2 Stratification for risk prediction and RD improved - Mito

Department of Experimental Oncology and Molecular Medicine
Unit of Molecular Therapies
XXV Riunione MITO
Napoli 25 Giugno 2014
MITO2 miRNA microarray profile identifies a
strong predictor of disease relapse in ovarian
cancer
2
MITO2 miRNA profiling
Aim:
development of a prognostic model to predict disease early relapse
Overall design
- training set:
179 cases from MITO2 trial; OC179
- validation set1: 263 cases from INT-CRO series; OC263
- validation set2: 452 cases from TCGA data; OC452
Overall 894 EOC cases were analyzed: “the largest miRNA EOC data set so far available”
Three different platforms used for profiling; Re-annotation of all detected miRNAs on
miRBase21
385 unique miRNA shared among all studies
2
Patients’ clinical-pathological characteristics
OC179 MITO2
N°(179)
%
Age, years
mean, median
range
Histology
Serous
Undifferentiated
Endometroid
Mucinous
Clear Cells
Others + Mixed
NA
Stage (FIGO)
I
II
III
IV
NA
Grade
border line
1, well differentiated
2, moderately differentiated
3, poorly differentiated
Undifferentiated
GX
NA
Amount of residual disease
NED
<1 cm, mRD
>1 cm, GRD
not operated
NA
Treatment
carboplatin + paclitaxel
carboplatin
carboplatin + caelyx
other
NA
Median follow up (months)
OC263
N°(263)
%
58, 59
28-78
TCGA
N°(452)
%
55, 56
25-85
58, 58
26-87
124
10
24
0
6
13
2
69
6
13
0
3
7
1
190
23
26
1
7
15
1
72
9
10
0
3
6
0
452
na
na
na
na
na
na
100
17
15
123
24
9
8
69
13
16
9
212
26
6
3
81
10
11
27
350
63
1
2
6
77
14
1
0
5
27
126
10
0
11
0
3
15
70
6
0
6
3
7
51
177
23
0
2
1
3
19
67
9
0
1
1
5
55
382
0
8
1
1
1
12
84
0
2
73
42
53
11
0
41
23
30
6
0
76
85
101
0
1
29
32
39
0
0
102
208
100
0
42
23
46
22
0
9
78
na
101
na
na
44
177
47
1
32
6
67
18
0
12
3
56
73 (IQR 60-88)
44 (IQR 24-71)
56 (IQR 25-86)
2
Patients’ clinical-pathological characteristics
OC263
OC452
0.8
PFSPFS
0.4
40
60
80
0
100
20
time (months)
events median
124
22.8
0.95CI
18-29
n
events
263 195
80
100
120
0
median
16
0.95CI
13-21
40
60
80
0.95CI
15-18
1.0
median
17
0.8
0.2
0.0
100
Time (months)
time (months)
n
179
150
0.6
Surv
Surv
0.0
20
100
n
events
452 327
0.6
0.2
0.4
Surv
Surv
0.4
0.2
0.0
0
50
time (months)
Time (months)
0.8
1.0
0.8
0.6
Surv
OS
60
1.0
n
179
40
time (months)
Time (months)
Time (months)
0.4
20
0.0
0.0
0.2
0.2
0.4
0.2
0.0
0
0.4
0.6
0.6
PFS
PFS
0.6
PFS
PFS
0.8
0.8
1.0
1.0
1.0
OC179
events median 0.95 CI
77
nyr
63-NA
0
50
100
150
time (months)
Time (months)
n
events
263 105
median
60
0
50
100
time (months)
150
Time (months)
0.95CI
46-77
n
events
452 223
median
49
0.95CI
45-52
2
miRNA-based classifier
End point: disease recurrance
Application of an algorithm that on the basis of
time-to-progression and relative expression of
the 385 miRNAs, classified MITO2 patients as
high or low risk to relapse.
