CTCF/cohesin-binding sites are frequently mutated in cancer

A Functional Survey of the Regulatory Landscape of Estrogen Receptor-Positive Breast Cancer Evolution

Only a handful of somatic alterations have been linked to endocrine therapy resistance in hormone-dependent breast cancer, potentially explaining ∼40% of relapses. If other mechanisms underlie the evolution of hormone-dependent breast cancer under adjuvant therapy is currently unknown. In this work, we employ functional genomics to dissect the contribution of cis-regulatory elements (CRE) to cancer evolution by focusing on 12 megabases of noncoding DNA, including clonal enhancers, gene promoters, and boundaries of topologically associating domains. Parallel epigenetic perturbation (CRISPRi) in vitro reveals context-dependent roles for many of these CREs, with a specific impact on dormancy entrance and endocrine therapy resistance. Profiling of CRE somatic alterations in a unique, longitudinal cohort of patients treated with endocrine therapies identifies a limited set of noncoding changes potentially involved in therapy resistance. Overall, our data uncover how endocrine therapies trigger the emergence of transient features which could ultimately be exploited to hinder the adaptive process. Significance: This study shows that cells adapting to endocrine therapies undergo changes in the usage or regulatory regions. Dormant cells are less vulnerable to regulatory perturbation but gain transient dependencies which can be exploited to decrease the formation of dormant persisters.

Lynch syndrome-associated and sporadic microsatellite unstable colorectal cancers: different patterns of clonal evolution yield highly similar tumours

Microsatellite unstable colorectal cancer (MSI-CRC) can arise through germline mutations in mismatch repair (MMR) genes in individuals with Lynch syndrome (LS), or sporadically through promoter methylation of the MMR gene MLH1. Despite the different origins of hereditary and sporadic MSI tumours, their genomic features have not been extensively compared. A prominent feature of MMR-deficient genomes is the occurrence of many indels in short repeat sequences, an understudied mutation type due to the technical challenges of variant calling in these regions. In this study, we performed whole genome sequencing and RNA-sequencing on 29 sporadic and 14 hereditary MSI-CRCs. We compared the tumour groups by analysing genome-wide mutation densities, microsatellite repeat indels, recurrent protein-coding variants, signatures of single base, doublet base, and indel mutations, and changes in gene expression. We show that the mutational landscapes of hereditary and sporadic MSI-CRCs, including mutational signatures and mutation densities genome-wide and in microsatellites, are highly similar. Only a low number of differentially expressed genes were found, enriched to interferon-γ regulated immune response pathways. Analysis of the variance in allelic fractions of somatic variants in each tumour group revealed higher clonal heterogeneity in sporadic MSI-CRCs. Our results suggest that the differing molecular origins of MMR deficiency in hereditary and sporadic MSI-CRCs do not result in substantial differences in the mutational landscapes of these tumours. The divergent patterns of clonal evolution between the tumour groups may have clinical implications, as high clonal heterogeneity has been associated with decreased tumour immunosurveillance and reduced responsiveness to immunotherapy.

ERCC2 mutations alter the genomic distribution pattern of somatic mutations and are independently prognostic in bladder cancer

Excision repair cross-complementation group 2 (ERCC2) encodes the DNA helicase xeroderma pigmentosum group D, which functions in transcription and nucleotide excision repair. Point mutations in ERCC2 are putative drivers in around 10% of bladder cancers (BLCAs) and a potential positive biomarker for cisplatin therapy response. Nevertheless, the prognostic significance directly attributed to ERCC2 mutations and its pathogenic role in genome instability remain poorly understood. We first demonstrated that mutant ERCC2 is an independent predictor of prognosis in BLCA. We then examined its impact on the somatic mutational landscape using a cohort of ERCC2 wild-type (n = 343) and mutant (n = 39) BLCA whole genomes. The genome-wide distribution of somatic mutations is significantly altered in ERCC2 mutants, including T[C>T]N enrichment, altered replication time correlations, and CTCF-cohesin binding site mutation hotspots. We leverage these alterations to develop a machine learning model for predicting pathogenic ERCC2 mutations, which may be useful to inform treatment of patients with BLCA.

Machine learning enables pan-cancer identification of mutational hotspots at persistent CTCF binding sites

CCCTC-binding factor (CTCF) is an insulator protein that binds to a highly conserved DNA motif and facilitates regulation of three-dimensional (3D) nuclear architecture and transcription. CTCF binding sites (CTCF-BSs) reside in non-coding DNA and are frequently mutated in cancer. Our previous study identified a small subclass of CTCF-BSs that are resistant to CTCF knock down, termed persistent CTCF binding sites (P-CTCF-BSs). P-CTCF-BSs show high binding conservation and potentially regulate cell-type constitutive 3D chromatin architecture. Here, using ICGC sequencing data we made the striking observation that P-CTCF-BSs display a highly elevated mutation rate in breast and prostate cancer when compared to all CTCF-BSs. To address whether P-CTCF-BS mutations are also enriched in other cell-types, we developed CTCF-INSITE-a tool utilising machine learning to predict persistence based on genetic and epigenetic features of experimentally-determined P-CTCF-BSs. Notably, predicted P-CTCF-BSs also show a significantly elevated mutational burden in all 12 cancer-types tested. Enrichment was even stronger for P-CTCF-BS mutations with predicted functional impact to CTCF binding and chromatin looping. Using in vitro binding assays we validated that P-CTCF-BS cancer mutations, predicted to be disruptive, indeed reduced CTCF binding. Together this study reveals a new subclass of cancer specific CTCF-BS DNA mutations and provides insights into their importance in genome organization in a pan-cancer setting.

Permeable TAD boundaries and their impact on genome-associated functions

TAD boundaries are genomic elements that separate biological processes in neighboring domains by blocking DNA loops that are formed through Cohesin-mediated loop extrusion. Most TAD boundaries consist of arrays of binding sites for the CTCF protein, whose interaction with the Cohesin complex blocks loop extrusion. TAD boundaries are not fully impermeable though and allow a limited amount of inter-TAD loop formation. Based on the reanalysis of Nano-C data, a multicontact Chromosome Conformation Capture assay, we propose a model whereby clustered CTCF binding sites promote the successive stalling of Cohesin and subsequent dissociation from the chromatin. A fraction of Cohesin nonetheless achieves boundary read-through. Due to a constant rate of Cohesin dissociation elsewhere in the genome, the maximum length of inter-TAD loops is restricted though. We speculate that the DNA-encoded organization of stalling sites regulates TAD boundary permeability and discuss implications for enhancer-promoter loop formation and other genomic processes.

Genome-wide Cas9-mediated screening of essential non-coding regulatory elements via libraries of paired single-guide RNAs

The functions of non-coding regulatory elements (NCREs), which constitute a major fraction of the human genome, have not been systematically studied. Here we report a method involving libraries of paired single-guide RNAs targeting both ends of an NCRE as a screening system for the Cas9-mediated deletion of thousands of NCREs genome-wide to study their functions in distinct biological contexts. By using K562 and 293T cell lines and human embryonic stem cells, we show that NCREs can have redundant functions, and that many ultra-conserved elements have silencer activity and play essential roles in cell growth and in cellular responses to drugs (notably, the ultra-conserved element PAX6_Tarzan may be critical for heart development, as removing it from human embryonic stem cells led to defects in cardiomyocyte differentiation). The high-throughput screen, which is compatible with single-cell sequencing, may allow for the identification of druggable NCREs.

