EAFO IV Hematology Forum, St.Petersburg, 2016

1. CYTOGENETICS AND
MOLECULAR GENETICS OF ALL
Molecular/gene,c-guided management
Robin Foà
Hematology, ‘Sapienza’ University, Rome, Italy
St Petersburg, 5 March 2016

2. ALL - MAJOR CHANGES OVER THE YEARS
• Prognosis in children cure rates ≈80%
• Exact lineage definiFon of pracFcally all cases at all
ages
• Treatment and prognosis of L3 ALL
• IdenFficaFon of subgroups with a different
prognosFc likelihood eg Ph+, t(4;11)+,….
• Targeted treatment eg Ph+ ALL, MoAb,….
• Management of adolescents and young adults
• Possibility of monitoring MRD in virtually all cases
• Tailored/personalizid management

3. Diagnos>c work-up: gene>c/molecular analysis

4. INTEGRATED APPROACHES UTILIZED
FOR A MODERN CHARACTERIZATION OF
HEMATOLOGIC MALIGNANCIES
• Morphology and cytochemistry
• Immunophenotype
• Cytogenetics
• Molecular genetics
• Cell cycle
• Ig and TCR gene rearrangements (if required)
• MRD monitoring flow, PCR
• Gene profiling, snp, whole exome sequencing,
NGS

5. Objec>ves of a Broad and Integrated
Characteriza>on at Diagnosis at all ages,
including the elderly
• Accurate diagnosDc work-up
• Precise definiFon of disease subenDDes
• Biologically-based prognosDc straDficaDon
• DefiniFon of markers for MRD monitoring
• Targeted therapies
• IdenFficaFon of targets for potenFal new
targeted therapies
Requirement of a central processing, recognized
laboratories and standardized methodologies

6. The Italian centers
participating in the
GIMEMA group are
≈150
1982-2012

7. GIMEMA NETWORK FOR ADULT
HEMATOLOGIC DISEASES
• Overall, more than 150 centers in Italy
• Central handling of samples at diagnosis (and
during the follow-up and at relapse) acFvated
for ALL in October 1996
• Aim broad and uniform characterizaFon of
all cases enrolled in the same clinical protocols
• IdenFficaFon of reference laboratories (Roma,
Ferrara, Perugia, Torino, Napoli, Bologna, etc)
• Bank of material
• Structured in WP for different condiFons

8. GIMEMA Cooperative Study Group
Adult ALL “Linee guida 2000” Protocol
(up to 60 yrs)
MOLECULAR BIOLOGY: 99% of cases
• BCR/ABL+ 27.7%
• ALL1/AF-4+ 5.0%
• E2A/PBX1+ 3.2%
• ALL1/ENL+ 1.1%
• TEL-AML1+ 0.3%
• SIL-TAL+ 1.5%

9. Standard-risk: median DFS = 3.2 years
years from CR
p<0.0001
Standard: 85 events 47
Intermediate: 56 events 34
High: 91 events 75
Intermediate-risk: median DFS = 1.6 years
High-risk: median DFS = 0.62 years
Pre-TKI Era. GIMEMA: DFS According to
Cytogene>c-Molecular Risk Groups
Mancini et al, Blood 2005
BCR/ABL+
ALL1/AF-4

10. Incidence of molecular aberra>ons in B-ALL
GIMEMA-AIEOP Data on >5000 cases
0
10
20
30
40
50
60
1--5 5--10 10--14 14--18 18--25 25--30 30--40 40--50 50--60
ALL1/AF4
E2A/PBX
ETV6/RUNX1
BCR /ABL
BCR/ABL+ (18-60 yrs): 27.7%
Age cohorts
<.0001
Chiaretti et al, Haematologica 2013

11. Ph+ ALL
• Important prevalence in adults (15 – 60% ?
of cases) increases with age
• Unfavorable prognosis in both children and
adults
• ConvenFonal chemotherapy unsaFsfactory
• Impact of tyrosine kinase inhibitors (TKI)
a revolu,on in the management of Ph+ ALL

12. Overall Survival Disease-Free Survival
GIMEMA LAL 0904 3rd Amendment (ima>nib
followed by chemo): Long-Term Survival
DFS at 60 months: 45.8%
(CI 95%: 33.6-62.5)
OS at 60 months: 48.8%
(CI 95%: 36.4-65.3)
Chiaretti et al , in press

