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.

中文翻译：

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CaClust：使用 BCR 和外显性变体将基因型与滤泡性淋巴瘤的转录异质性联系起来


肿瘤表现出高度的基因型和转录异质性。两者都影响癌症进展和治疗，但主要在滤泡性淋巴瘤中单独研究。为了全面研究滤泡性淋巴瘤的进化和基因型到表型图谱，我们引入了 CaClust，这是一种概率图形模型，集成了深度全外显子组、单细胞 RNA 和 B 细胞受体测序数据，以推断克隆基因型、细胞到克隆映射和单细胞基因分型。CaClust 在模拟和患者数据方面优于最先进的模型。对来自四个样本的单细胞的深入分析展示了驱动突变、滤泡性淋巴瘤进化、可能的治疗靶点和单细胞基因分型的影响，这与独立的靶向重测序实验一致。