Hidden secrets of the cancer genome: unlocking the impact of non-coding mutations in gene regulatory elements

Discoveries in the field of genomics have revealed that non-coding genomic regions are not merely "junk DNA", but rather comprise critical elements involved in gene expression. These gene regulatory elements (GREs) include enhancers, insulators, silencers, and gene promoters. Notably, new evidence shows how mutations within these regions substantially influence gene expression programs, especially in the context of cancer. Advances in high-throughput sequencing technologies have accelerated the identification of somatic and germline single nucleotide mutations in non-coding genomic regions. This review provides an overview of somatic and germline non-coding single nucleotide alterations affecting transcription factor binding sites in GREs, specifically involved in cancer biology. It also summarizes the technologies available for exploring GREs and the challenges associated with studying and characterizing non-coding single nucleotide mutations. Understanding the role of GRE alterations in cancer is essential for improving diagnostic and prognostic capabilities in the precision medicine era, leading to enhanced patient-centered clinical outcomes.

Mutation rate heterogeneity at the sub-gene scale due to local DNA hypomethylation

Local mutation rates in human are highly heterogeneous, with known variability at the scale of megabase-sized chromosomal domains, and, on the other extreme, at the scale of oligonucleotides. The intermediate, kilobase-scale heterogeneity in mutation risk is less well characterized. Here, by analyzing thousands of somatic genomes, we studied mutation risk gradients along gene bodies, representing a genomic scale spanning roughly 1-10 kb, hypothesizing that different mutational mechanisms are differently distributed across gene segments. The main heterogeneity concerns several kilobases at the transcription start site and further downstream into 5' ends of gene bodies; these are commonly hypomutated with several mutational signatures, most prominently the ubiquitous C > T changes at CpG dinucleotides. The width and shape of this mutational coldspot at 5' gene ends is variable across genes, and corresponds to variable interval of lowered DNA methylation depending on gene activity level and regulation. Such hypomutated loci, at 5' gene ends or elsewhere, correspond to DNA hypomethylation that can associate with various landmarks, including intragenic enhancers, Polycomb-marked regions, or chromatin loop anchor points. Tissue-specific DNA hypomethylation begets tissue-specific local hypomutation. Of note, direction of mutation risk is inverted for AID/APOBEC3 cytosine deaminase activity, whose signatures are enriched in hypomethylated regions.

DNA fragility at topologically associated domain boundaries is promoted by alternative DNA secondary structure and topoisomerase II activity

CCCTC-binding factor (CTCF) binding sites are hotspots of genome instability. Although many factors have been associated with CTCF binding site fragility, no study has integrated all fragility-related factors to understand the mechanism(s) of how they work together. Using an unbiased, genome-wide approach, we found that DNA double-strand breaks (DSBs) are enriched at strong, but not weak, CTCF binding sites in five human cell types. Energetically favorable alternative DNA secondary structures underlie strong CTCF binding sites. These structures coincided with the location of topoisomerase II (TOP2) cleavage complex, suggesting that DNA secondary structure acts as a recognition sequence for TOP2 binding and cleavage at CTCF binding sites. Furthermore, CTCF knockdown significantly increased DSBs at strong CTCF binding sites and at CTCF sites that are located at topologically associated domain (TAD) boundaries. TAD boundary-associated CTCF sites that lost CTCF upon knockdown displayed increased DSBs when compared to the gained sites, and those lost sites are overrepresented with G-quadruplexes, suggesting that the structures act as boundary insulators in the absence of CTCF, and contribute to increased DSBs. These results model how alternative DNA secondary structures facilitate recruitment of TOP2 to CTCF binding sites, providing mechanistic insight into DNA fragility at CTCF binding sites.

Cohesin regulation and roles in chromosome structure and function

Chromosome structure regulates DNA-templated processes such as transcription of genes. Dynamic changes to chromosome structure occur during development and in disease contexts. The cohesin complex is a molecular motor that regulates chromosome structure by generating DNA loops that bring two distal genomic sites into close spatial proximity. There are many open questions regarding the formation and dissolution of DNA loops, as well as the role(s) of DNA loops in regulating transcription of the interphase genome. This review focuses on recent discoveries that provide molecular insights into the role of cohesin and chromosome structure in gene transcription during development and disease.

Enhancer-promoter specificity in gene transcription: molecular mechanisms and disease associations

Although often located at a distance from their target gene promoters, enhancers are the primary genomic determinants of temporal and spatial transcriptional specificity in metazoans. Since the discovery of the first enhancer element in simian virus 40, there has been substantial interest in unraveling the mechanism(s) by which enhancers communicate with their partner promoters to ensure proper gene expression. These research efforts have benefited considerably from the application of increasingly sophisticated sequencing- and imaging-based approaches in conjunction with innovative (epi)genome-editing technologies; however, despite various proposed models, the principles of enhancer-promoter interaction have still not been fully elucidated. In this review, we provide an overview of recent progress in the eukaryotic gene transcription field pertaining to enhancer-promoter specificity. A better understanding of the mechanistic basis of lineage- and context-dependent enhancer-promoter engagement, along with the continued identification of functional enhancers, will provide key insights into the spatiotemporal control of gene expression that can reveal therapeutic opportunities for a range of enhancer-related diseases.

ADNP modulates SINE B2-derived CTCF-binding sites during blastocyst formation in mice

CTCF is crucial for chromatin structure and transcription regulation in early embryonic development. However, the kinetics of CTCF chromatin occupation in preimplantation embryos have remained unclear. In this study, we used CUT&RUN technology to investigate CTCF occupancy in mouse preimplantation development. Our findings revealed that CTCF begins binding to the genome prior to zygotic genome activation (ZGA), with a preference for CTCF-anchored chromatin loops. Although the majority of CTCF occupancy is consistently maintained, we identified a specific set of binding sites enriched in the mouse-specific short interspersed element (SINE) family B2 that are restricted to the cleavage stages. Notably, we discovered that the neuroprotective protein ADNP counteracts the stable association of CTCF at SINE B2-derived CTCF-binding sites. Knockout of Adnp in the zygote led to impaired CTCF binding signal recovery, failed deposition of H3K9me3, and transcriptional derepression of SINE B2 during the morula-to-blastocyst transition, which further led to unfaithful cell differentiation in embryos around implantation. Our analysis highlights an ADNP-dependent restriction of CTCF binding during cell differentiation in preimplantation embryos. Furthermore, our findings shed light on the functional importance of transposable elements (TEs) in promoting genetic innovation and actively shaping the early embryo developmental process specific to mammals.

