No driver behind the wheel? Targeting transcription in cancer.

Exploiting the dependence of cancer cells on transcription can be used as an effective strategy for targeting aggressive and therapeutically recalcitrant tumors. Wang et al. show that inhibiting transcription using THZ1, a small-molecule inhibitor of cyclin-dependent kinase CDK7, induces apoptotic cell death in triple-negative breast cancers.

A multi-omic single-cell landscape of human gynecologic malignancies.

Deconvolution of regulatory mechanisms that drive transcriptional programs in cancer cells is key to understanding tumor biology. Herein, we present matched transcriptome (scRNA-seq) and chromatin accessibility (scATAC-seq) profiles at single-cell resolution from human ovarian and endometrial tumors processed immediately following surgical resection. This dataset reveals the complex cellular heterogeneity of these tumors and enabled us to quantitatively link variation in chromatin accessibility to gene expression. We show that malignant cells acquire previously unannotated regulatory elements to drive hallmark cancer pathways. Moreover, malignant cells from within the same patients show substantial variation in chromatin accessibility linked to transcriptional output, highlighting the importance of intratumoral heterogeneity. Finally, we infer the malignant cell type-specific activity of transcription factors. By defining the regulatory logic of cancer cells, this work reveals an important reliance on oncogenic regulatory elements and highlights the ability of matched scRNA-seq/scATAC-seq to uncover clinically relevant mechanisms of tumorigenesis in gynecologic cancers.

TNFα signaling exposes latent estrogen receptor binding sites to alter the breast cancer cell transcriptome.

The interplay between mitogenic and proinflammatory signaling pathways plays key roles in determining the phenotypes and clinical outcomes of breast cancers. Using GRO-seq in MCF-7 cells, we defined the immediate transcriptional effects of crosstalk between estradiol (E2) and TNFα, identifying a large set of target genes whose expression is rapidly altered with combined E2 + TNFα treatment, but not with either agent alone. The pleiotropic effects on gene transcription in response to E2 + TNFα are orchestrated by extensive remodeling of the ERα enhancer landscape in an NF-κB- and FoxA1-dependent manner. In addition, expression of the de novo and synergistically regulated genes is strongly associated with clinical outcomes in breast cancers. Together, our genomic and molecular analyses indicate that TNFα signaling, acting in pathways culminating in the redistribution of NF-κB and FoxA1 binding sites across the genome, creates latent ERα binding sites that underlie altered patterns of gene expression and clinically relevant cellular responses.

Single-Cell Transcriptional and Epigenetic Profiles of Male Breast Cancer Nominate Salient Cancer-Specific Enhancers.

Male breast cancer represents about 1% of all breast cancer diagnoses and, although there are some similarities between male and female breast cancer, the paucity of data available on male breast cancer makes it difficult to establish targeted therapies. To date, most male breast cancers (MBCs) are treated according to protocols established for female breast cancer (FBC). Thus, defining the transcriptional and epigenetic landscape of MBC with improved resolution is critical for developing better avenues for therapeutic intervention. In this study, we present matched transcriptional (scRNA-seq) and epigenetic (scATAC-seq) profiles at single-cell resolution of two treatment naïve MBC tumors processed immediately after surgical resection. These data enable the detection of differentially expressed genes between male and female breast tumors across immune, stromal, and malignant cell types, to highlight several genes that may have therapeutic implications. Notably, MYC target genes and mTORC1 signaling genes were significantly upregulated in the malignant cells of MBC compared to the female counterparts. To understand how the regulatory landscape of MBC gives rise to these male-specific gene expression patterns, we leveraged the scATAC-seq data to systematically link changes in chromatin accessibility to changes in gene expression within each cell type. We observed cancer-specific rewiring of several salient enhancers and posit that these enhancers have a higher regulatory load than lineage-specific enhancers. We highlight two examples of previously unannotated cancer-cell-specific enhancers of ANXA2 and PRDX4 gene expression and show evidence for super-enhancer regulation of LAMB3 and CD47 in male breast cancer cells. Overall, this dataset annotates clinically relevant regulatory networks in male breast tumors, providing a useful resource that expands our current understanding of the gene expression programs that underlie the biology of MBC.

