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The Journal of Molecular Diagnostics, Vol. 16, No. 2, March 2014
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TECHNICAL ADVANCE Detection and Quantification of BCR-ABL1 Fusion Transcripts by Droplet Digital PCR Q16
Lawrence J. Jennings,*y David George,* Juliann Czech,* Min Yu,* and Loren Josephz From the Department of Pathology and Laboratory Medicine,* Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago; the Department of Pathology and Laboratory Medicine,y Northwestern University Feinberg School of Medicine, Chicago; and the Department of Pathology,z The University of Chicago, Chicago, Illinois Accepted for publication October 24, 2013. Address correspondence to Lawrence J. Jennings, M.D., Ph.D., D(ABHI), FCAP, Ann & Robert H. Lurie Children’s Hospital of Chicago, 2515 N. Clark St., Deming Bldg.dRoom 5027, Chicago, IL 606143363. E-mail: ljennings@ luriechildrens.org.
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Monitoring BCR-ABL1 fusion transcripts by real-time quantitative RT-PCR has become an important clinical test for the management of patients with chronic myeloid leukemia. However, it has some inherent limitations with regard to its lower limit of detection and limit of quantification. Improvement in the lower limit of detection could aid clinicians in selecting candidates for discontinuation of tyrosine kinase inhibitors without relapse. Improvement in the limit of quantification may also avoid unnecessary testing or changes in therapy. Here, we demonstrate the advantages of droplet digital RTPCR with regard to simplicity, lower limit of detection, and limit of quantification. We expect the advantages of droplet digital RT-PCR will make it the preferred method for quantification of BCR-ABL1 fusion transcripts. (J Mol Diagn 2014, 16: 1e6; http://dx.doi.org/10.1016/j.jmoldx.2013.10.007)
Several studies have demonstrated the clinical utility of quantifying BCR-ABL1 fusion transcript levels in chronic myeloid leukemia (CML) patients.1e7 Typically, this has been performed using real-time quantitative RT-PCR (RTqPCR). However, as a result of the rapid adoption of BCRABL1 transcript monitoring by clinical laboratories, testing methodologies vary considerably, as does the analytical performance.8 Efforts to harmonize methods and reporting have been underway for several years and have been aided by the manufacturing of commercially available calibrators.4,9e12 Nevertheless, analytical performance continues to vary considerably across laboratories because much of this variability may be inherent in the RT-qPCR methodology.10 The lower limit of detection (LOD) of the RT-qPCR method may be insufficient for managing CML patients who have had a good response to tyrosine kinase inhibitors (TKIs). The International Randomized Study of Interferon and STI571 (IRIS) trial defined a major molecular response as a 3-log reduction in BCR-ABL1 transcript levels from a median value at diagnosis, and this 3-log reduction has been defined as 0.1% on the International Scale (IS).1,2,4 Subsequently, a complete molecular response has been defined by the European LeukemiaNet as undetectable BCR-ABL1 transcripts in two consecutive, high-quality samples by a test
with an LOD of 0.01% IS.13 However, an even lower LOD may be necessary to manage those patients who may be eligible for TKI cessation.14,15 Several investigators have explored the discontinuation of imatinib for patients who had maintained a complete molecular response for an extended period of time.16e23 In all cases, regardless of the center monitoring BCR-ABL1 fusion transcripts, some patients maintain long-term remission, whereas many others relapse, indicating that the LOD for these tests is insufficient to differentiate these two groups of patients. Given the greater therapeutic responses exhibited with second-generation tyrosine kinase inhibitors, a larger proportion of patients can be expected to reach complete molecular response, and therefore, a more exact definition of complete molecular response and a lower LOD will be necessary to select candidates for discontinuation of TKIs with lower risk of relapse.15 The accuracy of current RT-qPCR methods, especially at the lower limits of quantification (LOQ), may also affect the clinical decisions on how CML patients are monitored and therapeutically managed. Rising BCR-ABL1 fusion transcript levels require more frequent patient follow-up and testing to detect development of therapy resistance and to exclude noncompliance to TKI therapy.13,24 How high the
Copyright ª 2014 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jmoldx.2013.10.007
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Jennings et al fusion transcript level must rise before it is considered biologically (and therefore clinically) relevant is not clear. Published recommendations range from an increase of 0.3 to 0.5 log (ie, a 200% to 316% increase).10,25e27 These recommendations, unfortunately, are based on the degree of accuracy of the RT-qPCR method and not on biological variation. Therefore, improvement in the accuracy of quantification, especially at the lower levels of detection and therapeutic thresholds (eg, major molecular response) could greatly affect the management of these patients by allowing closer monitoring of those with biologically relevant changes in fusion transcript level, and avoiding unnecessary follow-up and monitoring in those without. The advantages of digital PCR for quantifying DNA copy number and rare events have been highlighted previously.28e35 As compared to quantitative analog PCR, digital PCR gives the absolute copy number, so standard curves are not necessary and data are more accurate. Therefore, we developed a droplet digital RT-PCR (RT-ddPCR) test to quantify BCR-ABL1 fusion transcripts to demonstrate its advantages over the widely adopted conventional RT-qPCR.
Materials and Methods Samples
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With approval of the institutional review board, previously extracted total RNA from pre- and post-treatment clinical samples were de-identified and pooled to create a single sample. Specifically, a diagnostic sample with a relative BCR-ABL1 transcript ratio near the laboratory median was pooled with nine follow-up samples that had undetectable BCR-ABL1 transcript levels (LOD >4 log). This pooled sample was tested and compared to ARQ IS calibrator panels (Asuragen, Austin, TX) to show an undiluted concentration of 10% on the IS. The diluent RNA was obtained from a healthy volunteer, and total RNA was extracted using the QIAamp RNA Blood Kit by Qiagen (Cat#52304; Qiagen, Valencia, CA). The RNA concentration and purity was assessed using a NanoDrop spectrophotometer by NanoDrop Technologies (Wilmington, DE). Each of the ARQ IS calibrator panels (e13a2 and e14a2) consists of four calibrators of BCR-ABL1 to control genes (10%, 1%, 0.1%, and 0.01% IS) and a negative control.
