Digital PCR pp 459-474 | Cite as

Droplet Digital PCR for Absolute Quantification of Extracellular MicroRNAs in Plasma and Serum: Quantification of the Cancer Biomarker hsa-miR-141

  • Maria D. Giraldez
  • John R. Chevillet
  • Muneesh TewariEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 1768)


Droplet-based digital PCR provides high-precision, absolute quantification of nucleic acid target sequences with wide-ranging applications for both research and clinical diagnostic applications. Droplet-based digital PCR enables absolute quantification by counting nucleic acid molecules encapsulated in discrete, volumetrically defined water-in-oil droplet partitions. The current available systems overcome the previous lack of scalable and practical technologies for digital PCR implementation. Extracellular microRNAs in biofluids (plasma, serum, urine, cerebrospinal fluid, etc.) are promising noninvasive biomarkers in multiple diseases and different clinical settings (e.g., diagnosis, early diagnosis, prediction of recurrence, and prognosis). Here we describe a protocol that enables highly precise and reproducible absolute quantification of extracellular microRNAs using droplet digital PCR.

Key words

Digital PCR MicroRNA Biofluids Plasma Serum Absolute quantification qPCR Reproducibility 



M.D.G acknowledges initial support from a Rio Hortega Fellowship and later from a Martin Escudero Fellowship. M.T. acknowledges support from the Department of Defense Peer-Reviewed Cancer Research Program Award CA100606 and NIH US National Institutes of Health Transformative R01 grant R01DK085714.