DeepCBS: shedding light on the impact of mutations occurring at CTCF binding sites

CTCF-mediated chromatin loops create insulated neighborhoods that constrain promoter-enhancer interactions, serving as a unit of gene regulation. Disruption of the CTCF binding sites (CBS) will lead to the destruction of insulated neighborhoods, which in turn can cause dysregulation of the contained genes. In a recent study, it is found that CTCF/cohesin binding sites are a major mutational hotspot in the cancer genome. Mutations can affect CTCF binding, causing the disruption of insulated neighborhoods. And our analysis reveals a significant enrichment of well-known proto-oncogenes in insulated neighborhoods with mutations specifically occurring in anchor regions. It can be assumed that some mutations disrupt CTCF binding, leading to the disruption of insulated neighborhoods and subsequent activation of proto-oncogenes within these insulated neighborhoods. To explore the consequences of such mutations, we develop DeepCBS, a computational tool capable of analyzing mutations at CTCF binding sites, predicting their influence on insulated neighborhoods, and investigating the potential activation of proto-oncogenes. Futhermore, DeepCBS is applied to somatic mutation data of liver cancer. As a result, 87 mutations that disrupt CTCF binding sites are identified, which leads to the identification of 237 disrupted insulated neighborhoods containing a total of 135 genes. Integrative analysis of gene expression differences in liver cancer further highlights three genes: ARHGEF39, UBE2C and DQX1. Among them, ARHGEF39 and UBE2C have been reported in the literature as potential oncogenes involved in the development of liver cancer. The results indicate that DQX1 may be a potential oncogene in liver cancer and may contribute to tumor immune escape. In conclusion, DeepCBS is a promising method to analyze impacts of mutations occurring at CTCF binding sites on the insulator function of CTCF, with potential extensions to shed light on the effects of mutations on other functions of CTCF.

Role of chromosomal cohesion and separation in aneuploidy and tumorigenesis

Cell division is a crucial process, and one of its essential steps involves copying the genetic material, which is organized into structures called chromosomes. Before a cell can divide into two, it needs to ensure that each newly copied chromosome is paired tightly with its identical twin. This pairing is maintained by a protein complex known as cohesin, which is conserved in various organisms, from single-celled ones to humans. Cohesin essentially encircles the DNA, creating a ring-like structure to handcuff, to keep the newly synthesized sister chromosomes together in pairs. Therefore, chromosomal cohesion and separation are fundamental processes governing the attachment and segregation of sister chromatids during cell division. Metaphase-to-anaphase transition requires dissolution of cohesins by the enzyme Separase. The tight regulation of these processes is vital for safeguarding genomic stability. Dysregulation in chromosomal cohesion and separation resulting in aneuploidy, a condition characterized by an abnormal chromosome count in a cell, is strongly associated with cancer. Aneuploidy is a recurring hallmark in many cancer types, and abnormalities in chromosomal cohesion and separation have been identified as significant contributors to various cancers, such as acute myeloid leukemia, myelodysplastic syndrome, colorectal, bladder, and other solid cancers. Mutations within the cohesin complex have been associated with these cancers, as they interfere with chromosomal segregation, genome organization, and gene expression, promoting aneuploidy and contributing to the initiation of malignancy. In summary, chromosomal cohesion and separation processes play a pivotal role in preserving genomic stability, and aberrations in these mechanisms can lead to aneuploidy and cancer. Gaining a deeper understanding of the molecular intricacies of chromosomal cohesion and separation offers promising prospects for the development of innovative therapeutic approaches in the battle against cancer.

Evaluating topography of mutational signatures with SigProfilerTopography

The mutations found in a cancer genome are shaped by diverse processes, each displaying a characteristic mutational signature that may be influenced by the genome's architecture. While prior analyses have evaluated the effect of topographical genomic features on mutational signatures, there has been no computational tool that can comprehensively examine this interplay. Here, we present SigProfilerTopography, a Python package that allows evaluating the effect of chromatin organization, histone modifications, transcription factor binding, DNA replication, and DNA transcription on the activities of different mutational processes. SigProfilerTopography elucidates the unique topographical characteristics of mutational signatures, unveiling their underlying biological and molecular mechanisms.

Identification of common factors among fibrosarcoma, rhabdomyosarcoma, and osteosarcoma by network analysis

Sarcoma cancers are uncommon malignant tumors, and there are many subgroups, including fibrosarcoma (FS), which mainly affects middle-aged and older adults in deep soft tissues. Rhabdomyosarcoma (RMS), on the other hand, is the most common soft-tissue sarcoma in children and is located in the head and neck area. Osteosarcomas (OS) is the predominant form of primary bone cancer among young adults, primarily resulting from sporadically random mutations. This frequently results in the dissemination of cancer cells to the lungs, commonly known as metastasis. Mesodermal cells are the origin of sarcoma cancers. In this study, a rather radical approach has been applied. Instead of comparing homogenous cancer types, we focus on three main subtypes of sarcoma: fibrosarcoma, rhabdomyosarcoma, and osteosarcoma, and compare their gene expression with normal cell groups to identify the differentially expressed genes (DEGs). Next, by applying protein-protein interaction (PPI) network analysis, we determine the hub genes and crucial factors, such as transcription factors (TFs), affected by these types of cancer. Our findings indicate a modification in a range of pathways associated with cell cycle, extracellular matrix, and DNA repair in these three malignancies. Results showed that fibrosarcoma (FS), rhabdomyosarcoma (RMS), and osteosarcoma (OS) had 653, 1270, and 2823 differentially expressed genes (DEGs), respectively. Interestingly, there were 24 DEGs common to all three types. Network analysis showed that the fibrosarcoma network had two sub-networks identified in FS that contributed to the catabolic process of collagen via the G-protein coupled receptor signaling pathway. The rhabdomyosarcoma network included nine sub-networks associated with cell division, extracellular matrix organization, mRNA splicing via spliceosome, and others. The osteosarcoma network has 13 sub-networks, including mRNA splicing, sister chromatid cohesion, DNA repair, etc. In conclusion, the common DEGs identified in this study have been shown to play significant and multiple roles in various other cancers based on the literature review, indicating their significance.

Hotspot propensity across mutational processes

The sparsity of mutations observed across tumours hinders our ability to study mutation rate variability at nucleotide resolution. To circumvent this, here we investigated the propensity of mutational processes to form mutational hotspots as a readout of their mutation rate variability at single base resolution. Mutational signatures 1 and 17 have the highest hotspot propensity (5-78 times higher than other processes). After accounting for trinucleotide mutational probabilities, sequence composition and mutational heterogeneity at 10 Kbp, most (94-95%) signature 17 hotspots remain unexplained, suggesting a significant role of local genomic features. For signature 1, the inclusion of genome-wide distribution of methylated CpG sites into models can explain most (80-100%) of the hotspot propensity. There is an increased hotspot propensity of signature 1 in normal tissues and de novo germline mutations. We demonstrate that hotspot propensity is a useful readout to assess the accuracy of mutation rate models at nucleotide resolution. This new approach and the findings derived from it open up new avenues for a range of somatic and germline studies investigating and modelling mutagenesis.

