Census of the Apoptosis Pathway

1. Census of the Apoptosis Pathway
(and Other Uses of Pathway Analysis)
Phil Lorenzi, Ph.D.
Co-Director, The Proteomics and Metabolomics Core Facility
Dept. of Bioinformatics & Computational Biology
The University of Texas MD Anderson Cancer Center

2. Disclosures
• My attendance at this symposium was supported by Elsevier

3. The Drug Discovery & Development Process
Hypothesis Generation
Target Identification
Target Validation Lead Optimization
Pharmacodynamics
Pharmacokinetics
Clinical Trials
In Vivo Animal Studies
IND
Application NDA
Chemical Profiling Data
Database Construction
Exploration
In Vitro Absorption
and Metabolism
Discovery Preclinical
Toxicology
Old View:
Pharmacological Profiling Data Phase I: Safety in Healthy Subjects
Phase II: Efficacy in Patients
Phase III: Large-scale Trial in Patients
“omics”
Mechanism of Action Delivery
Biological Profiling Data
Drug Combinations
Small Molecule Screens
Technology and Information
New View:

4. Systems Pharmacology of L-Asparaginase (2005)
L-asparaginase (drug)
N
Q
ASNS
Ø
(total [D])
E
N
Q + D + ATP
?
Ø
SP2
Ara-C
ATF-2
ATF-4
ATF-3
NSRE-2NSRE-1
CHOP
AARE
RA
?
?
ASNS
ATF-6
5-aza-2’-deoxycytidine
diazo-4-oxo-L-norvaline
6-Diazo-5-oxo-L-norleucine &/or 8-N3-ATP
DMT
P
ATF-5
CHOP
•
AAREC/EBP-β
C/EBP-β
GC-IIIGC-IIGC-I
SP1
SP3
P
CD95 = FAS
FAS-L
Caspase-8
Caspase-3
↓Cell Volume
FADD
APOPTOSIS
D
Ø (< 0.4 mM)
GADD45
GRP78
ASK1
JNK
QRS
p53
p38
Ca2+
CAM kinase 2PKC
NOS
NFκB
MAPK
NO
ROS
Calpain
Bid
Q (Ø)
GSHBcl-2
cFLIP
HSP70
Ø
Ø
cPLA2
ERK
p21
p27
H2O
PLC
RAF
MEK
Proliferation
GCN2
P
EIF2A
↑Metabolism

5. The Autophagy Pathway (2014)
Lorenzi et al., Autophagy, 2014

6. Outline
1. Comparison of pathway analysis strategies
• introduction
• the autophagy pathway
• the apoptosis pathway
2. Pathway analysis for target validation (pharmacovigilance)
• COX2 inhibitors (post-market failure)
• AKT inhibitors (many years of failed clinical trials)
• EGFR inhibitors (already approved)
• MEK inhibitors (already approved)
• RANKL inhibitor (already approved)
• PARP inhibitors (already approved)
• GLS inhibitors (in clinical trials)

7. Pathway Analysis
• Growing demand in biological sciences to perform pathway
analysis on “big data”
• Common Goals:
– build pathway maps
– obtain insight not provided by specific gene/protein/metabolite-level
analyses
– drug development: because cancer cells acquire resistance to targeting
single nodes, targeting pathways may improve outcome

8. Popular Pathway Analysis Options
• Ingenuity Pathway Analysis (Ingenuity Systems)
• MetaCore (Thomson Reuters GeneGo)
– MetaDrug
• GeneSpring (Agilent)
– MPP
– NGS
• DAVID (open source)
• KEGG (http://www.kegg.jp)
• Roche Pathways (http://biochemical-pathways.com/#/map/1)
• Biocyc (http://biocyc.org)
• Pathway Studio (Elsevier)
– ChemEffect
– DiseaseFx

