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Webinar SeriesWebinar SeriesWebinar SeriesWebinar SeriesScienceScienceScienceScienceDETECTING DISEASE IN BLOODDETECTING DISEASE IN BLOODDETECTING DISEASE IN BLOODDETECTING DISEASE IN BLOODWhat miRNA Biomarkers Can Tell UsWhat miRNA Biomarkers Can Tell Us

30 May, 201230 May, 2012

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Webinar SeriesWebinar SeriesWebinar SeriesWebinar SeriesScienceScienceScienceScienceDETECTING DISEASE IN BLOODDETECTING DISEASE IN BLOOD

Brought to you by the Science/AAAS Custom Publishing Office

DETECTING DISEASE IN BLOODDETECTING DISEASE IN BLOODWhat miRNA Biomarkers Can Tell UsWhat miRNA Biomarkers Can Tell Us

30 May, 201230 May, 2012

Participating Experts:


Colin C. Pritchard M.D., Ph.D.University of WashingtonSeattle, WA

Monty Montano, Ph.D.Boston University School of MedicineBoston, MA

Adam Baker, Ph.D.ExiqonVedbaek, Denmark

Sponsored by:

Circulating microRNA as Disease Biomarkers: A LaboratoryBiomarkers: A Laboratory

Medicine Perspective

Colin C. Pritchard MD, PhDUniversity of Washington

Department of Laboratory MedicineScience Webinar, May 30, 2012

OutlineOutline

• microRNA as circulating biomarkers

• Laboratory medicine considerations:Sources of variation– Sources of variation

– State of microRNA in plasmaO i i d i li ti f di ifi it– Origin and implications for disease specificity

Circulating microRNA Are Attractive Biomarkers

• Abundant in Blood

• Easy to Measure

• Highly Stable

• Disease Associations

Over 200 Publications Since 2008 on Circulating miRNA

• Cancer• Prostate Breast Colon Lung Ovarian Leukemia• Prostate, Breast, Colon, Lung, Ovarian, Leukemia

Many other diseases• Many other diseases• Pregnancy, Diabetes, Heart Disease, etc.

• Sources of variation not well-studied

OutlineOutline




Sources of VariationSources of Variation

• Analyticaly

• Biological

Analytic VariationAnalytic Variation

• Pre-analytic

• Analytic

• Post-analytic

InterferencesInterferences

Li i• Hemolysis

Hemolysis Lipemia

• Lipemia

• Drugs

A tib di• Antibodies

Biological VariationBiological Variation

• Within individual– Diurnal

• Between individual– Age/GenderDiurnal

– Fasting/FedSick/Well

Age/Gender– Genetic/Ethnicity

Chronic disease– Sick/Well – Chronic disease

OutlineOutline




How is miRNA Stable in Plasma?How is miRNA Stable in Plasma?

• RNase-resistance hypotheses:• RNase-resistance hypotheses:– Intrinsically stable? (no)

– Protected in vesicles? (one model)

– Protected by other mechanisms?

Two Populations of Circulating miRNAdetected by size-exclusion chromatography

Protein ComplexVesicle/Exosome0.4

miR-142-3p0.4

miR-122

0 2

0.3

e C

opie

s miR-142-3p

0 2

0.3miR-122

e C

opie

s0.1

0.2

Rel

ativ

e

0.1

0.2

Rel

ativ

e

0 0

Relative SizeVesicle Protein

Relative SizeVesicle Protein

Adapted from Arroyo et al. (2011) PNAS

Relative Size Relative Size

Implications of Two Plasma States For CirculatingStates For Circulating miRNA Biomarkers?o a e s

Specimen Processing and Vesicles

PlasmaPlateletsVesicles

mL

2x106

er P

er m

2x106

Platelet-Poor Plasma

PlateletsVesicles

Num

be

2x10

Par

ticle

PlateletsVesicles3x105

Platelet-Poor Plasma Filtered

P PlateletsVesicles

Filtered

Diameter (µm)

OutlineOutline




Where do plasma miRNA come from?Where do plasma miRNA come from?

C ll O i i R l ti C t ib tiCell Origin

Bl d C ll

Relative Contribution

??• Blood Cells ??

• Endothelium ??

• Other Tissues ??

Plasma and Blood CellPlasma and Blood Cell miRNA Levels are Correlated

Plasma Blood Cells

higherRBC myeloid lymph

miRNA level

79 miRNA Biomarkers levelBiomarkers

Healthy Donors

lower

y

Adapted from Pritchard et al. (2012) Cancer Prev. Res.

