1 / 31

Prognostication in MF: From CBC to cytogenetics to molecular markers

Prognostication in MF: From CBC to cytogenetics to molecular markers. Alessandro M. Vannucchi University of Florence, Italy. p < 0.0001. Survival is S ignificantly Shortened in PMF. Median survival: 4.6 versus 6.5 y . Cervantes F et al. JCO 2012; 24:2891-7.

toya
Télécharger la présentation

Prognostication in MF: From CBC to cytogenetics to molecular markers

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Prognostication in MF: From CBC to cytogenetics to molecular markers Alessandro M. Vannucchi University of Florence, Italy

  2. p < 0.0001 SurvivalisSignificantlyShortened in PMF Median survival: 4.6 versus 6.5 y Cervantes F et al. JCO 2012; 24:2891-7.

  3. Why do weNeed Accurate PrognosticScores? • Long termremissions with the potential of beingcuredhavebeendescribedonly in patientsundergoingallogeneic HSCT • However, HSCT approach to MF hasseverallimitations, currently:

  4. Risk Stratification in PMF Cervantes et al, Blood 2009;113:2895-901 Passamonti et al, Blood 2010; 115:1703-8 Gangat N et al, J ClinOncol 2011; 29:392-7

  5. International PrognosticScoringSystem-IPSS Low Int-1 High Int-2 Cervantes F et al. Blood 2009;113:2895-901

  6. Impact of Anemia on Disease Progression • Disease-related anemia* hasbeenassociated with worseprognosis in all • riskscoringsystems (Lille, IPSS and derivatives) • RBC transfusionaldependencyisincluded in the DIPSS-plus score Passamonti F.et al, Blood 2010; 115:1703-8 * NOT treatment-related

  7. DynamicIPSS (DIPSS) Passamonti F et al. Blood 2010;115:1703-8

  8. Survival by Cytogenetic Category in PMF At diagnosis Beyond initialdiagnosis CPX= complex (>3 abnormalities) Tam C S et al. Blood 2009;113:4171-4178

  9. "Unfavorable"Karyotype in PMF: Effect on OS • Unfavorable Karyo: • - Complex karyo, • - Sole or 2 abnormalities including: • Trisomy 8 • -7/del(7q) • Del(5q) • Inv(3) • isochromosome 17q/17p- • 12p- • 11q23 abnormality UnfavorableKaryo M 2.0 yr 5-yr survival: 8% FavorableKaryo M 5.2 yr 5-yr survival: 51% Caramazza D et al. Leukemia 2011; 25:82-88

  10. "Unfavorable"Karyotype in PMF: Effect on LFS FavorableKaryo 5-yr AML transformation rate: 7% UnfavorableKaryo 5-yr AML transformation rate: 46% Caramazza D et al. Leukemia 2011; 25:82-88

  11. Risk Stratification in PMF Cervantes et al, Blood 2009;113:2895-901 Passamonti et al, Blood 2010; 115:1703-8 Gangat N et al, J ClinOncol 2011; 29:392-7

  12. DynamicIPSS-plus (DIPSS-plus) ∆ Low risk (0 adverse points) n=66; median survival ~ 185 months ▲ Intermediate-1 risk (1 adverse point) n=174; median survival ~ 78 months ○ Intermediate-2 risk (2 or 3 adverse points) n=360; median survival ~ 35 months High risk (4 or more adverse points) n=193; median survival ~ 16 months Survival Lowrisk(0 variable) M 185 mo Int-1 risk(1 variable) M 78 mo High risk (>4 variables) M 16 mo Int-2 risk(2-3 variables) M 35 mo Months Gangat et al. J ClinOncol2011;29:392-7

  13. Adverse Impact of MonosomalKaryotype Normalkaryo M 50 mo Complexkaryo No monosomal M 24 mo Sole +8 M 20 mo Monosomal karyo M 6 mo Vaidya R et al. Blood 2011;117:5612-15

  14. “Very-High Risk” Patients: >80% Mortality At 2 Years Low (3%) Int-1 (11%) Int-2 (26%) High (53%) Very High (82%) Tefferi A et al. Blood 2011; 118:4595-8

  15. NovelPrognosticVariables • SomaticMutations • GermlineCharacteristics • Cytokines • Otherbiomarkers (FLC, hepcidin & ferritinlevels)

  16. JAK2 V617F Mutation and Prognosis in PMF P=0.198 WT V617F N=483 Guglielmelli P et al, ASH2012

  17. No Impact of JAK2V617Fon LeukemiaRisk HR: 1.05 (95% CI, 0.7-1.7) P=0.839 WT V617F (Competitive riskanalysis) Guglielmelli P et al, ASH2012

  18. Blast transformation: Kaplan-Meier analysis Barosi et al. PlosOne 2013, In press

  19. MutationComplexity in PMF • 382 (79.1%) of patients presented at least one somatic mutation • 154 pts (32.5%) had >2 mutations • 31 pts (6.4%) had >3 mutations Guglielmelli P et al, ASH2012

