CDAC 2018 Cantor liquid biopsies

© 2015 Agena Bioscience.
All Rights Reserved. For Research Use Only.
Not for use in diagnostic procedures. Confidential.
The challenge of early
cancer detection by liquid
biopsy
Charles R. Cantor
Como, May 2018

© 2015 Agena Bioscience. All Rights Reserved. For Research Use Only. Not for use in diagnostic procedures. Confidential.
 Why early cancer detection is necessary
 DNA in plasma
 NIPT as a proof of concept
 Somatic mutation detection in tumor
biopsies versus plasma or urine
 Stochastic noise and how to overcome it
 Prospects for pre-symptomatic detection
2
Outline

 Annual routine inexpensive test from
blood, urine, or a buccal swab
 Must be inexpensive; good specificity and
sensitivity- i.e. few false positives and
false negatives
 Positives must be actionable- must reflex
to an established diagnostic test
3
Cancer screening in 2025

 Later stage tumors are extremely
heterogeneous
 Genome instability- mutator phenotype,
chromosome instability, massive
epigenetic alterations and probably
epigenetic instability
 Inexpensive cures are unlikely to be
achievable; therapy to combat disease
progression is extremely expensive
4
Why early detection is necessary

 Tumors very small and are likely to be
very similar to normal tissue
 Tumor-specific biomarkers will be present
at very low abundance in any sample that
can be obtained without biopsy
 Cost must be low
 Clinical trials are prohibitively expensive
5
Major challenges for early cancer
screening

 PCR and other amplification systems
allow robust detection of single molecules
 All aspects of sample preparation,
amplification and detection are generic
 Analysis is pretty cheap
 Multiplexing- it is routine to measure from
tens to thousands of analytes at once
6
Nucleic acids are the best biomarkers

 Sequences changes - definitively identify
a cancer and its drug sensitivity but are
hard to measure for early disease
 Chromosome copy number changes -
easy to measure but likely absent in early
disease
 Gene copy number changes - probably
not common many early cancers
 Methylation changes – interesting target!
7
Prioritizing biomarkers for early cancer
detection

Cell free DNA in plasma or urine
A mature commercial technique for non invasive prenatal
testing
Proven utility for monitoring transplant rejection
Very promising for monitoring cancer therapy and relapse
Possible utility in neurodegenerative diseases
Pre-symptomatic detection remains a future challenge

Characteristics of cell-free DNA in plasma
(half life 15 minutes)
• Amounts:
• Cellular DNA about 100 million molecules per ml
• Cell-free DNA 1,000 molecules per ml
• DNA from remote sites 100 molecules per ml
• Sizes:
• DNA from blood and endothelial cells about 160 base pairs
• DNA from remote sites about 145 base pairs
• Endosomes with DNA from distant sources about 10
molecules per ml
• Cells from distant sources about 1 molecule per ml
9

 Draw 10 cc of maternal blood; isolate 4
cc of plasma
 Random shotgun sequence and assign
sequences by comparing with an
assembled human sequence
 Ignore any sequence reads which cannot
be aligned to reference, ignore most or
all sequence differences from reference
Procedure for non-invasive prenatal testing by
analyzing fetal DNA in the mother’s blood
10

Principles of Fetal Aneuploidy Testing
 ~13% of the DNA fragments in
pregnant woman’s blood are from
the fetus ( )
 ~87% are from the mother ( )
18

GGCCCTGGGGACAGTCTCCAATCCACTGAGTCATCT chr10
GACACGGTGGAGCTCGGCCACACCAGGCCCAGCTGG chr14
ACAGTGGTGGGGCCCATCCCTGGGTGAGGCTCAGTT chr21
Principles of Fetal Aneuploidy Testing
TCCGCCCAGGCCATGAGGGACCTGGAAATGGCTGAT chr21
ACAGTGGTGGGGCCCATCCCTGGGTGAGGCTCAGTT chr21
Sequencing tells you
which chromosome
the fragment comes
from.
TCCGCCCAGGCCATGAGGGACCTGGAAATGGCTGAT chr21
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 X Y
19

Unaffected Chromosome 21 on left (2 fragments)
Affected Chromosome 21 on right (3 fragments)
Unaffected Fetus Fetus with Trisomy 21
Each fragment is
“x” thousands of counts.
20
Detecting a trisomy

