In silico Genetic Network Models for
Pre-clinical Drug Prioritization
Jianghui Xiong 熊江辉
Laserxiong@gmail.com
http://cn.li...
Network pharmacology
The information to deliver
• Network could be drug target
• Jianghui Xiong etc., Pre-clinical drug prioritization via prog...
Oncology Drug Development
One of most challenging scientific problems
What’s wrong with our cancer models? NATURE REVIEWS ...
The current models used for pre-clinical drug testing Do NOT
accurately predict how new treatments will act in clinical tr...
Hypothesis
– Considering gene networks associated with cancer
outcome in heterogeneous patient populations
– The difficult...
SOD (Synergistic Outcome Determination)
Bad Outcome
Gene Pair
Gene
A
Gene
B
Bad Outcome
Gene Pair
Gene
A
Gene
B
Good Outco...
SOD (Synergistic Outcome Determination)
vs Synthetic Lethality
Feature
compared SOD Synthetic Lethality
Phenotype Survival...
The pipeline
Protein Network
Pathway
Gene Ontology
miRNA Target Gene
Gene Module
Database
Prognostic Data
Inter-Module
Coo...
What is Gene Module?
And Why We use it instead of the single genes?
Gene Module:
a group of genes which
share similar func...
Gene Module Database
Protein
Network
Pathway
Gene
Ontology
miRNA
Target
Gene
Gene Module
Database
Chang H Y et al. PNAS 2005;102:3738-3743
a “wound response” gene
expression signature in predicting
breast cancer progress...
Gene Module
Database
Module-module cooperation network
K
1
2
...
For each gene
Query
Module
A
Gene K
SIN Gene
list
Gene2
S...
Inter-Module Cooperation Network (IMCN)
for lung cancer suggests that the network robustness highly
dependent on gatekeepe...
Characterization of the Inter-Module Cooperation Network (IMCN)
‘Gatekeeper’ modules for lung cancer (NSCLC)
3 Major
Biolo...
Contribution of various evidence sources
for gene module definition
Comparing genetic (somatic mutation) and epigenetic (DNA methylation)
aberration rate (in tumor vs. normal) of two types o...
Compound action on cells
NCI 60 in vitro Drug screen Project
Connectivity MAP
Use Perturbation Index (PI) to quantify
Drug action
Hypothesis
– To disrupt/perturb cancer network, the key to success is ...
Benchmarking for pre-clinical drug prioritizing
• Why test?
– Assess the potential application for prioritizing compounds ...
Bootstrapping-based assessment of Perturbation Index
on discriminating successful drugs from the candidate
Rank of drugs and agents in clinical development for lung
cancer according to their Perturbation Index
How to quantify synergistic effect of Drug
Combination?
Drug
A
Drug Perturbation
Gene list A
Drug
B
Drug Perturbation
Gene...
The Perturbation Index of
pair-wise combination of lung cancer agents
• Validity of Bortezomib-
Gemcitabine
– Notable surv...
Bortezomib-Gemcitabine Combination
Bortezomib
add a focused
perturbation
on key
gatekeeper
modules
Gemcitabine
baseline
pe...
Discussion (1)
As a preclinical in silico modeling tool
– Mirroring drug behavior on natural populations
– Cost-effectiven...
Discussion (2)
Strategy against cancer
• Gatekeeper modules as rate-limiting steps in therapeutic
treatment
 Drug metabol...
A new perspective to understand principle of drug combination in
Traditional Chinese Medicine ?
• 君 - King
• 臣 - Minister
...
Pre-clinical drug prioritization via prognosis-guided genetic interaction networks
Pre-clinical drug prioritization via prognosis-guided genetic interaction networks
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Pre-clinical drug prioritization via prognosis-guided genetic interaction networks

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Pre-clinical drug prioritization via prognosis-guided genetic interaction networks

  1. 1. In silico Genetic Network Models for Pre-clinical Drug Prioritization Jianghui Xiong 熊江辉 Laserxiong@gmail.com http://cn.linkedin.com/in/jianghuixiong http://www.researchgate.net/profile/JIANGHUI_XIONG/ October 23, 2010 Section 2-1: Genomics, Proteomics and Metabolomics in Drug Discovery and Target Validation Click to get the full text paper (PLoS ONE): http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0013937
  2. 2. Network pharmacology
  3. 3. The information to deliver • Network could be drug target • Jianghui Xiong etc., Pre-clinical drug prioritization via prognosis- guided genetic interaction networks. PloS ONE 2010 • “For more than a decade, scientists in systems biology have promised that real breakthrough in genetic medicine will come when we stop mapping individual genes to phenotypes and instead start looking at interacting networks. Yet, not much has happened. The field is still struggling to define relevant networks and to interpret data in terms of those networks. The paper by Xiong et al adds considerably to the progress of network-based genetic medicine. It is highly relevant, original and interesting.”
