scholarly journals Molecular landscape and targeted therapy of acute myeloid leukemia

2018 ◽  
Vol 6 (1) ◽  
Author(s):  
Runxia Gu ◽  
Xue Yang ◽  
Hui Wei
Blood Reviews ◽  
2011 ◽  
Vol 25 (6) ◽  
pp. 247-254 ◽  
Author(s):  
Brunangelo Falini ◽  
Ilaria Gionfriddo ◽  
Federica Cecchetti ◽  
Stelvio Ballanti ◽  
Valentina Pettirossi ◽  
...  

2018 ◽  
Vol 94 (1) ◽  
pp. E24-E27 ◽  
Author(s):  
Loïc Renaud ◽  
Olivier Nibourel ◽  
Alice Marceau-Renaut ◽  
Bérengère Gruson ◽  
Nathalie Cambier ◽  
...  

2020 ◽  
Vol 22 (6) ◽  
Author(s):  
Ludovica Marando ◽  
Brian J. P. Huntly

Abstract Purpose of Review The field of acute myeloid leukemia (AML) has been revolutionized in recent years by the advent of high-throughput techniques, such as next-generation sequencing. In this review, we will discuss some of the recently identified mutations that have defined a new molecular landscape in this disease, as well as their prognostic, predictive, and therapeutic implications. Recent Findings Recent studies have shown how many cases of AML evolve from a premalignant period of latency characterized by the accumulation of several mutations and the emergence of one or multiple dominant clones. The pattern of co-occurring mutations and cytogenetic abnormalities at diagnosis defines risk and can determine therapeutic approaches to induce remission. Besides the genetic landscape at diagnosis, the continued presence of particular gene mutations during or after treatment carries prognostic information that should further influence strategies to maintain remission in the long term. Summary The recent progress made in AML research is a seminal example of how basic science can translate into improving clinical practice. Our ability to characterize the genomic landscape of individual patients has not only improved our ability to diagnose and prognosticate but is also bringing the promise of precision medicine to fruition in the field.


2015 ◽  
Vol 366 (2) ◽  
pp. 160-172 ◽  
Author(s):  
Jingcao Huang ◽  
Hui Lyu ◽  
Jianxiang Wang ◽  
Bolin Liu

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