Preparation of Dilutions To assay for the BCR-ABL1 fusion transcript, the pooled RNA was serially diluted into the diluent RNA. Using 100 ng/mL for the pooled RNA and diluent, a 10-fold dilution series was performed to make the following concentrations: 100, 101, 102, 103, 104, and 105. Given the targeted starting concentration of 10% IS, these correspond to the following percentage IS values: 10%, 1%, 0.1%, 0.01%, 0.001%, and 0.0001%, respectively. The diluent RNA also served as a negative control. To assay for BCR, a similar
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dilution was performed, but the pooled and diluent RNA concentration was 8 ng/mL. The ARQ e13a2 and the ARQ e14a2 panels consisted of four diluted calibrators at 10%, Q6 1%, 0.1%, 0.01%, and a negative control. To assess the lower LOD, a 0.001% IS dilution was generated by making a 1:10 dilution of 0.01% IS with the negative RNA that was provided with each ARQ IS calibrator panel.
Design of Primers and Probes TaqMan MGB probes and primers (Life Technologies, Carlsbad, CA) were generated for the BCR-ABL1 fusion transcripts (e13a2 and e14a2) and the BCR transcripts (Table 1). Human ½T1 mRNA sequences for BCR-ABL1 (e13a2) and BCR were downloaded from the National Center for Biotechnology Information Nucleotide database (NCBI, http://www.ncbi.nlm. Q7 nih.gov/nucleotide, last accessed December 12, 2012), and cross-referenced with the sequences from Asuragen’s ARQ IS calibrator kits to ensure that the probe and primers could detect the BCR-ABL1 and BCR transcripts in the ARQ IS calibrator kits. The sequence of interest was transferred to Primer Express version 2.0 software (Applied Biosystems, Life Technologies) for probe and primer generation. Within Primer Express, the setting of the TaqMan MGB probe and primer design was used to generate probes and primers. The BCR-ABL1 probe was generated with a FAM reporter, and the BCR probe was generated with a VIC reporter.
Droplet Digital PCR Before the RT-PCR reaction mixture assembly, all of the RNA samples, including the ARQ IS calibrator panel, were incubated for 5 minutes at 75 C. The BCR-ABL1 and BCR transcripts were tested separately in different wells to account for the difference in input total RNA. The RT-PCR reaction mixture was assembled by using the One-Step RT-ddPCR kit from Bio-Rad Laboratories (Cat# 1863021; Hercules, CA). The BCR primer and probes were at final concentrations of 900 and 250 nmol/L, and 40 ng of template in a final volume of 20 mL. The BCR-ABL1 primer and probes were at final concentrations of 2250 and 625 nmol/L, and 600 ng of template in a final volume of 20 mL. The 20-mL droplet digital PCR (ddPCR) reaction mixture was then loaded into the BioRad DG8 disposable droplet generator cartridge. A volume of Table 1 Primer and Probe Sequences for BCR-ABL1 and BCR Transcripts Primer name
Primer sequence
BCR-ABL1 forward BCR-ABL1 reverse BCR-ABL1 probe
50 -CATTCCGCTGACCATCAATA-30 50 -ACACCATTCCCCATTGTGAT-30 50 -/56-FAM/CCCTTCAGCGGCCAGTAGCATCTGA-30 0 5 -CAGTGCGTGGAGGAGATCGA-30 50 -CGATGCCCTCTGCGAAGTTG-30 50 -VIC-CAGCCTTCGACGTCAA-30
BCR forward BCR reverse BCR probe
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BCR-ABL1 Detection by RT-ddPCR
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70 mL of droplet generation oil was loaded into the oil well for each sample. The cartridge was placed into the droplet generator. The generated droplets were transferred to an Eppendorf 96-well twin.tec PCR plate (Eppendorf, Hamburg, Germany). The plate was heat-sealed with a Thermo Scientific Easy Pierce pierceable foil seal from Thermo Fisher Scientific (Cat#AB-0757; Waltham, MA) and then placed on a thermal cycler and amplified to the endpoint. Thermal-cycling conditions were 60 C 30 minutes (1 cycle), 95 C 5 minutes (1 cycle), 95 C 30 seconds (ramp rate 2.5 C/second), and 59 C 60 seconds (ramp rate 2.5 C/second) (40 cycles), 98 C 10 minutes (1 cycle), and a 12 C hold. After PCR, the 96-well PCR plate was loaded on BioRad’s QX100 droplet reader, which reads the droplets from each well of the plate. Analysis of the ddPCR data was performed with QuantaSoft analysis software version 1.3.2.0 that accompanied the QX100 droplet reader. This system partitions the sample into an emulsion of up to 20,000 stable, nanoliter droplets. The emulsion is thermocycled, and each droplet serves as an independent reactor for PCR. After PCR, each droplet is read with a two-color fluorescence detector to determine how many droplets have positivity for the BCR-ABL1 fusion transcript, BCR transcript, or both. For these studies, BCR-ABL1 and BCR were analyzed separately so that more RNA could be added to the BCR-ABL1 wells and rare events could be detected. Replicates were tested by two technologists over 20 days.
