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Cancer Chemoprevention &
Surrogate End Point Markers
JianYu Rao, M.D.
Associate Prof. Of Pathology
UCLA
CANCER PREVENTION
• PRIMARY
• STOP THE EXPOSURE
• SECONDARY
• INTERVENTION OR CHEMOPREVENTION
• TERTIARY
• TREATMENT
CHEMOPREVENTION
• Administrating specific amounts of a
particular natural or synthetic chemical
in an attempt to identify agents that will
prevent, halt or reverse the process of
carcinogenesis
• The basic assumption is that treating
early stages of malignant process will
halt the progression of malignancy
• The key is to define early lesions, and
treat the malignant field
Exposure to Carcinogen
Birth
Precancerous
Intraepithelial
Lesions,
(PIN, CIN, PaIN..)
Additional
Molecular Event
CHEMOPREVENTION
Cancer
Multiyear progression from initiation and early
precancerous lesions to invasive disease in major
cancer target organs
Kelloff et al. 2000 (Fig. 1)
THEORIES SUPPORT FOR
CHEMOPREVENTION
• EPIDEMIOLOGICAL EVIDENCE:
• OVER 50% CANCERS HAVE NO KNOWN RISK
FACTORS
• NUMEROUS EVIDENCE TO DEMONSTRATE THE
INVERSE RELATIONSHIPS OF SOME NUTRIENT
FACTORS WITH CANCER RISKS
THEORIES SUPPORT FOR
CHEMOPREVENTION (Cont.)
• EXPERIMENTAL EVIDENCE:
• ALTHOUGH CARCINOGENESIS IS REGARDED AS
NONREVERSIBLE PROCESS, STUDIES SHOWED
THIS IS ONLY TRUE AT LATE STAGE. IN FACT, A
LARGE PORTION OF THE LONG LATENCY PERIOD
OF CARCINOGENIC PROCESS IS REVERSIBLE.
• IN VITRO CULTURE AND IN VIVO ANIMAL STUDIES
IDENTIFIED NUMEROUS AGENTS THAT CAN
REVERSE, OR HALT THE CARCINOGENESIS
PROCESS, PARTICULARLY AT THE EARLY STAGE.
THEORIES SUPPORT FOR
CHEMOPREVENTION (Cont.)
• CLINICALLY
• ADVANCES IN CERTAIN TYPES OF CANCER
TREATMENT HAVE LIMITED SUCCESS IN
REDUCING THE OVERALL INCIDENCE, OR EVEN
MORTALITY OF CANCER.
Chemoprevention:
Some Terminologies
• INDIVIDUAL RISK AND
STRATIFICATION
• INTERMEDIATE END POINT MARKER
(SURROGATE END POINT MARKER)
• FIELD CANCERIZATION
• MULTI-PATH OF CARCINOGENESIS
RISK STRATIFICATION
• Identification of AT-RISK subjects who are also SUSCEPTIBLE
to treatment:
LEGEND:
Not at risk to develop disease
At risk of developing disease, biology A, responsive to agent X
At risk of developing disease, biology B, NOT responsive to agent X
INTERMEDIATE END POINT
MARKER (SURROGATE END
POINT MARKER)
• These are prevention biomarkers
which are specifically related to early
stages of carcinogenesis.
• These markers are used to identify
individual’s risk for developing cancer
and to monitor the effectiveness of
intervention methods.
FIELD CANCERIZATION
• The whole field of tissue of a particular
organ is exposed to the carcinogenic
insult and is at increased risk for
developing cancer.
• Although only a few foci eventually
develop malignancy, the other areas
are not necessary entirely “normal”.
• Most common epithelia cancers are
developed through this mechanism.
Examples of such cancers are: Head
and neck ca, bladder ca, breast ca,
lung ca, GI ca, etc.
MULTI-PATH OF
CARCINOGENESIS
• The current model of carcinogenesis is
that cancer develops through multiple
events which are not necessary
through linear steps, but rather
through overlapping networks.
