bims-ectoca Biomed News
on Epigenetic control of tolerance in cancer
Issue of 2021–12–05
ten papers selected by
Ankita Daiya, Birla Institute of Technology and Science
  1. Mitochondrial homeostasis is maintained in the absence of autophagy.
  2. Construction and Validation of a Potent Epigenetic Modification-Related Prognostic Signature for Osteosarcoma Patients.
  3. Protocol for scChaRM-seq: Simultaneous profiling of gene expression, DNA methylation, and chromatin accessibility in single cells.
  4. Master lineage transcription factors anchor trans mega transcriptional complexes at highly accessible enhancer sites to promote long-range chromatin clustering and transcription of distal target genes.
  5. Epigenetic condensates regulate chromatin activity and tumorigenesis.
  6. Single cell imaging-based chromatin biomarkers for tumor progression.
  7. Sema4D/Plexin-B1 promotes the progression of osteosarcoma cells by activating Pyk2-PI3K-AKT pathway.
  8. Simplifying cancer: binary pan-cancer superclasses stratified by opposite YAP/TEAD effects.
  9. Identification of N6-methylandenosine related LncRNAs biomarkers associated with the overall survival of osteosarcoma.
  10. Identification of key genes as predictive biomarkers for osteosarcoma metastasis using translational bioinformatics.
  1. Mol Cell Oncol. 2021 ;8(5): 1984162
    Mitochondrial homeostasis is maintained in the absence of autophagy.
    Christina G Towers.
      Autophagy is a central recycling process, and it plays a complex role in cancer. We discovered that when autophagy is blocked, cancer cells compensate by increasing mitochondrial-derived vesicles. However, there are many unanswered questions remaining, particularly in the context of the dual roles of autophagy in cancer.
    Keywords:  Autophagy; cancer; mitochondria; mitochondrial derived vesicles; mitophagy
    DOI:  https://doi.org/10.1080/23723556.2021.1984162
  2. J Oncol. 2021 ;2021 2719172
    Construction and Validation of a Potent Epigenetic Modification-Related Prognostic Signature for Osteosarcoma Patients.
    Siyu Liu, Bing Wu, Xiaomin Li, Lulu Zhao, Wen Wu, Songtao Ai.
       Background: Increasing evidence has shown that tumorigenesis correlates with aberrant epigenetic factors, such as DNA methylation, histone modification, RNA m6A modification, RNA binding proteins, and transcription factors. However, it is unclear that how epigenetic genes linked with alteration contribute to osteosarcoma's incidence and clinical prognosis. We developed an epigenetic modification-related prognostic model that may improve the diagnosis and prognosis of osteosarcoma.
    Methods: We investigated the epigenetic modification-associated genes and their clinical significance in osteosarcoma in this research. Our gene transcriptome data were obtained from the TARGET database and the GEO database. Bioinformatics techniques were used to investigate their functionalities. The diagnostic and prognostic models were constructed using univariate and multivariate Cox regression. In addition, we developed a nomogram indicating the practicability of the prognostic model described above.
    Results: A risk score model constructed based on four epigenetic modification-related genes (MYC, TERT, EIF4E3, and RBM34) can effectively predict the prognosis of patients with osteosarcoma. Based on the risk score and clinical features, we constructed a nomogram.
    Conclusion: Epigenetic modification-related genes have been identified as important prognostic markers that may assist in osteosarcoma therapy therapeutic decision-making.
    DOI:  https://doi.org/10.1155/2021/2719172
  3. STAR Protoc. 2021 Dec 17. 2(4): 100972
    Protocol for scChaRM-seq: Simultaneous profiling of gene expression, DNA methylation, and chromatin accessibility in single cells.
    Rui Yan, Xin Cheng, Fan Guo.
