Download Cancer Biomarkers

Cancer Biomarkers
: Opportunities and Challenges
TCOS, Shanghai, May 20 2010
Ann-Lii Cheng M.D., Ph.D.
Department of Oncology and Department of Internal Medicine,
National Taiwan University Hospital;
Taipei, Taiwan.
Cancer Biomarkers
- the opportunities
• A new era in which physicians no longer
make treatment choices that are based on
population-based statistics but rather on
the specific characteristics of individual
patients and their tumors.
Dalton W Science 2006
First-line study of gefitinib vs carboplatin / paclitaxel in
patients with advanced non-small cell lung cancer (IPASS)
EGFR wild-type
EGFR mutation-positive
Gefitinib (n=132)
Carboplatin/paclitaxel (n=129)
Gefitinib (n=91)
Carboplatin/paclitaxel (n=85)
1.0
HR (95% CI) = 0.48 (0.36, 0.64)
p<0.0001
0.8
0.6
0.4
0.2
0
Probability of PFS
Probability of PFS
1.0
HR (95% CI) = 2.85 (2.05, 3.98)
p<0.0001
0.8
0.6
0.4
0.2
0
0
At risk:
Gefitinib 132
129
C/P
4
8
108
103
71
37
12
16
Months
31
7
11
2
20
24
0
4
8
3
1
0
0
91
85
21
58
4
14
12
16
Months
2
1
1
0
20
24
0
0
0
0
Mok et. al. ESMO 2008
First-line treatment of mCRC with FOLFOX  cetuximab
(OPUS Study)
Kaplan-Meier estimate
K-Ras mutant
K-Ras wild-type
1.0
Cetuximab + FOLFOX 1.0
FOLFOX
0.8
0.8
0.6
0.6
0.4
0.4
0.2
HR=1.83; p=0.0192
FOLFOX: 8.6 m
Cetuximab + FOLFOX: 5.5 m
0
0.2
Cetuximab + FOLFOX
FOLFOX
HR=0.57; p=0.016
FOLFOX: 7.2 m
Cetuximab + FOLFOX: 7.7 m
0
0
2
4
6
8
10
12
Progression-free time (months)
0
2
4
6
8
10
12
Progression-free time (months)
Bokemeyer C, et al. JCO 2009
Cancer Biomarkers
- the challenges
• Clinically a must in an increasing number
Non-Small cell lung cancer
of cancer types.
Colorectal cancer
Breast cancer
• Cost, workload, and workflow.
Gastric cancer
cell carcinoma
• Technic issues – reliabilityRenal
of
methods
GI stromal tumor
Leukemia
• Ethnic and geographic issuesLymphoma
– how far
can data be extrapolated fromMelanoma
area to
Basal cell carcinoma
area ?
Medulloblastoma
…………
Reliability of Biomarkers on Surgically
Resected Tumor Specimens
1. Ischemia during operation – unknown
in most specimens
2. Unknown processing of specimens
Warm ischemia
Specimen aging
Comparison of
Biopsy vs. Hepatectomy HCC Tissues
Study design:
• 46 paired HCC tissues (‘03~’08)
– Biopsy taken within 3 months before
hepatectomy
– Hepatectomy
• IHC studies:
– p-Akt (S473): rabbit antibody (Santa Cruz)
– p-ERK1/2 (T202/Y204): rabbit antibody
(Santa Cruz)
~ Shao YY et al: AACR 2010, Abstract 3759.
Comparison of
Biopsy vs. Hepatectomy HCC Tissues
• Poor correlation
• Higher expression in biopsy tissues
phospho-ERK
phospho-Akt
~ Shao YY et al: AACR 2010, Abstract 3759.
p-ERK
Biopsy tissue
Hepatectomy tissue
Tissue Ischemia Affects Gene Expression
within Minutes Following CRC Excision
─ Microarray analysis
Spruessel A, et al. BioTechniques 2004;36:1030-1037
Tissue Ischemia Affects Protein Expression
within Minutes Following CRC Excision
─ SELDI-TOF MS analysis
Spruessel A, et al. BioTechniques 2004;36:1030-1037
Slide Aging Affects Immunohistochemistry
HER2
ER
E-Cadherin
Mirlacher M, et al. Mod Pathol, 2004;17:1414-1420
Slide Aging Affects
Immunohistochemistry
Figure 2. Influence of slide aging on the fraction of positive
cases. For each antibody, the frequency of positive cases is
shown as separate bars for old (O) and fresh (F) sections.
Mirlacher M, et al. Mod Pathol, 2004;17:1414-1420
Slide Aging Affect p53 Immunostaining of
Breast Cancer Tissues
Jacob TW et al J, Natl Cancer Inst 1996;88:1054-09
The Problems of Genomic Biomarkers
- minimal reproducibility
• Numerous gene signatures have been
reported.
• Only marginal overlap of reports
– poor study design
lack of a standard technology platform
different ways of tumor collection
different statistical methods
• Only few validated into clinic practice.
