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利用纯化的CD3-CD56+组分对颗粒淋巴细胞自然杀伤细胞型淋巴增殖性疾病进行DNA微阵列分析。

DNA microarray analysis of natural killer cell-type lymphoproliferative disease of granular lymphocytes with purified CD3-CD56+ fractions.

作者信息

Choi Y L, Makishima H, Ohashi J, Yamashita Y, Ohki R, Koinuma K, Ota J, Isobe Y, Ishida F, Oshimi K, Mano H

机构信息

Division of Functional Genomics, Jichi Medical School, Kawachigun, Tochigi, Japan.

出版信息

Leukemia. 2004 Mar;18(3):556-65. doi: 10.1038/sj.leu.2403261.

Abstract

Natural killer (NK) cell-type lymphoproliferative disease of granular lymphocytes (LDGL) is characterized by the outgrowth of CD3(-)CD16/56(+) NK cells, and can be further subdivided into two distinct categories: aggressive NK cell leukemia (ANKL) and chronic NK lymphocytosis (CNKL). To gain insights into the pathophysiology of NK cell-type LDGL, we here purified CD3(-)CD56(+) fractions from healthy individuals (n=9) and those with CNKL (n=9) or ANKL (n=1), and compared the expression profiles of >12 000 genes. A total of 15 'LDGL-associated genes' were identified, and a correspondence analysis on such genes could clearly indicate that LDGL samples share a 'molecular signature' distinct from that of normal NK cells. With a newly invented class prediction algorithm, 'weighted distance method', all 19 samples received a clinically matched diagnosis, and, furthermore, a detailed cross-validation trial for the prediction of normal or CNKL status could achieve a high accuracy (77.8%). By applying another statistical approach, we could extract other sets of genes, expression of which was specific to either normal or LDGL NK cells. Together with sophisticated statistical methods, gene expression profiling of a background-matched NK cell fraction thus provides us a wealth of information for the LDGL condition.

摘要

颗粒淋巴细胞自然杀伤(NK)细胞型淋巴增殖性疾病(LDGL)的特征是CD3(-)CD16/56(+)NK细胞增生,可进一步细分为两个不同类别:侵袭性NK细胞白血病(ANKL)和慢性NK淋巴细胞增多症(CNKL)。为深入了解NK细胞型LDGL的病理生理学,我们从健康个体(n = 9)以及患有CNKL(n = 9)或ANKL(n = 1)的个体中纯化出CD3(-)CD56(+)组分,并比较了12000多个基因的表达谱。共鉴定出15个“LDGL相关基因”,对这些基因进行的对应分析能够清楚地表明,LDGL样本具有与正常NK细胞不同的“分子特征”。使用新发明的类别预测算法“加权距离法”,所有19个样本均获得了与临床相符的诊断,此外,针对正常或CNKL状态预测的详细交叉验证试验可达到较高的准确率(77.8%)。通过应用另一种统计方法,我们能够提取出其他几组基因,其表达分别特异于正常或LDGL NK细胞。因此,背景匹配的NK细胞组分的基因表达谱与复杂的统计方法相结合,为我们提供了关于LDGL病情的丰富信息。

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