Role of Genetic Variation in Transcriptional Regulatory Elements in Heart Rhythm

Genetic predisposition to cardiac arrhythmias has been a field of intense investigation. Research initially focused on rare hereditary arrhythmias, but over the last two decades, the role of genetic variation (single nucleotide polymorphisms) in heart rate, rhythm, and arrhythmias has been taken into consideration as well. In particular, genome-wide association studies have identified hundreds of genomic loci associated with quantitative electrocardiographic traits, atrial fibrillation, and less common arrhythmias such as Brugada syndrome. A significant number of associated variants have been found to systematically localize in non-coding regulatory elements that control the tissue-specific and temporal transcription of genes encoding transcription factors, ion channels, and other proteins. However, the identification of causal variants and the mechanism underlying their impact on phenotype has proven difficult due to the complex tissue-specific, time-resolved, condition-dependent, and combinatorial function of regulatory elements, as well as their modest conservation across different model species. In this review, we discuss research efforts aimed at identifying and characterizing-trait-associated variant regulatory elements and the molecular mechanisms underlying their impact on heart rate or rhythm.

Involvement of CCCTC-binding factor in epigenetic regulation of cancer

A major global health burden continues to be borne by the complex and multifaceted disease of cancer. Epigenetic changes, which are essential for the emergence and spread of cancer, have drawn a huge amount of attention recently. The CCCTC-binding factor (CTCF), which takes part in a wide range of cellular processes including genomic imprinting, X chromosome inactivation, 3D chromatin architecture, local modifications of histone, and RNA polymerase II-mediated gene transcription, stands out among the diverse array of epigenetic regulators. CTCF not only functions as an architectural protein but also modulates DNA methylation and histone modifications. Epigenetic regulation of cancer has already been the focus of plenty of studies. Understanding the role of CTCF in the cancer epigenetic landscape may lead to the development of novel targeted therapeutic strategies for cancer. CTCF has already earned its status as a tumor suppressor gene by acting like a homeostatic regulator of genome integrity and function. Moreover, CTCF has a direct effect on many important transcriptional regulators that control the cell cycle, apoptosis, senescence, and differentiation. As we learn more about CTCF-mediated epigenetic modifications and transcriptional regulations, the possibility of utilizing CTCF as a diagnostic marker and therapeutic target for cancer will also increase. Thus, the current review intends to promote personalized and precision-based therapeutics for cancer patients by shedding light on the complex interplay between CTCF and epigenetic processes.

High CTCF expression mediated by FGD5-AS1/miR-19a-3p axis is associated with immunosuppression and pancreatic cancer progression

The most common reason for cancer-related death globally is predicted to be pancreatic cancer (PC), one of the deadliest cancers. The CCCTC-binding factor (CTCF) regulates the three-dimensional structure of chromatin, was reported to be highly regulated in various malignancies. However, the underlying biological functions and possible pathways via which CTCF promotes PC progression remain unclear. Herein, we examined the CTCF function in PC and discovered that CTCF expression in PC tissues was significantly raised compared to neighboring healthy tissues. Additionally, Kaplan-Meier survival analysis demonstrated a strong connection between elevated CTCF expression and poor patient prognosis. A study of the ROC curve (receiver operating characteristic) revealed an AUC value for CTCF of 0.968. Subsequent correlation analysis exhibited a strong relationship between immunosuppression and CTCF expression in PC. CTCF knockdown significantly inhibited the malignant biological process of PC in vitro and in vivo, suggesting that CTCF may be a potential PC treatment target. We also identified the FGD5 antisense RNA 1 (FGD5-AS1)/miR-19a-3p axis as a possible upstream mechanism for CTCF overexpression. In conclusion, our data suggest that ceRNA-mediated CTCF overexpression contributes to the suppression of anti-tumor immune responses in PC and could be a predictive biomarker and potential PC treatment target.

Enhancers dysfunction in the 3D genome of cancer cells

Eukaryotic genomes are spatially organized inside the cell nucleus, forming a threedimensional (3D) architecture that allows for spatial separation of nuclear processes and for controlled expression of genes required for cell identity specification and tissue homeostasis. Hence, it is of no surprise that mis-regulation of genome architecture through rearrangements of the linear genome sequence or epigenetic perturbations are often linked to aberrant gene expression programs in tumor cells. Increasing research efforts have shed light into the causes and consequences of alterations of 3D genome organization. In this review, we summarize the current knowledge on how 3D genome architecture is dysregulated in cancer, with a focus on enhancer highjacking events and their contribution to tumorigenesis. Studying the functional effects of genome architecture perturbations on gene expression in cancer offers a unique opportunity for a deeper understanding of tumor biology and sets the basis for the discovery of novel therapeutic targets.

Perturbations in 3D genome organization can promote acquired drug resistance

Acquired drug resistance is a major problem in the treatment of cancer. hTERT-immortalized, untransformed RPE-1 cells can acquire resistance to Taxol by derepressing the ABCB1 gene, encoding for the multidrug transporter P-gP. Here, we investigate how the ABCB1 gene is derepressed. ABCB1 activation is associated with reduced H3K9 trimethylation, increased H3K27 acetylation, and ABCB1 displacement from the nuclear lamina. While altering DNA methylation and H3K27 methylation had no major impact on ABCB1 expression, nor did it promote resistance, disrupting the nuclear lamina component Lamin B Receptor did promote the acquisition of a Taxol-resistant phenotype in a subset of cells. CRISPRa-mediated gene activation supported the notion that lamina dissociation influences ABCB1 derepression. We propose a model in which nuclear lamina dissociation of a repressed gene allows for its activation, implying that deregulation of the 3D genome topology could play an important role in tumor evolution and the acquisition of drug resistance.

High-resolution CTCF footprinting reveals impact of chromatin state on cohesin extrusion dynamics

DNA looping is vital for establishing many enhancer-promoter interactions. While CTCF is known to anchor many cohesin-mediated loops, the looped chromatin fiber appears to predominantly exist in a poorly characterized actively extruding state. To better characterize extruding chromatin loop structures, we used CTCF MNase HiChIP data to determine both CTCF binding at high resolution and 3D contact information. Here we present FactorFinder, a tool that identifies CTCF binding sites at near base-pair resolution. We leverage this substantial advance in resolution to determine that the fully extruded (CTCF-CTCF) state is rare genome-wide with locus-specific variation from ~1-10%. We further investigate the impact of chromatin state on loop extrusion dynamics, and find that active enhancers and RNA Pol II impede cohesin extrusion, facilitating an enrichment of enhancer-promoter contacts in the partially extruded loop state. We propose a model of topological regulation whereby the transient, partially extruded states play active roles in transcription.

Myeloid leukemia vulnerabilities embedded in long noncoding RNA locus MYNRL15

The noncoding genome presents a largely untapped source of new biological insights, including thousands of long noncoding RNA (lncRNA) loci. While lncRNA dysregulation has been reported in myeloid malignancies, their functional relevance remains to be systematically interrogated. We performed CRISPRi screens of lncRNA signatures from normal and malignant hematopoietic cells and identified MYNRL15 as a myeloid leukemia dependency. Functional dissection suggests an RNA-independent mechanism mediated by two regulatory elements embedded in the locus. Genetic perturbation of these elements triggered a long-range chromatin interaction and downregulation of leukemia dependency genes near the gained interaction sites, as well as overall suppression of cancer dependency pathways. Thus, this study describes a new noncoding myeloid leukemia vulnerability and mechanistic concept for myeloid leukemia. Importantly, MYNRL15 perturbation caused strong and selective impairment of leukemia cells of various genetic backgrounds over normal hematopoietic stem and progenitor cells in vitro, and depletion of patient-derived xenografts in vivo.