  4. 4. Oncology Drug Development One of most challenging scientific problems What’s wrong with our cancer models? NATURE REVIEWS DRUG DISCOVERY, 2005
  5. 5. The current models used for pre-clinical drug testing Do NOT accurately predict how new treatments will act in clinical trials – Heterogeneity in patient populations – Unpredictable physiology What’s wrong with our cancer models? NATURE REVIEWS DRUG DISCOVERY, 2005 What’s wrong with our Disease Models Drug Discov Today Dis Models, 2008 ?
  6. 6. Hypothesis – Considering gene networks associated with cancer outcome in heterogeneous patient populations – The difficulty of identify effective cancer cures (as evidenced by drug resistance) may be a consequence of the robustness of this network – Network (robustness) as drug target Pre-clinical in silico Cancer Models for Drug action study – Incorporating heterogeneity and in vivo physiology information, which MISSING in pre-clinical cancer models Our proposal 1 2
  7. 7. SOD (Synergistic Outcome Determination) Bad Outcome Gene Pair Gene A Gene B Bad Outcome Gene Pair Gene A Gene B Good Outcome Gene Pair Gene A Gene B Good Outcome Gene Pair Gene A Gene B Synergistically Infered Nexus ( SIN ) 𝑆𝑦𝑛 𝐺1, 𝐺2; 𝐶 = 𝐼 𝐺1, 𝐺2; 𝐶 − 𝐼 𝐺1; 𝐶 + 𝐼(𝐺2; 𝐶) 𝐼 𝑋; 𝑌 = 𝑝 𝑥, 𝑦 log2 𝑝(𝑥, 𝑦) 𝑝 𝑥 𝑝(𝑦) 𝑦𝑥
  8. 8. SOD (Synergistic Outcome Determination) vs Synthetic Lethality Feature compared SOD Synthetic Lethality Phenotype Survival outcome of individual patient Cell death/growth Level Individual Cell Data Accessible Human population (via computation) Yeast (SGA); Human cell lines; Human population
  9. 9. The pipeline Protein Network Pathway Gene Ontology miRNA Target Gene Gene Module Database Prognostic Data Inter-Module Cooperation Network 1 Compound in vitro screen data NCI 60 panel gene Expression data Gene Signature for Compound Sensitivity Compound route of action Analysis Perturbation Index (PI) Benchmarking/Validation Drug Combination Simulation 2 3
  10. 10. What is Gene Module? And Why We use it instead of the single genes? Gene Module: a group of genes which share similar function a b c d e f Gene Module 1 x A single gene …… Gene Module 2 Gene Module 3 Gene Module 4 Gene Module n …… Gene Module: robust/reproducible features rather than single genes
  11. 11. Gene Module Database Protein Network Pathway Gene Ontology miRNA Target Gene Gene Module Database
  12. 12. Chang H Y et al. PNAS 2005;102:3738-3743 a “wound response” gene expression signature in predicting breast cancer progression • Natural population - Heterogeneity • Tumor tissue - Microenvironment reflection • Final point phenotype - Survival time • Comprehensive genomic characterization • Large Data Set Prognosis Data -- data associated gene expression with patients’ prognosis Benefit of Prognosis DataPrognosis Data Instance
  13. 13. Gene Module Database Module-module cooperation network K 1 2 ... For each gene Query Module A Gene K SIN Gene list Gene2 SIN Gene list WholeGeneSet(Mgenes) Gene-Gene SIN analysis Candidate Module B Candidate Module C Gene 1 SIN Gene list SIN A Query Module A SIN A Candidate Module C SIN A Cooperation Module C SIN A Candidate Module B SIN A Query Module A Cooperation Module B Pool Together
  14. 14. Inter-Module Cooperation Network (IMCN) for lung cancer suggests that the network robustness highly dependent on gatekeeper modules Gatekeeper Module Checkpoint Module
  15. 15. Characterization of the Inter-Module Cooperation Network (IMCN) ‘Gatekeeper’ modules for lung cancer (NSCLC) 3 Major Biological Theme
  16. 16. Contribution of various evidence sources for gene module definition
