首页> 美国卫生研究院文献>Cancer Medicine >Comprehensive mutation profiling and mRNA expression analysis in atypical chronic myeloid leukemia in comparison with chronic myelomonocytic leukemia
【2h】

Comprehensive mutation profiling and mRNA expression analysis in atypical chronic myeloid leukemia in comparison with chronic myelomonocytic leukemia

机译:与慢性粒细胞性白血病相比非典型慢性粒细胞白血病的综合突变谱和mRNA表达分析

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Atypical chronic myeloid leukemia (aCML) and chronic myelomonocytic leukemia (CMML) represent two histologically and clinically overlapping myelodysplastic/myeloproliferative neoplasms. Also the mutational landscapes of both entities show congruencies. We analyzed and compared an aCML cohort (n = 26) and a CMML cohort (n = 59) by next‐generation sequencing of 25 genes and by an nCounter approach for differential expression in 107 genes. Significant differences were found with regard to the mutation frequency of TET2, SETBP1, and CSF3R. Blast content of the bone marrow revealed an inverse correlation with the mutation status of SETBP1 in aCML and TET2 in CMML, respectively. By linear discriminant analysis, a mutation‐based machine learning algorithm was generated which placed 19/26 aCML cases (73%) and 54/59 (92%) CMML cases into the correct category. After multiple correction, differential mRNA expression could be detected between both cohorts in a subset of genes (FLT3, CSF3R, and SETBP1 showed the strongest correlation). However, due to high variances in the mRNA expression, the potential utility for the clinic is limited. We conclude that a medium‐sized NGS panel provides a valuable assistance for the correct classification of aCML and CMML.
机译:非典型慢性粒细胞白血病(aCML)和慢性粒细胞单核细胞白血病(CMML)代表两种组织学和临床上重叠的骨髓增生异常/骨髓增生性肿瘤。两个实体的突变景观也显示出一致性。我们通过25个基因的下一代测序和nCounter方法对107个基因的差异表达进行了分析并比较了aCML队列(n = 26)和CMML队列(n = 59)。发现在TET2,SETBP1和CSF3R的突变频率方面存在显着差异。骨髓的爆炸含量分别与aCML中SETBP1和CMML中TET2的突变状态呈负相关。通过线性判别分析,生成了基于突变的机器学习算法,该算法将19/26 aCML案例(73%)和54/59(92%)CMML案例归为正确类别。经过多次校正后,可以在一个基因子集中的两个队列之间检测到差异的mRNA表达(FLT3,CSF3R和SETBP1显示出最强的相关性)。然而,由于mRNA表达的高度差异,在临床上的潜在用途受到限制。我们得出的结论是,中型NGS面板为正确分类aCML和CMML提供了宝贵的帮助。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号