13. GIMEMA 1509: MRD and DFS
Survivalprobabilty
1.0
0.8
0.6
0.4
0.2
0.0
0 5 10 15 20 0 10 20 30
1.0
0.8
0.6
0.4
0.2
0.0
DFS by CMR at d +85 DFS by fusion type
DFS: 88.9% (CI 95%: 70.6-100) vs 57.8 (CI
95%: 44.3-75.2) in CMR vs no CMR at 18
months (p=0.07)
DFS: 68.1% (CI 95%: 52.3-88.8) vs 59.2
(CI 95%: 42.5-82.4) in p190 vs p210 at
18 months (p=0.2)
CMR
No CMR
Months from CR Months from CR
p210
p190
Chiaretti et al, ASH 2014

14. PC, diagnosed with Ph+ ALL in
September 2007 at the age of 89.
Treated with Imatinib alone (partly
at home…). Obtained a CHR,
MRD-, and turned 90...
Drived a car and occasionally
helped in the family garage…
Relapse in June 2009. IInd CR with
Dasatinib. Relapse in February
2010, responded to VCR.
Died in March of heart failure, at
91, 2½ years from diagnosis.
Courtesy of Prof. G. Pizzolo
A 91 YEAR OLD ALL PATIENT…

15. BCR/ABL1: muta>ons

16. BCR/ABL Kinase Domain Muta>ons
• “Kinase domain muta>ons of BCR-ABL frequently precede ima>nib-based
therapy and give rise to relapse in pa>ents with de novo Philadelphia-posi>ve
acute lymphoblas>c leukemia (Ph+ ALL)” (Pfeifer H et al. Blood 2007; 110:
727-734)
• “Philadelphia-posi>ve acute lymphoblas>c leukemia pa>ents already harbor
BCR-ABL kinase domain muta>ons at low levels at the >me of
diagnosis” (Soverini S et al. Haematologica. 2011; 96: 552-557)
Mutated subclones might be present at diagnosis and do not
preclude the achievement of a ini,al response
• “Drug resistance and BCR-ABL kinase domain muta>ons in Philadelphia
chromosome-positve acue lymphoblas>c leukemia from the Ima>nib to the
second-genera>on tyrosine kinase inhibitor era” (Soverini S et al. Cancer 2014;
120: 1002-1009)
Muta,ons are detected in 70% of ima,nib resistant cases and in
78% of second-genera,on TKIs

17. IKZF1 and outcome in BCR/ABL+ ALL
Correla>on with poorer outcome and increased incidence of relapse
MarFnelli, JCO 2009

18. Mature B-ALL (Burkih)
t(;14), t(2;8), o t(8;22), C-MYC rearrangement
Specific intensive chemotherapy
+
Rituximab (an>-CD20)

19. GENE EXPRESSION PROFILE OF PRE-B ALL
ALL1/AF4 has a unique gene expression
profile, that is comparable in children and
in adults. Overexpression of Flt3, HOXA5
and HOXA9.
E2A/PBX is also characterized by a strong
signature. Most overexpressed genes:
PBX1, NID2, FAT and several tyrosine
kinases. Gain of 1q behave like E2A/PBX+
samples.
BCR/ABL has a profile characterized by
overexpression of several tyrosine kinases
and cell cycle related genes. More
heterogeneous profile.
No clear palern is observed for samples
without molecular abnormaliFes.
Chiare et al, Clin Cancer Res, 2005
gain 1q and gain1q23

20. Novel groups: BCR-ABL like
By GEP: idenFficaFon of a subset of children (COALL and DCOG), accounFng for 17% of cases, with a BCR/
ABL1-like profile, frequent deregulaFon of CRLF2.
Array-CGH: aberraFons involving IKZF1, PAX5, TCF3, and VPREB1
Clinical findings: worse outcome, male gender, increased WBC count, poor response to L-ASP and DNM.
Den Boer et al, Lancet 2009

21. BCR/ABL1-LIKE ALL
• BCR/ABL1-like cases represent about 20% of
adult B-ALL cases and 15% of pediatric cases
• Poor prognosis well documented in children
• CRLF2 deregulaFon, as well as IKZF1 deleFon and
JAK (mostly JAK2) mutaFons are recurrent and
might be helpful in recognizing these cases
• In vitro use of TKI seem effec>ve in primay cells
• Design of ad hoc treatment including TKI and
other inhibitors?

