Transcription Factor Binding Events Research Articles

OR35-03 Uncovering Causative Mutations in Polycystic Ovary Syndrome

Abstract Disclosure: J. Srivastava: None. I. Ovcharenko: None. PCOS is a complex disorder manifesting as reproductive and metabolic abnormalities in women. The undefined etiology stems from our incomplete understanding of genetic aberrations contributing to the diseased phenotype. This has resulted in speculations surrounding the cause-consequence relationship between phenotypic features of PCOS and limited our knowledge of comprehensive genetic signatures of PCOS. Pleiotropic effects are salient features of genetic regulation in mammalian genomes. The contribution of a set of regulatory elements (REs) to upregulation of a single gene, or the genetic control of multigene loci by a single RE, give rise to heterogenous phenotypes. Enhancers in particular dictate the spatio-temporal scale of gene expression by controlling transcription factor (TF) binding events. The complex traits of PCOS are suggestive of pleiotropy originating from genetic and epigenetic changes that arise from nucleotide variations in REs of the genome. Genome Wide Association Studies (GWAS) have identified ∼100 risk variants associated with PCOS and implicated the involvement of several genes such as FSHB/R, THADA, DENND1A, etc. However, mechanisms by which they contribute to pathophysiology are unknown. Additionally, twin studies have implicated the heritability of PCOS to be ∼80% and yet, the heritability from GWAS variants accounts for less than 10%. Experimental data may account for the ‘missing heritability problem’ specifically through rare variants that are missed in GWAS. To address this issue, we developed a Deep Learning model of gene regulation in PCOS identifying hundreds of active REs orchestrating the activity of PCOS genes. We also established a foundation for quantifying the impact of single-nucleotide noncoding mutations on TF binding and RE activity. By combining thousands of experimental assays associated with a large number of biological events such as tissue-specific epigenetic maps of the human genome, multi-tissue profiling of TF binding and gene expression using data from high throughput experiments we devised a strategy to accurately identify functionally map causative mutations in the GWAS loci of PCOS genes. MPRA experimental data validates a large fraction of our predicted causative variants thus suggesting that our studies have a potential of a leap forward accurate dissection of genomic and epigenetic mechanisms of PCOS. Consolidated results of this analysis and experimental validation of our predictions will lead to detailing the regulatory mechanisms of PCOS. Presentation Date: Sunday, June 18, 2023

Kinetic networks identify TWIST2 as a key regulatory node in adipogenesis.

Adipocytes contribute to metabolic disorders such as obesity, diabetes, and atherosclerosis. Prior characterizations of the transcriptional network driving adipogenesis have overlooked transiently acting transcription factors (TFs), genes, and regulatory elements that are essential for proper differentiation. Moreover, traditional gene regulatory networks provide neither mechanistic details about individual regulatory element-gene relationships nor temporal information needed to define a regulatory hierarchy that prioritizes key regulatory factors. To address these shortcomings, we integrate kinetic chromatin accessibility (ATAC-seq) and nascent transcription (PRO-seq) data to generate temporally resolved networks that describe TF binding events and resultant effects on target gene expression. Our data indicate which TF families cooperate with and antagonize each other to regulate adipogenesis. Compartment modeling of RNA polymerase density quantifies how individual TFs mechanistically contribute to distinct steps in transcription. The glucocorticoid receptor activates transcription by inducing RNA polymerase pause release, whereas SP and AP-1 factors affect RNA polymerase initiation. We identify Twist2 as a previously unappreciated effector of adipocyte differentiation. We find that TWIST2 acts as a negative regulator of 3T3-L1 and primary preadipocyte differentiation. We confirm that Twist2 knockout mice have compromised lipid storage within subcutaneous and brown adipose tissue. Previous phenotyping of Twist2 knockout mice and Setleis syndrome Twist2 -/- patients noted deficiencies in subcutaneous adipose tissue. This network inference framework is a powerful and general approach for interpreting complex biological phenomena and can be applied to a wide range of cellular processes.

ΔNp63/p73 drive metastatic colonization by controlling a regenerative epithelial stem cell program in quasi-mesenchymal cancer stem cells.