Enhancer transcription reveals subtype-specific gene expression programs controlling breast cancer pathogenesis.

Noncoding transcription is a defining feature of active enhancers, linking transcription factor (TF) binding to the molecular mechanisms controlling gene expression. To determine the relationship between enhancer activity and biological outcomes in breast cancers, we profiled the transcriptomes (using GRO-seq and RNA-seq) and epigenomes (using ChIP-seq) of 11 different human breast cancer cell lines representing five major molecular subtypes of breast cancer, as well as two immortalized ("normal") human breast cell lines. In addition, we developed a robust and unbiased computational pipeline that simultaneously identifies putative subtype-specific enhancers and their cognate TFs by integrating the magnitude of enhancer transcription, TF mRNA expression levels, TF motif P-values, and enrichment of H3K4me1 and H3K27ac. When applied across the 13 different cell lines noted above, the Total Functional Score of Enhancer Elements (TFSEE) identified key breast cancer subtype-specific TFs that act at transcribed enhancers to dictate gene expression patterns determining growth outcomes, including Forkhead TFs, FOSL1, and PLAG1. FOSL1, a Fos family TF, (1) is highly enriched at the enhancers of triple negative breast cancer (TNBC) cells, (2) acts as a key regulator of the proliferation and viability of TNBC cells, but not Luminal A cells, and (3) is associated with a poor prognosis in TNBC breast cancer patients. Taken together, our results validate our enhancer identification pipeline and reveal that enhancers transcribed in breast cancer cells direct critical gene regulatory networks that promote pathogenesis.

Histone modification profiling in breast cancer cell lines highlights commonalities and differences among subtypes.

BACKGROUND: Epigenetic regulators are frequently mutated or aberrantly expressed in a variety of cancers, leading to altered transcription states that result in changes in cell identity, behavior, and response to therapy. RESULTS: To define alterations in epigenetic landscapes in breast cancers, we profiled the distributions of 8 key histone modifications by ChIP-Seq, as well as primary (GRO-seq) and steady state (RNA-Seq) transcriptomes, across 13 distinct cell lines that represent 5 molecular subtypes of breast cancer and immortalized human mammary epithelial cells. DISCUSSION: Using combinatorial patterns of distinct histone modification signals, we defined subtype-specific chromatin signatures to nominate potential biomarkers. This approach identified AFAP1-AS1 as a triple negative breast cancer-specific gene associated with cell proliferation and epithelial-mesenchymal-transition. In addition, our chromatin mapping data in basal TNBC cell lines are consistent with gene expression patterns in TCGA that indicate decreased activity of the androgen receptor pathway but increased activity of the vitamin D biosynthesis pathway. CONCLUSIONS: Together, these datasets provide a comprehensive resource for histone modification profiles that define epigenetic landscapes and reveal key chromatin signatures in breast cancer cell line subtypes with potential to identify novel and actionable targets for treatment.

Interplay between inflammatory and estrogen signaling in breast cancer.

Inflammation is known to have a paradoxical effect in cancers, in some cases promoting pathogenesis while in others inhibiting pathogenesis, depending on the cellular context. In an effort to answer a number of fundamental questions about two of the major signaling cascades that affect breast tumorigenesis and impact clinical outcome, we examined the genome-wide consequences of treating ERα-positive breast cancer cells with both estrogen and TNFα. Below, we highlight our observations, their biological significance, and how they provide a framework for understanding the molecular basis for integration of proinflammatory and estrogen signaling in breast cancer.

CRISPR Screening of Transcribed Super-Enhancers Identifies Drivers of Triple-Negative Breast Cancer Progression.