Results Analytical performance was assessed using IS calibrators and dilutions of the pooled clinical samples. A total of six replicates of each concentration were performed except for the lowest concentration of the IS calibrator (0.001%), which was tested 9 times, and the negative sample, which was tested 21 times. Samples were blinded, and replicate measures were performed by two technologists over 20 days. Data from both the calibrators and dilutions showed
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311 312 313 314 315 316 Figure 1 Log-log plot demonstrating correla317 tion of BCR-ABL1/BCR ratios to IS calibrators. Total 318 RNA was extracted from pooled patient samples 319 and diluted in total RNA from healthy donors. Replicates were tested together with IS calibrators 320 by two technologists over 20 days. Data show near 321 perfect correlation between sample dilutions and 322 calibrators. 323 324 325 326 327 328 329 330 remarkable linearity, trueness, and precision down to 331 ½F1½F2 ½F2 0.001% (Figures 1 and 2, and Tables 2 and 3). After con- ½F1 332 ½T2½T3 ½T3 verting to log-log scale, linear regression showed no ½T2 333 2 concentration-dependent bias, and R equaled 0.9995 and 334 0.999 for the calibrators and dilutions, respectively. More335 over, the dilutions of the pooled diagnostic sample 336 337 demonstrated near perfect correlation to the calibrators. All 338 negative samples were entirely negative. 339 Measurements of the lowest concentrations (0.001% IS 6 340 calibrator and 10 dilution) had some replicates that were 341 positive and others that were negative, indicating that these 342 concentrations were beyond the LOD for a single well. 343 Because the negative samples showed no background, even 344 a single positive droplet per well can be detected. Therefore, 345 by combining the counts from multiple replicate wells, the 346 limits of detection and quantification can be extended 347 further, and the copies of BCR-ABL1 transcripts in a larger 348 349 sample volume can be quantified. For example, as demon350 strated with the dilution samples, by combining the counts 351 of six wells, the LOD can be lowered to 0.0001% IS 352 although the quantification is inaccurate. As demonstrated 353 with the IS calibrators, by combining the counts of nine 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 Figure 2 Log transformations of BCR-ABL1/BCR ratios show linearity 369 and lack of bias. For both the dilution samples and the IS calibrator 370 samples, the slope equals 1, indicating no concentration-dependent bias, 371 and R2 is nearly 1, indicating remarkable correlation. 372
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Jennings et al Table 2
Analytical Performance Parameters of RT-ddPCR
N
Target value (%)
Data mean
SD
CV%
6 6 6 6 9
10 1 0.1 0.01 0.001
0.20482 0.0239796 0.0023995 0.0002233 2.023 105
0.0311485 0.0039164 0.0006142 6.693 105 2.928 105
15 16 26 30 145
IS calibrators were tested by two technologists over 20 days. Note that the lowest concentration (0.001% IS) had several negative wells resulting in a high SD and CV%. CV%, percent coefficient of variation.
wells, the LOQ of the calibrators can be lowered to 0.001%. The differences in the LOD for these sample types reflect the differences in amplifiable RNA that is added to each well. For this assay, we determined that 600 ng of total RNA can be added to a single well without affecting the accuracy (data not shown), so for the dilution samples, 600 ng was added to each well. For the IS calibrator samples, 5 mL was added to each well. For comparison, the number of copies of BCR in the dilution samples was approximately 366 copies/40 ng (or approximately 5489 copies/600 ng), whereas the number of copies of BCR in the IS calibrators was approximately 2750 copies/5 mL. Therefore, 1 mL of the IS calibrator is equivalent to approximately 60 ng of total RNA. If a lower LOD or more accurate data were required, the counts from additional wells could be combined, provided sufficient amplifiable RNA were available.
Discussion Herein, we demonstrate the advantages of RT-ddPCR for quantifying BCR-ABL1 fusion transcripts as compared to the widely adopted standard method, RT-qPCR. The most important advantages are improvement in simplicity, LOD, and LOQ. The advantages of digital PCR were first described 20 years ago.36 At that time, limiting dilutions, PCR, and Poisson statistics were used to quantitate the total number of amplifiable targets within a sample. The recent introduction of ddPCR has greatly simplified the process. With ddPCR, samples are partitioned into nanoliter droplets so that each droplet becomes a separate sample with zero, one, or more copies of the target DNA molecule. The droplets are thermally cycled to endpoint, and each droplet is read to determine the fraction of positive droplets. Using Poisson statistics, the absolute number of starting copies can very accurately be determined.37 Because ddPCR uses endpoint detection of the amplification product, the efficiency of amplification is much less of a concern, and calibration curves are not necessary. The advantages of digital PCR with regard to test development, LOD, and accuracy were highlighted previously.28e33 Using IS calibrators and dilutions of pooled clinical samples, we demonstrate an LOD of 0.001% and 0.0001%,
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respectively. The difference in the LOD for these sample types is a reflection of the total amount of RNA tested. For the IS calibrators, 5 mL of sample was added per well (equivalent to approximately 300 ng of total RNA), and for the dilution samples, 600 ng of sample was added per well. Given the negative background, higher concentrations per well and/or more wells per sample would theoretically allow one to extend the LOD even lower. Well-optimized RTqPCR assays cannot achieve the LOD demonstrated here.8,38e40 For RT-qPCR, interference from nontarget RNA and nonspecific amplification prevents detection of very rare transcripts. For example, a well-optimized assay may be able to detect 10 copies per well.14 However, RTddPCR partitions the sample into nanoliter droplets, thus minimizing interference from nontarget RNA and nonspecific amplification so that even a single, rare event can be detected. Therefore, with a negative background, the LOD using RT-ddPCR is only limited by the amount of patient material that is tested. Perhaps the most important advantage of RT-ddPCR over RT-qPCR is the improvement in quantitation. Here, we demonstrate absolute copy number determination without bias as compared to the IS calibrators. Furthermore, for those samples with concentrations greater than the LOD for a single well, the coefficient of variation ranged from 8% to 23% for the clinical dilution series, and 15% to 30% for the IS calibrators. By combining wells, the degree of imprecision can be reduced even further. This level of precision is far better than that achieved with well-optimized RT-qPCR assays.8,38e40 In a multi-institutional study to harmonize BCR-ABL1 quantification by RT-qPCR and reporting on the IS, only 58% of centers achieved a bias within 1.2-fold and an imprecision less than 5-fold.10 The use of digital PCR to detect BCR-ABL1 fusion transcripts has been reported previously.41 For that study, digital PCR was used in conjunction with a pre-amplification step. Digital PCR was performed using the BioMark Real-Time PCR System (Fluidigm, South San Francisco, CA), which partitions the sample into 765 separate wells. The investigators were able to demonstrate a 2- to 3-log improvement in the LOD as compared to conventional RT-qPCR. Table 3
Analytical Performance Parameters of RT-ddPCR
N
Target value (%)
Data mean
SD
CV%
21 6 5 6 6 6 6
0 10 1 0.1 0.01 0.001 0.0001
0 0.22354111 0.02718138 0.002443 0.00026597 2.0253 105 9.5105 106
0 0.01722102 0.00393607 0.00021324 4.3107 105 4.6423 106 1.0637 105
NA 8 14 9 16 23 112
Total RNA was extracted from pooled patient samples and diluted in total RNA from a healthy donor. Replicates were tested together by two technologists over 20 days. Note that the lowest concentration (0.0001% IS) had several negative wells, resulting in a high SD and CV%. Q1 CV%, percent coefficient of variation; NA, not applicable.