Cancer stem cells (CSCs) may serve as the cellular seeds of tumor recurrence and metastasis, and they can be generated via epithelial-mesenchymal transitions (EMTs). Isolating pure populations of CSCs is difficult because EMT programs generate multiple alternative cell states, and phenotypic plasticity permits frequent interconversions between these states. Here, we used cell-surface expression of integrin β4 (ITGB4) to isolate highly enriched populations of human breast CSCs, and we identified the gene regulatory network operating in ITGB4+ CSCs. Specifically, we identified ΔNp63 and p73, the latter of which transactivates ΔNp63, as centrally important transcriptional regulators of quasi-mesenchymal CSCs that reside in an intermediate EMT state. We found that the transcriptional program controlled by ΔNp63 in CSCs is largely distinct from the one that it orchestrates in normal basal mammary stem cells and, instead, it more closely resembles a regenerative epithelial stem cell response to wounding. Moreover, quasi-mesenchymal CSCs repurpose this program to drive metastatic colonization via autocrine EGFR signaling.

Changes in chromatin accessibility are not concordant with transcriptional changes for single-factor perturbations.

A major goal in the field of transcriptional regulation is the mapping of changes in the binding of transcription factors to the resultant changes in gene expression. Recently, methods for measuring chromatin accessibility have enabled us to measure changes in accessibility across the genome, which are thought to correspond to transcription factor‐binding events. In concert with RNA‐sequencing, these data in principle enable such mappings; however, few studies have looked at their concordance over short‐duration treatments with specific perturbations. Here, we used tandem, bulk ATAC‐seq, and RNA‐seq measurements from MCF‐7 breast carcinoma cells to systematically evaluate the concordance between changes in accessibility and changes in expression in response to retinoic acid and TGF‐β. We found two classes of genes whose expression showed a significant change: those that showed some changes in the accessibility of nearby chromatin, and those that showed virtually no change despite strong changes in expression. The peaks associated with genes in the former group had lower baseline accessibility prior to exposure to signal. Focusing the analysis specifically on peaks with motifs for transcription factors associated with retinoic acid and TGF‐β signaling did not reduce the lack of correspondence. Analysis of paired chromatin accessibility and gene expression data from distinct paths along the hematopoietic differentiation trajectory showed a much stronger correspondence, suggesting that the multifactorial biological processes associated with differentiation may lead to changes in chromatin accessibility that reflect rather than driving altered transcriptional status. Together, these results show many gene expression changes can happen independently of changes in the accessibility of local chromatin in the context of a single‐factor perturbation.

Single-cell chromatin profiling of the primitive gut tube reveals regulatory dynamics underlying lineage fate decisions

Development of the gastrointestinal system occurs after gut tube closure, guided by spatial and temporal control of gene expression. However, it remains unclear what forces regulate these spatiotemporal gene expression patterns. Here we perform single-cell chromatin profiling of the primitive gut tube to reveal organ-specific chromatin patterns that reflect the anatomical patterns of distinct organs. We generate a comprehensive map of epigenomic changes throughout gut development, demonstrating that dynamic chromatin accessibility patterns associate with lineage-specific transcription factor binding events to regulate organ-specific gene expression. Additionally, we show that loss of Sox2 and Cdx2, foregut and hindgut lineage-specific transcription factors, respectively, leads to fate shifts in epigenomic patterns, linking transcription factor binding, chromatin accessibility, and lineage fate decisions in gut development. Notably, abnormal expression of Sox2 in the pancreas and intestine impairs lineage fate decisions in both development and adult homeostasis. Together, our findings define the chromatin and transcriptional mechanisms of organ identity and lineage plasticity in development and adult homeostasis.

Epigenetic reorganization during early embryonic lineage specification.

