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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 Samuels 1 , Leonora Balaj 2 , Xandra Breakefield 2 , Julia Beaver 3 , Ben Ho Park 3 , Manuel Krispin 4 , Saumya Das 5 , Valerie Taly 6 , Pierre Laurent-Puig 6 1 RainDance Technologies, 2 Massachusetts General Hospital, Boston MA, 3 Johns Hopkins University, Baltimore MD, 4 Zymo Research, Los Angeles CA, 5 Beth Israel Deaconess, Boston MA, 6 University 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) GAPDH Molecules Counted Human Total RNA Input (ng) Log Plot 1 10 100 1000 10000 100000 1000000 10000000 0.001 0.01 0.1 1 10 100 1000 • 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 MD 2 , Rory Cochran BS 1 , Sarah Croessmann BS 1 , Daniel J. Zabransky BS 1 , Hong Yuen Wong BS 1 , Patricia Valda Toro BS 1 , Justin Cidado BS 1 , Brian G. Blair PhD 1 , David Chu BS 1 , Timothy Burns MD PhD 3 , Michaela J. Higgins MB BCh MD 4 , Vered Stearns MD 1 , Lisa Jacobs MD 1 , Mehran Habibi MD 1 , Julie Lange MD 1 , Paula J. Hurley PhD 1 , Josh Lauring MD PhD 1 , Dustin VanDenBerg BS 1 , Jill Kessler BS 1 , Stacie Jeter BS 1 , Michael L. Samuels PhD 5 , Dianna Maar PhD 6 , Leslie Cope PhD 1 , Ashley Cimino-Mathews MD 1 , Pedram Argani MD 1 , Antonio C. Wolff MD 1¥ and Ben H. Park MD PhD 1¥ 1 The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins 1650 Orleans Street Baltimore, MD 21287 2 Christian Medical College Vellore Tamil Nadu, India 632004 3 University of Pittsburgh Hillman Cancer Center Research Pavilion 5117 Centre Avenue Pittsburgh, PA 15213-1863 4 Massachusetts General Hospital 55 Fruit Street Boston, MA 02114-2696 5 RainDance Technologies, 749 Middlesex Turnpike Billerica, MA 01821 6 Bio-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 1 2 3 4 5 6 7 1 3 5 7 Log observed counts 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. RainStorm TM Droplet Microfluidics Divide and Count: Single volume divided into countable volume elements RainDrop TM 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 Intensity 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) Target Molecules R² = 0.9993 0 5000 10000 15000 20000 25000 30000 35000 0.00 5.00 10.00 15.00 R² = 0.9991 0 5000 10000 15000 20000 25000 30000 35000 0.00 5.00 10.00 15.00 R² = 0.9973 0 500 1000 1500 2000 2500 3000 0.00 5.00 10.00 15.00 POLR2A GAPDH PPI Human Total RNA Input (ng) Target Molecules Human Total RNA Input (ng) Target Molecules 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 0 10000 20000 30000 40000 50000 60000 70000 80000 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 %CV = 1.3 1.1 fold change %CV = 1.5 1.2 fold change GAPDH Molecules Counted 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