Dalton W. science 2006;312:1165-8
Toward Robust Genomic Biomarkers
•
•
•
•
•
Share samples
Common technology platform
Ask similar questions
Use similar criteria for patient enrollment
Partnership among academic groups,
pharmaceutical and biotechnology
companies, as well as government
agencies.
Dalton W. Science 2006;312:1165-8
Challenges of Cancer Biomarkers
- ethnic and geographic issues -
East vs West
Lung cancer
Breast cancer
Hepatocelluar carcinoma
Importance of Ethnicity for MTT
─ the lessons of ISEL trial
Proportion surviving
Asian (n=342)
Non-Asian (n=1350)
1.0
Gefitinib
Placebo
0.8
0.6
0.4
0.2
0.0
0
2
4
6
8
10 12 14 16
0
2
Time (months)
4
6
8 10 12 14 16
EGFR mutation rates in each subgroup
AdenoCa
(+BAC)
(%)
M (%) F (%)
Study
Centre
No. of
patients
Taiwan1
NTUH
62
49
25
61
29
56
Taiwan2
VGH-T
37
67.4
52
72
44
69
Korea3
Seoul NU
90
21
9
33
13
26
Japan4
NCC Tokyo
66
61
53
69
35
68
Japan5
Aichi CCH
59
64
44
70
42
71
HK6
Chinese U
72
32
—
—
—
—
China7
Pek UMCH
76
48.6
32.3
34.8
—
—
Italy8*
U Chieti
375
10
6
30
7
25
1.
2.
3.
4.
Shih et al, IJC 2005
Chou et al, CCR 2005
Han et al, JCO 2005
Takano et al, JCO 2005
*only AdenoCa
5.
6.
7.
8.
Mitsudomi et al, JCO 2005
Lung et al, PAACR 2005
Mu et al, CCR 2005
Machetti et al, JCO 2005
Smoker
s (%)
n-smokers
(%)
EGFR Mutations in NSCLC Patients
Born or Domiciled in the USA
• Other ethnicities 14/159 (9%)
• East Asians
12/22 (55%)
Adi Gazdar, 2005
Ethnic Difference in Mutational Pattern of
Lung Adenocarcinoma
East Asians
EGFR mutation
KRAS mutation
Other Countries
EGFR mutation
KRAS mutation
EML4-ALK
BRAF mutation
HER2 mutataion
PIK3CA
MET amplification
MEK1 mutation
Unknown
EGFR mutation
KRAS mutation
Trends in Breast Cancer Incidence
•
Incidence of breast cancer has been increasing around the
world including Latina America, Middle East and Asia
– Incidence now stabilizing in some Western populations
– Incidence continues to increase in many Asian
populations
Country
Japan (Miyagima)
Japan (Osaka)
Singapore (Chinese)
China (Shanghai)
Incidence
1973–77
17.5
12.7
21.9
19.6
Incidence
1993–97
34.4
28.7
45.9
27.2
%
Increase
97
126
110
39
Cancer Incidence in Five Continents (Vol. IV, VIII)
Katanoda et al, Jpn J Clin Oncol. 2007 Aug;37(8):638-9
Age-specific Breast Cancer Incidence
in Taiwan
600.0
500.0
American
Caucasion
400.0
台灣1994
300.0
台灣1998
台灣2002
200.0
台灣2005
100.0
0.0
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85+
年齡
Comparison of Molecular Subtypes between
American and Taiwanese
Population
(study period, y)
Patient
no.
USA (1993-1996)
496
African American
196
Luminal A Luminal B HER2+/ER- Basal-like Unclassified
(%)
(%)
(%)
(%)
(%)
Premenopausal
97
36
9
9
39
6
Postmenopausal
99
59
16
7
14
4
Non-African American
300
Premenopausal
164
51
18
6
16
10
Postmenopausal
136
58
16
6
16
4
Taiwan (2004-2006)
1028
≦50 y
515
66
11
10
9
4
>50 y
513
56
8
14
17
6
High frequency of ER expression in Taiwanese
YFBC: validated by Taiwan Cancer Database
TCDB (n=3899)
<35
35-49
≧50
P value
ER+
194 (63)
1837 (66)
1868 (57)
<0.001
ER-
114 (37)
927 (34)
1399 (43)
PR+
160 (52)
1744 (63)
1596 (49)
PR-
148(48)
1020 (37)
1671 (51)
<0.001
Taiwan Cancer DataBase 2005
Time Trend of Increase Frequency of ER
expressions in Young Breast Cancer at NTUH
100
1st cohort
2nd cohort
90
(1992-2000)
(2004-2006)
80
70
74
75
60
50
54
62
58
61
40
30
20
10
0
<36
36-50
>50
Preliminary data
ER expression : a poor prognostic factor for DFS
among very young patients receiving adjuvant
chemotherapy alone in Western Countries
IBCSG data Lancet 2000
ER expression : a favorable prognostic
factor for OS among very young (<35y)
patients in Taiwan
178 very young (<35 years) breast cancer patients diagnosed
at NTUH in 1997-2006
Proceeding ASCO 2009
Hepatocellular Carcinoma
— Distinct Geographic Distribution
Europe and United
States (%)
Risk Factors
Estimate Range
Japan (%)
Estimate Range
Asia and Africa (%)
Estimate Range
Hepatitis B virus
22
4~-58
20
18~-44
60
40~90
Hepatitis C virus
60
12~72
63
48~94
20
9~56
Alcohol
45
8~57
20
15~33
---
11~41
Tobacco
12
0~14
40
9~51
22
---
Oral contraceptives
---
10~50
---
---
8
---
Aflatoxin
Other and emerging
risk factors/cofactors
Limited exposure
<5
---
Limited exposure
---
---
Important exposure
<5
---
Bosch FX et al. Gastroenterology 2004;127:S5-16.
