bims-ectoca Biomed News
on Epigenetic control of tolerance in cancer
Issue of 2021‒08‒08
thirteen papers selected by
Ankita Daiya
BITS Pilani


  1. J Thorac Oncol. 2021 Aug 02. pii: S1556-0864(21)02332-7. [Epub ahead of print]
      A minor population of cancer cells may evade cell death from chemotherapy and targeted therapy by entering a reversible slow proliferation state known as the drug tolerant persister (DTP) state. This DTP state can allow cancer cells to survive drug therapy long enough for additional mechanisms of acquired drug resistance to develop. Thus, cancer persistence is a major obstacle to curing cancers, where insight into the biology of DTP cells and therapeutic strategies targeting this mechanism can have significant clinical implications. There is emerging evidence that DTP cells adapt to new environments through epigenomic modification, transcriptomic regulation, flexible energy metabolism, and interactions with the tumor microenvironment. Herein, we review and discuss the various proposed mechanisms of cancer persister cells and the molecular features underlying the DTP state, with insights into the potential therapeutic strategies to conquer DTP cells and prevent cancer recurrence or therapeutic failures.
    Keywords:  Drug persisters; EGFR TKI; chemotherapy; drug resistance; targeted therapy; tumor dormancy
    DOI:  https://doi.org/10.1016/j.jtho.2021.07.017
  2. IEEE J Biomed Health Inform. 2021 Aug 04. PP
      Different cancer patients may respond differently to cancer treatment due to the heterogeneity of cancer. It is an urgent task to develop an efficient computational method to identify drug responses in different cell lines, which guides us to design personalized therapy for an individual patient. Hence, we propose an end-to-end algorithm, namely MOFGCN, to predict drug response in cell lines based on Multi-Omics Fusion and Graph Convolution Network. MOFGCN first fuses multiple omics data to calculate the cell line similarity and then constructs a heterogeneous network by combining the cell line similarity, drug similarity, and the known cell line-drug associations. Secondly, it learns the latent features for cancer cell lines and drugs by performing graph convolution operations on the heterogeneous network. Finally, MOFGCN applies the linear correlation coefficient to reconstruct the cancer cell line-drug correlation matrix to predict drug sensitivity. To our knowledge, this is the first attempt to combine graph convolutional neural network and linear correlation coefficient for this significant task. We performed extensive evaluation experiments on the Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (CCLE) databases to validate MOFGCNs performance. The experimental results show that MOFGCN is superior to the state-of-the-art algorithms in predicting missing drug responses. It also leads to higher performance in predicting drug responses for new cell lines, new drugs, and targeted drugs.
    DOI:  https://doi.org/10.1109/JBHI.2021.3102186
  3. Brief Bioinform. 2021 Aug 05. pii: bbab295. [Epub ahead of print]
      Single-cell RNA sequencing (scRNA-seq) technologies facilitate the characterization of transcriptomic landscapes in diverse species, tissues, and cell types with unprecedented molecular resolution. In order to evaluate various biological hypotheses using high-dimensional single-cell gene expression data, most computational and statistical methods depend on a gene feature selection step to identify genes with high biological variability and reduce computational complexity. Even though many gene selection methods have been developed for scRNA-seq analysis, there lacks a systematic comparison of the assumptions, statistical models, and selection criteria used by these methods. In this article, we summarize and discuss 17 computational methods for selecting gene features in unsupervised analysis of single-cell gene expression data, with unified notations and statistical frameworks. Our discussion provides a useful summary to help practitioners select appropriate methods based on their assumptions and applicability, and to assist method developers in designing new computational tools for unsupervised learning of scRNA-seq data.
    Keywords:  feature selection; highly variable genes; single-cell genomics; unsupervised learning
    DOI:  https://doi.org/10.1093/bib/bbab295
  4. Int J Mol Sci. 2021 Aug 03. pii: 8337. [Epub ahead of print]22(15):
      Enhancers regulate multiple genes via higher-order chromatin structures, and they further affect cancer progression. Epigenetic changes in cancer cells activate several cancer-specific enhancers that are silenced in normal cells. These cancer-specific enhancers are potential therapeutic targets of cancer. However, the functions and regulation networks of colorectal-cancer-specific enhancers are still unknown. In this study, we profile colorectal-cancer-specific enhancers and reveal their regulation network through the analysis of HiChIP data that were derived from a colorectal cancer cell line and Hi-C and RNA-seq data that were derived from tissue samples by in silico analysis and in vitro experiments. Enhancer-promoter loops in colorectal cancer cells containing colorectal-cancer-specific enhancers are involved in more than 50% of the topological associated domains (TADs) changed in colorectal cancer cells compared to normal colon cells. In addition, colorectal-cancer-specific enhancers interact with 152 genes that are significantly and highly expressed in colorectal cancer cells. These colorectal-cancer-specific enhancer target genes include ITGB4, RECQL4, MSLN, and GDF15. We propose that the regulation network of colorectal-cancer-specific enhancers plays an important role in the progression of colorectal cancer.
