Precision medicine offers to transform patient care by targeting treatment to those with most to gain. To date the most significant advances have been at the level of DNA, for example, the use of somatic DNA alterations as diagnostic indicators of disease and for prediction of pharmacodynamic response. Development of RNA expression signatures as biomarkers has been more problematic. While RNA expression analysis has yielded valuable insights into the biological mechanisms of disease, RNA is a more unstable molecule than DNA, and more easily damaged or degraded during sample collection and isolation. In addition, RNA levels are inherently dynamic and gene expression signatures are extraordinarily complex. Recently, much progress has been made in identifying key changes in gene expression in cancer and other diseases, as well as identifying expression signatures in circulating nucleic acid that have the potential to be developed into diagnostic and prognostic indicators.

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Eric Lader, Ph.D.
Eric.Lader@qiagen.com
Senior Director, Product Development
Total RNA Discovery
For RNA Biomarker Development

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Supporting Sample to Insight
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The products describedin this webinar are intended for molecular biology applications.
These products are not intended for the diagnosis, prevention, or treatmentof a disease.

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Characteristic
presence of antibodies
abnormal bp, blood cells, electrolytes
distinct histological indicators
abnormal liver or kidney function markers
presence of muscle injury protein markers
gene status or gene expression status
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What is a biomarker?
Methodology
Elisa
blood counts, pressure
microscopy
biofluid assay
biofluid assay
qPCR, NGS, Array, etc.
A characteristic that is objectively measured and evaluated as an
indicator of normal biologic processes, pathogenic processes, or
pharmacologic responses to a therapeutic intervention.

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Nucleic Acid biomarkers
Gateway to Personalized Medicine
• Stable ‘universal’ analyte
• Universal detection technologies
• Single molecule sensitivity and specificity
What is the
prognosis
What is the
right treatment
Monitoring
effectiveness
Recurrence
or progression
What kind of
cancer is it
Predictive BRCA germline mutation
Diagnostic BCR-ABL somatic translocation
Prognostic HER2 somatic amplification
Theranostic CYP26 SNP germline variant

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Noninvasive biomarker
In order to use a biomarker for routine diagnostics, the sample
material must be as easy to obtain as possible.
urine or saliva sample
a drop of blood
blood sample
CSF
surgical biopsy
Evaluation
Minimally
Invasive
invasive

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Pubmed: gene expression as ‘biomarker’
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>22,000 peer-reviewed publications on RNA AND biomarker…
“RNABiomarker”

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RNA in body fluids
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Exosomes and
Microvesicles
RNA
Ago
Protein-RNA
complexes
 High levels of nucleases present in plasma
 Freely circulating RNA should be rapidly degraded
 Surprisingly, RNA can be detected in serum and plasma
CTC
(in cellular compartment)

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Exosomes harbor unique subsets of RNA and proteins
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 Exosomes are small vesicles excreted by all
cells, found in all biofluids
 Exosomes contain stable nucleic acids
(mRNA, microRNA, lncRNA), DNA, and
protein, protected from degradation by a lipid
bilayer
 Contents are specifically packaged,
mechanism of local and distant cellular
communication
 Exosomes can function as remote intercellular
mediators
 Cancer cells shed large numbers of exosomes
which may be critical in disease progression

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Total RNA isolation technologies
miRNeasy family
(total RNA from body fluids or cells)
QIAamp Circulating Nucleic Acid Kit
(larger input volumes of body fluid if required)
exoRNeasy Serum/Plasma Kit
(exosome purification)
Cells CSF Urine

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miRNeasy Serum/Plasma Kit
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RNA isolation from cells, serum, plasma, and other biofluids
 Includes synthetic RNA control assay for normalization
 1 µl to 400 µl input volume
 Optimized elution volume (14 µl)
 High-purity RNA suitable for all downstream applications
 Easy, robust procedures
 Automatable protocol
QIAzol Bind Wash Elute
Manual or automated on QIACube
Plasma, Serum, Cells

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exoRNeasy Serum/Plasma Maxi Kit
 Microvesicle isolation
 20 minutes
 RNAisolation
 35 minutes
Separate
Serum/Plasma
Isolate
Exosomes
Isolate
RNA

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What RNA species are being developed as biomarkers?
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RNA markers 2000: mRNA

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RNA markers 2000: mRNA
RNA markers 2015: mRNA, miRNA, lncRNA
What RNA species are being developed as biomarkers?

