首页> 外文期刊>Blood: The Journal of the American Society of Hematology >Genome-wide profiling of follicular lymphoma by array comparative genomic hybridization reveals prognostically significant DNA copy number imbalances.
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Genome-wide profiling of follicular lymphoma by array comparative genomic hybridization reveals prognostically significant DNA copy number imbalances.

机译:通过阵列比较基因组杂交对滤泡性淋巴瘤进行全基因组分析,揭示了预后显着的DNA拷贝数失衡。

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摘要

The secondary genetic events associated with follicular lymphoma (FL) progression are not well defined. We applied genome-wide BAC array comparative genomic hybridization to 106 diagnostic biopsies of FL to characterize regional genomic imbalances. Using an analytical approach that defined regions of copy number change as intersections between visual annotations and a Hidden Markov model-based algorithm, we identified 71 regional alterations that were recurrent in at least 10% of cases. These ranged in size from approximately 200 kb to 44 Mb, affecting chromosomes 1, 5, 6, 7, 8, 10, 12, 17, 18, 19, and 22. We also demonstrated by cluster analysis that 46.2% of the 106 cases could be sub-grouped based on the presence of +1q, +6p/6q-, +7, or +18. Survival analysis showed that 21 of the 71 regions correlated significantly with inferior overall survival (OS). Of these 21 regions, 16 were independent predictors of OS using a multivariate Cox model that included the international prognostic index (IPI) score. Two of these 16 regions (1p36.22-p36.33 and 6q21-q24.3) were also predictors of transformation risk and independent of IPI. These prognostic features may be useful to identify high-risk patients as candidates for risk-adapted therapies.
机译:与滤泡性淋巴瘤(FL)进展相关的继发性遗传事件尚未明确定义。我们将全基因组BAC阵列比较基因组杂交技术应用于FL的106例诊断性活检,以表征区域性基因组失衡。使用一种分析方法将拷贝数变化的区域定义为视觉注释和基于隐马尔可夫模型的算法之间的交点,我们确定了至少在10%的情况下经常发生的71个区域变化。它们的大小从大约200 kb到44 Mb不等,影响了1号,5号,6号,7号,8号,10号,12号,17号,18号,19号和22号染色体。我们还通过聚类分析证明了106例中的46.2%可以基于+ 1q,+ 6p / 6q-,+ 7或+18进行分组。生存分析表明,71个区域中有21个与总体生存率(OS)显着相关。在这21个地区中,有16个是使用包括国际预后指数(IPI)评分的多元Cox模型进行的OS的独立预测因子。这16个区域中的两个区域(1p36.22-p36.33和6q21-q24.3)也是转化风险的预测因子,并且独立于IPI。这些预后特征可能有助于确定高危患者为适应风险疗法的候选者。

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