In:
Frontiers in Pharmacology, Frontiers Media SA, Vol. 13 ( 2022-6-6)
Kurzfassung:
The KMT2A ( MLL ) gene rearrangements ( KMT2A -r) are associated with a diverse spectrum of acute leukemias. Although most KMT2A -r are restricted to nine partner genes, we have recently revealed that KMT2A - USP2 fusions are often missed during FISH screening of these genetic alterations. Therefore, complementary methods are important for appropriate detection of any KMT2A -r. Here we use a machine learning model to unravel the most appropriate markers for prediction of KMT2A -r in various types of acute leukemia. A Random Forest and LightGBM classifier was trained to predict KMT2A -r in patients with acute leukemia. Our results revealed a set of 20 genes capable of accurately estimating KMT2A -r. The SKIDA1 (AUC: 0.839; CI: 0.799–0.879) and LAMP5 (AUC: 0.746; CI: 0.685–0.806) overexpression were the better markers associated with KMT2A -r compared to CSPG4 (also named NG2 ; AUC: 0.722; CI: 0.659–0.784), regardless of the type of acute leukemia. Of importance, high expression levels of LAMP5 estimated the occurrence of all KMT2A-USP2 fusions. Also, we performed drug sensitivity analysis using IC50 data from 345 drugs available in the GDSC database to identify which ones could be used to treat KMT2A -r leukemia. We observed that KMT2A -r cell lines were more sensitive to 5-Fluorouracil (5FU), Gemcitabine (both antimetabolite chemotherapy drugs), WHI-P97 (JAK-3 inhibitor), Foretinib (MET/VEGFR inhibitor), SNX-2112 (Hsp90 inhibitor), AZD6482 (PI3Kβ inhibitor), KU-60019 (ATM kinase inhibitor), and Pevonedistat (NEDD8-activating enzyme (NAE) inhibitor). Moreover, IC50 data from analyses of ex-vivo drug sensitivity to small-molecule inhibitors reveals that Foretinib is a promising drug option for AML patients carrying FLT3 activating mutations. Thus, we provide novel and accurate options for the diagnostic screening and therapy of KMT2A -r leukemia, regardless of leukemia subtype.
Materialart:
Online-Ressource
ISSN:
1663-9812
DOI:
10.3389/fphar.2022.749472
DOI:
10.3389/fphar.2022.749472.s001
Sprache:
Unbekannt
Verlag:
Frontiers Media SA
Publikationsdatum:
2022
ZDB Id:
2587355-6
SSG:
15,3
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