Triple-negative breast cancer (TNBC) is the most therapeutically recalcitrant form of breast cancer, which is due in part to the paucity of targeted therapies. A systematic analysis of regulatory elements that extend beyond protein coding genes could uncover avenues for therapeutic intervention. To this end, we analyzed the regulatory mechanisms of TNBC-specific transcriptional enhancers together with their non-coding enhancer RNA (eRNA) transcripts. The functions of the top 30 eRNA-producing super-enhancers were systematically probed using high-throughput CRISPR-interference assays coupled to RNA-seq that enabled unbiased detection of target genes genome-wide. Generation of high resolution Hi-C chromatin interaction maps enabled annotation of the direct target genes for each super-enhancer, which highlighted their proclivity for genes that portend worse clinical outcomes in TNBC patients. Illustrating the utility of this dataset, deletion of an identified super-enhancer controlling the nearby PODXL gene or specific degradation of its enhancer RNAs led to profound inhibitory effects on target gene expression, cell proliferation, and migration. Furthermore, loss of this super-enhancer suppressed tumor growth and metastasis in TNBC mouse xenograft models. Single-cell RNA-seq and ATAC-seq analyses demonstrated the enhanced activity of this super-enhancer within the malignant cells of TNBC tumor specimens compared to non-malignant cell types. Collectively, this work examines several fundamental questions about how regulatory information encoded into eRNA-producing super-enhancers drives gene expression networks that underlie the biology of triple-negative breast cancer.

Defining the Regulatory Logic of Breast Cancer Using Single-Cell Epigenetic and Transcriptome Profiling.

Annotation of the cis-regulatory elements that drive transcriptional dysregulation in cancer cells is critical to improving our understanding of tumor biology. Herein, we present a compendium of matched chromatin accessibility (scATAC-seq) and transcriptome (scRNA-seq) profiles at single-cell resolution from human breast tumors and healthy mammary tissues processed immediately following surgical resection. We identify the most likely cell-of-origin for luminal breast tumors and basal breast tumors and then introduce a novel methodology that implements linear mixed-effects models to systematically quantify associations between regions of chromatin accessibility (i.e. regulatory elements) and gene expression in malignant cells versus normal mammary epithelial cells. These data unveil regulatory elements with that switch from silencers of gene expression in normal cells to enhancers of gene expression in cancer cells, leading to the upregulation of clinically relevant oncogenes. To translate the utility of this dataset into tractable models, we generated matched scATAC-seq and scRNA-seq profiles for breast cancer cell lines, revealing, for each subtype, a conserved oncogenic gene expression program between in vitro and in vivo cells. Together, this work highlights the importance of non-coding regulatory mechanisms that underlie oncogenic processes and the ability of single-cell multi-omics to define the regulatory logic of BC cells at single-cell resolution.

Homozygous nonsense mutations in TWIST2 cause Setleis syndrome.

The focal facial dermal dysplasias (FFDDs) are a group of inherited developmental disorders in which the characteristic diagnostic feature is bitemporal scar-like lesions that resemble forceps marks. To date, the genetic defects underlying these ectodermal dysplasias have not been determined. To identify the gene defect causing autosomal-recessive Setleis syndrome (type III FFDD), homozygosity mapping was performed with genomic DNAs from five affected individuals and 26 members of the consanguineous Puerto Rican (PR) family originally described by Setleis and colleagues. Microsatellites D2S1397 and D2S2968 were homozygous in all affected individuals, mapping the disease locus to 2q37.3. Haplotype analyses of additional markers in the PR family and a consanguineous Arab family further limited the disease locus to approximately 3 Mb between D2S2949 and D2S2253. Of the 29 candidate genes in this region, the bHLH transcription factor, TWIST2, was initially sequenced on the basis of its known involvement in murine facial development. Homozygous TWIST2 nonsense mutations, c.324C>T and c.486C>T, were identified in the affected members of the Arab and PR families, respectively. Characterization of the expressed mutant proteins, p.Q65X and p.Q119X, by electrophoretic mobility shift assays and immunoblot analyses indicated that they were truncated and unstable. Notably, Setleis syndrome patients and Twist2 knockout mice have similar facial features, indicating the gene's conserved role in mammalian development. Although human TWIST2 and TWIST1 encode highly homologous bHLH transcription factors, the finding that TWIST2 recessive mutations cause an FFDD and dominant TWIST1 mutations cause Saethre-Chotzen craniocynostosis suggests that they function independently in skin and bone development.

Redundant or separate entities?--roles of Twist1 and Twist2 as molecular switches during gene transcription.