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Human genome: 90% transcribed, BUT only 2% translated!
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The “Total RNA Story” is one of complex interaction
of coding and non-coding RNAs with each other, with
proteins, and with the genome.

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Non-coding RNA: lncRNA
 Long non-coding RNAs (long ncRNAs, lncRNA) are non-
protein coding transcripts longer than 200 nucleotides.
 There are >20,000 lncRNAs in humans. They are inter-genic,
intra-genic, and antisense to traditional mRNA loci.
 Do not contain an open reading frame – (or at least aren't
translated using standard codons).
 May contain a Poly-A or may be absent
 lncRNA expression is generally lower than mRNA. Sensitive
methods such as qPCR are needed for detection &
quantification.
 The important central roles of lncRNA in biology and
pathology are extremely diverse and currently being
elucidated.

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lncRNAs: Broad functionality leads to diverse biological roles
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1. Negatively affect expression
2. Positively affect expression
3. Hybridize to pre-mRNAresulting in an
alternatively spliced transcript
4. Hybridization of sense and antisense transcripts
allow Dicer to generate endogenous siRNAs
5. miRNA ‘sponges’
6. The complex of lncRNAand specific protein
partners can modulate the activity of the protein
7. Involved in structural and organizational roles in
the cell
8. Alters protein localization in the cell
9. Affects epigenetic process
 Imprinting
 Cancer and cancer
progression
 Development
 Signaling

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Non-coding RNA: miRNAs, Master regulators of gene expression
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 miRNAs are ~21 nucleotide, small non-coding RNAs that are conserved in all eukaryotes and
expressed in all mammalian tissues.
 Changes in miRNA expression can be correlated with gene expression changes in development,
differentiation, signal transduction,infection, aging, and disease.
 Transcribedby RNAPolymerase 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.
 Mature miRNAs are incorporated in RISC.
 miRNA guide RISC to inhibit translation of, destabilize, or
specifically cleave mRNA targets.
 ~1000-3000in humans

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Tools for qRTPCR-Based gene expression profiling
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RT2 Profiler and miScript PCR Arrays
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Innovative content, extensive species coverage, and formats for every real-time instrument
 Biologically relevantgene content
 Not simply biochemicalpathways or kinase cascades
 Published association with the biological or disease
pathways gathered from overlapping sources,including:
 Multiple publicly accessible databases
 Text mining relevant literature
 Technically relevantgene content(mRNA)
 Use genes that are regulated at the RNA level
 Specific feedbackfrom thought leaders
 What species?
 Human, mouse, rat
 Cow, horse, dog, chicken, fruit fly, CHO, zebrafish, pig,
rabbit, rhesus macaque
 What formats?
 96-well, 384-well, Fluidigm® BioMarkTM

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Pioneering content to accelerate your hypothesis testing
 Pathways
 Apoptosis
 Biomarkers
 Cell Cycle
 Cytokine & Inflammation
 ECM & Adhesion
 Neuroscience
 Signal Transduction
 Stem Cell & Development
 Toxicology & Drug ADME
 Diseases
 Specific Cancers
 Cardiovascular Diseases
 CNS Disorders
 Immune Disorders
 Infectious Diseases
 Metabolic Diseases
 Targeted miRNomes
 Targeted miRNomes
 miFinder 384HC: Best expressed,
best characterized miRNAs
 Serum & Plasma 384HC: Best expressed
miRNAs in serum/plasma
 Cancer PathwayFinder 384HC
 Liver miFinder 384HC
 Focused Arrays
 miFinder
 Cancer specific arrays
 Apoptosis
 Cell Differentiation & Development
 Diabetes
 Inflammatory Response & Autoimmunity
 T-Cell & B-Cell Activation
 Tumor Suppressor miRNAs
 Serum & Plasma
mRNA Arrays miRNA Arrays

