Molecular profiling 2013

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Molecular Profiling

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Molecular profiling 2013

  1. 1. Next Generation Molecular Profiling Woensdag 9 oktober 2013
  2. 2. Lab for Bioinformatics and computational genomics 10 “genome hackers” mostly engineers (statistics) 42 scientists technicians, geneticists, clinicians >100 people hardware engineers, mathematicians, molecular biologists
  3. 3. Next Generation Molecular Profiling
  4. 4. Overview Personalized Medicine, Biomarkers … … Molecular Profiling First Generation Molecular Profiling Next Generation Molecular Profiling Next Generation Epigenetic Profiling Concluding Remarks
  5. 5. Overview Personalized Medicine, Biomarkers … … Molecular Profiling First Generation Molecular Profiling Next Generation Molecular Profiling Next Generation Epigenetic Profiling Concluding Remarks
  6. 6. Personalized Medicine • The use of diagnostic tests (aka biomarkers) to identify in advance which patients are likely to respond well to a therapy • The benefits of this approach are to – avoid adverse drug reactions – improve efficacy – adjust the dose to suit the patient – differentiate a product in a competitive market – meet future legal or regulatory requirements • Potential uses of biomarkers – Risk assessment – Initial/early detection – Prognosis – Prediction/therapy selection – Response assessment – Monitoring for recurrence
  7. 7. Biomarker First used in 1971 … An objective and « predictive » measure … at the molecular level … of normal and pathogenic processes and responses to therapeutic interventions Characteristic that is objectively measured and evaluated as an indicator of normal biologic or pathogenic processes or pharmacologic response to a drug A biomarker is valid if: – It can be measured in a test system with well established performance characteristics – Evidence for its clinical significance has been established
  8. 8. Rationale 1: Why now ? Regulatory path becoming more clear There is more at stake than efficient drug development. FDA « critical path initiative » Pharmacogenomics guideline Biomarkers are the foundation of « evidence based medicine » - who should be treated, how and with what. Without Biomarkers advances in targeted therapy will be limited and treatment remain largely emperical. It is imperative that Biomarker development be accelarated along with therapeutics
  9. 9. Why now ? First and maturing second generation molecular profiling methodologies allow to stratify clinical trial participants to include those most likely to benefit from the drug candidate—and exclude those who likely will not—pharmacogenomics- based Clinical trials should attain more specific results with smaller numbers of patients. Smaller numbers mean fewer costs (factor 2-10) An additional benefit for trial participants and internal review boards (IRBs) is that stratification, given the correct biomarker, may reduce or eliminate adverse events.
  10. 10. Molecular Profiling The study of specific patterns (fingerprints) of proteins, DNA, and/or mRNA and how these patterns correlate with an individual's physical characteristics or symptoms of disease.
  11. 11. Generic Health advice • Exercise (Hypertrophic Cardiomyopathy) • Drink your milk (MCM6 Lactose intolarance) • Eat your green beans (glucose-6-phosphate dehydrogenase Deficiency) • & your grains (HLA-DQ2 – Celiac disease) • & your iron (HFE - Hemochromatosis) • Get more rest (HLA-DR2 - Narcolepsy)
  12. 12. Generic Health advice (UNLESS) • Exercise (Hypertrophic Cardiomyopathy) • Drink your milk (MCM6 Lactose intolarance) • Eat your green beans (glucose-6-phosphate dehydrogenase Deficiency) • & your grains (HLA-DQ2 – Celiac disease) • & your iron (HFE - Hemochromatosis) • Get more rest (HLA-DR2 - Narcolepsy)