Sequenom CMM Laboratory Cases,
Through March 2013
Bombard et al. Noninvasive prenatal testing (NIPT) in multiple gestations: A report of laboratory
experience. American College of Medical Genetics Annual Meeting. Poster. New Orleans, LA May
2013
14 | SCMM Slide CC-008

Reasons for NIPT Discrepancies
 Confined placental mosaicism
(CPM)
 Co-twin demise/vanishing twin
 Fetal mosaicism
 Maternal mosaicism
 Maternal malignancy
 Laboratory error
 Other

Oncology – Circulating Tumor DNA
Case 1
 Clinical indication – AMA
– Fetal fraction 48%
– Z21 3.15
– Z13 -10.68
– Z18 -39.70
Diagnosed 2 weeks post partum with
metastatic carcinoma.

Oncology – Circulating Tumor DNA
Case 2
 Clinical indication – AMA
– Fetal fraction 22%
– Z21 -11.62
– Z13 -15.83
– Z18 48.44
 Second aliquot
• Z21 -10.36
• Z13 -14.25
• Z18 46.75
Invasive
angiosarcoma

MaterniT21TM PLUS LDT:
Fetal Insertion – 18p+
Sequenom CMM – unpublished data
Information presented September 22, 2012; ACOG Districts VI, VIII, IX Annual Meeting; Phoenix, AZ

Preferential detection of methylated DNAof
Methylation Reaction
Step 3: Competitive PCR and and
single base extension
Step 1: CCF DNA isolation Step 2: DNA digestion using
methylation sensitive RE
D
C
Step4: Separation of analytes
using MassArray®
Unmethylated maternal DNA
Methylated fetal DNA (D)
19

Example a single methylation
marker
• Very low background in non
pregnant samples.
• Accurately identifies fetal DNA
percentage.
• Assay can identify sample with
no fetal DNA contribution.
Nygren et al Clin. Chem. 56:10 1627-1636 (2010)
20

Chromosome 21 Z score per Plate and
Complete Study results: epigenetic
testing
21

 We consider only bi-allelic single
nucleotide polymorphisms
 No tri-allelic loci, no insertions, deletions
 Focus just on sequence differences from
the reference loci
 Mendelian inheritance provides
relationship between fetus and parents
 No de novo mutations considered
22
A simple model for fetal sequencing

 Fraction fetal DNA , f, known or
determined by fitting data
 Sequence read depth is high- typically
100 x coverage
 For simplicity we consider just A/C SNPs.
All are equivalent
23
Fetal genome sequencing

Fetal DNA % Calculated for Each Chromosome
24 | Improving healthcare through revolutionary genetic analysis solutions

Types of SNPs Considered
SNP Category Parental Genomic DNA Analysis
Paternal Maternal
Genotype Genotype
Fetal Genotypes
Possible
1. A/A C/C AC
2. A/A A/A AA
3. A/C A/A AA or AC
4. A/A A/C AA or AC
5. A/C A/C AA or AC or CC
25 | Improving healthcare through revolutionary genetic analysis solutions

 Mother AA Father AC
 Fetus AA
 Allele frequencies A = 1 C = 0
Or
Fetus AC
Allele frequencies A = 1 – f/2 C = f/2
Thus from allele frequencies you know fetal
sequence at this location
26
Type 3 SNP’s

 Mother is AC Father is AA
 Fetus is AC
Allele frequencies A = 0.5 C = 0.5
Or
Fetus is AA
Allele frequencies A = 0.5 + f/2
C = 0.5 – f/2
Allele frequencies reveal fetal sequence
27
Type 4 SNP’s

28
Typical error rate of around 0.1% leads to false positives for all
sequence loci, and caps the minimum allele frequency detectable at
0.1%
To detect low allele frequencies require very high sequence coverage
To detect alleles at less than 1% requires “error free” double strand
sequencing which is still quite expensive
Sequencing will discover variants of unknown significance- what do
you tell the patient?
Limitations of DNA sequencing as a clinical
diagnostic tool

29
 Digital (droplet) PCR (Raindance, Biorad, Fluidigm,
Beaming)
 Single molecule sorting (Nanostream)
 DNA mass spectrometry (Sequenom, now Agena)
 Compare sensitivity, cost, flexibility, chances to create
custom assays, degree of target multiplexing
Genotyping – determining SNP’s
Techniques of intermediate complexity