Twist1 and Twist2 are highly conserved members of the Twist subfamily of bHLH proteins responsible for the transcriptional regulation of the developmental programs in mesenchymal cell lineages. The regulation of such processes requires that Twist1 and Twist2 function as molecular switches to activate and repress target genes by employing several direct and indirect mechanisms. Modes of action by these proteins include direct DNA binding to conserved E-box sequences and recruitment of coactivators or repressors, sequestration of E-protein modulators, and interruption of proper activator/repressor function through protein-protein interactions. Regulatory outcomes of Twist1 and Twist2 are themselves controlled by spatial-temporal expression, phosphoregulation, dimer choice and cellular localization. Although these two proteins are highly conserved and exhibit similar functions in vitro, emerging literature have demonstrated different roles in vivo. The involvement of Twist1 and Twist2 in a broad spectrum of regulatory pathways highlights the importance of understanding their roles in normal development, homeostasis and disease. Here we focus on the mechanistic models of transcriptional regulation and summarize the similarities and differences between Twist1 and Twist2 in the context of myogenesis, osteogenesis, immune system development and cancer.

Mechanisms of Regulation of the CHRDL1 Gene by the TWIST2 and ADD1/SREBP1c Transcription Factors.

Setleis syndrome (SS) is a rare focal facial dermal dysplasia caused by recessive mutations in the basic helix-loop-helix (bHLH) transcription factor, TWIST2. Expression microarray analysis showed that the chordin-like 1 (CHRDL1) gene is up-regulated in dermal fibroblasts from three SS patients with the Q119X TWIST2 mutation. METHODS: Putative TWIST binding sites were found in the upstream region of the CHRDL1 gene and examined by electrophoretic mobility shift (EMSA) and reporter gene assays. RESULTS: EMSAs showed specific binding of TWIST1 and TWIST2 homodimers, as well as heterodimers with E12, to the more distal E-boxes. An adjoining E-box was bound by ADD1/SREBP1c. EMSA analysis suggested that TWIST2 and ADD1/SREBP1c could compete for binding. Luciferase (luc) reporter assays revealed that the CHRDL1 gene upstream region drives its expression and ADD1/SREBP1c increased it 2.6 times over basal levels. TWIST2, but not the TWIST2-Q119X mutant, blocked activation by ADD1/SREBP1c, but overexpression of TWIST2-Q119X increased luc gene expression. In addition, EMSA competition assays showed that TWIST2, but not TWIST1, competes with ADD1/SREBP1c for DNA binding to the same site. CONCLUSIONS: Formation of an inactive complex between the TWIST2 Q119X and Q65X mutant proteins and ADD1/SREBP1c may prevent repressor binding and allow the binding of other regulators to activate CHRDL1 gene expression.

Tamoxifen Response at Single-Cell Resolution in Estrogen Receptor-Positive Primary Human Breast Tumors.

PURPOSE: In estrogen receptor-positive (ER+)/HER2- breast cancer, multiple measures of intratumor heterogeneity are associated with a worse response to endocrine therapy. We sought to develop a novel experimental model to measure heterogeneity in response to tamoxifen treatment in primary breast tumors. EXPERIMENTAL DESIGN: To investigate heterogeneity in response to treatment, we developed an operating room-to-laboratory pipeline for the collection of live normal breast specimens and human tumors immediately after surgical resection for processing into single-cell workflows for experimentation and genomic analyses. Live primary cell suspensions were treated ex vivo with tamoxifen (10 µmol/L) or control media for 12 hours, and single-cell RNA libraries were generated using the 10X Genomics droplet-based kit. RESULTS: In total, we obtained and processed normal breast tissue from two women undergoing reduction mammoplasty and tumor tissue from 10 women with ER+/HER2- invasive breast carcinoma. We demonstrate differences in tamoxifen response by cell type and identify distinctly responsive and resistant subpopulations within the malignant cell compartment of human tumors. Tamoxifen resistance signatures from resistant subpopulations predict poor outcomes in two large cohorts of ER+ breast cancer patients and are enriched in endocrine therapy-resistant tumors. CONCLUSIONS: This novel ex vivo model system now provides the foundation to define responsive and resistant subpopulations within heterogeneous human tumors, which can be used to develop precise single cell-based predictors of response to therapy and to identify genes and pathways driving therapeutic resistance.

