowen D, et al. Somatic SF3B1 mutation in myelodysplasia with ring sideroblasts. N Engl J Med. 2011;365:1384–95.

    CAS  Article  Google Scholar 

  2. 2.

    Yoshida K, Sanada M, Shiraishi Y, Nowak D, Nagata Y, Yamamoto R, et al. Frequent pathway mutations of splicing machinery in myelodysplasia. Nature. 2011;478:64–69.

    CAS  Article  Google Scholar 

  3. 3.

    Vardiman JW, Thiele J, Arber DA, Brunning RD, Borowitz MJ, Porwit A, et al. The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: rationale and important changes. Blood. 2009;114:937–51.

    CAS  Article  Google Scholar 

  4. 4.

    Shiozawa Y, Malcovati L, Gallì A, Sato-Otsubo A, Kataoka K, Sato Y, et al. Aberrant splicing and defective mRNA production induced by somatic spliceosome mutations in myelodysplasia. Nat Commun. 2018;9:3649.

    Article  Google Scholar 

  5. 5.

    Kim E, Ilagan JO, Liang Y, Daubner GM, Lee SCW, Ramakrishnan A, et al. SRSF2 mutations contribute to myelodysplasia by mutant-specific effects on exon recognition. Cancer Cell. 2015;27:617–30.

    CAS  Article  Google Scholar 

  6. 6.

    Pellagatti A, Armstrong RN, Steeples V, Sharma E, Repapi E, Singh S, et al. Impact of spliceosome mutations on RNA splicing in myelodysplasia: dysregulated genes/pathways and clinical associations. Blood. 2018;132:1225–40.

    CAS  Article  Google Scholar 

  7. 7.

    Saez B, Walter MJ, Graubert TA. Splicing factor gene mutations in hematologic malignancies. Blood. 2017;129:1260–9.

    CAS  Article  Google Scholar 

  8. 8.

    Malcovati L, Karimi M, Papaemmanuil E, Ambaglio I, Jadersten M, Jansson M, et al. SF3B1 mutation identifies a distinct subset of myelodysplastic syndrome with ring sideroblasts. Blood. 2015;126:233–41.

    CAS  Article  Google Scholar 

  9. 9.

    Arber DA, Orazi A, Hasserjian R, Thiele J, Borowitz MJ, Le Beau MM, et al. The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood. 2016;127:2391–405.

    CAS  Article  Google Scholar 

  10. 10.

    Malcovati L, Papaemmanuil E, Ambaglio I, Elena C, Galli A, Della Porta MG, et al. Driver somatic mutations identify distinct disease entities within myeloid neoplasms with myelodysplasia. Blood. 2014;124:1513–21.

    CAS  Article  Google Scholar 

  11. 11.

    Vannucchi AM, Lasho TL, Guglielmelli P, Biamonte F, Pardanani A, Pereira A, et al. Mutations and prognosis in primary myelofibrosis. Leukemia. 2013;27:1861–9.

    CAS  Article  Google Scholar 

  12. 12.

    Papaemmanuil E, Gerstung M, Bullinger L, Gaidzik VI, Paschka P, Roberts ND, et al. Genomic classification and prognosis in acute myeloid leukemia. N Engl J Med. 2016;374:2209–21.

    CAS  Article  Google Scholar 

  13. 13.

    Smeets MF, Tan SY, Xu JJ, Anande G, Unnikrishnan A, Chalk AM, et al. Srsf2 P95H initiates myeloid bias and myelodysplastic/myeloproliferative syndrome from hemopoietic stem cells. Blood. 2018;132:608–21.

    CAS  Article  Google Scholar 

  14. 14.

    Kon A, Yamazaki S, Nannya Y, Kataoka K, Ota Y, Nakagawa MM, et al. Physiological Srsf2 P95H expression causes impaired hematopoietic stem cell functions and aberrant RNA splicing in mice. Blood. 2018;131:621–35.

    CAS  Article  Google Scholar 

  15. 15.

    Zhang J, Lieu YK, Ali AM, Penson A, Reggio KS, Rabadan R, et al. Disease-associated mutation in SRSF2 misregulates splicing by altering RNA-binding affinities. Proc Natl Acad Sci USA. 2015;112:E4726–E4734.

    CAS  Article  Google Scholar 

  16. 16.