Dynamic chromatin reorganization occurs during two waves of cell lineage specification process, blastocyst formation and gastrulation, to generate distinct cell types. Epigenetic defects have been associated with severe developmental defects and diseases. How epigenetic remodeling coordinates the two lineage specification waves is becoming uncovered, benefiting from the development and application of new technologies including low-input or single-cell epigenome analysis approached in the past few years. In this review, we aim to highlight the most recent findings on epigenetic remodeling in cell lineage specification during blastocyst formation and gastrulation. First, we introduce how DNA methylation dynamically changes in blastocyst formation and gastrulation and its function in transcriptional regulation lineage-specific genes. Then, we discuss widespread remodeling of histone modification at promoters and enhancers in orchestrating the trajectory of cell lineage specification. Finally, we review dynamics of chromatin accessibility and 3D structure regulating developmental gene expression and associating with specific transcription factor binding events at stage specific manner. We also highlight the key questions that remain to be answered to fully understand chromatin regulation and reorganization in lineage specification. Here, we summarize the recent advances and discoveries on epigenetic reorganization and its roles in blastocyst formation and gastrulation, and how it cooperates with the lineage specification, painting from global sequencing data from mouse in vivo tissues.

Constructing gene regulatory networks using epigenetic data

The biological processes that drive cellular function can be represented by a complex network of interactions between regulators (transcription factors) and their targets (genes). A cell’s epigenetic state plays an important role in mediating these interactions, primarily by influencing chromatin accessibility. However, how to effectively use epigenetic data when constructing a gene regulatory network remains an open question. Almost all existing network reconstruction approaches focus on estimating transcription factor to gene connections using transcriptomic data. In contrast, computational approaches for analyzing epigenetic data generally focus on improving transcription factor binding site predictions rather than deducing regulatory network relationships. We bridged this gap by developing SPIDER, a network reconstruction approach that incorporates epigenetic data into a message-passing framework to estimate gene regulatory networks. We validated SPIDER’s predictions using ChIP-seq data from ENCODE and found that SPIDER networks are both highly accurate and include cell-line-specific regulatory interactions. Notably, SPIDER can recover ChIP-seq verified transcription factor binding events in the regulatory regions of genes that do not have a corresponding sequence motif. The networks estimated by SPIDER have the potential to identify novel hypotheses that will allow us to better characterize cell-type and phenotype specific regulatory mechanisms.

Chromatin Accessibility Landscapes of Acute Lymphoblastic Leukemia

Acute lymphoblastic leukemia (ALL) is the most common malignancy in pediatric patients spanning both B- and T-cell lineages. ALL also occurs less commonly in adults but with cure rates of only around 30%. Past work has characterized ALL into molecular subtypes spanning a range of aberrant chromosomal rearrangements and oncogene chimeric fusions driving malignancy. While transcriptional profiling of these subtypes has been extensively examined, the accompanying chromatin accessibility landscape and corresponding gene regulatory repertoire is not well characterized for many subtypes. To better profile the ALL epigenomic and gene regulatory repertoire we examined chromatin accessibility of 12 distinct molecular subtypes (BCR-ABL1, ETV6-RUNX1, Hyperdiploid, Hypodiploid, KMT2A rearranged, Ph-Like, PAX5, DUX4/ERG, TCF3-PBX1, T-ALL, Early T Precursor and B-other) across 189 primary patient samples of pediatric ALL (n = 106) and adult ALL (n = 83) origin using ATAC-seq. To our knowledge, this represents the largest collection of chromatin accessibility data in primary ALL samples spanning multiple molecular subtypes to date. Collectively, we identified over 600,000 accessible chromatin sites in the ALL genome with over 50,000 regions of differentially accessible chromatin encompassing both common and subtype-specific modalities. Further, transcription factor (TF) footprint profiling of ATAC-seq yielded tens of thousands of candidate TF binding events and identified key TF drivers within distinct molecular subtypes. We additionally performed H3K27ac ChIP-seq in a subset of 12 primary ALL patient samples, with integration of these histone data for select patient samples allowing inferences about candidate super-enhancer drivers of ALL molecular subtypes. Overall, these analyses and data offer a window into the gene regulatory and epigenetic landscape of ALL, and further highlight the complexity and heterogeneity of accessible chromatin landscapes among distinct molecular subtypes of ALL. DisclosuresStock: Pfizer: Consultancy, Honoraria, Research Funding; amgen: Honoraria; agios: Honoraria; jazz: Honoraria; kura: Honoraria; kite: Honoraria; morphosys: Honoraria; servier: Honoraria; syndax: Consultancy, Honoraria; Pluristeem: Consultancy, Honoraria. Pui: Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; Novartis: Other: Data Monitoring Committee. Evans: Princess Máxima Center for Pediatric Oncology, Scientific Advisory Board, Chair: Membership on an entity's Board of Directors or advisory committees; St. Jude Children's Research Hospital, Emeritus Member (began Jan 2021): Ended employment in the past 24 months; BioSkryb, Inc.: Membership on an entity's Board of Directors or advisory committees.