Tamoxifen Response at Single Cell Resolution in Estrogen Receptor-Positive Primary Human Breast Tumors.

In ER+/HER2- breast cancer, multiple measures of intra-tumor heterogeneity are associated with worse response to endocrine therapy. To investigate heterogeneity in response to treatment, we developed an operating room-to-laboratory pipeline for the collection of live human tumors and normal breast specimens immediately after surgical resection for processing into single-cell workflows for experimentation and genomic analyses. We demonstrate differences in tamoxifen response by cell type and identify distinctly responsive and resistant subpopulations within the malignant cell compartment of human tumors. Tamoxifen resistance signatures from 3 distinct resistant subpopulations are prognostic in large cohorts of ER+ breast cancer patients and enriched in endocrine therapy resistant tumors. This novel ex vivo model system now provides a foundation to define responsive and resistant sub-populations within heterogeneous tumors, to develop precise single cell-based predictors of response to therapy, and to identify genes and pathways driving resistance to therapy.

Enhancer RNA Transcription Is Essential for a Novel CSF1 Enhancer in Triple-Negative Breast Cancer.

Enhancers are critical regulatory elements in the genome that help orchestrate spatiotemporal patterns of gene expression during development and normal physiology. In cancer, enhancers are often rewired by various genetic and epigenetic mechanisms for the activation of oncogenes that lead to initiation and progression. A key feature of active enhancers is the production of non-coding RNA molecules called enhancer RNAs, whose functions remain unknown but can be used to specify active enhancers de novo. Using a combination of eRNA transcription and chromatin modifications, we have identified a novel enhancer located 30 kb upstream of Colony Stimulating Factor 1 (CSF1). Notably, CSF1 is implicated in the progression of breast cancer, is overexpressed in triple-negative breast cancer (TNBC) cell lines, and its enhancer is primarily active in TNBC patient tumors. Genomic deletion of the enhancer (via CRISPR/Cas9) enabled us to validate this regulatory element as a bona fide enhancer of CSF1 and subsequent cell-based assays revealed profound effects on cancer cell proliferation, colony formation, and migration. Epigenetic silencing of the enhancer via CRISPR-interference assays (dCas9-KRAB) coupled to RNA-sequencing, enabled unbiased identification of additional target genes, such as RSAD2, that are predictive of clinical outcome. Additionally, we repurposed the RNA-guided RNA-targeting CRISPR-Cas13 machinery to specifically degrade the eRNAs transcripts produced at this enhancer to determine the consequences on CSF1 mRNA expression, suggesting a post-transcriptional role for these non-coding transcripts. Finally, we test our eRNA-dependent model of CSF1 enhancer function and demonstrate that our results are extensible to other forms of cancer. Collectively, this work describes a novel enhancer that is active in the TNBC subtype, which is associated with cellular growth, and requires eRNA transcripts for proper enhancer function. These results demonstrate the significant impact of enhancers in cancer biology and highlight their potential as tractable targets for therapeutic intervention.

A multi-omic dissection of super-enhancer driven oncogenic gene expression programs in ovarian cancer.

The human genome contains regulatory elements, such as enhancers, that are often rewired by cancer cells for the activation of genes that promote tumorigenesis and resistance to therapy. This is especially true for cancers that have little or no known driver mutations within protein coding genes, such as ovarian cancer. Herein, we utilize an integrated set of genomic and epigenomic datasets to identify clinically relevant super-enhancers that are preferentially amplified in ovarian cancer patients. We systematically probe the top 86 super-enhancers, using CRISPR-interference and CRISPR-deletion assays coupled to RNA-sequencing, to nominate two salient super-enhancers that drive proliferation and migration of cancer cells. Utilizing Hi-C, we construct chromatin interaction maps that enable the annotation of direct target genes for these super-enhancers and confirm their activity specifically within the cancer cell compartment of human tumors using single-cell genomics data. Together, our multi-omic approach examines a number of fundamental questions about how regulatory information encoded into super-enhancers drives gene expression networks that underlie the biology of ovarian cancer.