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BCR-ABL1 Detection by RT-ddPCR However, the method is semiquantitative because of the variable efficiency associated with the pre-amplification step.14 The pre-amplification step was necessary to lower the LOD (ie, improve analytical sensitivity). For our assay, the sample of a single well is partitioned into up to 20,000 droplets. The increased partitioning further increases the limits of detection and quantification, so pre-amplification is not necessary, and the test can be performed as a one-step RT-PCR. Adding the counts of additional wells can further improve LOD and LOQ. Other investigators have demonstrated the advantages of quantifying genomic BCR-ABL1 DNA.42e44 The advantages as compared to conventional RT-PCR include improved LOD (1 to 2 log) and a more stable analyte that does not need to be normalized to the expression level of a housekeeping gene. However, the breakpoints for each patient are highly variable, requiring development and validation of primers and probes specific for each patient. This is technically challenging and labor intensive, and not easily adapted to the clinical laboratory. However, when rapidly sequencing and characterizing genomic BCR-ABL1 DNA becomes possible, ddPCR will have obvious advantages as compared to qPCR for monitoring disease burden. In addition to the improvement in accuracy and LOD/LOQ, limited only by the amount of patient material, development and validation of patient-specific assays will become easier because efficiency of amplification is less of a concern with ddPCR.
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Grigg AP, Melo JV, Hughes TP: Patients with chronic myeloid leukemia who maintain a complete molecular response after stopping imatinib treatment have evidence of persistent leukemia by DNA PCR. Leukemia 2010, 24:1719e1724 Benjamini O, Kantarjian H, Rios MB, Jabbour E, O’Brien S, Jain P, Cardenas-Turanzas M, Faderl S, Garcia-Manero G, Ravandi F, Borthakur G, Quintas-Cardama A, Cortes J: Patient-driven discontinuation of tyrosine kinase inhibitors: single institution experience. Leuk Lymphoma 2013, [Epub ahead of press] Thielen N, van der Holt B, Cornelissen JJ, Verhoef GE, Gussinklo T, Biemond BJ, Daenen SM, Deenik W, van Marwijk Kooy R, Petersen E, Smit WM, Valk PJ, Ossenkoppele GJ, Janssen JJ: Imatinib discontinuation in chronic phase myeloid leukaemia patients in sustained complete molecular response: a randomised trial of the DutchBelgian Cooperative Trial for Haemato-Oncology (HOVON). Eur J Cancer 2013, 49:3242e3246 Ross DM, Branford S, Seymour JF, Schwarer AP, Arthur C, Yeung DT, Dang P, Goyne JM, Slader C, Filshie RJ, Mills AK, Melo JV, White DL, Grigg AP, Hughes TP: Safety and efficacy of imatinib cessation for CML patients with stable undetectable minimal residual disease: results from the TWISTER study. Blood 2013, 122: 515e522 Yhim HY, Lee NR, Song EK, Yim CY, Jeon SY, Shin S, Kim JA, Kim HS, Cho EH, Kwak JY: Imatinib mesylate discontinuation in patients with chronic myeloid leukemia who have received front-line imatinib mesylate therapy and achieved complete molecular response. Leuk Res 2012, 36:689e693 Takahashi N, Kyo T, Maeda Y, Sugihara T, Usuki K, Kawaguchi T, Usui N, Okamoto S, Ohe Y, Ohtake S, Kitamura K, Yamamoto M, Teshima H, Motoji T, Tamaki T, Sawada K, Ohyashiki K: Discontinuation of imatinib in Japanese patients with chronic myeloid leukemia. Haematologica 2012, 97:903e906 Hardan I, Stanevsky A, Volchek Y, Tohami T, Amariglio N, Trakhtenbrot L, Koren-Michowitz M, Shimoni A, Nagler A: Treatment with interferon alpha prior to discontinuation of imatinib in patients with chronic myeloid leukemia. Cytokine 2012, 57:290e293 Marin D, Bazeos A, Mahon FX, Eliasson L, Milojkovic D, Bua M, Apperley JF, Szydlo R, Desai R, Kozlowski K, Paliompeis C, Latham V, Foroni L, Molimard M, Reid A, Rezvani K, de Lavallade H, Guallar C, Goldman J, Khorashad JS: Adherence is the critical factor for achieving molecular responses in patients with chronic myeloid leukemia who achieve complete cytogenetic responses on imatinib. J Clin Oncol 2010, 28:2381e2388 Press RD, Galderisi C, Yang R, Rempfer C, Willis SG, Mauro MJ, Druker BJ, Deininger MW: A half-log increase in BCR-ABL RNA predicts a higher risk of relapse in patients with chronic myeloid leukemia with an imatinib-induced complete cytogenetic response. Clin Cancer Res 2007, 13:6136e6143 Press RD, Willis SG, Laudadio J, Mauro MJ, Deininger MW: Determining the rise in BCR-ABL RNA that optimally predicts a kinase domain mutation in patients with chronic myeloid leukemia on imatinib. Blood 2009, 114:2598e2605 Branford S, Rudzki Z, Parkinson I, Grigg A, Taylor K, Seymour JF, Durrant S, Browett P, Schwarer AP, Arthur C, Catalano J, Leahy MF, Filshie R, Bradstock K, Herrmann R, Joske D, Lynch K, Hughes T: Real-time quantitative PCR analysis can be used as a primary screen to identify patients with CML treated with imatinib who have BCR-ABL kinase domain mutations. Blood 2004, 104:2926e2932 George D, Czech J, John B, Yu M, Jennings LJ: Detection and quantification of chimerism by droplet digital PCR. Chimerism 2013, 4:102e108 Weaver S, Dube S, Mir A, Qin J, Sun G, Ramakrishnan R, Jones RC, Livak KJ: Taking qPCR to a higher level: analysis of CNV reveals the
