From Discovery to Clinical Assay - Tecanww3.tecan.com/platform/content/element/9549/1-4rosenblatt.pdf · Pre‐Term Labor 4 Million Births ... Cases Percent Correct L N=133 NIL N=175

Kevin P. Rosenblatt, M.D., Ph.D.Kevin P. Rosenblatt, M.D., Ph.D.Associate Professor of Molecular MedicineAssociate Professor of Molecular MedicineDirector, Center for Clinical ProteomicsDirector, Center for Clinical Proteomics

Centers for Proteomics and Systems BiologyCenters for Proteomics and Systems BiologyBrown Foundation Institute of Molecular MedicineBrown Foundation Institute of Molecular Medicine

&&CoCo‐‐Director, Proteomics CoreDirector, Proteomics Core

Center for Clinical and Translational ScienceCenter for Clinical and Translational ScienceDepartment of PathologyDepartment of Pathology

UTUT‐‐Health Science Center HoustonHealth Science Center Houston

Phone: (713) 500Phone: (713) 500‐‐3611 3611 Fax: (713) 500Fax: (713) 500‐‐24202420EE‐‐mail: mail: [email protected]@UTH.TMC.edu

Sarofim Research BuildingSarofim Research Building1825 Pressler Street1825 Pressler StreetHouston, Texas 77030Houston, Texas 77030

Disclosure:Disclosure:Dr. Rosenblatt is a founder of Dr. Rosenblatt is a founder of

Risk Assessment Laboratories, LLCRisk Assessment Laboratories, LLC

RAL, LLC has a sponsored research agreement RAL, LLC has a sponsored research agreement with UT HSC and the IMMwith UT HSC and the IMM

RAL, LLC received funding from PerkinElmer RAL, LLC received funding from PerkinElmer InternationalInternational

From Discovery to Clinical Assay From Discovery to Clinical Assay

Clinical Proteomics: Translating Biomarkers from Clinical Proteomics: Translating Biomarkers from Bench to BedsideBench to Bedside

Discovery, Verification and Validation of Circulating Discovery, Verification and Validation of Circulating Biomarkers for Predicting PreBiomarkers for Predicting Pre‐‐Term DeliveryTerm Delivery

Pre term birthsPre term birthsCLINICAL IMPLICATIONSCLINICAL IMPLICATIONS

Impacts 12% of all deliveries and rising: Impacts 12% of all deliveries and rising: ‐‐ 500,000 cases per year. To 500,000 cases per year. To date, no strategies have been effective; rate is higher in certadate, no strategies have been effective; rate is higher in certain in populations (e.g. African Americans, >18% in some studies).populations (e.g. African Americans, >18% in some studies).

Costs the US over $40 Billion per yearCosts the US over $40 Billion per year

Preterm babies are far more likely to suffer from cerebral palsyPreterm babies are far more likely to suffer from cerebral palsy and and other lifelong, debilitating conditions (learning disabilities)other lifelong, debilitating conditions (learning disabilities)

TheThe accurateaccurate identification of mothers at high risk for PTB will drive identification of mothers at high risk for PTB will drive medical decisions that actually prolong pregnancy and prevent demedical decisions that actually prolong pregnancy and prevent delivery livery of premature babiesof premature babies

The The accurateaccurate identification of patients that are not at high risk for identification of patients that are not at high risk for premature birth will support medical decisions to let the patienpremature birth will support medical decisions to let the patient go t go home and will save millions of dollars per yearhome and will save millions of dollars per year

The The accurateaccurate identification of patients at high risk will support modern identification of patients at high risk will support modern clinical trials by selecting the right patientsclinical trials by selecting the right patients

Significant Public CostsSignificant Public Costs

March of Dimes (2003)March of Dimes (2003)

Cost of uncomplicated birth and hospital stay; $1700Cost of uncomplicated birth and hospital stay; $1700

Cost of pre term birth and hospital stay; $77,000Cost of pre term birth and hospital stay; $77,000

Subsequent cost per infant; >$100,000Subsequent cost per infant; >$100,000

High Risk WomenHigh Risk Women1.2 Million/Year1.2 Million/Year

Routine testingRoutine testingPhysicianPhysician’’s Offices Office

Annual Health Care SavingsAnnual Health Care SavingsTBDTBD

Negative Test ResultsNegative Test ResultsMaintain pregnancy at homeMaintain pregnancy at home

Positive Test Results1. Admit to Hospital

2. Ambulatory with treatment

Low Risk WomenLow Risk Women2.8 Million/Year2.8 Million/Year

PrePre‐‐Term LaborTerm Labor

4 Million Births/Year4 Million Births/Year

Assay development

Assay development

Biomarker Discovery & Development PipelineBiomarker Discovery & Development Pipeline

EndEnd‐‐Use Clinical AssayUse Clinical Assay

The declining rate of introduction of new protein tests, for allThe declining rate of introduction of new protein tests, for all diseases. The data are plotted diseases. The data are plotted to indicate the declining rate of introduction of new protein anto indicate the declining rate of introduction of new protein analytes in alytes in

FDAFDA‐‐approved or approved or ‐‐cleard clinical tests.cleard clinical tests.Revised: FDARevised: FDA‐‐cleared or cleared or ‐‐approved protein tests approved under CLIA regulations since 199approved protein tests approved under CLIA regulations since 19933

The Declining Rate of FDAThe Declining Rate of FDA‐‐Approved or Approved or ‐‐Cleared Blood Cleared Blood Borne Biomarkers to Reach the Clinical Lab Borne Biomarkers to Reach the Clinical Lab

Anderson and Anderson (2002)Anderson and Anderson (2002)Molecular & Cellular ProteomicsMolecular & Cellular ProteomicsVol. 1: 845Vol. 1: 845‐‐867. 867.