  13. 13. Generic Health advice (UNLESS) • Exercise (Hypertrophic Cardiomyopathy) • Drink your milk (MCM6 Lactose intolerance) • Eat your green beans (glucose-6-phosphate dehydrogenase Deficiency) • & your grains (HLA-DQ2 – Celiac disease) • & your iron (HFE - Hemochromatosis) • Get more rest (HLA-DR2 - Narcolepsy)
  14. 14. Generic Health advice (UNLESS) • Exercise (Hypertrophic Cardiomyopathy) • Drink your milk (MCM6 Lactose intolerance) • Eat your green beans (glucose-6-phosphate dehydrogenase Deficiency) • & your grains (HLA-DQ2 – Celiac disease) • & your iron (HFE - Hemochromatosis) • Get more rest (HLA-DR2 - Narcolepsy)
  15. 15. EGFR based therapy in mCRC
  16. 16. Overview Personalized Medicine, Biomarkers … … Molecular Profiling First Generation Molecular Profiling Next Generation Molecular Profiling Next Generation Epigenetic Profiling Concluding Remarks
  17. 17. Before molecular profiling …
  18. 18. Before molecular profiling …
  19. 19. Before molecular profiling …
  20. 20. First Generation Molecular Profiling • Flow cytometry correlates surface markers, cell size and other parameters • Circulating tumor cell assays (CTC’s) quantitate the number of tumor cells in the peripheral blood. • Exosomes are 30-90 nm vesicles secreted by a wide range of mammalian cell types. • Immunohistochemistry (IHC) measures protein expression, usually on the cell surface.
  21. 21. First Generation Molecular Profiling • Gene sequencing for mutation detection • Microarray for m-RNA message detection • RT-PCR for gene expression • FISH analysis for gene copy number • Comparative Genome Hybridization (CGH) for gene copy number
  22. 22. Basics of the ―old‖ technology • Clone the DNA. • Generate a ladder of labeled (colored) molecules that are different by 1 nucleotide. • Separate mixture on some matrix. • Detect fluorochrome by laser. • Interpret peaks as string of DNA. • Strings are 500 to 1,000 letters long • 1 machine generates 57,000 nucleotides/run • Assemble all strings into a genome.
  23. 23. Genetic Variation Among People 0.1% difference among people GATTTAGATCGCGATAGAG GATTTAGATCTCGATAGAG Single nucleotide polymorphisms (SNPs)
  24. 24. The genome fits as an e-mail attachment
  25. 25. First Generation Molecular Profiling • Gene sequencing for mutation detection • Microarray for m-RNA message detection • RT-PCR for gene expression • FISH analysis for gene copy number • Comparative Genome Hybridization (CGH) for gene copy number
  26. 26. mRNA Expression Microarray
  27. 27. First Generation Molecular Profiling • Gene sequencing for mutation detection • Microarray for m-RNA message detection • RT-PCR for gene expression • FISH analysis for gene copy number • Comparative Genome Hybridization (CGH) for gene copy number
  28. 28. Overview Personalized Medicine, Biomarkers … … Molecular Profiling First Generation Molecular Profiling Next Generation Molecular Profiling Next Generation Epigenetic Profiling Concluding Remarks
  29. 29. Basics of the ―new‖ technology • Get DNA. • Attach it to something. • Extend and amplify signal with some color scheme. • Detect fluorochrome by microscopy. • Interpret series of spots as short strings of DNA. • Strings are 30-300 letters long • Multiple images are interpreted as 0.4 to 1.2 GB/run (1,200,000,000 letters/day). • Map or align strings to one or many genome.
  30. 30. Next Generation Technologies • Roche (454) –Emulsion PCR –Polymerase –Natural Nucleotides • 100-500 Mb for 5-15k –1% error rate –Homopolymers
  31. 31. One additional insight ...
  32. 32. Read Length is Not As Important For Resequencing 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 8 10 12 14 16 18 20 Length of K-mer Reads (bp) %ofPairedK-merswithUniquely AssignableLocation E.COLI HUMAN Jay Shendure
  33. 33. Short Read Techologies • Illumina GA (HiSeq, MySeq) • ABI SOLID
  34. 34. Other second generation technology: (ABI) SOLID
  35. 35. So what ?
