The transcription factor GABP selectively binds and activates the mutant TERT promoter in cancer

Bell, Robert J.A.; Rube, H. Tomas; Kreig, Alex; Mancini, Andrew; Fouse, Shaun D.; Nagarajan, Raman P.; Choi, Serah; Hong, Chibo; He, Daniel; Pekmezci, Melike; Wiencke, John K.; Wrensch, Margaret; Chang, Susan M.; Walsh, Kyle M.; Myong, Sua; Song, Jun S.; Costello, J

doi:10.1126/science.aab0015

Cited by 478 publications

(560 citation statements)

References 44 publications

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“…91 In an attempt to rationalize the molecular basis for the transcriptional effects of these somatic mutations of hTERT, it was first proposed that new ETS transcription factor binding sites are generated in the duplex form of the promoter. 45 More recently it has been proposed that GABP transcription factors can be recruited to mutant promoter elements in glioblastoma multiforme, 52 thus providing an additional mechanism for the effects of these mutations. However, these mechanisms cannot fully account for the differences in transcriptional regulation of hTERT conferred by mutant promoters.…”

Section: Discussionmentioning

confidence: 99%

“…Critically, this finding also provides a direct opportunity to reverse the effects of these somatic mutations. 52 Significantly, these mutations are also localized in the 5-12 G-quadruplex with the 3:26:1 loop configuration.…”

Section: Introductionmentioning

confidence: 92%

“…45,46 In addition, it has recently been suggested that the mutations found in glioblastoma multiforme could lead to recruitment of multimeric GA-binding protein (GABP) transcription factors to activate hTERT. 52 However, these models cannot fully account for promoterdriven hTERT transcriptional modulation in part because genetic background may play a role in enabling aberrant transcription factor binding. For example, both BRAF and EGFR mutations frequently co-occur with hTERT promoter mutations in melanoma and glioblastoma and may be necessary for GABPmediated activation prior to its interaction with the mutant hTERT promoter.…”

Section: Introductionmentioning

confidence: 99%

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A Pharmacological Chaperone Molecule Induces Cancer Cell Death by Restoring Tertiary DNA Structures in Mutant hTERT Promoters

et al. 2016

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Activation of human telomerase reverse transcriptase (hTERT) is necessary for limitless replication in tumorigenesis. Whereas hTERT is transcriptionally silenced in normal cells, most tumor cells reactivate hTERT expression by alleviating transcriptional repression through diverse genetic and epigenetic mechanisms. Transcription-activating hTERT promoter mutations have been found to occur at high frequencies in multiple cancer types. These mutations have been shown to form new transcription factor binding sites that drive hTERT expression, but this model cannot fully account for differences in wildtype (WT) and mutant promoter activation and has not yet enabled a selective therapeutic strategy. Here we demonstrate a novel mechanism by which promoter mutations activate hTERT transcription, which also sheds light on a unique therapeutic opportunity. Promoter mutations occur in a core promoter region that forms tertiary structures consisting of a pair of G-quadruplexes involved in transcriptional silencing.We show that promoter mutations exert a detrimental effect on the folding of one of these Gquadruplexes, resulting in a nonfunctional silencer element that alleviates transcriptional repression. We have also identified a small drug-like pharmacological chaperone (pharmacoperone) molecule, GTC365, that acts at an early step in the G-quadruplex folding pathway to redirect mutant promoter G-quadruplex misfolding, partially reinstate the correct folding pathway, and reduce hTERT activity through transcriptional repression. This transcription-mediated repression effects cancer cell death through multiple routes including both induction of apoptosis through inhibition of hTERT's role in regulating apoptosis-related proteins and inducing senescence by decreasing telomerase activity and telomere length.We demonstrate the selective therapeutic potential of this strategy in melanoma cells that overexpress hTERT.3

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

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A Pharmacological Chaperone Molecule Induces Cancer Cell Death by Restoring Tertiary DNA Structures in Mutant hTERT Promoters

et al. 2016

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“…Lastly, it was shown that mutations in the TERT (telomerase reverse transcriptase) promoter are linked to many types of aggressive cancer 41 , mostly by gain-of-function mutations creating ETS family 42,43 or GABP 41 transcription factor binding sites. We analyzed the TERT promoter using DeepBind ETS (ELK1/ELK4) and GABP-α models and the resulting mutation maps all show potential gain-offunction mutations corresponding to the literature.…”