Long-range gene regulation in hormone-dependent cancer

The human genome is organized into multiple structural layers, ranging from chromosome territories to progressively smaller substructures, such as topologically associating domains (TADs) and chromatin loops. These substructures, collectively referred to as long-range chromatin interactions (LRIs), have a significant role in regulating gene expression. TADs are regions of the genome that harbour groups of genes and regulatory elements that frequently interact with each other and are insulated from other regions, thereby preventing widespread uncontrolled DNA contacts. Chromatin loops formed within TADs through enhancer and promoter interactions are elastic, allowing transcriptional heterogeneity and stochasticity. Over the past decade, it has become evident that the 3D genome structure, also referred to as the chromatin architecture, is central to many transcriptional cellular decisions. In this Review, we delve into the intricate relationship between steroid receptors and LRIs, discussing how steroid receptors interact with and modulate these chromatin interactions. Genetic alterations in the many processes involved in organizing the nuclear architecture are often associated with the development of hormone-dependent cancers. A better understanding of the interplay between architectural proteins and hormone regulatory networks can ultimately be exploited to develop improved approaches for cancer treatment.

Predicting regional somatic mutation rates using DNA motifs

How the locus-specificity of epigenetic modifications is regulated remains an unanswered question. A contributing mechanism is that epigenetic enzymes are recruited to specific loci by DNA binding factors recognizing particular sequence motifs (referred to as epi-motifs). Using these motifs to predict biological outputs depending on local epigenetic state such as somatic mutation rates would confirm their functionality. Here, we used DNA motifs including known TF motifs and epi-motifs as a surrogate of epigenetic signals to predict somatic mutation rates in 13 cancers at an average 23kbp resolution. We implemented an interpretable neural network model, called contextual regression, to successfully learn the universal relationship between mutations and DNA motifs, and uncovered motifs that are most impactful on the regional mutation rates such as TP53 and epi-motifs associated with H3K9me3. Furthermore, we identified genomic regions with significantly higher mutation rates than the expected values in each individual tumor and demonstrated that such cancer-related regions can accurately predict cancer types. Interestingly, we found that the same mutation signatures often have different contributions to cancer-related and cancer-independent regions, and we also identified the motifs with the most contribution to each mutation signature.

Multi-feature clustering of CTCF binding creates robustness for loop extrusion blocking and Topologically Associating Domain boundaries

Topologically Associating Domains (TADs) separate vertebrate genomes into insulated regulatory neighborhoods that focus genome-associated processes. TADs are formed by Cohesin-mediated loop extrusion, with many TAD boundaries consisting of clustered binding sites of the CTCF insulator protein. Here we determine how this clustering of CTCF binding contributes to the blocking of loop extrusion and the insulation between TADs. We identify enrichment of three features of CTCF binding at strong TAD boundaries, consisting of strongly bound and closely spaced CTCF binding peaks, with a further enrichment of DNA-binding motifs within these peaks. Using multi-contact Nano-C analysis in cells with normal and perturbed CTCF binding, we establish that individual CTCF binding sites contribute to the blocking of loop extrusion, but in an incomplete manner. When clustered, individual CTCF binding sites thus create a stepwise insulation between neighboring TADs. Based on these results, we propose a model whereby multiple instances of temporal loop extrusion blocking create strong insulation between TADs.

Sequence dependencies and mutation rates of localized mutational processes in cancer

BACKGROUND

Cancer mutations accumulate through replication errors and DNA damage coupled with incomplete repair. Individual mutational processes often show nucleotide sequence and functional region preferences. As a result, some sequence contexts mutate at much higher rates than others, with additional variation found between functional regions. Mutational hotspots, with recurrent mutations across cancer samples, represent genomic positions with elevated mutation rates, often caused by highly localized mutational processes.

METHODS

We count the 11-mer genomic sequences across the genome, and using the PCAWG set of 2583 pan-cancer whole genomes, we associate 11-mers with mutational signatures, hotspots of single nucleotide variants, and specific genomic regions. We evaluate the mutation rates of individual and combined sets of 11-mers and derive mutational sequence motifs.

RESULTS

We show that hotspots generally identify highly mutable sequence contexts. Using these, we show that some mutational signatures are enriched in hotspot sequence contexts, corresponding to well-defined sequence preferences for the underlying localized mutational processes. This includes signature 17b (of unknown etiology) and signatures 62 (POLE deficiency), 7a (UV), and 72 (linked to lymphomas). In some cases, the mutation rate and sequence preference increase further when focusing on certain genomic regions, such as signature 62 in transcribed regions, where the mutation rate is increased up to 9-folds over cancer type and mutational signature average.

CONCLUSIONS

We summarize our findings in a catalog of localized mutational processes, their sequence preferences, and their estimated mutation rates.

Inferring CTCF-binding patterns and anchored loops across human tissues and cell types

CCCTC-binding factor (CTCF) is a transcription regulator with a complex role in gene regulation. The recognition and effects of CTCF on DNA sequences, chromosome barriers, and enhancer blocking are not well understood. Existing computational tools struggle to assess the regulatory potential of CTCF-binding sites and their impact on chromatin loop formation. Here we have developed a deep-learning model, DeepAnchor, to accurately characterize CTCF binding using high-resolution genomic/epigenomic features. This has revealed distinct chromatin and sequence patterns for CTCF-mediated insulation and looping. An optimized implementation of a previous loop model based on DeepAnchor score excels in predicting CTCF-anchored loops. We have established a compendium of CTCF-anchored loops across 52 human tissue/cell types, and this suggests that genomic disruption of these loops could be a general mechanism of disease pathogenesis. These computational models and resources can help investigate how CTCF-mediated cis-regulatory elements shape context-specific gene regulation in cell development and disease progression.

Mutation-Attention (MuAt): deep representation learning of somatic mutations for tumour typing and subtyping

BACKGROUND

Cancer genome sequencing enables accurate classification of tumours and tumour subtypes. However, prediction performance is still limited using exome-only sequencing and for tumour types with low somatic mutation burden such as many paediatric tumours. Moreover, the ability to leverage deep representation learning in discovery of tumour entities remains unknown.

METHODS

We introduce here Mutation-Attention (MuAt), a deep neural network to learn representations of simple and complex somatic alterations for prediction of tumour types and subtypes. In contrast to many previous methods, MuAt utilizes the attention mechanism on individual mutations instead of aggregated mutation counts.

RESULTS

We trained MuAt models on 2587 whole cancer genomes (24 tumour types) from the Pan-Cancer Analysis of Whole Genomes (PCAWG) and 7352 cancer exomes (20 types) from the Cancer Genome Atlas (TCGA). MuAt achieved prediction accuracy of 89% for whole genomes and 64% for whole exomes, and a top-5 accuracy of 97% and 90%, respectively. MuAt models were found to be well-calibrated and perform well in three independent whole cancer genome cohorts with 10,361 tumours in total. We show MuAt to be able to learn clinically and biologically relevant tumour entities including acral melanoma, SHH-activated medulloblastoma, SPOP-associated prostate cancer, microsatellite instability, POLE proofreading deficiency, and MUTYH-associated pancreatic endocrine tumours without these tumour subtypes and subgroups being provided as training labels. Finally, scrunity of MuAt attention matrices revealed both ubiquitous and tumour-type specific patterns of simple and complex somatic mutations.