TARGET POPULATION
INDIVIDUALS AT RISK =
LATENCY (20 YEARS) x #
EXPECTED TO DIE IN ONE YEAR
(1.1 MILLION)
= 22 MILLION
CHEMOPREVENTION IN DIFFERENT
RISK CATEGORIES
Risk category
Parameter
General Population
High Risk
Agent toxicity
Trivial to none
Slight
Selection method
Public Health
Clinical
Other consideration
Use dietary supplements
may be applicable
Need biomarkers
From lee W. Wattenberg, P.S.E.B.M., 1997 216:133-141.
Phase I Trial
Objectives:
• To determine the intervention’s short-term (<1
yr.) dose-toxicity relationship
• To determine the intervention’s human
pharmacokinetics
Design:
•
•
•
•
Single arm, nonrandomized
Multiple dose levels
Less than 1 yr. duration
Accrual 25-100
Phase II Trial
Objectives:
• To determine the intervention’s side effects
• To determine optimal recruitment methods of the target
population
• To determine retention of study participants to the study
intervention and procedures
• To determine optimal methods for the conducting of a phase
III trial
• To determine the effect of the intervention on biomarkers of
carcinogenesis (phase II b)
Design:
•
•
•
•
Randomized, double-blind, placebo-controlled
Multiple dose levels or agents
One to five years in duration
Accrual 100s-1000s
Phase III Trial
Objectives:
• To determine the effect of the intervention on the cancer
incidence (total and specific cancer type)
• To determine the effect of the intervention on death rate and
disease incidence
• To determine the long-term side effects of the intervention
• To determine the nature history of specific biomarkers of
carcinogenesis (placebo group) and the effect of the
intervention agent (treatment group) on these markers.
Design:
•
•
•
•
Randomized, double-blind, placebo-controlled
Multiple dose levels or agents, alone or in combination
Five to ten years in duration
Accrual 1000s-10,000s
UNIQUE FEATURES OF
CHEMOPREVENTION
• Participants are usually healthy or at
least “cancer free”
• The degree and incidence of side
effects that are acceptable are low
• The end point is disease prevention,
not disease response
• The incidence of the study end point is
low
CATEGORIES OF
CHEMOPREVENTIVE AGENTS
• BLOCKING CARCINOGEN
METABOLISM AND EXPOSURE
• INCREASE TISSUE
RESISTANCE/DIFFERENTIAITON
• TARGETING ONCOGENIC PATHWAYS
CATEGORIES OF
CHEMOPREVENTIVE AGENTS
• BLOCKING AGENTS
• Prevent metabolic activation of
carcinogens or tumor promoters
• Enhance detoxification
Glutathione-S-transferase,Oltipraz
• Trap reactive carcinogenic species:
Glutathione, N-Acetylcysteine
• Vaccines: HBV, HPV
CATEGORIES OF CHEMOPREVENTIVE
AGENTS (Cont.)
• INCREASING TISSUE RESISTANCE
• Induce tissue
maturation/differentiaiton
Pregnancy or hormonal induced maturation of
terminal ducts of breast - decrease breast cancer
Retinoids, DMFO, etc
• Decrease target tissue function
Castration - reduce risk of prostate ca
• Decrease cell proliferation
Low fat diet decrease epithelial proliferation rate in
intestinal tract - reduce colon cancer risk
CATEGORIES OF CHEMOPREVENTIVE
AGENTS (Cont.)
• PATHWAY SPECIFIC AGENTS
• Cox-2 inhibitors
• Anti-angiogenesis
• Anti-EGFR
• Hormone antagonists
• Augmenting tumor suppressor functions
• Inhibiting oncogenic activities (e.g., Ras)
CHEMOPREVENTION TO HUMANS UPDATE
• BREAST CANCER
• Two agents showed promising results:
Tamoxifen and retinoids
• Animal model well established
• PROSTATE CANCER
• SCID model established
• Hormonal modulation may have potential
• PCPT Trial – Finasteride (5-a-reductase, 5mg/day)
• 2-arm trial, 18,882 subjects, 7 yrs
• PCP=18.4% vs 24.8% in treated vs ctrl group
• Ongoing Trial: Selenium/Vit E trial
CHEMOPREVENTION TO HUMANS UPDATE (CONT.)
