technology beats cancer
TRANSCRIPT
Technology Beats Cancer Tuesday 14th May, 2013 Eight Club, Bank
Robert Gardner Board Member, The Catalyst Club Founder & Co-CEO, Redington
Welcome
A transformational journey....
Hannah Foxley Founder of The Women’s Wealth Expert
The future of cancer treatment
James Hadfield Head of Genomics, Cancer Research UK
The Catalyst Club 2013
Core Genomics blog: http://core-genomics.blogspot.com
The GoogleMap of NGS: http://omicsmaps.com [email protected]
Personalising cancer medicine one genome at a time
The Human Genome Project
$3 billion and 15 years…for one genome
James Watson “It is essentially immoral not to get it [the Human Genome Project] done as quickly as possible”
Cancer: a disease of the genomes
Moore’s law
Moore’s Law” -- Proposed by Gordon Moore, co-founder of Intel, this law accurately projected that the transistor count on a microchip would nearly double every two years. By extension, performance of computing would also double ever two years at similar costs. Four
decades 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 a telecommunications network is proportional to the square of the number of connected users of the system. While a slightly obtuse
definition, 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!
Many ways to sequence DNA
Cancer genomes
CRUK uses Illumina technology
CRUK Stratified Medicine
• Currently around 60 clinical tests (10 with clinical
utility 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 test results
• 95% of patients agree to take part
• Current Sanger sequencing will be supplanted by Next-Generation Sequencing
Resected tumour
Biomarker discovery
Next-gen sequencing data
Blood sampling
Biomarker analysis
• Aim to identify an individuals tumour mutations for treatment and follow-up decisions.
Personalised Genomic Medicine
• Biopsies are invasive and costly, provide a snapshot of mutations. • Plasma DNA could be used as a “liquid biopsy”.
Sequencing circulating tumour DNA
Sequencing circulating tumour DNA
Sequencing circulating tumour DNA
Resected tumour
Biomarker discovery
Next-gen sequencing data
Blood sampling
Biomarker analysis
• The technology exists to analyse a few genes in Cancer patients today…
• …what can we do tomorrow?
Personalised Genomic Medicine
Understanding tumour evolution
Understanding tumour evolution
Understanding tumour evolution
Understanding tumour evolution
Case 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 in the levels of a MED1 mutation, this is an ER co-activator and these mutations are known to be involved in tamoxifen resistance. After secondary therapy with lapatinib + capecitabine a mutation in GAS6 was linked to activation of the AXL tyrosine-kinase receptor which is known to be involved with lapatanib resistance.
Case 4 OvCA: After cisplatin treatment an increase in the levels of a RB1 mutation, which was also seen in 95% of reads from the metastatic biopsy. RB1 loss is known to be involved 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 of gefitinib resistance.
How does it all fit together: putative clinical workflows for genomic biomarkers
100ng Tumour DNA
Blood sampling
Biomarker analysis
Resected tumour Biomarker discovery
Biomarker discovery
Amplicon-seq
COSMIC cancer mutation amplicon screen
Exome-seq
Clinical Exome-seq by Nextera:capture
Genome-seq
Whole genome sequencing from Nextera library
Exome-seq TAm-seq
Our genomes can be analysed
Our genomes can be analysed
“Genome in day” machines
HiSeq 2500 Ion Proton
Company Illumina Life Technologies
Max read length (insert) PE150 (1200bp) PE200 (400bp)
Genome in a day $$$ $1000 $1000
Genome in a day hr:mn 24hour 2.5hour
Data output 60Gb 10-100Gb
Personalised cancer genomics medicine
James Hadfield “It is essentially immoral not to get it [personalised cancer genomic medicine] done as quickly
as possible”
‘Personalised medicine is the most exciting change in cancer treatment since the invention of chemotherapy’ Professor Peter Johnson, Chief Clinician, Cancer Research UK
Technology Beats Cancer Tuesday 14th May, 2013 Eight Club, Bank