9. Pathway Studio - Introduction
• MedScan
• Mammalian cartridge
• ChemEffect cartridge
• DiseaseFx cartridge
Database

10. The Autophagy Pathway (2014)
Lorenzi et al., Autophagy, 2014

11. Construction of the Autophagy Pathway

12. Integrated Analysis of the Autophagy Pathway
1: siRNA Screen 1
2: siRNA Screen 2
3: siRNA Screen 3
4: siRNA Screen 4
5: IPA
6: MetaCore
7: Pathway Studio (raw)
8: Pathway Studio
(curated)
No single
method enables
comprehensive
pathway
interrogation
Lorenzi et al., Autophagy, 2014

13. Integration of Proteomic Data
No single method enables comprehensive pathway interrogation
Behrends et al. Nature 466:68 (2010)

14. Quality Assessment – How Accurate is PS?
• False positives
– manual curation of all extracted sentences indicated 1181/6215 (19%) of
the relations were incorrect (false positives)
• reduced to ~0% by manual curation
– Example: “The ability of the excess Atg4B mutant to inhibit autophagy...”
• Change direction of regulation from NEGATIVE to POSITIVE
• False negatives
– Example: “We show that ATF4 and LC3B play a critical role in activating
autophagy and protecting cells from Bortezomib-induced cell death.”
• Change direction of regulation from UNKNOWN to POSITIVE

15. Integrated Analysis of the Autophagy Pathway
1: siRNA Screen 1
2: siRNA Screen 2
3: siRNA Screen 3
4: siRNA Screen 4
5: IPA
6: MetaCore
7: Pathway Studio (raw)
8: Pathway Studio
(curated)
Lorenzi et al., Autophagy, 2014

16. Key Question
• Are these conclusions generalizable?
– Examine additional biological pathways to assess whether:
• siRNA screening limitations persist
• pathway analysis outperforms experimental approaches

17. Integrated Analysis of the Apoptosis Pathway
1: siRNA screen
2: siRNA screen
3: ORFeome screen
4: siRNA/miRNA screen
5: shRNA screen
6: siRNA screen
7: shRNA screen
The previous
conclusions are
generalizable
8: siRNA screen
9: siRNA screen
10: siRNA screen
11: siRNA screen
12: siRNA screen
13: IPA
14: Pathway Studio (raw)
2894
3487
484
Lorenzi et al., unpublished

18. Deriving Novel Therapeutic Strategies from
Pathway Analysis
• Clinical insight
– Temsirolimus (MTOR inhibitor/autophagy stimulator) – why is there not a
clear clinical response?
• Answer: induces mitophagy, which degrades mitochondrial proteins
(e.g., RIPK1, RIPK3) that promote cell death
• Our proposal
– Combination of an autophagy inhibitor + autophagy stimulator
• e.g., hydroxychloroquin (HCQ) + temsirolimus (TEM; rapamycin analog)
• Hypothesized outcome: inhibition of mitophagy (by HCQ) would
preserve death-promoting mitochondrial proteins that are activated in
response to the autophagy stimulator (TEM)

19. Deriving Novel Therapeutic Strategies from
Pathway Analysis

20. Outline
1. Comparison of pathway analysis strategies
• introduction
• the autophagy pathway
• the apoptosis pathway
2. Pathway analysis for target validation (pharmacovigilance)
• COX2 inhibitors (post-market failure)
• AKT inhibitors (many years of failed clinical trials)
• EGFR inhibitors (already approved)
• MEK inhibitors (already approved)
• RANKL inhibitor (already approved)
• PARP inhibitors (already approved)
• GLS inhibitors (in clinical trials)

21. Vignette: COX2 Inhibitors, Vioxx
• Vioxx/rofecoxib was a COX2 inhibitor and NSAID developed by
Merck that received FDA approval in 1999 but was removed in
2004 due to concerns about heart attack and stroke.
• Could text mining / literature searching have predicted the
disaster?
• Detective work using Pathway Studio:

22. Vignette: Vioxx
1999: “The question whether the suppression of COX2 gene expression is fully or
partially responsible for ADR-induced selective cardiovascular toxicity is still open.”

