Post on 03-Jun-2015
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Repositioning Old Drugs For New Indications Using Computational Approaches
Yannick Pouliot, PhDKhatri Laboratory
4/7/2014
Discovering New Drugs Is Getting Much Harder
One Approach: Finding Unrecognized Indications For Existing Drugs
• Most drugs have more than one activity beyond their approved indication(s)– usually unrecognized– example: thalidomide now approved for treatment of myeloma
• Focus of existing drugs because already FDA-approved…– “known” safety profile– increasingly off-patent
• But, how to identify unrecognized indications?– “wet lab” approaches– computational approaches
Target: Inflammatory Bowel Diseases
Approach Is A Sausage Machine:
Inflammatory Bowel Diseases - Overview
• IBD = Ulcerative colitis, Crohn’s disease• Inflammation of intestinal tract• Chronic, progressive, episodic
– North America: >1M patients
• High heritability• No cure; poor treatment options
– surgery– drugs with serious adverse effects (e.g., corticosteroids)
Players In Computational Drug Repositioning
functional genomics data repository with >1M samples
integration of medical terminologies, classification, and coding standards
free relational database server; dominant in life sciences
free statistical analysis and plotting language; dominant in life sciences
WARNING
If You Go Fishing And Don’t Know What Fish Look Like, You Will Definitely Find Something.
It Just Won’t Be A Fish.
The False Discovery Rate: A Key Concept Of Data Mining
“The q-value of a test measures the proportion of false positives incurred … when that particular test is called significant” Dabney, A., Storey, J. & Warnes, G., R Package "qvalue". (2011).
• When evaluating many significance test results, you must have an a priori expectation of what you will consider to be a “true” result across many tests, as well as for individual significance tests
• A significance test whose value results in rejecting the null hypothesis can still be a false positive because “too many” tests were performed.
• Controlled by multiple hypothesis testing, and the resulting q-value threshold.• Relies on “bootstrapping” permutation to generate a distribution of scores based
on observed values
Hypothesis
Drugs that increase gene expression in the reverse direction to what is observed in IBD vs. normal tissues should decrease symptoms
Assessment Method: 1. Characterize the effect of drugs on human gene transcript
levels2. Characterize the difference in human gene transcript levels
between disease and normal tissue pairs3. Find drugs that induce the reciprocal signature observed in
disease
Source Data
Disease data• Assemble MySQL database of 176 gene expression microarray
datasets from GEO– diseased vs. normal tissue pairs– 100 specific diseases manually reviewed and encoded using UMLS
identifiers
Drug data (“Connectivity Map”)Gene expression microarray profiles of effects of 164 drugs in:
– breast cancer: MCF7 epithelial cell line – prostate cancer: PC3 epithelial cell line– leukemia: HL60 – melanoma: SKMEL5
Finding Drug Candidates Using Rank-Ordered, Drug-Disease Anti-Correlation Scores
1. Compute an anti-similarity score for each drug-disease pairs (anti-correlation score)
2. Compute P-values of anti-correlation scores (significance testing) using distance between observed score vs. scores of 100 randomly-generated comparisons
3. Retain correlation that have FDR values better than 0.05
Selected Drug: Topiramate (Candidate #2)
• Anticonvulsant drug whose activity “may be due to a combination of potential mechanisms: Blocks neuronal voltage-dependent sodium channels, enhances GABA(A) activity, antagonizes AMPA/kainate glutamate receptors, and weakly inhibits carbonic anhydrase” -- UpToDate
• Off-patent since 2009!
Validation In Rat Model of IBD - 1
• Sprague-Dawley rats treated with TNBS to induce colitis
• Video endoscopy at days 3 and 7 post-induction
• Readout is fraction of animals with diarrhea
• Result: treatment with topiramate decreases diarrhea (one-way ANOVA p<0.005)
pos control
topiramate
prednisolone
neg control
Validation In Rat Model of IBD - 2
Evaluation of Eight Randomly-Selected Counter-Expressed Genes
qPCRmicroarrayEvaluation of Eight Randomly-Selected Counter-Expressed
Genes
Since Then…
• Upcoming case report to be published of topiramate working in a patient refractory to steroids.
Summary
• Proof of principle that drugs that affect gene transcript levels in an anti-correlated manner to the normal/disease pattern can ameliorate symptoms
• Everything from public domain– data– algorithm– software
• In principle, applicable to any domain where data exist