New Serum/Plasma Biomarker Discovery: A Dynamic ProblemNew Serum/Plasma Biomarker Discovery: A Dynamic Problem

Serum/Plasma Protein Pattern Serum/Plasma Protein Pattern DiagnosticsDiagnostics

ProteinsProteins

PatientPatient

Mass SpectroscopyMass Spectroscopy

Proteomic Proteomic ImageImage Pattern Pattern

RecognitionRecognitionLearning Learning AlgorithmAlgorithm

Early Early diagnosis of diagnosis of diseasedisease

Early Early warning of warning of toxicitytoxicity

Collisional CoolingCollisional Cooling

OrthogonalOrthogonalTime of flight tubeTime of flight tube

OrthogonalOrthogonalQuadrupoleQuadrupoleSELDI/MALDISELDI/MALDI

LaserLaser

Protein ChipProtein Chip

IonsIons

SourceSource

Ana

lyzer

Ana

lyzer

Detector

Detector

Biomarker DiscoveryBiomarker DiscoveryprOTOF 2000: Orthogonal MALDI and SELDIprOTOF 2000: Orthogonal MALDI and SELDI

Cibachron Blue Affinity Enrichment of Biomarkers Cibachron Blue Affinity Enrichment of Biomarkers Bound to Carrier ProteinsBound to Carrier Proteins……

Serum BiomarkerSerum Biomarker ProfilingProfiling PlatformPlatform

••Automated Sample Automated Sample Preparation Using Preparation Using MULTIPROBE IIMULTIPROBE II

••Affinity capture Albumin Affinity capture Albumin carrying biomarkerscarrying biomarkers

••Desalt and Concentrate Desalt and Concentrate Biomarkers ZipPlateBiomarkers ZipPlate™™

••Direct transfer onto Direct transfer onto MALDI plateMALDI plate

prOTOF prOTOF AnalysisAnalysis

Protein Samples (Serum)Protein Samples (Serum)

NormalNormal

CancerCancer

Discrim

inatory

Discrim

inatory

Analysis

Analysis

Biom

arker

Biom

arker

Barcod

esBa

rcod

es

AlbuminAlbumin

ROBOTICSROBOTICS

Clinical Samples for DiscoveryClinical Samples for Discovery•• Initial sample of 100 to train computer algorithmsInitial sample of 100 to train computer algorithms

50 Not50 Not‐‐inin‐‐Labor patientsLabor patients

50 Labor patients50 Labor patients

Some PTL in Labor cohortSome PTL in Labor cohort

Patient EthnicitiesPatient Ethnicities

CaucasianCaucasian 6%6%Part CaucasianPart Caucasian 28%28%FilipinoFilipino 21%21%JapaneseJapanese 10%10%Pacific IslanderPacific Islander 12%12%OtherOther 23%23%

Term Delivery vs. PTDTerm Delivery vs. PTD

•• Term Labor (Term Labor (>>37 wks)37 wks) n=39n=39

•• PTD Labor(<37 wks)PTD Labor(<37 wks) n=11 n=11 2424‐‐28 wks28 wks 11

2828‐‐32 wks32 wks 88

3232‐‐34 wks34 wks 22

•• NotNot‐‐inin‐‐LaborLabor n=50n=50includes includes ““symptomatic termssymptomatic terms”” or R/O PTLor R/O PTL

Patient CharacteristicsPatient Characteristics

MeanMeanAverage ageAverage age 27.2 yrs27.2 yrs

EGA at delEGA at del 36 wks 5 days36 wks 5 days

Birth WeightBirth Weight 3200 g3200 g

EGA at drawEGA at draw 35 wks35 wks

Biomarker DiscoveryBiomarker Discovery

# SVM + Markov Blanket# SVM + Markov Blanket

hyperplane

hyperplane

optimalhyperplane

Maximummargin )(

1i

l

iii xyW

Oh, J.H., Nandi, A., Gurnani, P., Bryant-Greenwood, P., Rosenblatt, K.P., and Gao, J. (2006) Prediction of labor for pregnant women using high-resolution mass spectrometry data. Proceedings of the Sixth IEEE International Symposium on BioInformatics and BioEngineering (BIBE 2006) 2006: 332-339, 16-18 October 2006, Arlington, Virginia, USA.

BioInformaticsBioInformatics

Oh et al. (2006) Sixth IEEE Symposium on BionInformatics and BioOh et al. (2006) Sixth IEEE Symposium on BionInformatics and BioEngineering (BIBE'06)Engineering (BIBE'06)

0

5

10

15

20

25

30

35

40

45

0 1000 2000 3000 4000 5000 6000 7000

Non-laborLabor

Four Marker PTD PanelFour Marker PTD PanelRe

lative In

tensity

Relative In

tensity

m/z Values in Daltonsm/z Values in Daltons

Mass Spectrometry Methods for Discovery Mass Spectrometry Methods for Discovery and Protein Identificationand Protein Identification

m/z

1.1. PBEF: PBEF: Differentiation factor, enzyme (Nampt), adipokine (? aka Differentiation factor, enzyme (Nampt), adipokine (? aka Visfatin), released from stretched fetal membranes, recently Visfatin), released from stretched fetal membranes, recently discovered by other labs, discovered by other labs, MSMS‐‐based discovery, verificationbased discovery, verification

