RainDance Technologies

Quantitative Cancer Genomic Analysis Using Droplet Digital PCR: Examples with Solid Tumors and Liquid Biopsies in Glioma, Breast, and Colon Cancer plus miRNA & RNA-Direct

Michael Samuels1, Leonora Balaj2, Xandra Breakefield2, Julia Beaver3, Ben Ho Park3, Manuel Krispin4, Saumya Das5, Valerie Taly6 , Pierre Laurent-Puig6 1RainDance Technologies, 2Massachusetts General Hospital, Boston MA, 3Johns Hopkins University, Baltimore MD, 4Zymo Research, Los Angeles CA, 5Beth Israel Deaconess, Boston MA, 6University Paris Descartes, FR

• High sensitivity

• Multiplex analysis

• Single pipetting step

www.raindancetech.com

Wide Dynamic Range With High Precision

Digital RNA Counting: 1-Step RT-dPCR Negative Control

Total Human RNA (1.04 ng)

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Human Total RNA Input (ng)

Log Plot

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• 4 different 1-Step RT-PCR Kits worked ‘right out of the box’

• mRNA and viral RNA demonstrated • Broad Dynamic Range (6 logs)

• Highly precise (%CV < 5% for >500 molecules per sample)

• Multiplexing capability demonstrated • True single RNA molecule counting enabled by droplet numbers

Sample #22

Negative for IDH1 mutation

WT

Dual

G395A

• One-Step qMethyl kit from Zymo Research used without optimization

• Kit Methylation Sensitive Restriction Enzymes eliminate the need for bisulfite treatment of DNA

• Linear counting of differences of 5-10% methylation across entire methylation range demonstrated

• Nanograms of input can be used directly without bisulfite treatment or additional purification steps

• Multiplex analysis works well for methylation determination using digital One Step qMethyl kit

Digital PCR Quantification of Breast Tumor Samples Using Normalized Duplex Assays and One Step qMethyl Kit

• Duplex assays using a methylation-independent REF assay enables normalized quantification

• Tumor CCDN2 methylation shows early stage increases; RARB methylation shows less change

• Digital quantification results confirmed by qPCR (data not shown) and consistent with literature

• Multiplexing of assays for methylation analysis demonstrated

4-plex Assay

CCDN2

RAB25

RARB

MGMT

STAGE II STAGE IV

Assay VIC/FAM REF/CCDN2 REF/CCDN2 REF/CCDN2 REF/CCDN2

Template Tumor Control Tumor Control

ng Input 20 20 20 20

ul Input 25 25 25 25

# Droplets 2821297 2695102 2777435 2459884

# NEG 2802492 2682575 2768332 2443456

# REF 6424 8066 7339 12673

# CCDN2 720 61 96 28

%CCDN2/REF 11.2 0.8 1.3 0.2

%RARB/REF 14.4 6.9 10.8 6.1

Cyclin D2

Target

RAR B

Target

Target

REF

Methylation Independent

Reference

Methylation

Target

Digital Methylation Analysis of Breast Cancer

Digital PCR of Glioma Spinal Fluid Exosomes

Digital PCR Analysis of Breast Cancer

Tumor #3 Tumor #4 Tumor #28 Positive Control

H1047 WT

E545K

H1047R

H1047 WT

E545K

H1047R

H1047 WT

E545K

H1047R

H1047 WT

E545K

H1047R

Precise Small-Fold-Change Measurements

Multiplexed 1-Step RT-dPCR Titration

Digital PCR of Colorectal Cancer using Plasma

Submitted for publication-Portions presented at ASCO (June 2013)

Detection of Cancer Specific Mutations in Plasma of Early Stage Breast Cancer Patients

Abstract

Sequencing of tumors identified seven PIK3CA exon 20 mutations (H1047R) and three exon 9 mutations (E545K). Analysis of

tumors by ddPCR confirmed these mutations and identified five additional mutations. Pre-surgery plasma samples (n=29)

were then analyzed for PIK3CA mutations using ddPCR. Of the fifteen PIK3CA mutations detected in tumor tissues by

ddPCR, fourteen of the corresponding mutations were detected in pre-surgical ptDNA specimens, while no mutations were

found in plasma from patients with PIK3CA wild type tumors (sensitivity 93.3%, specificity 100%). Ten patients with pre-

surgery mutation positive ptDNA had ddPCR analysis of post-surgery plasma, which identified five patients with detectable

ptDNA post-surgery.

