PO.MD01.02 · 分子诊断与数据
慢性淋巴细胞白血病及 Richter 转化在患者一生中的克隆演化轨迹
Clonal trajectories of chronic lymphocytic leukemia and Richter transformation over the patients' lifespan
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
Richter 转化(RT)是慢性淋巴细胞白血病(CLL)演化过程中一种罕见但临床上具有挑战性的事件,其特征是 CLL 转化为侵袭性淋巴瘤,通常为弥漫性大 B 细胞淋巴瘤。尽管 CLL 和 RT 的分子谱已得到充分表征,但其演化轨迹仍不确定。更好地理解 CLL/RT 的动态变化可以在高危患者中实现更早的识别和干预。因此,我们的目标是通过肿瘤系统发育,追踪 CLL/RT 在患者一生中的克隆历史。
为此,我们对 5 例患者应用了基于原始模板导向扩增的单细胞全基因组测序,分析了来自最多 6 个连续时间点的 349 个单细胞,这些时间点跨越从 CLL 诊断到 RT 长达 19 年。开发了一套将现有算法与内部 PTA 伪迹过滤策略相整合的生物信息学工作流程,以优化变异检出的敏感性和特异性。在约 20× 的测序深度下,点突变的中位敏感性达到 87.7%,仅有约 5% 的细胞特异性伪迹残留。
我们的分析揭示了从正常 B 细胞到 CLL 以及从 CLL 到 RT 突变负荷的增加,这可由治疗相关和细胞内在突变过程的组合来解释。此外,检测到高度的瘤内异质性,无论是在体细胞突变还是拷贝数改变方面,这些是先前的批量测序未能捕获的。系统发育重建揭示了显著的患者内平行基因组演化。这一点体现在 3 个病例中多个 del(13q) 的独立获得、2 个病例中的 del(9p21),或 1 例患者中 4 个具有不同 TP53 突变的不同系统发育分支中的 7 LOH(17p)。
接下来,我们使用类时钟突变来推算遗传驱动因素的获得时间、CLL 与 RT 之间的多样化步骤及其克隆爆发,后者提示快速增殖时期。这些分析揭示,初始 CLL 遗传驱动因素在诊断前长达 30 年即已获得。然而,突然的克隆爆发并非由这些遗传驱动因素触发,这提示细胞外在因素(如 B 细胞受体刺激或微环境变化)可能启动 CLL 的扩增。另一方面,RT 早期即从 CLL 分化出来,包括在 CLL 诊断之前。然而,这些克隆经历了长达数年的克隆演化过程,其中在晚期获得的高基因组复杂性促进了它们的最终增殖。
总体而言,本研究提供了 CLL 和 RT 起源、早期多样化步骤及演化的路线图,对早期检测和干预具有潜在临床意义,同时为研究其他血液系统和实体肿瘤的演化提供了框架。
查看英文原文 English abstract
Richter transformation (RT) is a rare but clinically challenging event in the evolution of chronic lymphocytic leukemia (CLL), characterized by transformation of CLL into an aggressive lymphoma, commonly diffuse large B-cell lymphoma. Although the molecular profiles of CLL and RT are well characterized, their evolutionary trajectories remain uncertain. A better understanding of CLL and RT dynamics could enable earlier identification and intervention in high-risk patients. Thus, our aim was to trace CLL/RT clonal histories over the lifespan of the patients through tumor phylogenies.
To that aim, we applied primary template-directed amplification-based single-cell whole-genome sequencing to 5 patients, analyzing 349 single cells from up to 6 sequential time points spanning up to 19 years from CLL diagnosis to RT. A bioinformatic workflow that integrates existing algorithms with an in-house PTA-artifact filtering strategy was developed to optimize the sensitivity and specificity of the variant calling. A median sensitivity of 87.7% was obtained for point mutations at a sequencing depth of ~20×, with only ~5% of cell-specific artifacts remaining.
Our analyses revealed an increased mutational burden from normal B-cells to CLL and from CLL to RT explained by the combination of therapy-related and cell-intrinsic mutational processes. In addition, a high intratumor heterogeneity was detected both in terms of somatic mutations and copy number alterations, which was not previously captured by bulk sequencing. The phylogenetic reconstruction revealed remarkable intrapatient parallel genomic evolution. This was exemplified by the independent acquisition of multiple del(13q) in 3 cases, del(9p21) in 2 cases, or 7 LOH(17p) in 4 different phylogenetic clades with distinct TP53 mutations in 1 patient.
Next, we used clock-like mutations to time the acquisition of genetic drivers, the diversification steps between CLL and RT, and their clonal bursts, which are indicative of periods of rapid proliferation. These analyses revealed that initial CLL genetic drivers were acquired up to 30 years before diagnosis. However, abrupt clonal bursts were not triggered by these genetic drivers, suggesting that cell-extrinsic factors such as B-cell receptor stimulation or microenvironmental changes could initiate the expansion of CLL. On the other hand, RT diversifies from the CLL early, including before CLL diagnosis. However, these clones follow a years-long process of clonal evolution in which the acquisition of high genomic complexity at advance stages facilitates their final outgrowth.
Overall, this study provides a roadmap of the origin, early diversification steps, and evolution of CLL and RT with potential clinical implications for early detection and intervention, while providing a framework for the study of the evolution of other hematological and solid tumors.
利益披露 Disclosure
I. Márquez-López, None..
A. Real, None..
N. Russiñol, None..
N. Williams, None..
R. Royo, None..
M. van Roosmalen, None..
H. Playa-Albinyana, None..
J. Piñeyroa, None..
M. Bashiri, None..
P. Mozas, None..
A. López-Guillermo, None..
J. Delgado, None..
D. Colomer, None.
R. van Boxtel,
Bioskryb Genomics Other, Scientific advisor.
Hartwig Medical Foundation Other, Scientific advisor.
J. Nangalia, None..
E. Campo, None..
F. Nadeu, None.