      Single-cell multi-omics sequencing technology can infer cell heterogeneity and reveal relationships across molecular layers. Combining single-cell RNA sequencing, DNA methylation, and chromatin accessibility allows a multimodal understanding of cell function and epigenetic regulation within individual cells. Here, we offer a protocol to perform scChaRM-seq (single-cell chromatin accessibility, RNA barcoding, and DNA methylation sequencing), which has been applied to study de novo DNA methylation and its relationship with transcription and chromatin accessibility in single human oocytes. For complete details on the use and execution of this protocol, please refer to Yan et al. (2021).
    Keywords:  Gene Expression; Genomics; Molecular Biology; RNAseq; Sequencing; Single Cell
    DOI:  https://doi.org/10.1016/j.xpro.2021.100972
  4. Nucleic Acids Res. 2021 Nov 24. pii: gkab1105. [Epub ahead of print]
    Master lineage transcription factors anchor trans mega transcriptional complexes at highly accessible enhancer sites to promote long-range chromatin clustering and transcription of distal target genes.
    Shannon M White, Michael P Snyder, Chunling Yi.
      The term 'super enhancers' (SE) has been widely used to describe stretches of closely localized enhancers that are occupied collectively by large numbers of transcription factors (TFs) and co-factors, and control the transcription of highly-expressed genes. Through integrated analysis of >600 DNase-seq, ChIP-seq, GRO-seq, STARR-seq, RNA-seq, Hi-C and ChIA-PET data in five human cancer cell lines, we identified a new class of autonomous SEs (aSEs) that are excluded from classic SE calls by the widely used Rank Ordering of Super-Enhancers (ROSE) method. TF footprint analysis revealed that compared to classic SEs and regular enhancers, aSEs are tightly bound by a dense array of master lineage TFs, which serve as anchors to recruit additional TFs and co-factors in trans. In addition, aSEs are preferentially enriched for Cohesins, which likely involve in stabilizing long-distance interactions between aSEs and their distal target genes. Finally, we showed that aSEs can be reliably predicted using a single DNase-seq data or combined with Mediator and/or P300 ChIP-seq. Overall, our study demonstrates that aSEs represent a unique class of functionally important enhancer elements that distally regulate the transcription of highly expressed genes.
    DOI:  https://doi.org/10.1093/nar/gkab1105
  5. Mol Cell Oncol. 2021 ;8(5): 1997040
    Epigenetic condensates regulate chromatin activity and tumorigenesis.
    Bi Shi, Wei Li, Hao Jiang.
      Alterations of epigenetic modulators are extensively associated with cancer, but their key molecular activities in cancer regulation are often unclear. We discovered that lysine demethylase 6A (KDM6A, also known as UTX) suppresses cancer by forming liquid-like condensates with lysine methyltransferase 2D (KMT2D, also known as MLL4) and regulating chromatin activity at multiple levels.
    Keywords:  KDM6A; Phase separation; UTX; chromatin; condensates; epigenetic
    DOI:  https://doi.org/10.1080/23723556.2021.1997040
  6. Sci Rep. 2021 Nov 29. 11(1): 23041
    Single cell imaging-based chromatin biomarkers for tumor progression.
    Saradha Venkatachalapathy, Doorgesh S Jokhun, Madhavi Andhari, G V Shivashankar.
      Tumour progression within the tissue microenvironment is accompanied by complex biomechanical alterations of the extracellular environment. While histopathology images provide robust biochemical markers for tumor progression in clinical settings, a quantitative single cell score using nuclear morphology and chromatin organization integrated with the long range mechanical coupling within the tumor microenvironment is missing. We propose that the spatial chromatin organization in individual nuclei characterises the cell state and their alterations during tumor progression. In this paper, we first built an image analysis pipeline and implemented it to classify nuclei from patient derived breast tissue biopsies of various cancer stages based on their nuclear and chromatin features. Replacing H&E with DNA binding dyes such as Hoescht stained tissue biopsies, we improved the classification accuracy. Using the nuclear morphology and chromatin organization features, we constructed a pseudo-time model to identify the chromatin state changes that occur during tumour progression. This enabled us to build a single-cell mechano-genomic score that characterises the cell state during tumor progression from a normal to a metastatic state. To gain further insights into the alterations in the local tissue microenvironments, we also used the nuclear orientations to identify spatial neighbourhoods that have been posited to drive tumor progression. Collectively, we demonstrate that image-based single cell chromatin and nuclear features are important single cell biomarkers for phenotypic mapping of tumor progression.
