Leucemia Linfoblastica Acuta dell’età pediatrica A.Biondi and G.Cazzaniga Department of Pediatrics and Centro Ricerca Tettamanti University of Milano-Bicocca S. Gerardo Hospital / Fondazione MBBM Monza, Italy
Outcome of contemporary trials involving children and adolescents with ALL Hunger SP and Mullighan CG N Engl J Med 2015;373: 1541-52 Teachey DT and Pui CH Lancet Oncolo.2019: 20(30):142-154
Contents MRD response: still the best proxy but with limitations; Impact of genomics; Genetic predisposition of childhood ALL? The AIEOP-BFM ALL 2017: integrate genetics in MRD-based strategies.
MRD evaluation as a marker of in vivo early response • Close association between the quality of the molecular remission and the final outcome, independently on the applied treatments in childhood and adult ALL ; • It is still unknown why the exposure to drugs during the early phases of treatment (induction or consolidation) discloses different in vivo chemosensitivities which influence the final treatment outcome Cazzaniga G. et al Br J Haematol, 2011; Cazzaniga G and Biondi A, Hematology, 2013
Relapses in BCP-ALL by MRD risk groups AIEOP-BFM ALL 2000 1.0 N.pts N. rel. 5-yrs CI 7-yrs CI SR 1348 61 6.0%(0.8) 7.2%(1.2) IR 1647 266 21.0%(1.2) 22.3%(1.4) HR 189 60 34.9%(3.8) 38.5%(5.0) 0.8 p-value<0.001 69% of all relapses Cum. Incidence 0.6 in IR pts 0.4 0.2 0.0 0 1 2 3 4 5 6 7 Years from diagnosis Conter V et al Blood 2010; 115: 3206
Relapses in T-ALL by MRD risk groups AIEOP-BFM ALL 2000 1.0 N.pts N. rel. 7-yrs CI SR 75 5 7.6%(3.3) IR 292 51 17.6%(2.2) HR 97 36 37.7%(5.0) 0.8 p-value: overall<0.001; SR vs MR=0.02; MR vs HR<0.001 Cum. Incidence 55% of all 0.6 relapses in IR pts 0.4 0.2 0.0 0 1 2 3 4 5 6 7 Years from diagnosis Schrappe et al. Blood 2011; 118: 2077
Improving MRD Detection by Next Generation/High Throughput Sequencing (HTS) • HTS of clonotypic Ig/TCR rearrangements detects MRD at ~1/1,000,000 • Pilot study of ~300 pts from AALL0331 showed that 20% had no detectable residual clonal sequence at any level at day 29 • These HTS neg pts had a 5- yr EFS of 98.1% and OS 100% • Includes pts with and without favorable genetics Wu et al, Clin Cancer Res 2014 Kirsch, SIOP 2016 and Wood, ASH 2016
The CyTOF instrument is similar to a traditional flow cytometer because it can screen numerous parameters on individual cells. However, it does so with the use of metal particle conjugated antibodies instead of the traditional antibody conjugated fluorophores that conventional flow cytometers uses.