    Keywords:  Hi-C; HiChIP; TAD; colorectal-cancer-specific enhancer; long-range interaction
    DOI:  https://doi.org/10.3390/ijms22158337
  5. Biochem (Lond). 2021 Feb;43(1): 14-19
      Symmetry and asymmetry are fundamental aspects of life. Most cells within a multicellular organism contain the same genetic information, passed on from one originating cell - the zygote; however, these cells can take on a variety of different identities, with diverse appearances and functions. A fundamental question in biology ponders how cells containing identical DNA content can take on different cell identities. Epigenetic mechanisms could be the symmetry breaking factor, as they are able to change gene expression in cells without changing the DNA sequence. While the process of duplication and segregation of DNA during cell division has been well studied, it is less understood how the epigenetic information is established and inherited in the cells within a multicellular organism. Studies of asymmetric stem cell division, where a stem cell division gives rise to a self-renewed stem cell and a differentiating daughter cell, provides a model to study how epigenetic information is maintained or changed to produce daughter cells with identical genetic information but distinct cell fates. Here, we discuss findings and ideas of how epigenetic information is maintained or changed during asymmetric cell division and the importance of this asymmetry in influencing cell fate.
    DOI:  https://doi.org/10.1042/bio_2020_110
  6. Nat Methods. 2021 Aug 02.
      Understanding intratumoral heterogeneity-the molecular variation among cells within a tumor-promises to address outstanding questions in cancer biology and improve the diagnosis and treatment of specific cancer subtypes. Single-cell analyses, especially RNA sequencing and other genomics modalities, have been transformative in revealing novel biomarkers and molecular regulators associated with tumor growth, metastasis and drug resistance. However, these approaches fail to provide a complete picture of tumor biology, as information on cellular location within the tumor microenvironment is lost. New technologies leveraging multiplexed fluorescence, DNA, RNA and isotope labeling enable the detection of tens to thousands of cancer subclones or molecular biomarkers within their native spatial context. The expeditious growth in these techniques, along with methods for multiomics data integration, promises to yield a more comprehensive understanding of cell-to-cell variation within and between individual tumors. Here we provide the current state and future perspectives on the spatial technologies expected to drive the next generation of research and diagnostic and therapeutic strategies for cancer.
    DOI:  https://doi.org/10.1038/s41592-021-01203-6
  7. F1000Res. 2021 ;10 182
      Background: The vault RNAs (vtRNAs) are a class of 84-141-nt eukaryotic non-coding RNAs transcribed by RNA polymerase III, associated to the ribonucleoprotein complex known as vault particle. Of the four human vtRNA genes, vtRNA1-1, vtRNA1-2 and vtRNA1-3, clustered at locus 1, are integral components of the vault particle, while vtRNA2-1 is a more divergent homologue located in a second locus. Gene expression studies of vtRNAs in large cohorts have been hindered by their unsuccessful sequencing using conventional transcriptomic approaches. Methods: VtRNA expression in The Cancer Genome Atlas (TCGA) Pan-Cancer cohort was estimated using the genome-wide DNA methylation and chromatin accessibility data (ATAC-seq) of their genes as surrogate variables. The association between vtRNA expression and patient clinical outcome, immune subtypes and transcriptionally co-regulated gene programs was analyzed in the dataset. Results: VtRNA1-1 has the most accessible chromatin, followed by vtRNA1-2, vtRNA2-1 and vtRNA1-3. Although the vtRNAs are co-regulated by transcription factors related to viral infection, vtRNA2-1 is the most independently regulated homologue. VtRNA1-1 and vtRNA1-3 chromatin status does not significantly change in cancer tissues. Meanwhile, vtRNA2-1 and vtRNA1-2 expression is widely deregulated in neoplastic tissues and its alteration is compatible with a broad oncogenic role for vtRNA1-2, and both tumor suppressor and oncogenic functions for vtRNA2-1. Yet, vtRNA1-1, vtRNA1-2 and vtRNA2-1 promoter DNA methylation predicts a shorter patient overall survival cancer-wide. In addition, gene ontology analyses of vtRNAs co-regulated genes identify a chromosome regulatory domain, epithelial differentiation, immune and thyroid cancer gene sets for specific vtRNAs. Furthermore, vtRNA expression patterns are associated with cancer immune subtypes and vtRNA1-2 expression is positively associated with cell proliferation and wound healing. Conclusions: Our study presents the landscape of vtRNA expression cancer-wide, identifying co-regulated gene networks and ontological pathways associated with the different vtRNA genes that may account for their diverse roles in cancer.