Julia A. Beaver MD*1, Danijela Jelovac MD*1, Sasidharan Balukrishna MD2, Rory Cochran BS1, Sarah Croessmann BS1, Daniel J. Zabransky BS1, Hong Yuen Wong BS1,

Patricia Valda Toro BS1, Justin Cidado BS1, Brian G. Blair PhD1, David Chu BS1, Timothy Burns MD PhD3, Michaela J. Higgins MB BCh MD4, Vered Stearns MD1, Lisa

Jacobs MD1, Mehran Habibi MD1, Julie Lange MD1, Paula J. Hurley PhD1, Josh Lauring MD PhD1, Dustin VanDenBerg BS1, Jill Kessler BS1, Stacie Jeter BS1, Michael L.

Samuels PhD5, Dianna Maar PhD6, Leslie Cope PhD1, Ashley Cimino-Mathews MD1, Pedram Argani MD1, Antonio C. Wolff MD1¥ and Ben H. Park MD PhD1¥

1The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins 1650 Orleans Street Baltimore, MD 21287 2Christian Medical College Vellore Tamil Nadu, India 632004 3University of Pittsburgh

Hillman Cancer Center Research Pavilion 5117 Centre Avenue Pittsburgh, PA 15213-1863 4Massachusetts General Hospital 55 Fruit Street Boston, MA 02114-2696 5RainDance Technologies, 749

Middlesex Turnpike Billerica, MA 01821 6Bio-Rad Laboratories, Digital Biology Center 7068 Koll Center Pkwy, Suite 401 Pleasanton, CA 94566

RainDrop dPCR Platform

• Contamination-free design

• Simple and flexible workflow

• Robust open reagent platform

Example RainDrop dPCR Data

IDH1 Duplex Analysis

WT

G395A

Sample #11

Positive for IDH1 mutation

Example RainDrop dPCR Data: PIK3CA Triplex Analysis

Example Multiplex Panels:

KRAS Codon 12 and 13

KRAS Panel#1: WT+3 MUTs

G12R

G13D

W T

PCR (-)

G12D

KRAS Panel#2: WT+4 MUTs

G12S

G12C

G12A

WT

G12V PCR (-)

Source Sense Disposable

Chips

*Xeno RNA is a synthetic template spiked-in at a known concentration

R² = 0.9981

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Log expected input

Abstract Picoliter droplet digital PCR was used in separate studies for quantification of mutant IDH1 mRNA in glioma patient

cerebrospinal fluid extracellular vesicles, PIK3CA mutations and methylation of CyclinB2 and Retinoic Acid Receptor

promoters in breast tumors, KRAS and BRAF mutations in colorectal cancer plasma, and multiplexed miRNA

biomarkers from plasma. In addition, we show quantification of RNA molecules directly loaded on the RainDrop

provides highly precise multiplex One-Step RT-PCR measurements across a wide dynamic range.

RainStormTM Droplet Microfluidics

Divide and Count: Single volume divided into countable volume elements

RainDropTM Droplet Digital PCR

Rapid and reproducible processing of millions of reactions is enabled by replacing traditional assay plates and automation

systems with microscopic droplets and disposable fluidic chips. Aqueous samples (beads, cells, enzymes, antibodies, DNA)

can be encapsulated within each droplet, surrounded by an immiscible carrier oil. The droplets are stabilized with bio-

compatible surfactants, allowing for robust manipulations both on and off chip. Droplet fluorescence can be measured by

flowing the droplets through a laser spot positioned in the microfluidic channel.