To view BCP-ALL through the lens of normal development, we classified individual leukemia cells to the closest normal stage of B-cell development Workflow experiments Developmental Classification Good Z and Sarno J, Nat Med 2018
DDPR synergize with current risk-stratification methods NCI-Rome + DDPR NCI-Rome Criteria Final risk + DDPR Final risk Good Z and Sarno J, Nat Med 2018
Developmentally Dependent Predictor of Relapse (DDPR) identifies critical features of pro-BII to pre-BI developmental transition that effectively predict relapse in childhood BCP-ALL based on diagnostic samples High basal pSYK , pCREB , and prpS6 in pre-BI cells not responsive to ex-vivo stimulation High basal prpS6 and p4EBP1 in pro-BII cells
Estimated frequency of specific genotypes in childhood ALL Others T-ALL; ETP; 2.0% T-ALL 1.7% MLL-ENL; 3,0% TLX1; 3,0% Hyperdiploid >50; LYL1; 1,4% 25,0% TLX3; 2,3% TAL1; 7,0% Other BCP-ALL; 4,5% Other MLL-R; 4,0% BCP-ALL Hipodiploid; 0,5% E2A-HLF; 0,5% iAMP21; 2,0% dic(9;20); 2,0% TEL-AML1; 20,0% ERG; 3,0% IKZF1; 12,0% E2A-PBX1; 4,0% MLL-AF4; 2,0% CRLF2; 4,0% BCR-ABL1; 2,0% BCR-ABL1-like; 9.0% Modified from Pui et al, Blood. 2012;120:1165
1 - Identification of new targetable chromosomal traslocations Integrated diagnostic algorithm BCR/ABL for childhood ALL Current analyses TEL/AML1 TCF3/PBX1 MLL/AF4 TCF3/HLF RQ-PCR RQ-PCR DNAindex Early MRD-risk Final MRD-risk FCM MRD HR-blocks Experimental arm 0 +8 +15 +33 +50 +78 alert ≥5x10 -4 (random) NGS ≥10% and ‘B-other’ Next analyses and ‘B-other’ IG/TR Targeted NGS TKI If HR 1) TK fusions 2) JAK/STAT CRLF2+ JAK inhibitor? 3) MLL-other NG2+ CLL1 + RNA-seq? Padova Monza IKZF1plus ERG-PCR ? By FCM by RNA by DNA dMLPA
A novel TCF3-HLF fusion in ALL with a t(17;19)(q22;p13) Panagopoulos I. et al., Cancer Genet. 2012;205:669-72 RT-PCR Multiplex RT-PCR (x6)
IKZF1 plus • Is present in 6 – 7% of patients • Is a very poor prognostic marker in intermediate and high-risk BCP ALL • Identifies 25% of relapses occurring in intermediate and high-risk BCP ALL • Acts as a prototype for a transition from prognostic markers prognostic patterns (Deletion of IKZF1 and: PAX5 and/or CDKN2A and/or CDKN2B and/or CRLF2 and negativity for ERG deletion) Stanulla M et al J Clin Oncol 2017
IKZF1 plus identification ‘Ikaros-plus’: any IKZF1del + del of PAX5 or CRLF2 or CDKN2, but ERGwt Digital MLPA ALL (MRC-Holland, kit and software not commercially available yet ): - 320 probes, targeting 56 key target genes, with at least 3 probes per gene. - all ‘B-others’ ALL (75%), @d33. - one run any 2 weeks (pooling of 10 samples). - 86 diagnosis ALL samples analyzed with MLPA P335 and digital MLPA- ALL kit. - 98.8% of concordance on IKZF1-plus identification between two methods. - Depending on samples availability, dMLPA can be spiked-in with IG/TR screening (once a week), no extra sequencing cost. Stanulla M. et al, J Clin Oncol. 2018 Mar 2
IKZF1 plus – cumulative relapse incidence in MRD- based risk groups MRD standard risk (SR) SR = 6% MR = 62% HR = 55% MRD intermediate risk (MR) MRD high risk (HR)
Class of Kinase rearrangements and therapeutic targets in Ph-like ALL CHILDREN ADOLESCENTS YOUNG ADULTS Roberts KG & Mullighan CG, Nat Rev Clin Onc 2015
