Myelodysplastic syndromes Impact of Biology Lionel Adès Hopital Saint Louis Groupe Francophone des SMD Épidémiologie Incidence : 3 à 6 / 100 000 hab. / An Prédomine chez les sujets âgés Augmentation de prévalence avec l âge 50 70 ans : 3 à 15 / 100 000 Hab. / an > 80 ans : 80 / 100 000 Hab. / an Neukirchen, Leuk Res, 2011 15-20 % des anémies du sujet âge (Guralink, Blood, 2004) 1
MDS : Etiologies Age : +++ > 60 ans Expositions toxiques : Radiations ionisantes Chimiothérapies Tabac, Liés à Pathologie sous-jacente : Maladie de Fanconi Aplasie médullaire, Putative Pathogenetic Mechanisms and Their Interaction in the Myelodysplastic Syndromes Tefferi A, Vardiman J. N Engl J Med 2009;361:1872-1885 2
Clonal evolution in MDS Walter, NEJM 2012 Prognostic factor of MDS 3
Scoring system Several scoring system Mostly designed in untreated patients Based on simple clinical parameters IPSS WPSS IPSS-R Among others International Prognostic Scoring System Prognostic Variable (points) 0 0.5 1 1.5 2 Bone marrow blasts (%) < 5% 5-10 % - 11-20% 21-30% 4 categories Cytopenias : - platelets < 100.10⁹ /L - Hemoglobin < 10 g/dl - ANC < 1.8.10⁹ /L 0/1 2/3 2 categories Cytogenetic Good: - Normal - -Y - del(5q) - del(20q) Intermediate: - other abnorm Poor: - Complex 3 abnorm - Chr 7 abnorm 3 categories 7 Subgroups Greenberg Blood 1997 4
International Prognostic Scoring System Survival AML Evolution Greenberg Blood 1997 New cytogenetic classification Survival 2,902 patients AML Evolution 5
New cytogenetic classification Revised IPSS (IPSS-R) points 0 0.5 1 1.5 2 3 4 blasts ( %) 2% - 2-4% - 5-10% >10% Hemoglobin >10 g/dl 8-10 g/dl <8 g/dl ANC >0.8 G/l <0/8 G/l 4 categories 3 categories 2 categories Platelet >100 50-100 <50 3 categories Cytogenetics Very Good -Y del(11q) Good Normal der(1;7) del(5q) del(20q) del(12p) Double incl del(5q) Intermed -7/7q +8 Iso(17q) +19 +21 other double inclusions Poor: der3q(21) der3q(26) Complex Double inclusion 7q/7 Very Poor Complex >3 5 categories 16 subgroups P. Greenberg et al, Blood 2012 6
IPSS-R Survie Transformation LAM IPSS-R Some low risk MDS patient according to IPSS might be Reclassied has Having Higher Risk MDS According to IPSS-R P. Greenberg et al, Blood 2012 7
Treatment 15 Treatment : Based on IPSS Malcovati et al, Blood 2013 16 8
Treatment : Based on IPSS Malcovati et al, Blood 2013 17 Room for improvement 18 9
Frequency of mutations 51% of MDS patients had at least one identified mutation 52% of cases with normal karyotype had at least one mutation Bejar et al, NEJM 2011 Splicing mutations Yoshida Nature 2011 10
Many more oncogenetic events 111 genes in 838 patients Mutations observed in 80% of the cases Elli Papaemmanuil, Blood 2013 Several Pathways MDS EZH2 DNMT3A EPIGENETIC REGULATION TET2 ASXL1 IDH1 et 2 UTX SETBP1 22 11
