1. Cancer Metabolite Profiling by GCxGC J.-M. D. Dimandja Spelman College

2. Cancer Research Strategies Curative Preventive

3. Bio-Metabolic Profiling Impulse Response Biological System First developed by Roger Williams and his associates in the 1940s (using paper chromatography) Examined over 200,000 samples from a variety of subjects (alcoholics, schizophrenics, etc.) and produced suggestive evidence of characteristic metabolic patterns associated with each of the groups. Williams, R.J., et al. “Individual Metabolic Patterns and Human Disease: An exploratory Study Utilizing Predominantly Paper Chromatographic Methods. U. Texas Publication No. 5109 (1951)

4. Carcinogenesis and Metabolic Profiling  Carcinogenesis is known to affect a complex network of metabolic interrelationships, leading to significant changes in concentration of a large number of body fluids.

5. Organic Acids  Organic acids are well established as important biochemical indicators of abnormal metabolism created by various diseases.

6. Goals of Metabolic Profiling  Characterization of normal and pathologic states  Studies of drug metabolism  Human developmental studies Horning, E.C., Horning, M.G. “Metabolic Profiles: Gas-Phase Methods for Analysis of Metabolites. Clin. Chem. 17, 802 (1971)

7. Challenges of Metabolic Profiling  Number of samples to analyze (for proper statistical treatment of the data)  Sample complexity  Sample preparation  Sample separation  Data processing

8. Starting Point

9. Sample Preparation Methoximation pH 13 SPE Acidification pH 2 SPE Silylation GC/MS K.-R. Kim et al. “Gas Chromatographic Profiling and Pattern Recognition Analysis of Urinary Organic Acids from Uterine Myoma Patients and Cervical Cancer Patients. J. Chrom. B, 712 (1998), 11-22. 12 Hours

10. Sample Separation

11. Data Processing

13. Challenges of the Kim Method Sample Preparation Sample Separation Data Processing

14. Goal of our Laboratory Sample Preparation Sample Separation Data Processing Impact: Higher Throughput

15. Sample Preparation

16. pH Reduction

17. Acidified Sample

18. Dichloromethane Addition

19. Liquid/Liquid Extraction

20. Liquid-Liquid Extraction

21. Filtration GCxGC Silylation in Pyridine Aqueous removal Sodium Sulfate Drying 2 Hours

22. GCxGC Instrumental Conditions  Pegasus 4D (LECO Corporation, St. Joseph, MI)  Sample Inlet  1 uL injection, splitless  Helium carrier gas (1 mL/min)  1st Dimension Column  30 m Rtx-1 column (Restek Corporation, Bellefonte, PA), 0.25 mm i.d., 0.25 um film  40°C to 280°C (5°C/min), 12 min hold at 280°C  Modulator  4-second modulation  80 msec release time  70°C to 310°C (5°C/min), 12 min hold at 310°C  2nd Dimension Column  1.5 m Rtx-50 column, 0.25 mm i.d., 0.25 um film  45°C to 285°C (5°C/min), 12 min hold at 285°C  TOF MS  100 scans/sec acquisition (30 - 500 amu)  Ion source temperature: 200°C  Transfer Line temperature: 285°C  FID  Detector temperature: 285°C

24. GCxGC Peak Apex Plot

25. Data Processing  “Extract” a pattern out of a profile  Compare profiles  Similarity indexing

26. Urinary Sample Comparisons  Similarity Index scale  Similar to library searching in Mass Spectrometry  Calculation of residual error  1st dimension retention  2nd dimension retention  Normalized relative peak area

27. Urinary Profile (Non-Diseased State) Hippuric acid trans-Aconitic acid 2-Hydroxybutyric acid Pyruvic acid Citric acid

28. Urinary Profile (Diseased State) Hippuric acid trans-Aconitic acid 2-Hydroxybutyric acid Pyruvic acid Citric acid

29. Profile Comparison Similarity Index: 628

30. Conventional Chromatography Sample Separation Sample Inlet Sample Detection

31. Alphabetography Letter Sorter Name mixture Alphabet Signal Profile

32. Stephen Reichenbach e n t c h i S e p e h R abcdefghijklmnopqrstuvwxyz en b a c h

33. abcdefghijklmnopqrstuvwxyz

34. abcdefghijklmnopqrstuvwxyz

37. Similarity Matching Table for Steve Reichenbach 1000 692 683 635

38. Similarity Matching Table for John Dimandja 1000 660 654 558 532

40. First Name Last Name

41. John Seeley John Dimandja 1D similarity Index: 654 2D first name similarity Index: 1000 2D second name similarity index: 654

42. Citric Citramalic Malic Monocarboxylic Acids Dicarboxylic Acids Tricarboxylic Acids Aromatics

43. Multi Level Similarity Indexing 340 960 429

44. Conclusions  Multidimensional profiling method has been demonstrated for selected organic acid standards; more standards need to be added to improve the screening process.  GCxGC allows for high-throughput sample preparation strategies  GCxGC-MS is indispensable for method development; GCxGC-FID can be used for routine analysis  Advanced chemometric methods need to be further developed for effective data processing

45. Acknowledgements  LECO Corporation  Restek Corporation  NSF/SEI Grant  Ms. Deanna J. Scott  Ms. Isioma Enwerem  Ms. Courtnea Rainey