Department of Human Genetics, Radboud University Nijmegen Medical Centre, Radboud University Centre for Oncology, Nijmegen, The Netherlands.
Genes Chromosomes Cancer. 2011 Dec;50(12):969-81. doi: 10.1002/gcc.20919. Epub 2011 Aug 31.
In acute lymphoblastic leukemia (ALL) specific genomic abnormalities provide important clinical information. In most routine clinical diagnostic laboratories conventional karyotyping, in conjunction with targeted screens using e.g., fluorescence in situ hybridization (FISH), is currently considered as the gold standard to detect such aberrations. Conventional karyotyping, however, is limited in its resolution and yield, thus hampering the genetic diagnosis of ALL. We explored whether microarray-based genomic profiling would be feasible as an alternative strategy in a routine clinical diagnostic setting. To this end, we compared conventional karyotypes with microarray-deduced copy number aberration (CNA) karyotypes in 60 ALL cases. Microarray-based genomic profiling resulted in a CNA detection rate of 90%, whereas for conventional karyotyping this was 61%. In addition, many small (< 5 Mb) genetic lesions were encountered, frequently harboring clinically relevant ALL-related genes such as CDKN2A/B, ETV6, PAX5, and IKZF1. From our data we conclude that microarray-based genomic profiling serves as a robust tool in the genetic diagnosis of ALL, outreaching conventional karyotyping in CNA detection both in terms of sensitivity and specificity. We also propose a practical workflow for a comprehensive and objective interpretation of CNAs obtained through microarray-based genomic profiling, thereby facilitating its application in a routine clinical diagnostic setting.
在急性淋巴细胞白血病 (ALL) 中，特定的基因组异常提供了重要的临床信息。在大多数常规临床诊断实验室中，传统的核型分析结合靶向筛查（例如荧光原位杂交 (FISH)）目前被认为是检测此类异常的金标准。然而，传统核型分析在分辨率和产量方面存在局限性，因此阻碍了 ALL 的遗传诊断。我们探讨了基于微阵列的基因组分析是否可以作为常规临床诊断环境中的替代策略。为此，我们比较了 60 例 ALL 病例的传统核型与微阵列推断的拷贝数异常 (CNA) 核型。基于微阵列的基因组分析的 CNA 检测率为 90%，而传统核型分析的检测率为 61%。此外，还遇到了许多较小的 (<5 Mb) 遗传病变，这些病变经常携带与 ALL 相关的临床相关基因，如 CDKN2A/B、ETV6、PAX5 和 IKZF1。根据我们的数据，我们得出结论，基于微阵列的基因组分析在 ALL 的遗传诊断中是一种强大的工具，在 CNA 检测方面，无论是在灵敏度还是特异性方面，都优于传统核型分析。我们还提出了一种实用的工作流程，用于全面和客观地解释通过基于微阵列的基因组分析获得的 CNA，从而促进其在常规临床诊断环境中的应用。
