Sarah Cadot, Chloe Audebert, Charlotte Dion, Soleakhena Ken, Loic Dupré, Laetitia Largeaud, Camille Laurent, Loic Ysebaert, Fabien Crauste, Anne Quillet-Mary
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Understanding which factors determine distinct disease courses upon ibrutinib treatment remains a scientific challenge.</p><p><strong>Methods and findings: </strong>From 2016 to 2021, we conducted a longitudinal and observational study in 2 cohorts of patients with chronic lymphocytic leukemia (CLL) (cohort 1, n = 41; cohort 2, n = 81). These cohorts reflect the well-known clinical features of CLL patients, such as Male/Female sex ratio of 2/1, a median age of 70 years at diagnosis, and include patients in first-line therapy (27%) or relapsed/refractory patients (73%). Blood cell counts were followed for each patient during 2 years of ibrutinib treatment. In addition, immunophenotyping and whole-body magnetic resonance imaging (MRI) were assessed in patients from cohort 1. These data were integrated in a newly built mathematical model, inspired by previous mathematical works on CLL treatment and combining dynamical and statistical models, leading to the identification of biological mechanisms associated with the 2 types of clinical responses. This multidisciplinary approach allowed to identify baseline parameters that dictated lymphocytes kinetics upon ibrutinib treatment. Indeed, ibrutinib-induced lymphocytosis defined 2 CLL patient subgroups, transient hyperlymphocytosis (tHL) or prolonged hyperlymphocytosis (pHL), that can be discriminated, before the treatment, by absolute counts of CD4+ T lymphocytes (p = 0.026) and regulatory CD4 T cells (p = 0.007), programmed cell death protein 1 PD1 (p = 0.022) and CD69 (p = 0.03) expression on B leukemic cells, CD19/CD5high/CXCR4low level (p = 0.04), and lymph node cellularity. We also pinpointed that the group of patients identified by the transient hyperlymphocytosis has lower duration response and a poor clinical outcome. The mathematical approach led to the reproduction of patient-specific dynamics and the estimation of associated patient-specific biological parameters, and highlighted that the differences between the 2 groups were mainly due to the production of leukemic B cells in lymph node compartments, and to a lesser extent to T lymphocytes and leukemic B cell egress into bloodstream. Access to additional data, especially longitudinal MRI data, could strengthen the conclusions regarding leukemic B cell dynamics in lymph nodes and the relevance of 2 distinct groups of patients.</p><p><strong>Conclusions: </strong>Altogether, our multidisciplinary study provides a better understanding of ibrutinib response and highlights new pharmacodynamic parameters before and along ibrutinib treatment. 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引用次数: 0
摘要
背景:伊布替尼治疗慢性淋巴细胞白血病(CLL)的首批临床观察结果之一是淋巴结体积迅速缩小。这一现象伴随着一过性或长期性的淋巴细胞增多,而淋巴细胞增多与不同的临床反应有关,因此会对长期预后产生影响。了解哪些因素决定了伊布替尼治疗后的不同病程仍是一项科学挑战:从2016年到2021年,我们对两组慢性淋巴细胞白血病(CLL)患者(组群1,n = 41;组群2,n = 81)进行了纵向观察研究。这些队列反映了CLL患者众所周知的临床特征,如男女性别比为2/1,诊断时的中位年龄为70岁,包括一线治疗患者(27%)或复发/难治患者(73%)。在伊布替尼治疗的两年期间,对每位患者的血细胞计数进行了跟踪。此外,还对第一组患者的免疫分型和全身磁共振成像(MRI)进行了评估。这些数据被整合到一个新建立的数学模型中,该数学模型的灵感来源于之前关于CLL治疗的数学研究,并结合了动态模型和统计模型,从而确定了与两种临床反应相关的生物机制。这种多学科方法有助于确定伊布替尼治疗时决定淋巴细胞动力学的基线参数。事实上,伊布替尼诱导的淋巴细胞增多定义了 2 个 CLL 患者亚群,即一过性淋巴细胞增多症(tHL)或长期淋巴细胞增多症(pHL),治疗前可通过 CD4+ T 淋巴细胞绝对计数(p = 0.026)和调节性 CD4 T 细胞(p = 0.007)、B 白血病细胞上程序性细胞死亡蛋白 1 PD1(p = 0.022)和 CD69(p = 0.03)的表达、CD19/CD5 高/CDXCR4 低水平(p = 0.04)和淋巴结细胞性。我们还发现,由一过性高淋巴细胞增多症识别出的一组患者的反应持续时间较短,临床预后较差。通过数学方法,我们再现了患者特异性的动态变化,并估算出了相关的患者特异性生物参数,突出表明两组患者之间的差异主要是由于淋巴结区白血病 B 细胞的产生,其次是 T 淋巴细胞和白血病 B 细胞进入血液。获得更多数据,尤其是纵向核磁共振成像数据,可以加强关于淋巴结中白血病B细胞动态以及两组不同患者相关性的结论:总之,我们的多学科研究让人们更好地了解了伊布替尼的反应,并强调了伊布替尼治疗前和治疗过程中的新药效学参数。由于我们的研究结果突显了一过性高淋巴细胞增多症患者的反应持续时间和结局缩短,因此我们的方法为伊布替尼治疗3个月后的管理提供了支持:试验注册:ClinicalTrials.gov NCT02824159。
