Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland.
Department of Hematology, Leiden University Medical Center, Leiden, Netherlands.
Genome Biol. 2024 Nov 5;25(1):286. doi: 10.1186/s13059-024-03417-1.
Tumours exhibit high genotypic and transcriptional heterogeneity. Both affect cancer progression and treatment, but have been predominantly studied separately in follicular lymphoma. To comprehensively investigate the evolution and genotype-to-phenotype maps in follicular lymphoma, we introduce CaClust, a probabilistic graphical model integrating deep whole exome, single-cell RNA and B-cell receptor sequencing data to infer clone genotypes, cell-to-clone mapping, and single-cell genotyping. CaClust outperforms a state-of-the-art model on simulated and patient data. In-depth analyses of single cells from four samples showcase effects of driver mutations, follicular lymphoma evolution, possible therapeutic targets, and single-cell genotyping that agrees with an independent targeted resequencing experiment.
肿瘤表现出高度的基因型和转录组异质性。这两者都影响癌症的进展和治疗，但在滤泡性淋巴瘤中主要分别进行研究。为了全面研究滤泡性淋巴瘤中的进化和基因型-表型图谱，我们引入了 CaClust，这是一种概率图形模型，整合了深度全外显子、单细胞 RNA 和 B 细胞受体测序数据，以推断克隆基因型、细胞到克隆的映射和单细胞基因分型。CaClust 在模拟和患者数据上的表现优于最先进的模型。对来自四个样本的单细胞进行深入分析，展示了驱动突变、滤泡性淋巴瘤进化、可能的治疗靶点以及与独立靶向重测序实验一致的单细胞基因分型的影响。
