miRNA profiling in serum & plasma

Sample & Assay Technologies- 1 -

Isolation FunctionalizationQuantification

The miRNA Revolution

miRNA Profiling in serum & plasma:On the road to biomarker development

Eric Lader, PhDSenior Director, R&[email protected]


RNA interference: A natural phenomenonDiscovery tool, potential therapeutic

May 26, 2003


Canonical pathway of microRNA biogenesis

� Transcribed by RNA Polymerase II as a long primary transcript (pri-miRNAs), which may contain more than one miRNA.

� In the nucleus, Pri-miRNAs are processed to hairpin-like pre-miRNAs by RNAse III-like enzyme Drosha

� Pre-miRNAs are then exported to the Cytosol by Exportin 5

� In the cytosol RNAse III-like Dicer, processes these precursors to mature miRNAs

� These miRNAs are incorporated in RISC

� miRNAs with imperfect base pairing to thetarget mRNA, lead to translational repression and/or mRNA degradation

CYTOPLASM

mRNA cleavage

NUCLEUSmicroRNA Gene

POL II

mature miRNA

Pre-miRNA

RISC Assembly

Drosha-DGCR8

Exportin

Exportin

DICER-TRBP

Pri-miRNA

Ago

RISC

DNA

Translational RepressionmRNA degradation

High homology Partial homology

Krol, J et.al., (2010) Nature Rev Genetics, 11, 597; Winter, J. et.al., (2009) Nature Cell Biology, 11, 228


Potential events leading to disruption of ‘normal’miRNA:target interaction in disease

AAAA

microRNA Gene

mature miRNA

Pre-miRNA

Drosha-DGCR8

Exportin

DICER-TRBP

Pri-miRNA

Ago

Target Transcript

miRNP

Altered Transcription

Methylation

Histone Modification

Transcription Factors

Drosha Processing

Genomic Instability

Amplification/Deletion

Translocation

Insertional Mutagenesis

Loss of miRNA Binding Site in target

SNP or Mutation

Alternative Splicing

Loss of 3’-UTR

Dicer Processing


Circa 2005: Unique miRNA signatures are found in human cancers

� miRNAs located in genomic regions amplified in cancers (e.g. miR-12-92 cluster) can function as oncogenes, whereas miRNAs located in portions of chromosomes deleted in cancers (e.g. miR-15a-miR-16-1 cluster) can function as tumor suppressors.

� Abnormal expression of miRNAs has been found in both solid and hematopoietic tumors.

� miRNA expression fingerprints correlate with clinical and biological characteristics of tumors , including tissue type, differentiation, aggression and response to therapy.

� The race was on to develop miRNA biomarkers and therapeutics!

Array data from Calin and Croce Nature Reviews Cancer 6, 857–866 (2006)


Circa 2011: A growing picture of miRNA dysregulation in cancer

.In the last 5 years, a substantial number of studies and reviews have associated

.the presence of various miRNAs with cell proliferation, resistance to apoptosis, and

.differentiation in cancer cells.

.For example;

� Deletions of miRNA-regulated genes have been detected in more than 65% of chronic lymphocytic leukemia cases, in 50% of mantle-cell lymphomas, in 16% to 40% of multiple myelomas, and in 60% of prostate cancers.

� Other miRNA abnormalities have been reported in a wide variety of � Human neoplasms, including other hematologic malignancies such as

promyelocytic leukemia; � Benign tumors such as leiomyoma and pituitary adenoma� Multiple types of carcinomas, including pancreatic, esophageal,

thyroid, lung, and breast� Neuroblastomas and glioblastomas.


Therapeutics:miRNA as ‘drug’, miRNA as ‘target of drug’


Purification ofcirculating miRNA



miRNA in BloodRBC, WBC, platelets, CTC, ‘other cells’, extracellu lar?