CONCLUSIONS

Integrated representations of somatic alterations learnt by MuAt were able to accurately identify histological tumour types and identify tumour entities, with potential to impact precision cancer medicine.

Comprehensive multiomics analyses reveal pervasive involvement of aberrant cohesin binding in transcriptional and chromosomal disorder of cancer cells

Chromatin organization, whose malfunction causes various diseases including cancer, is fundamentally controlled by cohesin. While cancer cells have been found with mutated or misexpressed cohesin genes, there is no comprehensive survey about the presence and role of abnormal cohesin binding in cancer cells. Here, we systematically identified ∼1% of cohesin-binding sites (701-2,633) as cancer-aberrant binding sites of cohesin (CASs). We integrated CASs with large-scale transcriptomics, epigenomics, 3D genomics, and clinical information. CASs represent tissue-specific epigenomic signatures enriched for cancer-dysregulated genes with functional and clinical significance. CASs exhibited alterations in chromatin compartments, loops within topologically associated domains, and cis-regulatory elements, indicating that CASs induce dysregulated genes through misguided chromatin structure. Cohesin depletion data suggested that cohesin binding at CASs actively regulates cancer-dysregulated genes. Overall, our comprehensive investigation suggests that aberrant cohesin binding is an essential epigenomic signature responsible for dysregulated chromatin structure and transcription in cancer cells.

Detecting recurrent passenger mutations in melanoma by targeted UV damage sequencing

Sequencing of melanomas has identified hundreds of recurrent mutations in both coding and non-coding DNA. These include a number of well-characterized oncogenic driver mutations, such as coding mutations in the BRAF and NRAS oncogenes, and non-coding mutations in the promoter of telomerase reverse transcriptase (TERT). However, the molecular etiology and significance of most of these mutations is unknown. Here, we use a new method known as CPD-capture-seq to map UV-induced cyclobutane pyrimidine dimers (CPDs) with high sequencing depth and single nucleotide resolution at sites of recurrent mutations in melanoma. Our data reveal that many previously identified drivers and other recurrent mutations in melanoma occur at CPD hotspots in UV-irradiated melanocytes, often associated with an overlapping binding site of an E26 transformation-specific (ETS) transcription factor. In contrast, recurrent mutations in the promoters of a number of known or suspected cancer genes are not associated with elevated CPD levels. Our data indicate that a subset of recurrent protein-coding mutations are also likely caused by ETS-induced CPD hotspots. This analysis indicates that ETS proteins profoundly shape the mutation landscape of melanoma and reveals a method for distinguishing potential driver mutations from passenger mutations whose recurrence is due to elevated UV damage.

When 3D genome changes cause disease: the impact of structural variations in congenital disease and cancer

Large structural variations (SV) are a class of mutations that have long been known to cause a wide range of genetic diseases, from rare congenital disease to cancer. Many of these SVs do not directly disrupt disease-related genes and determining causal genotype-phenotype relationships has been challenging to disentangle in the past. This has started to change with our increased understanding of the 3D genome folding. The pathophysiologies of the different types of genetic diseases influence the type of SVs observed and their genetic consequences, and how these are connected to 3D genome folding. We propose guiding principles for interpreting disease-associated SVs based on our current understanding of 3D chromatin architecture and the gene-regulatory and physiological mechanisms disrupted in disease.

Prediction of CTCF loop anchor based on machine learning

Introduction: Various activities in biological cells are affected by three-dimensional genome structure. The insulators play an important role in the organization of higher-order structure. CTCF is a representative of mammalian insulators, which can produce barriers to prevent the continuous extrusion of chromatin loop. As a multifunctional protein, CTCF has tens of thousands of binding sites in the genome, but only a portion of them can be used as anchors of chromatin loops. It is still unclear how cells select the anchor in the process of chromatin looping.

Methods: In this paper, a comparative analysis is performed to investigate the sequence preference and binding strength of anchor and non-anchor CTCF binding sites. Furthermore, a machine learning model based on the CTCF binding intensity and DNA sequence is proposed to predict which CTCF sites can form chromatin loop anchors.

Results: The accuracy of the machine learning model that we constructed for predicting the anchor of the chromatin loop mediated by CTCF reached 0.8646. And we find that the formation of loop anchor is mainly influenced by the CTCF binding strength and binding pattern (which can be interpreted as the binding of different zinc fingers).

Discussion: In conclusion, our results suggest that The CTCF core motif and it’s flanking sequence may be responsible for the binding specificity. This work contributes to understanding the mechanism of loop anchor selection and provides a reference for the prediction of CTCF-mediated chromatin loops.

Effect of Single-Residue Mutations on CTCF Binding to DNA: Insights from Molecular Dynamics Simulations

In humans and other eukaryotes, DNA is condensed into chromatin fibers that are further wound into chromosomes. This organization allows regulatory elements in the genome, often distant from each other in the linear DNA, to interact and facilitate gene expression through regions known as topologically associating domains (TADs). CCCTC–binding factor (CTCF) is one of the major components of TAD formation and is responsible for recruiting a partner protein, cohesin, to perform loop extrusion and facilitate proper gene expression within TADs. Because single-residue CTCF mutations have been linked to the development of a variety of cancers in humans, we aim to better understand how these mutations affect the CTCF structure and its interaction with DNA. To this end, we compare all-atom molecular dynamics simulations of a wildtype CTCF–DNA complex to those of eight different cancer-linked CTCF mutant sequences. We find that most mutants have lower binding energies compared to the wildtype protein, leading to the formation of less stable complexes. Depending on the type and position of the mutation, this loss of stability can be attributed to major changes in the electrostatic potential, loss of hydrogen bonds between the CTCF and DNA, and/or destabilization of specific zinc fingers. Interestingly, certain mutations in specific fingers can affect the interaction with the DNA of other fingers, explaining why mere single mutations can impair CTCF function. Overall, these results shed mechanistic insights into experimental observations and further underscore CTCF’s importance in the regulation of chromatin architecture and gene expression.

Myoepithelial carcinoma of the parotid gland with a novel CTCF::NCOA2 fusion

We describe a case of a myoepithelial carcinoma of the superficial parotid gland in a 46-year-old male harboring a novel CTCF::NCOA2 gene fusion. To our knowledge, this novel gene fusion has not been described previously in myoepithelial carcinoma. A 46-year-old male patient presented with a mass involving the superficial left parotid gland with extension into the external auditory canal (EAC) and erosion of the conchal cartilage. Histologically, the neoplasm was composed of uniform spindled, epithelioid/ovoid cells arranged in cords and nests within hyalinized to myxoid stroma. On immunohistochemistry (IHC), the tumor cells demonstrated patchy and variable staining for low molecular weight cytokeratin (CAM5.2), pan-cytokeratin (OSCAR), and S-100. Overall, the morphological and immunohistochemical attributes supported a locally aggressive tumor of myoepithelial differentiation consistent with myoepithelial carcinoma. Molecular analysis using a custom 115-gene gene panel by targeted RNA sequencing, showed an in-frame CTCF::NCOA2 fusion. In addition to reporting this novel fusion in myoepithelial carcinoma, we also discuss relevant differential diagnosis, and provide a brief review of NCOA2 gene function in both normal and neoplastic contexts.

