Download ASCO_2013_files/Lenz Poster Disc ASCO 2013

Biomarker and
Pharmacogenomic Modeling in
Upper GI Cancer: Fantasy or
Becoming Reality
Heinz-Josef Lenz
Professor of Medicine and Preventive Medicine
Associate Director, Clinical Research
Kathryn Balakrishnan Chair for Cancer Research
Co-Director, USC Center for Molecular Pathways and Drug Discovery
Co-Leader GI Oncology Program
USC/Norris Comprehensive Cancer Center
Discussion
• Pancreas Cancer (4016, 4017,4022)
– SPARC for real and where do we look? (Sinn et al)
– PG modeling: The Future is Here (Yu et al)
– Early diagnosis using Vit D levels? Let the Sun Shine
(Van Loon et al)
• Gastric Cancer (4019, 4020,4021)
– Predict the site of recurrence TOP2, CGH, PECAM1:
How Important is this ? (Terashima et al)
– MAGIC: Will Gene Profiling give us the answer? We
need your help (Smyth et al)
– Expand: HER2ve better outcome? Is this true? (Lordick et
al)
• Biliary Cancers (4018)
– Cetuximab in mutant kras biliary cancers? Need more
patients! (Chen et al)
What is
SPARC
SPARC in pancreas cancer
Infante et al JCO 2007, vol 25, 319.
Sparc in the Stroma was associated with
increased Median overall survival
©2011 by American Society of Clinical Oncology
Von Hoff D D et al. JCO 2011;29:4548-4554
Stromal and cytoplasmatic SPARC
only in gemcitabine group not Obs
CONKO SPARC
• Sparc is prognostic……predictive?
Gemcitabine effect?
• Sparc in the tumor and/or stroma?
• IHC (tissue handling/AB specificity and
sensitivity/subjective reading)
Pharmacogenomics Modeling
1. PGx Model
Gene expression Drug(s)
Sensitive to A, not B
4.
PGX
Analysi
s
2. Patients
with pancreatic
cancer
Sensitive to B, not A
3. Gene
expression
profiling
Resistant to A and B
Pharmacogenomic Modeling in Pancreatic Cancer, Yu KH, et al.
Circulating tumor/invasive cells
• Surprisingly, PGx profiling of circulating
invasive cell population mirrors tumor tissue
Wilms Tumor
Pharmacogenomic Modeling in Pancreatic Cancer, Yu KH, et al.
Liquid biopsies
Tumor specific change (e.g. Mutation)
Tumor cell
release DNA
Circulating
Tumor
Cells (CTC)
Circulating
tumor DNA
CTC
Normal DNA
Tumor
http://www.inostics.com/
Studies show emergence of KRAS mutations
during treatment with EGFR inhibitors
Metastatic
tumor
Blood biopsy
Tumor
0
4
Stable disease
(by imaging)
8
12
ctDNA levels
Anti-EGFR therapy
Progressive disease
(by imaging)
16
20
24
Different therapy
KRAS-mutant ctDNA
Other mutant ctDNA
0
4
8
12
16
20
24
Weeks of treatment Misale S, et al. Nature 2012;486:532‒536
Diaz LA, et al. Nature 2012;486;537‒540
Vilar E, Tabernero J. Nature 2012;486:482‒483
Treatment Response in 1st Line PDA
Results
Sensitivity and Specificity of
Treatment Response in 1st Line PDA
Performance of PGx Test
10
# Patients
# Patients
15
15
13
Sensitive
Sensitive
Resistant
Resistant
10
n = 24
p-value = 0.0073
Sensitivity = 0.81
n=24
Specificity =n=24
0.75
p-value
= 0.007
PPV = 0.87p-value =
NPV =Sensitivity
0.67
= 0.8
6
5
5
3
0
0
2
TTP>6 mo
TTP< 6 mo
TTP at 6 months
> 6 months
TTP>6
mo
PFS
< 6 months
TTP<
6 mo
TTP at 6 months
Specificity = 0.7
Sensitivi
Pos PV
= 0.8
Neg Specifici
PV
= 0.6
 Patients receiving treatment predicted by our
model to be effective had longer PFS.
Pharmacogenomic Modeling in Pancreatic Cancer, Yu KH, et al.
Pos PV
Neg PV
Pathway Analysis
• Increased sonic hedgehog pathway disruption
associated with shorter TTP
• Multiple pathways became more disrupted with
progression:
–
–
–
–
PI3K pathway
E2F pathway
CREB pathway
PLC E pathway
Pharmacogenomic Modeling in Pancreatic Cancer, Yu KH, et al.
