Download Delivering Next Generation Sequencing for Solid Tumours

Dr Matthew Smith
Clinical Scientist and Honorary Research Fellow
West Midlands Regional Genetics Laboratory
University of Birmingham
Targeted Treatments of Somatic Mutations in Cancer

Tumours contain hallmark mutations within oncogenes or tumour suppressor genes that may
confer a heightened susceptibility to targeted anticancer therapies

Herceptin targets HER2-overexpressing metastatic breast cancer

KIT mutations in gastrointestinal stromal tumours (GISTs) that predict response to imatinib or
nilotinib

EGFR mutations that are sensitive to erlotinib in Non-small cell lung cancers

Lung and colorectal cancers that harbour mutations in the KRAS oncogene are unresponsive to
treatment with anti-EGFR agents

Chemotherapy susceptibility
 Defective p53 and ATM susceptible to chemotherapy
 p53 only mutated – less susceptible
 ATM only mutated – resistant to certain types of chemotherapy
Stratified Medicine
Molecular characteristics of a patients tumour to enable targeted treatment to improve cancer care
•
Why is stratified Medicine so
important
• Ideal
•
Effective in all patients
Same dose
• No Side Effects
• Reality
•
•
Dosages vary
• Side effects
Germline genetics Pharmacogenetics
•
•
Not effective in all
patients
Current Diagnostic Testing in the NHS

Current testing of tumour material for molecular biomarkers is
fragmentary, costly and of variable quality

Multiple testing Scenarios
 Single mutation within an exon
 Multiple mutations within an exon
 Multiple mutations in multiple exons
 Targeted Recurrent Mutations in Oncogenes Vs. Inactivating mutations in
tumour suppressing genes

Available resources
 Equipment
 Cost
 Experience and expertise
Delivering Stratified Medicine in the NHS
CRUK Stratified Medicine Programme

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Cancer Research UK's Stratified Medicine Programme is a significant step in
making targeted therapies available for people with cancer in the UK.
Aims of project
 Develop assays with clinical utility that are cost effective and commercially
viable
 Provide national molecular diagnostics service delivering
○ high quality
○ cost effective tests for patients
○ routine consent for collection, storage and research
○ use of population-scale genetic and outcomes data.
Phase 1 2011-2013
 pilot study to demonstrate on a small scale how the NHS can provide
molecular diagnosis for all cancer types routinely
Infrastructure
Research
infrastructure
Service
delivery
The Burden of Multiple Tests
Samples Rec'd 01.09.2011 to
28.02.2013
Blood
Birmingham
Tumour
Breast
Colorectal
Lung
Melanoma
Ovary
Prostate
Total
Tumour
311
10
59
0
8
0
12
89
400
Cambridge
755
225
96
97
40
79
135
672
1427
Edinburgh
1494
236
220
153
27
34
288
958
2452
Totals Sample type
2560
471
375
250
75
113
435
1719
4279
Genes
4
5
4/5
4
4
3
Methods
3
3
4
3
3
3
14130
6750
2500
600
3390
8700
36070
38630
Tests
2560
Total
Samples
NGS Panel Tests under Development at the WMRGL
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CRUK working closely with Technology Strategy Board (TSB)
 Tumour Profiling and data capture
 WMRGL partners with
○ Oxford Gene Technology – Cancer Gene Panel
○ Affymetrix - MIP Array
CRUK Technical Hubs working with Illumina in developing a focused CRUK panel
for Phase I
In-house developments for tumour studies
58 AML gene panel – RainDance Technologies
Number of constitutional panels in service and development
Technology Strategy Board (TSB)
TSB-Oxford Gene Technology
 Accelerate Stratified Medicine in the UK.
 Funding industry lead collaborations
 Tumour profiling and data capture in cancer care
 Improving patient care and outcomes
 Developing cost effective strategies for Tumour profiling in the NHS
LEAD PARTNER:
INDUSTRY PARTNER:
ACADEMIC PARTNER 1:
University of Southampton
ACADEMIC PARTNER 2:
University of Birmingham
Next Generation Platform – Illumina MiSeq
•
Benchtop Sequencer
•
Sequencing by synthesis
technology
•
2X150 paired end read in 24hours
•
4.5-5 Gb of data
•
>80% reads above Q30 (1 in 1000
of an error)
Challenges of Panel Design and using NGS for Solid Tumours
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What to sequence
How deep to sequence
The NGS tests needs to be on a par or better than the established tests
What constitutes clinically relevant
Sample procurement
Data analysis burden
Diagnostic vs Discovery
 Small clinically relevant panels vs. Larger discovery panels
Turnaround time
Cost
MAJOR challenge is the material that will be used
DNA from Formalin-fixed, paraffin-embedded (FFPE) tissue
Working with FFPE-DNA



