Department of Biology, University of Copenhagen, Copenhagen, Denmark.
Blood. 2011 Nov 24;118(22):5891-900. doi: 10.1182/blood-2011-06-358382. Epub 2011 Aug 24.
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.
皮肤 T 细胞淋巴瘤(CTCL)是最常见的原发性皮肤淋巴瘤。然而,由于其临床表现和组织学与良性炎症性皮肤病相似,早期诊断一直很困难。为了确定 microRNA(miRNA)谱是否可以区分 CTCL 与良性炎症,我们研究了 198 例 CTCL、外周 T 细胞淋巴瘤(PTL)和良性皮肤疾病(银屑病和皮炎)患者的 miRNA 表达水平。使用微阵列,我们表明最诱导(miR-326、miR-663b 和 miR-711)和抑制(miR-203 和 miR-205)miRNA 可以区分 CTCL 与良性皮肤疾病,在 90 个样本的训练集和 58 个盲样测试集中具有 >90%的准确性。这些 miRNA 还可以区分 50 例 PTL 和皮肤炎症患者以及银屑病和 CTCL 的实验性人异种移植小鼠模型中的恶性和良性病变。对 103 例 CTCL 和良性皮肤疾病患者的定量(q)RT-PCR 分析验证了 5 个 miRNA 中 4 个的差异表达,并证实了 miR-155 在 CTCL 中的先前报道。由 miR-155、miR-203 和 miR-205 组成的 qRT-PCR 分类器可以区分 CTCL 与良性疾病,具有高特异性和敏感性,分类准确率为 95%,表明 miRNA 在 CTCL 中具有很高的诊断潜力。