Abstract The ERG (ETS-related gene) transcription factor is linked to various types of cancer, including leukemia. However, the specific ERG domains and co-factors contributing to leukemogenesis are poorly understood. Drug targeting a transcription factor such as ERG is challenging. Our study reveals the critical role of a conserved amino acid, proline, at position 199, located at the 3’ end of the PNT (pointed) domain, in ERG’s ability to induce leukemia. P199 is necessary for ERG to promote self-renewal, prevent myeloid differentiation in hematopoietic progenitor cells, and initiate leukemia in mouse models. Here we show that P199 facilitates ERG’s interaction with the NCoR-HDAC3 co-repressor complex. Inhibiting HDAC3 reduces the growth of ERG-dependent leukemic and prostate cancer cells, indicating that the interaction between ERG and the NCoR-HDAC3 co-repressor complex is crucial for its oncogenic activity. Thus, targeting this interaction may offer a potential therapeutic intervention.
Hypomethylating agents (HMAs) are frontline therapies for Myelodysplastic Neoplasms (MDS) and Acute Myeloid Leukemia (AML). However, acquired resistance and treatment failure are commonplace. To address this, we perform a genome-wide CRISPR-Cas9 screen in a human MDS-derived cell line, MDS-L, and identify TOPORS as a loss-of-function target that synergizes with HMAs, reducing leukemic burden and improving survival in xenograft models. We demonstrate that depletion of TOPORS mediates sensitivity to HMAs by predisposing leukemic blasts to an impaired DNA damage response (DDR) accompanied by an accumulation of SUMOylated DNMT1 in HMA-treated TOPORS-depleted cells. The combination of HMAs with targeting of TOPORS does not impair healthy hematopoiesis. While inhibitors of TOPORS are unavailable, we show that inhibition of protein SUMOylation with TAK-981 partially phenocopies HMA-sensitivity and DDR impairment. Overall, our data suggest that the combination of HMAs with inhibition of SUMOylation or TOPORS is a rational treatment option for High-Risk MDS (HR-MDS) or AML.
Abstract Oncofetal protein SALL4 is critical for tumor cell survival, making it a promising target in cancer therapy. However, it is detectable only in a subset of cancer patients, which limits the therapeutic impact of a SALL4 targeted therapy. Here we report that SALL4 can be activated and/or upregulated pharmacologically by hypomethylating agents, such as 5-Aza-2’-deoxycytidine (DAC), which are used clinically, and that SALL4 negative cancer cells become SALL4 dependent following exogenous expression of SALL4. In addition, the histone deacetylase inhibitor Entinostat (ENT) negatively regulates SALL4 expression by upregulating miR-205. Both ENT and miR-205 treatment induced cell apoptosis, rescuable by SALL4 expression or miR-205 inhibition. Finally, DAC pre-treatment sensitizes SALL4 negative cancer cell lines to ENT both in culture and in vivo by upregulating SALL4. Overall, we propose a framework whereby the scope of targeted therapy can be expanded by sensitizing cancer cells to treatment by target induction and engineered dependency. Significance This proof of concept study demonstrates that targeted cancer therapy can be achieved by inducing a targetable gene establishing a survival-dependency for cancer cells. For SALL4, sequential treatment of DAC and ENT could expand the scope of SALL4 targeted cancer therapy.
Whole genome sequencing has enabled the identification of thousands of somatic mutations within non-coding genomic regions of individual cancer samples. However, identification of mutations that potentially alter gene regulation remains a major challenge. Here we present OncoCis, a new method that enables identification of potential cis-regulatory mutations using cell type-specific genome and epigenome-wide datasets along with matching gene expression data. We demonstrate that the use of cell type-specific information and gene expression can significantly reduce the number of candidate cis-regulatory mutations compared with existing tools designed for the annotation of cis-regulatory SNPs. The OncoCis webserver is freely accessible at https://powcs.med.unsw.edu.au/OncoCis/ .
<p>Supplementary Tables S1-6. Table S1. Mutation coordinates and associated genes for potential putative promoter mutations identified in COLO-829. Table S2. Number of promoter and total mutations in each of 34 whole-genome sequenced cutaneous melanoma samples available from TCGA. Table S3. Details of polymerase chain reaction (PCR) amplification and genomic DNA used for reporter constructs. Table S4. Base calls at each mutation site for the four COLO-829 promoter mutations with changes observed in mutant promoter activity from wild-type by reporter assays. Table S5. Single nucleotide polymorphisms (SNPs) present within reporter constructs. Table S6. Primer sequences used for each candidate gene in polymerase chain reaction (PCR) and quantitative polymerase chain reaction (qPCR) experiments.</p>
Abstract Acute myeloid leukemia (AML) is a complex disease characterized by a diverse range of recurrent molecular aberrations that occur in many different combinations. Components of transcriptional networks are a common target of these aberrations, leading to network‐wide changes and deployment of novel or developmentally inappropriate transcriptional programs. Genome‐wide techniques are beginning to reveal the full complexity of normal hematopoietic stem cell transcriptional networks and the extent to which they are deregulated in AML, and new understandings of the mechanisms by which AML cells maintain self‐renewal and block differentiation are starting to emerge. The hope is that increased understanding of the network architecture in AML will lead to identification of key oncogenic dependencies that are downstream of multiple network aberrations, and that this knowledge will be translated into new therapies that target these dependencies. Here, we review the current state of knowledge of network perturbation in AML with a focus on major mechanisms of transcription factor dysregulation, including mutation, translocation, and transcriptional dysregulation, and discuss how these perturbations propagate across transcriptional networks. We will also review emerging mechanisms of network disruption, and briefly discuss how increased knowledge of network disruption is already being used to develop new therapies.
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