2.2. APO C1: APO C1: Lipid metabolism, protects Tg mice from obesity and Lipid metabolism, protects Tg mice from obesity and

insulin resistance, discovered by other labsinsulin resistance, discovered by other labs, , MSMS‐‐based discovery, based discovery, verificationverification

3.3. RBP4: RBP4: Adipokine, recently independently discovered by other Adipokine, recently independently discovered by other labs, labs, MSMS‐‐based discovery, verificationbased discovery, verification

4.4. ILIL‐‐6: 6: Inflammatory cytokine, adipokine, insulin sensitivity Inflammatory cytokine, adipokine, insulin sensitivity literature, verificationliterature, verification

5.5. Relaxin 2: Relaxin 2: Peptide hormone, insulin sensitivity, Peptide hormone, insulin sensitivity, discovery & discovery & literature, verificationliterature, verification

6.6. ILIL‐‐8:8: Inflammatory cytokine, Inflammatory cytokine, literature, verificationliterature, verification

7.7. CARD12:CARD12: Apoptosis regulator, Apoptosis regulator, discovery discovery

8.8. Transferrin: Transferrin: Iron metabolism, Iron metabolism, discovery discovery

Markers Selected via Biased and Unbiased ApproachMarkers Selected via Biased and Unbiased Approach

P

PP

P

P

P

Laser

Biomarker Qualification: ImmunoBiomarker Qualification: Immuno‐‐Mass SpectrometryMass Spectrometry

P

PP

PP

PrePre‐‐Term Labor Term Labor PrePre‐‐EclampsiaEclampsia Term LaborTerm Labor

MicroArray Spotted Patient SpecimensMicroArray Spotted Patient Specimens

Quantum DotQuantum Dot‐‐Labeled Labeled

AntibodiesAntibodies

PPP

P

P P

PP

P

PP

Phosphorylated Phosphorylated Target ProteinTarget Protein

High Throughput Marker VerificationHigh Throughput Marker Verification

LaborLabor

NILNIL

PE, PIHPE, PIH

Labor MarkerLabor Marker

Patient SamplesPatient Samples

Labor MarkerLabor Marker

Verification: HT Parallel Quantitative ScreeningVerification: HT Parallel Quantitative Screening

Clinical Samples for VerificationClinical Samples for Verification

•• 325 Patients of mixed ethnic groups from 24 325 Patients of mixed ethnic groups from 24 ‐‐38 38 weeksweeks 155 In labor within 48 hours of sample155 In labor within 48 hours of sample

168 Not in labor within 48 hours of sample168 Not in labor within 48 hours of sample

Including about 50 preIncluding about 50 pre‐‐term labor samples term labor samples

Term Delivery vs. PTDTerm Delivery vs. PTD

•• Term (Term (>>37 wks)37 wks) n=268n=268

•• PTD (<37 wks)PTD (<37 wks) n=57 n=57 –– 2424‐‐2828 33

2828‐‐3232 88

3232‐‐3434 88

>>3434 38 (4 questionable EDC38 (4 questionable EDC’’s)s)

Patient CharacteristicsPatient Characteristics

MeanMean Std devStd devAverage ageAverage age 27.47 yrs27.47 yrs (6.182)(6.182)

EGA at delEGA at del 36.70 wks36.70 wks (4.635)(4.635)

Birth WeightBirth Weight 3175 g3175 g (729.3789)(729.3789)

EGA at drawEGA at draw 35.06 wks35.06 wks (6.02)(6.02)

Total number of samples = 325Total number of samples = 325

Preeclampsia= 22Preeclampsia= 22

Intrauterine infection (histologic confirmation)= 14Intrauterine infection (histologic confirmation)= 14

Gestational diabetes= 37Gestational diabetes= 37

Patient EthnicitiesPatient Ethnicities

# # % %

CaucasianCaucasian 2121 6.46%6.46%

Part CaucasianPart Caucasian 9292 28.31%28.31%

FilipinoFilipino 7070 21.54%21.54%

JapaneseJapanese 3434 10.46%10.46%

Pacific IslanderPacific Islander 4040 12.31%12.31%

Other AsianOther Asian 6868 20.92%20.92%

No Labor at Draw (n=112)No Labor at Draw (n=112)

Average age Average age 27.227.2 yrsyrs (6.067)(6.067)EGA at drawEGA at draw 32.1wks32.1wks (5.356)(5.356)EGA at delEGA at del 38.838.8 wkswks (1.8673)(1.8673)Birth WeightBirth Weight 3356g3356g (698.8)(698.8)PTD (<37wks)PTD (<37wks) n=3n=3(+) ruptured membranes(+) ruptured membranes(+) advanced cervical dilation(+) advanced cervical dilation excludedexcluded

(+) strong persistent contractions(+) strong persistent contractions


QDot Protein Array Serum Assays

PTL Labor GBS+ NIL

PBEF

Recombinant StDLabor PTD

Not in Labor ROC plot In Labor ROC plot

Classification and Regression TreesClassification and Regression Trees

Class

NCases

N Mis-Classe

d

PctError

Cost

L 142 20 14.08 0.14NIL 166 11 6.63 0.07

Misclassification for Learn DataMisclassification for Learn DataClas

sN

CasesN Mis-Classe

d

PctError

Cost

L 142 66 46.48 0.46NIL 166 74 44.58 0.45

Misclassification for Test DataMisclassification for Test Data

ActualClass

TotalCases

PercentCorrect

LN=133

NILN=175

L 142 85.915 85.915 14.085

NIL 166 93.373 6.627 93.373

Prediction SuccessPrediction Success

VariableVariable ScoreScoreME3ME3 100.00 ||||||||||||||||||||||||||||||||||||||||||