A KMT2A-AFF1 gene regulatory network highlights the role of core transcription factors and reveals the regulatory logic of key downstream target genes.

Regulatory interactions mediated by transcription factors (TFs) make up complex networks that control cellular behavior. Fully understanding these gene regulatory networks (GRNs) offers greater insight into the consequences of disease-causing perturbations than can be achieved by studying single TF binding events in isolation. Chromosomal translocations of the lysine methyltransferase 2A (KMT2A) gene produce KMT2A fusion proteins such as KMT2A-AFF1 (previously MLL-AF4), causing poor prognosis acute lymphoblastic leukemias (ALLs) that sometimes relapse as acute myeloid leukemias (AMLs). KMT2A-AFF1 drives leukemogenesis through direct binding and inducing the aberrant overexpression of key genes, such as the anti-apoptotic factor BCL2 and the proto-oncogene MYC. However, studying direct binding alone does not incorporate possible network-generated regulatory outputs, including the indirect induction of gene repression. To better understand the KMT2A-AFF1-driven regulatory landscape, we integrated ChIP-seq, patient RNA-seq, and CRISPR essentiality screens to generate a model GRN. This GRN identified several key transcription factors such as RUNX1 that regulate target genes downstream of KMT2A-AFF1 using feed-forward loop (FFL) and cascade motifs. A core set of nodes are present in both ALL and AML, and CRISPR screening revealed several factors that help mediate response to the drug venetoclax. Using our GRN, we then identified a KMT2A-AFF1:RUNX1 cascade that represses CASP9, as well as KMT2A-AFF1-driven FFLs that regulate BCL2 and MYC through combinatorial TF activity. This illustrates how our GRN can be used to better connect KMT2A-AFF1 behavior to downstream pathways that contribute to leukemogenesis, and potentially predict shifts in gene expression that mediate drug response.

Landscape of allele-specific transcription factor binding in the human genome

Sequence variants in gene regulatory regions alter gene expression and contribute to phenotypes of individual cells and the whole organism, including disease susceptibility and progression. Single-nucleotide variants in enhancers or promoters may affect gene transcription by altering transcription factor binding sites. Differential transcription factor binding in heterozygous genomic loci provides a natural source of information on such regulatory variants. We present a novel approach to call the allele-specific transcription factor binding events at single-nucleotide variants in ChIP-Seq data, taking into account the joint contribution of aneuploidy and local copy number variation, that is estimated directly from variant calls. We have conducted a meta-analysis of more than 7 thousand ChIP-Seq experiments and assembled the database of allele-specific binding events listing more than half a million entries at nearly 270 thousand single-nucleotide polymorphisms for several hundred human transcription factors and cell types. These polymorphisms are enriched for associations with phenotypes of medical relevance and often overlap eQTLs, making candidates for causality by linking variants with molecular mechanisms. Specifically, there is a special class of switching sites, where different transcription factors preferably bind alternative alleles, thus revealing allele-specific rewiring of molecular circuitry.