  1. 1.
    Vogelstein B, Kinzler KW (1999) Digital PCR. Proc Natl Acad Sci U S A 96(16):9236–9241CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Sykes PJ, Neoh SH, Brisco MJ, Hughes E, Condon J, Morley AA (1992) Quantitation of targets for PCR by use of limiting dilution. BioTechniques 13(3):444–449PubMedPubMedCentralGoogle Scholar
  3. 3.
    Bustin SA, Nolan T (2004) Pitfalls of quantitative real-time reverse-transcription polymerase chain reaction. J Biomol Tech 15(3):155–166PubMedPubMedCentralGoogle Scholar
  4. 4.
    Rački N, Dreo T, Gutierrez-Aguirre I, Blejec A, Ravnikar M (2014) Reverse transcriptase droplet digital PCR shows high resilience to PCR inhibitors from plant, soil and water samples. Plant Methods 10(1):42CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Dingle TC, Sedlak RH, Cook L, Jerome KR (2013) Tolerance of droplet-digital PCR vs real-time quantitative PCR to inhibitory substances. Clin Chem 59:1670–1672CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Baker M (2012) Digital PCR hits its stride. Nat Methods 9:541–544CrossRefGoogle Scholar
  7. 7.
    Hindson BJ, Ness KD, Masquelier DA, Belgrader P, Heredia NJ, Makarewicz AJ, Bright IJ, Lucero MY, Hiddessen AL, Legler TC, Kitano TK, Hodel MR, Petersen JF, Wyatt PW, Steenblock ER, Shah PH, Bousse LJ, Troup CB, Mellen JC, Wittmann DK, Erndt NG, Cauley TH, Koehler RT, So AP, Dube S, Rose KA, Montesclaros L, Wang S, Stumbo DP, Hodges SP, Romine S, Milanovich FP, White HE, Regan JF, Karlin-Neumann GA, Hindson CM, Saxonov S, Colston BW (2011) High-throughput droplet digital PCR system for absolute quantitation of DNA copy number. Anal Chem 83(22):8604–8610CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Pinheiro LB, Coleman VA, Hindson CM, Herrmann J, Hindson BJ, Bhat S, Emslie KR (2012) Evaluation of a droplet digital polymerase chain reaction format for DNA copy number quantification. Anal Chem 84(2):1003–1011CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Kiss MM, Ortoleva-Donnelly L, Beer NR, Warner J, Bailey CG, Colston BW, Rothberg JM, Link DR, Leamon JH (2008) High-throughput quantitative polymerase chain reaction in picoliter droplets. Anal Chem 80(23):8975–8981CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Hindson CM, Chevillet JR, Briggs H, Gallichotte EN, Ruf IK, Hindson BJ, Vessella RL, Tewari M (2013) Absolute quantification by droplet digital PCR versus analog real-time PCR. Nat Methods 10:1003–1005CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Weiland M, Gao XH, Zhou L, Mi QS (2012) Small RNAs have a large impact: circulating microRNAs as biomarkers for human diseases. RNA Biol 9(6):850–859CrossRefPubMedGoogle Scholar
  12. 12.
    Mitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK, Pogosova-Agadjanyan EL, Peterson A, Noteboom J, O'Briant KC, Allen A, Lin DW, Urban N, Drescher CW, Knudsen BS, Stirewalt DL, Gentleman R, Vessella RL, Nelson PS, Martin DB, Tewari M (2008) Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci U S A 105(30):10513–10518CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Cheng H, Zhang L, Cogdell DE, Zheng H, Schetter AJ, Nykter M, Harris CC, Chen K, Hamilton SR, Zhang W (2011) Circulating plasma MiR-141 is a novel biomarker for metastatic colon cancer and predicts poor prognosis. PLoS One 6(3):e17745CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Bryant RJ, Pawlowski T, Catto JW, Marsden G, Vessella RL, Rhees B, Kuslich C, Visakorpi T, Hamdy FC (2012) Changes in circulating microRNA levels associated with prostate cancer. Br J Cancer 106(4):768–774CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Madhavan D, Zucknick M, Wallwiener M, Cuk K, Modugno C, Scharpff M, Schott S, Heil J, Turchinovich A, Yang R, Benner A, Riethdorf S, Trumpp A, Sohn C, Pantel K, Schneeweiss A, Burwinkel B (2012) Circulating miRNAs as surrogate markers for circulating tumor cells and prognostic markers in metastatic breast cancer. Clin Cancer Res 18(21):5972–5982CrossRefPubMedGoogle Scholar
  16. 16.
    Nadal E, Truini A, Nakata A, Lin J, Reddy RM, Chang AC, Ramnath N, Gotoh N, Beer DG, Chen G (2015) A novel serum 4-microRNA signature for lung cancer detection. Sci Rep 5(12464)Google Scholar
  17. 17.
    Kelly BD, Miller N, Sweeney KJ, Durkan GC, Rogers E, Walsh K, Kerin MJ (2015) A circulating MicroRNA signature as a biomarker for prostate cancer in a high risk group. J Clin Med 4(7):1369–1379CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Madhavan D, Peng C, Wallwiener M, Zucknick M, Nees J, Schott S, Rudolph A, Riethdorf S, Trumpp A, Pantel K, Sohn C, Chang-Claude J, Schneeweiss A, Burwinkel B (2016) Circulating miRNAs with prognostic value in metastatic breast cancer and for early detection of metastasis. Carcinogenesis 37(5):461–470CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Sun Y, Liu Y, Cogdell D, Calin GA, Sun B, Kopetz S, Hamilton SR, Zhang W (2016) Examining plasma microRNA markers for colorectal cancer at different stages. Oncotarget 7(10):11434–11449PubMedPubMedCentralGoogle Scholar
  20. 20.
    Kroh EM, Parkin RK, Mitchell PS, Tewari M (2010) Analysis of circulating microRNA biomarkers in plasma and serum using quantitative reverse transcription-PCR (qRT-PCR). Methods 50(4):298–301CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Cheng HH, Yi HS, Kim Y, Kroh EM, Chien JW, Eaton KD, Goodman MT, Tait JF, Tewari M, Pritchard CC (2013) Plasma processing conditions substantially influence circulating microRNA biomarker levels. PLoS One 8(6):e64795CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Maria D. Giraldez
    • 2
  • John R. Chevillet
    • 6
  • Muneesh Tewari
    • 1
    • 2
    • 3
    • 4
    • 5
    Email author
  1. 1.Comprehensive Cancer CenterUniversity of MichiganAnn ArborUSA
  2. 2.Department of Internal MedicineUniversity of MichiganAnn ArborUSA
  3. 3.Department of Biomedical EngineeringUniversity of MichiganAnn ArborUSA
  4. 4.Biointerfaces InstituteUniversity of MichiganAnn ArborUSA
  5. 5.Center for Computational Medicine and BioinformaticsUniversity of MichiganAnn ArborUSA
  6. 6.Institute for Systems BiologySeattleUSA

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