  20. Mutations Associated with Reduced Overall Survival in Multivariate Analysis EZH2 ASXL1 WT WT Mut Mut P= 0.0008 P< 0.0001 SRSF2 WT Mut P< 0.0001 Guglielmelli P et al, ASH2012

  21. Mutations Associated with Leukemia in Multivariate Analysis EZH2 ASXL1 WT Mut Mut WT P=.003 HR=1.98 (95%CI: 0.88-4.46) P<.0001 HR=2.5 (95%CI: 1.51-4.13) SRSF2 IDH1/2 Mut Mut WT WT P=.007 HR= 2.73 (95%CI: 1.34-5.55) P<.0001 HR= 2.66(95%CI: 1.10-6.47) * Competitive Risk Analysis Guglielmelli P et al, ASH2012

  22. A "Molecularly High-Risk" Status Associates with ReducedOverallSurvival P<0.0001 • EZH2 • ASXL1 • SRSF2 • IDH1/2 Low Risk High Risk HR= 2.29 (95%CI: 1.65-3.19) • In the “molecularly high-risk” category, overall survival was 81 months (range: 61.9-99.5) compared with 148 months (range: 52.5-243.2) in the “molecularly low-risk” category (P<0.0001). Mutivariate analysis. Guglielmelli P et al, ASH2012

  23. A "Molecularly High-Risk"Status AssociatesWith LeukemiaTransformation High Risk • EZH2 • ASXL1 • SRSF2 • IDH1/2 Low Risk P<0.0001 HR 2.96 (95%CI:1.85-4.76) • In the “molecularly high-risk” category, leukemia-free survival was 129 months (range: 90-168) compared with 323 months (range: 194-452) in the “molecularly low-risk” category (P<0.0001) – Competitive risk analysis Guglielmelli P et al, ASH2012

  24. The "Molecularly High-Risk" Status Contributes to Refined IPSS Categorization IPSS (LOW-INT1) IPSS (INT2-HIGH) P= 0.017 P= 0.002 Low Risk Low Risk High Risk High Risk Guglielmelli P et al, ASH2012

  25. The "Molecularly High-Risk" Status Predicts for LeukemiaRiskwithin IPSS Categories IPSS (LOW-INT1) IPSS (INT2-HIGH) P= 0.001 P= 0.01 High Risk’ High Risk Low Risk Low Risk Guglielmelli P et al, ASH2012

  26. ABSTRACT #430 Prognostic Interactions Between SRSF2, ASXL1, and IDH Mutations in Primary Myelofibrosis and Determination of Added Value to Cytogenetic Risk Stratification and DIPSS-Plus Terra L Lasho, MT, (ASCP)1*, Naseema Gangat, MD1*, Christy Finke, BS1*, Rebecca R. Laborde, PhD1*, Curtis A Hanson, MD2*, Rhett P Ketterling, MD3*, Ryan A Knudson3*, Animesh Pardanani, MBBS, PhD1 and Ayalew Tefferi, MD1

  27. The A3669G Polymorhism of GlucocorticoidReceptorContributes to BlastTransformation in PMF • The A3669G allele is a susceptibility allele for PMF (HR 1.6-1.8) • The G/G allele associated with a «more-myeloproliferative» phenotype OS* BT* 0.47 per 100 pt-yr N=274 N=21 13.6 per 100 pt-yr 77.6mo vs 298mo; P=0.049 76.7mo vs 261mo; P=0.018 remainedsignificant in multivariate *, restricted to JAK2V617Fpospts, n=295 Barosi G et al, Blood 2012; 120:3112-7

  28. AbnormallyIncreased IL-8 and IL2R Plasma Levels Are PrognosticallyDetrimental Int-1 (n=27) All (n=127) Int-2 (n=70) Treatment naive (n=90) Tefferi A et al. JCO 2011;29:1356-1363

  29. Plasma Free Light Chain (FLC) LevelsPredictSurvival in PMF FCL FCL +/- IL-8 and/or IL-2R < 3.78 mg/dL Bothnormal Bothabnormal > 3.78 mg/dL Eitherabnormal Bothabnormal Levelsabove or below the ROC cutoff (3.78 mg/dL) Pardanani A et al. JCO 2012;30:1087-94

  30. Conclusions • Prognosticscores in OMF are needed for therapeuticchoices • At present, they are mainlyreserved for HSCT decision • Mostusedscores are based on clinical and hematologicvariables • Cytogeneticshasbeen show to add to clinicalscores • Molecularcharacterizationmay help refineclinicalscores, be cost-effective and overcometechnicallimitations of conventionalcytogenetics

  31. Acknowledgments Contributors Section of Hematology, University of Florence Paola Guglielmelli FlaviaBiamonte Tiziana Fanelli Ambra Spolverini Maria Chiara Susini Giada Rotunno Alessandro Pancrazzi Lisa Pieri Mario Cazzola - Pavia Gianni Barosi - Pavia Francisco Cervantes - Barcelona Andrea Reiter - Mannheim Andrew Duncombe - Southampton Katerine Zoe - Athens Nick Cross - Salisbury

More Related