Whole bloodcontains RBC, WBC,platelets, other cells (e.g. circulating tumor cells)

Serum (after clotting)

Plasma (no clot)

High levels of nucleases present in plasma:Freely circulating RNA should be rapidly degradedSurprisingly, stabile miRNA can be detected in serum and plasma


1) Valadi, H., et.al.,(2007) Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells, Nat Cell Biol 9:654-659

2) Hunter MP et. al., (2008) Detection of microRNA Expression in Human Peripheral Blood Microvesicles, PLoS ONE 3:e36943) Kosaka, N et. al (2010) Secretory mechanisms and intercellular transfer of microRNAs in living cells, J Biol Chem 285: 17442-

174524) Arroyo, JD et. al., (2011) Argonaute2 complexes carry a population of circulating microRNAs independent of vesicles in human

plasma, Proc. Natl. Acad. Sci 108: 5003-50085) Vickers, KC., et. al., (2011) MicroRNAs are transported in plasma and delivered to recipient cells by high-density lipoproteins.

Nat Cell Biol 13:4236) Wang K, Zhang S, Weber J, Baxter D, Galas DJ.(2010) Export of microRNAs and microRNA-protective protein by mammalian

cells. Nucleic Acids Res. 2010 Nov 1;38(20):7248-59.

Exosomes & micro vesicles 1,2,3

miRNA

Ago

Ago-2-miRNA complexes 4

HDL mediatedmiRNA transport 5

Other ‘protective’protein 6

Stable miRNA in circulation Exosomes, microvesicles, complexed: An evolving st ory