    DOI:  https://doi.org/10.1038/s41598-021-02441-6
  7. J Musculoskelet Neuronal Interact. 2021 Dec 01. 21(4): 577-583
    Sema4D/Plexin-B1 promotes the progression of osteosarcoma cells by activating Pyk2-PI3K-AKT pathway.
    Changhui Li, Lei Wan, Peng Wang, Xiliang Guan, Congda Li, Xishan Wang.
       OBJECTIVES: Osteosarcoma (OS) is one of the two most common malignant bone tumors among children and teens but it is still a rare disorder. Semaphorin 4D (Sema4D) has been reported to play a specific role in human cancers. The aim of this study was to explore the function of Sema4D in the tumorigenesis and development of OS.
    METHODS: 10 pairs of OS tissues and paracancerous normal tissues from human OS samples and OS cell lines were used. Western blot assay was performed to detect the protein expression of Sema4D, Plexin-B1, and associated proteins of Pyk2-PI3K/AKT pathway. To explore the effect of Sema4D in the progression of OS, we reduced the expression of Sema4D. The effect of Sema4D knockdown on cell proliferation was explored by CCK-8 assay and clone formation assay. The effect of Sema4D knockdown on cell migration and invasion was assessed by Transwell assay.
    RESULTS: Sema4D was overexpressed in OS tissues and cell lines. Sema4D knockdown notably suppressed cell proliferation in OS cells. Cell migration and invasion were reduced by Sema4D knockdown. Sema4D/Plexin-B1 facilitated OS, progression by promoting Pyk2-PI3K/AKT pathway.
    CONCLUSION: Sema4D/Plexin-B1 promoted the development of OS so Sema4D might be a potential target of treatment for patients with OS.
    Keywords:  Osteosarcoma; Plexin-B1; Pyk2-PI3K-AKT Pathway; Sema4D
  8. Mol Cell Oncol. 2021 ;8(5): 1981111
    Simplifying cancer: binary pan-cancer superclasses stratified by opposite YAP/TEAD effects.
    Joel D Pearson, Rod Bremner.
      The inherent complexity of cancer complicates treatment. Identifying higher-order principles that govern cancer biology can circumvent this problem and pinpoint broadly applicable treatment options. We recently found that opposite expression and pro- versus anti-cancer activity of a single transcriptional complex functionally stratifies cancer into binary superclasses.
    Keywords:  TAZ/WWTR1; YAP; leukemia; neuroendocrine cancer; small cell lung cancer
    DOI:  https://doi.org/10.1080/23723556.2021.1981111
  9. BMC Cancer. 2021 Dec 01. 21(1): 1285
    Identification of N6-methylandenosine related LncRNAs biomarkers associated with the overall survival of osteosarcoma.
    Pei Zhang, Keteng Xu, Jingcheng Wang, Jiale Zhang, Huahong Quan.
       PURPOSE: Osteosarcoma (OS) is a differentiation disease caused by the genetic and epigenetic differentiation of mesenchymal stem cells into osteoblasts. OS is a common, highly malignant tumor in children and adolescents. Fifteen to 20 % of the patients find distant metastases at their first visit. The purpose of our study was to identify biomarkers for tracking the prognosis and treatment of OS to improve the survival rate of patients.
    MATERIALS AND METHODS: In this study, which was based on Therapeutically Applicable Research to Generate Effective Treatments (TARGET), we searched for m6A related lncRNAs in OS. We constructed a network between lncRNA and m6A, and built an OS prognostic risk model.
