Transcript A miRNA-based predictor of EOC early relapse

Department of Experimental Oncology and Molecular Medicine
Unit of Molecular Therapies
XXVIII^ Riunione Nazionale MITO
“Il lato oscuro di Venere”.
Mesagne (BR) January 19-20 2017
miRNAs come biomarcatori nel carcinoma ovarico
Delia Mezzanzanica
Biomarker definition
A biomarker is ‘ a characteristic that is objectively measured and evaluated as an indicator of
normal biological processes, pathologic processes, or pharmacologic responses to a therapeutic
intervention’. Biomarkers Definitions Working Group (National Institutes of Health 2001)
Biomarkers can be specific cells, molecules, genes, gene products, enzyme or hormone evaluated
for: disease prevention, diagnostic ad prognostic assessment, drug target identification and drug
response.
Biomarkers can be divided into integral, integrated and exploratory
ENGOT OV-16 NOVA (Niraparib maintenance in Pt-sensitive recurrent EOC) trial included:
Integral biomarker, detection of germline BRCA mutation (gBRCAmut) before randomization for
treatment with a PARP inhibitor vs placebo.
Integrated biomarker, HRD status in the non gBRCAmut arm to assess the treatment efficacy in
HRD-positive population in terms of progression free survival.
Exploratory biomarker, in non-gBRCAmut HRD-positive cohort, impact of somatic BRCA mutation
on progression free survival.
GCIG Brainstorming TR meeting, Lisbon 2016
microRNAs are non-coding RNA that regulate many biological processes by
controlling gene expression.
miRNAs
are
transcribed
by RNA
polymerase II into long pri-miRNAs that
are cleaved by DROSHA to form
precursor miRNA (pre-miRNA).
After nuclear export to the
cytoplasm pre-miRNAs are directly
processed by DICER and cleaved to
generate a 22 nt miRNA duplex. The
miRNA guide strand (highlighted in
red), is incorporated into RISC.
miRNAs mediate gene silencing via mRNA target
cleavage and degradation or translational repression,
depending on the complementarity between miRNA and
targeted mRNA.
Adams BD et al. Curr Biol 2014
Role of miRNAs
 Each miRNA can bind to and regulate multiple mRNAs.
 Aberrant expression of a single miRNA can affect translation of multiple
genes within a cell, leading to profound phenotypic responses.
 miRNA effects on target genes are tissue specific.
 miRNA expression signatures are associated with tumor type, tumor grade
and clinical outcomes, therefore miRNA could be potential candidates as:
 diagnostic biomarkers
 prognostic biomarkers
 therapeutic targets or therapeutic tools.
 Potential minimal invasive, diagnostic, and prognostic marker. miRNAs can
be found circulating in peripheral blood and body fluids, they are very stable,
bound to protein complexes or incorporated into micro vesicles (exosomes)
resistant to degradation by RNAses.
Therapeutic potential of miRNAs
miRNAs can function as either oncogenes (targeting oncosuppressive genes) or
tumor suppressor (targeting oncogenic genes).
miRNA mimics (miRNA replacement therapy) to restore loss-of-function
inhibition of the upregulated oncomiRs using antisense miRs (miRNA inhibition
therapy)
In hepatocellular carcinoma, miR-34 was recognized to be frequently
downregulated: phase I clinical trial in patients with hepatocellular carcinoma
or liver metastatic cancer with MRX34, a miR-34 mimic.
The miR-34 family has been shown to be significantly downregulated also in
OC.
Biospecimens
Biospecimens them self have become objects of investigation for
translational research and precision medicine.
Cancer research being genomics, proteomics, metabolomics depends on
biospecimens, and finding the right targets for detection, therapy and
prevention relies on the high quality of patient-derived specimen.
GCIG Brainstorming TR meeting, Lisbon 2016
miRNAs and ovarian cancer
Two of the most frequently identified, deregulated miRNAs in OC are the miR-200 and
the let-7 families.
The miR-200 family (miR-200a, miR-200b, miR-200c, miR-141, and miR-429) is involved in
EMT regulation. No definitive conclusions on the prognostic impact of the miR-200
family in OC have been drawn due to diverging results. However the majority of the
studies show that high miR-200 expression is linked to a favorable prognosis.
The human let-7 family (Let-7a, Let-7b, Let-7c, Let-7d, Let-7e, Let-7f, Let-7g, Let-7i,
miR-98, and miR-202) is known to suppress multiple oncogenes in OC and to inhibit cell
cycle activators, is reported to be frequently downregulated in OC and therefore is
believed to function as a tumor suppressor.
miRNAs and ovarian cancer
Several miRNA families with a prognostic role in the neo-adjuvant
chemotherapy setting of HGSOC (analysis on primary tumor and on sample at
interval surgery).