Discussion
• Liquid Biopsies and Genomic
Characterization will impact future trials
and drug development
• Complete TCGA data need to be analyzed
• Dynamic Changes critical for novel Drug
Development
• Explant Models but not possible in real
time but CTC are
• Prospective Studies needed
Vit D and Pancreas Cancer
Vitamin D deficiency (<20 ng/mL) was highly prevalent among patients with a
new diagnosis of APC (44.5%).
Black patients had significantly lower 25(OH)D levels than white patients
(median 10.7 vs. 22.4 ng/mL). 82.6% of blacks were deficient vs. 40.9% of
whites.
Discussion
1. Vit D associated with cancer incidence
2. Vit D key regulators in many pathways (wnt
etc)
3. Levels may be important prognostic
markers (population based cohorts)
4. Larger Studies needed (ethnicity
differences)
Gastric Cancer
DISEASE HETEROGENEITY
• Gastric Cancer is not one disease
– Histology
– Location
– Biology
– Etiology
(Intestinal vs Diffuse)
(Cardia/GEJ vs Antrum)
(MET, CDH1, FGFR others?)
(H. pylori related, others?)
Deep Sequencing
KRAS, ERBB2, EGFR, MET, PIK3CA, FGFR2 and AURKA genes in gastric cancer and suggests some of the
targeted therapies approved or in clinical development would be of benefit to 11 of the 50 patients studied. The data,
also suggests that agents targeting the wnt and hedgehog pathways would be of benefit to a majority of patients.
The previously undocumented DNA mutations discovered are likely to affect clinical response to marked therapeutics
and may be good drug targets.
Holbroook et al Journal of Translational Medicine 2011
(A) Focal regions exhibiting mutually exclusive patterns of
genome amplification. (B) Focal regions exhibiting
patterns of genomic co-amplification
Deng et al 2012 BMJ
Identifying Biomarkers for local recurrence:
Overlap of first recurrence site of 829 patients
(from 1059 pts in the ACTS-GC trial)
45
Lymph-node recurrence
8
16
3
118
10
76
Hematogenous recurrence
Peritoneal recurrence
*) Local (L) & Peritoneal(P); n=3, L & Lymph(Ly); n=3, L & H; n=3, L & Ly & H; n=1, L alone; n= 15
Presented by:
Results (RT-PCR candidates and low density array,
DISH (her2), IHC and Kras status)
1) TOP2A significantly correlated with hematogenous
recurrence. Hematogenous RFS was significantly worse in
TOP2A-high patients than in TOP2A-low patients (HR, 2.35;
95% CI, 1.55-3.57).
2) GGH significantly correlated with lymph-node recurrence.
Lymph-node RFS was significantly worse in GGH-high
patients than in GGH-low patients (HR, 1.87; 95% CI,1.133.08).
3) PECAM1 significantly correlated with peritoneal
recurrence. Peritoneal RFS was significantly worse in
PECAM1-high patients than in PECAM1-low patients (HR,
2.37: 95% CI, 1.65-3.41).
Presented by:
GGH expression in breast cancer
associated with OS
TransMAGIC NanoString panel
Genes (n = 200 + 3 controls)
E.g.
• Platinum treatment efficacy:
ERCC1/2, BRCA1/2, OPRT
• Chemosensitivity markers:
MYC, COX2, STAT3, HIF1a
E.g.
• Amplified in GC:
FGFR2, CCNE1,KRAS
• Deleted in GC:
FHIT, CDKN2A, CDKN2B, RB1
Presented by: Smyth EC, Tan IB, Cunningham D et al
E.g.
• GINT:
TOX3, MYB, CEACAM1
• GDIFF:
ABL2, SIX4, RASSF8
TransMAGIC NanoString RTK survival analysis:
ERBB2
0
2
4
Years from surgery
erbb2 = 1
6
erbb2 = 2
8
ERBB2 normal =
0.75
1.00
Survival
(all
pts)
SurvivalbybyERBB2
erbb2 (all
pats)
0.50
0.25
0.00
0.25
0.50
Proportion surviving
0.75
1.00
Survival
(surgery
pts)
Survivalby
byERBB2
erbb2 (surgery
pats)
0.00
0.00
0.25
0.50
Proportion surviving
0.75
1.00
Survival
(chemo
pts)
Survivalby
by ERBB2
erbb2 (chemo
pats)
0
2
4
Years from surgery
erbb2 = 1
6
erbb2 = 2
ERBB2 high =
8
0
2
4
Years from surgery
erbb2 = 1
6
8
erbb2 = 2
Overall survival from time of surgery in years
Chemotherapy
Surgery alone
Overall
ERBB2 normal ERBB2 high ERBB2 normal ERBB2 high ERBB2 normal ERBB2 high
Patients
80
9
104
16
184
25
Events
55
2
74
12
129
14
Median survival
1.45
Not reached
1.57
1.59
1.56
2.32
Logrank p-value
0.0197
0.5761
0.2317
Hazard ratio
1 (REF)
0.22
1 (REF)
1.19
1 (REF)
0.72
HR p-value
0.034
0.577
0.234
There is some evidence of an interaction between treatment arm and ERBB2 (p=0.027); reflecting very high survival rates
amongst the small group of patients on the chemotherapy arm with ERBB2 overexpression.