Plasma miRNA Correlate To Blood Counts

7.08.5miR-150miR-223

6 0

6.5 R=0.67

7 5

8.0 R=0.76

s/µl

pla

sma

s/µl

pla

sma

5.5

6.0

7.0

7.5

log 1

0co

pies

log 1

0co

pies

5.00.05 0.5 5

Lymphocyte Count (log10 thou/µl)

6.50.1 1 10

Neutrophil Count(log10 thou/µl)

Consecutive Clinical Plasma Samples

Adapted from Pritchard et al. (2012) Cancer Prev. Res.

RBC-Derived miRNA are Affected by Hemolysis

• miR-16, miR-451 increased up to 50-fold

• Non-RBC miRNA not impacted – e.g. miR-122, miR-223, miR-150

McDonald et al. (2011) Clin. Chem.Pritchard et al (2012) Cancer Prev ResPritchard et al. (2012) Cancer Prev. Res.

Summary/ConclusionsSummary/Conclusions• Circulating miRNA are promising as disease biomarkersg p g

• Little is known about analytic properties or biologic variationvariation

• miRNA are present in at least two states in plasmamiRNA are present in at least two states in plasma

• Plasma miRNA are likely released by blood cells

• Plasma miRNAs that are abundant in normal blood cells may have poor specificity as biomarkers because theymay have poor specificity as biomarkers because they are influenced by cell counts and hemolysis

AcknowledgementsAcknowledgements

• FHCRC• FHCRC– Evan Kroh

M h T i– Muneesh Tewari– Jason Arroyo – Brent Wood– Heather Cheng

• UW– Liz Setran– Hye Son Yi

– John Tait– Don Gibson

• UH– Marc Goodman

– Deb BardenMarc Goodman

– Yeonju Kim




30 May, 201230 May, 2012






Sponsored by:

AGING AND CHRONIC DISEASE: microRNA PROFILING in CENTENARIANS and HIV INFECTION

MONTY MONTANO, PhD

Principal Investigator

Section of Infectious Diseases, Boston University School of MedicineBoston OAIC Pepper Center for Aging

New England Centenarian Study

QUESTIONS POSED IN THIS PRESENTATIONQUESTIONS POSED IN THIS PRESENTATION

I. Is there evidence for microRNAs in aging ?



II. Can blood microRNA profiling be used to study aging in the extreme ?



II. Can blood microRNA profiling be used to study aging in the extreme ? Centenarians




III Can blood microRNA profiling be used to studyIII. Can blood microRNA profiling be used to study chronic infection ?




III Can blood microRNA profiling be used to studyIII. Can blood microRNA profiling be used to study chronic infection ? HIV infection




III Can blood microRNA profiling be used to study

IV. Summary and implications for future studies

III. Can blood microRNA profiling be used to study chronic infection ?

THE AGING BRAIN BASED ON i RNA EXPRESSIONTHE AGING BRAIN BASED ON microRNA EXPRESSION

AGE Adapted from Montano et al, Aging Res Rev 2010

i RNA PROCESSING AS A BIOMARKER OPPORTUNITY

pri-microRNA

microRNA PROCESSING AS A BIOMARKER OPPORTUNITY

pri microRNA

i RNA PROCESSING AS A BIOMARKER OPPORTUNITY

pri-microRNA

microRNA PROCESSING AS A BIOMARKER OPPORTUNITY

pri microRNA

Biomarkers in Plasma/Serum ?

CENT-1

CENT-2

CORRELATED microRNA EXPRESSION IN CENTENARIAN SAMPLES

COMPARATIVE MICRORNA PROFILING OF CENTENARIANSCOMPARATIVE MICRORNA PROFILING OF CENTENARIANS

35

40

35

40

20

25

30

35

Cq

leve

l

20

25

30

35

Cq

leve

l

15

20

1 5 9 13

17

21

25

29

33

37

41

45

49

53

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61

65

69

73

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81

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101

105

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113

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microRNA

15

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1 5 9 13

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microRNA

Exiqon average Centenarians Exiqon average Centenarians

COMPARATIVE MICRORNA PROFILING OF CENTENARIANSCOMPARATIVE MICRORNA PROFILING OF CENTENARIANS

35

40

35

40

above average

20

25

30

35

Cq

leve

l

20

25

30

35

Cq

leve

l

15

20

1 5 9 13

17

21

25

29

33

37

41

45

49

53

57

61

65

69

73

77

81

85

89

93

97

101

105

109

113

117

121

125

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133

137

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microRNA

15

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1 5 9 13

17

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25

29

33

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41

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49

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65

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73

77

81

85

89

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101

105

109

113

117

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125

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133

137

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microRNA

Exiqon average Centenarians Exiqon average Centenarians

MICRORNA PROFILING OF CENTENARIANS by GENDER

below average

MICRORNA PROFILING OF CENTENARIANS by GENDER




III Can blood microRNA profiling be used to studyIII. Can blood microRNA profiling be used to study chronic infection ?