Integrated analysis of miRNA and gene expression profiles in stage I EOC
allowed identification of a prognostic pathway (16 miRNAs and 10 genes)
associated with overall survival and progression-free survival
Importance of future longitudinal
management of relapsed EOC.
analyses
to
improve
the
clinical
Our effort: profile for miRNA and GE synchronous primary tumors,
secondary localizations and relapses.
A. Definition of a miRNA-based predictor of EOC early relapse :
a team work
Surgeons
Tumor samples collection
during surgical procedures
Pathologists
Pathological evaluation
and sample selection
Oncologists
Follow up and clinical
data collection
Researchers
RNA extraction/quality control,
Profiling, Data analysis
Profiling
data
Clinical
data
Data matrix
generation
and analysis
 Case materials
Three chemo-naive case materials were used for this study:
-OC179 FFPE material, derived from the MITO-2 clinical trial (carboplatin/taxol vs carboplatin/caelyx)
-OC263 Frozen (and FFPE) material, collected at INT-MI and CRO-Aviano
-OC452 TCGA public dataset collection
894 EOC cases:
the largest collection so far analyzed
A miRNA-based predictor of EOC early relapse- Discovery Phase
published
type of
material
n°
samples
profiling
miRNA
platform
n° of miRNA
on array
MITO2 OC179
Present study
FFPE
179
INT-MI
Agilent miRBASE 17
1512
INT-MI
Illumina v2
miR-BASE 12
public
dataset
Agilent
miR-Base 10
OC263
INT_CRO
ID
OC130
Bagnoli&DeCecco
frozen/FFPE
Oncotarget 2011
TRAINING
SET
130
OC133
Present study
frozen
133
TCGA OC452
Nature 2011
frozen
452
1146
VALIDATION
(including
SET 1
putative)
723
VALIDATION
SET 2
 Data preprocessing
- filtering for exclusion of miRNA not detectable in all samples
- reannotation on miRBase 21.0
- exclusion of viral miRNAs, putative miRNA, not specific or discontinued probeset
385 unique miRNA shared among all studies following reannotation
A miRNA-based predictor of EOC early relapse- Discovery Phase
 Development of the model
TRAINING SET (OC179 MITO2 case material)
Clinical end-point:
time to progression /relapse
1. Calculate the prognostic index (risk-score)
- Calculation of the prognostic risk score
Selection of the features entering into the model: semi supervised method, using the relative
expression of the selected 385 miRNAs and their impact (weight) on progression free survival.
- Internal validation (10-fold cross validation approach)
Reiterative process of classification to define the risk-score
2.
Patient stratification
A new sample is predicted as high (low) risk if its prognostic risk score is larger than (smaller
than or equal to) the calculated prognostic index median value obtained in cross-validation.
Low risk
we developed a model named
MiROvaR
containing 35 unique miRNAs for
the identification of patients at
high risk of relapse/progression
High risk
hsa-miR-890
hsa-miR-513a-5p
hsa-miR-513b-5p
hsa-miR-135b-5p
hsa-miR-141-3p
hsa-miR-200c-3p
hsa-miR-429
hsa-miR-200a-3p
hsa-miR-200b-3p
hsa-miR-592
hsa-miR-508-3p
hsa-miR-514a-3p
hsa-miR-509-3p
hsa-miR-509-5p
hsa-miR-506-3p
hsa-miR-507
hsa-miR-143-5p
hsa-miR-486-5p
hsa-miR-195-3p
hsa-miR-23a-5p
hsa-miR-193b-5p
hsa-miR-574-5p
hsa-miR-99b-5p
hsa-miR-151a-3p
Hsa-iR-30d-5p
hsa-miR-423-5p
hsa-miR-30b-3p
hsa-miR-330-3p
hsa-miR-452-5p
hsa-miR-100-3p
hsa-miR-193a-5p
hsa-miR-29c-5p
hsa-miR-29a-5p
hsa-miR-484
hsa-miR-769-5p
A miRNA-based predictor of EOC early relapse- Discovery Phase
 Validation of the model
MiROvaR stratified patients in High and Low risk of relapse with significantly different time to relapse
TRAINING SET – OC179
MiROvaR score
1.0
Progression FreeSurvival
VALIDATION SET 1 – OC263
LOW
HIGH
0.8
VALIDATION SET 2- TCGA
1.0
1.0
0.8
0.8
0.6
0.6
0.4
0.4
0.2
0.2
0.2
0.0
0.0
log-rank p= 0.00068
0.0
0
20
40
60
80
100
120
HR 3.16 (95%CI:2.33-4.29)
log-rank p<0.0001
0
Risk
prediction
Low
High
N°
patients
90
89
Events
52
72
Median
PFS
38
18
95%CI
24-nyr
15-22
20
40
60
80
100
Risk
prediction
Low
High
N°
patients
122
141
Events
73
122
Median
PFS
34
12
HR 1.39 (95%CI:1.11-1.74)
log-rank p=0.0045
0.4
120
0
time (months)
time (months)
0.6
95%CI
26-45
10-13
Risk
prediction
Low
High
20
40
N°
patients
169
283
60
Events
115
212
The miRNA classifier maintained its independent prognostic impact
after adjustment for the two strongest prognostic clinical variables for EOC:
Residual Disease after primary surgery and FIGO stage.
