neli ulrich, ms, phd huntsman cancer institute, salt lake...
TRANSCRIPT
February 3-5, 2016 | Lansdowne Resort, Leesburg, VA
Neli Ulrich, MS, PhD
Huntsman Cancer Institute,
Salt Lake City
“Using Genetics and Metabolomics
to Advance Precision Prevention”
Three Highlights
Aspirin precision prevention with genetics
Aspirin discovery with metabolomics
Colorectal cancer patients:
• Urinary biomarkers?
• Adipose tissue and metabolomics
Integration of –omics approaches
Flossman et al,. Lancet 2007
• Long-term follow up of British
Doctors Aspirin Trial and UK-TIA
Aspirin Trial
300, 500 or 1200 mg aspirin vs
control
• No risk reduction within first 5 years
• Risk reduction strongest:
10-14 years post randomization
• HR 0.51 (0.29-0.90)
Among compliant patients
Among long-term users (>5 years)
All of the above
• HR 0.26 (0.21-0.56)
Should we use aspirin for cancer
prevention?
• Aspirin is potent in cancer chemoprevention• However, GI symptoms, including in some cases serious
bleeding is a concern for the broad scale implementation
• Risk-benefit balance will differ by population Healthy, young individuals versus those with family
history, predisposing inflammatory or high-risk conditions, older, prior polyps, higher body mass index…
• Is pharmacogenetic tailoring possible?
• Personalized prevention:
Aspirin use
Benefits of pharmacogenetic tailoring
Being able to advice on aspirin, based on genetic predisposition
results in:
Risk minimization
Reduced concern among patients and treating clinicians
Reduced liability
Greater likelihood of response
Approaches to aspirin pharmacogenetics
Relevant targets:
Target pathways
• Efficacy and toxicity (prostaglandin synthesis,
leukotriene synthesis, thromboxane synthase)
• Metabolism and excretion (UGT, CYP2C9, MRP4-
for non aspirin NSAIDs)
Genome-wide association studies
Pharmacokinetic studies
All approaches are needed and complementary
>20 publications: Ulrich, Poole, Kulmacz et al
NSAID Pharmacogenetics
Meta-analysis & pooled analysis:colon & rectal cancer and adenoma,
NSAIDs and aspirin
• 4 individual study populations**
~10,000 individuals
• 2-stage approach based on
candidate pathways
Question: who benefits from NSAIDs
and who doesn’t?
** from Slattery, Potter, WHI, CCFR
Interaction between FLAP SNP and
NSAID use in risk of colorectal cancer
p for interaction
=0.038
Yes
No
0
0.2
0.4
0.6
0.8
1
1.2
GGCG/CC
Interaction between FLAP SNP and
NSAID use in risk of colorectal cancer
Ref
p for interaction
=0.038
Regular,
current use
of NSAIDs
FLAP genotype
0.97
1.02
0.68**Odds
Ratio
These signals are robust and replicate. When
can we take them to the clinic?
Discovery of new pathways: Metabolomics
in a randomized controlled trial of aspirin
• Randomized controlled trial
ABC Study (Johanna Lampe)
n=55
• Crossover study design
• 325mg ASS/d for 60d
• 3 month wash-out
• Reverse intervention
Each participant serves as their own control
Liesenfeld et al. Ca Epi Biom Prev 2016;25(1):180-7
Aspirin reduces
plasma 2-hydroxyglutarate
• ~30% reduction, p = 0.005 (robust)
• 2-HG is a known driver of carcinogenesis, particularly of brain
cancer (Losman et al. 2013)
Inte
ns
ity
Pla
ceb
o
Asp
irin
0
2 .01 04
4 .01 04
6 .01 04
8 .01 04
1 .01 05
U G T 1 A 6 g e n o ty p e
Inte
ns
ity
1*1
2*2
0
2 .01 04
4 .01 04
6 .01 04
8 .01 04
1 .01 05 P la c e b o
A s p ir in
2-hydroxyglutarate 2-hydroxyglutarate
Liesenfeld et al. Ca Epi Biom Prev 2016;25(1):180-7
Cell culture experiments suggest stereo-
specific reduction of 2-hydroxyglutarate with aspirin
• 500 µM aspirin (24 h):
reduction of (R)-2-HG in
6 of 8 colorectal cancer
cell lines;
Reduction: Ø = 20%,
p<0.01; range: 10 – 40%
• Effects achievable at
physiologic concentrations
• Salicylate inhibits the
HOT reaction
(R-2-HG formation)
Control ASS **: p < 0.01
All cell lines
S-2
-HG
R-2
-HG
0.0
0.5
1.0
1.5 **DLD1
S-2
-HG
R-2
-HG
0.0
0.5
1.0
1.5
s a lic y la te c o n c . [ lo g (n M ) ]
(R)-
2-H
G f
orm
ed
[nm
ol
* m
g-1 *
h-1]
0 2 4 6
0 .0
0 .5
1 .0
1 .5
2 .0
Liesenfeld et al. Ca Epi Biom Prev 2016;25(1):180-7