22. Novel groups: Early T Progenitor (ETP) ALL
Represent 12% of T-ALL in children and 10% in adults
Coustan-Smith et al, Lancet Onc, 2009
Chiaren et al, Haematologica 2010

23. By NGS, ETP-ALL are characterized by specific mutations in
signaling pathways and genes of myeloid lineage
Zhang J et al, Nature 2012
IdenFficaFon of typical AML mutaFons in immature T-ALL of adult paFents:
IDH1, IDH2, DNMT3A, FLT3 and NRAS.
Prominent role of ETV6 mutaFons (Van Vlierberghe et al, JEM 2011)
Zhang et al, Nature 2012

24. RelaFvely high rate of FLT3 mutaFons (35%)

25. IKZF1 and other dele>ons in B- ALL
Children
• Associated with higher WBC, older
age, poor response to PDN and
higher MRD levels.
• More frequent in the so-called “B-
other” subset.
• Holds prognosFc significance in
mulFvariate analysis (Clappier et al,
Leukemia 2015; Ollson et al, BJH
2015).
Adults
• Associated with higher WBC.
• Associated with higher CIR; not
significant in mulFvariate analysis
(Ribera et al, Cancer 2015).
• Other deleFons associated with
outcome; CDKN2A/B and EBF1 (Ribera et
al, Cancer 2015).
• IKZF1 deleFon predicFve of poorer
outcome, regardless of MRD (Bedjord et
al, Blood 2014).
In both pediatric and adult ALL, IKZF1 deletions are
recurrent (about 15% and 30%)

26. Age cohorts
Years
Probability
Outcome in different age cohorts
Is/are there underlying lesion/s that could be related
to the different outcome?
Chiaren et al, Haematologica 2013

27. CRLF2
JAK2
IL7R
NRAS
KRAS
FLT3
RAS-pathway
High-
risk
36%
1 TKD2 5 TKD2
5 ITD
B-NEG ALL - Pathway recurrency
FLT3 (p=0.039)
%ofmutatedcases
0
5
10
15
20
Children AYA Adults All cohorts
FLT3
KRAS
NRAS
0
2
4
6
8
10
12
Children AYA& adults
Messina et al, Oncotarget 2016

28. CRLF2
JAK2
IL7R
NRAS
KRAS
FLT3
RAS-pathway
High-
risk
36%
% of mutated cases
JAK2
IL7R
CRLF2
Pathway recurrency
0
2
4
6
8
10
12
Children AYA Adults All cohorts
Messina et al, Oncotarget 2016

