Center for Personalized Diagnostics Karthik Ganapathy€¦ · Center for Personalized Diagnostics ....
39
Bigger and Better: Building an NGS Panel to Meet the Needs of Clinical Researchers Karthik Ganapathy Division of Precision and Computational Diagnostics Center for Personalized Diagnostics
Transcript of Center for Personalized Diagnostics Karthik Ganapathy€¦ · Center for Personalized Diagnostics ....
Bigger and Better: Building an NGS Panel to Meet the Needs of Clinical Researchers
Karthik Ganapathy
Division of Precision and Computational Diagnostics
Center for Personalized Diagnostics
Conflict of Interest Disclosure
No conflicts of interest to disclose.
Discussion Overview
Solid Tumor Assay at the CPD
New Assay Development – Solid v2.0
HaloPlexHS Methodology and Assay Design
Results, Optimization, and Re-Design
Validation Testing
Discussion Overview
Solid Tumor Assay at the CPD
New Assay Development – Solid v2.0
HaloPlexHS Methodology and Assay Design
Results, Optimization, and Re-Design
Validation Testing
Tumor Sample DNA QC Assay Sequence
10 tumor types Melanoma - BRAF
Lung – EGFR GI tumors - KRAS
FFPE Slides FFPE Scrolls
FNA >95% from Penn
Medicine >=10% tumor
nuclei
2 day Extraction Protocol
Overnight digestion
Qubit DropSesnse
Genomic Tape - 4200 % of Degradation
Amplicon based 36 kbp
47 genes 212 amplicons
PPP reflex panel BRCA1/2 & ESR1
3x MiSeq v3 2x186bp
Sample mean 2000x
Target mean 250x 5% AF
SNV and indels
Solid Tumor Assay Workflow at the CPD
Discussion Overview
Solid Tumor Assay at the CPD
New Assay Development – Solid v2.0
HaloPlexHS Methodology and Assay Design
Results, Optimization, and Re-Design
Validation Testing
New Test Development Based on Institutional Priorities
How much is just right? Goldilocks Principle
85% actionable content
Content based on physician input to expand clinical utility for their patients
What makes a gene good? - Prognostic - Diagnostic - Actionable
- Known target - Clinical trial - Change in therapy
How can we help clinical researchers? - Match clinical and mutation data - Stratification of tumor types based on
mutation profile
Clinical research - mutation profile(s) linked to outcome data
Enrollment into mutation-specific treatment modalities
Discussion Overview
Solid Tumor Assay at the CPD
New Assay Development – Solid v2.0
HaloPlexHS Methodology and Assay Design
Results, Optimization, and Re-Design
Validation Testing
Designing Solid Tumor Assay v2.0
Specification Solid v1.0 (Current)
Solid v2.0 (Goal)
Genes Targeted 47 153
Coverage Mutational
hotspots All exons
Target region 37 kbp 506 kbp
DNA input 250ng 50ng
Indexing and Barcoding 96 indexes
No barcoding 96 indexes Barcoding
Variant detection 5% 1%
Cost per sample* $500/47 genes ($10.63/gene)
Reduce
* Based on reagents (including sequencing) and tech time. Not including other overhead, director salary, etc
Lowering the bar to raise the stakes
Specification Solid v1.0 (Current)
Solid v2.0 (Goal)
Genes Targeted 47 153
Coverage Mutational
hotspots All exons
Target region 37 kbp 506 kbp
DNA input 250ng 50ng
Indexing and Barcoding 96 indexes
No barcoding 96 indexes Barcoding
Variant detection 5% 1%
Cost per sample* $500/47 genes ($10.63/gene)
Reduce
* Based on reagents (including sequencing) and tech time. Not including other overhead, director salary, etc
Lowering the bar to raise the stakes
Physician Input
Laboratory Target
Designing Solid Tumor Assay v2.0
Specification Solid v1.0 (Current)
Solid v2.0 (Goal)
Solid v2.0 (Actual)
Genes Targeted 47 153 155
Coverage Mutational
hotspots All exons All exons
Target region 37 kbp 506 kbp 583 kbp
DNA input 250ng 50ng 35ng to 50ng
Indexing and Barcoding 96 indexes
No barcoding 96 indexes Barcoding
96 indexes Barcoding
Variant detection 5% 1% 0.5% to 1% (expected)
Cost per sample* $500/47 genes ($10.63/gene)
Reduce $800/155 genes
($5.16/gene)
* Based on reagents (including sequencing) and tech time. Not including other overhead, director salary, etc
Lowering the bar to raise the stakes
Designing Solid Tumor Assay v2.0
How HaloPlexHS Works
For Research Use Only. Not for use in diagnostic procedures.
