Transcript A R. Thierry - Master Biologie Santé

Intérêts de l’analyse de l’ADN circulant
en oncologie digestive
Alain R. Thierry
Directeur de Recherche, INSERM
Institut de Recherche en Cancerologie de Montpellier
Inserm U1194 – IRCM, Montpellier
Biomarkers for Solid tumors
Department
of Specialized Biology
Department
of Pathology
Blood
collection
FFPE
microdissection
Biomarkers
-free proteins
-cell receptors
-NA sequences
Circulating
Tumor Cells
Biomarkers
-free proteins
-cell receptors
Immunology
LIQUID BIOPSY
A.R. Thierry
Confidential
Circulating
Nucleic Acids
Circulating DNA: an old discovery, a late development
Thierry et al, 2014
Circulating or Extracellular Nucleic Acids
Circulating Fluids
Non circulating Fluids
• Serum / plasma
• Lymphatic fluids
•
•
•
•
•
•
•
Ascites
Milk
Feces
Urine
CFS
Saliva
Mucous lavage
Circulating NA
Extracellular NA
Cell culture supernatants
cell lines,
primary cells,
organoid
embryo cultures
Distinct cellular origins of cfDNA
Primary tumor:
Processes:
Blood stream:
Malignant cells
Non-malignant cells
Apoptosis, Necrosis, Active release, Phagocytosis, Cell detachment
Tumor-derived cell free DNA (ctDNA)
Distinct cellular origins of cfDNA
Healthy non tumoral cells
Primary tumor:
Processes:
Blood stream:
Malignant cells
Non-malignant cells
Apoptosis, Necrosis, Active release, Phagocytosis, Cell detachment
Tumor-derived cell free DNA (ctDNA)
Non-tumor cell-free DNA
Distinct cellular origins of cfDNA
Healthy non tumoral cells
Primary tumor:
Processes:
Blood stream:
3 cfDNAorigins:
Malignant cells
Non-malignant cells
Apoptosis, Necrosis, Active release, Phagocytosis, Cell detachment
Tumor-derived cell free DNA (ctDNA)
Malignant cell-derived ctDNA
Non-malignant cell-derived ctDNA
Non-tumor cell-free DNA
Germline cfDNA
Circulating DNA vs Circulating Tumor Cells
« there is a discrepancy between the number of CTCs and the quantity of
cfDNA in the blood. A single human cell contains 6 pg of DNA and there is a
median of 17 ng of DNA per ml of plasma in advanced-stage cancers; therefore,
if CTCs were the primary source of ctDNA it would require over 2,000 cells per
ml of plasma. In reality, there are, on average, less than 10 CTCs per 7.5 ml
blood »
Crowley, Nature Reviews Clinical Oncology 10, 472-484 (August 2013)
Our data: there are between 50 and 1,000 times more Genome
equivalents in ccfDNA as compared to CTCs
ccfDNA do not derive from CTCs
Much higher analytical signal when analyzing tumor cell DNA
Various types and structure of circulating nucleic acids
Schwarzenbach et al., Nat Rev Cancer 2011
Various forms of ccfNA
Nucleosome
Exosome
Apoptotic bodies
ProteoLipidoNucleic complexes
Membrane bound
Types of Nucleic acids
Genetic and epigenetic alterations
DNA (nuclear and mitochondrial)
RNA
miRNA
•Mutation and polymorphism
•Microsatellite alteration
•Methylation
•Copy Number Variation
Detection of Tumor-associated genetic aberrations in ccfDNA
SNPs & Point mutations
KRAS, BRAF, PIK3CA,
EGFR, APC, TP53….
MSI, LOH, AI
Chromosomal alterations
Epigenetic alterations
Crowley, E. et al. (2013)
Nat. Rev. Clin. Oncol
cfDNA originated from numerous types of cancer
Bettegowda et al, 2014
Applications of ccfDNA analysis in
oncology
Promises of personalized cancer medicine
Patient stratification based therapy
Clinical progression
Predictive information
(theragnostics)
Personalized medicine
by longitudinal follow up to potentially
examine:
1. Surveillance of the recurrence
2. Detection of the minimal residual
disease
3. Therapy monitoring
4. Detection of resistance
5. Prognosis
Intplex : an ASB Q-PCR derived method dedicated to tumour ccfDNA study
INFORMATION:
300 bp
•qualitative:
60 bp
60 bp
Detection of
point mutation
•quantitative:
Total ccfDNA
concentration
•quantitative:
Mutant ccfDNA
concentration
•quantitative:
Mutant ccfDNA
proportion
Fragmentation
•quantitative:
index
• Single-copy detection of variant alleles down to a sensitivity of 0.005% mutant to WT ratio.