After a 10-fold cross validation a model was
developed containing 35 unique miRNAs whose
expression, although with different relevance,
significantly contributed to define the risk of
relapse of MITO2 cohort.
miRNAs (19) whose expression associated to poor
prognosis
miRNAs (16) whose expression associated to
good prognosis
Unique id
hsa-miR-193a-5p
hsa-miR-508-3p
hsa-miR-509-5p
hsa-miR-514a-3p
hsa-miR-506-3p
hsa-miR-507
hsa-miR-509-3p
hsa-miR-592
hsa-miR-29c-5p
hsa-miR-513b-5p
hsa-miR-513a-5p
hsa-miR-200c-3p
hsa-miR-141-3p
hsa-miR-200b-3p
hsa-miR-423-5p
hsa-miR-486-5p
hsa-miR-200a-3p
hsa-miR-23a-5p
hsa-miR-330-3p
hsa-miR-30b-3p
hsa-miR-484
hsa-miR-769-5p
hsa-miR-135b-5p
hsa-miR-100-3p
hsa-miR-99b-5p
hsa-miR-143-5p
hsa-miR-429
hsa-miR-151a-3p
hsa-miR-574-5p
hsa-miR-452-5p
hsa-miR-29a-5p
hsa-miR-195-3p
hsa-miR-890
hsa-miR-30d-5p
hsa-miR-193b-5p
p-value % CV Support Hazard Ratio
0,0000177
100
1,977
0,0000311
100
0,747
0,0000474
100
0,684
0,0000478
100
0,811
0,0000507
100
0,635
0,0000572
100
0,588
0,0000713
100
0,783
0,0001548
100
0,255
0,0007134
100
1,595
0,0007233
100
0,817
0,0007357
100
0,766
0,0015449
100
0,793
0,0016807
100
0,819
0,0026893
100
0,786
0,002895
90
1,765
0,0029908
90
1,345
0,0031706
100
0,808
0,0052072
80
1,641
0,0060584
80
1,856
0,0064133
100
1,983
0,0078602
80
1,6
0,008215
70
1,762
0,008942
80
0,851
0,0089818
90
1,958
0,0093801
70
1,35
0,0095842
80
1,674
0,0122341
60
0,835
0,013404
60
1,363
0,0161045
50
1,283
0,0174535
60
1,276
0,0179111
50
1,765
0,0186502
40
1,629
0,0231142
40
0,085
0,0233194
40
1,253
0,0240755
60
1,506
2
OC179 – MITO2 patients’ stratification according to
Residual disease
1.0
the molecular classifier
0.4
0.2
PFS
PFS
0.6
0.8
OD
SOD
Log-rank P<1.001
0.0
Log-rank P<1.001
0
20
40
60
80
100
time
(months)
Time
(months)
n°
high risk 89
low risk 90
events median 0.95Cl HR
72
18
15-22 1.85
52
38
24-nyr
OD
SOD
n° events median 0.95Cl
115
71
34
24-54
64
53
15
12-18
HR
2.1
2
Stratification for risk prediction and RD improved prognosis of a patients’ subgroup
0.8
1.0
Stratification for risk prediction and RD improved prognosis of a patients’ subgroup and
identified a subset of patients with favorable clinical prognostic marker and high risk of relapse
0.4
0.2
miRLr-SOD 26
miRHr-OD 51
miRHr-SOD 38
0.0
TTRPFS
0.6
n° events median 0.95Cl
miRLr-OD 64 33
53
34-nyr
0
20
40
60
80
19
38
34
100
time (months)
Time (months)
High risk-OD includes 9 stage I-II
patients defined NED at primary
surgery
15
21
15
11-nyr
15-34
10-21
2
Molecular classifier validation on independent datasets
OC452 TCGA
OC263 – INT-CRO
P=0.0045
P=1.33E-14
n
events median 0.95CI HR
high risk
low risk
miR=L
122
73
34
26-45 3.16
Sample size
141
122
miR=HPFS (months)
141 12 122
12 3410-13
Median
n high
events
0.95CI
risk median low
risk HR
1.39
miR=L size 169 283
115
19
17-27
Sample
169
miR=H PFS (months)
283 15.2
212
15
14-18
Median
18.7
HR= 0.356
HR= 0.72
95% CI = 0. 267 to 0.476
95% CI = 0. 58 to 0.899
Stratification for risk prediction and RD improved prognosis of a patients’ subgroup
and identified a subset of patients with favorable clinical prognostic marker but high
risk of relapse
1.0
2
59
62
46
27
13
10
42
18.5
11-15
7-12
34-62
10-26
High risk-OD includes 8 stage I-II
patients, 7 defined NED at primary
surgery
0.6
TTR
71
69
90
32
0.4
PFS
n° events median 0.95Cl
