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High Throughput Screening as a Research Tool
Robert Damoiseaux. Ph.D., Scientific DirectorMolecular Shared Screening Resources, UCLA
Structure of this seminar
• Applications of High Throughput Screening
•The Drug Discovery Workflow – old and new
• Adaptive Diseases
• Case Study: Biofilms
• Case Study: Prostate Cancer
• Case Study: Cancer Stem Cells
High Throughput Screening as a Research Tool
High-Throughput Screening
Drug Discovery• Targeted Libraries• Drug-like Libraries• Diverse LibrariesFunctional Genomics
• siRNA Screens• Lentiviral Screens• cDNA screens
Chemical Genomics• FDA Approved Drugs• Bioactives• Natural Products
Materials Discovery• High-throughput Chemistry• High-throughput QC
Materials Characterization• Automated Toxicity Profiling• Profiling on Live Cells Using Functional/Chemical Genomics
Disease relevant process
Disease modifying target
Disease
High Throughput Screening Campaign
Target Centric Drug Discovery- pregenomic
Disease relevant process, pathway or phenotype
Disease
High Throughput Screening Campaign
Drug Discovery- postgenomic
Target Discovery
What changed?
• More targets are known than can be reasonably screened
• Not all players in a disease relevant pathway are known-or accessible for screening
• Novel technology such as High Content Screening (HCS)allows for black box screening approaches
•Target discovery for hits from screens has become morefeasible using Functional Genomics using HighThroughput Screening
Screening StrategyAssay Technology
Library Choice
Screen Validation and Execution
Data Mining,rescreeningand secondary screening
Novel Target
Further specificityprofiling
Lead discovery
Unknown Target
Novel Target(s)
Target Discovery
Small MoleculeProbe for Chemical
Genomics
Novel agonist or antagonist
Known Target
Compound rejected
General Screening Workflow
Taken from: “Molecular Screening” by R. Damoiseaux, Ph.D.in “Development of Therapeutic Agents Handbook”
Forthcoming from Wiley and Sons
Integrated
Using HTS as a Research Tool
Examples:
• Cancer: e.g. occurrence of resistance to chemotherapy
• Infectious diseases: occurrence of resistance to e.g. anti--virals, antibiotics etc.
Adaptive Diseases
- diseases which are able to adjust to the selective pressure exerted by the treatment with drugs.
Overcoming Adaptive Diseases
Examples:
• HIV: Development of HAART
• Cancer Therapy: Multi-drug therapy
Acute Disease ⇒ Chronic Disease
HTS as Research tool : Case Studies
• Modulation of Bacterial Biofilms by compounds and drugs
• Prostate Cancer
•Cancer Stem cells
• Biofilm: A macroscopic structure on a biological (e.g. mucous membrane) or inert surface consisting of bacteria and extracellularmatrix consisting of polyglycans.
• Biofilms are not easily permeated by antibiotics
• Biofilms are not easily accessible to the immune system
⇒ Biofilms are a bacterial resistance mechanism causing many problems in the medical area.
Biofilm assay examples
In a 384 well plate biofilm forming Haemophilus Influencae bacteria or media control were incubated over night, the resulting biofilm detected in a fully
automated fashion.
media control Biofilm0
1000000
2000000
3000000
4000000
5000000
6000000B
FU
Biofilm assay examples
0
150
300
450
Frequency
% B
iofil
m M
odul
atio
n
A set of about 2 k compounds was incubated with biofilm forming bacteria and the amount of biofilm production measured.
0
70
Frequency
% B
iofil
m M
odul
atio
n
Biofilm assay examples
Bacteriocidal and biofilm stimulating
Bacteriocidal and not biofilm stimulating
Exploring the HER kinase‐androgen receptor interaction in prostate cancer
Using Chemical Genomics to explore the HER‐kinase axis in Prostate Cancer
In 2008, an estimated 186,320 new cases will occur in the US.Prostate cancer is the most frequently diagnosed cancer and the leading cause of cancer death in men with an estimated 28,660 deaths in 2008 alone.
American Cancer Society
AD-PCAndrogen-dependent
prostate cancer
PSA
PSA
AI-PCAndrogen-independent
prostate cancer
PSA
Activation of growth promoting signaling pathways:
BCL2 antiapoptotic pathwayProtein kinase A Phosphatidylinositol 3‐kinaseRas/Raf/MAPKReceptor tyrosine kinases
Activation of growth promoting signaling pathways:
BCL2 antiapoptotic pathwayProtein kinase A Phosphatidylinositol 3‐kinaseRas/Raf/MAPK
Receptor tyrosine kinases• Activating HER2/HER3 dimerization supports prostate cancer progression.