Several Pathways MDS EZH2 DNMT3A SF3B1 U2AF1 EPIGENETIC REGULATION ASXL1 TET2 IDH1 et 2 ZRS F2 SPLICING SRSF2 UTX SETBP1 23 Several Pathways JAK2 PTPN11 BRAF TYROSINE KINASE KRAS NRAS CBL MDS EZH2 DNMT3A SF3B1 U2AF1 EPIGENETIC REGULATION ASXL1 TET2 IDH1 et 2 ZRS F2 SPLICING SRSF2 UTX SETBP1 24 12
Several Pathways JAK2 PTPN11 TYROSINE KINASE BRAF KRAS NRAS CBL RUNX1 GATA2 TRANSCRIPTION ETV6 WT1 MDS EZH2 DNMT3A SF3B1 U2AF1 EPIGENETIC REGULATION SPLICING TET2 IDH1 et 2 ASXL1 ZRS F2 SRSF2 UTX SETBP1 25 Several Pathways JAK2 PTPN11 BRAF NPM1 RUNX1 GATA2 TYROSINE KINASE TRANSCRIPTION OTHERS KRAS ETV6 NRAS WT1 CBL TP53 BCOR MDS EZH2 DNMT3A SF3B1 U2AF1 EPIGENETIC REGULATION SPLICING TET2 IDH1 et 2 ASXL1 ZRS F2 SRSF2 UTX SETBP1 26 13
Mutation mutually exclusive Point Mutation Cytogenetic Elli Papaemmanuil, Blood 2013 Co-mutated Mutually exclusive Transcription DNA Methylation Splicing Signalling Chromatin Other Mutually exclusive gene pairs often imply functional redundancy, especially if such genes are in the same biological pathway 27 Co occurrence of mutations Splicing 50% and Epigenetic genes 45% Splicing Epigenetic Mutation TP53 No Mutation Other Mutation 28 14
Impact to Stratify MDS? Impact on OS Clinical Correlations Mutations and Survival Bejar et al, NEJM 2011 15
Impact on OS Bejar et al, NEJM 2011 Add new information to IPSS Bejar et al, NEJM 2011 16
Probabilité de Survie sans Leucémie 28/01/2016 Impact of the number of mutation Pas de mutation 1 mutation 2 mutations 3 mutations 4-5 mutations 6 ou plus mutations Temps (mois) Elli Papaemmanuil, Blood 2013 Impact in treated patients? 17
Cytogentics Impact of Cytogenetics on OS compared to NK in 931 treated pts Cytogenetic n Hazard Ratio (95% CI) Reference Better -1 Worse 1 4 M. Sebert et al., ASH 2013 18
Gene mutations Impact of TET2 mutation in patients treated with AZA all TET2 mutated TET2 WT p* Patients 103 17 (17%) 86 (83%) Cycles of AZA 7 [1-39] 11 [4-34] 6 [1-39] 0,016 High risk cytogenetics 30 (34%) 1 (7%) 29 (39%) 0,01 Complete Response 24 (23%) 7 (41%) 17 (20%) 0,07 ORR (including HI) 53 (52%) 14 (82%) 39 (45%) 0,007 Higher Response Rate in TET 2 mutated patients Response duration and overall survival were, however, comparable in the MUT and WT groups. R. Itzykson et al. 19
Impact of TP53 in AZA treated pts TP53: 35-40% mutations By deep-sequencing Bally Leuk Res 2014; Walter Leukemia 2013 Impact of mutations in pts treated with HMA DFS OS HR IC 95 p HR IC 95 p Mutation status Methylation patway genes - TET2 (wt vs mutated) - DNMT3A (wt vs mutated) - IDH1/IDH2 (wt vs mutated) - TET2/DNMT3A (both wt vs one or both mutated) - TET2/DNMT3A/IDH1/IDH2 (all wt vs 1 mutation) 1,33 1,14 0,82 1,29 1,10 0,73-2,43 0,49-2,64 0,35-1,90 0,76-2,21 0,67-1,82 0,35 0,76 0,64 0,35 0,70 1,10 1,21 0,62 1,17 1,02 0,57-2,13 0,48-3,01 0,25-1,56 0,65-2,08 0,59-1,76 0,76 0,68 0,31 0,61 0,96 Histone-modifying gene ASXL1 (wt vs mutated) 0,68 0,41-1,12 0,13 0,48 0,28-0,82 0,008 Signal transduction genes CBL (wt vs mutated) CBL /RAS (wt vs mutated) 0,26 1,69 0,08-0,85 0,53-5,41 0,03 0,37 0,41 1,81 0,10-1,72 0,44-7,46 Spliceosomal gene SF3B1 (wt vs mutated) 1,95 0,93-4,08 0,08 3,76 1,36-10,42 0,01 0,22 0,41 Traina et al., Leukemia 2014 20