  36. 36. Second generation DNA/RNA profiling
  37. 37. Second Generation DNA profiling • Enrichment Sequencing • ChIP-Seq (Chromosome Immunoprecipitation) • A substitute for ChIP-chip • Eg. to find the binding sequence of proteins (TFBS)
  38. 38. Paired End Reads are Important! Repetitive DNA Unique DNA Single read maps to multiple positions Read 1 Read 2 Known Distance
  39. 39. Paired End Reads are Important! Repetitive DNA Unique DNA Single read maps to multiple positions Read 1 Read 2 Known Distance
  40. 40. Second Generation DNA profiling • Exome Sequencing (aka known as targeted exome capture) is an efficient strategy to selectively sequence the coding regions of the genome to identify novel genes associated with rare and common disorders. • 160K exons
  41. 41. Second Generation DNA profiling
  42. 42. Second Generation DNA profiling
  43. 43. Bioinformatics tools
  44. 44. Bioinformatics tools
  45. 45. Contents-Schedule Besides the 6000 protein coding-genes … 140 ribosomal RNA genes 275 transfer RNA gnes 40 small nuclear RNA genes >100 small nucleolar genes Function of RNA genes pRNA in 29 rotary packaging motor (Simpson et el. Nature 408:745-750,2000) Cartilage-hair hypoplasmia mapped to an RNA (Ridanpoa et al. Cell 104:195-203,2001) The human Prader-Willi ciritical region (Cavaille et al. PNAS 97:14035-7, 2000) Second Generation RNA profiling
  46. 46. RNA genes can be hard to detects UGAGGUAGUAGGUUGUAUAGU C.elegans let-27; 21 nt (Pasquinelli et al. Nature 408:86-89,2000) Often small Sometimes multicopy and redundant Often not polyadenylated (not represented in ESTs) Immune to frameshift and nonsense mutations No open reading frame, no codon bias Often evolving rapidly in primary sequence Second Generation RNA profiling
  47. 47. Although details of the methods vary, the concept behind RNA-seq is simple: • isolate all mRNA • convert to cDNA using reverse transcriptase • sequence the cDNA • map sequences to the genome The more times a given sequence is detected, the more abundantly transcribed it is. If enough sequences are generated, a comprehensive and quantitative view of the entire transcriptome of an organism or tissue can be obtained. Second Generation RNA profiling
  48. 48. • Comparing to microarray – Microarray • Closed technology: Prior knowledge required • Affected by pseudo-genes (homologous of real genes) • Low sensitivity – RNA-Seq • Open technology: No prior knowledge required • Not affected by pseudo-genes because exact sequence is measured • Other information could be yielded (SNP, Alternative splicing) Second Generation RNA profiling
  49. 49. ncRNAs in human genome tRNA 600 18S rRNA 200 5.8S rRNA 200 28S rRNA 200 5S rRNA 200 snoRNA 300 miRNA 250 U1 40 U2 30 U4 30 U5 30 U6 20 U4atac 5 U6atac 5 U11 5 U12 5 SRP RNA 1 RNase P RNA 1 Telomerase RNA 1 RNase MRP 1 Y RNA 5 Vault 4 7SK RNA 1 Xist 1 H19 1 BIC 1 Antisense RNAs 1000s? Cis reg regions 100s? Others ?