23. Vignette: AKT Inhibitors
• AKT activation is among the most frequently observed genetic
alterations in cancer, yet no AKT inhibitors have been approved
for cancer treatment. Why?
• Hypothesis generation using Pathway Studio:

24. Vignette: AKT Inhibitors
!

25. Vignette: EGFR Inhibitors
• Approvals:
– Iressa/gefitinib (AstraZeneca, Teva); non-small cell lung cancer (NSCLC)
– Erbitux/cetuximab (Bristol-Myers Squibb); KRAS-WT colon cancer
– Tarceva/erlotinib (Astellas, Genentech, OSI, Roche); metastatic, EGFR-
positive non-small cell lung cancer (NSCLC)
– Gilotrif/afatinib (Boehringer-Ingelheim); metastatic, non-small cell lung
cancer (NSCLC)
– Vectibix/panitumumab (Abgenix, Amgen); EGFR-positive colon cancer
• Pathway Studio:
– Are text mining results consistent with approval of EGFR inhibitors for
clinical use?

26. Vignette: EGFR Inhibitors
No serious concerns

27. Vignette: MEK Inhibitors
• Approval:
– 2013: Mekinist/trametinib (GSK); MEK1 and MEK2 co-inhibitor; metastatic
melanoma with BRAF V600 mutations (V600E or V600K)
• Pathway Studio:
– Are text mining results consistent with approval of MEK inhibitors for
clinical use?

28. Vignette: MEK Inhibitors
No serious concerns

29. Vignette: RANKL Inhibitors
• Approvals:
– 2013: Xgeva/denosumab (Amgen); mAb; giant cell tumor of bone
• Pathway Studio:
– Are text mining results consistent with approval of RANKL inhibitors for
clinical use?

30. Vignette: RANKL Inhibitors
No serious concerns

31. Vignette: PARP1 Inhibitors
• First agent approved (2014); many others in development
• Pathway Studio:
– Are text mining results consistent with approval of PARP1 inhibitors for
clinical use?

32. Vignette: PARP Inhibitors
!
!
!
!
!
!
!
!
!
!
!
!
!
!

33. Vignette: GLS Inhibitors
• In clinical development now
• Pathway Studio:
– Are text mining results consistent with approval of GLS inhibitors for
clinical use?

34. Vignette: GLS Inhibitors
No serious concerns

35. Doing Your Part for the Future of Text Mining
• Facilitate accurate text-mining of your own publications
– Remember: regulation has direction
• not good writing: “Protein X regulates Protein Y.”
• good writing: “Protein X positively regulates Protein Y.”

36. Our Team
David Hawke
Wai Kin Chan
Phil Lorenzi
John Weinstein Thomas Horvath
Michael Pontikos
Bih-Fang Pan
Ron Bouchard
Daniel Du
Yulun Chiu
Bo Peng
Lin Tan

37. Acknowledgements and Collaborators
John Weinstein Gordon Mills David Hawke
Wai Kin Chan
Tom Horvath
Lin Tan
Leona Martin
Michael Pontikos
Bih-Fang Pan
Yiling Lu
Tracy Guo
Jennifer Dennison
Pradeep Raghavan
Susan Rempe
David Rogers
Juan Vanegas
Sergei Sukharev
Andriy Anishkin
Yann Godfrin
Fabien Gay
Willy Berlier
Bo Peng
Daniel Du
Yulun Chiu
Jing Wang
Bradley Broom
Jiexin Zhang
Rehan Akbani
Shiyun Ling
Keith Baggerly
Marina Konopleva
Gautam Borthakur
Steve Kornblau
Ken Aldape
The Chapman Foundation
The Michael and Susan Dell Foundation
NCI grant CA14883 (TCGA GDAC)
NCI grant CA083639 (Ovarian SPORE)
CPRIT grant RP130397
MD Anderson Cancer Center
Cliff Stephan
David Brunell
Peter Davies
+_
+_
Bill Reinhold
Natasha Caplen
Yves Pommier
Sudhir Varma
Chris Beecher
Felice de Jong
MDACC
MDACC
MDACC
MDACC
Sandia/U Maryland
Texas A&M
NCI
Erytech Pharma
Elsevier
IROA Technologies
Virginia Heatwole
Travis Vaught
Chris Cheadle
Jaqui Hodgkinson
Dave Arndt
ThermoFisher
Ken Miller
Bob Swaim
Jamie Humphries
Bernard Delanghe