Neli Ulrich, MS, PhD Huntsman Cancer Institute, Salt Lake City Using Genetics and Metabolomics to Advance Precision Prevention
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1 Neli Ulrich, MS, PhD Huntsman Cancer Institute, Salt Lake City Using Genetics and Metabolomics to Advance Precision Prevention February 3-5, 2016 Lansdowne Resort, Leesburg, VA
2 Three Highlights Aspirin precision prevention with genetics Aspirin discovery with metabolomics Colorectal cancer patients: Urinary biomarkers? Adipose tissue and metabolomics Integration of omics approaches
3 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: years post randomization HR 0.51 ( ) Among compliant patients Among long-term users (>5 years) All of the above HR 0.26 ( ) Flossman et al,. Lancet 2007
4 Aspirin use 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:
5 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
6 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
7 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
8 Interaction between FLAP SNP and NSAID use in risk of colorectal cancer p for interaction =0.038
9 Interaction between FLAP SNP and NSAID use in risk of colorectal cancer Ref p for interaction = ** Odds 0.6 Ratio No Regular, 0 Yes current use GG of NSAIDs These signals are robust CG/CC and replicate. When FLAP genotype can we take them to the clinic?
10 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
11 In te n s ity In te n s ity Aspirin reduces plasma 2-hydroxyglutarate 2-hydroxyglutarate 2-hydroxyglutarate P la c e b o A s p irin P la c e b o A s p ir in 0 1 * 1 2 * 2 U G T 1 A 6 g e n o ty p e ~30% reduction, p = (robust) 2-HG is a known driver of carcinogenesis, particularly of brain cancer (Losman et al. 2013) Liesenfeld et al. Ca Epi Biom Prev 2016;25(1):180-7
12 (R )-2 -H G fo r m e d [n m o l * m g - 1 * h - 1 ] Cell culture experiments suggest stereospecific 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) All cell lines 1.5 ** S-2-HG R-2-HG S-2-HG DLD1 Control ASS **: p < R-2-HG 0.5 Liesenfeld et al. Ca Epi Biom Prev 2016;25(1): s a lic y la te c o n c. [ lo g (n M ) ]
13 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)
14 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
15 ColoCare as a resource for novel scientific projects on cancer prognosis Examples: Genomics Metagenomics Metabolomics Epigenomics Proteomics Other biomarkers Quality of Life Nutrition Physical activity Lifestyle factors GAME-ON, Oncoarray, gene expression, mutations Next Gen Sequencing of the gut microbiome Metabolic profiling of blood, adipose tissue, urine Tumor methylation and mirna Protein Array Prostaglandins, 25(OH)-vitamin D, 8-oxo-dG, Physical and emotional functioning and other QoL Dietary patterns and supplements State of the art physical activity (accelerometry) NSAIDs, smoking, etc.
16 The ColoCare Study Results to date Urine metabolomics Pre-surgery vs. post-surgery: metabolites presumably from microbial origin were lower Aromatic compounds gut microbiota associated Several amino acids and downstream products of tryptophan metabolism were altered Dopamine levels lower in patients pre-surgery Metabolite map for the therapeutic effects on colorectal cancer patients metabolomes. Metabolites were mapped using the NIH WCMC MetaMapR ( Liesenfeld et al Metabolomics 11(4)
17 The ColoCare Study Results to date Urine metabolomics PLS-DA model enabled good separation of groups (pre-surgery vs. post-surgery) 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 Metabolomics 11(4)
18 Biology of adipose tissue More than a storage organ Composed of: Adipocytes Macrophages Fibroblasts Endothelial cells Ouchi, Nature Reviews, 2011 Fully functioning endocrine organ that produces and secretes adipokines, cytokines, hormones
19 The ColoCare Study Adipose tissue metabolomics in colorectal cancer patients n=59 CRC patients (stage I to IV) SAT VAT 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
20 Gene Expression Analysis: VAT / SAT Principal Component Analysis VAT SAT (n = 83, paired)
21 The ColoCare Study Adipose tissue metabolomics & transcriptomics illustrates inflammatory character of VAT 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:
22 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:
23 ColoCare adipose tissue metabolomics suggests biomarkers to be investigated further 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 Liesenfeld, Grapov, Fahrmann et al. Am J Clin Nutr. 2015;102:
24 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
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