Back

KAT7 is a therapeutic vulnerability of MLL-rearranged acute myeloid leukemia

Au, Y. Z.; Gu, M.; De Braekeleer, E.; Yu, J. S. L.; Ong, S. H.; Gozdecka, M.; Chen, X.; Tzelepis, K.; Huntly, B. J. P.; Vassiliou, G. S.; Yusa, K.

2020-04-25 cancer biology
10.1101/2020.04.25.054049 bioRxiv
Show abstract

Histone acetyltransferases (HATs) catalyze the transfer of an acetyl group from acetyl-CoA to lysine residues of histones and play a central role in transcriptional regulation in diverse biological processes. Dysregulation of HAT activity can lead to human diseases including developmental disorders and cancer. Through genome-wide CRISPR-Cas9 screens, we identified several HATs of the MYST family as fitness genes for acute myeloid leukaemia (AML). Here we investigate the essentiality of lysine acetyltransferase KAT7 in AMLs driven by the MLL-X gene fusions. We found that KAT7 loss leads to a rapid and complete loss of both H3K14ac and H4K12ac marks, in association with reduced proliferation, increased apoptosis and differentiation of AML cells. Acetyltransferase activity of KAT7 is essential for the proliferation of these cells. Mechanistically, our data propose that acetylated histones provide a platform for the recruitment of MLL-fusion-associated adaptor proteins such as BRD4 and AF4 to gene promoters. Upon KAT7 loss, these factors together with RNA polymerase II rapidly dissociate from several MLL-fusion target genes that are essential for AML cell proliferation, including MEIS1, PBX3 and SENP6. Our findings reveal that KAT7 is a plausible therapeutic target for this poor prognosis AML subtype.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Leukemia
○ 42 papers in training set
Top 0.1%
13.0%
Similar papers in this journal
2
Nature Communications
○ 5641 papers in training set
Top 14%
12.7%
Similar papers in this journal
3
Blood
● 74 papers in training set
Top 0.1%
12.0%
Similar papers in this journal
4
Science Advances
● 1243 papers in training set
Top 3%
6.3%
Similar papers in this journal
5
Cell Reports
○ 1498 papers in training set
Top 6%
5.5%
6
eLife
● 5828 papers in training set
Top 22%
5.5%
Similar papers in this journal
50% of probability mass above
7
Cancer Discovery
● 66 papers in training set
Top 0.7%
3.5%
8
Oncogene
○ 85 papers in training set
Top 0.6%
3.3%
9
Cancers
○ 213 papers in training set
Top 3%
1.9%
10
Scientific Reports
○ 3612 papers in training set
Top 49%
1.9%
11
Oncogenesis
○ 12 papers in training set
Top 0.1%
1.9%
12
Haematologica
● 25 papers in training set
Top 0.4%
1.7%
13
Blood Advances
● 62 papers in training set
Top 0.8%
1.4%
14
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 34%
1.1%
15
Molecular Cancer Research
● 49 papers in training set
Top 0.9%
1.1%
16
Cell Death & Disease
147 papers in training set
Top 3%
1.1%
17
Cancer Research
● 130 papers in training set
Top 2%
1.1%
18
Genome Biology
○ 637 papers in training set
Top 8%
1.1%
19
Journal of Hematology & Oncology
○ 10 papers in training set
Top 0.3%
1.1%
20
Journal of Experimental Medicine
● 119 papers in training set
Top 3%
1.0%
21
Communications Biology
○ 993 papers in training set
Top 25%
1.0%
22
Molecular Cell
○ 350 papers in training set
Top 4%
1.0%
23
Journal of Clinical Investigation
● 179 papers in training set
Top 5%
0.9%
24
Clinical Cancer Research
● 64 papers in training set
Top 2%
0.9%
25
EMBO Reports
○ 263 papers in training set
Top 7%
0.8%
26
Nucleic Acids Research
◐ 1281 papers in training set
Top 13%
0.8%
27
iScience
○ 1154 papers in training set
Top 35%
0.8%
28
PLOS Genetics
● 862 papers in training set
Top 11%
0.8%
29
HemaSphere
○ 16 papers in training set
Top 0.3%
0.8%
30
Nature Genetics
○ 286 papers in training set
Top 5%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.