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power of high throughput qPCR to enhance quantitative resolution. Methods 2010, 50:271e276 Hindson BJ, Ness KD, Masquelier DA, Belgrader P, Heredia NJ, Makarewicz AJ, et al: High-throughput droplet digital PCR system for absolute quantitation of DNA copy number. Anal Chem 2011, 83: 8604e8610 Lun FM, Tsui NB, Chan KC, Leung TY, Lau TK, Charoenkwan P, Chow KC, Lo WY, Wanapirak C, Sanguansermsri T, Cantor CR, Chiu RW, Lo YM: Noninvasive prenatal diagnosis of monogenic diseases by digital size selection and relative mutation dosage on DNA in maternal plasma. Proc Natl Acad Sci U S A 2008, 105: 19920e19925 Barrett AN, McDonnell TC, Chan KC, Chitty LS: Digital PCR analysis of maternal plasma for noninvasive detection of sickle cell anemia. Clin Chem 2012, 58:1026e1032 Lo YM, Lun FM, Chan KC, Tsui NB, Chong KC, Lau TK, Leung TY, Zee BC, Cantor CR, Chiu RW: Digital PCR for the molecular detection of fetal chromosomal aneuploidy. Proc Natl Acad Sci U S A 2007, 104:13116e13121 Hindson CM, Chevillet JR, Briggs HA, Gallichotte EN, Ruf IK, Hindson BJ, Vessella RL, Tewari M: Absolute quantification by droplet digital PCR versus analog real-time PCR. Nat Methods 2013, 10:1003e1005 Farago N, Kocsis AK, Lovas S, Molnar G, Boldog E, Rozsa M, Szemenyei V, Vamos E, Nagy LI, Tamas G, Puskas LG: Digital PCR to determine the number of transcripts from single neurons after patchclamp recording. Biotechniques 2013, 54:327e336 Sykes PJ, Neoh SH, Brisco MJ, Hughes E, Condon J, Morley AA: Quantitation of targets for PCR by use of limiting dilution. Biotechniques 1992, 13:444e449 Pinheiro LB, Coleman VA, Hindson CM, Herrmann J, Hindson BJ, Bhat S, Emslie KR: Evaluation of a droplet digital polymerase chain reaction format for DNA copy number quantification. Anal Chem 2012, 84:1003e1011 Jennings LJ, Smith FA, Halling KC, Persons DL, Kamel-Reid S, Molecular Oncology Resource Committee of the College of American Pathologists: Design and analytic validation of BCR-ABL1 quantitative reverse transcription polymerase chain reaction assay for monitoring minimal residual disease. Arch Pathol Lab Med 2012, 136: 33e40 Press RD, Kamel-Reid S, Ang D: BCR-ABL1 RT-qPCR for monitoring the molecular response to tyrosine kinase inhibitors in chronic myeloid leukemia. J Mol Diagn 2013, 15:565e576 Brown JT, Laosinchai-Wolf W, Hedges JB, Watt CD, Van Deerlin VM, Fletcher L, Branford S, Labourier E: Establishment of a standardized multiplex assay with the analytical performance required for quantitative measurement of BCR-ABL1 on the international reporting scale. Blood Cancer J 2011, 1:e13 Goh HG, Lin M, Fukushima T, Saglio G, Kim D, Choi SY, Kim SH, Lee J, Lee YS, Oh SM, Kim DW: Sensitive quantitation of minimal residual disease in chronic myeloid leukemia using nanofluidic digital polymerase chain reaction assay. Leuk Lymphoma 2011, 52:896e904 Bartley PA, Martin-Harris MH, Budgen BJ, Ross DM, Morley AA: Rapid isolation of translocation breakpoints in chronic myeloid and acute promyelocytic leukaemia. Br J Haematol 2010, 149:231e236 Sobrinho-Simoes M, Wilczek V, Score J, Cross NC, Apperley JF, Melo JV: In search of the original leukemic clone in chronic myeloid leukemia patients in complete molecular remission after stem cell transplantation or imatinib. Blood 2010, 116:1329e1335 Mattarucchi E, Spinelli O, Rambaldi A, Pasquali F, Lo Curto F, Campiotti L, Porta G: Molecular monitoring of residual disease in chronic myeloid leukemia by genomic DNA compared with conventional mRNA analysis. J Mol Diagn 2009, 11:482e487
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The Journal of Molecular Diagnostics, Vol. 16, No. 2, March 2014
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TECHNICAL ADVANCE Detection and Quantification of BCR-ABL1 Fusion Transcripts by Droplet Digital PCR Q16
Lawrence J. Jennings,*y David George,* Juliann Czech,* Min Yu,* and Loren Josephz From the Department of Pathology and Laboratory Medicine,* Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago; the Department of Pathology and Laboratory Medicine,y Northwestern University Feinberg School of Medicine, Chicago; and the Department of Pathology,z The University of Chicago, Chicago, Illinois Accepted for publication October 24, 2013. Address correspondence to Lawrence J. Jennings, M.D., Ph.D., D(ABHI), FCAP, Ann & Robert H. Lurie Children’s Hospital of Chicago, 2515 N. Clark St., Deming Bldg.dRoom 5027, Chicago, IL 606143363. E-mail: ljennings@ luriechildrens.org.