A pilot study of circulating miRNAs as potential biomarkers of early stage breast Differential expression of microRNAs in plasma of patients with colorectal A translational study of circulating cell-free microRNA-1 in acute myocardial Direct serum assay for microRNA-21 concentrations in early and advanced breast Altered expression levels of miRNAs in serum as sensitive biomarkers for early Exosomal microRNA: a diagnostic marker for lung cancer. Analysis of circulating microRNA biomarkers in plasma and serum using Exosome isolation for proteomic analyses and RNA profiling. Analysis of Circulating MicroRNA: Preanalytical and Analytical Challenges. Exosomes: proteomic insights and diagnostic potential. Argonaute2 complexes carry a population of circulating microRNAs independent of Extracellular microRNA: A new source of biomarkers. Cell-free miRNAs may indicate diagnosis and docetaxel sensitivity of tumor cells Flow cytometric analysis of circulating microparticles in plasma. Circulating microRNA in body fluid: a new potential biomarker for cancer Functional delivery of viral miRNAs via exosomes. Circulating MicroRNA Is A Biomarker of Pediatric Crohn Disease. Human traumatic brain injury alters plasma microRNA levels. Circulating MicroRNA Signatures of Tumor-Derived Exosomes for Early Diagnosis of Identification of Muscle-Specific MicroRNAs in Serum of Muscular Dystrophy Animal Circulating microRNA: a novel potential biomarker for early diagnosis of acute Let-7 microRNA family is selectively secreted into the extracellular environment Circulating microRNA-1 as a potential novel biomarker for acute myocardial Let-7 microRNAs are developmentally regulated in circulating human erythroid Circulating MicroRNA-208b and MicroRNA-499 reflect myocardial damage in Liver-specific microRNA-122 target sequences incorporated in AAV vectors Circulating microRNAs (miRNA) in Serum of Patients With Prostate Cancer. Measuring circulating miRNAs: the new "PSA" for Breast Cancer? Circulating microRNAs are new and sensitive biomarkers of myocardial infarction. Methods for the discovery of low-abundance biomarkers for urinary bladder cancer Circulating microRNAs as biomarkers and potential paracrine mediators of Micromarkers: miRNAs in cancer diagnosis and prognosis. Circulating microRNAs as biomarkers for hepatocellular carcinoma. MicroRNA as biomarkers and regulators in B-cell chronic lymphocytic leukemia. Circulating microRNAs as blood-based markers for patients with primary and MicroRNA dysregulation in gastric cancer: a new player enters the game. Circulating microRNAs as novel minimally invasive biomarkers for breast cancer. MicroRNA expression in human omental and subcutaneous adipose tissue. Circulating microRNAs as potential biomarkers of coronary artery disease: a MicroRNA signatures of tumor-derived exosomes as diagnostic biomarkers of ovarian Circulating microRNAs as stable blood-based markers for cancer detection. MicroRNA-134 plasma levels before and after treatment for bipolar mania. Circulating microRNAs in breast cancer and healthy subjects. MicroRNAs are transported in plasma and delivered to recipient cells by Circulating microRNAs in patients with coronary artery disease. MicroRNAs as circulating biomarkers for heart failure: questions about Circulating microRNAs in plasma of patients with gastric cancers. MicroRNAs as Novel Biomarkers for Breast Cancer. Circulating microRNAs, miR-21, miR-122, and miR-223, in patients with MiR423-5p as a circulating biomarker for heart failure. Circulating microRNAs, possible indicators of progress of rat Pancreatic cancers epigenetically silence SIP1 and hypomethylate and overexpress Circulating microRNAs, potential biomarkers for drug-induced liver injury. Peripheral blood microRNAs distinguish active ulcerative colitis and Crohn's Circulating MicroRNAs: a novel class of biomarkers to diagnose and monitor human Plasma microRNA profiling reveals loss of endothelial miR-126 and other microRNAs Circulating microRNAs: Association with disease and potential use as biomarkers. Plasma microRNA-122 as a biomarker for viral-, alcohol-, and chemical-related Circulating microRNAs: novel biomarkers for cardiovascular diseases? Plasma microRNAs are promising novel biomarkers for early detection of colorectal Circulating microRNAs: novel biomarkers for esophageal cancer. Plasma MicroRNAs as sensitive and specific biomarkers of tissue injury. Circulating microRNAs: possible prediction biomarkers for personalized therapy of Plasma miR-208 as a biomarker of myocardial injury. Circulating microRNAs: promising breast cancer biomarkers - authors' response. Recovering circulating extracellular or cell-free RNA from bodily fluids. Circulating microRNAs: promising breast cancer Biomarkers. Relevance of circulating tumor cells, extracellular nucleic acids, and exosomes Circulating miR-210 as a Novel Hypoxia Marker in Pancreatic Cancer. Screening for circulating nucleic acids and caspase activity in the peripheral Circulating miR-221 directly amplified from plasma is a potential diagnostic and Secretory mechanisms and intercellular transfer of microRNAs in living cells. Circulating miR-29a levels in patients with scleroderma spectrum disorder. Secretory microRNAs as a versatile communication tool. Circulating miRNA and cancer diagnosis. Selective release of microRNA species from normal and malignant mammary Circulating miRNA signatures: promising prognostic tools for cancer. Serum and urinary free microRNA level in patients with systemic lupus Circulating miRNAs are correlated with tumor progression in prostate cancer. Serum microRNA characterization identifies miR-885-5p as a potential marker for Circulating muscle-specific microRNA, miR-206, as a potential diagnostic marker Serum microRNAs are promising novel biomarkers. Circulating nucleic acids as a potential source for cancer biomarkers. Serum microRNAs as non-invasive biomarkers for cancer. Circulating plasma MiR-141 is a novel biomarker for metastatic colon cancer and Serum miR-146a and miR-223 as potential new biomarkers for sepsis. Detection and characterization of placental microRNAs in maternal plasma. Stable serum miRNA profiles as potential tool for non-invasive lung cancer Detection of circulating fetal nucleic acids: a review of methods and Systemic miRNA-195 differentiates breast cancer from other malignancies and is a Detection of elevated levels of tumour-associated microRNAs in serum of patients The circulating microRNA-221 level in patients with malignant melanoma as a new Detection of microRNA expression in human peripheral blood microvesicles. The levels of hypoxia-regulated microRNAs in plasma of pregnant women with fetal Diagnostic and prognostic value of circulating miR-221 for extranodal natural Tissular and soluble miRNAs for diagnostic and therapy improvement in digestive Diagnostic applications of cell-free and circulating tumor cell-associated miRNAs Vesicle-related microRNAs in plasma of nonsmall cell lung cancer patients and