FFPE tissue is one of the most widely practiced methods for clinical sample preservation and
archiving
Standard for histopathology and microscopic investigation
FFPE samples pose a major challenge for molecular pathologists
 nucleic acids are heavily modified and trapped by extensive protein-nucleic acid and proteinprotein cross linking.
FFPE DNA cont’d
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Nucleic acids highly fragmented and often in the presence of high conc of
contaminates
Large variation in sample quantity, quality and purity
Non-reproducible sequence artefacts are frequently detected in DNA from
formalinfixed and paraffin-embedded (FFPE) tissues
Cytosine deamination
C>T (and G>A) sequence artefacts
Represents a significant challenge in NGS
Tumour Enrichment
• For solid tumours this can be achieved through macrodissection
• Scrolls – deep enough read depth to balance the presence of
“normal”
Which Capture Technology

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Choice of enrichment assay driven by the application.
PCR-amplicon and hybridisation capture approaches
Amplicon based
 Microfluidics – Fluidigm and Raindance
Hybridisation
 probes or ‘baits’ to hybridise and capture target DNA
 Array or solution based
Enrichment for TSB-OGT Stratified Medicine Panel
Hybridisation Based
Hybridisation/Amplicon
• 3 in solution hybridisation
technologies
• Haloplex
Criteria – Sequencing-platform agnostic
V1 SMP Enrichment Assay Evaluation
V1 Panel
Agilent/
Basic
Agilent/
OGT
Agilent/
Exp
Comp 1
Comp 2
Haloplex
AKT1
BRCA2
HRAS
PTEN
APC
CDKN2A
KIT
RB1
ARID1A
CTNNB1
KRAS
RET
ATM
CYP2D6
NF1
SMAD4
BRAF
EGFR
NRAS
STK11
BRCA1
FGFR3
PIK3CA
TP53
UGT1A1
red = COSMIC top 21 gene panel
blue = TSB required
Comp 1 and 2 excluded due to
poor coverage
Haloplex and Sureselect taken
forward
Haloplex
Sureselect
FFPE-DNA Quantity and Quality
Conc. Nanodrop Conc. Nanodrop
(ng/µl)
(ng)
Conc. Qubit
(ng/µl)
Conc. Qubit
(ng)
Volume (µl)
Sample 1
24.1
4820
1.8
358
200
Sample 2
39.5
7898
8.3
1656
200
Sample 3
18.3
3650
0.6
115.6
200
Sample 4
51.5
10300
8.4
1676
200
577
3078
A2
B1
C1
0
421
247
50
3104
3161
1671
2479
2271
2381
2428
1946
1796
1328
5142
FFPE-DNA and Enrichment
ROI Enrichment
Starting Material

DNA requirement
Agilent/OGT concordance for 147 variants
Sample 1
(3000ng)
(500ng)
(100ng)
WGA (from
25 ng)
100%
98.0%
97.3%
96.3%
HaloPlex – concordance for 113 variants
Sample 1