ChIP-R: Assembling reproducible sets of ChIP-seq and ATAC-seq peaks from multiple replicates

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is the primary protocol for detecting genome-wide DNA-protein interactions, and therefore a key tool for understanding transcriptional regulation. A number of factors, including low specificity of antibody and cellular heterogeneity of sample, may cause “peak” callers to output noise and experimental artefacts. Statistically combining multiple experimental replicates from the same condition could significantly enhance our ability to distinguish actual transcription factor binding events, even when peak caller accuracy and consistency of detection are compromised.We adapted the rank-product test to statistically evaluate the reproducibility from any number of ChIP-seq experimental replicates. We demonstrate over a number of benchmarks that our adaptation “ChIP-R" (pronounced ‘chipper’) performs as well as or better than comparable approaches on recovering transcription factor binding sites in ChIP-seq peak data. We also show ChIP-R extends to evaluate ATAC-seq peaks, finding reproducible peak sets even at low sequencing depth. ChIP-R decomposes peaks across replicates into “fragments” which either form part of a peak in a replicate, or not. We show that by re-analysing existing data sets, ChIP-R reconstructs reproducible peaks from fragments with enhanced biological enrichment relative to current strategies.

Direct Quantification of Gene Regulation by Transcription-Factor Binding at an Endogenous Gene Locus

Gene activity is controlled by the binding of transcription factors (TFs) to the regulatory sequence of the gene, yet a direct in situ mapping from TF binding to mRNA production of a single gene remains elusive, due to the difficulty of capturing individual TF binding events for a specific gene from the ocean of TF signal in the cell nucleus. Here we combine single-molecule fluorescent imaging of protein, mRNA, and gene loci to detect and quantify distinct binding configurations of multiple TFs and epigenetically modified histones, as well as the resulting nascent mRNAs at endogenous hunchback (hb) gene loci in early Drosophila embryos. Using stochastic theoretical analysis, we show that TF binding follows nonequilibrium multi-state kinetics, breaking the law of mass action. hb transcription activation is a multi-step process initiated by transient binding of the Bicoid transcription factor. Unlike TF binding at hb, the histone signal is deprived at active gene loci, indicating that nucleosome unwinding is necessary for gene activation. Our method provides a general framework to decipher the dynamics of complex gene regulatory networks in situ.

Chromatin dynamics: Nucleosome occupancy and sensitivity as determinants of gene expression and cell fate.

The nucleosome, consisting of ~150bp of DNA wrapped around a core histone octamer, is a regulator of nuclear events that contributes to gene expression and cell fate. Nucleosome organization at promoters and their associated remodeling events are important regulators of access to the genome. Occupancy alone, however, is not the only nucleosomal characteristic that plays a role in genome regulation. Nucleosomes at the transcription start sites (TSSs) of genes show differential sensitivity to micrococcal nuclease (MNase) and this differential sensitivity is linked to transcription and regulatory factor binding events. Recently, lymphoblastoid cells treated with heat-killed Salmonella typhimurium were shown to exhibit increased MNase sensitivity specifically at genes implicated in immune responses. Increased sensitivity at the −1-nucleosome permitted transcription factor and RNA Pol II binding events. This system illustrates how cytoplasmic signals induce altered chromatin states to produce a specific cellular response to a stimulus. Innate immune activation is a longstanding model for inducible promoters, transcriptional activation, and differential nucleosomal sensitivity in response to immune activation and offers a model that may be largely applicable to other specific cellular responses including viral infection and cancer. Previous work has shown that early transformation events are associated with prolonged nucleosome occupancy changes that are not observed later in cancer progression. Herein, we propose a model in which we suggest that detailed studies of nucleosomal occupancy and sensitivity in response to specific stimuli will provide insight into the regulation of nuclear events in cancer and other biological processes.

Abstract 2478: Assessing regulatory network rewiring in cancer patients using chromatin accessibility profiles