PBEFPBEF 75.39 |||||||||||||||||||||||||||||||

PBG2PBG2 62.18 ||||||||||||||||||||||||||

JL7JL7 59.55 |||||||||||||||||||||||||

BG4BG4 58.65 ||||||||||||||||||||||||

KPR5KPR5 58.44 ||||||||||||||||||||||||

1.1. PBEF: PBEF: Differentiation factor, enzyme (Nampt), adipokine (? aka Differentiation factor, enzyme (Nampt), adipokine (? aka Visfatin), released from stretched fetal membranes, recently Visfatin), released from stretched fetal membranes, recently discovered by other labs, discovered by other labs, MSMS‐‐based discovery, verificationbased discovery, verification

2.2. APO C1: APO C1: Lipid metabolism, protects Tg mice from obesity and Lipid metabolism, protects Tg mice from obesity and

insulin resistance, discovered by other labsinsulin resistance, discovered by other labs, , MSMS‐‐based discovery, based discovery, verificationverification

3.3. RBP4: RBP4: Adipokine, recently independently discovered by other Adipokine, recently independently discovered by other labs, labs, MSMS‐‐based discovery, verificationbased discovery, verification

4.4. ILIL‐‐6: 6: Inflammatory cytokine, adipokine, insulin sensitivity Inflammatory cytokine, adipokine, insulin sensitivity literature, verificationliterature, verification

5.5. Relaxin 2: Relaxin 2: Peptide hormone, insulin sensitivity, Peptide hormone, insulin sensitivity, discovery & discovery & literature, verificationliterature, verification

Markers Selected via Biased and Unbiased ApproachMarkers Selected via Biased and Unbiased Approach

6.6. ILIL‐‐8:8: Inflammatory cytokine, Inflammatory cytokine, literature, verificationliterature, verification

7.7. CARD12:CARD12: Apoptosis regulator, Apoptosis regulator, discovery discovery

8.8. Transferrin: Transferrin: Iron metabolism, Iron metabolism, discovery discovery

0.0

0.2

0.4

0.6

0.8

1.0

0.0 0.2 0.4 0.6 0.8 1.0

Sens

itivi

ty1 - Specif icity

ROC Integral0.982

NIL

0.0

0.2

0.4

0.6

0.8

1.0

0.0 0.2 0.4 0.6 0.8 1.0

Sens

itivi

ty

1 - Specif icity

ROC Integral0.982

L


PBG2PBG2

ME3ME3

BG4BG4

KPR5KPR5

Fetal FibronectinFetal Fibronectin SENSSENS SPECSPEC PPVPPV NPVNPV

Current Gold Standard testCurrent Gold Standard test 21.4%21.4% 94.5%94.5% 30%30% 91.6%91.6%

If Spec is set at 95%, and prevalence of preIf Spec is set at 95%, and prevalence of pre‐‐term birth = term birth = 12% then a fair comparison can be made12% then a fair comparison can be made

Statistical ComparisonsStatistical Comparisons

FDA Approved TestFDA Approved Test

MultiMarker Blood Test: BirthStatMultiMarker Blood Test: BirthStatPredicts Birth in <48 hoursPredicts Birth in <48 hours

IMM Clinical ValidationIMM Clinical Validation•• Validation StudiesValidation Studies

–– Standardized collection SOP in placeStandardized collection SOP in place–– Must have broad ethnic diversity (Caucasian, African, Must have broad ethnic diversity (Caucasian, African, Hispanic, Asian/Pacific Islander)Hispanic, Asian/Pacific Islander)

•• CollaboratorsCollaborators–– Dr. Roberto Romero et al./NICHD: freezer & prospective Dr. Roberto Romero et al./NICHD: freezer & prospective collection at Hutzel: 750 to 1000 Pt. samplescollection at Hutzel: 750 to 1000 Pt. samples•• Hundreds of PTL in freezerHundreds of PTL in freezer•• Matched control specimensMatched control specimens•• Study ready to go on 228 patients with fFN valuesStudy ready to go on 228 patients with fFN values

–– Ram Menon et al./Emory/UTMB: 192 samples Ram Menon et al./Emory/UTMB: 192 samples –– Includes high risk population Includes high risk population –– About 50%/50% African Americans/CaucasiansAbout 50%/50% African Americans/Caucasians

•• Long term prospective trial is planned!Long term prospective trial is planned!

Reaction Monitoring Increases Signal:Noise for Target Reaction Monitoring Increases Signal:Noise for Target DetectionDetection

m/z

m/z

Q3 monitors only characteristic fragments 158 and 191 from ion 210 for quant and qual.

