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NorCal SOT Fall Symposium: New Frontiers in Oncology Drug DevelopmentSeptember 27, 2012
Jocelyn HolashNovartis Institutes for Biomedical Research
Preclinical strategies to help better identify responder populations in the clinic
| NorCal SOT Fall Symposium | Holash | September 20122
Limitations of existing preclinical model systems
• The number of models used in preclinical evaluation typically under-represents the number of distinct tumor types
• Models often inadequately characterized at the molecular level (making alignment to human disease impossible)
• In vitro selection pressures alleviate dependence on key oncogenic pathways
• In vitro models do not replicate stromal-tumor cell interactions
• Use of immuno-compromised animals eliminates the ability to study modulators of antitumor immunity, and suffer from cross-species imperfections in ligand-receptor interactions etc
• Low throughput of in vivo models limits the number of tumor types that can be tested
Building a robust pre-clinical translational infrastructure
Human Cancer Therapeutic-ProfilingModel Systems• Build databases from
public sources
• Fill gaps with external and internal efforts:- Sequencing project
• Cancer Cell Line Encyclopedia
• Murine tumor allograft models
• Primary tumor models
• CLiP (cell line profiling)
• Drug Combinations Zalicus screen
• Drug resistance
• shRNA pooled screens
Improving indication selection and patient stratification – what can we do pre-clinically ?
Building a robust pre-clinical translational infrastructure
3 | NorCal SOT Fall Symposium | Holash | September 2012
Human Cancer
3 key human cancer databases integrate internal and external (GEO, TCGA, COSMIC) data meticulous sample curation consistent QC and data normalization accessible for analysis and visualization
OncExpress OncCNAOnc*Base• N= ~50,000 samples
• Expression data for tumors, models and normal tissue
• Analytical tools: Prevalence analysis, Outlier analysis, Correlation analysis
• N= ~580,000
• Allows retrieval of mutation data in human cancer
• Analytical tools: Find gene mutation frequency, recurrent gene mutations, lineage patterns, structure
• N = ~6,000
• Copy number data base derived from SNP array analysis
• Analytical tools: Find recurrent chromosome alterations, delineate regions of conserved copy number change, correlate with expression
Human cancer databases provide the foundation
4| NorCal SOT Fall Symposium | Holash | September 2012
| NorCal SOT Fall Symposium | Holash | September 20125
Cancer Cell Line Encyclopedia: 1000 cell lines annotated by molecular profiles and response Goal: to identify predictive biomarkers for patient selection
Expression profiling Affy U133 Plus2 array
Copy number/LOH analysis, genotyping: Affy SNP6.0 array
Mutation analysis:• Oncomap Ver 3.0, 353 mutations (Sequenom
iPlex) • Hybrid (exon) capture ~1600 genes (Illumina)
Compound Sensitivity2000 cpd x 500 lines x 8 pt IC50
shRNA Sensitivity145 cell lines x ~2000 genes
| NorCal SOT Fall Symposium | Holash | September 20126
Cell lines model the genetic diversity of tumors
| NorCal SOT Fall Symposium | Holash | September 20127
CCLE portalhttp://www.broadinstitute.org/ccle
| NorCal SOT Fall Symposium | Holash | September 2012810 15 20 25
0
500
1000
1500
2000Vehicle0.6 mg/kg bid6 mg/kg bid60 mg/kg bid300 mg/kg bid
Time Post-Implant (Days)
Tu
mo
r V
olu
me
(mm