  17. 17. Comparing genetic (somatic mutation) and epigenetic (DNA methylation) aberration rate (in tumor vs. normal) of two types of modules Top 10% or 20% of genes which highly used (i.e. one gene involved in multiple gene modules) as representative of each types of modules
  18. 18. Compound action on cells NCI 60 in vitro Drug screen Project Connectivity MAP
  19. 19. Use Perturbation Index (PI) to quantify Drug action Hypothesis – To disrupt/perturb cancer network, the key to success is to simultaneously perturbs the corresponding gatekeeper modules with the checkpoint modules • Hi -- the number of hits by compound c • Li -- the active links ( i.e. links in which both source node and target node are matched by compound c) • N -- the number of gatekeeper modules
  20. 20. Benchmarking for pre-clinical drug prioritizing • Why test? – Assess the potential application for prioritizing compounds for clinical trials, based on the information available in pre-clinical stage • ‘Standard Agent Database’ – Originally created by Boyd [29] and ultimately finalized by the NCI – Compounds which have been submitted to the FDA for review as a New Drug Application – OR compounds that have reached a particular high stage of interest at the NCI • Successful drug list - FDA approved and routinely used drugs • Candidate list - the remainder • Test what? – Whether we could statistically discriminate between these two compound lists using the perturbation index
  21. 21. Bootstrapping-based assessment of Perturbation Index on discriminating successful drugs from the candidate
  22. 22. Rank of drugs and agents in clinical development for lung cancer according to their Perturbation Index
  23. 23. How to quantify synergistic effect of Drug Combination? Drug A Drug Perturbation Gene list A Drug B Drug Perturbation Gene list B Drug A Drug Perturbation Gene list AB Drug B Pool Together (Union) PI Analysis
  24. 24. The Perturbation Index of pair-wise combination of lung cancer agents • Validity of Bortezomib- Gemcitabine – Notable survival benefits in lung cancer patients using a Bortezomib + gemcitabine/carboplatin combination as first-line treatment (phase II clinical trial reported) • Davies, A.M. et al. J Thorac Oncol 4, 87-92 (2009) • Validity of Bortezomib-Paclitaxel – In an RNA interference (RNAi)-based synthetic lethal screen for seeking paclitaxel chemosensitizer genes in human NSCLC cell line, proteasome is the most enriched gene group • Whitehurst, A.W. et al. Nature 446, 815-819 (2007)
  25. 25. Bortezomib-Gemcitabine Combination Bortezomib add a focused perturbation on key gatekeeper modules Gemcitabine baseline perturbation Gemcitabine
  26. 26. Discussion (1) As a preclinical in silico modeling tool – Mirroring drug behavior on natural populations – Cost-effectiveness – Easy to integrate drug action mechanisms/patterns
  27. 27. Discussion (2) Strategy against cancer • Gatekeeper modules as rate-limiting steps in therapeutic treatment  Drug metabolism and accessibility  Microenvironment  immune system modulation • Epigenetic plasticity on gatekeeper modules could exploited by tumor for attaining resistance to treatment – Drug accessibility <- Multi Drug Resistance – Microenvironment <- Inflammatory – Immune modulation <- Complement activation • Battle against cancer • know the history of tumorigenesis <etiology> • know future survival strategy of tumor under therapeutic interventions • Systems biology modeling could provide prediction of the tumor survival strategy Etiology-based strategy Prediction-based strategy
  28. 28. A new perspective to understand principle of drug combination in Traditional Chinese Medicine ? • 君 - King • 臣 - Minister • 佐 - Assistant • 使 - Ambassador The Inter-Module Network Different Roles of the Gene Modules & their cooperation effects

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