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Monitoring BCR-ABL1 fusion transcripts by real-time quantitative RT-PCR has become an important clinical test for the management of patients with chronic myeloid leukemia. However, it has some inherent limitations with regard to its lower limit of detection and limit of quantification. Improvement in the lower limit of detection could aid clinicians in selecting candidates for discontinuation of tyrosine kinase inhibitors without relapse. Improvement in the limit of quantification may also avoid unnecessary testing or changes in therapy. Here, we demonstrate the advantages of droplet digital RTPCR with regard to simplicity, lower limit of detection, and limit of quantification. We expect the advantages of droplet digital RT-PCR will make it the preferred method for quantification of BCR-ABL1 fusion transcripts. (J Mol Diagn 2014, 16: 1e6; http://dx.doi.org/10.1016/j.jmoldx.2013.10.007)
Several studies have demonstrated the clinical utility of quantifying BCR-ABL1 fusion transcript levels in chronic myeloid leukemia (CML) patients.1e7 Typically, this has been performed using real-time quantitative RT-PCR (RTqPCR). However, as a result of the rapid adoption of BCRABL1 transcript monitoring by clinical laboratories, testing methodologies vary considerably, as does the analytical performance.8 Efforts to harmonize methods and reporting have been underway for several years and have been aided by the manufacturing of commercially available calibrators.4,9e12 Nevertheless, analytical performance continues to vary considerably across laboratories because much of this variability may be inherent in the RT-qPCR methodology.10 The lower limit of detection (LOD) of the RT-qPCR method may be insufficient for managing CML patients who have had a good response to tyrosine kinase inhibitors (TKIs). The International Randomized Study of Interferon and STI571 (IRIS) trial defined a major molecular response as a 3-log reduction in BCR-ABL1 transcript levels from a median value at diagnosis, and this 3-log reduction has been defined as 0.1% on the International Scale (IS).1,2,4 Subsequently, a complete molecular response has been defined by the European LeukemiaNet as undetectable BCR-ABL1 transcripts in two consecutive, high-quality samples by a test
with an LOD of 0.01% IS.13 However, an even lower LOD may be necessary to manage those patients who may be eligible for TKI cessation.14,15 Several investigators have explored the discontinuation of imatinib for patients who had maintained a complete molecular response for an extended period of time.16e23 In all cases, regardless of the center monitoring BCR-ABL1 fusion transcripts, some patients maintain long-term remission, whereas many others relapse, indicating that the LOD for these tests is insufficient to differentiate these two groups of patients. Given the greater therapeutic responses exhibited with second-generation tyrosine kinase inhibitors, a larger proportion of patients can be expected to reach complete molecular response, and therefore, a more exact definition of complete molecular response and a lower LOD will be necessary to select candidates for discontinuation of TKIs with lower risk of relapse.15 The accuracy of current RT-qPCR methods, especially at the lower limits of quantification (LOQ), may also affect the clinical decisions on how CML patients are monitored and therapeutically managed. Rising BCR-ABL1 fusion transcript levels require more frequent patient follow-up and testing to detect development of therapy resistance and to exclude noncompliance to TKI therapy.13,24 How high the
Copyright ª 2014 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jmoldx.2013.10.007
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Jennings et al fusion transcript level must rise before it is considered biologically (and therefore clinically) relevant is not clear. Published recommendations range from an increase of 0.3 to 0.5 log (ie, a 200% to 316% increase).10,25e27 These recommendations, unfortunately, are based on the degree of accuracy of the RT-qPCR method and not on biological variation. Therefore, improvement in the accuracy of quantification, especially at the lower levels of detection and therapeutic thresholds (eg, major molecular response) could greatly affect the management of these patients by allowing closer monitoring of those with biologically relevant changes in fusion transcript level, and avoiding unnecessary follow-up and monitoring in those without. The advantages of digital PCR for quantifying DNA copy number and rare events have been highlighted previously.28e35 As compared to quantitative analog PCR, digital PCR gives the absolute copy number, so standard curves are not necessary and data are more accurate. Therefore, we developed a droplet digital RT-PCR (RT-ddPCR) test to quantify BCR-ABL1 fusion transcripts to demonstrate its advantages over the widely adopted conventional RT-qPCR.
Materials and Methods Samples
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With approval of the institutional review board, previously extracted total RNA from pre- and post-treatment clinical samples were de-identified and pooled to create a single sample. Specifically, a diagnostic sample with a relative BCR-ABL1 transcript ratio near the laboratory median was pooled with nine follow-up samples that had undetectable BCR-ABL1 transcript levels (LOD >4 log). This pooled sample was tested and compared to ARQ IS calibrator panels (Asuragen, Austin, TX) to show an undiluted concentration of 10% on the IS. The diluent RNA was obtained from a healthy volunteer, and total RNA was extracted using the QIAamp RNA Blood Kit by Qiagen (Cat#52304; Qiagen, Valencia, CA). The RNA concentration and purity was assessed using a NanoDrop spectrophotometer by NanoDrop Technologies (Wilmington, DE). Each of the ARQ IS calibrator panels (e13a2 and e14a2) consists of four calibrators of BCR-ABL1 to control genes (10%, 1%, 0.1%, and 0.01% IS) and a negative control.
Preparation of Dilutions To assay for the BCR-ABL1 fusion transcript, the pooled RNA was serially diluted into the diluent RNA. Using 100 ng/mL for the pooled RNA and diluent, a 10-fold dilution series was performed to make the following concentrations: 100, 101, 102, 103, 104, and 105. Given the targeted starting concentration of 10% IS, these correspond to the following percentage IS values: 10%, 1%, 0.1%, 0.01%, 0.001%, and 0.0001%, respectively. The diluent RNA also served as a negative control. To assay for BCR, a similar
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dilution was performed, but the pooled and diluent RNA concentration was 8 ng/mL. The ARQ e13a2 and the ARQ e14a2 panels consisted of four diluted calibrators at 10%, Q6 1%, 0.1%, 0.01%, and a negative control. To assess the lower LOD, a 0.001% IS dilution was generated by making a 1:10 dilution of 0.01% IS with the negative RNA that was provided with each ARQ IS calibrator panel.
Design of Primers and Probes TaqMan MGB probes and primers (Life Technologies, Carlsbad, CA) were generated for the BCR-ABL1 fusion transcripts (e13a2 and e14a2) and the BCR transcripts (Table 1). Human ½T1 mRNA sequences for BCR-ABL1 (e13a2) and BCR were downloaded from the National Center for Biotechnology Information Nucleotide database (NCBI, http://www.ncbi.nlm. Q7 nih.gov/nucleotide, last accessed December 12, 2012), and cross-referenced with the sequences from Asuragen’s ARQ IS calibrator kits to ensure that the probe and primers could detect the BCR-ABL1 and BCR transcripts in the ARQ IS calibrator kits. The sequence of interest was transferred to Primer Express version 2.0 software (Applied Biosystems, Life Technologies) for probe and primer generation. Within Primer Express, the setting of the TaqMan MGB probe and primer design was used to generate probes and primers. The BCR-ABL1 probe was generated with a FAM reporter, and the BCR probe was generated with a VIC reporter.
