Precision Treatment of Acute Myeloid Leukemia : Predictive Response Biomarkers for BET inhibitor JQ1
Saad, Joseph (2018-09-19)
Precision Treatment of Acute Myeloid Leukemia : Predictive Response Biomarkers for BET inhibitor JQ1
Saad, Joseph
(19.09.2018)
Julkaisu on tekijänoikeussäännösten alainen. Teosta voi lukea ja tulostaa henkilökohtaista käyttöä varten. Käyttö kaupallisiin tarkoituksiin on kielletty.
avoin
Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2018100237127
https://urn.fi/URN:NBN:fi-fe2018100237127
Tiivistelmä
Acute myeloid leukemia (AML) is a hematological malignancy characterized by the accumulation of immature and abnormally proliferating blast cells in the patient’s bone marrow and peripheral blood. Despite the mounting knowledge, there remains a lack of targeted treatment options. A novel class of inhibitors targeting bromodomain and extra terminal (BET) proteins has recently demonstrated promising therapeutic activity in AML. This study sought to identify biomarkers predictive of sensitivity or resistance to BET inhibitors, using JQ1 as the representative compound. Samples from AML patients (n = 170) were analyzed for their clinical characteristics, molecular profiles, and ex vivo JQ1 responses. Associations between the different molecular features and the drug responses were investigated using statistical and bioinformatic approaches. As a result, a mutation in the NCOR2 gene was identified as a predictor of sensitivity. On the other hand, mutually exclusive mutations in a set of genes (IDH1, IDH2, TET2, and WT1) appeared to confer JQ1 resistance. Incorporation of copy number variation data from the patients was in line with both hypotheses, which were also successfully validated using publicly available cell line data. The results suggest a novel strategy to identify AML patients for treatment using BET inhibition therapy. This study also demonstrates the feasibility of using the bioinformatics pipeline to identify treatment biomarkers for personalized medicine. This work supports the implementation of personalized medicine in the clinical setting, allowing the attainment of better disease management techniques and clinical outcomes.