miRNA in circulation Exosomes, other vesicles, complexed: An evolving s tory


miRNeasy MiniPurification of total circulating miRNA

QIAzol Bind Wash Elute

Manual or Automated on QIAcube

Plasma Serum

RNeasy Protect Animal BloodPAXgene Blood miRNA Kit


Quantification and profiling of circulating miRNA

Quantitect Sybr AssaysQuantifast Probe Assays

mRNAs miRNAs

Other small RNAs

Pre-miRNAs

Pre-miRNA Assays

miScript AssaysRT2 Profiling ArraysRT2 miRNOme

ncRNA Assays

miScriptSystem


miScript systemReverse transcription - principle

2 cells

2x105 cells

Linear cDNA synthesis from 10 pg – 1µg RNA

mRNA miRNA, other small RNAsmRNA miRNA, other small RNAs


RT2 miRNA PCR ArraysGenome-wide, disease, & pathway-focused analysis

miRNome (human, rat, mouse, dog)

miFinderabundantly expressed & well-characterized miRNAs

General Cancer

Cell Development & Differentiation

Immunopathology

Inflammation

Neurological Dev and Disease

Brain Cancer

Serum and Disease

Custom Arrays


Compatible instrumentation: 96- & 384-well formats

PCR Array Service Core

.96-Well Blocks: 7000, 7300, 7500, 7700, 7900HT, Vii A 7

.FAST 96-Well Blocks: 7500, 7900HT, Step One Plus, ViiA 7

.FAST 384-Well Block: 7900HT, ViiA 7

.iCycler, MyiQ, MyiQ2, iQ5, CFX96, CFX384

.Opticon, Opticon 2, Chromo 4

.Mastercycler ep realplex 2/2S/ 4/4S .LightCycler 480

.Mx3000p, Mx3005p, Mx4000p.TP-800

.RotorGene Q


RT2 miRNA Arrays: Reproducibility of technical replicat es

The RT2 miRNA PCR Assays are highly reproducible, ensuring plate-to-plate, run-to-run, and sample-to-sample reliability.


Replicates: Technical versus biological

Technical Replicates� Reproducibility of the PCR Arrays is very high

� Results demonstrate that what you are seeing is a result of biology, not technique� RTC & PPC show technical reproducibility, and can be compared across plates

Biological Replicates� Needed to verify the results are a result of biology

� Three biological replicates needed for statistical analysis

p values and 95% Confidence Intervals


Genome-wide miRNA profiling with RT 2 miRNome ArrayPC3 cells transduced with p53 vs. empty control vect or

RT2 Human miRNome PCR Array: Identifies Known and Novel miRNA Targets of the p53 Signaling Pathway

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15 20 25 30 35 40Ct Control

Ct A

deno

-p53

34a 940

203 551a

miR-203 miR-551a

miR-34amiR-940


Serum miRNA profiling

.Human Serum RT2 miRNA PCR Array (MAH-106)� Profile the expression of mature miRNA that researchers have reported as

elevated in serum and other bodily fluids in disease� Heart and liver injury or disease, atherosclerosis, diabetes, and a number of

organ-specific cancers

� What is on the array?� 85 miRNA assays� housekeeping gene assays� Reverse Transcription Control assays

– Monitor RT efficiency� PCR Control assays

– Monitor PCR efficiency� RNA Recovery Control assays

– Works with Syn-cel-miR-39 miScript miRNA Mimic (MSY0000010) spiked into samples before nucleic acid preparation to monitor miRNA recovery rates


Human Serum RT 2 miRNA PCR Array

1 2 3 4 5 6 7 8 9 10 11 12

A let-7a miR-1 miR-100 miR-106a miR-106b miR-10b miR-122 miR-124 miR-125b miR-126 miR-133a miR-133b

B miR-134 miR-141 miR-143 miR-146a miR-150 miR-155 miR-17 miR-17* miR-18a miR-192 miR-195 miR-196a

C miR-19a miR-19b miR-200a miR-200b miR-200c miR-203 miR-205 miR-208a miR-20a miR-21 miR-210 miR-214

D miR-215 miR-221 miR-222 miR-223 miR-224 miR-23a miR-25 miR-27a miR-296-5p miR-29a miR-30d miR-34a