3)
mea
n
SE
M
Progress towards targeting the RAS/RAF/MAPK pathway
Kinase Assay IC50 (nM)
BRAFV600E 0.4
BRAF 0.5
CRAF 0.3
Cell-Based – A375
pERK 3
Proliferation 4
LGX818 Potency
A375 (BRAFV600E) xenograft
pERK Ki67
Veh
icle
10 m
g/k
g
Growth Factors
RTKs
Grb2/SOS
RAS
RAF
MEK
ERK
| NorCal SOT Fall Symposium | Holash | September 20129
The Cancer Cell Line Encyclopedia: CLiP
Cpds (2
00
0)
Therapeutic Profiling
Sensitive Insensitive Cell Lines (>500)
LGX818
CliP: Large-scale compound profiling using CCLE cell lines
| NorCal SOT Fall Symposium | Holash | September 201210
LGX818 Cellular GI50(uM) across 501 cell lines
1-
0.1-
0.01-
LGX818 is a potent and highly selective RAF kinase inhibitor
LGX818 is selective for cells expressing BRAFV600E/D/KIC
50 (
uM
)
Melanoma and CRCV600E/D/K lines are themost sensitive
BRAF mutation status
V600E
V600D/K
Non -V600
Wildtype
Sensitivity is greatest within melanoma and CRC lineages
11 | NorCal SOT Fall Symposium | Holash | September 2012
| NorCal SOT Fall Symposium | Holash | September 201212
A genotype centric view of the “cube” (CLE)Pharmacologic sensitivity for 1300 compounds in >500 cell lines
BRAF V600E mutated cell line
Cell Lines (>500)
Cp
ds (1
30
0)
Sensitive Insensitive
| NorCal SOT Fall Symposium | Holash | September 201213
BRAF mutant cancer cell lines are more sensitive to RAF or MEK inhibitors
Compound Rank
Class Mechanism of Action Rank
RA
F in
hib
ME
K in
h
BR
AF
mut
Sel
ectiv
ityB
RA
F m
ut S
elec
tivity
| NorCal SOT Fall Symposium | Holash | September 201214
A Computational Framework for IdentifyingPredictive Biomarkers
Copy number
Expression
Explicit feature selection (Fisher or Wilcoxon +
local FDR)
Categorical machine
learning and cross-validation (predict class)
Mutation
Lineage
Sensitive
Intermediate
Insensitive
Cell line rank
Co
mp
ou
nd
re
spo
nse
Assign Response class
Output of predictive “features”
Effe
ct v
s co
ntro
l
Concentration (log)
IC50
Amax
AUC
| NorCal SOT Fall Symposium | Holash | September 201215
Genetic features identified as predictors of sensitivity
LGX818 “feature matrix” 50K features#1 predictive feature: BRAF mutation
Compound Target(s) Feature Rank
LGX818 BRAF BRAF mut 1*
RAF265 BRAF BRAF mut 1*
lapatinibEGFR, ERBB2 ERBB2 amp 1
BYL719 PI3Ka PIK3CA mut 1
PD0325901 MEK BRAF mut 10*
AZD6244 MEK BRAF mut 1*
PF2341066 MET Met amp 3
*additional MAPK pathway features in top 50 (DUSP, SPRY, ETV, NRAS for MEK inhibitors)
Cell Lines
Fea
ture
s
| NorCal SOT Fall Symposium | Holash | September 201216
BRAF
MEK1ERK2
Finding synthetic lethality through shRNA screeningPooled shRNA screens across many cell lines
Growth: Inhibition Induction
PooledshRNA POOLS
T24Count
Cell Line
Countby NextGenSequencing
Day 0
Day 7
Day 14
| NorCal SOT Fall Symposium | Holash | September 201217
Com
bina
tions
Mut
atio
ns
• Mid-scale hypothesis directed screens enabled through a global effort e.g. PI3K-RAS pathway combination screens across melanoma and CRC cell lines
0
100
200
300
400
500
600
0 5 10 15 20
Tumor
Volum
e (mm
3+/
-SEM
)
Days Post-dose
Vehicle
RAF265 25 mg/kg q4dx7
BKM120 20 mg/kg qdx19
RAF265 25 mg/kg + BKM120 20 mg/kg
Vehicle
RAF265 25mg/kg q4d
BKM120 20 mg/kg qd
RAF265 + BKM120
* p < 0.05 vs Vehicle
Days
Mea
n tum
or v
olum
e (m
m3) �S
EM
RAF265 + BKM120 HT29 (B-RafV600E; PI3KaP449T)
Colon Xenograft Model
• Large-scale systematic discovery of combination activity on-going in collaboration with Zalicus.