HRG
HER2
P
HER3
P
Cell deathCell death
HRG
HER2 HER3
No Cell deathNo Cell death
2C4
Cell membrane
HER1 HER2 HER3 HER4
A: Bar Graph
Sample Replicates
Rel
ativ
e lu
min
esce
nce
light
-out
put
0
50K
100K
150K200K
250K
300K
350K
400K
450K
500K
No treatment 2C4 HRG HRG+2C4
25nM HRG50nM HRG
0 5 10 15 20 25 30 35 40 45 50
HRGHRG+2C4
B: Scatter Plot Z-factor = 0.65
AI
AI
AD
Mechanism of HRG‐induced cell kill
What is the mechanism of HRG‐induced cell kill in LNCap cells?Why does it occur in the LNCap AD prostate cancer cell model and not in the isogenic AI models?
Starved HRG 2C4
Control 2C4
HRG2.5
2C4+HRG2.5
EGF4R1881
R1881+HRG2.5
Figure 3C: Representative cellular pictures with various treatments (Hoechst 33342-PI-stained cells).
Develop a highthroughput assay to effectively screen for compounds that rescue LNCap cells from HRG‐induced cell kill.
Prestwick Chemical Library1120 molecules dissolved in DMSO90% are marketed drugs
Biomol bioactive lipid library201 bioactive lipids
Biomol enzyme libraryKinase phosphatase inhibitors (80 known kinaseinhibitors and 33 known phosphatase inhibitors)
384‐well highthroughput format1200 cells/well are plated in RPMI/10%serum.10μM compound is added the next day followed by 10nM HRG. 24hrs later viable cells are quantified using the ATPlite 1step, single addition luminescence ATP detection Assay system. Percent viability of cells is calculated with respect to DMSO treated cells.Normalized data is uploaded in the CDD database to screen for hits.
DMSOcontrolHRG
High viability Low viability
HRG: average viability: 25.5 %
Add EGFR inhibitor
Prestwick compounds Rescuing Heregulin‐induced Prostate Cell Kill
Glucocorticoid steroid
C‐21 steroid hormone
Hormone precursor to aldosterone
Cardenolide
Corticosteroid
Topical corticosteroids
0
10
20
30
40
50
60
70
80
Control
2C4
HRG 2.5n
MHRG 25
nMHRG 2.
5+ 2C
4HRG 25
+ 2C4
EGF4EGF4+
2C4
R1881
R1881
+2C4
R1881
+HRG2.5
R1881
+ HRG25
Perc
ent P
I pos
itive
LN
CaP
cells
(P
erce
nt c
ellu
lar k
illin
g no
rmal
ized
to to
tal c
ell n
umbe
r)
AR amplifications and mutations
have been involved in AI prostate cancer.
HSPAR HSP AR
androgens
AR AR
AR ARnucleus
0
200
400
600
800
1000
1200
--------HRG(25)
+-+-+-+-2C4
++--++--HRG(2.5)++++----R1881(1)
Nor
mal
ized
Rel
ativ
e L
UC
Act
ivity
Z-factor = 0.2
PSA promoter TATA Luciferase
Develop a highthroughput luminescence assay to detect cell viability in prostate cancer cells and identify several compounds and categories of compounds namely steroids that prevent HRG‐induced cell kill.
Use compound screening to connect two pathways together, to better understand the biology of HER2/HER3 mediated cell kill in AD prostate cancer cells.
HSPAR HSP AR
androgens
AR AR
AR ARnucleus
HRG
HER2
P
HER3
P
Cell deathCell death
HSPAR HSP AR
androgens
AR AR
AR ARnucleus
HRG
HER2
P
HER3
P
Cell deathCell death
Identify molecules involved in connecting the HER2/HER3 and AR pathway by using siRNAand overexpression screens.Create several options to successfully inhibit AR in advanced prostate cancer patients.
Jack Altura, Talar Kechichian CSMC
Robert D. Damoiseaux MSSR UCLA
Barry A Bunin CDDKellan Gregory CDD
NIHProstate Cancer Foundation