MiROvaR Adjusted HR: 3.09 (95%CI: 2.24-4.28), pval <0.0001
1.41 (95%CI: 1.11-1.79), pval=0.0047
80
time (months)
OC2634
TCGA
100
Median
PFS
19
15
120
95%CI
17-27
14-18
A miRNA-based predictor of EOC early relapse- Discovery Phase
Low risk
High risk
hsa-miR-890
hsa-miR-513a-5p
hsa-miR-513b-5p
hsa-miR-135b-5p
hsa-miR-141-3p
hsa-miR-200c-3p
hsa-miR-429
hsa-miR-200a- 3p
hsa-miR-200b-3p
hsa-miR-592
hsa-miR-508-3p
hsa-miR-514a- 3p
hsa-miR-509-3p
hsa-miR-509-5p
hsa-miR-506-3p
hsa-miR-507
hsa-miR-143-5p
hsa-miR-486-5p
hsa-miR-195-3p
hsa-miR-23a-5p
hsa-miR-193b-5p
hsa-miR-574-5p
hsa-miR-99b-5p
hsa-miR-151a-3p
Hsa-iR- 30d-5p
hsa-miR-423-5p
hsa-miR-30b-3p
hsa-miR-330-3p
hsa-miR-452-5p
hsa-miR-100-3p
hsa-miR-193a-5p
hsa-miR-29c-5p
hsa-miR-29a-5p
hsa-miR-484
hsa-miR-769-5p
MiROvaR contains 35 unique miRNAs with individually different
relevance and individually different impact on patients’ prognosis.
Among the 16 miRNAs that gave 100% of cross-validation support
to the classifier,
13/16 were individually associated to favorable prognosis
3/16 were individually associated to poor prognosis
Maintenance/loss of potentially oncosuppressive miRNAs has
a greater impact on EOC prognosis than expression/loss of
potentially oncogenic miRNAs.
4/5 miR-200 family members are included in the classifier as
main contributors with potentially oncosuppressive role
miR-506 family members are included in the classifier as main
contributors with potentially oncosuppressive role, confirming our
previous data.
Bagnoli&DeCecco et al, Oncotarget 2011
Liu et al , JNCI 2015
Sun et al J Pathol 2015
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
miRNA-506 in EOC
miR-506 expression is associated with a better response to therapy and longer PFS and OS
miR-506 downregulation promotes an aggressive phenotype
Ectopic expression of miR-506:
inhibited cell proliferation
promoted senescence via direct targeting CDK4 and CDK6
suppresses the CDK4/6-FOXM1 signaling pathway, which is activated in the majority of ovarian
carcinomas
Inhibits EMT, cell migration and invasion by targeting SNAI2
simultaneously suppressed Vimentin and N-cadherin
increases sensitivity to cisplatin and olaparib by targeting RAD51 to suppress HR-mediated
repair of double-strand breaks
MiROvaR
a strong predictor of EOC risk of progression/relapse
Relevance of EMT processes in EOC aggressiveness
To stratify patients according to risk of progression regardless of clinical-pathological
characteristics of tumor at presentation
 Suitable in several clinical settings to contribute to a more precise patients’ selection
-
refine selection of high-risk subgroup of patients who may experience
an OS advantage after Bevacizumab treatment (ICON7 trial)
- selection of stage I-II patients likely to relapse and who can really benefit from
chemotherapy
Next steps: toward a clinical grade assay
- TEST VALIDATION PHASE
(external validation, selection of method, number of features)
- EVALUATION FOR CLINICAL UTILITY
(prospective clinical trial)
Acknowledgements
Department of Experimental Oncology and Molecular Medicine
Unit of Molecular Therapies
Functional Genomics
Delia Mezzanzanica
Silvana Canevari
Paola Alberti
Roberta Nicoletti
Loris De Cecco
Edoardo Marchesi
Dept of Gynaecologic Oncology
Dept of Pathology
Francesco Raspagliesi
Domenica Lorusso
Antonino Ditto
Maria Luisa Carcangiu
Barbara Valeri
Wei Zhang
Anil Sood
Sandro Pignata
Francesco Perrone
Daniela Califano
Simona Losito
Massimo di Maio
Gennaro Chiappetta
Giosué Scognamiglio
Erika Cecchin
Giuseppe Toffoli
Roberto Sorio
Vincenzo Canzonieri
Gustavo Baldassarre
Funding
Thank you for your attention