Bioinformatics and Personalized Medicine Nicholas A. Shackel 1  A.W. Morrow Gastroenterology and Liver Centre  Royal Princ...
Overview <ul><li>Genome / Transcriptome </li></ul><ul><li>Understanding disease </li></ul><ul><ul><li>mRNA Expression  </l...
Bioinformatics <ul><li>A long term goal of Bioinformatics is to discover the causal processes among genes, proteins, and o...
Functional Genomics  Cell Nucleus Chromosome Protein Graphics courtesy of the National Human Genome Research Institute Gen...
Systems Biology <ul><li>New Paradigm </li></ul><ul><li>“   The reductionist approach has successfully identified most of t...
Genome <ul><li>3 billion bases (x2) </li></ul><ul><li>1.5% protein encoding = 23,000 unique proteins </li></ul><ul><li>>10...
Transcriptomes <ul><li>Total transcriptome (mRNA pool) </li></ul><ul><ul><li>SAGE ~ 100 000  (www.sagenet.org) </li></ul><...
Gene Regulation and Expression Post Translational Mechanisms Alternate Splicing / ncRNA Epigenetic regulation
 
Understanding Disease
HCC Pathogenesis Saffroy (2007)  Clin Chem Lab Med 45(9) : 1169
<ul><li>HCV Genotype 1 vs Genotype 3 Clustering </li></ul>
Gene Expression  and Outcome  in HCC Hoshida (2008) NEJM :  1
Chromosomal Aberrations Pie (2009)  Acta Biochim Biophys Sin : 1
mRNA profiling of HCV-induced cirrhosis and HCC - Hierarchal Clustering HCC Cirrhotic (F4) Donor Cirrhotic G1  HCC G1 HCC ...
HCC Pathogenesis Aravalli (2008)  Hepatology : 2049
MicroRNA Targets Chen  WJG  2009  p1665 LIVER
miRNA Clinical Outcomes Junfang et al  NEJM  2009  p1437
<ul><li>Donor </li></ul><ul><li>Donor </li></ul><ul><li>Donor </li></ul>Pearson ’ s Correlation <ul><li>Segregation is bas...
Personalised Medicine
Interleukin-28B <ul><li>1671 Patients from IDEAL </li></ul><ul><li>19q13.13 </li></ul><ul><li>Rapidly confirmed </li></ul>...
IL-28B Ge et al  Nature  2009 461, p1
IL-28B Ge et al  Nature  2009 461, p1
New Technologies
Sequencing costs
Deep Sequencing Technologies
 
 
Summary <ul><li>Genomics methods have already lead to personalized medicine </li></ul><ul><ul><li>Warfarin therapy </li></...
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Dr Nicholas Shackel - Bioinformatics and Personalised Medicine

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Delivered Grand rounds, RPA hospital Friday 22 July 2011.

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Dr Nicholas Shackel - Bioinformatics and Personalised Medicine