    Malcovati L, Papaemmanuil E, Bowen DT, Boultwood J, Della Porta MG, Pascutto C, et al. Clinical significance of SF3B1 mutations in myelodysplastic syndromes and myelodysplastic/myeloproliferative neoplasms. Blood. 2011;118:6239–46.

    CAS  Article  Google Scholar 

  17. 17.

    Malcovati L, Hellstrom-Lindberg E, Bowen D, Ades L, Cermak J, del Canizo C, et al. Diagnosis and treatment of primary myelodysplastic syndromes in adults: recommendations from the European LeukemiaNet. Blood. 2013;122:2943–64.

    CAS  Article  Google Scholar 

  18. 18.

    Döhner H, Estey E, Grimwade D, Amadori S, Appelbaum FR, Büchner T, et al. Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel. Blood. 2017;129:424–47.

    Article  Google Scholar 

  19. 19.

    Greenberg PL, Tuechler H, Schanz J, Sanz G, Garcia-Manero G, Sole F, et al. Revised international prognostic scoring system for myelodysplastic syndromes. Blood. 2012;120:2454–65.

    CAS  Article  Google Scholar 

  20. 20.

    Such E, Germing U, Malcovati L, Cervera J, Kuendgen A, Della Porta MG, et al. Development and validation of a prognostic scoring system for patients with chronic myelomonocytic leukemia. Blood. 2013;121:3005–15.

    CAS  Article  Google Scholar 

  21. 21.

    Passamonti F, Cervantes F, Vannucchi AM, Morra E, Rumi E, Pereira A, et al. A dynamic prognostic model to predict survival in primary myelofibrosis: a study by the IWG-MRT (International Working Group for Myeloproliferative Neoplasms Research and Treatment). Blood. 2010;115:1703–8.

    CAS  Article  Google Scholar 

  22. 22.

    Pacilli A, Rotunno G, Mannarelli C, Fanelli T, Pancrazzi A, Contini E, et al. Mutation landscape in patients with myelofibrosis receiving ruxolitinib or hydroxyurea. Blood Cancer J. 2018;8.

  23. 23.

    Karimi M, Nilsson C, Dimitriou M, Jansson M, Matsson H, Unneberg P, et al. High-throughput mutational screening adds clinically important information in myelodysplastic syndromes and secondary or therapy-related acute myeloid leukemia. Haematologica. 2015;100:e223–e225.

    Article  Google Scholar 

  24. 24.

    Shiozawa Y, Malcovati L, Gallì A, Pellagatti A, Karimi M, Sato-Otsubo A, et al. Gene expression and risk of leukemic transformation in myelodysplasia. Blood. 2017;130:2642–53.

    CAS  Article  Google Scholar 

  25. 25.

    Chen Y, Zhao L, Wang Y, Cao M, Gelowani V, Xu M, et al. SeqCNV: a novel method for identification of copy number variations in targeted next-generation sequencing data. BMC Bioinform. 2017;18.

  26. 26.

    Nik-Zainal S, Van Loo P, Wedge DC, Alexandrov LB, Greenman CD, Lau KW, et al. The life history of 21 breast cancers. Cell. 2012;149:994–1007.

    CAS  Article  Google Scholar 

  27. 27.

    Salcedo A, Tarabichi M, Espiritu SMG, Deshwar AG, David M, Wilson NM, et al. A community effort to create standards for evaluating tumor subclonal reconstruction. Nat Biotechnol. 2020;38:97–107.

    CAS  Article  Google Scholar 

  28. 28.

    Chen L, Chen JY, Huang YJ, Gu Y, Qiu J, Qian H, et al. The augmented R-loop is a unifying mechanism for myelodysplastic syndromes induced by high-risk splicing factor mutations. Mol Cell. 2018;69:412–25.e6.

    CAS  Article  Google Scholar 

  29. 29.

    Abelson S, Collord G, Ng SWK, Weissbrod O, Mendelson Cohen N, Niemeyer E, et al. Prediction of acute myeloid leukaemia risk in healthy individuals. Nature. 2018;559:400–4.

    CAS  Article  Google Scholar 

  30. 30.

    Shimizu T, Kubovcakova L, Nienhold R, Zmajkovic J, Meyer SC, Hao-Shen H, et al. Loss of Ezh2 synergizes with JAK2-V617F in initiating myeloproliferative neoplasms and promoting myelofibrosis. J Exp Med. 2016;213:1479–96.

