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| MicroRNA Expression Profiles Classify Human Cancers |
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| Project | microRNA |
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| Abstract | |
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 Recent work has revealed the existence of a class of small noncoding RNA species, known as microRNAs (miRNAs), which
have critical functions across various biological processes1,2. Here we use a new, bead-based flow cytometric miRNA expression profiling method to present a systematic expression analysis of 217 mammalian miRNAs from 334 samples, including multiple human cancers. The miRNA profiles are surprisingly informative, reflecting the developmental lineage and differentiation state of the tumours. We observe a general downregulation of miRNAs in
tumours compared with normal tissues. Furthermore, we were
able to successfully classify poorly differentiated tumours using miRNA expression profiles, whereas messenger RNA profiles were highly inaccurate when applied to the same samples. These findings highlight the potential of miRNA profiling in cancer diagnosis. |
| Authors | Jun Lu, Gad Getz, Eric A. Miska, Ezequiel A. Alvarez-Saavedra, Justin Lamb, David Peck, Alejandro Sweet-Cordero, Benjamin L. Ebert, Raymond H. Mak, Adolfo A. Ferrando, James R. Downing, Tyler Jacks, H. Robert Horvitz and Todd R. Golub |
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| Publication Date | 06/09/2005 |
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Contact emails |
junlu@broad.mit.edu
gadgetz@broad.mit.edu
golub@broad.mit.edu
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| Publication URL | http://www.nature.com/nature/journal/v435/n7043/abs/nature03702.html |
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| Citation | Nature 435, 834-838 (9 June 2005) |
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| Keywords | microRNA, miRNA, cancer, tumor, differentiation, poorly differentiated tumor |
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| Supplemental Information |
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| URLs | |
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| Files | | Description | File |
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| Supplementary Table 1, probe information | supplementary_table_1.xls |
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| Supplementary Table 2, sample information | supplementary_table_2.xls |
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| Supplementary Table 3, N vs T predition result | supplementary_table_3.xls |
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| Suppl. Table 4, poorly differentiated tumor prediction result | supplementary_table_4.xls |
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| microRNA data, miGCM_218 collection | miGCM_218.gct |
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| microRNA data, acute lymphoblastic leukemia | ALL.gct |
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| microRNA data, for samples with both miRNA and mRNA data | Common_miRNA.gct |
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| microRNA data, mouse lung samples | mLung.gct |
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| microRNA data, poorly differentiated tumors | PDT_miRNA.gct |
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| microRNA data, HL-60 differentiation | HL60.gct |
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| microRNA data, erythroid differentiation | Erythroid.gct |
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| mRNA data, for samples with both miRNA and mRNA data | Common_Affy.zip |
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| mRNA data, poorly differentiated tumors | PDT_Affy.zip |
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| microRNA data, raw data | miRNA_raw.zip |
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| Expression data in MAGE-ML format | Expression_Data_MAGE_ML.zip |
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| Raw data in MAGE-ML format | miRNA_raw_MAGE_ML.zip |
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| Frequently Asked Questions | FAQ_miGCM.html |
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| Paper | Nature_miR_classify_cancer.pdf |
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| Supplementary Notes | Supplementary_Notes.pdf |
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