Droplet Digital PCR Before the RT-PCR reaction mixture assembly, all of the RNA samples, including the ARQ IS calibrator panel, were incubated for 5 minutes at 75 C. The BCR-ABL1 and BCR transcripts were tested separately in different wells to account for the difference in input total RNA. The RT-PCR reaction mixture was assembled by using the One-Step RT-ddPCR kit from Bio-Rad Laboratories (Cat# 1863021; Hercules, CA). The BCR primer and probes were at final concentrations of 900 and 250 nmol/L, and 40 ng of template in a final volume of 20 mL. The BCR-ABL1 primer and probes were at final concentrations of 2250 and 625 nmol/L, and 600 ng of template in a final volume of 20 mL. The 20-mL droplet digital PCR (ddPCR) reaction mixture was then loaded into the BioRad DG8 disposable droplet generator cartridge. A volume of Table 1 Primer and Probe Sequences for BCR-ABL1 and BCR Transcripts Primer name
Primer sequence
BCR-ABL1 forward BCR-ABL1 reverse BCR-ABL1 probe
50 -CATTCCGCTGACCATCAATA-30 50 -ACACCATTCCCCATTGTGAT-30 50 -/56-FAM/CCCTTCAGCGGCCAGTAGCATCTGA-30 0 5 -CAGTGCGTGGAGGAGATCGA-30 50 -CGATGCCCTCTGCGAAGTTG-30 50 -VIC-CAGCCTTCGACGTCAA-30
BCR forward BCR reverse BCR probe
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BCR-ABL1 Detection by RT-ddPCR
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70 mL of droplet generation oil was loaded into the oil well for each sample. The cartridge was placed into the droplet generator. The generated droplets were transferred to an Eppendorf 96-well twin.tec PCR plate (Eppendorf, Hamburg, Germany). The plate was heat-sealed with a Thermo Scientific Easy Pierce pierceable foil seal from Thermo Fisher Scientific (Cat#AB-0757; Waltham, MA) and then placed on a thermal cycler and amplified to the endpoint. Thermal-cycling conditions were 60 C 30 minutes (1 cycle), 95 C 5 minutes (1 cycle), 95 C 30 seconds (ramp rate 2.5 C/second), and 59 C 60 seconds (ramp rate 2.5 C/second) (40 cycles), 98 C 10 minutes (1 cycle), and a 12 C hold. After PCR, the 96-well PCR plate was loaded on BioRad’s QX100 droplet reader, which reads the droplets from each well of the plate. Analysis of the ddPCR data was performed with QuantaSoft analysis software version 1.3.2.0 that accompanied the QX100 droplet reader. This system partitions the sample into an emulsion of up to 20,000 stable, nanoliter droplets. The emulsion is thermocycled, and each droplet serves as an independent reactor for PCR. After PCR, each droplet is read with a two-color fluorescence detector to determine how many droplets have positivity for the BCR-ABL1 fusion transcript, BCR transcript, or both. For these studies, BCR-ABL1 and BCR were analyzed separately so that more RNA could be added to the BCR-ABL1 wells and rare events could be detected. Replicates were tested by two technologists over 20 days.
Results Analytical performance was assessed using IS calibrators and dilutions of the pooled clinical samples. A total of six replicates of each concentration were performed except for the lowest concentration of the IS calibrator (0.001%), which was tested 9 times, and the negative sample, which was tested 21 times. Samples were blinded, and replicate measures were performed by two technologists over 20 days. Data from both the calibrators and dilutions showed
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311 312 313 314 315 316 Figure 1 Log-log plot demonstrating correla317 tion of BCR-ABL1/BCR ratios to IS calibrators. Total 318 RNA was extracted from pooled patient samples 319 and diluted in total RNA from healthy donors. Replicates were tested together with IS calibrators 320 by two technologists over 20 days. Data show near 321 perfect correlation between sample dilutions and 322 calibrators. 323 324 325 326 327 328 329 330 remarkable linearity, trueness, and precision down to 331 ½F1½F2 ½F2 0.001% (Figures 1 and 2, and Tables 2 and 3). After con- ½F1 332 ½T2½T3 ½T3 verting to log-log scale, linear regression showed no ½T2 333 2 concentration-dependent bias, and R equaled 0.9995 and 334 0.999 for the calibrators and dilutions, respectively. More335 over, the dilutions of the pooled diagnostic sample 336 337 demonstrated near perfect correlation to the calibrators. All 338 negative samples were entirely negative. 339 Measurements of the lowest concentrations (0.001% IS 6 340 calibrator and 10 dilution) had some replicates that were 341 positive and others that were negative, indicating that these 342 concentrations were beyond the LOD for a single well. 343 Because the negative samples showed no background, even 344 a single positive droplet per well can be detected. Therefore, 345 by combining the counts from multiple replicate wells, the 346 limits of detection and quantification can be extended 347 further, and the copies of BCR-ABL1 transcripts in a larger 348 349 sample volume can be quantified. For example, as demon350 strated with the dilution samples, by combining the counts 351 of six wells, the LOD can be lowered to 0.0001% IS 352 although the quantification is inaccurate. As demonstrated 353 with the IS calibrators, by combining the counts of nine 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 Figure 2 Log transformations of BCR-ABL1/BCR ratios show linearity 369 and lack of bias. For both the dilution samples and the IS calibrator 370 samples, the slope equals 1, indicating no concentration-dependent bias, 371 and R2 is nearly 1, indicating remarkable correlation. 372
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Jennings et al Table 2
Analytical Performance Parameters of RT-ddPCR
N
Target value (%)
Data mean
SD
CV%
6 6 6 6 9
10 1 0.1 0.01 0.001
0.20482 0.0239796 0.0023995 0.0002233 2.023 105
0.0311485 0.0039164 0.0006142 6.693 105 2.928 105
15 16 26 30 145
IS calibrators were tested by two technologists over 20 days. Note that the lowest concentration (0.001% IS) had several negative wells resulting in a high SD and CV%. CV%, percent coefficient of variation.
