Stiehl Thomas, Marciniak-Czochra Anna
Institute for Computational Biomedicine - Disease Modeling, RWTH Aachen University, Aachen, Germany.
Institute of Applied Mathematics, Interdisciplinary Center for Scientific Computing and Bioquant Center, Heidelberg University, Heidelberg, Germany.
Front Physiol. 2021 Aug 23;12:596194. doi: 10.3389/fphys.2021.596194. eCollection 2021.
Acute myeloid leukemia is an aggressive cancer of the blood forming system. The malignant cell population is composed of multiple clones that evolve over time. Clonal data reflect the mechanisms governing treatment response and relapse. Single cell sequencing provides most direct insights into the clonal composition of the leukemic cells, however it is still not routinely available in clinical practice. In this work we develop a computational algorithm that allows identifying all clonal hierarchies that are compatible with bulk variant allele frequencies measured in a patient sample. The clonal hierarchies represent descendance relations between the different clones and reveal the order in which mutations have been acquired. The proposed computational approach is tested using single cell sequencing data that allow comparing the outcome of the algorithm with the true structure of the clonal hierarchy. We investigate which problems occur during reconstruction of clonal hierarchies from bulk sequencing data. Our results suggest that in many cases only a small number of possible hierarchies fits the bulk data. This implies that bulk sequencing data can be used to obtain insights in clonal evolution.
急性髓系白血病是一种侵袭性血液形成系统癌症。恶性细胞群体由多个随时间演变的克隆组成。克隆数据反映了控制治疗反应和复发的机制。单细胞测序能最直接地洞察白血病细胞的克隆组成，但在临床实践中仍未常规应用。在这项工作中，我们开发了一种计算算法，该算法能够识别与在患者样本中测量的大量变异等位基因频率兼容的所有克隆层次结构。克隆层次结构代表不同克隆之间的谱系关系，并揭示突变获得的顺序。使用单细胞测序数据对所提出的计算方法进行测试，该数据允许将算法的结果与克隆层次结构的真实结构进行比较。我们研究了从大量测序数据重建克隆层次结构过程中会出现哪些问题。我们的结果表明，在许多情况下，只有少数可能的层次结构符合大量数据。这意味着大量测序数据可用于深入了解克隆进化。