(900ng)
(450ng)
(200ng)
WGA (from
25 ng)
100%
98.2%
95.6%
97.3%
Filtered variants on exon + near exon
No apparent bias introduced by WGA - add additional time and expense
OGT-Sureselect Vs Haloplex
V2 Panel
Cosmic genes
TSB required genes
Requested genes
Genes common to other
panels
Version 2
60 full genes
Including UTRs
SureSelect size: 466Kb
OGT
SureSelect
OGT HaloPlex
%bases with 0x
coverage
0.76%
%bases with 2x
coverage
% bases with 10x
coverage
Metric
%bases with 20x
coverage
%bases with 30x
coverage
Birmingham
SureSelect
Birmingham
HaloPlex
0.09%
0.88%
0.11%
98.46%
97.80%
98.37%
96.19%
97.93%
94.93%
97.66%
90.61%
97.49%
92.36%
96.77%
85.34%
97.07%
89.99%
95.66%
80.95%
% on target
47.12%
71.81%
52.97%
69.53%
Mean target coverage
472
480
199
480
% bases with 30x coverage Is an
important indicator of uniformity of
sequence enrichment.
% on-target is a direct measure of
enrichment efficiency, and shows
the number of sequenced bases
which fall into the targeted regions.
Mean target coverage is the
average number of reads observed
for all bases within the targeted
region
Analysis Pipeline
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Challenges in detecting true low level
mutations come from sequencing error,
library contamination, PCR artefacts
Samples analysed together
 Increase confidence of genuine
variation
Exclude strand bias
Exclude Duplicates
Set minimum coverage and read cut-off
 Min of 10 reads
Should you keep only high quality data
Low quality data could be localised – loss
of seq information
Accuracy of genotyping for difficult
samples improved by using more than
one genotyper
Software is evolving
Variant
% tumour
SureSelect –
Gene DoC
OGT BIRM
SureSelect –
Position DoC
OGT BIRM
Halo- Gene
DoC
OGT BIRM
Halo –
Position DoC
OGT BIRM
Detected?
BRAF V600
Not
known
Not
known
Not
known
380x, 103x
376x, 202x
324x, 103x
94x, 80x
YES
416x, 189x
264x, 205x
396x, 207x
203x, 87x
YES
416x, 189x
142x, 89x
396x, 207x
161x, 102x
YES
30-40%
257x, 113x
289x, 93x
195x, 130x
49x, 12x
YES^
20-30%
225x, 91x
237x, 65x
187x, 64x
18x, 6x
5-10%
281x,109x
349x, 102x
350x, 108x
68x, 29x
SureSelect
only^
SureSelect
only^
KIT c.1676T>A
p.Val559Asp
KIT c.1735_1737delGAT
p.Asp579del
KRAS c.34G>T
p.Gly12Cys*
KRAS c.34G>C
p.Gly12Arg
KRAS c.38G>A
p.Gly13Asp
^ Variants were not detected by standard analysis algorithms, but were detected using OGT’s optimised pipeline for tumour
analysis
SureSelect discrimination at high depth
Dilution
T Allele (%)
A Allele (%)
Neat
(Heterozygous 50%)
415 (56%)
320 (43%)
1:2 (25%)
596 (73%)
214 (26%)
1:10 (5%)
573 (93%)
42 (7%)
1:20 (2.5%)
699 (95%)
37 (5%)
1:50 (1.25%)
625 (96%)
24 (4%)
1:100 (0.5%)
712 (99%)
8 (1%)
Detected?
Technical validation – Summary

OGT SureSelect
Haloplex
Coverage
Uniform
Variable
Bases at 30X
Avg 96%
Avg 85%
On Target
Avg 50%
Avg 70%
DNA to data
5-6 days
3-4days
Experimental steps
>15
<10
Additional Equipment
Yes - Covaris
No
SURESELECT OVER HALOPLEX
 Data quality
 Sensitivity for detecting variants
 In process QC
 Assay stability

HALOPLEX OVER SURESELECT
 No additional expensive equipment
 Less technically demanding
 Quicker turnaround
SURESELECT Enrichment Selected
Panel Revision
•
•
Version 2
Version 2.1
• 60 full genes
• Including UTRs
• SureSelect size:
466Kb
• Samples per lane for
500x: 7
• 58 full genes
• Minus UTRs
• SureSelect size:
244kb
• Samples per lane for
500x: 12 (estimated)
6 month ≥300 clinical samples will be run @ OGT, Salisbury and Birmingham as part of the
clinical validation/utility assessment
•
48 Pancreatic cancer samples – defined clinical cohort
•
48 Oesophageal cancer samples – defined clinical cohort
Bait design with be further improved
NGS of Solid Tumours as a Diagnostic service
•
How do you truly validate these panels
•
Confirmation of low level variants
• Confirmation test has lower sensitivity
•
Determining a mutant allele threshold
• Quoted to achieve a sensitivity of 1%, a read depth of 1000X required
• More reads = greater sensitivity
• Panel size vs. throughput at desired coverage
• Increased costs
• Increased TAT
•
Quality control
• Improving the quality of starting material
• Impose a quality cut-off
• Duplex testing – in poor quality samples the number of variants can be
reduced by comparing variant calls unique to either of the runs
•
Assay re-validation given continuing hardware software improvements
Acknowledgments
Simon Hughes
James Clough
Daniel Swan
Zandra Carrington
Mike Griffiths
Jennie Bell
Brendan O’Sullivan
Claire Hoey
Chris Mattocks
Matt Lyons