29. Impact of RAS/RTK and JAK/STAT pathway
muta>ons on prognosis - OS
18 8 2 2 1 1
67 40 21 13 8 2
0 20 40 60 80 100
survival time (months)
0.0
0.2
0.4
0.6
0.8
1.0
SurvivalProbability
M
WT
WTM
1) RAS/RTK canonical mutations vs WT for all (excluding JAK/STAT
Logrank p=0.0747
+ Censored
Product-Limit Survival Estimates
With Number of Subjects at Risk
18 8 2 2 1 1
67 40 21 13 8 2
0 20 40 60 80 100
survival time (months)
0.0
0.2
0.4
0.6
0.8
1.0
SurvivalProbability
M
WT
WTM
1) RAS/RTK canonical mutations vs WT for all (excluding JAK/STAT
Logrank p=0.0747
+ Censored
Product-Limit Survival Estimates
With Number of Subjects at Risk
14 9 5 0
34 24 12 1
0 50 100 150
survival time (months)
0.0
0.2
0.4
0.6
0.8
1.0
SurvivalProbability
M
WT
WTM
1) RAS/RTK canonical mutations vs WT for all (excluding JAK/STAT
Logrank p=0.9925
+ Censored
Product-Limit Survival Estimates
With Number of Subjects at Risk
14 9 5 0
34 24 12 1
0 50 100 150
survival time (months)
0.0
0.2
0.4
0.6
0.8
1.0
SurvivalProbability
M
WT
WTM
1) RAS/RTK canonical mutations vs WT for all (excluding JAK/STAT
Logrank p=0.9925
+ Censored
Product-Limit Survival Estimates
With Number of Subjects at Risk
Survival Fme (months)
Survival probability
Children
Survival Fme (months)
Survival probability
Adolescents and adults
RAS/RTK pathway muta>ons
M
WT
M
WT
JAK/STAT pathway muta>ons
8 2 1 0
29 15 6 4 2 1
0 20 40 60 80 100
survival time (months)
0.0
0.2
0.4
0.6
0.8
1.0
SurvivalProbability
M
WT
WTM
3) JAK/STAT clonal mutations vs WT for all (excluding RAS/RTK ca
Logrank p=0.2074
+ Censored
Product-Limit Survival Estimates
With Number of Subjects at Risk
8 2 1 0
29 15 6 4 2 1
0 20 40 60 80 100
survival time (months)
0.0
0.2
0.4
0.6
0.8
1.0
SurvivalProbability
M
WT
WTM
3) JAK/STAT clonal mutations vs WT for all (excluding RAS/RTK ca
Logrank p=0.2074
+ Censored
Product-Limit Survival Estimates
With Number of Subjects at Risk
Survival Fme (months)
Survival probability
M
WT
Adults
5 1 1 0
67 40 21 13 8 2
0 20 40 60 80 100
survival time (months)
0.0
0.2
0.4
0.6
0.8
1.0
SurvivalProbability
M
WT
WTM
7) IL7R mutated vs WT for JAK/STAT clonal and RAS/RTK canonical
Logrank p=0.0459
+ Censored
Product-Limit Survival Estimates
With Number of Subjects at Risk
5 1 1 0
67 40 21 13 8 2
0 20 40 60 80 100
survival time (months)
0.0
0.2
0.4
0.6
0.8
1.0
SurvivalProbability
M
WT
WTM
7) IL7R mutated vs WT for JAK/STAT clonal and RAS/RTK canonical
Logrank p=0.0459
+ Censored
Product-Limit Survival Estimates
With Number of Subjects at Risk
Survival Fme (months)
Survival probability
IL7R muta>ons
M
WT
Messina et al, Oncotarget 2016

30. Missense SNV
INDEL
Nonsense SNV
Fusion driving inactivation
ATE
RNAseq identified targeted pathways in refractory/
early relapsed T-ALL
47% 42% 42%
Ø JAK/STAT and PI3K/AKT were the most commonly disrupted pathways
Ø The NOTCH1/FBXW7 pathway was also affected, but a concomitant
mutation in the JAK/STAT pathway was frequently detected
Ø OVERLAPPING MUTATIONS BETWEEN GENES/PATHWAYS
JAK/STAT PI3K/AKT NOTCH
JAK1
JAK3
STAT5A
STAT6
IL7R
TYK2
PTPRC
NRAS
KRAS
ITPKB
ITPR1
PIK3R1
PTEN
NOTCH1
NOTCH2
NOTCH3
FBXW7
1 0 0 0 0 0 5 0 0 0 0 0 3 0 0 1
1 1 0 0 0 0 0 0 0 0 0 0 3 0 0 0
3 1 0 0 0 0 0 0 0 0 2 3 3 0 0 1
0 1 1 0 0 0 0 0 0 0 0 0 1 1 0 0
0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0
0 1 0 1 0 0 0 1 0 0 0 3 1 0 0 0
0 0 0 0 3 0 0 0 0 0 0 0 1 0 1 0
0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 1 0 1 0 0 0 0 0
0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0
0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
0 0 0 0 0 0 0 1 1 0 0 0 0
0 0 0 0 0 0 0 0 3 0 0 0 0
0 0 0 0 0 0 0 0 3 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Gianfelici et al, in press