Presented by: Smyth EC, Tan IB, Cunningham D et al
EXPAND Study
Her2ve- has significant shorter OS (HR 1.55)
Her2ve- response was significantly lower (OR 0.48)
Cet, cetuximab; CT, chemotherapy
Overall Survival
By Amplification
Obs Arm
100%
No
Yes
80%
N
109
18
Events
89
14
P = .71
Median
in Months
24
24
60%
40%
20%
0%
0
24
48
72
96
Months After Registration
120
144
TransMAGIC NanoString RTK survival analysis:
EGFR
Survival by EGFR (chemo pts)
Survival by EGFR (surgery pts)
Survival by EGFR (all pts)
0
2
4
Years from surgery
egfr = 1
6
egfr = 2
8
EGFR normal =
0.75
1.00
Survival by egfr (all pats)
0.50
0.25
0.00
0.25
0.50
Proportion surviving
0.75
1.00
Survival by egfr (surgery pats)
0.00
0.00
0.25
0.50
Proportion surviving
0.75
1.00
Survival by egfr (chemo pats)
0
2
4
Years from surgery
egfr = 1
6
8
0
egfr = 2
EGFR high =
Overall survival from time of surgery in years
Chemotherapy
Surgery alone
EGFR normal
EGFR high
EGFR normal
EGFR high
Patients
83
6
115
5
Events
52
5
83
3
Median survival
1.83
0.53
1.59
0.59
Logrank p-value
0.0650
0.4403
Hazard ratio
1 (REF)
2.33
1 (REF)
1.57
HR p-value
0.073
0.444
2
4
Years from surgery
egfr = 1
6
8
egfr = 2
Overall
EGFR normal
EGFR high
198
11
135
8
1.63
0.59
0.0772
1 (REF)
1.89
0.082
EGFR was overexpressed in 11 patients; their prognosis was poorer in both treatment arms, there is no evidence of an interaction
between treatment arm and EGFR (p=0.601).
Presented by: Smyth EC, Tan IB, Cunningham D et al
Discussion
• Her family needs to be evaluated her1-4
(IHC+/- FISH)
• TOP2A co amplified with her2
• Unknown if prognostic (treatment effect)
Clinical Trials in Biliary Cancer using
EGFR/VEGF/MEK inhibitors
Randomized, Phase II GEMOX ± Cetuximab in Advanced BTC:
TCOG T1210 - Schema
Unresectable, locally advanced or metastatic BTC
Stratification:
ECOG PS: 0 versus 1
KRAS: wt versus mutant
Intra- versus extra-hepatic
R
N=60
Gemcitabine 800 mg/m2
Oxaliplatin 85 mg/m2
Q 2 weeks
N=62
Cetuximab 500 mg/m2
Gemcitabine 800 mg/m2
Oxaliplatin 85 mg/m2
Q 2 weeks
Primary EP: ORR,C-GEMOX 30% vs GEMOX 20%, (a=0.2/b=0.5)
Secondary EP: DCR≥16 weeks, PFS, OS, Safety & Biomarker
35
Presented by: Chen et al.
Randomized, Phase II GEMOX ± Cetuximab in Advanced BTC:
comparing therapeutic outcome of treatment arms in KRAS
mutation status-stratified subpopulations
36
Presented by: Chen et al.
Discussion
• Too small to draw any conclusions (RR,
PFS and OS consistent with previous
studies)
• Kras spectrum may be critical
• Braf mutations are important for biliary
cancer
• No detremental effect of Cetuximab in
these patients
• Previous trial negative for Cetuximab
combinations
We have a Future
There is Light on the end of
the Tunnel
• Completion of TCGA for Gastric, Pancreas
and Hepatobiliary Cancers
• Liquid Biopsies CTC/tumor DNA reflect
pathway changes under therapy
• Biomarker/PG Modeling Driven Trials
(based on mutation and gene expression
data e.g. SPARC, FGFR….)
• International Collaborations to move
science forward