    RESULTS: We identified 14,581 lncRNAs by using the dataset from TARGET. We obtained 111 m6A-related lncRNAs through a Pearson correlation analysis. A network was built between lncRNA and m6A genes. Eight m6A-related lncRNAs associated with survival were identified through a univariate Cox analysis. A selection operator (LASSO) Cox regression was used to construct a prognostic risk model with six genes (RP11-286E11.1, LINC01426, AC010127.3, DLGAP1-AS2, RP4-657D16.3, AC002398.11) obtained through least absolute shrinkage. We also discovered upregulated levels of DLGAP1-AS2 and m6A methylation in osteosarcoma tissues/cells compared with normal tissues/osteoblasts cells.
    CONCLUSION: We constructed a risk score prognosis model of m6A-related lncRNAs (RP11-286E11.1, LINC01426, AC010127.3, DLGAP1-AS2, RP4-657D16.3, AC002398.11) using the dataset downloaded from TRAGET. We verified the value of the model by dividing all samples into test groups and training groups. However, the role of m6A-related lncRNAs in osteosarcoma needs to be further researched by cell and in vivo studies.
    Keywords:  Bioinformatics; N6-methylandenosine; Osteosarcoma
    DOI:  https://doi.org/10.1186/s12885-021-09011-z
  10. Cancer Cell Int. 2021 Dec 02. 21(1): 640
    Identification of key genes as predictive biomarkers for osteosarcoma metastasis using translational bioinformatics.
    Fu-Peng Ding, Jia-Yi Tian, Jing Wu, Dong-Feng Han, Ding Zhao.
       BACKGROUND: Osteosarcoma (OS) metastasis is the most common cause of cancer-related mortality, however, no sufficient clinical biomarkers have been identified. In this study, we identified five genes to help predict metastasis at diagnosis.
    METHODS: We performed weighted gene co-expression network analysis (WGCNA) to identify the most relevant gene modules associated with OS metastasis. An important machine learning algorithm, the support vector machine (SVM), was employed to predict key genes for classifying the OS metastasis phenotype. Finally, we investigated the clinical significance of key genes and their enriched pathways.
    RESULTS: Eighteen modules were identified in WGCNA, among which the pink, red, brown, blue, and turquoise modules demonstrated good preservation. In the five modules, the brown and red modules were highly correlated with OS metastasis. Genes in the two modules closely interacted in protein-protein interaction networks and were therefore chosen for further analysis. Genes in the two modules were primarily enriched in the biological processes associated with tumorigenesis and development. Furthermore, 65 differentially expressed genes were identified as common hub genes in both WGCNA and protein-protein interaction networks. SVM classifiers with the maximum area under the curve were based on 30 and 15 genes in the brown and red modules, respectively. The clinical significance of the 45 hub genes was analyzed. Of the 45 genes, 17 were found to be significantly correlated with survival time. Finally, 5/17 genes, including ADAP2 (P = 0.0094), LCP2 (P = 0.013), ARHGAP25 (P = 0.0049), CD53 (P = 0.016), and TLR7 (P = 0.04) were significantly correlated with the metastatic phenotype. In vitro verification, western blotting, wound healing analyses, transwell invasion assays, proliferation assays, and colony formation assays indicated that ARHGAP25 promoted OS cell migration, invasion, proliferation, and epithelial-mesenchymal transition.
    CONCLUSION: We identified five genes, namely ADAP2, LCP2, ARHGAP25, CD53, and TLR7, as candidate biomarkers for the prediction of OS metastasis; ARHGAP25 inhibits MG63 OS cell growth, migration, and invasion in vitro, indicating that ARHGAP25 can serve as a promising specific and prognostic biomarker for OS metastasis.
    Keywords:  ARHGAP25; Metastasis; Osteosarcoma; TCGA; WGCNA
    DOI:  https://doi.org/10.1186/s12935-021-02308-w
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