• GASTRIC AND ESOPHAGEAL CANCER
• A combination of beta carotene, vitamin E,
and selenium may be effective in early
stage lesions, but not late severe
dysplastic lesions.
• LUNG CANCER
• Beta-carotene or alpha-tocopherol showed
reverse effect in lung cancer risk in heavy
smokers in Finland
• Ongoing trials with COX-2 inhibitor in
former smokers here at UCLA
CHEMOPREVENTION TO HUMANS UPDATE (CONT.)
• COLON CANCER
• Sulindac, a nonsteroidal anti-inflammatory
compound hold great promise. Others,
such as Oltiparz, selenium, and
antioxidants vit. E/A, etc, may also be
effective.
• HEAD AND NECK CANCER
• Retinoids showed promising results in
both animal models and human studies.
PROBLEMS OF
CHEMOPREVENTION
• TOO LONG
• TOO LARGE COHORT
• TOO MUCH COST
ANSWER:
NEED TO DEVELOP RELIABLE SEMS
BIOMARKERS OF CANCER
• CLINICAL SETTINGS (TUMOR
MARKERS)
• EPIDEMIOLOGICAL AND PREVENTIVE
SETTINGS (INTERMEDIATE END POINT
OR SURROGATE END POINT
MARKERS).
CURRENT CLINICALLY
USED TUMOR MARKERS
• PSA - Prostate Adenocarcinoma
• Alpha FP - Hepatoma & some Ovarian
Ca
• HCG - Choriocarcinoma
• CEA - Ovarian CA
BIOMARKERS
• Genetic susceptibility markers
• Markers of exposure
• Markers of biological effects
-Detect early lesions
-Prognostic indicators
GENETIC SUSCEPTIBILITY
MARKERS
• Glutathione S-transferase (GST) M1
and T1
• N-acetyl transferase (NAT)
• Cytochrome P-450
• DNA repair gene defect (Lynch
syndrome)
MARKERS OF EXPOSURE
• Metabolic product of carcinogen in
urine
• DNA, RNA and hemoglobin adducts
-Reflects only current exposure
-Only a small fraction of DNA adducts will
result in mutation
• DNA repair targets
BIOMARKERS OF EFFECT
• Reflect the interactions of genetics and
exposures and so the first choice for
SEM
• If they persist, may also be the markers
of disease
• Histopathologic evaluation is the “gold
standard”
HOW TUMOR MARKERS
ARE USED CLINICALLY
• Early detection
• Predict the biological potential of
cancer (metastasize and recurrence)
• Monitor the effectiveness of therapy
Exposure to Carcinogen
Birth
Precancerous
Intraepithelial
Lesions,
(PIN, CIN, PaIN..)
Additional
Molecular Event
Cancer
Surrogate End Point Markers
Genetic Suscep.
Marker
Markers for
Exposure
Markers of
Effect
CHEMOPREVENTION
Tumor
Markers
CRITERIA FOR SELECTING
SEM
• FITS EXPECTED BIOLOGICAL
MECHANISM
• BIOMARKER AND ASSAY PROVIDE
ACCEPTABLE SENSITIVITY,
SPECIFICITY, AND ACCURACY
• BIOMARKER IS EASILY MEASURED
• BIOMARKER MODULATION
CORRELATES TO DECREASED
CANCER INCIDENCE
FITS EXPECTED
BIOLOGICAL MECHANISM
• DIFFERENTIALLY EXPRESSED IN
NORMAL AND HIGH RISK TISSUE
• CLOSELY LINKED, EITHER DIRECTLY
OR INDIRECTLY, TO CAUSAL
PATHWAY FOR CANCER
• MODULATED BY CHEMOPREVENTIVE
AGENTS
• LATENCY IS SHORT COMPARED WITH
CANCER
ASSAY VALIDITY
• ASSAY SHOULD BE STANDARDIZED
AND VALIDATED
• DOSE-RELATED RESPONSE TO THE
CHEMOPREVENTIVE AGENT IS
OBSERVED
• STATISTICALLY SIGNIFICANT
DIFFERENCE BETWEEN LEVELS IN
TREATMENT GROUPS AND
CONTROLS
OTHER ASSAY ISSUES
• BIOMARKER CAN BE OBTAINED BY NONINVASIVE TECHNIQUES
• ASSAY IS NOT TECHNICALLY DIFFICULT
• MULTIPLE MARKERS CAN BE EVALUATED