Viral Proteins And Signal Transduction Pathways
Toxins,
other
stress
Growth
factor
receptor
Cytokine
receptor
HBx
AKT
Pre-S
mutant
IkB
IKK
RAS
GRB2
Src
PTEN
HCV
core
SHC
SOS1
Raf
PKC
MEK
IkB
NFKB
NFKB
Cell survival
Angiogenesis
Metastasis
Cell cycle
Cell survival
Metabolism
DNA damage
HBx
GSK3
Forkhead
HBx
Protein
degradation
PI3K
SHP2
SHP2
ER stress
Proteasome
HBx
Wnt
Axin
mTOR
BAD
ERK
APC
β-catenin
Cell cycle
Protein
translation
Nutrient
response
Cell survival
Metabolism
Cell cycle
Cell survival
Cell cycle
Angiogenesis
Metastasis
: Dys-regulated in HCC
: Targeted agents in clinical development
: Targeted agents in pre-clinical development
By Hsu C, Shen YC, Cheng AL
HCV
core
Transcriptome classification of HCC
G1-group (N=11)
G2-group (N=17)
Others (N= 92)
Over-expression
IGF1R
Akt
p-GSK3β
64%
75%
78%
25%
42%
9%
8%
9%
HBV(+)
8
7
22
HCV(+)
3
4
23
~ Boyault S et al: Hepatol 2007;45:42. based on120 surgically resected HCC, including transcriptome analysis on 57
HCCs and 3 adenomas, and qRT-PCR validation in additional 63 HCCs
31
HBV-related HCC
Is HBV-related HCC a more
aggressive tumor ?
Is HBV-related HCC associated with
molecular changes which affect
molecular therapy ?
HCC ─ East vs West
Long-term results after surgical
treatment were similar in West and
East when clinicopatnologic factors
were accounted for.
Pawlik TM et al Liver Transplantation 2004;10(suppl 1) 74-80
Taeck D et al Liver Transplantation 2004;10(suppl 1) 58-63
HBV vs. HCV HCC
Italian Liver Cancer group
• Patients with HBV-HCC tended to have poor
prognosis; and the difference became statistically
significant among patients with advanced HCC
Survival in patients with advanced HCC. HBVHCC patients had a lower survival than HCVHCC patients (p=0.025)
~ Cantarini MC et al: Am J Gastroenterol 2006;101:91-8.
HBV vs. HCV HCC in NTUH
Survival for patients with advanced ds.
• 927 patients receiving supportive care or
chemotherapy.
Etiology
HBV HCV B+C NBNC
Median
2.5 3.4 3.4
survival (M)
1 year (%) 12.4 21.7 10.8
3 year (%) 3.4 8.5 3.1
5 year (%) 0.8 2.2 1.5
10 year (%) 0.5 1.1
0
2.6
11.2
3.1
1.0
1.0
HCV+
HBV+
HCV-HCC patients had better survival than HBV-HCC patients
Chen CH et al. Eur J Cancer. 2006 Oct;42(15):2524-9. Epub 2006 Aug 22
Sorafenib phase II HCC study
HCV- vs. HBV-related HCC
HCV+
HBV+
P’t No.
33
13
Median age
Race (%)
71
66
Caucasians
Clinical benefit (%)
82
75
54
53
6.5
6.5
12.4
3.5
4
7.3
PFS (median, M)
TTP (median, M)
OS (median, M)
P
.27
.05
.29
~ Huitzil-Melendez FD et al: ASCO-2007 GI Symposium Abstract# 173.
A retrospective analysis
Thalidomide phase II HCC study
HCV- vs. HBV-related HCC
P’t No.
Median age
Objective response+
AFP response (%)
TTP (median)
OS (median)
HCV+
HBV+
P
33
67.5
61
53.6
61
< .001
13.1
27.3
14.1 W 8.3 W
32.6 W 21.4 W
.09
.03
.08
~ Hsu C et al: Proc. ASCO 2004: Abs#4198.
Conclusions
─ Cancer biomarkers
• Provide excellent opportunity for
personalized care.
• Cost, workload, and workflow remain
a problem.
• Technic issues should not be
overlooked.
• Significant ethnic and geographic
difference exist.
Cancer Biomarkers
: Opportunities and Challenges
TCOS, Shanghai, May 20 2010