Strand Asymmetries Across Genomic Processes

Across biological systems, a number of genomic processes, including transcription, replication, DNA repair, and transcription factor binding, display intrinsic directionalities. These directionalities are reflected in the asymmetric distribution of nucleotides, motifs, genes, transposon integration sites, and other functional elements across the two complementary strands. Strand asymmetries, including GC skews and mutational biases, have shaped the nucleotide composition of diverse organisms. The investigation of strand asymmetries often serves as a method to understand underlying biological mechanisms, including protein binding preferences, transcription factor interactions, retrotransposition, DNA damage and repair preferences, transcription-replication collisions, and mutagenesis mechanisms. Research into this subject also enables the identification of functional genomic sites, such as replication origins and transcription start sites. Improvements in our ability to detect and quantify DNA strand asymmetries will provide insights into diverse functionalities of the genome, the contribution of different mutational mechanisms in germline and somatic mutagenesis, and our knowledge of genome instability and evolution, which all have significant clinical implications in human disease, including cancer. In this review, we describe key developments that have been made across the field of genomic strand asymmetries, as well as the discovery of associated mechanisms.

Distinct Mechanisms of Mismatch-Repair Deficiency Delineate Two Modes of Response to Anti-PD-1 Immunotherapy in Endometrial Carcinoma

Mismatch repair-deficient (MMRd) cancers have varied responses to immune-checkpoint blockade (ICB). We conducted a phase II clinical trial of the PD-1 inhibitor pembrolizumab in 24 patients with MMRd endometrial cancer (NCT02899793). Patients with mutational MMRd tumors (6 patients) had higher response rates and longer survival than those with epigenetic MMRd tumors (18 patients). Mutation burden was higher in tumors with mutational MMRd compared with epigenetic MMRd; however, within each category of MMRd, mutation burden was not correlated with ICB response. Pretreatment JAK1 mutations were not associated with primary resistance to pembrolizumab. Longitudinal single-cell RNA-seq of circulating immune cells revealed contrasting modes of antitumor immunity for mutational versus epigenetic MMRd cancers. Whereas effector CD8+ T cells correlated with regression of mutational MMRd tumors, activated CD16+ NK cells were associated with ICB-responsive epigenetic MMRd tumors. These data highlight the interplay between tumor-intrinsic and tumor-extrinsic factors that influence ICB response.

SIGNIFICANCE

The molecular mechanism of MMRd is associated with response to anti-PD-1 immunotherapy in endometrial carcinoma. Tumors with epigenetic MMRd or mutational MMRd are correlated with NK cell or CD8+ T cell-driven immunity, respectively. Classifying tumors by the mechanism of MMRd may inform clinical decision-making regarding cancer immunotherapy. This article is highlighted in the In This Issue feature, p. 247.

Alterations of cohesin complex genes in acute myeloid leukemia: differential co-mutations, clinical presentation and impact on outcome

Functional perturbations of the cohesin complex with subsequent changes in chromatin structure and replication are reported in a multitude of cancers including acute myeloid leukemia (AML). Mutations of its STAG2 subunit may predict unfavorable risk as recognized by the 2022 European Leukemia Net recommendations, but the underlying evidence is limited by small sample sizes and conflicting observations regarding clinical outcomes, as well as scarce information on other cohesion complex subunits. We retrospectively analyzed data from a multi-center cohort of 1615 intensively treated AML patients and identified distinct co-mutational patters for mutations of STAG2, which were associated with normal karyotypes (NK) and concomitant mutations in IDH2, RUNX1, BCOR, ASXL1, and SRSF2. Mutated RAD21 was associated with NK, mutated EZH2, KRAS, CBL, and NPM1. Patients harboring mutated STAG2 were older and presented with decreased white blood cell, bone marrow and peripheral blood blast counts. Overall, neither mutated STAG2, RAD21, SMC1A nor SMC3 displayed any significant, independent effect on clinical outcomes defined as complete remission, event-free, relapse-free or overall survival. However, we found almost complete mutual exclusivity of genetic alterations of individual cohesin subunits. This mutual exclusivity may be the basis for therapeutic strategies via synthetic lethality in cohesin mutated AML.

Multilevel view on chromatin architecture alterations in cancer

Chromosomes inside the nucleus are not located in the form of linear molecules. Instead, there is a complex multilevel genome folding that includes nucleosomes packaging, formation of chromatin loops, domains, compartments, and finally, chromosomal territories. Proper spatial organization play an essential role for the correct functioning of the genome, and is therefore dynamically changed during development or disease. Here we discuss how the organization of the cancer cell genome differs from the healthy genome at various levels. A better understanding of how malignization affects genome organization and long-range gene regulation will help to reveal the molecular mechanisms underlying cancer development and evolution.

Deep learning approaches for noncoding variant prioritization in neurodegenerative diseases

Determining how noncoding genetic variants contribute to neurodegenerative dementias is fundamental to understanding disease pathogenesis, improving patient prognostication, and developing new clinical treatments. Next generation sequencing technologies have produced vast amounts of genomic data on cell type-specific transcription factor binding, gene expression, and three-dimensional chromatin interactions, with the promise of providing key insights into the biological mechanisms underlying disease. However, this data is highly complex, making it challenging for researchers to interpret, assimilate, and dissect. To this end, deep learning has emerged as a powerful tool for genome analysis that can capture the intricate patterns and dependencies within these large datasets. In this review, we organize and discuss the many unique model architectures, development philosophies, and interpretation methods that have emerged in the last few years with a focus on using deep learning to predict the impact of genetic variants on disease pathogenesis. We highlight both broadly-applicable genomic deep learning methods that can be fine-tuned to disease-specific contexts as well as existing neurodegenerative disease research, with an emphasis on Alzheimer's-specific literature. We conclude with an overview of the future of the field at the intersection of neurodegeneration, genomics, and deep learning.

Untangling the roles of TOP2A and TOP2B in transcription and cancer

Type II topoisomerases (TOP2) are conserved regulators of chromatin topology that catalyze reversible DNA double-strand breaks (DSBs) and are essential for maintaining genomic integrity in diverse dynamic processes such as transcription, replication, and cell division. While controlled TOP2-mediated DSBs are an elegant solution to topological constraints of DNA, DSBs also contribute to the emergence of chromosomal translocations and mutations that drive cancer. The central importance of TOP2 enzymes as frontline chemotherapeutic targets is well known; however, their precise biological functions and impact in cancer development are still poorly understood. In this review, we provide an updated overview of TOP2A and TOP2B in the regulation of chromatin topology and transcription, and discuss the recent discoveries linking TOP2 activities with cancer pathogenesis.