  1. 1. Bioinformatics and Personalized Medicine Nicholas A. Shackel 1 A.W. Morrow Gastroenterology and Liver Centre Royal Prince Alfred Hospital 2 Liver Laboratory, Centenary Institute Sydney, NSW, Australia 3 Medicine University of Sydney Sydney, NSW, Australia.
  2. 2. Overview <ul><li>Genome / Transcriptome </li></ul><ul><li>Understanding disease </li></ul><ul><ul><li>mRNA Expression </li></ul></ul><ul><ul><li>miRNA Expression </li></ul></ul><ul><li>Personalised medicine </li></ul><ul><li>New technologies </li></ul>
  3. 3. Bioinformatics <ul><li>A long term goal of Bioinformatics is to discover the causal processes among genes, proteins, and other molecules in cells </li></ul><ul><li>This can be achieved by using data from High Throughput experiments, such as microarrays, deep-sequencing and proteomics </li></ul>
  4. 4. Functional Genomics Cell Nucleus Chromosome Protein Graphics courtesy of the National Human Genome Research Institute Gene (DNA) Gene (mRNA), single strand
  5. 5. Systems Biology <ul><li>New Paradigm </li></ul><ul><li>“ The reductionist approach has successfully identified most of the components and many of the interactions but, unfortunately, offers no convincing concepts or methods to understand how system properties emerge...the pluralism of causes and effects in biological networks is better addressed by observing, through quantitative measures, multiple components simultaneously and by rigorous data integration...&quot; </li></ul><ul><li>(Sauer Science April 2007) </li></ul>
  6. 6. Genome <ul><li>3 billion bases (x2) </li></ul><ul><li>1.5% protein encoding = 23,000 unique proteins </li></ul><ul><li>>100,000 alternate splicing and post translation protein variants </li></ul><ul><li>1.5-8% of the genome has regulatory elements </li></ul><ul><ul><li>UTRs, Promoters etc </li></ul></ul><ul><li>Single Nucleotide Polymorphism (SNP) 1:100 – 1:1000 </li></ul><ul><li>90% “Junk” DNA </li></ul><ul><ul><li>Unrecognized regulatory elements? </li></ul></ul><ul><ul><li>Entropy rate for coding and non-coding regions different </li></ul></ul><ul><li>Transcription without translation </li></ul>
  7. 7. Transcriptomes <ul><li>Total transcriptome (mRNA pool) </li></ul><ul><ul><li>SAGE ~ 100 000 (www.sagenet.org) </li></ul></ul><ul><ul><li>UniGene 86 820 (Build 193) </li></ul></ul><ul><li>Organ transcriptomes (Velculescu et. al. 1999 Nature Genetics 23 p387) </li></ul><ul><ul><li>Brain - 46 % </li></ul></ul><ul><ul><li>Liver - 26 % </li></ul></ul><ul><ul><ul><li>“ Liverpool ” Liver array (Coulouarn et al. 2004 Hepatology 39 p353) </li></ul></ul></ul><ul><ul><ul><ul><li>12638 transcripts </li></ul></ul></ul></ul><ul><ul><ul><li>Normal colon – 32% -> Diseased colon - 50% </li></ul></ul></ul><ul><li>Understanding the liver transcriptome (Anderson et. al. 1997 Electrophoresis 18 p533) </li></ul><ul><ul><li>Secreted and abundant transcripts over represented in mRNA (29/50 mRNA vs. 0/50 protein) </li></ul></ul><ul><li>Cell transcriptomes 5000 to > 15000 genes (lymphocyte ~ 12 000 genes) </li></ul>
  8. 8. Gene Regulation and Expression Post Translational Mechanisms Alternate Splicing / ncRNA Epigenetic regulation
  9. 9.
  10. 11.
  11. 12. Understanding Disease
  12. 13. HCC Pathogenesis Saffroy (2007) Clin Chem Lab Med 45(9) : 1169
  13. 14. <ul><li>HCV Genotype 1 vs Genotype 3 Clustering </li></ul>
  14. 15. Gene Expression and Outcome in HCC Hoshida (2008) NEJM : 1
  15. 16. Chromosomal Aberrations Pie (2009) Acta Biochim Biophys Sin : 1
  16. 17. mRNA profiling of HCV-induced cirrhosis and HCC - Hierarchal Clustering HCC Cirrhotic (F4) Donor Cirrhotic G1 HCC G1 HCC G3 HCC G1 Cirrhotic G3 Cirrhotic G3 HCC G_ HCC G_+HBV HCC G3 HCC ALD HCC G3 HCC ALD HCC ALD HCC G3 Cirrhotic G1 Cirrhotic G1 HCC G1 Cirrhotic G3 Cirrhotic G3 HCC G4+HBV Cirrhotic G1 HCC G1 Cirrhotic G3 Cirrhotic G1 Cirrhotic G3 HCC G1 HCC G3 Cirrhotic ALD Cirrhotic ALD Cirrhotic ALD Cirrhotic ALD Cirrhotic ALD Donor D o nor Donor Donor Pearson ’ s Correlation
  17. 18. HCC Pathogenesis Aravalli (2008) Hepatology : 2049
  18. 19. MicroRNA Targets Chen WJG 2009 p1665 LIVER
  19. 20. miRNA Clinical Outcomes Junfang et al NEJM 2009 p1437
  20. 21. <ul><li>Donor </li></ul><ul><li>Donor </li></ul><ul><li>Donor </li></ul>Pearson ’ s Correlation <ul><li>Segregation is based on grade and cause of injury </li></ul><ul><ul><li>Donor < Low fibrosis < Severe fibrosis / Cirrhotic < HCC </li></ul></ul><ul><ul><li>HCV vs ALD </li></ul></ul>G3 F0 Explant G1 F4 G3 F3 G1 F4 Explant G3 HCC Explant G1 F4 Explant G1 F4 Explant G3 F4 G1 F3 Explant G1 F4 Explant G3 F4 Explant G3 F4 Explant G1 HCC Explant G3 HCC Explant G3 HCC Explant G1 HCC Explant G1 HCC Explant G3 F4 ALD ALD ALD Explant G3 HCC ALD Explant G1 HCC Donor G1 F0 G1 F0 G3 F2 G3 F1 G3 F2 G1 F4 G1 F0 G3 F1 G1 F4 G3 F3 Donor Low Fibrosis Severe fibrosis/ Cirrhotic HCC ALD miRNA profiling of HCV-induced fibrosis, cirrhosis and HCC Hierarchal Clustering
  21. 22. Personalised Medicine
  22. 23.
  23. 24.
  24. 25.
  25. 26. Interleukin-28B <ul><li>1671 Patients from IDEAL </li></ul><ul><li>19q13.13 </li></ul><ul><li>Rapidly confirmed </li></ul><ul><li>Australia Group </li></ul><ul><li>Japanese Group </li></ul><ul><li>European Group </li></ul>Ge et al Nature 2009 461, p1
  26. 27. IL-28B Ge et al Nature 2009 461, p1
  27. 28. IL-28B Ge et al Nature 2009 461, p1
  28. 29. New Technologies
  29. 30. Sequencing costs
  30. 31.
  31. 32.
  32. 33. Deep Sequencing Technologies
  33. 36. Summary <ul><li>Genomics methods have already lead to personalized medicine </li></ul><ul><ul><li>Warfarin therapy </li></ul></ul><ul><ul><li>Hepatitis C Treatment responses </li></ul></ul><ul><ul><li>Malignancy </li></ul></ul><ul><li>Deep Sequencing presents a “deluge” of data </li></ul><ul><ul><li>Promise of personalised medicine </li></ul></ul><ul><ul><li>Analysis problems dramatically amplified </li></ul></ul>

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