14
Scheme of the positive wells to the detection KRAS G12V point mutation
when the ctDNA fragment quantification is under Poisson law
Probability distribution law applied to discrete quantitative variables expressed as the observed event number
in case of rare events being independent and randomly in a space/volume
Platform LC40, Roche
Platform CFX, Bio-Rad
Pastor et al, submitted
Theoretically
1 molecule
1 mutant cirDNA copy out of 260 000 WT CirDNA copies in the Q-PCR reaction mixture
1 specific cirDNA fragment out of 10 billions non specific CIRDNA fragment in blood
Intplex : an ASB Q-PCR derived method dedicated to tumour ccfDNA study
INFORMATION:
300 bp
•qualitative:
60 bp
60 bp
Detection of
point mutation
•quantitative:
Total ccfDNA
concentration
•quantitative:
Mutant ccfDNA
concentration
•quantitative:
Mutant ccfDNA
proportion
Fragmentation
•quantitative:
index
• Single-copy detection of variant alleles down to a sensitivity of 0.005% mutant to WT ratio.
• Targeted method for known mutations applicable to all mutations and all genes
• The only method enabling muti-marker analysis of ccfDNA in a single run
16
Context of the study
Anti-EGFR Targeted Therapies are restricted to Ras Wt patients
JCO, 2008
KRAS (exon 2) mutations leads to resistance to
anti-EGFR targeted therapies
Sridharan et al, 2014
~50 % of mCRC patients
are mutants for KRAS ,
NRAS mutations
Primary resistance to
anti-EGFR
2008 FDA/EMA : Cetuximab and
Panitumumab are restricted to KRAS (exon 2)
wild type patients
~10 % of mCRC patients
are mutants for BRAF
V600E mutations
Poor prognosis
The first clinical validation of the analysis of circulating DNA in oncology
First blinded clinical study
Following STARD criteria
Prospective, multicentric
KRAS/BRAF
* 106 mCRC patients
The first clinical validation of the analysis of circulating DNA in oncology
100% success rate
Unprecedented concordance rate
Sensitivity : Detection of mutation.
Specificity :Detection of WT
Thierry AR et al, Nat Med, 2014
19
Clinical utility of the analysis of circulating DNA
in just-in-time basis and in clinical setting
Kplex2 is equivalent to Kplex1 (prospective, multicentric blinded clinical study
comparing the determination of KRAS and BRAF mutational status performed
from tumor tissue and from plasma of mCRC patients).
Differences:
•11 clinical centers from France
•ancilliary studies: -KRAS exon 3 and 4 and NRAS
-Evaluation of the four other
parameters
•Just-in-time analysis of plasma
•No cfDNA level threshold (higher sensitivity)
140 included patients
•
comparison for the 7 KRAS mutations based on 121 matched tumor tissue and plasma
•
comparison for the BRAFV600E mutation based on 96 matched tumor tissue and plasma
NUMEROUS ADVANTAGES OF PLASMA ANALYSIS
Tumor Tissue Analysis
Plasma Analysis
And higher sensitivity:
• Kplex2 confirms Kplex1 data
• Low frequency mutation (in terms of mutation load) detected (down to 0.003%)
First potential clinical impact: reduction of anti-EGFR in mCRC
while consequently enhancing response rate
Tumor heterogeneity:
Clonal expansion of the colorectum
clonal heterogeneity
1. Intra-tumoral
2. Inter-tumoral
3. temporal
Uchi R. Integrated Multiregional Analysis Proposing a New Model of
Colorectal Cancer Evolution. Plos Genet. 2016 Feb 18;12(2):
IntPlex surpasses all methods developed in the field
in regards to the detection of hotspot mutations
And this is supported by an obvious rationale based on clear observation: based on the fact that ctDNA
analysis represent a wider genetic picture of the entire tumor mass, and

Since there is a clonal intra-tumor heterogeneity, genetic alterations can be missed depending on
what area of the tumor is sampled;

since there is a clonal inter-tumoral heterogeneity, some mutations specific to the metastasis
tissue won’t be detected from the resected primary tumor specimen;

since dynamic genetic changes often occur in the course of tumor growth and treatment over
time, there are loss and gain of mutations;
As such tumor tissue testing does miss a fraction of mutations present in ctDNA (up to 25%)
IntPlex testing
optimal hotspot mutation profile.
IS TUMOR TISSUE ANALYSIS STILL THE GOLD STANDARD?
Tumor Tissue Analysis
Plasma Analysis
And higher sensitivity:
• Kplex2 confirms Kplex1 data
• Low frequency mutation (in terms of mutation load) detected (down to 0.003%)
First potential clinical impact: reduction of anti-EGFR in mCRC
while consequently enhancing response rate
Kplex R study: Tracking acquired resistance under treatment
by longitudinal molecular analysis
Under represented mutant subclones are
selected under anti-EGFR therapy leading
to subsequent resistance
Tracking resistance in mCRC patients under EGFR therapy
Clinical study (NTC00501410); MD Anderson Cancer Center, Houston, Dr. S. Kopetz
Title: Dual Inhibition of EGFR and c-Src by Cetuximab and Dasatinib Combined With FOLFOX
Chemotherapy in Metastatic Colorectal Cancer
Goal Phase II: Study is to learn if Dasatinib given in combination with FOLFOX with or without
Cetuximab can help to control metastatic colorectal cancer
46 patients who become refractory to Cetuximab or Dasatinib
combined with Folfox chemotherapy
Total of 79 different plasma samples
Retrospective blinded study
Baseline
Before treatment
Cycle 4
Cycle 8
Cycle 12
2 months
4 months
6 months
Cycle 16
OFF STUDY
8 months
confidential
Technical Challenges
Main issue : sensitivity
Targeted methods
IntPlex
Sequencing methods
Singlelocus assay Beaming
Digital PCR
TAm-Seq
NGS
Wholeexome
seq.