E miR-375 miR-423-5p miR-499-5p miR-516a-3p miR-574-3p miR-885-5p miR-9 miR-92a miR-93 let-7c miR-107 miR-10a

F miR-128 miR-130b miR-145 miR-148a miR-15a miR-184 miR-193a-5p miR-204 miR-206 miR-211 miR-26b miR-30e

G miR-372 miR-373 miR-374a miR-376c miR-7 miR-96 miR-103 miR-15b miR-16 miR-191 miR-22 miR-24

H miR-26a cel-miR-39 cel-miR-39 cel-miR-39 SNORD48 SNORD47 SNORD44 RNU6-2 miRTC miRTC PPC PPC

Circulating Disease mIRNAs serum miRNAs NC RNA

Oncogenic miRNA spike in control RT2 Controls

Functional Gene Groupings Injury: Heart Injury: miR-1, miR-133a, miR-192, miR-208a, miR-423-5p, miR-499-5p. Liver Injury: miR-122. Disease: Atherosclerosis: miR-150. Diabetes: miR-124, miR-146a, miR-29a, miR-30d, miR-34a, miR-375, miR-9. Heart Disease: miR-133a, miR-208a. Liver Disease: miR-146a, miR-215, miR-224, miR-574-3p, miR-885-5p, miR-92a. Cancer: Adenocarcinoma: miR-29a, miR-92a. B Cell Lymphoma: miR-21, miR-210. Breast: let-7a, miR-106a, miR-10b, miR-141, miR-155, miR-195, miR-21, miR-34a. Colon: miR-134, miR-146a, miR-17*, miR-221, miR-222, miR-23a, miR-29a, miR-92a. Gastric: let-7a, miR-1, miR-106a, miR-106b, miR-17, miR-17*, miR-20a, miR-21, miR-27a, miR-34a, miR-423-5p. Leukemia: miR-155, miR-21, miR-210. Liver: miR-122, miR-21, miR-223. Lung: miR-134, miR-146a, miR-17*, miR-21, miR-210, miR-221, miR-222, miR-223, miR-23a, miR-25. Ovarian: miR-126, miR-141, miR-200a, miR-200b, miR-200c, miR-203, miR-205, miR-21, miR-214, miR-29a, miR-92a, miR-93. Pancreatic: miR-196a, miR-200a, miR-200b, miR-21, miR-210. Prostate: miR-100, miR-125b, miR-141, miR-143, miR-18a, miR-19a, miR-19b, miR-20a, miR-21, miR-296-5p, miR-375, miR-516a-3pRenal: miR-124. Rhabdomyosarcoma: miR-1, miR-133a, miR-133b.


Workflow for circulating miRNA profiling

Spike C elegansmiRNA control

into lysate


Profiling of circulating miRNA Stability of endogenous miRNA in human serum and pl asma at 25 oC

R2 = 0.945

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30

35

R2 = 0.932

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35

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Serum

Plasma

24 h

ours

25o

C

0 hours 25oC

� Circulating miRNA is not naked,

as unprotected miRNA would

have a half-life of only minutes

� 24 hours at ambient temperature

has little effect on the miRNA profile from serum or plasma


R2 = 0.973

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35Serum

Profiling of circulating miRNA Freeze/thaw stability of miRNA in human serum and p lasma

R2 = 0.984

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35

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Plasma

20 F

/T c

ycle

s

1 freeze-thaw cycle

� Circulating miRNA is unaffected by up to 20 freeze-thaw cycles

� Storing multiple archival aliquots

is suggested for precious samples to avoid mishaps

� Whole blood should NOT besubject to freeze-thaw to avoid

cell lysis


Profiling of circulating miRNA Subtle differences between serum and plasma (same d onor)

R2 = 0.922

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20.0

25.0

30.0

35.0

40.0

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plasma

seru

m

� Triplicate isolations from the same plasma or serum sample

(not triplicate collections of fluid)

� Most assays do not vary by more than one Ct� Either serum or plasma is suitable for profiling but plasma may be more

consistent as the additional variability of clotting is not required� Recommendation is to compare serum to serum, plasma to plasma,

as normalization will not correct for these outliers.