    Keywords:  DNA methylation; TCGA; cancer; chromatin accessibility; mir-886; nc886; vault RNA; vtRNA1-1; vtRNA1-2; vtRNA1-3; vtRNA2-1
    DOI:  https://doi.org/10.12688/f1000research.28510.1
  8. Nat Rev Mol Cell Biol. 2021 Aug 02.
      Gene regulation requires the dynamic coordination of hundreds of regulatory factors at precise genomic and RNA targets. Although many regulatory factors have specific affinity for their nucleic acid targets, molecular diffusion and affinity models alone cannot explain many of the quantitative features of gene regulation in the nucleus. One emerging explanation for these quantitative properties is that DNA, RNA and proteins organize within precise, 3D compartments in the nucleus to concentrate groups of functionally related molecules. Recently, nucleic acids and proteins involved in many important nuclear processes have been shown to engage in cooperative interactions, which lead to the formation of condensates that partition the nucleus. In this Review, we discuss an emerging perspective of gene regulation, which moves away from classic models of stoichiometric interactions towards an understanding of how spatial compartmentalization can lead to non-stoichiometric molecular interactions and non-linear regulatory behaviours. We describe key mechanisms of nuclear compartment formation, including emerging roles for non-coding RNAs in facilitating their formation, and discuss the functional role of nuclear compartments in transcription regulation, co-transcriptional and post-transcriptional RNA processing, and higher-order chromatin regulation. More generally, we discuss how compartmentalization may explain important quantitative aspects of gene regulation.
    DOI:  https://doi.org/10.1038/s41580-021-00387-1
  9. Oncogene. 2021 Aug 04.
      The Polycomb group (PcG) protein Enhancer of Zeste Homolog 2 (EZH2) is one of the three core subunits of the Polycomb Repressive Complex 2 (PRC2). It harbors histone methyltransferase activity (MTase) that specifically catalyze histone 3 lysine 27 (H3K27) methylation on target gene promoters. As such, PRC2 are epigenetic silencers that play important roles in cellular identity and embryonic stem cell maintenance. In the past two decades, mounting evidence supports EZH2 mutations and/or over-expression in a wide array of hematological cancers and solid tumors, including prostate cancer. Further, EZH2 is among the most upregulated genes in neuroendocrine prostate cancers, which become abundant due to the clinical use of high-affinity androgen receptor pathway inhibitors. While numerous studies have reported epigenetic functions of EZH2 that inhibit tumor suppressor genes and promote tumorigenesis, discordance between EZH2 and H3K27 methylation has been reported. Further, enzymatic EZH2 inhibitors have shown limited efficacy in prostate cancer, warranting a more comprehensive understanding of EZH2 functions. Here we first review how canonical functions of EZH2 as a histone MTase are regulated and describe the various mechanisms of PRC2 recruitment to the chromatin. We further outline non-histone substrates of EZH2 and discuss post-translational modifications to EZH2 itself that may affect substrate preference. Lastly, we summarize non-canonical functions of EZH2, beyond its MTase activity and/or PRC2, as a transcriptional cofactor and discuss prospects of its therapeutic targeting in prostate cancer.
    DOI:  https://doi.org/10.1038/s41388-021-01982-4
  10. Hortic Res. 2021 Aug 03. 8(1): 187
      Watercore is a physiological disorder in apple (Malus × domestica Borkh.) fruits that appears as water-soaked tissues adjacent to the vascular core, although there is little information on what exactly occurs at cell level in the watercored apples, particularly from the viewpoint of cell water relations. By combining picolitre pressure-probe electrospray-ionization mass spectrometry (picoPPESI-MS) with freezing point osmometry and vapor pressure osmometry, changes in cell water status and metabolisms were spatially assayed in the same fruit. In the watercored fruit, total soluble solid was lower in the watercore region than the normal outer parenchyma region, but there was no spatial difference in the osmotic potentials determined with freezing point osmometry. Importantly, a disagreement between the osmotic potentials determined with two methods has been observed in the watercore region, indicating the presence of significant volatile compounds in the cellular fluids collected. In the watercored fruit, cell turgor varied across flesh, and a steeper water potential gradient has been established from the normal outer parenchyma region to the watercore region, retaining the potential to transport water to the watercore region. Site-specific analysis using picoPPESI-MS revealed that together with a reduction in turgor, remarkable metabolic modifications through fermentation have occurred at the border, inducing greater production of watercore-related volatile compounds, such as alcohols and esters, compared with other regions. Because alcohols including ethanol have low reflection coefficients, it is very likely that these molecules would have rapidly penetrated membranes to accumulate in apoplast to fill. In addition to the water potential gradient detected here, this would physically contribute to the appearance with high tissue transparency and changes in colour differences. Therefore, it is concluded that these spatial changes in cell water relations are closely associated with watercore symptoms as well as with metabolic alterations.
