Genetic biomarkers of drug resistance: A compass of prognosis and targeted therapy in acute myeloid leukemia

髓系白血病 医学 抗药性 肿瘤科 癌症研究 精密医学 靶向治疗 生物信息学 内科学 生物 遗传学 癌症 病理
作者
Luyao Long,Yehuda G. Assaraf,Zi‐Ning Lei,Hongwei Peng,Lin Yang,Zhe‐Sheng Chen,Simei Ren
出处
期刊:Drug Resistance Updates [Elsevier BV]
卷期号:52: 100703-100703 被引量:36
标识
DOI:10.1016/j.drup.2020.100703
摘要

Acute myeloid leukemia (AML) is a highly aggressive hematological malignancy with complex heterogenous genetic and biological nature. Thus, prognostic prediction and targeted therapies might contribute to better chemotherapeutic response. However, the emergence of multidrug resistance (MDR) markedly impedes chemotherapeutic efficacy and dictates poor prognosis. Therefore, prior evaluation of chemoresistance is of great importance in therapeutic decision making and prognosis. In recent years, preclinical studies on chemoresistance have unveiled a compendium of underlying molecular basis, which facilitated the development of targetable small molecules. Furthermore, routing genomic sequencing has identified various genomic aberrations driving cellular response during the course of therapeutic treatment through adaptive mechanisms of drug resistance, some of which serve as prognostic biomarkers in risk stratification. However, the underlying mechanisms of MDR have challenged the certainty of the prognostic significance of some mutations. This review aims to provide a comprehensive understanding of the role of MDR in therapeutic decision making and prognostic prediction in AML. We present an updated genetic landscape of the predominant mechanisms of drug resistance with novel targeted therapies and potential prognostic biomarkers from preclinical and clinical chemoresistance studies in AML. We particularly highlight the unfolded protein response (UPR) that has emerged as a critical regulatory pathway in chemoresistance of AML with promising therapeutic horizon. Futhermore, we outline the most prevalent mutations associated with mechanisms of chemoresistance and delineate the future directions to improve the current prognostic tools. The molecular analysis of chemoresistance integrated with genetic profiling will facilitate decision making towards personalized prognostic prediction and enhanced therapeutic efficacy.

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