oil

aqueous

Droplet Fluorescence Readout Droplet Generation

Laser spot

Droplets Flowing In Oil

B: Multiplex with intensity

Different intensity for different targets

Target 1 Target 2

A: Multiplex with color

Different color for different targets

Target 1 Target 2

Probe Concentration sets

Endpoint Fluorescence

oil

Droplet Schematic

surfactant

molecules

fluorocarbon oil

exterior

DNA/RNA Protein/

Antibodies

Single cells

aqueous

interior

Droplets Stable for Off-Chip Collection,

Incubation and Re-injection

Digital PCR with droplet microfluidics. A) Sample containing Target nucleic acids is mixed with assay reagents in 50ul; B) A

microfluidic device is used to divide the sample with assays into 10 million discrete 5 pl droplets such that only a single

target molecule is present in any droplet; C) Hydrolysis of the assay probe during PCR amplification makes droplets

containing specific sequences fluorescent; D) The fluorescence signal intensity is measured as droplets pass one at a time

through a laser spot positioned in a microfluidic channel on the readout chip.

No Target PCR-

droplet

Divide & Collect

PCR Amplification

Count

Background

Target

Sample+ Assay

PCR+ “bright”

droplets

PCR- “dark”

droplets

Target PCR+

droplet A B C D

Single molecule endpoint PCR enables easy multiplexing

Digital Multiplex Analysis With Endpoint PCR

Multiplexing enabled by creating ‘digital’ partitions containing either single target molecules or no targets. A) Each Target

molecule is assayed with a different ‘color’; B) Each Target molecule is assayed with a different ‘endpoint intensity’, with the

fluorescence at PCR endpoint determined by the probe concentration added for each target type (see plot); C) Multiplex

analysis of multiple target types in every sample is performed by combining assays based on color and/or intensity of the

added probes (e.g. Target 1 and 2 use different FAM probe concentrations, Target 3 uses a VIC probe only, Targets 4 and 5

use mixtures of FAM and VIC probes for each target, with the Target 5 probe mixture weighted more with FAM than Target 4).

Data is presented in a 2-D “Cluster Plot” of fluorescence intensity (VIC y-axis; FAM x-axis) with gates used to count droplets.

FAM Intensity

VIC

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C: Multiplex with color and intensity

“Cluster Plot”

EvaGreen® Assays on the RainDrop System

RNA Dilution Series Shows Linearity with 3 Endogenous Targets and Xeno Control

Human Total RNA Input (ng)

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POLR2A GAPDH PPI

Human Total RNA Input (ng)

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Human Total RNA Input (ng)

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Intercalating dye-based assay worked on the RainDrop “off the shelf”

Chen and Balaj, et.al. Molecular Therapy—Nucleic Acids (2013) 2, e109; doi:10.1038/mtna.2013.28

BEAMing and Droplet Digital PCR Analysis of Mutant IDH1 mRNA in

Glioma Patient Serum and Cerebrospinal Fluid Extracellular Vesicles

Abstract

Development of biofluid-based molecular diagnostic tests for cancer is an important step

towards tumor characterization and real-time monitoring in a minimally invasive fashion.

Extracellular vesicles (EVs) are released from tumor cells into body fluids and can provide a

powerful platform for tumor biomarkers because they carry tumor proteins and nucleic acids.

Detecting rare point mutations in the background of wild-type sequences in biofluids such as

blood and cerebrospinal fluid (CSF) remains a major challenge. Techniques such as BEAMing

(beads, emulsion, amplification, magnetics) PCR and droplet digital PCR (ddPCR) are

substantially more sensitive than many other assays for mutant sequence detection. Here, we

describe a novel approach that combines biofluid EV RNA and BEAMing RT-PCR (EV-

BEAMing), as well droplet digital PCR to interrogate mutations from glioma tumors. EVs from

CSF of patients with glioma were shown to contain mutant IDH1 transcripts, and we were

able to reliably detect and quantify mutant and wild-type IDH1 RNA transcripts in CSF of

patients with gliomas. EV-BEAMing and EV-ddPCR represent a valuable new strategy for

cancer diagnostics, which can be applied to a variety of biofluids and neoplasms.