CRISPR-based knock-in mutagenesis of the pioneer transcription factor FOXA1: optimization of strategies for multi-allelic proteins in cancer cells.

Precise genome engineering of living cells has been revolutionized by the introduction of the highly specific and easily programmable properties of the clustered regularly interspaced short palindromic repeats (CRISPR) technology. This has greatly accelerated research into human health and has facilitated the discovery of novel therapeutics. CRISPR-Cas9 is most widely employed for its ability to inactivate or knockout specific genes, but can be also used to introduce subtle site-specific substitutions of DNA sequences that can lead to changes in the amino acid composition of proteins. Despite the proven success of CRISPR-based knock-in strategies of genes in typical diploid cells (i.e., cells containing two sets of chromosomes), precise editing of cancer cells, that typically have unstable genomes and multiple copies of chromosomes, is more challenging and not adequately addressed in the literature. Herein, we detail our methodology for replacing endogenous proteins with intended knock-in mutants in polyploid cancer cells and discuss our experimental design, screening strategy, and facile allele frequency estimation methodology. As proof of principle, we performed genome editing of specific amino acids within the pioneer transcription factor FOXA1, a critical component of estrogen and androgen receptor signaling, in MCF-7 breast cancer cells. We confirm mutant FOXA1 protein expression and intended amino acid substitutions via western blotting and mass spectrometry. In addition, we show that mutant allele frequency estimation is easily achieved by topoisomerase-based cloning combined with allele-specific PCR, which we later confirmed by next-generation RNA-sequencing. Typically, there are 4 - 5 copies (alleles) of FOXA1 in breast cancer cells, making the editing of this protein inherently challenging. As a result, most studies that focus on FOXA1 mutants rely on ectopic overexpression of FOXA1 from a plasmid. Therefore, we provide an optimized methodology for replacing endogenous wild-type FOXA1 with precise knock-in mutants to enable the systematic analysis of its molecular mechanisms within the appropriate physiological context.

Total Functional Score of Enhancer Elements Identifies Lineage-Specific Enhancers That Drive Differentiation of Pancreatic Cells.

The differentiation of embryonic stem cells into various lineages is highly dependent on the chromatin state of the genome and patterns of gene expression. To identify lineage-specific enhancers driving the differentiation of progenitors into pancreatic cells, we used a previously described computational framework called Total Functional Score of Enhancer Elements (TFSEE), which integrates multiple genomic assays that probe both transcriptional and epigenomic states. First, we evaluated and compared TFSEE as an enhancer-calling algorithm with enhancers called using GRO-seq-defined enhancer transcripts (method 1) versus enhancers called using histone modification ChIP-seq data (method 2). Second, we used TFSEE to define the enhancer landscape and identify transcription factors (TFs) that maintain the multipotency of a subpopulation of endodermal stem cells during differentiation into pancreatic lineages. Collectively, our results demonstrate that TFSEE is a robust enhancer-calling algorithm that can be used to perform multilayer genomic data integration to uncover cell type-specific TFs that control lineage-specific enhancers.

Transcriptional control by enhancers and enhancer RNAs.

The regulation of gene expression is a fundamental cellular process and its misregulation is a key component of disease. Enhancers are one of the most salient regulatory elements in the genome and help orchestrate proper spatiotemporal gene expression during development, in homeostasis, and in response to signaling. Notably, molecular aberrations at enhancers, such as translocations and single nucleotide polymorphisms, are emerging as an important source of human variation and susceptibility to disease. Herein we discuss emerging paradigms addressing how genes are regulated by enhancers, common features of active enhancers, and how non-coding enhancer RNAs (eRNAs) can direct gene expression programs that underlie cellular phenotypes. We survey the current evidence, which suggests that eRNAs can bind to transcription factors, mediate enhancer-promoter interactions, influence RNA Pol II elongation, and act as decoys for repressive cofactors. Furthermore, we discuss current methodologies for the identification of eRNAs and novel approaches to elucidate their functions.