首页> 外文期刊>Nucleic Acids Research >Targeted next-generation sequencing of DNA regions proximal to a conserved GXGXXG signaling motif enables systematic discovery of tyrosine kinase fusions in cancer
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Targeted next-generation sequencing of DNA regions proximal to a conserved GXGXXG signaling motif enables systematic discovery of tyrosine kinase fusions in cancer

机译:靶向保守GXGXXG信号基序附近的DNA区域的下一代测序可以系统地发现癌症中的酪氨酸激酶融合体

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Tyrosine kinase (TK) fusions are attractive drug targets in cancers. However, rapid identification of these lesions has been hampered by experimental limitations. Our in silico analysis of known cancer-derived TK fusions revealed that most breakpoints occur within a defined region upstream of a conserved GXGXXG kinase motif. We therefore designed a novel DNA-based targeted sequencing approach to screen systematically for fusions within the 90 human TKs; it should detect 92% of known TK fusions. We deliberately paired 'in-solution' DNA capture with 454 sequencing to minimize starting material requirements, take advantage of long sequence reads, and facilitate mapping of fusions. To validate this platform, we analyzed genomic DNA from thyroid cancer cells (TPC-1) and leukemia cells (KG-1) with fusions known only at the mRNA level. We readily identified for the first time the genomic fusion sequences of CCDC6-RET in TPC-1 cells and FGFR1OP2-FGFR1 in KG-1 cells. These data demonstrate the feasibility of this approach to identify TK fusions across multiple human cancers in a high-throughput, unbiased manner. This method is distinct from other similar efforts, because it focuses specifically on targets with therapeutic potential, uses only 1.5 mu g of DNA, and circumvents the need for complex computational sequence analysis.
机译:酪氨酸激酶(TK)融合蛋白是癌症中有吸引力的药物靶标。然而,实验限制限制了对这些病变的快速识别。我们对已知的癌症衍生的TK融合进行的计算机分析表明,大多数断点发生在保守的GXGXXG激酶基序上游的指定区域内。因此,我们设计了一种新颖的基于DNA的靶向测序方法,以系统地筛选90种人类TK中的融合蛋白。它应该可以检测到92%的已知传统知识融合。我们特意将“溶液中” DNA捕获与454测序配对,以最大程度地减少起始物质的需求,利用长序列读取的优势并促进融合图谱的绘制。为了验证该平台,我们分析了甲状腺癌细胞(TPC-1)和白血病细胞(KG-1)的基因组DNA,仅在mRNA水平上已知融合。我们很容易地首次确定了TPC-1细胞中CCDC6-RET和KG-1细胞中FGFR1OP2-FGFR1的基因组融合序列。这些数据证明了这种方法以高通量,无偏见的方式识别跨多种人类癌症的传统知识融合的可行性。该方法与其他类似的研究方法不同,因为它专门针对具有治疗潜力的靶标,仅使用1.5μgDNA,并且无需进行复杂的计算序列分析。

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