EBF1-PDGFRB (Ph-like) responds to TKI Weston BW et al, J Clin Oncol. 2013;31:e413-6 Cario G et al Haematologica, 2020 Cario G et al Haematologica, 2019 Lengline E et al, Haematologica. 2013;98:e146-8 days
RNA target capture in the diagnostic flowchart MISEQ ILLUMINA RNA CAPTURED LIBRARY - ILLUMINA TRUSIGHT RNA PANCANCER PANEL - NUGEN OVATION TARGET ENRICHMENT SYSTEM - pooling of 8 samples (MRD TP1 +33>5X10-4) - once any 3-4 weeks BIOINFORMATICS (TopHat and RNASeq Alignment analysis) IDENTIFICATION OF FUSION GENES
Prospective analysis of B- ALL cases in years 2017 - 2018 MRD-SER (N=39) 2017 2018 - nowadays 2017: BCP-ALL TP1(D33) > 5 X 10^-4 56 52 N=15 negative N=7 not available MRD SER ( TP2 D78 < 5 X 10^-4 ) 16 28 (5 on going) N=4 with known traslocations 1 chr12-chr19 ETV6/JAK3 1 chrX-chrX USP9X/DDX3X (ref.5) MRD HR ( TP2 D78 > 5 X 10^-4 ) 15 8 (1 on going) 1 chr12 -chr22 ZNF384EP300 (ref.6) 2 chr19-chr19 DOT1/OAZ1 MRD- nonHR 25 16 (7 on going) 2 chrX-chrX P2RY87CRLF2 1 chr12-chr22 ZNF384/TCF3 MRD-non HR (N=34) 1 chr9-chr12 PAX5/FBRLS1 1 chr19-chr19 BRD4/KLF2 2017: 1 chrX-chrX ASMTL/P2RY8 MRD-HR (N=22) N=16 negative 1 chr5-chr5 ZNF608/PDGFRB 2017: N=4 not available 1 chr16-chr16 ZNF276/FANCA N=14 negative N=5 with known traslocations N=1 with known traslocations 1 chrX-chrX P2RY8/CRLF2 chr1-chr1 HDAC1/MARCKSL1 1 1 del(5) EBF1/PDGFRB (ref.1) PAX5/C20orf112 (ref.2) chr9-chr20 2 chr8-chr8 NDRG1/ST3GAL1 1 chr17 - chr19 TCF3/HLF (ref.3) 1 chrX-chrX P2RY8/ZEBD1 1 chr11 - chr11 MLL/USP2 (ref.4) 1 chr12-chr12 BCL7A/NCOR2 1 chr19-chr19 DOT1/OAZ1 EBF1/PDGFRB (ref.1) 1 del(5) 1 chrX-chrX GPR128/TGF 1 chr17 - chr19 TCF3-HLF (ref.3) 1 chr8-chr8 NDRG1/ST3GAL1 1 chrX-chrX GPR128/TGF chr19-chr19 DOT1/OAZ1 1.Schwab, Blood, 2016 May 5; 127(18):2214-8 2.Kawamata N, Oncogene. 2011;31(8):966-77 3. Panagopoulos, Cancer Genet. 2012 Dec;205(12):669-72 4.Andersson AK, Nat Genet. 2015 Apr;47(4):330-7 5.Russell L., Genes Chromosomes Cancer. 2017 May;56(5):363-372 6.Hirabhayashi, Haematologica, 2017 Jan; 102(1): 118–129
Challenges in clinical development of “targeted therapies”in childhood ALL • In vitro and in vivo evaluation of new agents in ALL model systems: lenghty and often imperfect; • Single-agent biologic activity in murine models and translational into clinical activity in patients, and improper drug sequencing can result in untoward clinical outcomes; • Complex dymamics, with highly variable patterns of genetic diversity and resulting clonal architecture.
Selective pressures on branching clonal architecture of clonal evolution in leukemia Greaves M, Nature 2012;481:306
Genetic predisposition to acute lymphoblastic leukemia Pui CH , Nichols KE, Yang JJ. Somatic and germline genomics in paediatric acute lymphoblastic leukaemia. Nat Rev Clin Oncol. 2019 Apr;16(4):227-240.
Background • Causes of ALL remain largely unknown, and ALL has been considered for long time as not inheritable. • It is estimated that at least 5-10% of cases diagnosed with cancer harbor constitutional genetic variants that increase their lifetime cancer risk. • Recently, both low and high impact genetic risk factors for familial and non-familial childhood leukemia have been identified.
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