Assay Design Process
Target : 153 genes (All exons +/- 10bp on exon boundaries) Total Coverage: 99.77%
Target region size : 506 kbp No. of Target regions: 2654
Amplicons: 24,797
Design length 150bp Total Sequenceable size: 1.39 Mbp
Minimum recommended sequencing per sample: 277.91 Mbp (Mean 200x)
Discussion Overview
Solid Tumor Assay at the CPD
New Assay Development – Solid v2.0
HaloPlexHS Methodology and Assay Design
Results, Optimization, and Re-Design
Validation Testing
Evaluating the Design Parameter Range Tested Results
Number of samples 40 29
DNA Input range 25ng to 100ng >= 35ng
DNA Source Blood, FPPE Blood (n=6) FPPE (n=23)
DNA Degradation 1% to 20% >18% more duplicates
Variant Profile Known and Blinded Orthogonally verified and
Orthogonally validated
SNV Allele Frequency 0.05% to 100% Detected; prefer additional
unique reads
Indel Allele Frequency (<=18bp)
1% to 100% Detected; prefer additional
unique reads
Reproducibility Duplication rates Within run variability Run to run variability
High with low DNA input and degraded samples
Gene amplifications, Gene Deletions, Indels >18 bp
Pending bioinformatics pipeline optimization
0
10
20
30
40
50
60
70
80
90
100
% of target regionscovered at 100x
% of target regionscovered at 200x
% of target regionscovered at 0.2x mean
% of target regionscovered at 0.1x mean
25ng-35ng (n=3) 50ng (n=18) 100ng (n=5)
Mean Coverage of Target Regions – Unique Reads
0
10
20
30
40
50
60
70
80
90
100
Previously Observed AF
Sequence Run 1 25ng input
Sequence Run 2 50ng input
Sequence Run 3 50ng input
Sequence Run 3 100ng input
Reproducibility A
llele
Fre
qu
ency
0
10
20
30
40
50
60
70
80
90
100
Previously Observed AF
Sequence Run 1 25ng input
Sequence Run 2 50ng input
Sequence Run 3 50ng input
Sequence Run 3 100ng input
Reproducibility A
llele
Fre
qu
ency
*
Variant Type
Expected AF Observed AF Unique Variant
Reads Total Unique Reads
SNV1 5 3.53 12 340
SNV2 1
0.96 1 104 1.94 2 103
0.5 0.95 1 105 SNV 3 0.8 0.77 4 521
SNV 4 0.1 0.19 2 1026 0.22 2 886 0.12 1 824
SNV 5 0.05 0.1 1 924
0.11 1 886 0.06 1 1634
Indel 1 6.26 4.7 34 723 Indel 2 5 5.24 63 1217 Indel 3 4 6.3 8 127 Indel 4 1 0.93 3 324 Indel 5* 1 Not detected 0 283
* Insertion > 150bp
Limits of Detection
Variant Type
Expected AF Observed AF Unique Variant
Reads Total Unique Reads
SNV1 5 3.53 12 340
SNV2 1
0.96 1 104 1.94 2 103
0.5 0.95 1 105 SNV 3 0.8 0.77 4 521
SNV 4 0.1 0.19 2 1026 0.22 2 886 0.12 1 824
SNV 5 0.05 0.1 1 924
0.11 1 886 0.06 1 1634
Indel 1 6.26 4.7 34 723 Indel 2 5 5.24 63 1217 Indel 3 4 6.3 8 127 Indel 4 1 0.93 3 324 Indel 5* 1 Not detected 0 283
* Insertion > 150bp
Limits of Detection
Variant Type
Expected AF Observed AF Unique Variant
Reads Total Unique Reads
SNV1 5 3.53 12 340
SNV2 1
0.96 1 104 1.94 2 103
0.5 0.95 1 105 SNV 3 0.8 0.77 4 521
SNV 4 0.1 0.19 2 1026 0.22 2 886 0.12 1 824
SNV 5 0.05 0.1 1 924
0.11 1 886 0.06 1 1634
Indel 1 6.26 4.7 34 723 Indel 2 5 5.24 63 1217 Indel 3 4 6.3 8 127 Indel 4 1 0.93 3 324 Indel 5* 1 Not detected 0 283
* Insertion > 150bp
Limits of Detection
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
Expected Allele Frequency
Expected and Observed Allele Frequencies
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
Expected Allele Frequency
Observed AF 25ng DNA input
Observed AF 35ng DNA input
Observed AF 50ng DNA input
Expected and Observed Allele Frequencies
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
Expected Allele Frequency
Observed AF 25ng DNA input
Observed AF 35ng DNA input
Observed AF 50ng DNA input
*
*
*
*
Expected and Observed Allele Frequencies
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
Expected Allele Frequency
Observed AF 25ng DNA input
Observed AF 35ng DNA input
Observed AF 50ng DNA input
Expected and Observed Allele Frequencies
Chromosome Position Gene Expected
Frequency Observed AF
@ 25ng Observed AF
@ 35ng Observed AF
@ 50ng
chr1 27101401 ARID1A 32.5 22.7 25.5 21.9
chr1 156785544 SH2D2A 7.5 9.4 7.5 6.8
chr13 32913558 BRCA2 32.5 31.3 36.3 36.3
chr13 28578214 FLT3 10.0 10.4 13.3 11.3
chr17 29552143 NF1 7.5 4.8 8.7 10.8
chr22 30060990 NF2 7.5 7.9 9.9 7.8
chr4 153244155 FBXW7 32.5 32.4 32.0 34.5
chr7 55242465 EGFR 1.9 2.5 1.5 1.3