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RT2 mRNA and lncRNA System, miScript System
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Quantify mRNA, lncRNA, miRNA from ANY sample on ANY real-time instrument
1. Isolate total RNA
2. Perform Reverse-transcription
3. (Optional): Perform PreAMP
4. Prepare PCR pre-mix
5. Load PCR arrays or plates
6. Perform real-time PCR
7. Analyze data

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Profiling example: miRNAs present in biofluids
serum 20 ul urine 20ul & preamp csf 20ul & preamp
In each array, expression values normalized to mean of expressed sequences

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RNAexpression distinguishesthyroid cancer frombenign nodules
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Thyroid nodules and thyroid cancer
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 Thyroid nodules are very common
 525,000 U.S. patients each year undergo
fine needle aspiration (FNA) biopsies to rule
out cancer in thyroid nodules
 Some commercial malignancy classifier
assays are available but their performance
requires further evaluation

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Profiling workflow
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 Samples: Frozen thyroid tissue
 Benign: Nodular hyperplasia (NH) and follicular adenoma (FA)
 Cancer: Papillary thyroid cancer (PTC) and follicularvariant of papillary thyroid
carcinoma (FVPTC)
 Sample prep: miRNeasy Mini Kit
 Real-time PCR Assays:
 mRNAand lncRNA: RT2 Expression System
 mRNA: Thyroidcancer-related mRNAs
 lncRNA: Cancer PathwayFinder
 miRNA: miScript PCR System
 miRNA: miFinder 384HC
 Data analysis: GeneGlobeData Analysis Center
 Further interpretation: Ingenuity Pathway Analysis

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mRNA profiling of thyroid nodules and thyroid cancer
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68 mRNAs up-regulated
 CHI3L1 (Jarzab et al., Cancer
Res, 2005)
46 mRNAs down-regulated
 cKIT (Marini et al., Journal of
Thyroid Research, 2011)
Thyroid cancer-focusedarray

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miRNA profiling of thyroid nodules and thyroid cancer
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17 miRNAs up-regulated
 hsa-miR-146b-5p & hsa-miR-221-3p
(Chen et al., Mod Pathol, 2008)
 hsa-miR-31-5p and hsa-miR-31-3p
~100X up-regulated
4 miRNAs down-regulated
 hsa-miR-211-3p (down-regulatedin
breast cancer)
miFinder 384HC (core miRNome)

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lncRNA profiling of thyroid nodules and thyroid cancer
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 PTCSC1, papillary thyroid carcinoma susceptibility
candidate 1
 A susceptibility locus for papillary thyroid
carcinoma on chromosome 8q24
 SNHG16 (ncRAN) disregulated in colorectal cancer
and bladder cancer
 Down-regulation of ncRAN contributes to cell
migration and invasion
 BANCR, BRAF-activated non-protein coding RNA
 Down-regulation of BANCR promotes metastasis in
NSCLC
8 lncRNAs up-regulated
 PCA3 (oncogene)
 MIR31HG (114-fold upregulated)
8 lncRNAs down-regulated
 LINC00261 and PTCSC1 (tumor-suppressor genes)
lncRNA Cancer PathwayFinder

