Transcript Diapositiva 1 - Progetto Onev

IRCCS Istituto Tumori
Giovanni Paolo II, Bari, Italy
Omica e nanotecnologie negli ESSERI VIVENTI
Il Progetto ONEV
Biomarkers for therapeutic
response in metastatic melanoma
S. Tommasi
Bari, 1 Dicembre 2014
APPROVED AGENTS USED FOR THE TREATMENT OF METASTATIC MELANOMA
Treatment type
Approved drugs
Mechanism of action
Mechanism of resistance
Chemotherapy
DTIC, TMZ
DNA methylation
High expression MGMT
MMR deficiency
BER deficiency
Inhibition of BRAFV600
mutant
MAPK pathway reactivation
PI3K/AKT/mTOR reactivation
Trametinib
Blockade of MEK in
presence of BRAFV600
mut
MAPK pathway reactivation
IL2
Stimulation of T and NK
cell-mediated acitivities
Tumor escape from immune
surveillance mechanisms
Ipilimumab
Tremelimumab
CTLA4 blockade with
Low melanoma antigen
enhacement of effector expression
T cell function and
inhibition of Treg activity
Pembrolizumab
Nivolumab
Binding to PD-1 resulting
in enhancement of the
immune response
against tumor
Targeted therapy Vemurafenib
Dabrafenib
Immunotherapy
-
Base excision repair (BER) key factors :
predictive biomarkers - new promising targets for therapies
in detail
Liu L , and Gerson S L Clin Cancer Res 2006;12:328-331
PROGNOSTIC AND PREDICTIVE ROLE OF MGMT METHYLATION
Tuominen et al. 2014
Base excision repair (BER) key factors : new promising
targets for therapies
in detail
Liu L , and Gerson S L Clin Cancer Res 2006;12:328-331
Prognostic role in pts BRAF V600 untreated by Vemurafenib
APE1 inhibition induces a synthetic lethal response in PTEN-deficient cells by causing
accumulation of abasic sites and subsequent strand breaks, and ultimately the
induction of apoptosis
Abbotts R – Madhusudan 2014
BRAF
C A U S E S o f R A F k i n a s e I N H I B I TO R S R E S I TA N C E
NRAS & MEK
mutations
BRAF
amplification
Stromal
secretion of
HGF-like
COT or EGFR
activation
NF1 loss
↓ BIM
expression via
PTEN loss
Disrupted
feedback
regulation
MAPK pathway
44%
Downstreem effectors:
NRAS, BRAF, MAP2K1,
MAP2K2, MITF, NF1
Alternative
splicing of
BRAF mRNA
PI3K pathway:
PIK3CA, PTEN, PIK3R1
HOXD8
RAC1
Van Allen EM 2014
NRAS as predictive biomarker
PI3K i
MEK i
IL2
Ipilimumab
Next Generation Sequencing and Custom Ampliseq Panels:
a new opportunity to predict response to chemotherapy,
targeted therapy, immunotherapy……….
SENSITIVITY TO ……….
Project PON01_01297 “Virtualab”
Next Generation Sequencing and Custom Ampliseq Panels:
a new opportunity to predict response to targeted therapy
The aim was to identify mutations able to predict therapy response in a quick, accurate and cost
effective method. The panel was developed to analyze the coding region of 11 genes with a coverage of
93.85% . The melanoma custom panel size was 39.08Kb, contains 303 amplicons and for the analysis is
required an input of 20ng of FFPE DNA (2 pools).
Pinto confidential 2014
Patients in which at least one gene
results mutated
90
% of alterations
80
70
60
50
40
30
20
10
0
NRAS
CTLA4
MITF PIK3CA
KIT
BRAF MGMT PTEN
CDK4
RB1
MC1R
Pinto R confidential 2014
ION PGM, ARMS AND SANGER METHODS
ION PGM
Sanger Method
BRAF
V600 mut
n.11
1 false negative
BRAF
V600 wt
n.6
2 false positive
NRAS
Glu61 mut
n.2
ARMS Method
1 false negative
Pinto R confidential 2014
U S I N G c f D N A A D V A N TA G E S
 Analysis in the lack of tumor material in patients whose tumors are difficult to
biopsy
 The small amount of archival tumor tissue mixed with normal stroma tissue
 Degraded DNA by formalin fixation – cfDNA presented less non specific
amplifications
 Potentially mutant clones could be missed in biopsy from small part of tumor
 Shorten turnaround timefor testing
PRE-ANALYTICAL
AND ANALYTICAL PHASES
SERUM
PLASMA
Sensitivity
Specificity
Sensitivity
Specificity
44%
96%
52%
96%
95%CI 35%53%
95%CI 90%99%
95%CI 43%61%
95%CI 90%99%
More BRAF mutations were detected in
plasma than in serum although differences
in assay sensitivity and specificity are not
statistical different
Plasma contains less wt DNA than serum
but higher mutation fraction
CONCORDANCE
SERUM
PLASMA
64%
70%
Discordance between tumor and cfDNA could depend:
on time of sampling
Archival tumor biopsy did not fully represent the tumor heterogeneity
Different mutation status in primary and metastatic sites
Sensitivity of assays: ARMS  2%
Aung 2014