chr7 116339847 MET 10.0 10.0 5.8 6.1
Expected and Observed Allele Frequencies
Specification Design v1.0 Design v2.0
Read length 150bp 150bp
Probe groups 2 4
Number of genes 153 155
Target region size 505.783 kbp 582.922 kbp
Total Amplicons 24,797 30,600
Target coverage 99.77% 99.81%
On Target Specificity > 98.5% > 98.2%
Total Sequenceable Design 1.39 Mbp 1.43 Mbp
Recommended Sequencing (200x)
277.91 Mbp 286.45 Mbp
Actual Sequencing 694.50 Mbp
(500x) 1.08 Gbp
(750x)
Design Modification
Discussion Overview
Solid Tumor Assay at the CPD
New Assay Development – Solid v2.0
HaloPlexHS Methodology and Assay Design
Results, Optimization, and Re-Design
Validation Testing
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
Expected Allele Frequency
Observed AF 25ng DNA input
Observed AF 35ng DNA input
Observed AF 50ng DNA input
Expected and Observed Allele Frequencies
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
Expected Allele Frequency
Observed AF 25ng DNA input
Observed AF 35ng DNA input
Observed AF 50ng DNA input
Expected and Observed Allele Frequencies - Redesign
Observed AF 50ng DNA Input
*
0.00
5.00
10.00
15.00
20.00
25.00
30.00
Expected AF
Observed AF
Expected and Observed Allele Frequencies - Redesign
Parameters for sample rejection <35ng of DNA and/or >20% degradation
Accuracy 100% concordance of known variants
Precision TSCA validation 10% for assay variability. Intrarun
variability.
Reproducibility Within run and Between runs
Ranges – Reference vs. Reportable (what we tested and detected) vs. Reportable
(what we can test and are capable of detecting)
Analytic Sensitivity vs. Analytic Specificity
100%
Limits of Detection Unique reads (5) and depth of coverage
Orthogonal validation vs. Orthogonal verification
Horizon Dx, Amplicon Based, and Capture Based
Assay Validation and Analytical Parameters
Summary • Accurate identification of somatic mutations in
tumors by NGS is required for enrollment into mutation-specific treatment modalities.
• Our Solid Panel using HaloPlexHS can reliably detect low-level SNVs by tagging DNA fragments with more than a million unique molecular identifiers before PCR.
• This panel will greatly benefit clinical researchers who desire to detect low-level actionable mutations and those who study minimal residual disease.
Acknowledgements
Clinical Lab Alan Fox
David Lieberman Joseph Grubb
Patrick Candrea Barnett Li
Bioinformatics Shrey Sukhadia Ashkan Bigdeli
Dr. Robert Faryabi
Leadership Dr. Kojo Elenitoba-Johnson
Dr. Jennifer Morrissette Joseph Milano
Dr. Josh Zhiyong Wang Brigette Brown-Kipphut
Michelle Filipek
THANK YOU
Agilent Products Described For Research Use Only.
Not for use in diagnostic procedures.
Assay Validation and Analytical Parameters
Parameters for sample rejection
Accuracy
Precision
Reproducibility
Ranges – Reference vs. Reportable
Analytic Sensitivity vs. Analytic Specificity
Limits of Detection
Orthogonal validation vs. Orthogonal verification
Assay Validation and Analytical Parameters Parameters for sample rejection <35ng of DNA and/or >20% degradation
Accuracy – 100% concordance of known variants
Precision – TSCA validation 10% for assay variability. Intrarun variability.
Reproducibility – within run and between runs
Ranges – Reference (what we tested and detected) vs. Reportable (what we can test and are capable of detecting)
(20 normal blood and possibly FFPE normal) – CNV, exon dup/dels, baseline performance of probes assay.
Analytic Sensitivity vs. Analytic Specificity
Limits of Detection – unique reads (5) and depth of coverage
Orthogonal validation vs. Orthogonal verification
Quantity of tumor can be reflected in the mutational allele frequency
25% variant allele frequency
50% Tumor
25% Tumor
Few tumor cells or low allele burden can be more challenging
5% variant allele frequency
10% Tumor
5% Tumor
![WELCOME [] · Personalized Medicine - enabling hypothesis driven patient stratification and individualized diagnostics, therapies and prevention. • Joint initiative of Helmholtz](https://static.fdocuments.in/doc/165x107/5fb73229d198d31d150c9a03/welcome-personalized-medicine-enabling-hypothesis-driven-patient-stratification.jpg)