miRLr-OD 90 46
42
34-62
0.2
OC263
0.8
miRH_ OD
miRH_ SOD
miRL_ OD
miRL_ SOD
0.0
miRLr-SOD 32
miRHr-OD 71
miRHr-SOD 69
0
20
40
60
time (months)
80
100
27
59
62
18
13
10
10-26
11-15
7-12
120
1.0
Time (months)
0.6
TTR
n events median
188
134
15
66
61
15
122
75
21
34
31
14
0.95CI
13-18
12-18
18-27
12-19
High risk-OD includes 14 stage I-II
patients, 11 defined NED at primary
surgery
0.4
PFS
0.2
n° events median 0.95Cl
miRLr-OD 122 75
21
18-27
miRLr-SOD 34 31
14
12-19
miRHr-OD 188 134
15
13-18
miRHr-SOD 66 61
10
12-18
0.0
OC452
0.8
miRH_OD
miRH_SOD
miRL_OD
miRL_SOD
0
20
40
60
80
100
2
1.0
No interaction with treatment arm
miR_treat
0.2
0.4
miR-Low risk
miR-high risk
0.0
PFS
PFS
0.6
0.8
L_PC
L_PT
H_PT
H_PC
0
20
40
60
80
time (months)
Time (months)
100
2
The miRNA molecular classifier is an independent prognostic marker
Univariate analysis
OC179
(n=168,
events=116)
OC263
(n=262,
events=194
TCGA
(n=409,
events=300)
Multivariable analysis
HR
(95%CI)
4.7
2.4-9.3
2.1
1.5-3
miRNA predictor
High vs Low risk
Stage
1.85
1.29-2.6
III-IV vs I-II
2.16
1.25-3.73
<0.001
2.16
0.009
Surgical debulking
SOD vs OD
2.23
1.67-2.9
<0.001
1.53
0.006
3.16
2.3-4.3
<0.001
3.09
<0.001
1.68
1.01-2.78
0.04
1.79
1.04-3.08
0.03
1.37
1.07-1.75
0.012
1.27
0.99-1.63
0.059
1.39
1.1-1.74
0.004
1.41
1.11-1.79
0.005
Stage
III-IV vs I-II
Surgical debulking
SOD vs OD
miRNA predictor
High vs Low risk
Stage
III-IV vs I-II
Surgical debulking
SOD vs OD
miRNA predictor
High vs Low risk
P*
<0.001
<0.001
<0.001
HR
(95%CI)
P*
3.7
1.8-7.5
1.46
1.01-2.1
0.043
1.48
1.03-2.1
0.036
<0.001
Covariates:
Stage:
III-IV vs. I-II
Residual disease: >1cm vs. <1cm
35 miRNA model: above threshold cut-off vs. below threshold cut-off
The miRNA molecular classifier is an independent prognostic marker also in HGSOC subgroup
2
MITO2 miRNA profiling: conclusions
Punti di forza:
 prima meta-analisi di miRNAs su EOC
 EOC dataset al momento più numeroso (n=894; OC179 da MITO2; OC263 da INT-CRO; OC452 da
TCGA)
 meta-analisi su diverse piattaforme
 analisi di sottotipi miRNA integrabili con espressione genica (RNAseq) per sviluppo di modelli
predittivi di risposta
OC263 –INT-CRO
OC179 MITO2
OC452 –TGCA
P=3.98E-14
P=0.000742
Cl1
Cl2
Cl3
Cl4
P=0.00228
 Emendamento per RNAseq su MITO2 ed emendamento su MITO7 per validazione custom panel
miRNA/Genes
2
MITO2 miRNA profiling: conclusions
Punti critici:
 annotazioni diverse tra piattaforme con conseguente riduzione dei miRNA comuni alle
piattaforme
continuo aggiornamento miRBASE
 necessità di recuperare nuove casistiche indipendenti di validazione: MITO7, MITO16??
Ringraziamenti:
 Sandro Pignata, Danela Califano, Simona Losito, Gennaro Chiappetta, Massimo Di Maio,
Franco Perrone.................
 Loris De Cecco, Marina Bagnoli, Silvana Canevari, Francesco Raspagliesi, Ketta Lorusso,
Maria Luisa Carcangiu
 Giuseppe Toffoli, Erika Cecchin
 tutto il gruppo MITO
2
MITO2 miRNA profiling: future plans
miRNA expression patterns on OC179 identified 4 robust and stable patients’ subtypes
with different prognosis
Consensus matrix
OC179 MITO2
P=0.000742
Cl1
Cl2
Cl3
Cl4
miRNA subtype classifier maintained prognostic relevance in OC263 and TCGA case
materials
OC263 –INT-CRO
OC452 –TGCA
Strenght: possible integration
with gene expression profile to
predict response to therapy
P=3.98E-14
P=0.00228