miRNeasy Mini and RT 2 Array:Profiling of circulating miRNA from plasma or serum

0

5

10

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25

30

35

miR

-16

miR

-92a

miR

-19b

mir-

223

miR

-126

miR

-21

miR

-15b

let-7

bm

iR-9

3m

iR-1

91m

iR-2

7a

let-7

g

let-7

a

mir-

24m

iR-2

6bm

iR-4

25m

iR-1

92m

iR-1

48a

miR

-125

bm

iR-1

46a

miR

-15a

miR

-29c

miR

-30e

let-7

dm

ir-30

am

iR-1

97m

iR-1

82m

iR-2

9am

iR-1

25a

miR

-222

miR

-99a

miR

-152

miR

-193

am

iR-1

0bm

iR-1

96a

miR

-183

miR

-17-

3pm

iR-1

42m

iR-1

45 U6R

NU1

A

~ 20 µl serum per cDNA synthesis (per 384 array)


Title

Description

Date

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Title

Description

Date

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Variability in circulating miRNA in normal voluntee rs

y = 0.9098x + 1.8318

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y = 0.9092x + 1.9134

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y = 0.9707x + 0.9286

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‘Normal’ expression levels of ‘serum miRNAs’Deviation from mean level of expression, each gene

Black = least variableGreen = variance above geometric meanRed = variance below geometric mean


‘Normal’ expression levels of ‘serum miRNAs’Displayed as relative level of expression, normaliz ed to plate mean

Green = highly expressedRed = low level of expressionBlack = mean expression


Variability in miRNA in RT 2 Serum ArrayAmong 10 ‘normal’ volunteers

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hsa-miR-155 hsa-miR-124 hsa-miR-206 hsa-miR-204 hsa-miR-376c hsa-miR-215 hsa-miR-128 hsa-miR-143 hsa-miR-203

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hsa-miR-30e hsa-miR-17 hsa-miR-19b hsa-miR-150 hsa-miR-106a hsa-miR-423-5p hsa-miR-93 hsa-miR-92a hsa-let-7c

Less than 2-fold variability

>100-fold

Up to 10,000 foldVariability.


R2 = 0.9361

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pooled normal n=10 pooled normal n=10

pool

ed c

olon

can

cer

n=3

pool

ed b

reas

t can

cer

n=3

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Normal

Pro

stat

e C

ance

r A

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27

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31

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29 31 33 35 37

Normal

Pan

crea

tic C

ance

r A

‘Unacceptable’ commercial serumLow signal levelsMore ‘undetectable’ targetsHigh variability between samples

Profiling of circulating miRNA in cancerRT2 Circulating Array, colon and breast cancer samples

R2 = 0.9067

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RT2 Dog miRNome serum/plasma profiling

R2 = 0.9628

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R2 = 0.97

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serum vs plasma, same dog

serum dog 1 vs dog 2

� miRNeasy serum / plasma protocol

� 200 ul serum or plasma prep

� 50 ul eluate� 5ul or RNA prep for cDNA synthesis

� one 384 well RT2 PCR Array

� Mirbase v16, 275 genes

� Single use 384 RT2 Array� RT and PCR controls

� Wet lab validated


Circulating miRNA data normalization



Expression profiling of normal human serum samplesData normalization strategies

. Two normal human serum samples (Sample A and Sample B)� Total RNA was isolated using the miRNeasy Mini Kit

� QIAGEN Supplementary Protocol for total RNA purification from serum or plasma� Option syn-cel-miR-39 spike-in control included

� 5 µl of each RNA elution was used in an RT2 miRNA First Strand Kit reverse transcription reaction

� Mature miRNA expression was profiled using the Human Serum RT2 miRNA PCR Array (MAH-106)

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Raw Ct: Serum Sample A

Raw

Ct:

Ser

um S

ampl

e B

R2 = 0.9079

� Non-normalized Ct values are highly comparable� How should the data be normalized to uncover fine

differences between the two samples?