New pharmacodynamic parameters linked with ibrutinib responses in chronic lymphocytic leukemia: Prospective study in real-world patients and mathematical modeling.
Background: One of the first clinical observations of ibrutinib activity in the treatment of chronic lymphocytic leukemia (CLL) is a rapid decline in lymph nodes size. This phenomenon is accompanied by an hyperlymphocytosis, either transient or prolonged, which is associated with distinct clinical responses and thus has an impact on long-term outcomes. Understanding which factors determine distinct disease courses upon ibrutinib treatment remains a scientific challenge.
Methods and findings: From 2016 to 2021, we conducted a longitudinal and observational study in 2 cohorts of patients with chronic lymphocytic leukemia (CLL) (cohort 1, n = 41; cohort 2, n = 81). These cohorts reflect the well-known clinical features of CLL patients, such as Male/Female sex ratio of 2/1, a median age of 70 years at diagnosis, and include patients in first-line therapy (27%) or relapsed/refractory patients (73%). Blood cell counts were followed for each patient during 2 years of ibrutinib treatment. In addition, immunophenotyping and whole-body magnetic resonance imaging (MRI) were assessed in patients from cohort 1. These data were integrated in a newly built mathematical model, inspired by previous mathematical works on CLL treatment and combining dynamical and statistical models, leading to the identification of biological mechanisms associated with the 2 types of clinical responses. This multidisciplinary approach allowed to identify baseline parameters that dictated lymphocytes kinetics upon ibrutinib treatment. Indeed, ibrutinib-induced lymphocytosis defined 2 CLL patient subgroups, transient hyperlymphocytosis (tHL) or prolonged hyperlymphocytosis (pHL), that can be discriminated, before the treatment, by absolute counts of CD4+ T lymphocytes (p = 0.026) and regulatory CD4 T cells (p = 0.007), programmed cell death protein 1 PD1 (p = 0.022) and CD69 (p = 0.03) expression on B leukemic cells, CD19/CD5high/CXCR4low level (p = 0.04), and lymph node cellularity. We also pinpointed that the group of patients identified by the transient hyperlymphocytosis has lower duration response and a poor clinical outcome. The mathematical approach led to the reproduction of patient-specific dynamics and the estimation of associated patient-specific biological parameters, and highlighted that the differences between the 2 groups were mainly due to the production of leukemic B cells in lymph node compartments, and to a lesser extent to T lymphocytes and leukemic B cell egress into bloodstream. Access to additional data, especially longitudinal MRI data, could strengthen the conclusions regarding leukemic B cell dynamics in lymph nodes and the relevance of 2 distinct groups of patients.
Conclusions: Altogether, our multidisciplinary study provides a better understanding of ibrutinib response and highlights new pharmacodynamic parameters before and along ibrutinib treatment. Since our results highlight a reduced duration response and outcome in patients with transient hyperlymphocytosis, our approach provides support for managing ibrutinib therapy after 3 months of treatment.
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