HIV INFECTION AND PHENOCOPIES OF AGING

Frailty related phenotype

HIV INFECTION AND PHENOCOPIES OF AGING

Frailty related phenotype Desquilbet et al., 2007; Effros et al., 2008; Fried et al., 2001

Decline in bone and muscle massDecline in bone and muscle massBrown et al., 2009; Brown and Qaqish, 2006, Banerjee et al., 2012

Systemic inflammatory burden Systemic inflammatory burdenFinch and Morgan, 2007; Yarasheski et al., 2005

Immuosenescence elevated Immuosenescence elevatedEffros 2008, Appay 2007

Cognitive and brain function decline Cognitive and brain function declineAnces et al., 2009

SIV+ SIV- SIV+ SIV-

COMPARATIVE MICRORNA PROFILING OF SIV INFECTION

CLUSTERING BASED ON MICRORNAS AND SAMPLESCLUSTERING BASED ON MICRORNAS AND SAMPLES

Serum samplesSerum samples

roRN

As

roRN

As

mic

micr

SSIV‐

SIVSIV‐

Rescaled by row (microRNAs) Rescaled by columns (samples)

SIV+ SIV+

CLUSTERING SERUM AND HIPPOCAMPUS i RNA EXPRESSIONCLUSTERING SERUM AND HIPPOCAMPUS microRNA EXPRESSION

Serum samples Brain samples

croR

NAs

croR

NAs

mic

mi




III Can blood microRNA profiling be used to study

IV. Summary and implications for future studies

III. Can blood microRNA profiling be used to study chronic infection ?

SUMMARY d IMPLICATIONSSUMMARY and IMPLICATIONS

microRNAs may reflect underlying tissue/organ processes



microRNA signatures may distinguish biologic from chronologic age




microRNAs may be useful biomarkers for acute and chronic infection




microRNAs may be useful biomarkers for acute and chronic infection

i RNA b f l i t t d th ti di ti microRNAs may be useful in targeted therapeutic-diagnostics

ACKNOWLEDGEMENTSACKNOWLEDGEMENTS

AGING STUDIESPaola Sebastiani NECS, Boston UniversityTom Perls NECS, Boston UniversityKim Kafadar Long Boston UniversityKim Kafadar Long Boston UniversityClinton Baldwin Boston UniversityGreg Gibson Georgia Institute of TechnologyAdam Baker Exiqon, Inc.

HIV STUDIESDaniel Michaels Boston UniversitySusan Westmoreland NEPRC, Harvard Universityy

SUPPORTNIA NIAMSNIAMS NIAID




30 May, 201230 May, 2012






Sponsored by:

Translating miRNA discovery in biofluids

Science WebinarMay 30th 2012, Adam Baker, PhD. [email protected]

g yinto robust biomarkers for disease,

toxicology or injury studies

AgendaAgenda

• How to study microRNAs – introduction to LNA™

• Detection of microRNAs in clinical samples

• Diagnostic development using LNA™ UniversalDiagnostic development using LNA Universal

RT microRNA PCR

• Toxicology – new focused platform and servicesToxicology new focused platform and services

Analyzing microRNAs –Analyzing microRNAs overcoming challenges by using LNA™

F t Ch ll LNA™ llFeature Challenge LNA™ allows

Short sequences (19-22 nt) Hard to achieve high sensitivity

Increased affinity

Highly homologous families (single base differences)

Hard to achieve sufficient specificity

Single nucleotide discrimination

Large variation in base composition (GC content varies between 5-95%)

Hard to design good multiplex assays

Tm normalization

LNA™ enables high sensitivity and highLNA enables high sensitivity and high specificity in hybridization assays

• Increased Tm (Tm increases by 2 - 8ºC per base)

• Increased ∆Tm (larger difference between mismatch and perfect match)

• Tm normalization (adjust oligos to the same Tm)

K. Bondensgaard et al., Chem. Eur. J. 2000, 6, 2687M. Petersen et al., J. Am. Chem. Soc. 2002, 124, 5974

Searching for microRNA biomarkers is like looking for a needle in a Haystack.

A cell contains total RNA level in plasmaA cell contains Approximately 10 to 30pg of total RNA

total RNA level in plasma is in the range 6-300

ng/ml.