Towards the systematic study of combination effects
| NorCal SOT Fall Symposium | Holash | September 201218
Rationale/Goal
• Human tumors propagated in culture undergo artificial selection
e.g. p16 deletion increases loss of Hedgehog signaling loss of Wnt signaling
• Primary propagation in nude mice may lead to more predictive models or provide models that otherwise are very limited
e.g. Pancreatic xenograft modelsvs. pancreatic cancer cell lines
Building predictive preclinical modelsPrimary human tumor xenograft models
Primary Tumor
Implant
| NorCal SOT Fall Symposium | Holash | September 201219
Novartis Primary Human tumor model bank
Primary Tumor
Implant
Tumor type Received Established
Colon 125 63
Lung 196 55
Breast 362 47
Pancreas 159 52
Ovary 231 39
Sarcoma 199 47
Kidney 328 25
Melanoma 61 27
Uterus 25 10
Esophagus 21 10
Brain 49 8
Lymphoma 73 4
Stomach 43 4
Liver 56 2
Intestine 8 3
Others 179 15
Total 2115 410
Molecular Annotations
Progress(total = 410)
SNP 6.0 286
Affy U133 288
RNA-Seq 55
Whole Exome 12
2K Exome 185
| NorCal SOT Fall Symposium | Holash | September 201220
In vitro to in vivo translation: LGX818 is efficacious only in human tumor xenografts expressing BRAFV600E
22 24 26 28 30 32 34 360
300
600
900
1200
Vehicle bid
20mg/kg bid
Time Post-Implant (Days)
Tum
or V
olum
e (m
m3)
mea
n
SE
M HMEX1655 (BRAFwt, KITN822K)
HMEX1906 (BRAFV600E)Malme-3M (BRAFV600E)
15 18 21 24 270
500
1000
1500
2000
Vehicle bid
0.6mg/kg bid6mg/kg bid
60mg/kg bid300mg/kg bid
Time Post-Implant (Days)
Tum
or V
olum
e (m
m3)
mea
n
SE
M SW620 (BRAFwt, KRASG13D)
55 60 65 700
100
200
300
400
500
Vehicle qd0.5mg/kg qd3mg/kg qd20mg/kg qd
Time Post-Implant (Days)
Tum
or V
olum
e (m
m3)
mea
n
SE
M
**
21
Taking Advantage of Primary Tumors: Modeling Resistance to RAF inhibitors in BRAF(V600E) Human Melanoma Xenografts
Time
Con
cent
ratio
n
• Treatment with vemurafinib models human clinical response: initial tumor regression followed by the emergence of resistant tumors
0
500
1,000
1,500
2,000
2,500
20 40 60 80 100 120 140
Tum
or
volu
me
(mm
3 ) resistant
HMEX1906 Human melanoma xenograft
| NorCal SOT Fall Symposium | Holash | September 2012
Serial biopsy of resistant tumors for PD analysis
| NorCal SOT Fall Symposium | Holash | September 201222
Gene signature predicted from cell line sensitivity screening accurately predicted 3/3 responses on primary tumor models
A mini-randomized trial of therapeutics in pancreatic cancer
stasis
Tum
or G
row
th
Tested 7 NVS compounds in 9 pancreas primary tumors.
One therapeutic candidate was the most active.
Tumor Growth Curve (HPAX2406)
27 34 41 480
250
500
750
1000
Days post implantation
Tum
or V
olum
e (m
m3 )
mea
n
SE
M
Tumor Growth Curve (HPAX2198)
59 66 73 80 870
250
500
750
1000
Days post implantation
Tum
or V
olum
e (m
m3 )
mea
n
SE
M
Tumor Growth Curve (HPAX2633)
38 45 52 59 66 730
250
500
750
1000
Days Post Implantation
Tum
or V
olum
e (m
m3 )
mea
n
(SE
M)
Tumor Growth Curve (HPAX1959)
57 64 71 78 850
250
500
750
1000
Days Post Implantation
Tum
or V
olum
e (m
m3 )
mea
n
(SE
M)
Tumor Growth Curve (HPAX1317)
31 38 45 52 590
250
500
750
1000
Days Post Implantation
Tum
or V
olum
e (m
m3 )
mea
n
(SE
M)
Tumor Growth Curve (HPAX2046)
21 28 35 42 490
500
1000
1500
Days Post Implantation
Tum
or V
olum
e (m
m3 )
mea
n
(SE
M)
HPAX2402 HPAX1317 HPAX1959
HPAX2406 HPAX2198 HPAX2633
HPAX1948 HPAX2043 HPAX2428
| NorCal SOT Fall Symposium | Holash | September 201223
Primary Mouse Tumor Allograft Models
Primary Tissue
MonitorTumor growth
Passage (P1)
Fix Tissue Flash Freeze
HistologyIHC
Fix / freeze
SNP arraysExp Prof.
Exome seq.
Efficacy studies
Freeze (master stock)
Passage (P2)
Passage (P3)
Passage (P4)(working stock)
Implant
Rationale
• Use of immunocompetent mice supports species-matched host- tumor interactions
• Tumor immunology• Tumor stroma interactions• Developmental signaling pathways
• GEMM-derived tumors may provide broader coverage of disease progression
• Include tissues not available from patients
• Forward genetics approach
| NorCal SOT Fall Symposium | Holash | September 201224
Model SystemsMolecularProfiles
Cancer
Human Cancer
CompoundProfiles
Towards curative therapy for cancer
• Define to completion the genetic basis of cancer
• Create a large collection of genetically annotated human cancer cell lines and preclinical animal models representative of human cancers for therapeutic profiling
• Define resistance mechanisms early (prior to clinical entry) and develop either second-generation inhibitors or combination strategies
• Define highly active combinations that can lead to curative therapies
| NorCal SOT Fall Symposium | Holash | September 201225
NIBR
Emeryville, Basel
Shanghai
Cambridge
GNF San Diego
Acknowledgements
• External Collaborators and partners• Patients and their families