Chromosome Banding Analysis Versus Genomic Microarrays: A Comparison of Methods for Genomic Complexity Risk Stratification in Chronic Lymphocytic Leukemia Patients with Complex Karyotype

SNP阵列 慢性淋巴细胞白血病 生物 核型 IGHV@ 内科学 DNA微阵列 肿瘤科 比较基因组杂交 生物信息学 白血病 遗传学 医学 染色体 单核苷酸多态性 基因型 基因 基因表达
作者
Silvia Ramos Campoy,Anna Puiggros,Sı́lvia Beà,Sandrine Bougeon,María José Larráyoz,Guillem Clot,Dolors Costa,Gian Matteo Rigolin,Margarita Ortega,Laura Blanco,Rosa Collado,Rocío Salgado,María‐Dolores Garcia‐Malo,Andrea Campeny,Alberto Valiente,Ferran Nadeu,Julio Delgado,Tycho Baumann,Idoya Ancín,Marco Garcia
出处
期刊:Blood [Elsevier BV]
卷期号:134 (Supplement_1): 4287-4287 被引量:2
标识
DOI:10.1182/blood-2019-126557
摘要

INTRODUCTION. Chromosome banding analysis (CBA) is the gold standard to identify complex karyotypes (CK; ≥3 chromosomal aberrations in the same clone). CK are predictors of poor prognosis and treatment refractoriness in patients with chronic lymphocytic leukemia (CLL). Patients with CK (15% at diagnosis) constitute a heterogeneous subgroup with highly variable clinical course. Recent studies that aim to refine CK definition in CLL suggest that ≥5 is the number of anomalies detected by CBA that better predicts an impaired outcome (Baliakas et al, 2019). Molecular techniques as genomic microarrays also detect genomic complexity (GC). A recent multicentric ERIC study (Leeksma et al, ASH 2017) identified that patients with ≥5 copy number alterations (CNA) detected by microarrays are associated with an adverse outcome. However, risk stratification regarding genomic complexity assessed by CBA and microarrays has not been compared. OBJECTIVES. 1. To compare genomic complexity in CLL defined by CBA vs microarrays; 2. To compare risk stratification based on genomic complexity measured by both techniques. METHODS. The study cohort included 293 CLL patients from 16 European institutions (67% males) with available CBA result at diagnosis or prior to first treatment. The cohort was enriched in patients with CK (n=153, 52%). Tumor DNA extracted from peripheral blood (n=254) or bone marrow samples (n=39) obtained at the time of CBA was hybridized to CGH-arrays (n=12) and SNP-arrays (n=281) platforms. Clinically relevant aberrations [11q-, +12, 13q-, 17p-] and CNA ≥5Mb were considered for the anomaly count. Three risk groups were defined using previously suggested cut-off points for CBA and microarrays [non-CK/low-GC: 0-2; low/intermediate-CK/GC: 3-4; high-CK/GC: ≥5 (Baliakas et al, Leeksma et al)]. Groups obtained by both methods were compared and correlated with other clinical and biological data. Time to first treatment (TTT) of patients categorized according to the number of alterations detected by CBA and microarrays was analyzed. RESULTS. Median number of abnormalities detected was 3 (range: 0-19) by CBA and 2 (range: 0-18) by microarrays. When stratified according to previously defined criteria, a moderate agreement was observed between both techniques (κ=0.483, p<0.001). Remarkably, 8/74 (11%) of patients with high-CK were considered low-GC by microarrays while none of the 140 patients with non-CK was classified as high-GC by microarrays (Table 1). Discordances in those 8 cases underestimated by microarrays were due to the presence of chromosome markers or complex rearrangements in the karyotype which were globally balanced or to subclonal aberrations expanded during CBA culture but represented in a