Biomarker analysis in Phase II Dabrafenib study
Ascierto JCO 2013
CORRELATION
tumor tissue - cfDNA
SPECIFICITY
SENSITIVITY
V600E
84%
100%
79%
V600K
97%
99%
89%
P=0.0134
Significant association between
baseline cfDNA mut fraction and OS
(HR:0,83; 95%CI, 0,72-0,96)
P=0.0006
Significant association between
baseline cfDNA mut fraction and PFS
(HR:1,09; n=46)
STUDY DESIGN
AIM: to individuate novel candidate peptides useful as biomarkers to predict the
response or resistance to treatment in two sets of patients treated with
TMZ/FM and vemurafenib
39 patients - serum
charge range
1,5 – 50 D  IMAC 30
19 BRAF V600E/K  Vemurafenib
17 BRAF wt
3 BRAF V600E
 Temozolomide/FM
Garrisi, Strippoli Plos One 2014
M/Z
P
ROC
Intensity
Intensity
Area
BRAF mut
BRAF wt
Regulation
9446
0,0148
down
0,715
6,182
8,43
9295
0,0217
up
0,715
16,709
8,296
1883
0,023
up
0,296
14,284
7,596
9176
0,025
down
0,704
6,9
8,22
4652
0,027
down
0,696
7,4
11,351
BRAF mut vs BRAF wt
Sequence
Acrostic name
Description
coverage
Score
(%)
SLAIN1
Invasiveness
GLIS2
ABCC12
Resistance
SLAIN motif-containing protein 1
20
38
Zinc finger protein
21
36
Multidrug resistance-associated protein 9
6
27
12
18
Cyclic AMP-dependent transcription
ATF6
factor
Garrisi, Strippoli Plos One 2014
VEMURAFENIB RESPONDERS VS NON RESPONDERS
Regulation in
M/Z
p-value
Shorter Resp
5900
0.019
Acrostic
Sequence
Description
name
Score
coverage (%)
up
12544
0.033
up
49124
0.048
up
11724
0.022
up
KLF17
Krueppel-like factor
31
40
RBM10
RNA-binding protein
12
26
20
22
TOX high mobility group box
TOX3
family member 3
PFS
P=0.0011
Regulatory activity of gene transcription
Basal Level
RNA alternative splicing
Overexpressed
Garrisi, Strippoli Plos One 2014
TMZ / FM RESPONDERS VS NON RESPONDERS
BRAF wild-type patients
Regulation in
M/Z
p-value
Resp
6411
0.022
Acrostic
name
NQO1
up
Description
Sequence
coverage
(%)
Score
NAD(P)H dehydrogenase [quinone] 1
21
28
25
28
COMM domain-containing protein - HypertensionCOMD5
4075
0.020
Related Calcium-Regulated Gene Protein
up
CA4
Carbonic anhydrase 4
18
26
VATL
V-type proton ATPase 16 kDa proteolipid subunit
41
26
TM50A
Transmembrane protein 50A
37
26
PFS
P=0.0024
Pathway of detoxification
Overexpressed
Cell acidification
Basal level
Garrisi, Strippoli Plos One 2014
miRNAs
NEW PREDICTIVE BIOMARKERS?
Greemberg 2014
miRNA expression in Metastatic Melanoma
* Our cohort included 43 patients (treatment naïve and with histologically confirmed stage IV of metastatic
melanoma), 30 cases were BRAF mutated at the codon 600, while 13 were wild type;
* We have selected 15 miRNAs that scientific reports and informatics tools have established to target the crucial
genes involved in melanoma biology.;
* We analyzed miRNAs expression and the expression of the correspondent target genes by TaqMan probes;
* We correlated miRNAs and gene expression data to time to progression of 20 patients treated with Vemurafenib.
Pinto R confidential 2014
Non -invasive biomarkers : circulating miRNAS
Proteic
complexes
Tumor miRNA
biogenesis
Tailored therapy
Microvescicles
Clinical decision
miRNA release
Clinical biomarkers
Prognosis
miRNA extraction
(blood)
Apoptotic
bodies
Passive
delivery into
bodily fluids
Quantification
qRT-PCR
EXPERIMENTAL WORKFLOW
BLOOD BASED miRNA STUDY AND ADVANTAGES
 Non invasive technique
 Possibility to multiple time point sampling
 Tissue specific dysregulation
 Stability to RNAase digestion, harsh conditions.
Extended storage and multiple freeze-thaw cycles.
Circulating mir125b expression in response to TMZ/FE treatment: preliminary results
TP53
DNA repair and
damage
prevention
De Summa confidential 2014
Cellular
senescence
CONCLUSIONS
Deregulated miRNAs and their respective targets may
serve as molecular targets/tools for future platform
of molecular directed therapy or as predictive
biomarkers in melanoma patients.
Only integrated studies on genetics and
epigenetics are needed to evidence a
complete pattern of pharmacological
sensitivity
THANKS to:
Molecular Biology Laboratory
Pinto R.
De Summa S.
Garrisi V.M.
Medical Oncology Unit
Guida M.
Strippoli S.
Anatomopathology Unit
Simone G.
Popescu O.
In vitro Pharmacology Laboratory
Azzariti A.
Porcelli L.
Quatrale A.E.
Biology & Biochemistry Lab
Univ Bari
Guida G
Maida I.
Cocco T.
Grieco C.
PON01_01297 Virtualab
PONa_00034 ONEV