Genomic bases
screened/run
1~20
1~8
1~10
104
103-108
108
Sensitivity
<0.01%
<0.05%
<0.1%
0.2%
1%
10%
Cost per sample
($)
~400
~700
~700
1,000
1,000
3,000
Data turnaround
2 days
2 days
6-10 days
2 weeks
1 month 2 months
Increasing sensitivity for rare mutations
Increasing genomic coverage
Increasing cost
Increasing data turnaround time
Main issue : sensitivity
Targeted methods
IntPlex
Sequencing methods
Singlelocus assay Beaming
Digital PCR
TAm-Seq
NGS
Wholeexome
seq.
Genomic bases
screened/run
1~20
1~8
1~10
104
103-108
108
Sensitivity
<0.01%
<0.05%
<0.1%
0.2%
1%
10%
Cost per sample
(RAS, $)
~400
~700
~700
1,000
1,000
3,000
Data turnaround
2 days
2 days
6-10 days
2 weeks
3 weeks
2 months
Increasing sensitivity for rare mutations
Increasing genomic coverage
Increasing cost
Increasing data turnaround time
Michael J.Bierer, ASCO 2015, Oral abstract session ‘Tumor Biology’
Main issue : sensitivity
Targeted methods
IntPlex
Sequencing methods
Singlelocus assay Beaming
Digital PCR
TAm-Seq
NGS
Wholeexome
seq.
Genomic bases
screened/run
1~20
1~8
1~10
104
103-108
108
Sensitivity
<0.01%
<0.05%
<0.1%
0.2%
1%
10%
Cost per sample
($)
~400
~700
~700
1,000
1,000
3,000
Data turnaround
2 days
2 days
6-10 days
2 weeks
30% mutant
samples would
have been missed
in our studies
1 month 2 months
Prognostic value of multiparametric analysis
* 106 mCRC patients.
Better than CEA
Higher levels of total
ccfDNA correlated
with diminution of
OS
El Messaoudi S et al, Clinical Cancer Research, submitted
31
Prognostic value of multiparametric analysis
43 mCRC patients KRAS or BRAF mutant
Lower survival with
Higher mutant
ccfDNA conc.
Higher mutation load
Higher ccfDNA
fragmentation level
32
*Screening
* Treatment monitoring
*Prognosis
*MRD detection
*Surveillance
of the recurrence
*Prediction of response (CDx)
*Detection of resistance
Initial response
CT +Anti-EGFR therapy
Surgery
m
Clone genotyping
and quantification
wt wt
m
m
Resected Tumor
Real
time
monitoring
Real time monitoring in the course of
CRC
patients
management care by plasma testing
lounches this week
companion diagnostics
testing RUO services
to physicians and analytical laboratories in various types of cancer for various genetic alterations.
KRAS
exon 2
KRAS exon
3/4
http://www.diadx.com
NRAS exon
2/3/4
BRAFV600
PIK3CA
EGFR
EGFR T790M
Exon 7/9/20 Exon 18-19-20-21
[email protected]
Team DNAplex
Safia El Messaoudi
Joelle Azzi
Anthony Laybats
Brice Pastor
Cynthia Sanchez
Alain Thierry
Amaelle Otendault
Rita Tanos
Florent Mouliere
Marc Ychou
Charles Theillet
Supports:
DNAplex group
Safia El Messaoudi
Brice Pastor
Romain Meddeb
Cynthia Sanchez
Amaelle Otendault
Rita Tanos
Alain Thierry
IRCM, Montpellier:
Céline Gongora
Maguy Del Rio
Bruno Robert
Caroline Mollevi (ICM)
Stanislas Du Manoir
Charles Theillet
ICM, Montpellier:
Oncologie digestive
Marc Ychou
Virginie Loriot
Frédéric Bibeau
Lab. Biologie Specialisée
Pierre-Jean Lamy
Evelyne Crapez
Former collaborator
Florent Mouliere
Lombardi Cancer Center
Washington DC, USA:
Anatoly Dritschilo
Dalong Pang
Clinical Collaborators
D. Pezet, CHU Clermont-Fd
M. Mathonnet, CHU Limoges
J. Robert, Inst. Bergonié,
Bordeaux
Scott Kopetz, MD Anderson,
Houston, USA
King’s College, London
Peter Gahan
OncoXL, Geneva
Maurice Stroun
Philip Anker
diadx.com
Cefipra
Cambridge Cancer Institute:
Nitzan Rosenfeld
CCMB, hyderabad, India:
Sridhar Rao
36