160

158

Multiple/Selective Reaction Monitoring (MRM/SRM)Multiple/Selective Reaction Monitoring (MRM/SRM)

Quad Mass Filter (Q3)Quad Mass Filter (Q1)

Collision Cell

170 210 250 290

210

222

268 280165

Spectrum with background ions(from ESI)

Q1 lets only target ion 210 pass through

190 210

210

Collision cell breaks ion 210 apart

150 170 190 210

210158

191

190

191

minimized chemical background

Ion source

214 214

160 193 160 193

= Isotope Standards

Serum ImmunoSerum Immuno‐‐SRM assays: Validation PlatformSRM assays: Validation Platform(SRM: Selected Reaction Monitoring)(SRM: Selected Reaction Monitoring)

Serum/plasma Samples

ProcessingProcessing

Wash and EluteWash and Elute

Agilent 6430Agilent 6430

AnalysisAnalysis

ApoC1ApoC1

VisfVisf‐‐AA

VisfVisf

RBP4RBP4

Dynamic range : 5X 101 to 2 x 105

VisfatinVisfatin

LOD: 112 amol (7.11nM)LOQ: 500 amol (31.7 nM)Analyte response (slope): 0.835Correlation coefficient: 0.997CV: 0.79 -18.30 %CV (mean): 5.54%Linear dynamic range:>500

36 SRM transitions of tryptic digested peptides from patient sam36 SRM transitions of tryptic digested peptides from patient samplesples

ApoC1ApoC1 IL6IL6 PBEFPBEF‐‐bb PBEFPBEF‐‐aa Relaxin2Relaxin2 RBP4RBP4

Plasma SRM assays: 3 Replicates of a Plasma SRM assays: 3 Replicates of a Patient Sample and 3 Different SamplesPatient Sample and 3 Different Samples

4

FIRST PASS: FIRST PASS: DELIVERY IN 2 DAYSDELIVERY IN 2 DAYS

•• FRESH run ffN vs up to 12 FRESH run ffN vs up to 12 years for SRM assayyears for SRM assay

•• 128 specimens128 specimens

•• BirthStat algorithm requires BirthStat algorithm requires more iterations before more iterations before completecomplete

PRELIMARY COMPARISIONPRELIMARY COMPARISION

ffN RAL

Sensitivity 66.7% 66.7%

Specificity 73.9% 99.2%

PPV 16.2% 85.7%

NPV 96.7% 97.5%




•• RAL algorithm (here with RAL algorithm (here with only 2 parameters) only 2 parameters) designed to maximize designed to maximize sensitivity at expense of sensitivity at expense of specificityspecificity–– requires more iterations requires more iterations

before completebefore complete


ffN RAL

Sensitivity 73.7% 100%


PPV 37.8% 19.0%

NPV 94.5% 100%




•• RAL algorithm (here with only RAL algorithm (here with only 2 parameters) designed to 2 parameters) designed to maximize sensitivity at maximize sensitivity at expense of specificityexpense of specificity–– requires many more iterations requires many more iterations

before completebefore complete


ffN RAL



PPV 45.9% 23.5%

NPV 92.3% 96.7%

2011 SRM 2011 SRM ValidationValidation of BirthStat: of BirthStat: Predicts PTB <48 hrsPredicts PTB <48 hrs

ffN RAL



PPV 16.2% 85.7%

NPV 96.7% 97.5%

2007 Protein Microarray 2007 Protein Microarray VerificationVerification of BirthStatof BirthStatPredicts PTB <48 hoursPredicts PTB <48 hours

2011 SRM 2011 SRM Phase II ValidationPhase II Validation of BirthStat: New Cohort of BirthStat: New Cohort

(192 Patients from Emory) (192 Patients from Emory)

Predicts PTB <48 hrs by RacePredicts PTB <48 hrs by Race

Newest SRM Newest SRM AssaysAssays for Biomarker Validation for Biomarker Validation Down to Zeptomole SensitivityDown to Zeptomole Sensitivity

SRM

PBEF Stretch modelPBEF Stretch model

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

PBEF

↑ MMP-1↑ MMP-3

↑ IL-1β↑ TNF-α↑ IL-6

Feed-forward

↑ IL-1↑ TNF-α↑ IL-6

PBEFPBEFPBEF

PBEF

Stretch Stretch

Membrane weakening

Stretch/releaseIL-8

Neutrophils(express PBEF)

Build theSRM Table

Interrogate Interrogate clinical clinical samples samples LCLC‐‐MS/MSMS/MS

OrbiTrapOrbiTrap

SRMs SRMs Triple QuadrupolesTriple Quadrupoles

DiscoveryDiscovery VerificationVerification‐‐Validation Validation ClinicClinic

SRM Workflow SW

Discovery SW

Collect raw Collect raw msms

discovery discovery datadata


Thermo VantageThermo Vantage

IMM/RAL, LLC: Discovery to Clinical ValidationIMM/RAL, LLC: Discovery to Clinical Validation

LCLC‐‐MS/MSMS/MS6538 QToF6538 QToF

Biomarker Discovery and Development Timeline

1 2 3 4 5 6 7Discovery > Proof of Principle > Clinical Configuration > Biomarker Validation > CLIA Home Brew > IVD > PCO

1 Year 1 Year 0.5 Year

Q1-4, Q3 Q4 Q1 Q1 Completed Completed Completed 2010-11 2011 2013 2014

>300 SamplesPublication

750-1000 SamplesSympt. and Asympt.Statistical analysisPublications

FDA Submission

POCSubmission

Operations/ManagementFinal Assay DevelopmentClinical TrialsPublication/Marketing

Home Brew Marketing

FDA Trial

IVD Manufacturing

IVD MarketingPOC ManufacturingPOC Marketing

$??M$??M$??M

$??M

$??M

$??M$??M

$??M

ConclusionsConclusions1.1. Biomarker discovery should follow a carefully designed Biomarker discovery should follow a carefully designed

workflow separated into different clinical phases.workflow separated into different clinical phases.

2.2. Well selected samples clinical samples, with increasing Well selected samples clinical samples, with increasing numbers, should be used in each phase, generalizing to a numbers, should be used in each phase, generalizing to a broader patient population.broader patient population.