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An lncRNA expression panel can distinguish thyroid cancer
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TPR FPR SPC PPV NPV ACC AUC
16-gene 1.00 0.08 0.92 0.90 1.00 0.96 0.99
An unsupervised hierarchical clustering with
selected lncRNAs showed expression
discrimination pattern of the known groups.
Class probability plot when using a16-gene signature
panel. Red bar: benign; Blue bar: cancer. X: class
probability, >0.5 means classified as cancer.
Cross-verification of classifier
HAND2-AS1 LINC00963 SNHG16 NBR2 PTCSC1 RMRP MALAT1 HEIH
TUG1 LINC00261 CAHM BANCR LINC00538 LINC00312 IPW XIST

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Can integration of mRNA, miRNA and ncRNAdata improve signatures?
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MicroRNA and messenger RNA profiling reveals new biomarkers and mechanisms for RDX induced
neurotoxicity.
Deng Y, Ai J, Guan X, Wang Z, Yan B, Zhang D, Liu C, Wilbanks MS, Escalon BL, Meyers SA, Yang MQ, Perkins EJ.
Integrating microRNA and mRNA expression profiles in response to radiation-induced injury in rat lung.
Xie L, Zhou J, Zhang S, Chen Q, Lai R, Ding W, Song C, Meng X, Wu J.
Integration of mRNA expression profile, copy number alterations, and microRNA expression levels in breast
cancer to improve grade definition.
Cava C, Bertoli G, Ripamonti M, Mauri G, Zoppis I, Della Rosa PA, Gilardi MC, Castiglioni I.
Screening biomarkers of prostate cancer by integrating microRNA and mRNA signatures.
Feng J, Huang C, Diao X, Fan M, Wang P, Xiao Y, Zhong X, Wu R.
A Systems Biology Approach to Characterize Biomarkers for Blood Stasis Syndrome of Unstable Angina
Patients by Integrating MicroRNA and Messenger RNAExpression Profiling.
Wang J, Yu G.

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Ingenuity Pathway Analysis (IPA)
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Asking “what’s next?” by modeling, analyzing, and understanding complex 'omics data
 Integrate gene expression/miRNA/genomics data
 Identification of upstream regulators, downstream targets
 Insight into molecular interactions and cellular phenotypes
 Discoveries about disease processes
 5 million relationships in IPA database
http://www.ingenuity.com/products/ipa

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Understanding miRNA regulation of mRNAs in thyroid carcinoma
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microRNA Target Filter: Searched for mRNA targets that were differentially expressed
in papillary thyroid carcinoma (PTC) and follicular variant of papillary thyroid
carcinoma (FVPTC):
 Example: 7 aberrantly expressed miRNAs known to target 7 mRNAs
 Filters employed:
 Inverse relationship between miRNA & mRNA expression
 Relationships reported in Cancer and/or Endocrine Disorders
 Thyroid gland expression and selected signaling pathways
http://www.ingenuity.com/products/ipa

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Differentiallyexpressed miRNAs & mRNAs affect invasiveness
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Importance of miRNA regulation is shown here by targeting genes involved in
invasion of cells necessary for tumor progression and metastasis
http://www.ingenuity.com/products/ipa

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miRNA-mRNA-lncRNAexpression patternsaffect metastasis progression
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Using MAP (Molecule Activity Predictor): Metastasis is predicted to be increased based on
observed expression pattern of miRNA, mRNA and lncRNA
http://www.ingenuity.com/products/ipa

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Total RNA Discovery with QIAGEN Sample to Insight Workflows
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 Complex interaction of coding and non-coding RNAs
 Engaging in Total RNA Discovery can result in a deeper understanding of
the functional relationships of different RNAmolecules
 QIAGEN offers Sample to Insight solutions for Total RNADiscovery
 Sample prep: any and all samples
 Real-time PCR assays and arrays: miRNA, mRNA, lncRNA
 Primary data analysis:onlinetools
 Interpretation:IngenuitySystems IPA
 Choose QIAGEN and turn your hypotheses into actionable insights!

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All RNAresources at www.qiagen.com/geneglobe
Questions to: qiawebinars@qiagen.com

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AACR 2015, QIAGEN 2015.4 37