Abstract
T-cell Acute Lymphoblastic Leukemia (T-ALL) is a NOTCH1-driven disease in need of novel therapies. Here, we identify a NOTCH1-SIRT1-KAT7 link as a therapeutic vulnerability in T-ALL, in which SIRT1 is overexpressed downstream of a novel NOTCH1-bound enhancer. SIRT1 loss impairs leukemia generation, while SIRT1 overexpression accelerates leukemia and confers resistance to NOTCH1 inhibition in a deacetylase-dependent manner. Moreover, secondary SIRT1 loss extends survival and synergizes with NOTCH1 inhibition. Global acetyl-proteomics upon SIRT1 loss uncovered hyperacetylation of KAT7 and BRD1, subunits of a histone acetyltransferase complex targeting H4K12. Metabolic and gene expression profiling revealed a metabolic crisis together with a transcriptional signature resembling KAT7 deletion. Consistently, SIRT1 loss resulted in reduced H4K12ac, and overexpression of a non-acetylatable KAT7 mutant partly rescued SIRT1 loss-induced proliferation defects. The newly unveiled NOTCH1-SIRT1-KAT7 axis uncovers novel therapeutic targets in T-ALL and reveals a circular feedback mechanism balancing deacetylase/acetyltransferase activation with potentially broad relevance in cancer.
Statement of significance We identified a novel axis in T-ALL whereby NOTCH1 activates SIRT1 through an enhancer region, and SIRT1 deacetylates and activates KAT7. Targeting SIRT1 shows antileukemic effects, partly mediated by KAT7 inactivation. Our results identify novel therapeutic targets and uncover a rheostat mechanism between deacetylase/acetyltransferase activities with potentially broader cancer relevance.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Financial support: Work in the laboratory of DH is supported by the US National Institutes of Health (R01CA236936), the American Cancer Society (RSG-19-161-01-TBE), The Leukemia & Lymphoma Society (Scholar Award 1386-23), the Alex’s Lemonade Stand Foundation, the Children’s Leukemia Research Association, the Gabrielle’s Angel Foundation for Cancer Research, the American Association for Cancer Research (AACR-Bayer Cancer Discovery and Innovation grant) and the Rutgers Cancer Institute of New Jersey. Work in the laboratory of H.K. is supported by the National Institutes of Health (R01CA233662) and the V Foundation (T2019-012), as well as by Rutgers Office of Advanced Research Computing (NIH 1S10OD012346-01A1). In addition, Rutgers Cancer Institute of New Jersey shared resources supported in part by the National Cancer Institute Cancer Center Support Grant P30CA072720 were instrumental for this project, including Biomedical Informatics Shared Resource (P30CA072720-5917), Flow Cytometry and Cell Sorting Shared Resource (P30CA072720-5921), the Pilot Award/New Investigator Award (P30CA072720-5931). Moreover, purchase of the Eclipse and QE instruments was supported by NIH grants S10OD025140 and S10OD01640. Work in the lab of P.R. is supported by the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Development (NICHD). We also thank the NICHD molecular genomics core and computational resources of the NIH HPC Biowulf cluster (hpc.nih.gov). Fellowships from the New Jersey Commission on Cancer Research supported the work of V.dD. (DCHS19PPC008). L.T. (DCHS20PPC010) and P.R.N. (COCR22PDF002). V.dD. was also supported by the Pediatric Cancer and Blood Disorders Research Center at the Rutgers Cancer Institute of New Jersey.
Conflict of interest disclosure: The authors declare no competing financial interests.