3.3. Research and clinical assays and assay platforms should be Research and clinical assays and assay platforms should be carefully designed to suit the particular clinical phase of a carefully designed to suit the particular clinical phase of a studystudy——an endan end‐‐use clinical platform is not a research platform use clinical platform is not a research platform and vice versa.and vice versa.

4.4. SRM technologies can move protein markers into the SRM technologies can move protein markers into the commercialization phase.commercialization phase.

5.5. A consortium of experts, including clinicians, basic scientists,A consortium of experts, including clinicians, basic scientists,bioinformaticists and biostatisticians, technologists, industry,bioinformaticists and biostatisticians, technologists, industry,and regulatory experts is needed to properly develop the next and regulatory experts is needed to properly develop the next generation of screening markers for the clinic.generation of screening markers for the clinic.

Acknowledgements: UTHSC/IMM, UTMB, and UTSW LabsAcknowledgements: UTHSC/IMM, UTMB, and UTSW Labs

•• Reynolds BrobeyReynolds Brobey

•• Proteomics discovery workProteomics discovery work

•• Proteomics signaling assaysProteomics signaling assays

•• Nataliya Bulayeva and Li LiNataliya Bulayeva and Li Li

•• PTB SRM/MRMsPTB SRM/MRMs

•• Sample PrepsSample Preps

•• Mehdi DehghaniMehdi Dehghani

•• Sample PrepsSample Preps

•• Proteomics signaling assays and SRMsProteomics signaling assays and SRMs

NIH Funding: AG025326‐01, AG19712‐5, RFP‐NIH BAA‐HL‐02‐04 NSF: 04‐528 (#0612214)

IMM and UTMB

Prem Gurnani, Johanne Pastor, Animesh Nandi, Kiran Sikder, Dwight German, and “Skip” Garner UT Southwestern

Jean Gao, Jun Ho Oh, Young Bun Kim UT Arlington

4 Key Measures4 Key Measures

•• SensitivitySensitivity•• SpecificitySpecificity•• Positive predictive valuePositive predictive value•• Negative predictive valueNegative predictive value

TestTest

DiseaseDisease

++

++

--

AA BB

CC DD

--

Proportion of people with the disease whoProportion of people with the disease whotest positive.test positive.

SensitivitySensitivity

++

++

--

AA BB

CC DD

--

A A A + CA + C

Probability that a person without the disease Probability that a person without the disease will be correctly identified by the test.will be correctly identified by the test.

SpecificitySpecificity

++

++

--

AA BB

CC DD

--

DDB + DB + D

Probability of actually being affected withProbability of actually being affected withdisease given a positive test result.disease given a positive test result.

Positive Predictive ValuePositive Predictive Value

++

++

--

AA BB

CC DD

--

AAA + BA + B

Probability of actually being unaffected withProbability of actually being unaffected withdisease given a negative test result.disease given a negative test result.

Negative Predictive ValueNegative Predictive Value

++

++

--

AA BB

CC DD

--

DDC + DC + D

TestTest

DiseaseDisease

++

++

--

AA BB

CC DD

--

Sens.Sens. Spec.Spec.

PPVPPV

NPVNPV

TestTest

DiseaseDisease

++

++

--

AA BB

CC DD

--

Sens.Sens. Spec.Spec.

PPVPPV

NPVNPV

Columns give Sens. & Spec.Columns give Sens. & Spec.Rows give PPV and NPVRows give PPV and NPV

Sensitivity & SpecificitySensitivity & SpecificityDo Not Vary With Do Not Vary With

PrevalencePrevalence

Predictive Values DoPredictive Values Do

CLINICAL INTERPRETATIONCLINICAL INTERPRETATION

••DEPENDS NOT ONLY ON THE DEPENDS NOT ONLY ON THE TEST RESULT, TEST RESULT, ––PER SE,PER SE,

•• BUT ALSO UNDERSTANDING BUT ALSO UNDERSTANDING THE POPULATION TESTEDTHE POPULATION TESTED

““A COIN FLIPA COIN FLIP””•• Disease X: Disease X:

–– Population incidence 20 per Population incidence 20 per 10001000

–– New test: flip coinNew test: flip coin–– Expect 10 of 20 disease Expect 10 of 20 disease positivepositive

–– Expect 490 of 980 normals Expect 490 of 980 normals negativenegative

COIN FLIPCOIN FLIP

++

++

--

AA BB

CC DD

--

1010

1010 490490

490490Sensitivity = 10/ 20 = 50%Sensitivity = 10/ 20 = 50%

Positive Predictive ValuePositive Predictive Value= 10 / 500 = 2%= 10 / 500 = 2%

Specificity = 490 / 980 = 50%Specificity = 490 / 980 = 50%

Negative Predictive ValueNegative Predictive Value= 490 / 500 = 98%= 490 / 500 = 98%

COIN FLIPCOIN FLIP

++

++

--

AA BB

CC DD

--

6060

6060 440440

440440Sensitivity = 60/ 120 = 50%Sensitivity = 60/ 120 = 50%

Positive Predictive ValuePositive Predictive Value= 60 / 500 = 12%= 60 / 500 = 12%

Specificity = 440 / 880 = 50%Specificity = 440 / 880 = 50%

Negative Predictive ValueNegative Predictive Value= 440 / 500 = 88%= 440 / 500 = 88%

For fFN w/Prevalence 12%For fFN w/Prevalence 12%120 out of 1000 True +ves120 out of 1000 True +ves

