4.8 Article

Diagnostic tool for the identification of MLL rearrangements including unknown partner genes

出版社

NATL ACAD SCIENCES
DOI: 10.1073/pnas.0406994102

关键词

acute leukemia; MILL translocitions; translocation partner genes

向作者/读者索取更多资源

Approximately 50 different chromosomal translocations of the human MLL gene are currently known and associated with high-risk acute leukemia. The large number of different MLL translocation partner genes makes a precise diagnosis a demanding task. After their cytogenetic identification, only the most common MLL translocations are investigated by RT-PCR analyses, whereas infrequent or unknown MLL translocations are excluded from further analyses. Therefore, we aimed at establishing a method that enables the detection of any MLL rearrangement by using genomic DNA isolated from patient biopsy material. This goal was achieved by establishing a universal long-distance inverse-PCR approach that allows the identification of any kind of MLL rearrangement if located within the breakpoint cluster region. This method was applied to biopsy material derived from 40 leukemia patients known to carry MLL abnormalities. Thirty-six patients carried known MLL fusions (34 with der(11) and 2 with reciprocal alleles), whereas 3 patients were found to carry novel MLL fusions to ACACA, SELB, and SMAP1, respectively. One patient carried a genomic fusion between MLL and TIRAP, resulting from an interstitial deletion. Because of this interstitial deletion, portions of the MLL and TIRAP genes were deleted, together with 123 genes located within the 13-Mbp interval between both chromosomal loci. Therefore, this previously undescribed diagnostic tool has been proven successful for analyzing any MLL rearrangement including previously unrecognized partner genes. Furthermore, the determined patient-specific fusion sequences are useful for minimal residual disease monitoring of MLL associated acute leukemias.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据