The co-evolution of the genome and epigenome in colorectal cancer

Colorectal malignancies are a leading cause of cancer-related death1 and have undergone extensive genomic study2,3. However, DNA mutations alone do not fully explain malignant transformation4-7. Here we investigate the co-evolution of the genome and epigenome of colorectal tumours at single-clone resolution using spatial multi-omic profiling of individual glands. We collected 1,370 samples from 30 primary cancers and 8 concomitant adenomas and generated 1,207 chromatin accessibility profiles, 527 whole genomes and 297 whole transcriptomes. We found positive selection for DNA mutations in chromatin modifier genes and recurrent somatic chromatin accessibility alterations, including in regulatory regions of cancer driver genes that were otherwise devoid of genetic mutations. Genome-wide alterations in accessibility for transcription factor binding involved CTCF, downregulation of interferon and increased accessibility for SOX and HOX transcription factor families, suggesting the involvement of developmental genes during tumourigenesis. Somatic chromatin accessibility alterations were heritable and distinguished adenomas from cancers. Mutational signature analysis showed that the epigenome in turn influences the accumulation of DNA mutations. This study provides a map of genetic and epigenetic tumour heterogeneity, with fundamental implications for understanding colorectal cancer biology.

Super-enhancers in esophageal carcinoma: Transcriptional addictions and therapeutic strategies

The tumorigenesis of esophageal carcinoma arises from transcriptional dysregulation would become exceptionally dependent on specific regulators of gene expression, which could be preferentially attributed to the larger non-coding cis-regulatory elements, i.e. super-enhancers (SEs). SEs, large genomic regulatory entity in close genomic proximity, are underpinned by control cancer cell identity. As a consequence, the transcriptional addictions driven by SEs could offer an Achilles’ heel for molecular treatments on patients of esophageal carcinoma and other types of cancer as well. In this review, we summarize the recent findings about the oncogenic SEs upon which esophageal cancer cells depend, and discuss why SEs could be seen as the hallmark of cancer, how transcriptional dependencies driven by SEs, and what opportunities could be supplied based on this cancer-specific SEs.

CohesinDB: a comprehensive database for decoding cohesin-related epigenomes, 3D genomes and transcriptomes in human cells

Cohesin is a multifunctional protein responsible for transcriptional regulation and chromatin organization. Cohesin binds to chromatin at tens of thousands of distinct sites in a conserved or tissue-specific manner, whereas the function of cohesin varies greatly depending on the epigenetic properties of specific chromatin loci. Cohesin also extensively mediates cis-regulatory modules (CRMs) and chromatin loops. Even though next-generation sequencing technologies have provided a wealth of information on different aspects of cohesin, the integration and exploration of the resultant massive cohesin datasets are not straightforward. Here, we present CohesinDB (https://cohesindb.iqb.u-tokyo.ac.jp), a comprehensive multiomics cohesin database in human cells. CohesinDB includes 2043 epigenomics, transcriptomics and 3D genomics datasets from 530 studies involving 176 cell types. By integrating these large-scale data, CohesinDB summarizes three types of 'cohesin objects': 751 590 cohesin binding sites, 957 868 cohesin-related chromatin loops and 2 229 500 cohesin-related CRMs. Each cohesin object is annotated with locus, cell type, classification, function, 3D genomics and cis-regulatory information. CohesinDB features a user-friendly interface for browsing, searching, analyzing, visualizing and downloading the desired information. CohesinDB contributes a valuable resource for all researchers studying cohesin, epigenomics, transcriptional regulation and chromatin organization.

CTCF shapes chromatin structure and gene expression in health and disease

CCCTC-binding factor (CTCF) is an eleven zinc finger (ZF), multivalent transcriptional regulator, that recognizes numerous motifs thanks to the deployment of distinct combinations of its ZFs. The great majority of the ~50,000 genomic locations bound by the CTCF protein in a given cell type is intergenic, and a fraction of these sites overlaps with transcriptional enhancers. Furthermore, a proportion of the regions bound by CTCF intersect genes and promoters. This suggests multiple ways in which CTCF may impact gene expression. At promoters, CTCF can directly affect transcription. At more distal sites, CTCF may orchestrate interactions between regulatory elements and help separate eu- and heterochromatic areas in the genome, exerting a chromatin barrier function. In this review, we outline how CTCF contributes to the regulation of the three-dimensional structure of chromatin and the formation of chromatin domains. We discuss how CTCF binding and architectural functions are regulated. We examine the literature implicating CTCF in controlling gene expression in development and disease both by acting as an insulator and a factor facilitating regulatory elements to efficiently interact with each other in the nuclear space.

Recent Advances in Glioma Cancer Treatment: Conventional and Epigenetic Realms

Glioblastoma (GBM) is the most typical and aggressive form of primary brain tumor in adults, with a poor prognosis. Successful glioma treatment is hampered by ineffective medication distribution across the blood-brain barrier (BBB) and the emergence of drug resistance. Although a few FDA-approved multimodal treatments are available for glioblastoma, most patients still have poor prognoses. Targeting epigenetic variables, immunotherapy, gene therapy, and different vaccine- and peptide-based treatments are some innovative approaches to improve anti-glioma treatment efficacy. Following the identification of lymphatics in the central nervous system, immunotherapy offers a potential method with the potency to permeate the blood-brain barrier. This review will discuss the rationale, tactics, benefits, and drawbacks of current glioma therapy options in clinical and preclinical investigations.

Structural variations in cancer and the 3D genome

Structural variations (SVs) affect more of the cancer genome than any other type of somatic genetic alteration but difficulties in detecting and interpreting them have limited our understanding. Clinical cancer sequencing also increasingly aims to detect SVs, leading to a widespread necessity to interpret their biological and clinical relevance. Recently, analyses of large whole-genome sequencing data sets revealed features that impact rates of SVs across the genome in different cancers. A striking feature has been the extent to which, in both their generation and their influence on the selective fitness of cancer cells, SVs are more specific to individual cancer types than other genetic alterations such as single-nucleotide variants. This Perspective discusses how the folding of the 3D genome, and differences in its folding across cell types, affect observed SV rates in different cancer types as well as how SVs can impact cancer cell fitness.

Chromatin accessibility of primary human cancers ties regional mutational processes and signatures with tissues of origin

Somatic mutations in cancer genomes are associated with DNA replication timing (RT) and chromatin accessibility (CA), however these observations are based on normal tissues and cell lines while primary cancer epigenomes remain uncharacterised. Here we use machine learning to model megabase-scale mutation burden in 2,500 whole cancer genomes and 17 cancer types via a compendium of 900 CA and RT profiles covering primary cancers, normal tissues, and cell lines. CA profiles of primary cancers, rather than those of normal tissues, are most predictive of regional mutagenesis in most cancer types. Feature prioritisation shows that the epigenomes of matching cancer types and organ systems are often the strongest predictors of regional mutation burden, highlighting disease-specific associations of mutational processes. The genomic distributions of mutational signatures are also shaped by the epigenomes of matched cancer and tissue types, with SBS5/40, carcinogenic and unknown signatures most accurately predicted by our models. In contrast, fewer associations of RT and regional mutagenesis are found. Lastly, the models highlight genomic regions with overrepresented mutations that dramatically exceed epigenome-derived expectations and show a pan-cancer convergence to genes and pathways involved in development and oncogenesis, indicating the potential of this approach for coding and non-coding driver discovery. The association of regional mutational processes with the epigenomes of primary cancers suggests that the landscape of passenger mutations is predominantly shaped by the epigenomes of cancer cells after oncogenic transformation.