Abstract The regulation of gene expression in humans is the result of a complex interplay between DNA, small RNA molecules and a multitude of proteins, particularly histones and transcription factors (TFs). To identify the key TFs regulating gene expression in cancer we are integrating ATAC-Seq data from 371 TCGA patients in conjunction with matching expression data and DNA-binding motifs for 780 TFs and TF families. We infer the regulatory networks in these patients by detecting true TF binding events in individual patients and the regulatory elements that said TFs are bound to using the Protein Interaction Quantification algorithm (PIQ). The inferred networks were then clustered by the similarity of inferred TF binding activity followed by identification of the TFs most likely driving the identity of each cluster. We observe robust clustering by site of origin of disease with canonical TFs such as FOXA1 and ESR1 being putative key TFs in ER+ breast cancer, PAX8 in renal cancer as well as TP63 and SOX2 in multiple squamous cell cancers. To validate these putative super-TFs, we used gene essentiality data from CRISPR-mediated knockout experiments of 18K genes in 625 well characterized cell lines performed by the Broad Institute. We observe statistically significant differences in the essentiality of putative super-TFs in cell lines matching the disease types of clusters. Citation Format: Andre Forbes, Duo Xu, Ekta K. Khurana. Assessing regulatory network rewiring in cancer patients using chromatin accessibility profiles [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2478.

Prediction of transcription factors binding events based on epigenetic modifications in different human cells.

Aim: We aim to predict transcription factor (TF) binding events from knowledge of gene expression and epigenetic modifications. Materials & methods: TF-binding events based on the Encode project and The Cancer Genome Atlas data were analyzed by the random forest method. Results: We showed the high performance of TF-binding predictive models in GM12878, HeLa, HepG2 and K562 cell lines and applied them to other cell lines and tissues. The genes bound by the top TFs (MAX and MAZ) were significantly associated with cancer-related processes such as cell proliferation and DNA repair. Conclusion: We successfully constructed TF-binding predictive models in cell lines and applied them in tissues.

An OCT2 / OCA-B / MEF2B Ternary Complex Controls the Activity and Architecture of an Essential Locus Control Region for Normal and Malignant Germinal Center B-Cells

Melnick: Epizyme: Consultancy; Constellation: Consultancy; Janssen: Research Funding.

Predicting functional variants in enhancer and promoter elements using RegulomeDB.

Here we present a computational model, Score of Unified Regulatory Features (SURF), that predicts functional variants in enhancer and promoter elements. SURF is trained on data from massively parallel reporter assays and predicts the effect of variants on reporter expression levels. It achieved the top performance in the Fifth Critical Assessment of Genome Interpretation "Regulation Saturation" challenge. We also show that features queried through RegulomeDB, which are direct annotations from functional genomics data, help improve prediction accuracy beyond transfer learning features from DNA sequence-based deep learning models. Some of the most important features include DNase footprints, especially when coupled with complementary ChIP-seq data. Furthermore, we found our model achieved good performance in predicting allele-specific transcription factor binding events. As an extension to the current scoring system in RegulomeDB, we expect our computational model to prioritize variants in regulatory regions, thus help the understanding of functional variants in noncoding regions that lead to disease.

Enrichment of Genomic Pathways Based on Differential DNA Methylation Associated With Chronic Postsurgical Pain and Anxiety in Children: A Prospective, Pilot Study

We have reported child anxiety sensitivity (Child Anxiety Sensitivity Index [CASI]) predicts chronic postsurgical pain (CPSP). Herein, we evaluated DNA methylation profiles to understand the gene–environment interactions underlying CPSP and CASI, to identify shared, enriched, genomic pathways. In 73 prospectively recruited adolescents undergoing spine fusion, preoperative CASI and pain data over 12 months after surgery were collected. DNA from the peripheral blood of evaluable subjects with (n = 16) and without CPSP (n = 40) were analyzed using MethylationEPIC arrays. We identified 637 and 2,445 differentially DNA methylated positions (DMPs) associated with CPSP and CASI, respectively (P ≤ .05). Ingenuity pathway analysis of 39 genes with DMPs for both CPSP and CASI revealed enrichment of several canonical pathways, including GABA receptor (P = .00016 for CPSP; P =.0008 for CASI) and dopamine-DARPP32 feedback in cyclic adenosine monophosphate (P = .004 for CPSP and P =.00003 for CASI) signaling. Gene–gene interaction network enrichment analysis revealed participation of pathways in cell signaling, molecular transport, metabolism, and neurologic diseases (P < 10-8). Bioinformatic approaches to identify histone marks and transcription factor (TF) binding events underlying DMPs, showed their location in active regulatory regions in pain pathway relevant brain cells. Using Enrichr/Pinet enrichment and Library of Integrated Network-Based Cellular Signatures knockdown signatures, we identified TFs regulating genes with DMPs in association with CPSP and CASI. In conclusion, we identified epigenetically enriched pathways associated with CPSP and anxiety sensitivity in children undergoing surgery. Our findings support GABA hypofunction and the roles of the dopamine–DARPP32 pathway in emotion/reward and pain. This pilot study provides new epigenetic insights into the pathophysiology of CPSP and a basis for future studies in biomarker development and targetable interventions. PerspectiveDifferential DNA methylation in regulatory genomic regions enriching shared neural pathways were associated with CPSP and CASI in adolescents undergoing spine surgery. Our findings support GABA hypofunction and the roles of the dopamine–DARPP32 pathway in emotion/reward contributing to behavioral maintenance of pain 10 to 12 months after surgery.

