Selective gene dependencies in MYCN-amplified neuroblastoma include the core transcriptional regulatory circuitry

Durbin, Adam D.; Zimmerman, Mark W.; Dharia, Neekesh V.; Abraham, Brian J.; Iniguez, Amanda Balboni; Weichert-Leahey, Nina; He, Shuning; Krill-Burger, John M.; Root, David E.; Vázquez, Francisca; Tsherniak, Aviad; Hahn, William C.; Golub, Todd R.; Young, Richard A.; Look, A. Thomas; Stegmaier, Kimberly

doi:10.1038/s41588-018-0191-z

Cited by 230 publications

(357 citation statements)

References 44 publications

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“…We therefore profiled genome-wide distribution of H3K27Ac by ChIP-sequencing of JQ1 naive and resistant cells across both cell line models (Fig S3I-P). In concordance with previous studies, SE-associated genes: HAND1/2, GATA3, and PHOX2B , were identified in naive cells (Boeva et al, 2017; Chipumuro et al, 2014; van Groningen et al, 2017, Durbin et al, 2018). SE-marked genes and typical enhancer (TE)-marked genes, defined by high H3K27Ac signal in enhancer regions, were preferentially repressed by JQ1 (Figure S4A, B).…”

Section: Resultssupporting

confidence: 91%

Resistance to Epigenetic-Targeted Therapy Engenders Tumor Cell Vulnerabilities Associated with Enhancer Remodeling

et al. 2018

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SUMMARY Drug resistance represents a major challenge to achieving durable responses to cancer therapeutics. Resistance mechanisms to epigenetically-targeted drugs remain largely unexplored. We used BET inhibition in neuroblastoma as a prototype to model resistance to chromatin modulatory therapeutics. Genome-scale, pooled lentiviral open reading frame (ORF) and CRISPR knockout rescue screens nominated the PI3K pathway as promoting resistance to BET inhibition. Transcriptomic and chromatin profiling of resistant cells revealed that global enhancer remodeling is associated with upregulation of receptor tyrosine kinases (RTKs), activation of PI3K signaling and vulnerability to RTK/PI3K inhibition. Large-scale combinatorial screening with BET inhibitors identified PI3K inhibitors among the most synergistic upfront combinations. These studies provide a roadmap to elucidate resistance to epigenetic-targeted therapeutics and inform efficacious combination therapies.

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Section: Resultssupporting

confidence: 91%

Resistance to Epigenetic-Targeted Therapy Engenders Tumor Cell Vulnerabilities Associated with Enhancer Remodeling

et al. 2018

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“…Accumulating evidence indicates that tumor cells are driven by a small set of transcription factors (TFs) that control global gene expression programs (Durbin et al, 2018;Mansour et al, 2014;Sanda et al, 2012). While disused in corresponding healthy cells, some tumor-driving master transcription factors (MTFs) are often developmental regulators that are aberrantly expressed and functionally co-opted to regulate tumor cell states.…”

Section: Introductionmentioning

confidence: 99%

“…For example, regulators of T cell development, TAL1, GATA3, RUNX1, and MYB, are over-expressed and coregulate oncogenic programs in T-cell acute lymphoblastic leukemias (Mansour et al, 2014;Sanda et al, 2012). Additionally, developmental regulators MYCN, HAND2, ISL1, PHOX2B, GATA3, and TBX2 have been identified as MTFs in neuroblastoma (Durbin et al, 2018). MTFs are generally expressed in only a limited number of cell types, consistent with their potent role in establishing a gene expression program that drives cell identity (D'Alessio et al, 2015;Whyte et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Although TFs are notoriously difficult to directly target with small molecules, several MTFs have been shown to be highly sensitive to pharmaceutical inhibition of general transcriptional regulators, including those that target bromodomain (BRD)-containing proteins and transcriptional cyclin-dependent kinase 7 (Chapuy et al, 2013;Durbin et al, 2018;Kwiatkowski et al, 2014;Wang et al, 2015). The expression of tumor cell MTFs are often driven by large clusters of enhancers, or termed super-or stretch-enhancers (SEs) (Lovén et al, 2013;Parker et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…MTFs are thought to form core transcriptional regulatory circuitries by co-occupying genomic sites, particularly at SEs, and co-regulating the expression of MTF genes and others genes critical for cellular identity (Chen et al, 2019a;Durbin et al, 2018;Sanda et al, 2012). Presently, the main approaches to identifying MTFs in cancer cells attempts to model these features by identifying TFs predicted to exhibit evidence of interconnected autoregulation Saint-André et al, 2016;Zhang et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Predicting master transcription factors from pan-cancer expression data

