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Liquid Biopsies in Cancer Diagnostics
Allen Chan MBBS, PhD, MRCP, FRCPA, HKCPath
Professor of Chemical PathologyThe Chinese University of Hong Kong
Disclosure of potential conflict of interest
• Hold patents/patent applications for the molecular diagnostic technologies
• Patent profiles licensed to Illumina, Sequenom, Xcelom• Equity interests in Xcelom, Cirina, Sequenom• Director of Xcelom, Cirina, Sanomics• Consultant for Xcelom
CONFIDENTIAL 3
?=
How solid is liquid biopsy?
Clinical service China US Germany UK The Netherlands Austria Switzerland Czech Republic Slovakia Israel Japan Singapore Malaysia Australia, etc
2 million tests performedin 60 countries
Lo et al. Sci Transl Med 2010
Cancer genome sequencing from plasma?
Detecting the cancer finger-printin plasma DNA
• Human genome: 3000 Mb• 1 Mb resolution• ~3,000 segments per genome• Sequence ~100 million plasma DNA fragments
Liver Cancer
M/77HCC 6.2 cm
Tumour
Pre-Txplasma
Post-Txplasma
Tumour
M/53HCC 14 cm
Tumour
Pre-TxPlasma
Post-TxPlasma
Tumour
M/53HCC 7.4 cm
Tumour
Pre-TxPlasma
Post-TxPlasma
Tumour
Chronic hepatitis B (HBV) carriers without HCC
HBV carrier 1Plasma
HBV carrier 4Plasma
HBV carrier 3Plasma
HBV carrier 2Plasma
HBV carrier 1Plasma
Tumoral heterogeneity
3 cm infiltrating ductal carcinomain the left breast
12 cm right ovarian tumour(Regions A & B) 6 cm left
ovarian tumour(Regions C & D)
Breast cancer
Ovariancancer
TumourTissues
Breast cancer
Ovarian cancer(Region A)
Pre-op plasma
Post-op plasma
Plasma DNA
Ovarian cancer: 46%
Breast cancer: 2.1%
Ovariancancer
Tumor Tissues
Group
Single NucleotideMutations
in Tumor
A 71
B 122
C 168
D 248
AB 10
CD 12
ABCD 2,216
Ready for clinical use?
Cancer methylomics
• Global hypomethylation• Pervasive changes• Potentially more sensitive detection with low
coverage sequencing
24
Tumour
Blood cells
Plasma(c.f. healthy controls)
Methylomic analysis
HCC patient
Chan et al. PNAS 2013
Chan et al. PNAS 2013
Methylation analysis CNA analysis
Higher resolution, high price
Worth the money?
Plasma
Tumour
Jiang et al. PNAS 2015
84%22%4.5%0%
Jiang et al. PNAS 2015
Other cancer types?
Breast cancer
Lung cancer
Smooth muscle sarcoma
Neuroendocrine tumor
Nasopharyngeal carcinoma
Pathogenesis Symptoms Treatment Clinical remission Progression
Clinical applications
Early detection
Treatment selection
Identity residual disease
Monitoring
Pathogenesis Symptoms Treatment Clinical remission Progression
Clinical applications
Early detection
Treatment selection
Identity residual disease
Monitoring
Sensitivity 96%Specificity 93%
Pla
sma
EBV
DN
A c
on
cen
trat
ion
(co
pie
s/m
L)
NPCpatients
Healthycontrols
0
10
100
1000
10000
1000000
100000
Plasma Epstein-Barr virus (EBV) DNA as a marker for nasopharyngeal cancer (NPC)
NPC screening study
• Screen 20,000 asymptomatic subjects • Males aged 40-60• Plasma EBV DNA analysis
→ Nasal endoscopic examination
Progress
• Subject recruitment started in July 2013• 10,300 subjects recruited till January 2015• 17 subjects identified of having undifferentiated
NPC
Stage IVStage IIIStage IIStage I
3 (18%) 1
(6%)
13 (76%)
8%
16%
46%
30%
Unscreened populationHong Kong cancer registry2010
Identifying the source of cancer-associated abnormalities
PlasmaMethylomic
analysis
Tissue-specific methylation
profiles
Blood cells
Plasma DNA tissue mapping
Tissue contribution %
Prenatal testing
Cancer detection & monitoring
Organ transplant monitoring
Adipose tissues
Blood cells
LiverSmall intestines
Adipose tissues
LungColon
Liver
Lungs
Small intestines Colon
etc.
