Technology Beats Cancer


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Technology Beats Cancer

  1. 1. Technology Beats CancerTuesday 14th May, 2013Eight Club, Bank
  2. 2. Robert GardnerBoard Member, The Catalyst ClubFounder & Co-CEO, RedingtonWelcome
  3. 3. A transformational journey....Hannah FoxleyFounder of The Women’s Wealth Expert
  4. 4. The future of cancer treatmentJames HadfieldHead of Genomics, Cancer Research UK
  5. 5. The Catalyst Club 2013Core Genomics blog: http://core-genomics.blogspot.comThe GoogleMap of NGS: cancer medicineone genome at a time
  6. 6. The Human Genome Project$3 billion and 15 years…for one genomeJames Watson “It is essentially immoral not to get it[the Human Genome Project] done as quickly as possible”
  7. 7. Cancer: a disease of the genomes
  8. 8. Moore’s lawMoore’s Law” -- Proposed by Gordon Moore, co-founder of Intel, this law accurately projected that the transistor count on a microchipwould nearly double every two years. By extension, performance of computing would also double ever two years at similar costs. Fourdecades later, transistor count has grown by a factor 105 and silicon technology has seeped into every aspect of our lives.“Metcalfe Law” -- Attributed to Robert Metcalfe, co-inventor of Ethernet and founder of 3Com, this law proposes that the value of atelecommunications network is proportional to the square of the number of connected users of the system. While a slightly obtusedefinition, in essence it suggests that the value of a network increases exponentially as you add more people to it.Think Facebook, Twitter, and now Instagram!
  9. 9. Many ways to sequence DNA
  10. 10. Cancer genomes
  11. 11. CRUK uses Illumina technology
  12. 12. CRUK Stratified Medicine• Currently around 60 clinical tests (10 with clinicalutility in drug testing) on 5-10,000 patients per year• Potential: BrCA54000, PrCa36000, OvCa6000, PaCa7000(UK cases per year)• 100,000 cases but which tests and how?• Stratified Medicine Project: Sample collection,Sample Prep, Throughput, Analysis, Ethics• >2500 patients, 815 sets of cancer gene testresults• 95% of patients agree to take part• Current Sanger sequencing will be supplantedby Next-Generation Sequencing
  13. 13. ResectedtumourBiomarkerdiscoveryNext-gensequencingdataBloodsamplingBiomarkeranalysis• Aim to identify an individuals tumour mutations for treatment and follow-updecisions.Personalised Genomic Medicine• Biopsies are invasive and costly, provide a snapshot of mutations.• Plasma DNA could be used as a “liquid biopsy”.
  14. 14. Sequencing circulating tumour DNA
  15. 15. Sequencing circulating tumour DNA
  16. 16. Sequencing circulating tumour DNA
  17. 17. ResectedtumourBiomarkerdiscoveryNext-gensequencing dataBloodsamplingBiomarkeranalysis• The technology exists to analyse a few genes in Cancer patientstoday…• …what can we do tomorrow?Personalised Genomic Medicine
  18. 18. Understanding tumour evolution
  19. 19. Understanding tumour evolution
  20. 20. Understanding tumour evolution
  21. 21. Understanding tumour evolutionCase 1 BrCA: After paclitaxel treatment an increase in the levels of a PIK3CA mutation,these mutations are known to be involved in paclitaxel resistance.Case 2 BrCA ER+, Her2+: After tamoxifen + trastuzumab treatment an initial increase inthe levels of a MED1 mutation, this is an ER co-activator and these mutations are knownto be involved in tamoxifen resistance. After secondary therapy with lapatinib +capecitabine a mutation in GAS6 was linked to activation of the AXL tyrosine-kinasereceptor which is known to be involved with lapatanib resistance.Case 4 OvCA: After cisplatin treatment an increase in the levels of a RB1 mutation, whichwas also seen in 95% of reads from the metastatic biopsy. RB1 loss is known to beinvolved in chemotherapy resistance.Case 6 NSCLC: After gefitinib treatment an EGFR mutation was detected with digital-PCR,this mutation is known to inhibit binding of gefitinib to EGFR and is the main driver ofgefitinib resistance.
  22. 22. How does it all fit together: putative clinicalworkflows for genomic biomarkers100ng Tumour DNABloodsamplingBiomarkeranalysisResectedtumourBiomarker discoveryBiomarker discoveryAmplicon-seqCOSMIC cancer mutation amplicon screenExome-seqClinical Exome-seq by Nextera:captureGenome-seqWhole genome sequencing from Nextera libraryExome-seqTAm-seq
  23. 23. Our genomes can be analysed
  24. 24. Our genomes can be analysed
  25. 25. “Genome in day” machinesHiSeq 2500 Ion ProtonCompany Illumina Life TechnologiesMax read length (insert) PE150 (1200bp) PE200 (400bp)Genome in a day $$$ $1000 $1000Genome in a day hr:mn 24hour 2.5hourData output 60Gb 10-100Gb
  26. 26. Personalised cancer genomics medicineJames Hadfield “It is essentially immoral not to get it[personalised cancer genomic medicine] done as quicklyas possible”
  27. 27. ‘Personalised medicine is the most excitingchange in cancer treatment since theinvention of chemotherapy’Professor Peter Johnson, Chief Clinician, Cancer Research UK
  28. 28. Technology Beats CancerTuesday 14th May, 2013Eight Club, Bank