SIMULTANEOUSLY IN LIMITED SAMPLE
VOLUMES
• COST
• FALSE POSITIVE OR FALSE NEGATIVE
RESULTS ARE LESS IMPORTANT, IN
COMPARING WITH CLINICAL TUMOR
MARKERS
CATEGORIES OF SEM
• HISTOLOGICAL AND MORPHOMETRIC
MARKERS
• PROLIFERATION, DIFFERENTIATION
AND INVASION MARKERS
• SPECIFIC ONCOGENES/GROWTH
REGULATORS
• MARKERS OF GENETIC AND
EPIGENETIC INSTABILITY
POTENTIAL SEMS FOR BREAST,
COLON AND PROSTATE
Breast
Histological
DCIS, LCIS, ADH
Proliferation
Differentiation
Genetic
Biochemical
Colon
Prostate
Adenomatous polyps
Aberrant polyps
PIN
S-phase fraction
Ki-67
S-phase fraction
Brdu Uptake, PCNA
PCNA
Ki-67
Myoepithelial (s-100
Vimentin), etc
BGA, Mucin core ag
Cytokeratins
HM Cytok
BGA, actin
Onc (erb-2, myc
fos, ras)
Suppressor (p53)
Estradiol
Onc (ras, myc, src)
Suppressor (p53,
DCC)
Onc (erb-2)
Ornithine Decarboxylase
Polyamine
TGF-beta, PSA
SEM Modulation in
Chemoprevention
• Complete Phenotypic Response -idea
• Less Than Complete Phenotypic
Response -Genotypic markers to
distinguish chemoprevention from
selecting regressing of existing
disease
– true effect is seen if post-treated lesion has
less genotypic change than baseline or
control)
• No Response.
Genome Wide Genotypic
SEM Analysis
• Identify high risk population
• Identify individuals with genetic
susceptibility for treatment
(pharmacogenomics)
• Monitoring/analyzing individual’s
treatment response
Issues in Using SEM
• The observed SEM change may not
correlate with end point (cancer
incidence).
• Can not measure the quality of life.
• Adverse effect may not be observed in
short term SEM studies.
Lessons learned from
SELDI-TOF
• Initial study on patient serum from cancer
patients (ovarian, prostate, etc) versus
cancer showed very promising results (nearly
100% sensitivity/specificity to separate
cancer from normal)
– Used case-control design
– Only 2 group-comparison (cancer vs. normal)
– No validation
• However, recent validation studies were
rather disappointing
Biomarker-Directed Targeted
Design
• Increase the efficiency of the trial, but
depends on:
– The performance of the biomarker test
(sensitivity/specificity)
– Size of the treatment effect for targetnegative patients
BIOMARKER STUDY DSEIGN
a. Untargeted Design:
Treatment
Register
Randomize
Control
b. Untargeted Design:
Treatment
Register
Test
Biomarker
Biomarker Randomize
+
Control
BIOMARKER STUDY DSEIGN
Biomarker by Treatment Interaction Design:
Treatment
Biomarker Randomize
+
Control
Register
Test
Stratify
Biomarker
Treatment
Biomarker Randomize
Control
BIOMARKER STUDY DSEIGN
Biomarker Based Strategy Design:
Biomarker
+
Treatment A
Test
Biomarker
Biomarker
-
Treatment B
Register Randomize
No Biomarker
Evaluation
Treatment B
BIOMARKER STUDY DSEIGN
Modified Biomarker Based Strategy Design:
Biomarker
+
Treatment A
Test
Biomarker
Biomarker
-
Treatment B
Register Randomize
Treatment A
No Biomarker Randomize
Evaluation
Treatment B
Actin Remodeling
As a Target for Biomarker
Development
NORMAL
CA
Morphological hallmarks of cancer cells:
•Altered N/C-ratio
•Altered membrane (cytoplasmic and nuclear)
•Loss of cell adhesion
•Increased motility/invasion/met.