30
DNA mass spectrometry
• PCR amplify 10 to 40 loci in a single microtitre
plate well
• Simultaneously sequence polymorphic loci
within these amplicons
• Results are much more sensitive, quantitative,
and cost effective than real time PCR alone
• Requires sequence to be approximately known
in advance

Genotyping by mass spectrometry
31
PCR and primer extension
DNA consists of a four-
letter alphabet:
A, C, G, T
Each letter (nucleotide)
has defined molecular
mass:
dAMP = 313.2 Da
dCMP = 289.2 Da
dGMP = 329.2 Da
dTMP = 304.2 Da

Haplotype Analysis with Multiplexed
Genotyping of Single DNA Molecules
Dilution5 ng Genomic DNA
~1600 copies
3 pg Genomic DNA
~1 copy
A/C C/GG/A
SNP1 SNP2 SNP3
Each SNP is genotyped, but phase
of SNPs is not determined.
A CG
Dilution into single molecule
physically separates two haplotypes
and simultaneous genotyping of all
three SNPs with multiplex assay
directly determines the haplotype
Chunming Ding
Bioinformatics Program and
Center for Advanced Biotechnology
Boston University

Confidential, Do Not Distribute
Routine Genotyping and Single
Molecule Genotyping
5 ng Genomic DNA
~1600 copies
3 pg Genomic DNA
~1 copy
Note: 3-plex PCR. P: unextended primer, A/G/C: individual genotype
3 different colors represent the 3 different assays in the 3-plex.
…………………………………
…….
Note: 3-plex PCR. P: unextended primer, A/G/C: individual genotype.
3 different colors represent the 3 different assays in the 3-plex.
Routine Genotyping and Single
Molecular Genotyping

Confidential, Do Not Distribute
0
10
20
30
40
50
60
Incomplete
multiplex
Both
Alleles
Haplotype
Percentage
Percentage
No PCR
product
1 DNA copy
1.6 DNA copies
3 DNA copies
Performance with Different Genomic
Concentrations

 Need to search for somatic (de novo)
mutations not present in normal tissue
 These mutations are difficult to distinguish
from sequencing errors- Mendelian
inheritance doesn’t help you
 Heterogeneity: you cannot tell which
mutations arose in the same cell
 Allele frequencies may be much smaller
35
Plasma DNA: Cancer is harder than
fetus

Biopsy Somatic Mutation Analysis
36
MassSpectra for a PIK3CA somatic mutation
 Used OncoCarta to screen
primary and metastatic
colorectal cancer samples
 Created a subpanel of assays
specific to colorectal cancer
mutations
 Achieved 5-10% sensitivity of
mutant detection within normal
background in FFPE tissue
 Data example shown:
– 4.8% PIK3CA mutation
A rapid, sensitive, reproducible and cost-effective method for mutation profiling of colon cancer and metastatic lymph nodes
Fumagalli et al., 2010, BMC Cancer; 10(101)

37
Lung adenocarcinoma testing paradigm
Image based on Horn L and Pao W:
EML4-ALK: Honing in on a new
target in non-small-cell lung cancer.
J Clin Oncol 27:4232-4235, 2009
Test for KRAS
Mutations
Cytotoxic
Chemotherapy
(15-30%)
Test for EGFR
Mutations
Test for
EML4-ALK
translocation
Test for other
Mutations ?*
EGFR Tyrosine
Kinase
Inhibitor (10%)
ALK Kinase
Inhibitor
(5-10%)-
+
-
+
-
+
Test for acquired
resistance (eg.
EGFR_T790M)
(*) “Other” includes
BRAF, MEK1, AKT1,
PIK3CA, DDR2……and/or
intensive research to
identify new driver
mutations

Patient 6 – Complete Metabolic Response
1.9
0.6
0
0.2
0.10
0
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
7/30/14 8/29/14 9/28/14 10/28/14
KRAS G12D - Frequency (%) NRAS G12AV - Frequency (%)

Copyright©2015
39
1Husain et al., ELCC 2015
0
10
20
30
40
50
60
70
80
0
50
100
150
200
250
10/20/2014
10/27/2014
11/3/2014
11/10/2014
11/17/2014
11/24/2014
12/1/2014
12/8/2014
12/15/2014
12/22/2014
12/29/2014
1/5/2015
1/12/2015
1/19/2015
UrineEGFRCopies/100KGE
T790M
Ex19 del
Size on CT scan
SumofLongestDiameters(mm)
Week 1 on drug 6 wks CT scan 12 wks CT scan
Oncogene mutations in urine following therapy against
EGFR T790M resistant lung cancer
(Slide from Trovagene)

