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慢性淋巴细胞白血病诊断时的广泛二代测序分析:临床与生物学相关性

Extensive next-generation sequencing analysis in chronic lymphocytic leukemia at diagnosis: clinical and biological correlations.

作者信息

Rigolin Gian Matteo, Saccenti Elena, Bassi Cristian, Lupini Laura, Quaglia Francesca Maria, Cavallari Maurizio, Martinelli Sara, Formigaro Luca, Lista Enrico, Bardi Maria Antonella, Volta Eleonora, Tammiso Elisa, Melandri Aurora, Urso Antonio, Cavazzini Francesco, Negrini Massimo, Cuneo Antonio

机构信息

Hematology Section, Department of Medical Sciences, Azienda Ospedaliero-Universitaria, Arcispedale S. Anna, University of Ferrara, Via Aldo Moro, 8, 44124, Ferrara, Cona, Italy.

Department of Morphology, Surgery and Experimental Medicine, and "Laboratorio per le Tecnologie delle Terapie Avanzate" (LTTA), University of Ferrara, Ferrara, Italy.

出版信息

J Hematol Oncol. 2016 Sep 15;9(1):88. doi: 10.1186/s13045-016-0320-z.

DOI:10.1186/s13045-016-0320-z
PMID:27633522
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5025606/
Abstract

BACKGROUND

In chronic lymphocytic leukemia (CLL), next-generation sequencing (NGS) analysis represents a sensitive, reproducible, and resource-efficient technique for routine screening of gene mutations.

METHODS

We performed an extensive biologic characterization of newly diagnosed CLL, including NGS analysis of 20 genes frequently mutated in CLL and karyotype analysis to assess whether NGS and karyotype results could be of clinical relevance in the refinement of prognosis and assessment of risk of progression. The genomic DNA from peripheral blood samples of 200 consecutive CLL patients was analyzed using Ion Torrent Personal Genome Machine, a NGS platform that uses semiconductor sequencing technology. Karyotype analysis was performed using efficient mitogens.

RESULTS

Mutations were detected in 42.0 % of cases with 42.8 % of mutated patients presenting 2 or more mutations. The presence of mutations by NGS was associated with unmutated IGHV gene (p = 0.009), CD38 positivity (p = 0.010), risk stratification by fluorescence in situ hybridization (FISH) (p < 0.001), and the complex karyotype (p = 0.003). A high risk as assessed by FISH analysis was associated with mutations affecting TP53 (p = 0.012), BIRC3 (p = 0.003), and FBXW7 (p = 0.003) while the complex karyotype was significantly associated with TP53, ATM, and MYD88 mutations (p = 0.003, 0.018, and 0.001, respectively). By multivariate analysis, the multi-hit profile (≥2 mutations by NGS) was independently associated with a shorter time to first treatment (p = 0.004) along with TP53 disruption (p = 0.040), IGHV unmutated status (p < 0.001), and advanced stage (p < 0.001). Advanced stage (p = 0.010), TP53 disruption (p < 0.001), IGHV unmutated status (p = 0.020), and the complex karyotype (p = 0.007) were independently associated with a shorter overall survival.

CONCLUSIONS

At diagnosis, an extensive biologic characterization including NGS and karyotype analyses using novel mitogens may offer new perspectives for a better refinement of risk stratification that could be of help in the clinical management of CLL patients.

摘要

背景

在慢性淋巴细胞白血病(CLL)中,下一代测序(NGS)分析是一种用于基因突变常规筛查的灵敏、可重复且资源高效的技术。

方法

我们对新诊断的CLL进行了广泛的生物学特征分析,包括对CLL中20个常发生突变的基因进行NGS分析以及核型分析,以评估NGS和核型结果在细化预后和评估疾病进展风险方面是否具有临床相关性。使用Ion Torrent Personal Genome Machine(一种采用半导体测序技术的NGS平台)对200例连续CLL患者外周血样本的基因组DNA进行分析。使用高效促有丝分裂原进行核型分析。

结果

42.0%的病例检测到突变,42.8%的突变患者存在2个或更多突变。NGS检测到的突变与未突变的IGHV基因(p = 0.009)、CD38阳性(p = 0.010)、荧光原位杂交(FISH)风险分层(p < 0.001)以及复杂核型(p = 0.003)相关。FISH分析评估的高风险与影响TP53(p = 0.012)、BIRC3(p = 0.003)和FBXW7(p = 0.003)的突变相关,而复杂核型与TP53、ATM和MYD88突变显著相关(分别为p = 0.003、0.018和0.001)。通过多变量分析,多重打击特征(NGS检测到≥2个突变)与首次治疗时间较短独立相关(p = 0.004),同时与TP53破坏(p = 0.040)、IGHV未突变状态(p < 0.001)和晚期(p < 0.001)相关。晚期(p = 0.010)、TP53破坏(p < 0.001)、IGHV未突变状态(p = 0.020)和复杂核型(p = 0.007)与总生存期较短独立相关。

结论

在诊断时,包括使用新型促有丝分裂原进行NGS和核型分析在内的广泛生物学特征分析可能为更好地细化风险分层提供新的视角,这可能有助于CLL患者的临床管理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31a8/5025606/cad20747e3d1/13045_2016_320_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31a8/5025606/6802b5093ceb/13045_2016_320_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31a8/5025606/cad20747e3d1/13045_2016_320_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31a8/5025606/6802b5093ceb/13045_2016_320_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31a8/5025606/cad20747e3d1/13045_2016_320_Fig2_HTML.jpg

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