wells, the LOQ of the calibrators can be lowered to 0.001%. The differences in the LOD for these sample types reflect the differences in amplifiable RNA that is added to each well. For this assay, we determined that 600 ng of total RNA can be added to a single well without affecting the accuracy (data not shown), so for the dilution samples, 600 ng was added to each well. For the IS calibrator samples, 5 mL was added to each well. For comparison, the number of copies of BCR in the dilution samples was approximately 366 copies/40 ng (or approximately 5489 copies/600 ng), whereas the number of copies of BCR in the IS calibrators was approximately 2750 copies/5 mL. Therefore, 1 mL of the IS calibrator is equivalent to approximately 60 ng of total RNA. If a lower LOD or more accurate data were required, the counts from additional wells could be combined, provided sufficient amplifiable RNA were available.
Discussion Herein, we demonstrate the advantages of RT-ddPCR for quantifying BCR-ABL1 fusion transcripts as compared to the widely adopted standard method, RT-qPCR. The most important advantages are improvement in simplicity, LOD, and LOQ. The advantages of digital PCR were first described 20 years ago.36 At that time, limiting dilutions, PCR, and Poisson statistics were used to quantitate the total number of amplifiable targets within a sample. The recent introduction of ddPCR has greatly simplified the process. With ddPCR, samples are partitioned into nanoliter droplets so that each droplet becomes a separate sample with zero, one, or more copies of the target DNA molecule. The droplets are thermally cycled to endpoint, and each droplet is read to determine the fraction of positive droplets. Using Poisson statistics, the absolute number of starting copies can very accurately be determined.37 Because ddPCR uses endpoint detection of the amplification product, the efficiency of amplification is much less of a concern, and calibration curves are not necessary. The advantages of digital PCR with regard to test development, LOD, and accuracy were highlighted previously.28e33 Using IS calibrators and dilutions of pooled clinical samples, we demonstrate an LOD of 0.001% and 0.0001%,
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respectively. The difference in the LOD for these sample types is a reflection of the total amount of RNA tested. For the IS calibrators, 5 mL of sample was added per well (equivalent to approximately 300 ng of total RNA), and for the dilution samples, 600 ng of sample was added per well. Given the negative background, higher concentrations per well and/or more wells per sample would theoretically allow one to extend the LOD even lower. Well-optimized RTqPCR assays cannot achieve the LOD demonstrated here.8,38e40 For RT-qPCR, interference from nontarget RNA and nonspecific amplification prevents detection of very rare transcripts. For example, a well-optimized assay may be able to detect 10 copies per well.14 However, RTddPCR partitions the sample into nanoliter droplets, thus minimizing interference from nontarget RNA and nonspecific amplification so that even a single, rare event can be detected. Therefore, with a negative background, the LOD using RT-ddPCR is only limited by the amount of patient material that is tested. Perhaps the most important advantage of RT-ddPCR over RT-qPCR is the improvement in quantitation. Here, we demonstrate absolute copy number determination without bias as compared to the IS calibrators. Furthermore, for those samples with concentrations greater than the LOD for a single well, the coefficient of variation ranged from 8% to 23% for the clinical dilution series, and 15% to 30% for the IS calibrators. By combining wells, the degree of imprecision can be reduced even further. This level of precision is far better than that achieved with well-optimized RT-qPCR assays.8,38e40 In a multi-institutional study to harmonize BCR-ABL1 quantification by RT-qPCR and reporting on the IS, only 58% of centers achieved a bias within 1.2-fold and an imprecision less than 5-fold.10 The use of digital PCR to detect BCR-ABL1 fusion transcripts has been reported previously.41 For that study, digital PCR was used in conjunction with a pre-amplification step. Digital PCR was performed using the BioMark Real-Time PCR System (Fluidigm, South San Francisco, CA), which partitions the sample into 765 separate wells. The investigators were able to demonstrate a 2- to 3-log improvement in the LOD as compared to conventional RT-qPCR. Table 3
Analytical Performance Parameters of RT-ddPCR
N
Target value (%)
Data mean
SD
CV%
21 6 5 6 6 6 6
0 10 1 0.1 0.01 0.001 0.0001
0 0.22354111 0.02718138 0.002443 0.00026597 2.0253 105 9.5105 106
0 0.01722102 0.00393607 0.00021324 4.3107 105 4.6423 106 1.0637 105
NA 8 14 9 16 23 112
Total RNA was extracted from pooled patient samples and diluted in total RNA from a healthy donor. Replicates were tested together by two technologists over 20 days. Note that the lowest concentration (0.0001% IS) had several negative wells, resulting in a high SD and CV%. Q1 CV%, percent coefficient of variation; NA, not applicable.
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BCR-ABL1 Detection by RT-ddPCR However, the method is semiquantitative because of the variable efficiency associated with the pre-amplification step.14 The pre-amplification step was necessary to lower the LOD (ie, improve analytical sensitivity). For our assay, the sample of a single well is partitioned into up to 20,000 droplets. The increased partitioning further increases the limits of detection and quantification, so pre-amplification is not necessary, and the test can be performed as a one-step RT-PCR. Adding the counts of additional wells can further improve LOD and LOQ. Other investigators have demonstrated the advantages of quantifying genomic BCR-ABL1 DNA.42e44 The advantages as compared to conventional RT-PCR include improved LOD (1 to 2 log) and a more stable analyte that does not need to be normalized to the expression level of a housekeeping gene. However, the breakpoints for each patient are highly variable, requiring development and validation of primers and probes specific for each patient. This is technically challenging and labor intensive, and not easily adapted to the clinical laboratory. However, when rapidly sequencing and characterizing genomic BCR-ABL1 DNA becomes possible, ddPCR will have obvious advantages as compared to qPCR for monitoring disease burden. In addition to the improvement in accuracy and LOD/LOQ, limited only by the amount of patient material, development and validation of patient-specific assays will become easier because efficiency of amplification is less of a concern with ddPCR.
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