BEWARE OF NPVBEWARE OF NPV•• If there is a low prevalence of a condition, If there is a low prevalence of a condition, even a useless test will have a great NPVeven a useless test will have a great NPV

–– 9090’’s: s: ““Genetic sonogramGenetic sonogram”” reported to reported to have 99% NPVhave 99% NPV

••Problem: before they turned on the Problem: before they turned on the US Machine, they had a 98% NPVUS Machine, they had a 98% NPV

VALUE OF TESTSVALUE OF TESTS•• A test is useful if the odds of having the A test is useful if the odds of having the disease after the test are increased compared disease after the test are increased compared to general populationto general population–– (does not by itself mean cost effective)(does not by itself mean cost effective)

•• A test is useless if the odds of having the A test is useless if the odds of having the disease after the test are unchangeddisease after the test are unchanged

•• A test is worse than useless if the odds of A test is worse than useless if the odds of having the disease after the test are lowerhaving the disease after the test are lower

VALUE OF TESTSVALUE OF TESTS

••With a disorder of low With a disorder of low prevalenceprevalence––Even a great test will have a Even a great test will have a low positive predictive valuelow positive predictive value

Build theSRM Table

Interrogate clinical

samples

LC-MS/MSOrbiTrap

MRMs Triple Quadrupoles

Discovery Verification-Validation Clinic

SRM Workflow SW

Discovery SW

Collect raw ms

discovery data

Agilent 6460

Thermo Vantage

IMM: Discovery to Clinical ValidationIMM: Discovery to Clinical Validation

EGFR ImmunoEGFR Immuno‐‐ vs. Aptamervs. Aptamer‐‐PrecipitationPrecipitation

Aptam

er

mAb

1 Keratin, type II cytoskeletal 1

2 Keratin, type I cytoskeletal 10


4 Epidermal growth factor receptor

5 Keratin, type II cytoskeletal 2 epidermal

6 Keratin, type II cytoskeletal 6B

7 52 kDa Ro protein

8 60 kDa heat shock protein, mitochondrial

9 Heat shock cognate 71 kDa protein

10 DnaJ homolog subfamily C member 13

11 40S ribosomal protein S19


13 Multidrug resistance protein 1

14 Arf-GAP with SH3 domain, ANK repeat and PH domain-containing protein 2

15 Brain-specific angiogenesis inhibitor 2

16 MAGUK p55 subfamily member 5

17 Zinc finger protein 473

18 Probable helicase senataxin

Proteins Identified from EGFR antibody-Co-IP

5

1 Leucine-rich PPR motif-containing protein, mitochondrial 27 40S ribosomal protein S19

2 Trifunctional enzyme subunit alpha, mitochondrial 28 Keratin, type I cytoskeletal 9

3 40S ribosomal protein S3 29 60S ribosomal protein L9

4 Ras GTPase-activating-like protein IQGAP1 30 Tubulin beta-3 chain

5 Trifunctional enzyme subunit beta, mitochondrial 31 Peptidyl-prolyl cis-trans isomerase B

6 Heat shock cognate 71 kDa protein 32 Plasminogen activator inhibitor 1 RNA-binding protein

7 78 kDa glucose-regulated protein 33 Probable ATP-dependent RNA helicase DDX46

8 ATP synthase subunit alpha, mitochondrial 34 DNA-binding protein A

9 Keratin, type II cytoskeletal 1 35 40S ribosomal protein S24

10 40S ribosomal protein S4, X isoform 36 Beta-actin-like protein 2

11 Nucleolin 37 General transcription factor II-I

12 60 kDa heat shock protein, mitochondrial 38 Keratin, type I cytoskeletal 10

13 Tubulin alpha-1C chain 39 Neuroblast differentiation-associated protein AHNAK

14 Sulfide:quinone oxidoreductase, mitochondrial 40 Actin, aortic smooth muscle

15 Tubulin beta chain 41 Heat Heat shock protein HSP 90-beta

16 Tubulin beta-2C chain 42 28 kDa heat- and acid-stable phosphoprotein

17 Probable ATP-dependent RNA helicase DDX5 43 40S ribosomal protein S18

18 Annexin A2 44 Stress-70 protein, mitochondrial

19 Pre-B-cell leukemia transcription factor-interacting protein 1 45 Keratin, type II cytoskeletal 2 epidermal

20 Actin, cytoplasmic 1 46 40S ribosomal protein S20

21 Nuclease-sensitive element-binding protein 1 47 40S ribosomal protein S2

22 Very long-chain specific acyl-CoA dehydrogenase, mitochondrial 48 Transcription factor A, mitochondrial

23 Myosin light polypeptide 6 49 Keratin, type II cytoskeletal 6B

24 6-phosphofructokinase type C 50 High mobility group protein B2

25 Phenylalanyl-tRNA synthetase alpha chain 51 Acyl-coenzyme A thioesterase 9, mitochondrial


Proteins Identified from EGFR aptamer-Co-IP

1

53 Heterogeneous nuclear ribonucleoprotein U 79 Heterogeneous nuclear ribonucleoprotein

54 tRNA (cytosine-5-)-methyltransferase NSUN2 80 Arginine/serine-rich coiled-coil protein 2