•etc..
ALMOST All ARE RELATED TO ACTIN REMODELING
WHAT TO DO WITH THIS?
HYPOTHESIS/RATIONALE
• Altered cytoskeletal proteins, e.g., actin
remodeling, is the foundation for malignant
morphological phenotype
• Thus, signaling pathways associated actin
remodeling may provide a potential target for
anti-cancer drug development as well as
biomarkers for a more objective assessment
of malignant transformation and progression
• These targets can be identified through
genomic/proteomic approach
Model in Focal Adhesions
F-Actin
Tenuin
VASP
Zyxin
- Ras Sup.
Family
(Rac/Rho/CDC42)
Vinculin
Tensin
ECM
Actinin - pp60sro
- pp125FAK
-Abl
Paxillin
p-Tyr?
Talin
b
a
Substrate
R/E/M
Integrin
b
a
PM
ACTIN ASSCOIATED MOLECULARS IMPLICATED IN
MALIGNANT TRANSFORMATION
• Oncogene signal
transduction pathways
– Ras family ( GTPase):
• Rho (stress fibers)
• Rac (lamellipodia)
• Cdc42 (filopodia)
– Src family (tyrosine
kinase)*
– FAK*
* Relate to intergin signaling
• Tumor Suppresor
– Gelsolin*
– Tropomyosin/merlin
– Alpha-actinin*
– E-cadhelin
– Beta-Catanin
– Vinculin
– Fodrin*
*Implicated in apoptosis
Increased cellular F-actin is a marker of
cellular differentiation
Using leukemic cell lines:
HL-60- Transformed/Differentiable
Daudi- Transformed/Undifferentiable
RPMI - Nontransfomed
We demonstrated that increased Factin content is associated with
cellular differentiation
(J. Rao, Cancer Res., 1990)
In contrast, loss of F-actin is a marker for
cellular transformation and bladder cancer
risk
Bladder wash samples from
a spectrum of cases with
various risk for TCC show a
strong correlation of loss of
cellular F-actin contents
with increased bladder
cancer risk.
(J. Rao, Cancer Res., 1991)
Furthermore, actin alteration is a field
disease marker for bladder cancer
A careful mapping analysis
on touch prep slides obtained
from distant, adjacent and
tumor tissues showed that
increased G-actin is seen in
over 50% of the distant field
epithelial cells of cancer
bearing bladder.
(J. Rao, P.N.A.S., 1993)
QFIABiomarker Profile
G-actin: Texas-Red conjugated
DNase I
M344: FITC (or Rhodamin) 3Step Immunofluorescence
DNA: Hoechst or DAPI
Test Our
Our Biomarker
Biomarker Profile
Profile
)Test
to
to Detect
Detect Bladder
Bladder Cancer
Cancer
in
in Workers
Workers Exposed
Exposed to
to
Cancer
Cancer Causing
Causing Chemicals
Chemicals
Study Design in Worker Risk Assessment Study
1788
Workers
Very High
Risk
High Risk
Positive
Cystoscopy
TREAT
Negative
Moderate
Risk
373
controls
Monitor in
1 yr
Monitor in 3 yrs
Low Risk
Screen Workers
Markers
Exposure
Physical Exam
Questionnaire
Smoking Asses.
Classify
Risk
Action/Intervention
Procedures in Screening Program
!
Notification of
of exposed
exposed workers.
workers.
!Notification
!
Selection of
of matching
matching controls.
controls.
!Selection
!
Administration of
of questionnaire.
questionnaire.
!Administration
66Occupational
Occupational history.
history.
66Medical
Medical history.
history.
66Genitourinary
Genitourinary tract
tract history.
history.
66Smoking
Smoking assessment.
assessment.
!
Physical examination.
examination.
!Physical
!
Urinalysis
!Urinalysis
!
Papanicolaou cytology
cytology
!Papanicolaou
!
DNA, M344,
M344, G-actin
G-actin biomarkers
biomarkers
!DNA,
Pathology Summary
6 30 Cancers detected
) 29 Transitional Cell Carcinoma
) 1 Squamous Cell Carcinoma
6 4 Cases of Muscle Invasion (>T2)
6 20 Cases Grades 1-2; 8 Cases Grade 3.
