American Association for Cancer Research
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Supplementary Figure 4 from MicroRNA Sequence and Expression Analysis in Breast Tumors by Deep Sequencing

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journal contribution
posted on 2023-03-30, 20:32 authored by Thalia A. Farazi, Hugo M. Horlings, Jelle J. ten Hoeve, Aleksandra Mihailovic, Hans Halfwerk, Pavel Morozov, Miguel Brown, Markus Hafner, Fabien Reyal, Marieke van Kouwenhove, Bas Kreike, Daoud Sie, Volker Hovestadt, Lodewyk F.A. Wessels, Marc J. van de Vijver, Thomas Tuschl
Supplementary Figure 4 from MicroRNA Sequence and Expression Analysis in Breast Tumors by Deep Sequencing



MicroRNAs (miRNA) regulate many genes critical for tumorigenesis. We profiled miRNAs from 11 normal breast tissues, 17 noninvasive, 151 invasive breast carcinomas, and 6 cell lines by in-house–developed barcoded Solexa sequencing. miRNAs were organized in genomic clusters representing promoter-controlled miRNA expression and sequence families representing seed sequence–dependent miRNA target regulation. Unsupervised clustering of samples by miRNA sequence families best reflected the clustering based on mRNA expression available for this sample set. Clustering and comparative analysis of miRNA read frequencies showed that normal breast samples were separated from most noninvasive ductal carcinoma in situ and invasive carcinomas by increased miR-21 (the most abundant miRNA in carcinomas) and multiple decreased miRNA families (including miR-98/let-7), with most miRNA changes apparent already in the noninvasive carcinomas. In addition, patients that went on to develop metastasis showed increased expression of mir-423, and triple-negative breast carcinomas were most distinct from other tumor subtypes due to upregulation of the mir∼17–92 cluster. However, absolute miRNA levels between normal breast and carcinomas did not reveal any significant differences. We also discovered two polymorphic nucleotide variations among the more abundant miRNAs miR-181a (T19G) and miR-185 (T16G), but we did not identify nucleotide variations expected for classical tumor suppressor function associated with miRNAs. The differentiation of tumor subtypes and prediction of metastasis based on miRNA levels is statistically possible but is not driven by deregulation of abundant miRNAs, implicating far fewer miRNAs in tumorigenic processes than previously suggested. Cancer Res; 71(13); 4443–53. ©2011 AACR.