AML中FAB亚型和分子突变的药物敏感性模式:精准医学的综合分析

Mobina Shrestha, Bishwas Mandal, Vishal Mandal, Sabin Karki, Reshu Thapa
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引用次数: 0

摘要

急性髓性白血病(AML)是一种异质性疾病,其特征是不同的法、美、英(FAB)分类和分子突变。了解这些生物标记物与药物反应的关系对于改进治疗方法至关重要。研究人员使用选择性药物敏感性评分(sDSS)对186名AML患者的药物敏感性模式进行了研究,分析了515种市售化疗药物和靶向肿瘤药物的数据。分析不同FAB亚型(M0、M1、M2、M4、M4 eos、M4/M5和M5)和重要突变(NPM1、FLT3、FLT3- itd、FLT3- tkd和KIT)的药物敏感性。结果Navitoclax对M0、M1和M2亚型均有较好的疗效。NPM1突变与对多种治疗药物的敏感性增加有关。FLT3-ITD突变与对PI3K/mTOR抑制剂的显著反应性相关。对药物组合的分析揭示了使用多种治疗药物的复杂性,通常导致有效性降低,但为成功的药物配对提供了见解。研究结果强调了AML个性化治疗策略的必要性,提倡将个体突变谱和FAB分类结合起来的治疗方案,以加强患者护理和改善临床结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Drug Sensitivity patterns across FAB subtypes and molecular mutations in AML: A comprehensive analysis for precision medicine

Drug Sensitivity patterns across FAB subtypes and molecular mutations in AML: A comprehensive analysis for precision medicine

Background

Acute myeloid leukaemia (AML) is a heterogeneous disease characterised by distinct French–American–British (FAB) classifications and molecular mutations. Understanding how these biological markers relate to drug responses is crucial for refining therapeutic approaches.

Methods

We examined drug sensitivity patterns in 186 AML patients using selective Drug Sensitivity Scores (sDSS), analysing data from 515 commercially available chemotherapeutic and targeted oncology agents. Drug sensitivity was analysed across various FAB subtypes (M0, M1, M2, M4, M4 eos, M4/M5, and M5) and important mutations (NPM1, FLT3, FLT3-ITD, FLT3-TKD and KIT).

Results

Navitoclax showed greater effectiveness in M0, M1, and M2 subtypes. NPM1 mutations were linked to increased sensitivity to multiple therapeutic agents. FLT3-ITD mutations were associated with significant responsiveness to PI3K/mTOR inhibitors. Analysis of drug combinations revealed complexities in using multiple therapeutic agents, often leading to reduced effectiveness but providing insights into successful drug pairings.

Conclusions

The findings underscore the necessity for personalised therapeutic strategies in AML, advocating for treatment protocols that integrate individual mutation profiles and FAB classifications to enhance patient care and improve clinical outcomes.

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