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Applying GenomicsApplying GenomicsA Rationale For Genomic Profiling in the Clinics
F d i Z h PhD MBAFrederic Zenhausern, PhD., MBAProfessor & Director, ANBM Center, University of Arizona;Assoc. Dir. MDTV Division, Translational Genomics Research Institute (TGen)Di PMRL S tt d l Cli i l R h I tit tDir. PMRL, Scottsdale Clinical Research Institute
Outline
Applying Genomics in Medical & Public Health Context
Th A h d Ad d T l S t The Approach and Advanced Tool Set
“Omics”, Miniaturization, Next Gen Sequencing...
Toward A Precise, Intelligent, Personalized Medicine
Translational Development Clinical Examples
The 6th Vital Sign: Viewpoint from patients and clinicians
What is the 6th Vital Sign?
1. Blood pressure
2. Pulse
3. Respiration3. Respiration
4. Temperature
5. Pain
6. Context of VulnerabilityyUnifying molecular diagnostics and therapeuticsfor a precise and personal care
Emergency Response Medicine
Who will need: M di l T i 2 G ?•Medical Triage > 2 Gy?
• Mitigating Agent ?• Bone Marrow Transplant?
Medical Countermeasures Against Radiation
Doctors May Risk Overuse of CT ScansNovember 29, 2007November 29, 2007
U.S. not prepared for ‘dirty bomb’ attackCongressional report: Nation lacks labs to test
Radiation Over‐exposure in 16 hospitals in CA
for contamination after blast
Medical scandal in France : 145 French hospital patients overexposed to radiation (February 2008)
July, 2010
p p ( y )
Logistics for Medical CountermeasuresSpecimen collection / identification / processing / InterpretationSpecimen collection / identification / processing / Interpretation
Diagnostics AssaysPlatform Developments
Discovery
Test sample
y
Ex vivo0.5 8G
y
Ex vivoIn Ex1.5 GyControl
S. A. Amundson, et al. Radiat. Res. (2000)
Panel correctly predicted 98% of samples after either 6hrs or 24hrs
74 genes separating samples by dose
Classifying of 10 samples from each dose (5 each at 6 and 24 hours after exposure) using leave one out and nearest centroid classifier
y p p
Dose(G y ) Sensitivity Specificity
F ive ‐dos e pre dic tion0 1 10 1 10.5 1 12 0.9 15 0.5 0.858 0.5 0.875
Fou r‐dose pred ict ion0 1 10 5 1 10.5 1 12 0.9 15 or 8 1 0.967
Agilent Whole Genome PlatformPaul and Amundson (2008) Int J Radiat Oncol Biol Phys, 71:1236
Agilent Whole Genome Platform
Biomarker Performances, ClassifiersE ll t• Excellent– Single biomarkers ensemble classifier– Single components each competent classifiers– Clear connection with process– Simple decision by voting– Modest numbers of samples required toModest numbers of samples required to
validate
• Acceptable– Multiple biomarker aggregate classifier– No single component capable of discrimination– Connection to process vague– Requires multidimensional decision boundary– Large numbers of samples required to validate
Outline
Applying Genomics in Medical & Public Health Context
Th A h d Ad d T l S t The Approach and Advanced Tool Set
“Omics”, Miniaturization, Next Gen Sequencing
Toward A Precise, Intelligent, Personalized Medicine
Translational Development Enabling Workflow Integration and Miniaturization
Cli i l E l Clinical Examples
The 6th Vital Sign: Viewpoint from patients and clinicians
2 DNA Q tifi ti 3 DNA A lifi ti 4 D i
Workflow Integration and Miniaturization1. Sample Preparation 2. DNA Quantification 3. DNA Amplification 4. Detection
6’4’ 6’ 3’ 6’ 6’4 6 3 6 6 6’ 8’
Nanofluidics
45’ Real‐estate for conventional Lab equipment
Nanoarray
J. Gu, F. Zenhausern et al., LOC, 2007
Plastic Electronics
MicrochipNanoarray
J.G. Eden, F.Zenhausern et al. J Ph D A l Ph (2003)
J. Gu, F. Zenhausern et al., JVSTA, 2009
Electronics
J.Z. Wang, F. Zenhausern et al.