0.3% of this is microRNA 5% of this microRNA

60

Jensen et al. BMC Genomics 2011, 12:435http://www.biomedcentral.com/1471-2164/12/435

Persat, Alexandre; Chivukula, Raghu R.; Mendell, Joshua T.;Santiago, Juan G.Journal Title: Analytical Chemistry Columbus 60http://www.biomedcentral.com/1471 2164/12/435Journal Title: Analytical Chemistry - ColumbusISSN: 0003-2700

LNA™ microRNA PCR System:LNA microRNA PCR System: ideal for finding needles

Ad antagesAdvantages:● Universal RT → no bias,

no pre-amplification(no extra hay generated)

● LNA™ in two specificLNA in two specific primers → sensitivity and specificity(teases out the needle(teases out the needle from the hay)

Extreme sensitivity allows microRNA PCR profilingExtreme sensitivity allows microRNA PCR profiling from clinical samples

Accurate microRNA PCR profiling with simpleAccurate microRNA PCR profiling with simple workflow

● 20 µl plasma/serum or 150pg RNA input/ One RT reaction

● 96 or 384-well PCR including calibrators / controlscalibrators / controls

● QC / normalization and data analysis

miRCURY LNA™ microRNA PCR SystemmiRCURY LNA microRNA PCR System- a solution for every project

AgendaAgenda




RT microRNA PCR


LNA™ PCR assays show linearity at very low

Plasma or serum

concentrations as found in plasma and serum

● Serial dilution of a l f 647 th tipool of 647 synthetic

microRNAs

● Correlation between microRNA input and median Ct

● LNA™ PCR assays show near perfect plinearity even at very low concentrations

We are experienced at overcoming the challenges ofWe are experienced at overcoming the challenges of microRNA qPCR normalization in serum/plasma

● Normalization adjusts for technical biases (RNA amount, quality etc)j ( q y )● No housekeeping genes are stably expressed in all situations● U6 and 5S are not applicable to serum/plasma samples● With qPCR panels, no prior assumptions about housekeeping genesWith qPCR panels, no prior assumptions about housekeeping genes● Select a normalization method appropriate for the dataset

Raw data values Quantile normalizationMean centered normalization

Mean centered (top 50 expressed)( p p )

normalization

Unique QC possibilities with our Normal reference range – Human serum1400+ human samples with over 1 million PCR data points make up the reference range

DynamicWindowOf miRNAExpressionExpressionIn serum

AgendaAgenda




RT microRNA PCR


Early Detection of CRC in blood plasmaEarly Detection of CRC in blood plasma addresses large unmet need

Colorectal cancer

● The second most important cancer in terms of deaths in the western world

● Estimated deaths in 2009 in the USA was 49,920

● The addressable screening market is 3.75 Billion USD (or 300 million people per year)

Stage 5 yr relative Treatmentg ysurvival

0-I 93% Surgery

II 80% Surgery

III 58% Surgery/adjuvantchemotherapy

IV 6.9% Chemotherapy

Exiqon’s discovery process and PCR platformExiqon s discovery process and PCR platform are compatible with clinical procedures

Development of microRNA Early Detection

DISCOVERY PHASE VALIDATION PHASE

Development of microRNA Early Detection Test of CRC in blood plasma

• 50 controls• 50 CRC patients

• Multiple QC check

• Data analysis• Quality control

• 325 samples• Focused

Genome wide screening

Normalization, QC, processing

Bioinformatics, data analysis

Candidate miRNA discovery screen

• Defined miRNA signature

Validation SetmiRNA signature

50 CRC patients• 742 miRNA

screen• Genome wide

check• Data flagging• Normalization

Quality control• ROC curve• miRNA selection

Focused Serum/Plasma panel

• Multiple controls

signature• Pick & Mix panel• Multiple controls

microRNA Biomarker discovery workflow

DISCOVERY PHASE VALIDATION PHASE

microRNA Biomarker discovery workflow and panel selection options

Genome wide screening

Normalization, QC, processing

Bioinformatics, data analysis

Candidate miRNA discovery screen

Validation SetmiRNA signature

AgendaAgenda




RT microRNA PCR


Focus microRNA PCR PanelsFocus microRNA PCR Panels Available from the Pick & Mix configurator allows for full customization to improve sample analysis

● Focus panels are available for customization through the Pick&Mixfi tconfigurator:

New Focused PCR developmentNew Focused PCR development

AcknowledgementsAcknowledgements




30 May, 201230 May, 2012




To submit your questionsMonty Montano, Ph.D.Boston University School of MedicineBoston, MA

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Sponsored by:




30 May, 201230 May, 2012

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For related information on this webinar topic, go to:

www.exiqon.com/bloodbiomarkers

Sponsored by:

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