Serum sample and RTPCR data normalization

.Step 1: Check reverse transcription control (miRTC) and PCR control (PPC) Ct values

19.7619.61PPCH12

19.6119.43PPCH11

18.6418.73miRTCH10

18.5218.76miRTCH09

Ct: Sample BCt: Sample AControlPosition

� As determined by the raw Ct values, the reverse transcription and PCR efficiency of both samples are highly comparable

� Ct values differ by less than 0.25 units


Serum sample data normalization (cont.)

.Step 2: Observe housekeeping gene Ct values

35.0035.00RNU6-2H08

35.0035.00SNORD44H07

35.0035.00SNORD47H06

32.7931.81SNORD48H05

Ct: Sample BCt: Sample AGenePosition

� Housekeeping genes are either not expressed or exhibit borderline detectable expression

� As is often found with serum samples, standard housekeeping genes cannot be used for data normalization

� How should you proceed?


Serum sample data normalization (cont.)

Four potential data normalization options

1. Normalize data of each plate to its RNA Recovery Control Assays (wells H02 to H04)� Can only be used if Syn-cel-miR-39 miScript miRNA Mimic

(MSY0000010) is spiked into the sample @ nucleic acid preparation

2. Normalize data to Ct mean of all expressed targets (targets with Ct < 35) for a given plate

3. Normalize data to Ct mean of targets that are commonly expressed in the samples of interest

4. Normalize data to ‘0’� Essentially you are relying on the consistency of the quantity

and quality of your original RT input


Serum sample data normalization (cont.)Option 1: Normalize to RNA recover control assays

� Calculate the average Ct of the cel-miR-39 wells (H02 to H04)

• Sample A: 17.85

• Sample B: 19.42

� Using these cel-miR-39 Ct means as normalizers, calculate ∆∆Ct values, fold-change, and fold up/down regulation

19.3917.85cel-miR-39H04

19.4917.85cel-miR-39H03

19.3717.84cel-miR-39H02

Ct: Sample BCt: Sample AControlPosition

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100

Fol

d-R

egul

atio

n (B

to A

)


Serum sample data normalization (cont.)Option 2: Normalize to Ct mean of expressed targets for a given plate

� Determined the number of expressed targets in each plate (Ct < 35)� Sample A: 66

� Sample B: 59

� Calculate the Ct Mean of the expressed targets� Sample A: 28.96

� Sample B: 29.70

� Using these Ct means as normalizers, calculate ∆∆Ct values, fold-change, and fold up/down regulation

� NOTE: same strongly up-regulated and down-regulated miRNAs are identified

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60

Fol

d-R

egul

atio

n (B

to A

)


Serum sample data normalization (cont.)Option 3: Normalize to Ct mean of commonly expresse d targets

� Determined the number of commonly expressed targets for the plates being analyzed (Ct < 35 in all samples)

� Commonly expressed in Sample A and Sample B: 48

� Calculate the associated Ct Mean� Sample A: 27.52� Sample B: 28.86

� Using these Ct means as normalizers, calculate ∆∆Ct values, fold-change, and fold up/down regulation

� NOTE: same strongly up-regulated and down-regulated miRNAs are identified

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80

Fol

d-R

egul

atio

n (B

to A

)


Serum sample data normalization (cont.)Option 4: Normalize to ‘0’

� Normalizing to ‘0’ relies on the consistency in the quantity and quality of your original RT input

� For serum samples, this may not be the best option, as the RNA is not routinely quantified prior to addition to a reverse transcription reaction

� Normalizing the data to ‘0’, calculate ∆∆Ct values, fold-change, and fold up/down regulation

� NOTE: These results are not completely comparable to the results achieved with the other three normalization methods. The same strongly up-regulated and down-regulated miRNAs are identified; however, additionally up- and down-regulated genes are potentially (incorrectly) identified. This suggests that there is the need for some method of normalization, other than just normalizing to ‘0’.

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www.qiagen.com/geneglobe


Thank you!Eric [email protected]

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Webinar 2 : miRNAs and Cancer: The role of miR-211 in Melanoma

Webinar 3 : miRNA Profiling in serum & plasmaOn the road to biomarker development

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miRNA profiling in serum & plasma