minor proportion of the whole sample. Regarding the prognostic value of genomic complexity and considering the number of abnormalities detected as a continuous variable, CBA and microarrays showed a similar concordance index (C-index) for TTT (0.615 vs 0.609, respectively). When considering all the abnormalities independently of their size or when lowering the cutoff to 1Mb for those non-CLL abnormalities, similar impact on TTT was observed (C-index=0.593 vs 0.616). The three risk groups defined by each method showed significant differences on TTT (Figure 1, p<0.001). In discordant cases, significant differences on TTT were only observed in cases with high-CK, where low-GC and high-GC showed poor outcome when compared to intermediate-GC group (Figure 2, p=0.009). As genomic complexity category increased in both techniques, a significant increment of del/mutTP53 (CBA: 13% vs 29% vs 62%, p<0.001; microarrays: 16% vs 26% vs 68%, p<0.001) and unmutated IGHV (U-IGHV) (CBA: 49% vs 59% vs 71%, p=0.015; microarrays: 47% vs 68% vs 73%, p=0.001) cases was observed. Of note, among the 8 high risk patients underscored by microarrays, 3 showed del/mutTP53 and 6 showed U-IGHV. Additional techniques, as chromosome painting, are ongoing to confirm microarray results and find an explanation for discordances. CONCLUSIONS. 1. CBA and microarrays are helpful techniques for assessing genomic complexity in CLL patients; 2. Risk categories established by both methods have a significant impact on TTT although they show a moderate agreement; 3. Discordant cases are being investigated to refine genomic complexity criteria equivalent by both techniques. ACKNOWLEDGEMENTS. 17SGR437, GLD17/00282, FPU17/00361 Disclosures Rigolin: AbbVie: Speakers Bureau; Gilead: Speakers Bureau; Gilead: Research Funding. Gimeno:JANSSEN: Consultancy, Speakers Bureau; Abbvie: Speakers Bureau. Bosch:Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; AstraZeneca: Honoraria, Research Funding; Takeda: Honoraria, Research Funding; F. Hoffmann-La Roche Ltd/Genentech, Inc.: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Acerta: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Kyte: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Honoraria, Research Funding. Cuneo:Amgen: Honoraria; Abbvie: Honoraria, Speakers Bureau; Gilead: Honoraria, Speakers Bureau; Janssen: Honoraria, Speakers Bureau; Roche: Honoraria, Speakers Bureau. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
yang完成签到,获得积分10
刚刚
刚刚
刚刚
刚刚
1秒前
坚定的老六完成签到,获得积分10
1秒前
英姑应助无限的小鸽子采纳,获得10
1秒前
1秒前
zhouzhou完成签到,获得积分10
1秒前
oo完成签到,获得积分10
1秒前
1秒前
科研狗应助my采纳,获得50
1秒前
典雅的访风完成签到,获得积分10
2秒前
胖崽胖崽完成签到,获得积分10
2秒前
3秒前
3秒前
4秒前
哈基米发布了新的文献求助10
4秒前
4秒前
4秒前
光亮绿柳完成签到 ,获得积分10
4秒前
科研通AI6.4应助fujikaze采纳,获得50
5秒前
5秒前
Yeung发布了新的文献求助20
5秒前
Cu完成签到,获得积分10
5秒前
5秒前
科研通AI6.4应助满意盈采纳,获得10
5秒前
cxxx发布了新的文献求助10
6秒前
pp发布了新的文献求助10
6秒前
科研通AI6.2应助TogawaSakiko采纳,获得10
6秒前
6秒前
丰丰扫心发布了新的文献求助10
6秒前
6秒前
hc完成签到,获得积分20
7秒前
7秒前
7秒前
8秒前
月沁蓝山完成签到,获得积分20
8秒前
所所应助PhDL1采纳,获得10
8秒前
9秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场现状调查及投资机会研判报告 1000
模型平均及其应用 900
Nondestructive Testing Handbook: Vol. 4, Thermal and Infrared Testing (IR), 4th ed 800
Évora na Idade Média 555
作者名:Kristopher P. Plain,悉尼大学的,目前只能查到其四篇论文,想找到其博士论文 550
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7350107
求助须知:如何正确求助?哪些是违规求助? 8961863
关于积分的说明 19035492
捐赠科研通 6999868
什么是DOI,文献DOI怎么找? 3220864
关于科研通互助平台的介绍 2385604
邀请新用户注册赠送积分活动 2201259