Impact in HR MDS treated patients Role of TP53 in del(5q) patients TP53 mutations with a median clone size of 11% (range, 1% to 54%) were detected in 10 patients (18%) already at an early phase of the disease. Associated with evolution to acute myeloid leukemia. The probability of a complete cytogenetic response to lenalidomide was lower in mutated patients Jadersten M et al., JCO 2011 21
Impact of mutation in Lower risk MDS Park et al. Soumis Genetic-driven treatment? 22
Some Drugable mutations? JAK2 PTPN11 BRAF RUNX1 GATA2 NPM1 NRAS CBL KRAS WT1 ETV6 BCOR TP53 MDS EZH2 DNMT3A SF3B1 U2AF1 TET2 IDH1 et 2 ASXL1 ZRS F2 SRSF2 UTX SETBP1 45 Drugable? Study Drug disease n Response Ref JAK2 Phase II Ruxolitinib AML 18 2 CR 1 CRi Case report Case report Ruxolitinib Azacytidine Ruxolitinib 7+3 IDH2 Phase I AG-221 Myeloid malignanc ies TP53 Phase Ib RG7388 MDM2 inhibitor 3 2 responses AML 6 2 CR 2 PR Lundberg, Blood 2014 Mwirigi, BJH 2014 Cluzeau, BJH 2015 45 56% de Botton, ASH 2014 AML 88 15% Yee, ASH 2014 BCL2 Phase II ABT199 AML/MDS 32 19% Konopleva, ASH 2014 46 23
Many oncogenetic events Do we really expect to have One drug for each oncogenetic Event? Elli Papaemmanuil, Blood 2013 Mutations in patients without Hematological Malignacies NEJM 2014; 371:2488-98 48 24
Drug targeting pathways Tipifarnib MAPK inhibitor MAPK Histone Deacetylase Inhibitor Me Me H3 Me MAP PI3K Hypomethylating Agents PI3K Inhibitor Bcl2 P53 inhibitor 49 Other Pathways BFU-E CFU-E Pro E Baso E Poly E Ortho E Retic RBC EPO drives proliferation GDF11 (TGF beta family) and the GDF11-ActRIIB- Smad2/3 pathway in the late stage of Erythropoiesis Mouse model of MDS: Murine ACE-536 (RAP-536) increased hemoglobin levels and decreased bone marrow erythroid hyperplasia (Suragani R et al., Nature Med 2014) Phase 1 study: ACE-536 well tolerated and dose-dependent increase in Hemoglobin (Attie K et al., Am J Hematol 2014) 25
TGFB inhibitors Key Role of GDF11 (TGF beta family) and the GDF11-ActRIIB- Smad2/3 pathway in the late stage of Erythropoiesis Luspatercept (Phase II) Mean (SD) Max. Change in Hemoglobin (g/dl) 4,0 3,0 2,0 1,0 0,0 Efficacy +++ in SF3B1 mutated patients 0,8 0.125 (n=1) 1,0 2,2 0.25 0.75 (n=1) (n=3) Dose Group (mg/kg) 3,5 1.75 (n=2) 26
Conclusions Several mutated genes in different Pathways are involved in MDS Some Serve as prognostic marker Might help for a better definition of the disease and Might Serve in the future as target to new therapeutic drugs Toward a personalized medicine but the road is still long!! 53 27