55 60S ribosomal protein L10 81 Epidermal growth factor receptor

56 Putative RNA-binding protein Luc7-like 2 82 60S ribosomal protein L19

57 SAP domain-containing ribonucleoprotein 83 Brain acid soluble protein 1

58 SRA stem-loop-interacting RNA-binding protein, mitochondrial 84 ATP synthase subunit gamma, mitochondrial

59 Elongation factor Tu, mitochondrial 85 RNA-binding protein EWS

60 CD44 antigen OS=Homo sapiens 86 Sarcoplasmic/endoplasmic reticulum calcium ATPase 1

61 40S ribosomal protein S14 87 Heterogeneous nuclear ribonucleoprotein H

62 ATP synthase subunit delta, mitochondrial 88 Long-chain-fatty-acid--CoA ligase 4

63 RNA-binding protein FUS 89 Keratin, type II cytoskeletal 75

64 Calnexin 90 Keratin, type II cytoskeletal 5

65 ATP-dependent RNA helicase DDX3X 91 Keratin, type II cytoskeletal 79

66 High mobility group protein B1 92 60S ribosomal protein L22

67 Putative 40S ribosomal protein S10-lik 93 ATP synthase subunit O, mitochondrial

68 Vesicle-trafficking protein SEC22b 94 60S ribosomal protein L30

69 Putative elongation factor 1-alpha-like 3 95 Eukaryotic translation initiation factor 5B

70 Heat shock 70 kDa protein 1A/1B 96 ATP synthase subunit e, mitochondrial

71 ADP/ATP translocase 2 97 Dolichol-phosphate mannosyltransferase

72 Luc7-like protein 3 98 UDP-glucose 6-dehydrogenase

73 60S ribosomal protein L23a 99 Receptor tyrosine-protein kinase erbB-4

74 Isoleucyl-tRNA synthetase, 100 Reticulon-4

75 40S ribosomal protein S28 101 Keratin, type I cytoskeletal 28

76 GTP-binding nuclear protein Ran 102 Uncharacterized protein C19orf43

77 Signal recognition particle receptor subunit beta 103 28S ribosomal protein S15, mitochondrial

78 DNA-dependent protein kinase catalytic subunit 104 Protein LYRIC

2

105 Transcription intermediary factor 1-beta 130 Peroxiredoxin-1

106 Nicotinamide phosphoribosyltransferase 131 40S ribosomal protein S3a

107 40S ribosomal protein S9 132 40S ribosomal protein S11

108 Ubiquitin-associated protein 2-like 133 Protein FAM103A1

109 60S ribosomal protein L13 134 Janus kinase and microtubule-interacting protein 3

110 40S ribosomal protein S5 135 40S ribosomal protein S29

111 Putative 60S ribosomal protein L13a-like MGC87657 136 Rho-related GTP-binding protein RhoC

112 60S ribosomal protein L38 137 Uncharacterized protein C6orf125

113 Heterogeneous nuclear ribonucleoprotein U-like protein 2 138 Transmembrane protein 192

114 Microtubule-associated protein 4 139 Inactive ubiquitin carboxyl-terminal hydrolase 53


116 Nucleolar transcription factor 1 141 Dolichyl-diphosphooligosaccharide-protein glycosyltransferase 48 kDa subunit

117 Eukaryotic translation initiation factor 1A 142 E3 ubiquitin-protein ligase SHPRH

118 THO complex subunit 4 143 60S ribosomal protein L27a

119 Probable dimethyladenosine transferase 144 60S ribosomal protein L23

120 40S ribosomal protein S25 145 Ras GTPase-activating protein nGAP

121 28S ribosomal protein S7 mitochondrial 146 Mannosyl-oligosaccharide glucosidase

122 ATP synthase subunit b, mitochondrial 147 Putative mitochondrial carrier protein FLJ44862

123 Translational activator of cytochrome c oxidase 1 148 KN motif and ankyrin repeat domain-containing protein 2

124 Coatomer subunit alpha 149 Histone-lysine N-methyltransferase SUV420H1

125 Pyruvate kinase isozymes M1/M2 150 40S ribosomal protein S30

126 Probable saccharopine dehydrogenase 151 Putative high mobility group protein B3-like-1

127 Long-chain-fatty-acid--CoA ligase 1 152 Rab11 family-interacting protein 1

128 60S ribosomal protein L35 OS=Homo sapiens 153 Meiosis-specific nuclear structural protein 1

129 Myosin light chain 1/3, skeletal muscle isoform 154 E3 ubiquitin-protein ligase UBR3

3

155 NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 10, mitochondrial

156 Solute carrier family 22 member 7

157 Werner syndrome ATP-dependent helicase

158 Oxidoreductase NAD-binding domain-containing protein 1

159 40S ribosomal protein S13

160 Cytosolic carboxypeptidase 4

161 Cyclin-dependent kinase-like 1

162 Histone acetyltransferase p300

163 Uncharacterized protein C2orf72

164 Myosin-XIX

4

AntibodyAntibody AptamerAptamer

1818 164164

Serum Serum AptamerAptamer‐‐SRM assays: Validation PlatformSRM assays: Validation Platform(SRM: Selected Reaction Monitoring)(SRM: Selected Reaction Monitoring)

Serum/plasma Samples

ProcessingProcessing

Wash and EluteWash and Elute


AnalysisAnalysis

Fixed Tissue (FFPE) Fixed Tissue (FFPE) SRM SRM AssaysAssays for Cancer Biomarker Validation for Cancer Biomarker Validation

Documents

From Discovery to Clinical Assay - Tecanww3.tecan.com/platform/content/element/9549/1-4rosenblatt.pdf · Pre‐Term Labor 4 Million Births ... Cases Percent Correct L N=133 NIL N=175