Incidence Rate (per 100,000 person-year) of Bladder
Cancer in the Cohort Exposed to Benzidine ( 1991-1997)
Cohort
No. of
Subjects
Followed
Age ( Mean ± SD )
Cancer
Cases
Incidence
Unexposed
373
57.7 ± 10.8
2
87.23
Exposed
1788
55.4 ± 10.5
28
263.35
Total
2161
55.8 ± 10.5
30
232.11
TEST POSITIVE PRIOR TO OR AT
THE TIME OF DIAGNOSIS
NO. OF
RATE
BIOMARKERS POSITIVE/NO.
POSITIVE %
OF CASES
QFIA HIGH OR
MODERATE
RISK
PAP
CYTOLOGY
HEMATURIA
28/29
96.5
15/28
53.6
4/28
14.3
Biomarker Results of Cohort Study
Detection
Sensitivity Specificity
OR
PPV
DNA
67
87
12.8
5.2
M344
55
98
55
23.1
High Risk
68
91
21.1
8.3
HM or P
86
70
15
3.4
PAP
62
99
244
48.1
Biomarker Results of Cohort Study
Risk Assessment
Sensitivity Specificity
OR
PPV
DNA
88
87
46
2.7
M344
50
98
46
9.1
High Risk
63
91
17.3
2.9
HM or P
88
70
16.6
1.3
PAP
14
99
24.7
6.7
Cox Proportional Regression Model with
Time Dependent Covariates
Biomarkers
DNA
G-actin
M344
PAP
Hematuria
High or Middle Risk
High Risk
Risk Ratio1
16.2
3.2
37.9
14.7
5.1
13.5
25.5
95% Confidence Limits
7.1 - 37.0
1.2 - 8.4
16.8 - 85.3
6.2 - 34.6
1.2 - 22.1
5.3 - 34.7
11.0 - 59.1
1. Risk ratios were adjusted by age and total months of exposure
Lead Time to Tumor Detection During the Follow-up
(1991-1997)
Total
Cases=25*
N
% Cases
Mean
Months
Moderate Risk
10**
40
33
High Risk
23
92
15
Pap
16
64
8
Hematuria
4
16
3
** 44cases
caseswere
were excluded
excluded due
due to
to their
theirdetection
detection at
atthe
the initial
initial screen.
screen. 11
case
case was
wasexcluded
excluded due
due to
to the
the error
error of
of sample
sample collection.
collection.
**** 88out
of
10
cases
progressed
to
high
risk
prior
to
out of 10 cases progressed to high risk prior to tumor
tumor detection.
detection.
Abnormal G-actin in the Field Predicts Tumor Recurrence
Cellular actin levels can be used to monitor
the effectiveness of chemoprevention
•Cellular F/G-actin levels in the
non-tumor field epithelial cells
after tumor was removed by TUR
predicted the recurrence potential
of the tumor.
•In addition, cellular F/G-actin
levels fluctuate from abnormal to
normal as results of
chemopreventive effect of
differentiation agent DMSO.
(G.P. Hemstreet, J. Rao, Cancer Det. And Prev.,
1999)
SUMMARY:
Actin Remodeling in Cancer
• Actin remodeling as a generalized marker for:
– Cancer field changes
– Precancerous lesions
– and thus, a candidate for chemopreventive SEM
• However:
– Measuring actin remodeling is technically
challenging
• New method/tools are needed
Nanomechanical analysis of cancer
cell softness/elasticity
• Atomic Force Microscope:
– A new tool for cancer research
– Ideal for analyzing the functional role of
actin remodeling in various cellular events
in single living cells
– Combine functional analysis with
morphology at nanometer level
NEWS HEADLINES
• Nanotechnology shows cancer cells
are 'softer' than normal cells
• Microscopic 'tools' can identify cancer
cells by 'feel‘
• Nano breakthrough in cancer
detection: study
• ….