UltraSEEK™ Oncogene Panel
 55 samples contained the expected
mutation
– 46 samples (3/3 replicates
positive)
positive)
positive)
 68 samples were negative
negative)
– 1 failed sample (degraded
plasma DNA)
40
Feasibility study with cell free DNA

UltraSEEK™ Oncogene Panel
41
Feasibility study with cell free DNA

42
• If you have less than a few hundred molecules of
analyte:
• Impossible to quantify abundance precisely
• May miss a rare sequence altogether
• Sample handling must compulsively try to not lose
any of the analyte
• Critical to have a way to qualify samples: e.g. leave
in a little detection of wild type allele
Stochastic noise is a major complication
in the measurement of rare biomarkers
FALSE NEGATIVES

43
• Repeat individual measurements – but
impossible if each measurement consumes
all of a 10 ml blood sample
• Combine results from different but biologically
equivalent markers
Can we overcome stochastic noise?

Sensitivity Enhancement by Fragmentation (SEF)
Application of SEF to a typical nucleic acid assay
Preparation of target nucleic acid molecules for analysis (such as extraction
of DNA or RNA, removal of other materials, and conversion of RNA to DNA)
Amplification of target nucleic acid molecules or their segments
Detection of many different amplified nucleic acid molecules or their
segments ( many amplicons)
Fragmentation of target nucleic acid molecules

Application of SEF to Digital PCR
Target nucleic acid molecule
Digital PCR
Fragmentation
Digital PCR
Target-derived fragments

46
Detection rate per assay using 24 replicates

Pre-symptomatic plasma DNA testing
 There are not enough molecules of any
single DNA sequence to see in 10 ml of
blood
 Must aggregate results from large numbers
of different DNA sequences
 Or find a way to perturb the patient to
increase the number of molecules of a single
DNA sequence or switch to RNA or proteins

Hierarchical clustering based on methylation profiles identifies tissue specific
sample groups. 66 cell lines (vertical) versus meCpG sites (horizontal)
Methylation of 12,000 sites in genes
relevant to cancer
48

Multiplex DNA methylation markers in
plasma
 Single tube qPCR assay – robustly detect 0.02% ctDNA in total
cell-free DNA
– Multiple cancer specific methylation markers
– Internal control
Methylation Level
(One Way ANOVA)
I II III IV
-10
-5
0
5
10
15 *** (p = 0.0003)
CRC Stage
Mean_ΔCq
Methylation Level
(One Way ANOVA)
Healthy
BenignPolyp
dvancedAdenoma
CRC
-10
-5
0
5
10
15
*** (p < 0.0001)
Mean_ΔCq
NormalBenign polypAdv. Ad CRC
ΔCt = Ct(Internal control) – Ct(multiplex
markers)
Higher ΔCt means stronger cancer-specific
signal

Improved sample preparation may be
the answer
 Can you recover more DNA molecules
from plasma
 Are some cancer DNA sequences over-
represented in plasma for whatever
reason
 Is it time to revisit using plasma RNA or
proteins instead of plasma DNA
50

Total circulating free DNA (cfDNA, average size ~176bp) in human peripheral
blood plasma was enriched with the Apostle MiniMax technology (red),
compared with a major current technology (blue). The enriched samples were
characterized by Bioanalyzer 2100 and HS Kit (Agilent).
Apostle MiniMaxTM technology – performance of total cfDNA
isolation

52
..Thanks for your attention…

CDAC 2018 Cantor liquid biopsies

Empfohlen

Empfohlen

Weitere ähnliche Inhalte

Was ist angesagt?

Was ist angesagt? (19)

Ähnlich wie CDAC 2018 Cantor liquid biopsies

Ähnlich wie CDAC 2018 Cantor liquid biopsies (20)

Mehr von Marco Antoniotti

Mehr von Marco Antoniotti (14)

Kürzlich hochgeladen

Kürzlich hochgeladen (20)

CDAC 2018 Cantor liquid biopsies

Hinweis der Redaktion