H. Tomas Rube

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

A mutant promoters partner in crime Telomerase is an enzyme that maintains the ends of chromosomes. TERT, the gene coding for the enzymes catalytic subunit, is not expressed in healthy somatic cells, but its expression is reactivated in the majority of human cancers. The resultant high levels of telomerase help cancer cells survive and multiply. Recurrent mutations in the promoter region of TERT are associated with high telomerase levels in multiple cancer types. Bell et al. show that a specific transcription factor called GABP is selectively recruited to the mutant form of the TERT promoter, which activates TERT gene expression Science, this issue p. 1036 Cancer-associated mutations in the promoter of the telomerase gene allow increased activation by transcription factor binding. Reactivation of telomerase reverse transcriptase (TERT) expression enables cells to overcome replicative senescence and escape apoptosis, which are fundamental steps in the initiation of human cancer. Multiple cancer types, including up to 83% of glioblastomas (GBMs), harbor highly recurrent TERT promoter mutations of unknown function but specific to two nucleotide positions. We identified the functional consequence of these mutations in GBMs to be recruitment of the multimeric GA-binding protein (GABP) transcription factor specifically to the mutant promoter. Allelic recruitment of GABP is consistently observed across four cancer types, highlighting a shared mechanism underlying TERT reactivation. Tandem flanking native E26 transformation-specific motifs critically cooperate with these mutations to activate TERT, probably by facilitating GABP heterotetramer binding. GABP thus directly links TERT promoter mutations to aberrant expression in multiple cancers.

Understanding TERT Promoter Mutations: A Common Path to Immortality.

Telomerase (TERT) activation is a fundamental step in tumorigenesis. By maintaining telomere length, telomerase relieves a main barrier on cellular lifespan, enabling limitless proliferation driven by oncogenes. The recently discovered, highly recurrent mutations in the promoter of TERT are found in over 50 cancer types, and are the most common mutation in many cancers. Transcriptional activation of TERT, via promoter mutation or other mechanisms, is the rate-limiting step in production of active telomerase. Although TERT is expressed in stem cells, it is naturally silenced upon differentiation. Thus, the presence of TERT promoter mutations may shed light on whether a particular tumor arose from a stem cell or more differentiated cell type. It is becoming clear that TERT mutations occur early during cellular transformation, and activate the TERT promoter by recruiting transcription factors that do not normally regulate TERT gene expression. This review highlights the fundamental and widespread role of TERT promoter mutations in tumorigenesis, including recent progress on their mechanism of transcriptional activation. These somatic promoter mutations, along with germline variation in the TERT locus also appear to have significant value as biomarkers of patient outcome. Understanding the precise molecular mechanism of TERT activation by promoter mutation and germline variation may inspire novel cancer cell-specific targeted therapies for a large number of cancer patients. Mol Cancer Res; 14(4); 315–23. ©2016 AACR.

Sequence features accurately predict genome-wide MeCP2 binding in vivo

Methyl-CpG binding protein 2 (MeCP2) is critical for proper brain development and expressed at near-histone levels in neurons, but the mechanism of its genomic localization remains poorly understood. Using high-resolution MeCP2-binding data, we show that DNA sequence features alone can predict binding with 88% accuracy. Integrating MeCP2 binding and DNA methylation in a probabilistic graphical model, we demonstrate that previously reported genome-wide association with methylation is in part due to MeCP2s affinity to GC-rich chromatin, a result replicated using published data. Furthermore, MeCP2 co-localizes with nucleosomes. Finally, MeCP2 binding downstream of promoters correlates with increased expression in Mecp2-deficient neurons.

Quantitative analysis and prediction of G-quadruplex forming sequences in double-stranded DNA

Abstract G-quadruplex (GQ) is a four-stranded DNA structure that can be formed in guanine-rich sequences. GQ structures have been proposed to regulate diverse biological processes including transcription, replication, translation and telomere maintenance. Recent studies have demonstrated the existence of GQ DNA in live mammalian cells and a significant number of potential GQ forming sequences in the human genome. We present a systematic and quantitative analysis of GQ folding propensity on a large set of 438 GQ forming sequences in double-stranded DNA by integrating fluorescence measurement, single-molecule imaging and computational modeling. We find that short minimum loop length and the thymine base are two main factors that lead to high GQ folding propensity. Linear and Gaussian process regression models further validate that the GQ folding potential can be predicted with high accuracy based on the loop length distribution and the nucleotide content of the loop sequences. Our study provides important new parameters that can inform the evaluation and classification of putative GQ sequences in the human genome.

