Diagnostic microRNA profiling in cutaneous T-cell lymphoma (CTCL)

Research output: Contribution to journalJournal articleResearchpeer-review

  • Ulrik Ralfkiaer
  • Peter Hagedorn
  • Nannie Bangsgaard
  • Marianne B Løvendorf
  • Charlotte B Ahler
  • Lars Svensson
  • Katharina L Kopp
  • Marie T Vennegaard
  • Britt Lauenborg
  • John R Zibert
  • Thorbjørn Krejsgaard
  • Rolf Søkilde
  • Lise M Gjerdrum
  • Tord Labuda
  • Anne-Merete Mathiesen
  • Mariusz A Wasik
  • Malgorzata Sokolowska-Wojdylo
  • Catherine Queille-Roussel
  • Robert Gniadecki
  • Elisabeth Ralfkiaer
  • Christian Glue
  • Mads A Røpke
Cutaneous T-cell lymphomas (CTCLs) are the most frequent primary skin lymphomas. Nevertheless, diagnosis of early disease has proven difficult because of a clinical and histologic resemblance to benign inflammatory skin diseases. To address whether microRNA (miRNA) profiling can discriminate CTCL from benign inflammation, we studied miRNA expression levels in 198 patients with CTCL, peripheral T-cell lymphoma (PTL), and benign skin diseases (psoriasis and dermatitis). Using microarrays, we show that the most induced (miR-326, miR-663b, and miR-711) and repressed (miR-203 and miR-205) miRNAs distinguish CTCL from benign skin diseases with > 90% accuracy in a training set of 90 samples and a test set of 58 blinded samples. These miRNAs also distinguish malignant and benign lesions in an independent set of 50 patients with PTL and skin inflammation and in experimental human xenograft mouse models of psoriasis and CTCL. Quantitative (q)RT-PCR analysis of 103 patients with CTCL and benign skin disorders validates differential expression of 4 of the 5 miRNAs and confirms previous reports on miR-155 in CTCL. A qRT-PCR-based classifier consisting of miR-155, miR-203, and miR-205 distinguishes CTCL from benign disorders with high specificity and sensitivity, and with a classification accuracy of 95%, indicating that miRNAs have a high diagnostic potential in CTCL.
Original languageEnglish
JournalBlood
Volume118
Issue number22
Pages (from-to)5891-5900
Number of pages10
ISSN0006-4971
DOIs
Publication statusPublished - 2011

ID: 35354609