Leveraging molecular and clinical data to transform drug discovery in the era of precision medicine

1. Leveraging molecular and clinical data to
transform drug discovery in the era of
precision medicine
Aug 2017 @Stanford CLIPSS
Bin Chen, PhD
Assistant Professor
Dept. of Pediatrics
InsDtute for ComputaDonal Health Sciences
University of California, San Francisco
hHp://binchenlab.org
Bin.Chen@ucsf.edu
@DrBinChen

2. David Silver, Nature, 2016

3. IMAGE-NET
hHp://www.image-net.org/

4. Person
Car
Motorcycle
Helmet

6. hHps://junyanz.github.io/CycleGAN/

7. Andre Esteva, Nature, 2017

8. 25 petabytes 2014
hHp://bit.ly/1OyTuqZ
60 petabytes 2015
hHp://bit.ly/2o3QJdy

9. × 60 petabytes = 30,000
120 000 datasets!

10. DNA
RNA
Protein
Interaction
Metabolite

11. T Barre' - ‎2013, Nucleic Acids Research

12. hHp://firebrowse.org
Cancers

13. hHp://www.lincsproject.org/data/data-releases/
• >20,000 Small-molecule compounds
• ~1,300 FDA-approved drugs
• >20,000 genomic perturbagens
• > 70 cell types
• Cancer cell lines
• Primary cells
Library of Network-Based Cellular Signatures (LINCS)
Cell lines
Assays

14. hHp://www.mskcc.org/research/health-policy-outcomes/cost-drugs

15. Data-driven translaDonal drug discovery in oncology
Chen B., Bu'e AJ. Clinical Pharmacology and TherapeuCcs, 2016
Big Data
+ AI

16. Central hypothesis: Drugs that reverse a disease gene expression
signature may be therapeuDc agents for that disease

17. A systems approach to idenDfying drug candidates for
hepatocellular carcinoma (HCC)
Chen B#, Wei W#, Ma L, Yang B, Gill RM, Chua MS*, BuHe AJ*, So S, Computa5onal Discovery of
Niclosamide Ethanolamine, A Repurposed Drug Candidate That Reduces Growth of
Hepatocellular Carcinoma Cells in Vitro and in Mice by Inhibi5ng CDC37 Signaling.
Gastroenterology. 2017, doi: 10.1053/j.gastro.2017.02.039.
Code available at hHps://github.com/Bin-Chen-Lab/HCC_NEN

18. Some tumor samples poorly correlated with HCC cell lines
Chen B., et al. BMC medical genomics, 2015

19. HCC disease gene expression signature
type
non−tumor
tumor
−3
−2
−1
0
1
2
3
Sample
274 disease genes

20. Niclosamide is the top candidate that reverses HCC gene
expression signature
H
C
C
niclosam
ide
cam
ptothecin
doxorubicin
iverm
ectin
daunorubicin
fluphenazine
cefixim
e
papaverine
purom
ycin
vorinostat
m
itoxantrone
staurosporine
pentam
idine
ouabaindigoxin
m
ebendazole
halofantrine
down
up
anthelminDcs

21. Select right cell lines for validaDon
Chen B., et al. BMC medical genomics, 2015
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0.2
0.3
0.4
0.5
0.6
0.7
H
EPG
2C
3AH
U
H
1JH
H
5
SN
U
878
SN
U
761H
U
H
7
SN
U
886JH
H
7
PLC
PR
F5
ALEXAN
D
ER
C
ELLS
H
EP3B217
LI7JH
H
2
SN
U
387
SN
U
475JH
H
4JH
H
1
SN
U
449JH
H
6
SN
U
423
SN
U
182H
LFH
LE
SN
U
398
correlationtotumors
HCC relevant cell lines (P<0.05)
cell lines used for validation

22. Niclosamide and its salt NEN reduced the viability of HCC cells
D
M
S
O
0.05
0.1
0.2
0.4
0.8
1.6
3.2
6.4
12.8
0.0
0.5
1.0
1.5
2.0
concentration (µ )
OD490
HepG2
NEN
niclosamide
D
M
S
O
0.05
0.1
0.2
0.4
0.8
1.6
3.2
6.4
12.8
0.0
0.5
1.0
1.5
2.0
concentration (µ )
OD490
Huh7
NEN
niclosamide
A
Niclosamide
ethanolamine (NEN)
Niclosamide

23. NEN inhibited tumor growth in three PDX models
control NEN

24. NEN inhibited tumor growth in primary HCC models
control NEN

25. Choose drug combinaDon based on exisDng clinical trials
Menghua Wu
Jane Wei Wu M., et al. Pacific Symposium on BiocompuCng, 2015
APPROVAL STATUS
Approved
Pre-Approved
Discontinued (two
stacks only)
79%
19%
1.3%
<1%
<1%
Total Appearances
Approved 92%
Pre-approved 8%
Discontinued <1%

26. The combinaDon with the standard of care Sorafenib has a
more profound effect
drinking water
NEN
sorafenib
NEN & sorafenib

27. Illumina HT-12
V4 bead chip
Control
NEN
NEN reversed HCC signature in one PDX model

28. Potency to reverse disease gene expression correlates to drug
efficacy in cancers
Chen B*#, Ma L#, Paik H, Sirota M, So S, Chua MS*, BuHe AJ*. Reversal of cancer gene
expression correlates with drug efficacy and suggests therapeu5c targets, Nature
CommunicaCons, 2017
Code available at hHps://github.com/Bin-Chen-Lab/RGES

29. Potency to reverse disease expression correlates to drug
efficacy in liver cancer
Potency to reverse disease gene expression
Drug efficacy
●
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●
●
●
●
LIHC
r=0.55, P=2.1e−05
rho=0.61, P=1.34e−06
0
2
4
6
8
−0.4 0.0 0.4
sRGES
log10(IC50)nm

30. and in breast and colon cancers
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r=0.47, P=8.19e−08
rho=0.5, P=1.4e−08
0
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6
8
−0.4 0.0 0.4
sRGES
log10(IC50)nm
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COAD
r=0.31, P=2.46e−03
rho=0.3, P=3.56e−03
0
2
4
6
8
−0.4 0.0 0.4
sRGES
log10(IC50)nm

31. sRGES idenDfied four novel compounds in LIHC LIHCpyrvinium
−pam
oate
CG
K−733
FCCP
strophanthidin
CGK-733
Strophanthidin
FCCP
Pyrvinium Pamoate

32. sRGES predicted drug efficacy in vitro and in vivo
HepG2 Huh7 Hep3B PLC5 Hep40 Median
IC50 (µM)
strophanthidin 11.59 0.72 0.16 1.61 0.19 0.72
FCCP 7.84 2.67 0.29 1.78 0.87 1.78
CGK 733 6.12 2.96 3.18 9.51 2.73 3.18
pyrvinium pamoate 0.14 0.02 0.01 0.15 0.07 0.07
1 3 5 7 9 11
0
1000
2000
3000
4000
Treatment time (d)
Tumorvolume(mm3)
Vehicle Control
pyrvinium pamoate (1 µg)
*