Reddy

Fonseca

Fuente

et al. 2019

Preprint

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The function of critical developmental regulators can be subverted by cancer cells to control expression of oncogenic transcriptional programs. These "master transcription factors" (MTFs) are often essential for cancer cell survival and represent vulnerabilities that can be exploited therapeutically. The current approaches to identify candidate MTFs examine super-enhancer associated transcription factor-encoding genes with high connectivity in network models. This relies on chromatin immunoprecipitation-sequencing (ChIP-seq) data, which is technically challenging to obtain from primary tumors, and is currently unavailable for many cancer types and clinically relevant subtypes. In contrast, gene expression data are more widely available, especially for rare tumors and subtypes where MTFs have yet to be discovered. We have developed a predictive algorithm called CaCTS (Cancer Core Transcription factor Specificity) to identify candidate MTFs using pancancer RNA-sequencing data from The Cancer Genome Atlas. The algorithm identified 273 candidate MTFs across 34 tumor types and recovered known tumor MTFs. We also made novel predictions, including for cancer types and subtypes for which MTFs have not yet been characterized. Clustering based on MTF predictions reproduced anatomic groupings of tumors that share 1-2 lineage-specific candidates, but also dictated functional groupings, such as a squamous group that comprised five tumor subtypes sharing 3 common MTFs. PAX8, SOX17, and MECOM were candidate factors in high-grade serous ovarian cancer (HGSOC), an aggressive tumor type where the core regulatory circuit is currently uncharacterized. PAX8, SOX17, and MECOM are required for cell viability and lie proximal to super-enhancers in HGSOC cells. ChIPseq revealed that these factors co-occupy HGSOC regulatory elements globally and co-bind at critical gene loci including MUC16 (CA-125). Addiction to these factors was confirmed in studies using THZ1 to inhibit transcription in HGSOC cells, suggesting early down-regulation of these genes may be responsible for cytotoxic effects of THZ1 on HGSOC models. Identification of MTFs across 34 tumor types and 140 subtypes, especially for those with limited understanding of transcriptional drivers paves the way to therapeutic targeting of MTFs in a broad spectrum of cancers.

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Transcription factor 4 is a key mediator of oncogenesis in neuroblastoma by promoting MYC activity

Aljouda,

Shrestha,

DeVaux

et al. 2024

Molecular Oncology

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Super‐enhancer‐associated transcription factor networks define cell identity in neuroblastoma (NB). Dysregulation of these transcription factors contributes to the initiation and maintenance of NB by enforcing early developmental identity states. We report that the class I basic helix–loop–helix (bHLH) transcription factor 4 (TCF4; also known as E2‐2) is a critical NB dependency gene that significantly contributes to these identity states through heterodimerization with cell‐identity‐specific bHLH transcription factors. Knockdown of TCF4 significantly induces apoptosis in vitro and inhibits tumorigenicity in vivo. We used genome‐wide expression profiling, TCF4 chromatin immunoprecipitation sequencing (ChIP‐seq) and TCF4 immunoprecipitation–mass spectrometry to determine the role of TCF4 in NB cells. Our results, along with recent findings in NB for the transcription factors T‐box transcription factor TBX2, heart‐ and neural crest derivatives‐expressed protein 2 (HAND2) and twist‐related protein 1 (TWIST1), propose a role for TCF4 in regulating forkhead box protein M1 (FOXM1)/transcription factor E2F‐driven gene regulatory networks that control cell cycle progression in cooperation with N‐myc proto‐oncogene protein (MYCN), TBX2, and the TCF4 dimerization partners HAND2 and TWIST1. Collectively, we showed that TCF4 promotes cell proliferation through direct transcriptional regulation of the c‐MYC/MYCN oncogenic program that drives high‐risk NB. Mechanistically, our data suggest the novel finding that TCF4 acts to support MYC activity by recruiting multiple factors known to regulate MYC function to sites of colocalization between critical NB transcription factors, TCF4 and MYC oncoproteins. Many of the TCF4‐recruited factors are druggable, giving insight into potential therapies for high‐risk NB. This study identifies a new function for class I bHLH transcription factors (e.g., TCF3, TCF4, and TCF12) that are important in cancer and development.

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Selective gene dependencies in MYCN-amplified neuroblastoma include the core transcriptional regulatory circuitry

Cited by 230 publications

References 44 publications

Resistance to Epigenetic-Targeted Therapy Engenders Tumor Cell Vulnerabilities Associated with Enhancer Remodeling

Resistance to Epigenetic-Targeted Therapy Engenders Tumor Cell Vulnerabilities Associated with Enhancer Remodeling

Predicting master transcription factors from pan-cancer expression data

Transcription factor 4 is a key mediator of oncogenesis in neuroblastoma by promoting MYC activity

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