Deregulation of enhancer structure, function, and dynamics in acute lymphoblastic leukemia

A Therapeutically Targetable NOTCH1-SIRT1-KAT7 Axis in T-cell Leukemia

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 the histone deacetylase SIRT1 is overexpressed downstream of a NOTCH1-bound enhancer. SIRT1 loss impaired leukemia generation, whereas SIRT1 overexpression accelerated leukemia and conferred resistance to NOTCH1 inhibition in a deacetylase-dependent manner. Moreover, pharmacologic or genetic inhibition of SIRT1 resulted in significant antileukemic effects. 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 metabolic changes together with a transcriptional signature resembling KAT7 deletion. Consistently, SIRT1 loss resulted in reduced H4K12ac, and overexpression of a nonacetylatable KAT7-mutant partly rescued SIRT1 loss-induced proliferation defects. Overall, our results uncover therapeutic targets in T-ALL and reveal a circular feedback mechanism balancing deacetylase/acetyltransferase activation with potentially broad relevance in cancer.

SIGNIFICANCE

We identify a T-ALL axis 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 reveal T-ALL therapeutic targets and uncover a rheostat mechanism between deacetylase/acetyltransferase activities with potentially broader cancer relevance. This article is highlighted in the In This Issue feature, p. 1.

An enhancer RNA-based risk model for prediction of bladder cancer prognosis

Background

Bladder cancer patients have a high recurrence and poor survival rates worldwide. Early diagnosis and intervention are the cornerstones for favorable prognosis. However, commonly used predictive tools cannot meet clinical needs because of their insufficient accuracy.

Methods

We have developed an enhancer RNA (eRNA)-based signature to improve the prediction for bladder cancer prognosis. First, we analyzed differentially expressed eRNAs in gene expression profiles and clinical data for bladder cancer from The Cancer Genome Atlas database. Then, we constructed a risk model for prognosis of bladder cancer patients, and analyzed the correlation between this model and tumor microenvironment (TME). Finally, regulatory network of downstream genes of eRNA in the model was constructed by WGCNA and enrichment analysis, then Real-time quantitative PCR verified the differentiation of related genes between tumor and adjacent tissue.

Results

We first constructed a risk model composed of eight eRNAs, and found the risk model could be an independent risk factor to predict the prognosis of bladder cancer. Then, the log-rank test and time-dependent ROC curve analysis shown the model has a favorable ability to predict prognosis. The eight risk eRNAs may participate in disease progression by regulating cell adhesion and invasion, and up-regulating immune checkpoints to suppress the immunity in TME. mRNA level change in related genes further validated regulatory roles of eRNAs in bladder cancer. In summary, we constructed an eRNA-based risk model and confirmed that the model could predict the prognosis of bladder cancer patients.