Identification of miR-29c and its Target FBXO31 as a Key Regulatory Mechanism in Esophageal Cancer Chemoresistance: Functional Validation and Clinical Significance.

Rationale: Dysregulated microRNA (miRNA) expressions in cancer can contribute to chemoresistance. This study aims to identify miRNAs that are associated with fluorouracil (5-FU) chemoresistance in esophageal squamous cell carcinoma (ESCC). The potential of miR-29c as a novel diagnostic, prognostic and treatment-predictive marker in ESCC, and its mechanisms and therapeutic implication in overcoming 5-FU chemoresistance were explored.Methods: The miRNA profiles of an ESCC cell model with acquired chemoresistance to 5-FU were analyzed using a Taqman miRNA microarray to identify novel miRNAs associated with 5-FU chemoresistance. Quantitative real-time PCR was used to determine miR-29c expression in tissue and serum samples of patients. Bioinformatics, gain- and loss-of-function experiments, and luciferase reporter assay were performed to validate F-box only protein 31 (FBXO31) as a direct target of miR-29c, and to identify potential transcription factor binding events that control miR-29c expression. The potential of systemic miR-29c oligonucleotide-based therapy in overcoming 5-FU chemoresistance was evaluated in tumor xenograft model.Results: MiR-29c, under the regulatory control of STAT5A, was frequently downregulated in tumor and serum samples of patients with ESCC, and the expression level was correlated with overall survival. Functional studies showed that miR-29c could override 5-FU chemoresistance in vitro and in vivo by directly interacting with the 3'UTR of FBXO31, leading to repression of FBXO31 expression and downstream activation of p38 MAPK. Systemically administered miR-29c dramatically improved response of 5-FU chemoresistant ESCC xenografts in vivo.Conclusions: MiR-29c modulates chemoresistance by interacting with FBXO31, and is a promising non-invasive biomarker and therapeutic target in ESCC.

Gene expression models based on transcription factor binding events confer insight into functional cis-regulatory variants.

MotivationDeciphering the functional roles of cis-regulatory variants is a critical challenge in genome analysis and interpretation. It has been hypothesized that altered transcription factor (TF) binding events are a central mechanism by which cis-regulatory variants impact gene expression levels. However, we lack a computational framework to understand and quantify such mechanistic contributions.ResultsWe present TF2Exp, a gene-based framework to predict the impact of altered TF-binding events on gene expression levels. Using data from lymphoblastoid cell lines, TF2Exp models were applied successfully to predict the expression levels of 3196 genes. Alterations within DNase I hypersensitive, CTCF-bound and tissue-specific TF-bound regions were the greatest contributing features to the models. TF2Exp models performed as well as models based on common variants, both in cross-validation and external validation. Combining TF alteration and common variant features can further improve model performance. Unlike variant-based models, TF2Exp models have the unique advantage to evaluate the functional impact of variants in linkage disequilibrium and uncommon variants. We find that adding TF-binding events altered only by uncommon variants could increase the number of predictable genes (R2 > 0.05). Taken together, TF2Exp represents a key step towards interpreting the functional roles of cis-regulatory variants in the human genome.Availability and implementationThe code and model training results are publicly available at https://github.com/wqshi/TF2Exp.Supplementary information Supplementary data are available at Bioinformatics online.