31. Impact of mutation in JAK/STAT pathway
on survival
Significant negative impact of JAK/
STAT alterations on outcome
Could targeted therapy improve
outcome?
OS DFS
EFS
SurvivalProbability
SurvivalProbability
SurvivalProbability
JAK/STAT+ -----------
JAK/STAT-
JAK/STAT pos -----------
JAK/STAT wt -----------
median JAK/STAT pos: 11 months
median JAK/STAT wt: not yet reached
median JAK/STAT pos: 3.3 months
median JAK/STAT wt: 17.3 months
median JAK/STAT pos: 15.7 months
median JAK/STAT wt: not yet reached
JAK/STAT pos -----------
JAK/STAT wt -----------
JAK/STAT pos -----------
JAK/STAT wt -----------

32. Impact of mutation in RAS/AKT pathway
on survival
Significant negative impact of RAS/
AKT alterations on outcome
Could targeted therapy improve
outcome?
OS DFS
EFS
SurvivalProbability
SurvivalProbability
SurvivalProbability
RAS/AKT pos -----------
RAS/AKT wt -----------
median RAS/AKT pos: 7.9 months
median RAS/AKT wt: not yet reached
median RAS/AKT pos: 4.3 months
median RAS/AKT wt: not yet reached
median RAS/AKT pos: 3.3 months
median RAS/AKT wt: 17.3 months
RAS/AKT pos -----------
RAS/AKT wt -----------
RAS/AKT pos -----------
RAS/AKT wt -----------

33. Impact of mutation in NOTCH1/FBXW7
on survival
The positive impact of NOTCH1/
FBXW7 mutations is overcome by
the concomitant presence of
mutations in JAK/STAT or RAS/AKT
pathway
OS DFS
EFS
SurvivalProbability
SurvivalProbability
SurvivalProbability
NOTCH1/FBXW7single hit ----------
NOTCH1/FBXW7wt ----------
NOTCH1/FBXW7+other hit ----------
NOTCH1/FBXW7single hit ----------
NOTCH1/FBXW7wt ----------
NOTCH1/FBXW7+other hit ----------
NOTCH1/FBXW7single hit ----------
NOTCH1/FBXW7wt ----------
NOTCH1/FBXW7+other hit ----------

34. Cellviability
0%
25%
50%
75%
100%
CTR 0,001
uM
0,01 uM 0,1 uM 1 uM 10 uM
Ruxoli>nib
(JAK1/2 inhibitor)
CTR 0,001 0,01 0,1 1 10 uM
0%
25%
50%
75%
100%
CTR 0,001
uM
0,01
uM
0,1 uM 1 uM 10 uM
R31
R7
R14
G97
Tofaci>nib
(JAK3 inhibitor)
(JAK/STAT wt)
(JAK1/JAK3/STAT5B mut)
(JAK1/PTPRC mut)
(JAK1 mut)
Cellviability CTR 0,001 0,01 0,1 1 10 uM
In vitro assays on primary T-ALL cells carrying JAK/STAT
muta>on
Primary cells from pa>ents with JAK1 altera>ons revealed a selec>ve
sensi>vity to Ruxoli>nib.
Different sensi>vity to Ruxoli>nib among the 3 cases harboring different
combina>ons of JAK/STAT altera>ons.

35. Conclusions and open ques>ons
• Outcome of BCR/ABL1+ paFents has drasFcally
improved since the introducFon of TKI
• Other ALL: BCR/ABL1-like, ETP and gene mutaFons
involving TK, JAK/STAT and RAS pathways should be
invesFgated to drive therapeuFc decisions.
• With risk-straFfied protocols, the impact of novel
lesions could be redefined
• Is MRD superseding all these findings?
• If so, when to use targeted therapies? At MRD
reappearance? At relapse?

36. ‘TECHNOLOGY’-DRIVEN
MANAGEMENT OF ALL
• GeneFc/molecular characterizaFon at diagnosis
prognosDcaDon, targeted treatment, MRD
• Targeted management of Ph+ ALL
• MoAb-driven management of Burkil leukemia
• Role of anF-CD20, anF-CD22
• Impact of blinatumumab (anF-CD19/CD3)
• Ph-like ALL, ETP
• Pathway alteraFons in B-NEG ALL and T-ALL
• MRD-driven personalized management

37. Acknowledgments
Monica Messina
ValenFna Gianfelici
Sara GrammaFco
Anna Lucia Fedullo
Anna Guarini
Robin Foà
Alfonso Piciocchi
Marco Vignen
Raul Rabadan
Jiguang Wang
Truus te Kronnie