  50. 50. Mapping Structural Variation in Humans - Thought to be Common 12% of the genome (Redon et al. 2006) - Likely involved in phenotype variation and disease - Until recently most methods for detection were low resolution (>50 kb) CNVs >1 kb segments
  51. 51. Size Distribution of CNV in a Human Genome
  52. 52. Next next generation sequencing Third generation sequencing Now sequencing
  53. 53. Ultra-low-cost SINGLE molecule sequencing
  54. 54. Pacific Biosciences: A Third Generation Sequencing Technology Eid et al 2008
  55. 55. Complete genomics
  56. 56. Nanopore Sequencing
  57. 57. Second Generation Protein profiling • Proteomics MS-MS-based exclusively in discovery mode • Automate diagnostics assay generation (next generation proteomics) • Aptamers as alternative to antibodies • ImmunoPCR
  58. 58. MS/MS identification pipeline pipeline overview Bonanza Bonanza + IggyPep Goal define PTMs profile prior to database search Goal multi-tiered database search Goal filter dataset prior to database search
  59. 59. Second Generation Protein profiling • Proteomics MS-MS-based exclusively in discovery mode • Automate diagnostics assay generation (next generation proteomics) • Aptamers as alternative to antibodies • ImmunoPCR
  60. 60. Overview Personalized Medicine, Biomarkers … … Molecular Profiling First Generation Molecular Profiling Next Generation Molecular Profiling Next Generation Epigenetic Profiling Concluding Remarks
  61. 61. CONFIDENTIAL Defining Epigenetics  Reversible changes in gene expression/function  Without changes in DNA sequence  Can be inherited from precursor cells  Allows to integrate intrinsic with environmental signals (including diet) Methylation I Epigenetics | Oncology | Biomarker Genome DNA Gene Expression Epigenome Chromatin Phenotype I NEXT-GEN | PharmacoDX | CRC
  62. 62. CONFIDENTIAL Methylation I Epigenetics | Oncology | Biomarker I NEXT-GEN | PharmacoDX | CRC
  63. 63. CONFIDENTIAL Epigenetic Regulation: Post Translational Modifications to Histones and Base Changes in DNA  Epigenetic modifications of histones and DNA include: – Histone acetylation and methylation, and DNA methylation Histone Acetylation Histone Methylation DNA Methylation MeMe Ac Me Methylation I Epigenetics | Oncology | Biomarker I NEXT-GEN | PharmacoDX | CRC
  64. 64. CONFIDENTIAL MGMT Biology O6 Methyl-Guanine Methyl Transferase Essential DNA Repair Enzyme Removes alkyl groups from damaged guanine bases Healthy individual: - MGMT is an essential DNA repair enzyme Loss of MGMT activity makes individuals susceptible to DNA damage and prone to tumor development Glioblastoma patient on alkylator chemotherapy: - Patients with MGMT promoter methylation show have longer PFS and OS with the use of alkylating agents as chemotherapy Methylation I Epigenetics | Oncology | Biomarker I NEXT-GEN | PharmacoDX | CRC
  65. 65. CONFIDENTIAL MGMT Promoter Methylation Predicts Benefit form DNA-Alkylating Chemotherapy Post-hoc subgroup analysis of Temozolomide Clinical trial with primary glioblastoma patients show benefit for patients with MGMT promoter methylation 0 5 10 15 20 25 Median Overall Survival 21.7 months 12.7 months radiotherapy plus temozolomide Methylated MGMT Gene Non-Methylated MGMT Gene radiotherapy Adapted from Hegi et al. NEJM 2005 352(10):1036-8. Study with 207 patients Methylation I Epigenetics | Oncology | Biomarker I NEXT-GEN | PharmacoDX | CRC
  66. 66. CONFIDENTIAL Genome-wide methylation by methylation sensitive restriction enzymes Methylation I Epigenetics | Oncology | Biomarker I NEXT-GEN | PharmacoDX | CRC
  67. 67. CONFIDENTIAL Genome-wide methylation by probes Methylation I Epigenetics | Oncology | Biomarker I NEXT-GEN | PharmacoDX | CRC
  68. 68. CONFIDENTIAL# samples # markers Genome-wide methylation …. by next generation sequencing Discovery Verification Validation Methylation I Epigenetics | Oncology | Biomarker I NEXT-GEN | PharmacoDX | CRC