(a)
(b)
(b)
Force
(a)
(c)
Displacement
Fig. 1. Schematic of an AFM tip
(a) approaching,
(b) indenting and
(c) retracting from a cell
(c)
0 hr
6 hr
24 hr
Average Young’s Modulus (E) values for A549 human lung
adenocarcinoma cells treated with or without (ctrl) 40 ug/mL green
tea extract (GTE) for 6 and 12 hours, respectively.
Ctrl
GTE
Effects of GTE on the migration of A549 cells. Confluent
monolayers of cells were maintained in a serum free media
and a lane was scraped through the monolayers of the cells
with a plastic micropipette tip. The cells were allowed to
migrate across the lane at 37 oC for 6 or 24 h in the
presence (40 µg/ml) or absence of GTE. The distance that
cells migrated into the area of the wound at different
points was photographed using a computer imaging
system. Top panels: GTE untreated; lower panels: GTE
treated (40 μg/ml).
A
B
Mesothelial cells
Tumor
Phase-contrast
D
C
Adhesion Force Measured between
Mesothelial Cells and Cancer Cells
8
Mesothelial cells
Cancer cells
7
Measurement
6
Counts
5
4
3
2
1
300
250
200
150
100
50
0
E
AF
0
0
50
100
150
200
250
Young's Modulus (E)
300
350
400
AFM Measurements
c
a
(ii)
(i)
b
d
“Chemoprevention of Superficial Bladder
Cancer in Former Smokers”
Parallel, Randomized, Double-blind, Placebo-Controlled, Phase II
Adjuvent Studies of Erlotinib and Polyphenol E to Prevent the
Recurrence and Progression of Tobacco-Related, High-grade
Superficial Bladder Cancer
U01-CA-96116
Study Objectives
• Primary:
– To evaluate the effects of a daily dose of PE,
Erlotinib, and placebo on tumor recurrence for pts
with superficial bladder ca (former smokers)
• Secondary:
– To assess toxicities of PE and Erlotinib
– To correlate the modulation of biomarkers with
tumor recurrence/progression
– To assess the effects of PE and Erlotinib on tumor
progression
Study Design
• Phase II, randomized, double-blinded,
placebo-controlled, 3-arm trials
• A random permuted study design with one
stratification factor (Ta vs T1 vs CIS)
• Two agents: PE- 800mg/daily, Erlotinib (up
to 100mg/daily
• 330 former smokers (<12 months) with
prior superficial bladder ca
Placebo
Stage
Ta
T1
CIS
Treatment
PE
Erlotinib
Specimen Types
• Blood
• Urine cytological specimens
– Voided urine
– Catheterized urine
– Bladder wash
• Tissue
– Biopsy
– Cystectomy specimen
Key Secondary Biomarkers
• Cytology
• QFIA Profile:
– DNA & G-actin by LSC
– M344/19A211/LDQ10 by Immunocyt kit
• Microsatellite Instability Markers
(M.S.I.)
• bFGF
• Survivin
Biomarker Core
Urinary Cytology
Tissue
Blood
5 cc
(VU/CU/BW, 100 cc each)
(ca, random)
(20 cc)
Store
10 cc 2-bFGF
Thin Prep (3)
1 slide
2- Cytology
Leukocyte
Brook’s lab
Fresh
Frozen
2 slide
2-QFIA
Rao’s Lab
Store
(Rao’s lab)
Paraffin
Emb.
Plasma
3- Genetic
Polym.
(Zhang’s lab)
1- Histology
4- Polyphenol
(Heber’s lab)
3- Tissue Array
Extract Genomic DNA
2- M.S.I.
(Core facility)
EGFR, Ki67, Gelsolin, p53, etc
(Seligson’s lab)
3- Genetic
Polymorphism
(Zhang’s lab)
1- Primary end point
2- Secondary end point
3-Tertiary end point
4- Compliance marker
Summary
• Biomarker is needed in Chemoprevention
Trial to:
– Detect early preventable lesions
– Monitoring the efficacy
• Actin remodeling and associated cellular
nanomechanical changes provide a wealth of
targets for chemopreventive biomarker
selection:
– Actin change occurs in premalignant field lesion
– Chemopreventive agents (e.g., green tea)
modulates actin remodeling
– Actin change can be detected either by traditional
biochemical assays or AFM measurements of
cellular nanomechanics