Section: A N a Ly S I Smentioning

confidence: 99%

Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning

et al. 2015

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Knowing the sequence specificities of DNA-and RNA-binding proteins is essential for developing models of the regulatory processes in biological systems and for identifying causal disease variants. Here we show that sequence specificities can be ascertained from experimental data with 'deep learning' techniques, which offer a scalable, flexible and unified computational approach for pattern discovery. Using a diverse array of experimental data and evaluation metrics, we find that deep learning outperforms other state-of-the-art methods, even when training on in vitro data and testing on in vivo data. We call this approach DeepBind and have built a stand-alone software tool that is fully automatic and handles millions of sequences per experiment. Specificities determined by DeepBind are readily visualized as a weighted ensemble of position weight matrices or as a 'mutation map' that indicates how variations affect binding within a specific sequence.DNA-and RNA-binding proteins play a central role in gene regulation, including transcription and alternative splicing. The sequence specificities of a protein are most commonly characterized using position weight matrices 1 (PWMs), which are easy to interpret and can be scanned over a genomic sequence to detect potential binding sites. However, growing evidence indicates that sequence specificities can be more accurately captured by more complex techniques 2-5 . Recently, 'deep learning' has achieved record-breaking performance in a variety of information technology applications 6,7 . We adapted deep learning methods to the task of predicting sequence specificities and found that they compete favorably with the state of the art. Our approach, called DeepBind, is based on deep convolutional neural networks and can discover new patterns even when the locations of patterns within sequences are unknown-a task for which traditional neural networks require an exorbitant amount of training data.There are several challenging aspects in learning models of sequence specificity using modern high-throughput technologies. First, the data come in qualitatively different forms. Protein binding microarrays (PBMs) 8 and RNAcompete assays 9 provide a specificity coefficient for each probe sequence, whereas chromatin immunoprecipitation (ChIP)-seq 10 provides a ranked list of putatively bound sequences of varying length, and HT-SELEX 11 generates a set of very high affinity sequences. Second, the quantity of data is large. A typical high-throughput experiment measures between 10,000 and 100,000 sequences, and it is computationally demanding to incorporate them all. Third, each data acquisition technology has its own artifacts, biases and limitations, and we must discover the pertinent specificities despite these unwanted effects. For example, ChIP-seq reads often localize to "hyper-ChIPable" regions of the genome near highly expressed genes 12 .DeepBind (Fig. 1) addresses the above challenges. (i) It can be applied to both microarray and sequencing data; (ii) it can learn from millions of...

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“…Recent studies identified the presence of hotspot somatic mutations in the promoter region of TERT gene, specifically the −124:C>T and −146:C>T mutations, in a range of human cancers such as bladder, gliomas, thyroid and melanoma [2][3][4][5]. These mutations have been shown to create a new binding motif sites for ETS transcription factors, which induces upregulation of TERT levels [2,5,6]. Recently, the less frequent variant C of the single nucleotide polymorphism (SNP) rs2853669 located −245 bp upstream from the ATG start site of the TERT promoter region has been shown to decrease TERT expression levels in both −124:C>T and −146:C>T mutant cases, apparently introducing a protective effect [7].…”

Section: Introductionmentioning

confidence: 99%

Hotspot TERT promoter mutations are rare events in testicular germ cell tumors

et al. 2015

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The abnormal activation of telomerase, codified by the telomerase reverse transcriptase (TERT) gene, is related to one of cancer hallmarks. Hotspot somatic mutations in the promoter region of TERT, specifically the c.-124:C>T and c.-146:C>T, were recently identified in a range of human cancers and have been associated with a more aggressive behavior. Testicular germ cell tumors frequently exhibit a good prognosis; however, the development of refractory disease is still a clinical challenge. In this study, we aim to evaluate for the first time the presence of the hotspot telomerase reverse transcriptase gene promoter mutations in testicular germ cell tumors. A series of 150 testicular germ cell tumor cases and four germ cell tumor cell lines were evaluated by PCR followed by direct Sanger sequencing and correlated with patient's clinical pathological features. Additionally, we genotyped the telomerase reverse transcriptase gene promoter single nucleotide polymorphism rs2853669 (T>C) located at −245 position. We observed the presence of the TERT promoter mutation in four patients, one exhibited the c.-124:C>T and three the c.-146:C>T. No association between TERT mutation status and clinicopathological features could be identified. The analysis of the rs2853669 showed that variant C was present in 22.8 % of the cases. In conclusion, we showed for the first time that TERT promoter mutations occur in a small subset (~3 %) of testicular germ cell tumors.

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The transcription factor GABP selectively binds and activates the mutant TERT promoter in cancer

Cited by 478 publications

References 44 publications

A Pharmacological Chaperone Molecule Induces Cancer Cell Death by Restoring Tertiary DNA Structures in Mutant hTERT Promoters

A Pharmacological Chaperone Molecule Induces Cancer Cell Death by Restoring Tertiary DNA Structures in Mutant hTERT Promoters

Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning

Hotspot TERT promoter mutations are rare events in testicular germ cell tumors

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