J. Phys.D: Appl. Phys., (2003) Appl. Phys, 2006
Miniaturization ‐ Deterministic Hydrodynamic Chip
Circulating Biomarkers – Metastatic Breast Cancer
• only 27% of women diagnosed with MBC will survive to 5 years, median survival of 18 months;
• Lacking ways to monitoring response to therapy and detecting g y g p py grecurrence: often relying on clinician’s experiences and bias
• Current serum tumor markers, such as CA 15‐3, CA 27.29 and CEA lacking sensitivity and specificityCEA lacking sensitivity and specificity
New approach utilizinggenomic profiles generatedfrom isolated CTC patientsamples as a robust predictorf h i i di iof therapeutic indication
during treatment
Fehm et al, Breast Cancer Res., 2010
Next Gen Platforms – Grand challengeCP F b i i f Hi h D i DNA N f S i b H b idi i
Inking:Stamp-2
Inking:Stamp-2
A C G TA C
Round 1
A C G TA C
Round 1Round 1Round 1
nCP Fabrication of High Density DNA Nanoarray for Sequencing by Hybridization
Inking: Tphosphoramidite
Stamp-1
Stamp-2
OH OH
Substrate
TT TPrinting
Inking:Gphosphoramidite
Stamp-2
Inking: Tphosphoramidite
Stamp-1Stamp-1
Stamp-2
OH OH
Substrate
TT T
Stamp-2Stamp-2
OH OH
Substrate
TT TOH OH
Substrate
TTTT TTPrinting
Inking:Gphosphoramidite
Stamp-2
Round 1
Round 2 C
G
T
C
A C G TA C G TA C G T
Round 1
Round 2 C
G
T
C
A C G TA C G TA C G T
Round 1
Round 2
Round 1
Round 2 C
G
T
C
A C G TA C G TA C G T
Stamp-1
PrintingStamp-1
G TT TG
Stamp-1Stamp-1
PrintingStamp-1Stamp-1
G TT TG GG TTTT TTGG
ou d
Round 3
A A
C
G
T
A C G T
ou d
Round 3
A A
C
G
T
A C G T
ou d
Round 3
ou d
Round 3
A A
C
G
T
A C G T
OHOH OHOHOH
OHOH OHOHOH
Substrate
G
Substrate
TT TG
Cycle entry 1. Capping OHOH OHOHOHOHOH OHOHOHOHOH OHOHOH
OHOH OHOHOH
Substrate
OHOH OHOHOH
Substrate
OHOH OHOHOHOHOH OHOHOH
Substrate
G
Substrate
TT TG GG
Substrate
TTTT TTGG
Cycle entry 1. Capping Round 4
ACGT ACGT ACGT ACGTA A A A AC AC AC AC
CAC
AC
A
A
A
A
Round 4
ACGT ACGT ACGT ACGTA A A A AC AC AC AC
CAC
AC
A
A
A
A
Round 4Round 4
ACGT ACGT ACGT ACGTA A A A AC AC AC AC
CAC
AC
A
A
A
CAC
AC
A
A
A
A
OHOH OHOHOH
Substrate
G
Substrate
TT TG 2. Oxidation3. Deprotection
OHOH OHOHOH
Substrate
OHOH OHOHOH
Substrate
G
Substrate
TT TG G
Substrate
TT TG GG
Substrate
TTTT TTGG 2. Oxidation3. Deprotection
Probe length Chemical steps Number of possible probes4 16 2566 24 4096
10 40 1,048,57616 64 4 294 967 296
Round 4
AC
AC
A
A
Probe length Chemical steps Number of possible probes4 16 2566 24 4096
10 40 1,048,57616 64 4 294 967 296
Round 4
AC
AC
A
A
Probe length Chemical steps Number of possible probes4 16 2566 24 4096
10 40 1,048,57616 64 4 294 967 296
Round 4Round 4
AC
AC
A
A
AC
AC
A
A
16 64 4,294,967,29616 64 4,294,967,29616 64 4,294,967,296Unpublished data, Gu et al.
Printed high density nanoarrays (10 billion/cm2)
nCP Stamp Sub‐100 nm AlignmentCold welded Au array
Streptavidin protein array100 nm size/250 nm period
5 µm
Multilayer Printing of Nucleoside Phosphoramiditeon Nanoarray
Personal Genomics on the Next Gen Platform: Personal Genomics on the Next Gen Platform: Genomic Data Generation/CaptureGenomic Data Generation/Capture
SOLiD Sequencing and Genome Interrogation John Carpten
Whole Genome Sequencing @ 30X Coverage; Tumor and Matched Normal DNA
• Point Mutations• IndelsIndels• Translocations and Breakpoints• Copy Number• SNP Data from Drug Metabolism Genes
Whole Transcriptome Sequencing
• Exon Level Gene ExpressionExon Level Gene Expression• Exon Usage• Allele Specific Expression
Genome Sequencing Data AnalysisGenome Sequencing Data Analysis
David CraigComputing time (wall‐time) per sample
Whole Genome Alignment (based on corona_litesoftware)software)
400 Million 35 mer run takes 3 days1200M reads will take ~ 9 days @ 35 mer
50 mers, ~ 15 days (20x) Ed Suh
Annotation and Conversion to standard format 2‐days
AnalysisIndels/MatePair + SNP calling + Assembly etc. ~ 3 d~ 3 days
Total Computing time per sample=20 days Sonora Supercomputer(SGI Altix)