Digital Liquid Biopsy of Cancer using Urine*

Taly V , et. al. Clin Chem. 2013 Aug 12. [Epub ahead of print]

Multiplex Picodroplet Digital PCR to Detect KRAS Mutations in

Circulating DNA from the Plasma of Colorectal Cancer Patients.

Abstract

BACKGROUND:Multiplex digital PCR (dPCR) enables noninvasive and sensitive detection of

circulating tumor DNA with performance unachievable by current molecular-detection

approaches. Furthermore, picodroplet dPCR facilitates simultaneous screening for multiple

mutations from the same sample.METHODS: We investigated the utility of multiplex dPCR to

screen for the 7 most common mutations in codons 12 and 13 of the KRAS (Kirsten rat

sarcoma viral oncogene homolog) oncogene from plasma samples of patients with metastatic

colorectal cancer. Fifty plasma samples were tested from patients for whom the primary tumor

biopsy tissue DNA had been characterized by quantitative PCR.RESULTS: Tumor

characterization revealed that 19 patient tumors had KRAS mutations. Multiplex dPCR analysis

of the plasma DNA prepared from these samples identified 14 samples that matched the

mutation identified in the tumor, 1 sample contained a different KRAS mutation, and 4 samples

had no detectable mutation. Among the tumors samples that were wild type for KRAS, 2 KRAS

mutations were identified in the corresponding plasma samples. Duplex dPCR (i.e., wild-type

and single-mutation assay) was also used to analyze plasma samples from patients with

KRAS-mutated tumors and 5 samples expected to contain the BRAF (v-raf murine sarcoma

viral oncogene homolog B) V600E mutation. The results for the duplex analysis matched those

for the multiplex analysis for KRAS-mutated samples and, owing to its higher sensitivity,

enabled detection of 2 additional samples with low levels of KRAS-mutated DNA. All 5 samples

with BRAF mutations were detected.CONCLUSIONS: This work demonstrates the clinical utility

of multiplex dPCR to screen for multiple mutations simultaneously with a sensitivity sufficient to

detect mutations in circulating DNA obtained by noninvasive blood collection.

Normal Patient Plasma Affected Patient Plasma

miRNA #1 2504 molecules

miRNA #2 1011 molecules

PCR - PCR -

Multiplexed FAM-Probes for Counting Cardiomyopathy-specific Plasma miRNA*

Digital PCR of Plasma miRNA Biomarkers

Rare Mutation Detection

Viral Load

Aneuploidy Detection

Copy Number Variation

Applications

Methylation Quantification

Many Others

miRNA Biomarker Counting

RNA Counting

Xeno

PPI

Neg

GAPDH

POLR2A

Xeno

GAPDH Neg

Xeno

GAPDH Neg

R² = 0.9999

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%CV = 1.3

1.1 fold change

%CV = 1.5

1.2 fold change

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Human Total RNA Input (ng)

Total Human RNA (1.04 ng)

Predesigned TaqMan® MGB gene expression assays – off the shelf!

• Data shows SMN assay primers with EvaGreen detection

• Highly precise quantification (%CV from 0.9 - 8%)

• Over 3 logs of dynamic range

• Demonstrates miRNA biomarker counting from plasma

• Duplexed FAM assays (TaqMan)

• cDNA counts agree with miRNA inputs

*Information reproduced from Trovagene Corporate Slide Deck

Filip Janku MD PhD; MD Anderson Cancer Center

1 Janku et al, AACR-NCI-EROTC International Conference, 2013

*1

• EvaGreen dye purchased from Biotium

CV = 1.5%

CV = 3.3%

CV = 7.6%

Linear Plot

• miRNA cDNA analyzed

*Collaboration with Dr. Saumya Das, Beth Israel Deaconess Medical Center