Aspirin pharmacometabolomics
• Resulted in the discovery of a potential new biologic
mechanism of aspirin in cancer chemoprevention
2-hydroxyglutarate is a known oncometabolite
• Confirmation in vitro and mechanism (HOT
inhibition)
ColoCare Patient Cohort
International Consortium Cohort Study
• Fred Hutchinson Cancer Research Center
• Moffitt Cancer Center
• Huntsman Cancer Institute
• NCT Heidelberg
Inclusion of patients
• With colorectal carcinoma stages I-IV
• n = 5000 in 5 years
Inclusion criteria:
• Women and men from the age of 18
• Newly diagnosed CRC of all stages
ColoCare as a resource
for novel scientific projects on cancer prognosisExamples:
Genomics GAME-ON, Oncoarray, gene expression, mutations
Metagenomics Next Gen Sequencing of the gut microbiome
Metabolomics Metabolic profiling of blood, adipose tissue, urine
Epigenomics Tumor methylation and miRNA
Proteomics Protein Array
Other biomarkers Prostaglandins, 25(OH)-vitamin D, 8-oxo-dG, …
Quality of Life Physical and emotional functioning and other QoL
Nutrition Dietary patterns and supplements
Physical activity State of the art physical activity (accelerometry)
Lifestyle factors NSAIDs, smoking, etc.
The ColoCare Study
Results to date –
Urine metabolomics
Metabolite map for the therapeutic effects on
colorectal cancer patients’ metabolomes.
Metabolites were mapped using the NIH WCMC
MetaMapR (https://github.com/dgrapov/MetaMapR/)
Liesenfeld et al. 2015. Metabolomics 11(4). 998-1012
Aromatic
compounds
gut microbiota
associated
• Pre-surgery vs. post-surgery:
metabolites presumably from
microbial origin were lower
• Several amino acids and
downstream products of
tryptophan metabolism were
altered
• Dopamine levels lower in
patients pre-surgery
PLS-DA model enabled good separation of groups (pre-surgery
vs. post-surgery)
The ColoCare Study
Results to date – Urine metabolomics
Receiver operator characteristic (ROC) curve and score plot from a
partial least squares-discriminant analysis (PLS-DA) model
containing 20 metabolites for all patients (red line) and a subset of
fasted patients (blue line)
Liesenfeld et al. 2015. Metabolomics 11(4). 998-1012
More than a storage organ
Composed of:
• Adipocytes
• Macrophages
• Fibroblasts
• Endothelial cells
Fully functioning endocrine organ that produces and secretes
adipokines, cytokines, hormones
Biology of adipose tissue
Ouchi, Nature Reviews, 2011
The ColoCare Study
Adipose tissue metabolomics in colorectal cancer patients
SAT
VAT
n=59 CRC patients
(stage I to IV)
LC-qTOF lipidome
GC-TOF primary metabolites
Microarray transcriptome
Pilot Study with NIH West Coast Metabolomics Center (O. Fiehn)
Goal – to understand metabolomics and transcriptomic differences
between the visceral and subcutaneous adipose tissue
Gene Expression Analysis: VAT / SAT
VAT
SAT
(n = 83, paired)
Principal Component Analysis
VAT
inflammatory
profile:
• Arachidonic acid
higher compared to
SAT
• Increased liberation
of arachidonic acid
through PLA2
• Based on gene
expression:
metabolic flux into
prostaglandins
anticipated
Liesenfeld, Grapov, Fahrmann et al. Am J Clin Nutr. 2015;102:433-43.
The ColoCare Study
Adipose tissue metabolomics & transcriptomics
illustrates inflammatory character of VAT
Adipose tissue metabolomics
– ratio of triglycerides to membrane lipids:
a marker for adipocyte size
Liesenfeld, Grapov, Fahrmann et al. Am J Clin Nutr. 2015;102:433-43.
• 9 unknown metabolites showed a linear trend of
increasing/decreasing concentration with increasing tumor stage
(raw p < 0.05, Kendall’s τ > 0.25 or < -0.25) when comparing
stages I to IV
• None of which remained significant after FDR correction…
ColoCare adipose tissue metabolomics suggests
biomarkers to be investigated further
Liesenfeld, Grapov, Fahrmann et al. Am J Clin Nutr. 2015;102:433-43.
Summary and outlook into the future
Precision prevention is important to translate chemoprevention
to the clinic
Metabolomics advances our understanding of prevention
• Discovery of new pathways
• Biomarkers for exposures
Power of integrative analysis