Analysis of the Tumor Microenvironment Transcriptome via NanoString mRNA and miRNA Expression Profiling

  • Marie-Noël M’Boutchou
  • Léon C. van KempenEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 1458)


Gene expression analysis in the tumor microenvironment using archived clinical samples is challenging because of formalin fixation, RNA degradation, and limiting sample volume. NanoString gene expression profiling is a RNA–DNA hybrid capture technology that does not require PCR and can accurately quantify the expression of to 800 transcripts in a single reaction. The technology requires 50–100 ng of RNA, which can be degraded (EDITOR: is this correct?) to a 200 bp fragment size. In contrast to amplification technologies, nanoString counts the actual numbers of transcripts that are captured with transcript-specific and fluorescently-barcoded probes. This chapter describes protocols for RNA extraction, quantification, mRNA and miRNA profiling and data analysis.

Key words

NanoString mRNA and miRNA expression profiling 



The Molecular Pathology Centre at Jewish General Hospital is grateful to the Jewish General Hospital Foundation and all participants of the Enbridge Ride to Conquer Cancer® event who have enabled the purchase of the nCounter Analysis System. The images in Figs. 1 and 2 were reproduced from nanoString publications with the consent from nanoString® Technologies, Inc.


  1. 1.
    Bustin SA, Benes V, Garson J, Hellemans J, Huggett J, Kubista M et al (2013) The need for transparency and good practices in the qPCR literature. Nat Methods 10:1063–1067CrossRefPubMedGoogle Scholar
  2. 2.
    Geiss GK, Bumgarner RE, Birditt B, Dahl T, Dowidar N, Dunaway DL et al (2008) Direct multiplexed measurement of gene expression with color-coded probe pairs. Nat Biotechnol 26:317–325CrossRefPubMedGoogle Scholar
  3. 3.
    Reis PP, Waldron L, Goswami RS, Xu W, Xuan Y, Perez-Ordonez B et al (2011) mRNA transcript quantification in archival samples using multiplexed, color-coded probes. BMC Biotechnol 11:46CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Koti M, Siu A, Clement I, Bidarimath M, Turashvili G, Edwards A et al (2015) A distinct pre-existing inflammatory tumour microenvironment is associated with chemotherapy resistance in high-grade serous epithelial ovarian cancer. Br J Cancer 112:1215–1222CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Golubeva Y, Salcedo R, Mueller C, Liotta LA, Espina V (2013) Laser capture microdissection for protein and NanoString RNA analysis. In: Taatjes D, Roth J (eds) Methods in Molecular Biology 931:213–257Google Scholar
  6. 6.
    Castro NP, Fedorova-Abrams ND, Merchant AS, Rangel MC, Nagaoka T, Karasawa H et al (2015) Cripto-1 as a novel therapeutic target for triple negative breast cancer. Oncotarget 6:11910–11929CrossRefPubMedGoogle Scholar
  7. 7.
    Waggott D, Chu K, Yin S, Wouters BG, Liu F-F, Boutros PC (2012) NanoStringNorm: an extensible R package for the pre-processing of NanoString mRNA and miRNA data. Bioinformatics 28:1546–1548CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Brumbaugh CD, Kim HJ, Giovacchini M, Pourmand N (2011) NanoStriDE: normalization and differential expression analysis of NanoString nCounter data. BMC Bioinformatics 12:479CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Marie-Noël M’Boutchou
    • 1
  • Léon C. van Kempen
    • 1
    • 2
    Email author
  1. 1.Lady Davis Institute for Medical ResearchMcGill UniversityMontréalCanada
  2. 2.Department of Pathology, Molecular Pathology CenterJewish General HospitalMontréalCanada

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