Perturbing Enhancer Activity in Cancer Therapy

Hamdan, Feda H.; Johnsen, Steven A.

doi:10.3390/cancers11050634

Cited by 22 publications

(13 citation statements)

References 203 publications

(221 reference statements)

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“…In this section, we will therefore concentrate mainly on enhancer inhibitors affecting eRNA production to elucidate their potential therapeutic effects on inflammatory immune diseases and even cancer. The eRNA-related agents in cancer have been previously reviewed, including bromodomain and extra-terminal (BET) inhibitors, cyclin-dependent kinases (CDKs), HAT inhibitors and HDAC inhibitors ( 33 , 34 , 177 ). Since inhibitors that fully target eRNAs in inflammatory immune-related diseases have been rarely studied, the combined inhibitors of eRNAs and active enhancers, which produce eRNAs, have been summarized along with their therapeutic potential in inflammatory immune diseases in Figure 4 .…”

Section: Resultsmentioning

confidence: 99%

“…Furthermore, enhancer transcription analyses and eRNA generation processes revealed that TF modulators, HAT inhibitors and HDAC inhibitors influence eRNA and mRNA production by modulating enhancer epigenetic characteristics ( 177 ) ( Figure 4 ). HATs, such as p300-CBP, enable histone tail acetylation modifications ( 195 ), whereas polycomb repressive complex (PRC) mediates histone methylation.…”

Section: Resultsmentioning

confidence: 99%

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Inflammatory Immune-Associated eRNA: Mechanisms, Functions and Therapeutic Prospects

Wan

Meng

et al. 2022

Front. Immunol.

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The rapid development of multiple high-throughput sequencing technologies has made it possible to explore the critical roles and mechanisms of functional enhancers and enhancer RNAs (eRNAs). The inflammatory immune response, as a fundamental pathological process in infectious diseases, cancers and immune disorders, coordinates the balance between the internal and external environment of the organism. It has been shown that both active enhancers and intranuclear eRNAs are preferentially expressed over inflammation-related genes in response to inflammatory stimuli, suggesting that enhancer transcription events and their products influence the expression and function of inflammatory genes. Therefore, in this review, we summarize and discuss the relevant inflammatory roles and regulatory mechanisms of eRNAs in inflammatory immune cells, non-inflammatory immune cells, inflammatory immune diseases and tumors, and explore the potential therapeutic effects of enhancer inhibitors affecting eRNA production for diseases with inflammatory immune responses.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Inflammatory Immune-Associated eRNA: Mechanisms, Functions and Therapeutic Prospects

Wan

Meng

et al. 2022

Front. Immunol.

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“…Recent studies have linked nucleotide variations in enhancer-associated chromatin-modifying components to a number of phenotypic changes [ 11 , 12 ]. As reported, the absence of a SE can lead to under-expression of cancer associated genes and has profound effects on certain oncogenic properties [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

“…Cohen et al indicated that the change of epigenetic characteristics on enhancer elements is an important factor driving the formation of human colorectal cancer [ 12 ]. Accordingly, targeting aberrant enhancer components has become an effective therapeutic strategy on various cancers [ 8 , 11 ]. However, tremendous efforts remain to be invested to further clarify the mechanisms underlying enhancer-mediated processes in cancer and other diseases [ 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

iEnhancer-GAN: A Deep Learning Framework in Combination with Word Embedding and Sequence Generative Adversarial Net to Identify Enhancers and Their Strength

Zhang

2021

IJMS

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As critical components of DNA, enhancers can efficiently and specifically manipulate the spatial and temporal regulation of gene transcription. Malfunction or dysregulation of enhancers is implicated in a slew of human pathology. Therefore, identifying enhancers and their strength may provide insights into the molecular mechanisms of gene transcription and facilitate the discovery of candidate drug targets. In this paper, a new enhancer and its strength predictor, iEnhancer-GAN, is proposed based on a deep learning framework in combination with the word embedding and sequence generative adversarial net (Seq-GAN). Considering the relatively small training dataset, the Seq-GAN is designed to generate artificial sequences. Given that each functional element in DNA sequences is analogous to a “word” in linguistics, the word segmentation methods are proposed to divide DNA sequences into “words”, and the skip-gram model is employed to transform the “words” into digital vectors. In view of the powerful ability to extract high-level abstraction features, a convolutional neural network (CNN) architecture is constructed to perform the identification tasks, and the word vectors of DNA sequences are vertically concatenated to form the embedding matrices as the input of the CNN. Experimental results demonstrate the effectiveness of the Seq-GAN to expand the training dataset, the possibility of applying word segmentation methods to extract “words” from DNA sequences, the feasibility of implementing the skip-gram model to encode DNA sequences, and the powerful prediction ability of the CNN. Compared with other state-of-the-art methods on the training dataset and independent test dataset, the proposed method achieves a significantly improved overall performance. It is anticipated that the proposed method has a certain promotion effect on enhancer related fields.

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“…Alterations in chromatin, including changes in histone modifications or their modifying enzymes or changes in the expression or activity of chromatin remodelers due to genetic alterations, also frequently occurs in cancer, but are more poorly understood [11,12]. To date, most studies examining changes in histone modifications have largely been performed in cultured cells, precluding a clear interpretation of the clinical importance of these analyses.…”

Section: Introductionmentioning

confidence: 99%

Epigenome Mapping Identifies Tumor-Specific Gene Expression in Primary Rectal Cancer

Flebbe¹,

Hamdan

Kari³

et al. 2019

Cancers

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Epigenetic alterations play a central role in cancer development and progression. The acetylation of histone 3 at lysine 27 (H3K27ac) specifically marks active genes. While chromatin immunoprecipitation (ChIP) followed by next-generation sequencing (ChIP-seq) analyses are commonly performed in cell lines, only limited data are available from primary tumors. We therefore examined whether cancer-specific alterations in H3K27ac occupancy can be identified in primary rectal cancer. Tissue samples from primary rectal cancer and matched mucosa were obtained. ChIP-seq for H3K27ac was performed and differentially occupied regions were identified. The expression of selected genes displaying differential occupancy between tumor and mucosa were examined in gene expression data from an independent patient cohort. Differential expression of four proteins was further examined by immunohistochemistry. ChIP-seq for H3K27ac in primary rectal cancer and matched mucosa was successfully performed and revealed differential binding on 44 regions. This led to the identification of genes with increased H3K27ac, i.e., RIPK2, FOXQ1, KRT23, and EPHX4, which were also highly upregulated in primary rectal cancer in an independent dataset. The increased expression of these four proteins was confirmed by immunohistochemistry. This study demonstrates the feasibility of ChIP-seq-based epigenome mapping of primary rectal cancer and confirms the value of H3K27ac occupancy to predict gene expression differences.

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Perturbing Enhancer Activity in Cancer Therapy

Cited by 22 publications

References 203 publications

Inflammatory Immune-Associated eRNA: Mechanisms, Functions and Therapeutic Prospects

Inflammatory Immune-Associated eRNA: Mechanisms, Functions and Therapeutic Prospects

iEnhancer-GAN: A Deep Learning Framework in Combination with Word Embedding and Sequence Generative Adversarial Net to Identify Enhancers and Their Strength

Epigenome Mapping Identifies Tumor-Specific Gene Expression in Primary Rectal Cancer

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