  69. 69. CONFIDENTIAL MBD_Seq DNA Sheared Immobilized Methyl Binding Domain Methylation I Epigenetics | Oncology | Biomarker Condensed Chromatin DNA Sheared I NEXT-GEN | PharmacoDX | CRC
  70. 70. CONFIDENTIAL Immobilized Methyl binding domain MgCl2 Next Gen Sequencing GA Illumina: 100 million reads MBD_Seq Methylation I Epigenetics | Oncology | Biomarker I NEXT-GEN | PharmacoDX | CRC
  71. 71. CONFIDENTIAL MBD_Seq MGMT = dual core Methylation I Epigenetics | Oncology | Biomarker I NEXT-GEN | PharmacoDX | CRC
  72. 72. CONFIDENTIAL# samples # markers MBD_Seq Genome-wide methylation …. by next generation sequencing Discovery 1-2 million methylation cores Methylation I Epigenetics | Oncology | Biomarker I NEXT-GEN | PharmacoDX | CRC
  73. 73. CONFIDENTIAL Data integration Correlation tracks 99 methylation methylation expression expression Corr =-1 Corr = 1
  74. 74. CONFIDENTIAL Correlation track in GBM @ MGMT 100 Methylation I Epigenetics | Oncology | Biomarker I NEXT-GEN | PharmacoDX | +1 -1
  75. 75. CONFIDENTIAL# samples Methylation I Epigenetics | Oncology | Biomarker # markers MBD_Seq 454_BT_Seq MSP Genome-wide methylation …. by next generation sequencing Discovery Verification Validation I NEXT-GEN | PharmacoDX |
  76. 76. CONFIDENTIAL GCATCGTGACTTACGACTGATCGATGGATGCTA unmethylated alleles less methylationmethylated alleles more methylation Deep Sequencing
  77. 77. CONFIDENTIAL Deep MGMT Heterogenic complexity Methylation I Epigenetics | Oncology | Biomarker I NEXT-GEN | PharmacoDX | CRC
  78. 78. 104
  79. 79. CONFIDENTIAL 105 Methylation I Epigenetics | Oncology | Biomarker I NEXT-GEN | PharmacoDX | CRC
  80. 80. Overview Personalized Medicine, Biomarkers … … Molecular Profiling First Generation Molecular Profiling Next Generation Molecular Profiling Next Generation Epigenetic Profiling Concluding Remarks
  81. 81. Math Informatics Bioinformatics, a life science discipline … (Molecular) Biology
  82. 82. Math Informatics Bioinformatics, a life science discipline … Theoretical Biology Computational Biology (Molecular) Biology Computer Science
  83. 83. Math Informatics Bioinformatics, a life science discipline … Theoretical Biology Computational Biology (Molecular) Biology Computer Science Bioinformatics
  84. 84. Math Informatics Bioinformatics, a life science discipline … management of expectations Theoretical Biology Computational Biology (Molecular) Biology Computer Science Bioinformatics Interface Design AI, Image Analysis structure prediction (HTX) Sequence Analysis Expert Annotation NP Datamining
  85. 85. Math Informatics Bioinformatics, a life science discipline … management of expectations Theoretical Biology Computational Biology (Molecular) Biology Computer Science Bioinformatics Discovery Informatics – Computational Genomics Interface Design AI, Image Analysis structure prediction (HTX) Sequence Analysis Expert Annotation NP Datamining
  86. 86. Translational Medicine: An inconvenient truth • 1% of genome codes for proteins, however more than 90% is transcribed • Less than 10% of protein experimentally measured can be ―explained‖ from the genome • 1 genome ? Structural variation • > 200 Epigenomes ?? • Space/time continuum …
  87. 87. Translational Medicine: An inconvenient truth • 1% of genome codes for proteins, however more than 90% is transcribed • Less than 10% of protein experimentally measured can be ―explained‖ from the genome • 1 genome ? Structural variation • > 200 Epigenomes … • ―space/time‖ continuum
  88. 88. Epigenetic (meta)information = stem cells Cellular programming
  89. 89. Cellular reprogramming Tumor Epigenetically altered, self- renewing cancer stem cells Tumor Development and Growth
  90. 90. Gene-specific Epigenetic reprogramming Cellular reprogramming
  91. 91. 119 biobix wvcrieki biobix.be bioinformatics.be

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