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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.
Background. Recent pathomolecular studies on the MLL-AF4 fusion protein revealed that the murinized version of MLL-AF4, the MLL-Af4 fusion protein, was able to induce leukemia when expressed in murine or human hematopoietic stem/progenitor cells (Lin et al. in Cancer Cell 30:737–749, 2016). In parallel, a group from Japan demonstrated that the pSer domain of the AF4 protein, as well as the pSer domain of the MLL-AF4 fusion is able to bind the Pol I transcription factor complex SL1 (Okuda et al. in Nat Commun 6:8869, 2015). Here, we investigated the human MLL-AF4 and a pSer-murinized version thereof for their functional properties in mammalian cells. Gene expression profiling studies were complemented by intracellular localization studies and functional experiments concerning their biological activities in the nucleolus.
Results: Based on our results, we have to conclude that MLL-AF4 is predominantly localizing inside the nucleolus, thereby interfering with Pol I transcription and ribosome biogenesis. The murinized pSer-variant is localizing more to the nucleus, which may suggest a different biological behavior. Of note, AF4-MLL seems to cooperate at the molecular level with MLL-AF4 to steer target gene transcription, but not with the pSer-murinized version of it.
Conclusion: This study provides new insights and a molecular explanation for the described differences between hMLL-hAF4 (not leukemogenic) and hMLL-mAf4 (leukemogenic). While the human pSer domain is able to efficiently recruit the SL1 transcription factor complex, the murine counterpart seems to be not. This has several consequences for our understanding of t(4;11) leukemia which is the most frequent leukemia in infants, childhood and adults suffering from MLL-r acute leukemia.