MicroRNAs accurately identify cancer tissue origin

Nitzan Rosenfeld, Ranit Aharonov*, Eti Meiri, Shai Rosenwald, Yael Spector, Merav Zepeniuk, Hila Benjamin, Norberto Shabes, Sarit Tabak, Asaf Levy, Danit Lebanony, Yaron Goren, Erez Silberschein, Nurit Targan, Alex Ben-Ari, Shlomit Gilad, Netta Sion-Vardy, Ana Tobar, Meora Feinmesser, Oleg KharenkoOfer Nativ, Dvora Nass, Marina Perelman, Ady Yosepovich, Bruria Shalmon, Sylvie Polak-Charcon, Eddie Fridman, Amir Avniel, Isaac Bentwich, Zvi Bentwich, Dalia Cohen, Ayelet Chajut, Iris Barshack

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

877 Scopus citations


MicroRNAs (miRNAs) belong to a class of noncoding, regulatory RNAs that is involved in oncogenesis and shows remarkable tissue specificity. Their potential for tumor classification suggests they may be used in identifying the tissue in which cancers of unknown primary origin arose, a major clinical problem. We measured miRNA expression levels in 400 paraffin-embedded and fresh-frozen samples from 22 different tumor tissues and metastases. We used miRNA microarray data of 253 samples to construct a transparent classifier based on 48 miRNAs. Two-thirds of samples were classified with high confidence, with accuracy >90%. In an independent blinded test-set of 83 samples, overall high-confidence accuracy reached 89%. Classification accuracy reached 100% for most tissue classes, including 131 metastatic samples. We further validated the utility of the miRNA biomarkers by quantitative RT-PCR using 65 additional blinded test samples. Our findings demonstrate the effectiveness of miRNAs as biomarkers for tracing the tissue of origin of cancers of unknown primary origin.

Original languageAmerican English
Pages (from-to)462-469
Number of pages8
JournalNature Biotechnology
Issue number4
StatePublished - Apr 2008
Externally publishedYes


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