    CAS  Article  Google Scholar 

  31. 31.

    Yang Y, Akada H, Nath D, Hutchison RE, Mohi G. Loss of Ezh2 cooperates with Jak2V617F in the development of myelofibrosis in a mouse model of myeloproliferative neoplasm. Blood. 2016;127:3410–23.

    CAS  Article  Google Scholar 

  32. 32.

    Vainchenker W, Kralovics R. Genetic basis and molecular pathophysiology of classical myeloproliferative neoplasms. Blood. 2017;129:667–79.

    CAS  Article  Google Scholar 

  33. 33.

    Rumi E, Pietra D, Pascutto C, Guglielmelli P, Martínez-Trillos A, Casetti I, et al. Clinical effect of driver mutations of JAK2, CALR, or MPL in primary myelofibrosis. Blood. 2014;124:1062–9.

    CAS  Article  Google Scholar 

  34. 34.

    Della Porta MG, Malcovati L, Boveri E, Travaglino E, Pietra D, Pascutto C, et al. Clinical relevance of bone marrow fibrosis and CD34-positive cell clusters in primary myelodysplastic syndromes. J Clin Oncol. 2009;27:754–62.

    Article  Google Scholar 

  35. 35.

    Hu Z, Ramos CEB, Medeiros LJ, Zhao C, Yin CC, Li S, et al. Utility of JAK2 V617F allelic burden in distinguishing chronic myelomonocytic Leukemia from Primary myelofibrosis with monocytosis. Hum Pathol. 2019;85:290–8.

    CAS  Article  Google Scholar 

  36. 36.

    Cargo C, Cullen M, Taylor J, Short M, Glover P, Van Hoppe S, et al. The use of targeted sequencing and flow cytometry to identify patients with a clinically significant monocytosis. Blood. 2019;133:1325–34.

    CAS  Article  Google Scholar 

  37. 37.

    Cazzola M. Clonal monocytosis of clinical significance. Blood. 2019;133:1271–2.

    CAS  Article  Google Scholar 

  38. 38.

    Valent P, Orazi A, Savona MR, Patnaik MM, Onida F, van de Loosdrecht AA, et al. Proposed diagnostic criteria for classical chronic myelomonocytic leukemia (CMML), CMML variants and pre-CMML conditions. Haematologica. 2019;104:1935–49.

    CAS  Article  Google Scholar 

  39. 39.

    Yoshimi A, Lin K-T, Wiseman DH, Rahman MA, Pastore A, Wang B, et al. Coordinated alterations in RNA splicing and epigenetic regulation drive leukaemogenesis. Nature. 2019.

Download references


This study was supported by Associazione Italiana per la Ricerca sul Cancro (Milan, Italy) through the International Accelerator Program (Early detection and intervention: Understanding the mechanisms of transformation and hidden resistance of incurable hematological malignancies, Project Code: 22796); the 5×1000 project “Actionable targets in clonal progression and systemic spreading of myeloid neoplasms,” (MYNERVA project, Project Code: 21267); and the Investigator Grant 2017 (Project Code: 20125). Additional support was provided by the Italian Ministry of Health for young researchers (GR-2016-02361272), the Italian Society of Hematology, American-Italian Cancer Foundation, the Swedish Cancer Society (Cancerfonden, 150269), the Cancer Research Foundations of Radiumhemmets (Radiumhemmets Forskningsfonder, 151103), the Swedish Research Council (Vetenskapsrådet, 521-2013-3577), the JSPS KAKENHI (JP15H05909 and JP19H05656), the Japanese Ministry of Education, Culture, Sports, Science and Technology (hp160219), and by AMED (JP19ck0106250h0003).

Author information




GT, LM, and MCa designed the study, performed statistical analysis, and wrote the manuscript; AG, PG, YN, DP, and MD analyzed sequencing data; VR performed single-cell colony genotyping; EM and SC processed samples; MR and ERi performed bioinformatic analysis; GT, MCr, PG, ERu, CE, EB, and JU collected clinical data; AMV, SO, and EH-L contributed to study design and interpretation of the data.

Corresponding author

Correspondence to Luca Malcovati.

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

Todisco, G., Creignou, M., Gallì, A. et al. Co-mutation pattern, clonal hierarchy, and clone size concur to determine disease phenotype of SRSF2P95-mutated neoplasms. Leukemia (2020).

Download citation


Quick links