Impact of myeloid leukemia associated mutations (ASXL1, DNMT3A, TET2, IDH1 and IDH2) on treatment responses among Chronic Myeloid Leukemia (CML) patients in Tanzania

摘要 本申请是为了回应被确认为非CA-CA的特殊利益通知(NOSI)而提交的 23-038.酪氨酸激酶抑制剂(TKIs)，如伊马替尼，治疗慢性前列腺癌的进展 髓系白血病(CML)极大地延长了患者的预期寿命。在高收入国家，生活 慢性粒细胞白血病患者的期望值接近普通人群。而高收入国家 转向允许在完全缓解的情况下停止TKI的治疗范例， 不幸的是，坦桑尼亚没有观察到同样的结果，尽管TKI很好地获得了CML 通过既定的患者援助计划为患者提供帮助。我们的小组此前已经表明，延迟 具有高级疾病特征的诊断和表现导致观察到的不良反应 在坦桑尼亚的慢性粒细胞白血病患者中。最近的研究表明，慢性粒细胞白血病的晚期诊断与 累积更多的遗传损伤，这可能随后导致治疗失败、疾病 进展，并最终死亡。这些突变最常见于表观遗传修饰基因。 例如ASXL1、DNMT3A、TET2、IDH1和IDH2。我们假设不良的治疗反应 在坦桑尼亚的CML患者中观察到的是由于当时这些髓系白血病突变的高负担 诊断的结果。因此，本研究旨在更好地了解TKI的抗性机制。 这些髓系相关突变。我们将对新诊断的慢性粒细胞白血病进行前瞻性队列研究。 达累斯海路癌症研究所的患者在伊马替尼开始治疗后12个月内进行了随访 坦桑尼亚的萨拉姆。存在髓系白血病相关突变(ASXL1、DNMT3A、TET2、IDH1和 IDH2)将在诊断时进行评估。提取的基因组DNA(GDNA)将进行下一代测序 在MiSeq(美国圣地亚哥Illumina)上使用商业上可用的髓系白血病面板。泛化 将使用估计方程(GEE)来研究诊断时突变状态对 根据欧洲白血病网络指南的定义，治疗前12个月的分子反应。 其他变量，包括性别、年龄和确诊时的Sokal评分，将被视为模型中的协变量。 识别治疗耐药的预测因素对改进CML治疗指南具有很高的潜力 坦桑尼亚和撒哈拉以南非洲，根据从非洲人口中得出的科学证据。

ABSTRACT This application is being submitted in response to the Notice of Special Interest (NOSI) identified as NOT-CA- 23-038. The development of tyrosine kinase inhibitors (TKIs), such as imatinib, for the treatment of chronic myeloid leukemia (CML) has dramatically improved patients’ life expectancy. In high-income nations, the life expectancy of a patient with CML approaches that of the general population. While high-income countries are moving towards a treatment paradigm that allows for TKI discontinuation in the setting of complete remission, these same outcomes are unfortunately not observed in Tanzania, despite good access of TKIs to CML patients through an established patient assistance program. Our group has previously shown that delayed diagnoses and presentations with advanced disease features contribute to the observed poor responses among patients with CML in Tanzania. Recent studies have shown that late CML diagnosis is associated with cumulative accumulation of more genetic lesions which can subsequently lead to treatment failure, disease progression, and eventual death. These mutations are most commonly identified in epigenetic modifier genes such as ASXL1, DNMT3A, TET2, IDH1, and IDH2. We hypothesize that the poor treatment responses observed in CML patients in Tanzania is due to a high burden of these myeloid leukemia mutations at the time of diagnosis. Therefore, this study aims to better understand mechanisms of TKI resistance contributed by these myeloid-associated mutations. We will conduct a prospective cohort study of newly diagnosed CML patients followed over a period of 12 months after imatinib initiation at Ocean Road Cancer Institute in Dar es Salaam, Tanzania. Presence of myeloid-leukemia associated mutations (ASXL1, DNMT3A, TET2, IDH1, and IDH2) will be assessed at diagnosis. Extracted genomic DNA (gDNA) will undergo next generation sequencing using commercially available myeloid leukemia panel on MiSeq (Illumina, San Diego, USA). Generalized Estimating Equations (GEE) will be used to investigate the influence of mutation status at diagnosis on molecular responses in the first 12 months of treatment as defined by the European Leukemia Net Guidelines. Other variables including sex, age, and Sokal score at diagnosis will be considered as covariates in the model. Identification of predictors of treatment resistance has a high potential to improve CML treatment guidelines in Tanzania and sub-Saharan Africa broadly, based on scientific evidence derived from African population.