Quantifying the role of steric constraints in nucleosome positioning

Statistical positioning, the localization of nucleosomes packed against a fixed barrier, is conjectured to explain the array of well-positioned nucleosomes at the 5′ end of genes, but the extent and precise implications of statistical positioning in vivo are unclear. We examine this hypothesis quantitatively and generalize the idea to include moving barriers as well as nucleosomes actively packed against a barrier. Early experiments noted a similarity between the nucleosome profile aligned and averaged across genes and that predicted by statistical positioning; however, we demonstrate that aligning random nucleosomes also generates the same profile, calling the previous interpretation into question. New rigorous results reformulate statistical positioning as predictions on the variance structure of nucleosome locations in individual genes. In particular, a quantity termed the variance gradient, describing the change in variance between adjacent nucleosomes, is tested against recent high-throughput nucleosome sequencing data. Constant variance gradients provide support for generalized statistical positioning in ∼50% of long genes. Genes that deviate from predictions have high nucleosome turnover and cell-to-cell gene expression variability. The observed variance gradient suggests an effective nucleosome size of 158 bp, instead of the commonly perceived 147 bp. Our analyses thus clarify the role of statistical positioning in vivo.

Categorical spectral analysis of periodicity in nucleosomal DNA

DNA helical twist imposes geometric constraints on the location of histone–DNA interaction sites along nucleosomal DNA. Certain 10.5-bp periodic nucleotides in phase with these geometric constraints have been suggested to facilitate nucleosome positioning. However, the extent of nucleotide periodicity in nucleosomal DNA and its significance in directing nucleosome positioning still remain unclear. We clarify these issues by applying categorical spectral analysis to high-resolution nucleosome maps in two yeast species. We find that only a small fraction of nucleosomal sequences contain significant 10.5-bp periodicity. We further develop a spectral decomposition method to show that the previously observed periodicity in aligned nucleosomal sequences mainly results from proper phasing among nucleosomal sequences, and not from a preponderant occurrence of periodicity within individual sequences. Importantly, we show that this phasing may arise from the histones’ proclivity for putting preferred nucleotides at some of the evenly spaced histone–DNA contact points with respect to the dyad axis. We demonstrate that 10.5-bp periodicity, when present, significantly facilitates rotational, but not translational, nucleosome positioning. Finally, although periodicity only moderately affects nucleosome occupancy genome wide, reduced periodicity is an evolutionarily conserved signature of nucleosome-depleted regions around transcription start/termination sites.

SelexGLM differentiates androgen and glucocorticoid receptor DNA-binding preference over an extended binding site

The DNA-binding interfaces of the androgen (AR) and glucocorticoid (GR) receptors are virtually identical, yet these transcription factors share only about a third of their genomic binding sites and regulate similarly distinct sets of target genes. To address this paradox, we determined the intrinsic specificities of the AR and GR DNA-binding domains using a refined version of SELEX-seq. We developed an algorithm, SelexGLM, that quantifies binding specificity over a large (31-bp) binding site by iteratively fitting a feature-based generalized linear model to SELEX probe counts. This analysis revealed that the DNA-binding preferences of AR and GR homodimers differ significantly, both within and outside the 15-bp core binding site. The relative preference between the two factors can be tuned over a wide range by changing the DNA sequence, with AR more sensitive to sequence changes than GR. The specificity of AR extends to the regions flanking the core 15-bp site, where isothermal calorimetry measurements reveal that affinity is augmented by enthalpy-driven readout of poly(A) sequences associated with narrowed minor groove width. We conclude that the increased specificity of AR is correlated with more enthalpy-driven binding than GR. The binding models help explain differences in AR and GR genomic binding and provide a biophysical rationale for how promiscuous binding by GR allows functional substitution for AR in some castration-resistant prostate cancers.