Sun et al. PNAS 2015
p-value < 0.001
Controls HCC patients
Live
r co
ntrib
utio
n by
tiss
ue m
appi
ng (
%)
0
10
20
30
40
50
60
Effect of cancer on tissue contribution to plasma DNA
Sun et al. PNAS 2015
Chr with copy number gain
in tumor
Tumor-derivedDNA
DNA derived from
other organsTissue origin of the tumor
Other tissues
Tissue origin of the tumor
Other tissues
Chr with copy number loss
in tumor
Plasma with CNA detected
Tissue origin for the tumor Other tissues
ΔM (%)
Difference in tissue contributionsbetween two sets of chromosomes
Sun et al. PNAS 2015
-15
-5
5
15
-15
-5
5
15
-15
-5
5
15
-15
-5
5
15
T21-1
T21-2
T21-3
T21-4
Liv
er
Lu
ng
Sm
all i
nte
stin
es
Pan
crea
s
Co
lon
Ad
ren
al g
lan
ds
Eso
ph
agu
s
Ad
ipo
se t
issu
es
Hea
rt
Neu
tro
ph
ils
Lym
ph
ocy
tes
Bra
in
Pla
cen
ta
∆M (%)
Pregnant women carrying Down syndrome fetus
-30
-10
10
30
-30
-10
10
30
-30
-10
10
30
-30
-10
10
30
-30
-10
10
30
-30
-10
10
30
-30
-10
10
30
-30
-10
10
30
HCC-2
HCC-1
HCC-28
HCC-29
HCC-4
HCC-26
Lung cancer-1
Colorectal cancer-1
-30
-10
10
30
HCC-13
Ad
ipo
se t
issu
es
Liv
er
Lu
ng
Sm
all i
nte
stin
es
Pan
crea
s
Ad
ren
al g
lan
ds
Eso
ph
agu
s
Hea
rt
Neu
tro
ph
ils
Lym
ph
ocy
tes
Bra
in
Co
lon
∆M (%)
A pregnant woman requesting NIPT for chromosomal aneuploidies
Sun et al. PNAS 2015
∆M analysis result
-10
-5
0
5
10
Liv
er
Lu
ng
Sm
all i
nte
stin
es
Pan
crea
s
Co
lon
Ad
ren
al g
lan
ds
Eso
ph
agu
s
Ad
ipo
se t
issu
es
Hea
rt
Neu
tro
ph
ils
B c
ells
Bra
in
Pla
cen
ta
Tce
lls
∆M
(%
)
Sun et al. PNAS 2015
B-cell lymphoma
tissues
Pre-Txplasma
Post-Txplasma
Sun et al. PNAS 2015
Pathogenesis Symptoms Treatment Clinical remission Progression
Clinical applications
Early detection
Treatment selection
Identity residual disease
Monitoring
Efficacy of EGFR TKI in patients with EGFR mutations
Author Study N (EGFR mut +)
RR Median PFS
Mok et al IPASS 132 71.2% vs 47.3 9.8 vs 6.4 months
Lee et al First-SIGNAL 27 84.6% vs 37.5% 8.4 vs 6.7 months
Mitsudomi et al WJTOG 3405 86 62.1% vs 32.2% 9.2 vs 6.3 months
Maemondo et al NEJGSG002 114 73.7% vs 30.7% 10.8 vs 5.4 months
Zhou et al OPTIMAL 154 83% vs 36%
13.1 vs 4.6 months
Rosell et al EURTAC 135 56% vs 18% 9.2 vs 4.8 months
Wu et al LUX Lung 6 364 67% vs 23% 11.0 vs 5.6 months
Mok et al NEJM 2009, Lee et al WCLC 2009, Mitsudomi et al Lancet Oncology 2010, Maemondo NEJM 2010Zhou et al Lancet Oncol 2010
We need to find EGFR mutation at time of diagnosis
of adenocarcinoma
Courtesy slide from Tony Mok
EGFR mutation testing in Asia
Country (N
diagnosed with
NSCLC*)
Proportion tested for
EGFR mutations
% (95% CI†)
Proportion of males/females, smokers and non-smokers, and
histological subtypes that were tested for EGFR mutations‡
Gender Smoking status Histology
Males / Females (%)Current + ex-smoker /
Never smoker (%)
ADC /
All non-ADC / Only
SCC (%)
Total (22,193) 31.8 (31.2–32.5) 26.9 / 40.2 47.0 / 57.4 50.4 / 12.5 / 12.5
China (12,086§) 18.3 (17.6–19.0) 15.2 / 25.3 N.D. 30.3 / 8.0 / 9.4
Hong Kong (795) 42.0 (38.6–45.5) 36.2 / 52.3 34.1 / 52.1 55.4 / 9.0 / 6.4
Japan (2,379) 64.8 (62.9–66.7) 63.6 / 67.0 68.8 / 68.3 69.2 / 55.0 / 50.3
Korea (3,794) 33.5 (32.0–35.0) 26.1 / 38.1 27.1 / 42.9 62.7 / 9.8 / 8.3
Taiwan (2,890) 54.3 (52.5–56.1) 47.1 / 64.3 37.0 / 56.8 69.3 / 15.5 / 8.5
Thailand (249§) 57.8 (51.6–63.8) 51.6 / 69.3 49.5 / 84.7 83.6 / 7.1 / 6.9
PFS of p-EGFR and t-EGFR mut+ patients
Wu and Mok Lancet Oncology 2013
PFS of p-EGFR and t-EGFR mut- patients
Wu and Mok Lancet Oncology 2013
Pathogenesis Symptoms Treatment Clinical remission Progression
Clinical applications
Early detection
Treatment selection
Identity residual disease
Monitoring
Detecting residual disease
Chan et al. JNCI 2002
Pro
gres
sio
n-f
ree
Su
rviv
al
Weeks after treatment
UndetectablePlasma EBV DNA
undetectable
Plasma EBV DNApositive
NPC patients received ChemoRT
Plasma EBV DNA at 6 weeks after Tx
Plasma EBV DNA negative
Plasma EBV DNA positive
Multi-center international randomised control trial
CTRL ARM3 cycles of Cisplatin &
5-FU
EXP ARM
Observation
Randomize
CTRL ARM3 cycles of Cisplatin &
5-FU
EXP ARM4 cycles of
GemcitabinePaclitaxel
Randomize
Conclusions
Liquid biopsy• Generic tumour marker for all cancers• Screening for early cancers• Choosing the right treatment• Identifying residual disease
