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(1) Can we identify metabolites or metabolic pathways that are associated with breast cancer clinical parameters?. Alex-CIS-GCTOF MS w/ BinBase: 470 detected compounds 161 known metabolites, 309 without identified structure. grade2. grade1. Partial Least Square (multivariate stats).

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Results

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  1. (1) Can we identify metabolites or metabolic pathways that are associated with breast cancer clinical parameters? Alex-CIS-GCTOF MS w/ BinBase: 470 detected compounds 161 known metabolites, 309 without identified structure. grade2 grade1 Partial Least Square (multivariate stats) Results grade3 grade1 grade3 breast adipose grade2

  2. Grade n1  23 tumors show differential up-regulation inPentose Phosphate Pathway, nucleotides, amino acids, arachidonic acid (but not free fatty acids, gln) Results production of NADPH, ribose units production of DNA, RNA

  3. Grade n1  23 tumors show differential up-regulation inPentose Phosphate Pathway, nucleotides, amino acids, arachidonic acid (but not free fatty acids, gln) Amino acids Amino acids citrate glu b-ala n 1 2 3 grade n 1 2 3 grade Results malate lactate n 1 2 3 grade n 1 2 3 grade C20:4 2HOglutarate IDH1? n 1 2 3 grade n 1 2 3 grade

  4. Can we validate biomarkers in a fully independent study?Cohort 2 (113 patients) Results

  5. Matej Orešič et al. (subm.) Can we validate lipidomic biomarkers in a fully independent study?Cohort 2 (113 patients) Results

  6. Orešič et al. (subm) Can we validate lipidomic biomarkers in a fully independent study? Immunohistochemistry on tissue slides. Results

  7. Can we get biochemical maps of differential regulation for hormone receptor status? Methods • Up to 20% of the identified metabolites lack enzyme annotations. • Metabolic endpoint metabolites accumulate more than intermediates. ‘Comprehensive maps’ do not work.

  8. Can we get biochemical maps of differential regulation for hormone receptor status? Methods • Up to 20% of the identified metabolites lack enzyme annotations. • Metabolic endpoint metabolites accumulate more than intermediates. ‘Comprehensive maps’ do not work.

  9. Chemical and biochemical mapping of metabolomic results Methods

  10. Grade 1 tumors vs normal Results Red nodes: up-regulated in tumors at p<0.05, size ~ x-fold Blue nodes: down-regulated in tumors at p<0.05, size~x-fold Red edges: enzyme substrate/product in KEGGRpair DB Green edges:chemical similarity > 0.7

  11. Hormone receptor @ grade 3 single neg. ER+ PR+ HER2- % of patients Methods triple neg. ER- PR- HER2- Estrogen positive Estrogen negative

  12. Metabolic phenotype of triple negative tumorsPatients without Estrogen, Herceptin neu2, Progesteron receptor Results

  13. Hormone receptor @ grade 3 % of patients Methods triple neg. ER- PR- HER2- double neg. ER- PR- HER2+ Estrogen positive Estrogen negative

  14. Effect of HER2 status on metabolic phenotype of triple negative tumors Results

  15. Hormone receptor @ grade 2 double pos. % of patients ER+ PR+ HER2- Methods triple pos. ER+ PR+ HER2+ Estrogen positive Estrogen negative

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