Accurate and Sensitive Quantification of Protein-DNA Binding Affinity

Significance One-tenth of human genes produce proteins called transcription factors (TFs) that bind to our genome and read the local DNA sequence. They work together to regulate the degree to which each gene is expressed. The affinity with which DNA is bound by a particular TF can vary more than a thousand-fold with different DNA sequences. This study presents the first computational method able to quantify the sequence-affinity relationship almost perfectly over the full affinity range. It achieves this by analyzing data from experiments that use massively parallel DNA sequencing to comprehensively probe protein–DNA interactions. Strikingly, it can accurately predict the effect in vivo of DNA mutations on gene expression levels in fly embryos even for very-low-affinity binding sites. Transcription factors (TFs) control gene expression by binding to genomic DNA in a sequence-specific manner. Mutations in TF binding sites are increasingly found to be associated with human disease, yet we currently lack robust methods to predict these sites. Here, we developed a versatile maximum likelihood framework named No Read Left Behind (NRLB) that infers a biophysical model of protein-DNA recognition across the full affinity range from a library of in vitro selected DNA binding sites. NRLB predicts human Max homodimer binding in near-perfect agreement with existing low-throughput measurements. It can capture the specificity of the p53 tetramer and distinguish multiple binding modes within a single sample. Additionally, we confirm that newly identified low-affinity enhancer binding sites are functional in vivo, and that their contribution to gene expression matches their predicted affinity. Our results establish a powerful paradigm for identifying protein binding sites and interpreting gene regulatory sequences in eukaryotic genomes.

A unified approach for quantifying and interpreting DNA shape readout by transcription factors

Transcription factors (TFs) interpret DNA sequence by probing the chemical and structural properties of the nucleotide polymer. DNA shape is thought to enable a parsimonious representation of dependencies between nucleotide positions. Here, we propose a unified mathematical representation of the DNA sequence dependence of shape and TF binding, respectively, which simplifies and enhances analysis of shape readout. First, we demonstrate that linear models based on mononucleotide features alone account for 60–70% of the variance in minor groove width, roll, helix twist, and propeller twist. This explains why simple scoring matrices that ignore all dependencies between nucleotide positions can partially account for DNA shape readout by a TF. Adding dinucleotide features as sequence‐to‐shape predictors to our model, we can almost perfectly explain the shape parameters. Building on this observation, we developed a post hoc analysis method that can be used to analyze any mechanism‐agnostic protein–DNA binding model in terms of shape readout. Our insights provide an alternative strategy for using DNA shape information to enhance our understanding of how cis‐regulatory codes are interpreted by the cellular machinery.

Abstract B12: GABP selectively binds and activates the mutant TERT promoter across multiple cancer types

Reactivation of telomerase reverse transcriptase (TERT) expression enables cells to overcome replicative senescence and escape apoptosis, fundamental steps in the initiation of human cancer. Multiple cancer types, including up to 83% of glioblastomas (GBM), harbor highly recurrent mutations in the TERT promoter specific to two nucleotide positions. The common mutation sites, G228A and G250A, may create de-novo ETS family transcription factor binding sites, but the precise mechanism of how these mutations confer increased TERT expression has been elusive. Here, we demonstrate the de-novo ETS motif to be critical for mutant TERT activation by site directed mutagenesis. A focused siRNA screen of the many ETS transcription factors expressed in GBM identifies GABPA as the single ETS factor to selectively regulate the mutant but not the wild type TERT promoter. Single molecule binding assays and ChIP-qPCR analysis reveal that GABPA is exclusively recruited to the mutant allele in vitro and in vivo respectively. Furthermore, this allelic recruitment is consistent across four tested cancer types, highlighting a shared mechanism underlying mutant TERT promoter activation. Tandem flanking native ETS motifs critically cooperate with these mutations to activate TERT, likely by facilitating GABP heterotetramer binding. GABP thus directly links TERT promoter mutations to aberrant expression and may provide a novel therapeutic target for multiple cancers. Citation Format: Robert J.A Bell, H. Tomas Rube, Alex Kreig, Andrew Mancini, Shaun F. Fouse, Raman P. Nagarajan, Serah Choi, Chibo Hong, Daniel He, Melike Pekmezci, John K. Wiencke, Margaret R. Wrensch, Susan M. Chang, Kyle M. Walsh, Sua Myong, Jun S. Song, Joseph F. Costello. GABP selectively binds and activates the mutant TERT promoter across multiple cancer types. [abstract]. In: Proceedings of the AACR Special Conference: Advances in Brain Cancer Research; May 27-30, 2015; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2015;75(23 Suppl):Abstract nr B12.