48 Cores 576 GB shared48 Cores, 576 GB shared RAM
Outline
Applying Genomics in Medical & Public Health Context
Th A h d Ad d T l S t The Approach and Advanced Tool Set
“Omics”, Miniaturization, Next Gen Sequencing
Toward A Precise, Intelligent, Personalized Medicine
Translational Development Clinical Examples
The 6th Vital Sign: Viewpoint from patients and clinicians
A Lot of People Talk About Personalized Medicine
1. But who is really doing it?
2 All h i i t t ti li d 2. All physicians try to practice personalized
medicine
• Take good care of a person
3 L t’ id th t3. Let’s consider another term
• “Precision Medicine” (because nurses and
doctors already practice personalized
medicine)medicine)
Clinical Studies To Test Personalized Genomics
i i i h (fi i i ) i l11,935 participants in 460 phase I (first in patients) trials new anticancer agents led to a response rate (shrink by ≥ 30%) = 4.4%
Validate hypothesis that we can help patients with RefractoryAdvanced Cancer by profiling individual patient’s tumors
1. Performed a pilot trial to see how often targets are present in patients referred for phase I studies whose tumors have progressed on all standard therapies (logistics, sample size etc.) ‐ Target Now( g , p ) g
2. Performing a prospective clinical trial – Bisgrove Trial
Using a treatment suggested by a molecular profiling approach would favorably
3. Deeper studies – Triple Negative Breast Cancer, pancreas solid tumor
Using a treatment suggested by a molecular profiling approach would favorably change the clinical course for an individual patient with refractory cancer
Target Now (pilot trial)1 112 patients referred for phase I studies (had exhausted conventional1. 112 patients referred for phase I studies (had exhausted conventional
chemotherapy options, undergoing procedures for a cancer‐related matter –e.g. obstruction)
2. Patients tissues submitted for molecular profiling in 2 formats: (i) Paraffin embedded tumor samples submitted for immunohistochemistry (IHC) (ER, Kit, etc.) and (ii) Frozen tumor samples processed for oligonucleotidei (OMA)microarray (OMA)
IHC results
Microarray results
Methods– Overview Mechanics9 national sites9 national sites
Selection of treatment for the patient based on MP results –i h f ll i l i hvia the following algorithm
• IHC/FISH and microarray indicates same target
• IHC positive result alone
• Microarray positive result alone
Results: Primary Endpoint: PFS Ratio ≥ 1.3 By Tumor Type
Tumor type Total treated Number with PFS ratio≥ 1.3 (%)
Breast 18 8 44Colorectal 11 4 36Ovarian 5 1 20Miscellaneous* 32 5 16
66 18 27Miscellaneous tumor types with PFS ratio ≥ 1.3 included: lung 1/3,
Cholangiocarcinoma 1/2, Mesothelioma 1/2, Eccrine sweat 1/1, GIST (gastric) 1/1Cholangiocarcinoma 1/2, Mesothelioma 1/2, Eccrine sweat 1/1, GIST (gastric) 1/1
The hypothesis was that ≤ 15% of this patient population would have a PFS ratio of ≥ 1.3 BUT in this study ‐ 27% did !!!
Clinicians selected new drugs they would have not selected for the 18 patients before MP
Conclusion
• “Applied” Genomics is translating in clinical settings for personal care, as well as in emergency response
• Multidimensional information requires combining a multitude of advanced molecular tools and sophisticated algorithms and databases to recover intelligent g gknowledge
• New clinical trial models are demonstrating faster development cycles and may provide more appropriatedevelopment cycles and may provide more appropriate therapies
• Some cancers may benefit from precision medicine y pmaking them more like “chronic” diseases
Acknowledgments
SCRI / Tgen Clinical Services
• D. von Hoff
UofA/TGen
• M BrenguesD. von Hoff• R. Ramanathan• M. Bittner
M. Brengues• J. Gu• J. Yang
• J. Trent• R. Korn
g• S. Rogers• H. Cuntliffe
• M. Slater • J. Carpenten• S. Amundson (CU)
We are grateful to all our sponsors, co‐workers and all the patients and their families for their outstanding support and commitmentfamilies for their outstanding support and commitment