    DOI:  https://doi.org/10.1038/s41438-021-00603-1
  11. Cancers (Basel). 2021 Jul 31. pii: 3869. [Epub ahead of print]13(15):
      Keratins are the main identification markers of circulating tumor cells (CTCs); however, whether their deregulation is associated with the metastatic process is largely unknown. Previously we have shown by in silico analysis that keratin 16 (KRT16) mRNA upregulation might be associated with more aggressive cancer. Therefore, in this study, we investigated the biological role and the clinical relevance of K16 in metastatic breast cancer. By performing RT-qPCR, western blot, and immunocytochemistry, we investigated the expression patterns of K16 in metastatic breast cancer cell lines and evaluated the clinical relevance of K16 expression in CTCs of 20 metastatic breast cancer patients. High K16 protein expression was associated with an intermediate mesenchymal phenotype. Functional studies showed that K16 has a regulatory effect on EMT and overexpression of K16 significantly enhanced cell motility (p < 0.001). In metastatic breast cancer patients, 64.7% of the detected CTCs expressed K16, which was associated with shorter relapse-free survival (p = 0.0042). Our findings imply that K16 is a metastasis-associated protein that promotes EMT and acts as a positive regulator of cellular motility. Furthermore, determining K16 status in CTCs provides prognostic information that helps to identify patients whose tumors are more prone to metastasize.
    Keywords:  circulating tumor cells (CTCs); epithelial to mesenchymal transition (EMT); keratin 16 (KRT16)
    DOI:  https://doi.org/10.3390/cancers13153869
  12. Biochem Soc Trans. 2021 Aug 02. pii: BST20210758. [Epub ahead of print]
      Different classes of non-coding RNA (ncRNA) influence the organization of chromatin. Imprinted gene domains constitute a paradigm for exploring functional long ncRNAs (lncRNAs). Almost all express an lncRNA in a parent-of-origin dependent manner. The mono-allelic expression of these lncRNAs represses close by and distant protein-coding genes, through diverse mechanisms. Some control genes on other chromosomes as well. Interestingly, several imprinted chromosomal domains show a developmentally regulated, chromatin-based mechanism of imprinting with apparent similarities to X-chromosome inactivation. At these domains, the mono-allelic lncRNAs show a relatively stable, focal accumulation in cis. This facilitates the recruitment of Polycomb repressive complexes, lysine methyltranferases and other nuclear proteins - in part through direct RNA-protein interactions. Recent chromosome conformation capture and microscopy studies indicate that the focal aggregation of lncRNA and interacting proteins could play an architectural role as well, and correlates with close positioning of target genes. Higher-order chromatin structure is strongly influenced by CTCF/cohesin complexes, whose allelic association patterns and actions may be influenced by lncRNAs as well. Here, we review the gene-repressive roles of imprinted non-coding RNAs, particularly of lncRNAs, and discuss emerging links with chromatin architecture.
    Keywords:  CTCF; chromatin; epigenetics; genomic imprinting; non-coding RNA
    DOI:  https://doi.org/10.1042/BST20210758
  13. J Cancer. 2021 ;12(17): 5220-5230
      Breast cancer is one of the most common causes of female death globally. Numerous clinical drugs for breast cancer have been developed, but the unsatisfactory, inevitable side effects and drug resistance are the emerging threatens. Therefore, it is necessary to investigate the comprehensive mechanism of breast cancer. Enhancer of zeste homolog 2 (EZH2) is a candidate oncogenic driver in diverse cancers, such as breast cancer. The canonical role of EZH2 has been vastly investigated, but the non-canonical function of EZH2 in breast cancer remains unclear. Here, we demonstrated that EZH2 exacerbated breast cancer in non-canonical manner by methylating STAT3. EZH2 over-expressed in breast cancer patients and regulated STAT3 post-transcriptionally according to TCGA datasets. Chemical and genetic inhibition of EZH2 impeded proliferation and migration of breast cancer cells, which may be partially rescued by STAT3 over-expression. EZH2 physically interacted with STAT3 and methylated STAT3 directly, resulting in increased nuclear localization and chromatin of STAT3. Furthermore, the mutation of STAT3 methylation site, targeted by EZH2, impeded the transcriptional activity of STAT3. Eventually, disturbed STAT3 methylation by EZH2 in animal model showed decreased breast cancer growth. These data confirm that EZH2 exacerbates breast cancer by methylating STAT3 directly, and thus providing a promising therapeutic target for breast cancer.
    Keywords:  Breast cancer; EZH2; Methylation; STAT3
    DOI:  https://doi.org/10.7150/jca.50675