DNA methylation variation along the cancer epigenome and the identification of novel epigenetic driver events

Heery, Richard; Schaefer, Martin H.

doi:10.1093/nar/gkab1167

Cited by 13 publications

(5 citation statements)

References 68 publications

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“…Growing evidence showed that aberrant methylation was associated with oncogenesis and may have a significant clinical value [ 22 ]. Therefore, we assessed the DNA methylation levels of SETDB1 and its prognosis value in various human cancers.…”

Section: Resultsmentioning

confidence: 99%

Pancancer Analyses Reveal Genomics and Clinical Characteristics of the SETDB1 in Human Tumors

Lin

Xiao

Chen

et al. 2022

Journal of Oncology

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Background. Malignant tumor is one of the most common diseases that seriously affect human health. The prior literature has reported the biological function and potential therapeutic targets of SET domain bifurcated histone lysine methyltransferase 1 (SETDB1) as an oncogene. However, SETDB1 has rarely been analyzed from a pan-cancer perspective. Methods. Bioinformatics analysis tools and databases, including GeneCards, National Center for Biotechnology Information (NCBI), UniProt, Illustrator for Biological Sequences (IBS), Human Protein Atlas (HPA), GEPIA, TIMER2, Sangerbox 3.0, UALCAN, Kaplan-Meier (K-M) plotter, cBioPortal, Catalogue Of Somatic Mutations In Cancer (COSMIC), PhosphoSitePlus, TISIDB, STRING, and GeneMANIA, were utilized to clarify the biological functions and clinical significance of SETDB1 from a pan-cancer perspective. Results. In this study, the pan-cancer analysis demonstrated that SETDB1 showed significantly differential expression in most tumor tissues and paracancerous tissues, and SETDB1 expression was associated with clinicopathological features and clinical prognosis. We also found that SETDB1 mutations occurred in most tumors and were related to tumorigenesis. In addition, DNA methylation of SETDB1 primarily occurred at the cg10444928 site and was associated with prognosis in several human tumors. The predicted phosphorylation site of SETDB1 was Ser1006. We found that SETDB1 was significantly related to the specific tumor-infiltrating immune cell populations and expression of clinically targetable immune checkpoints and may be a promising immunotherapy target. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses also indicated that SETDB1 may function as crucial regulator in carcinogenesis of human cancers. Conclusions. SETDB1 is an important oncogene involved in tumorigenesis and tumor progression through different biological mechanisms. Furthermore, SETDB1 may be a potential therapeutic target for cancer treatment.

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Section: Resultsmentioning

confidence: 99%

Pancancer Analyses Reveal Genomics and Clinical Characteristics of the SETDB1 in Human Tumors

Lin

Xiao

Chen

et al. 2022

Journal of Oncology

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“…Promoter-level methylation measurements calculated from probe-level methylation data in TCGA were used in this analysis ( Heery and Schaefer, 2021 ). For each gene, the most upstream promoter was considered for the analysis.…”

Section: Methodsmentioning

confidence: 99%

Regulation of protein complex partners as a compensatory mechanism in aneuploid tumors

Senger

Santaguida

Schaefer

2022

eLife

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Aneuploidy, a state of chromosome imbalance, is a hallmark of human tumors, but its role in cancer still remains to be fully elucidated. To understand the consequences of whole-chromosome-level aneuploidies on the proteome, we integrated aneuploidy, transcriptomic and proteomic data from hundreds of TCGA/CPTAC tumor samples. We found a surprisingly large number of expression changes happened on other, non-aneuploid chromosomes. Moreover, we identified an association between those changes and co-complex members of proteins from aneuploid chromosomes. This co-abundance association is tightly regulated for aggregation-prone aneuploid proteins and those involved in a smaller number of complexes. On the other hand, we observe that complexes of the cellular core machinery are under functional selection to maintain their stoichiometric balance in aneuploid tumors. Ultimately, we provide evidence that those compensatory and functional maintenance mechanisms are established through post-translational control and that the degree of success of a tumor to deal with aneuploidy-induced stoichiometric imbalance impacts the activation of cellular protein degradation programs and patient survival.

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“…For instance, Søes et al found promoter hypomethylation and increased expression of putative OCG ELMO3 to be associated with development of non-small cell lung cancer [20]. Other studies have also identified driver genes with aberrant methylation profiles [21][22][23][24][25][26][27][28]. For example, one study identified 118 differentially expressed methylation-driven genes associated with lung adenocarcinoma of which five genes (CCDC181, PLAU, S1PR1, ELF3, KLHDC9) were used to construct a prognostic risk model which could divide patients with lung adenocarcinoma into high-and low-risk groups [28].…”

Section: Introductionmentioning

confidence: 99%

Revealing cancer driver genes through integrative transcriptomic and epigenomic analyses with Moonlight

Nourbakhsh,

Zheng,

Noor

et al. 2024

Preprint

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Cancer involves dynamic changes caused by (epi)genetic alterations such as mutations or abnormal DNA methylation patterns which occur in cancer driver genes. These driver genes are divided into oncogenes and tumor suppressors depending on their function and mechanism of action. Discovering driver genes in different cancer (sub)types is important not only for increasing current understanding of carcinogenesis but also from prognostic and therapeutic perspectives. We have previously developed a framework called Moonlight which uses a systems biology multi-omics approach for prediction of driver genes. Here, we present further updates to Moonlight by incorporating a DNA methylation layer which provides epigenetic evidence for deregulated expression profiles of driver genes. To this end, we present a novel functionality called Gene Methylation Analysis (GMA) which investigates abnormal DNA methylation patterns to predict driver genes. This is achieved by integrating the tool EpiMix which is designed to detect such aberrant DNA methylation patterns in a cohort of patients and further couples these patterns with changes in gene expression. To showcase GMA, we applied it to three cancer (sub)types (basal-like breast cancer, lung adenocarcinoma, and thyroid carcinoma) where we discovered 33, 190, and 263 epigenetically driven genes, respectively. A subset of these driver genes had prognostic effects with expression levels significantly affecting survival of the patients. Moreover, a subset of the driver genes demonstrated therapeutic potential as drug targets. This study provides a framework for exploring the driving forces behind cancer and provides novel insights into the landscape of three cancer sub(types) by integrating gene expression and methylation data. Moonlight2R is available on GitHub (https://github.com/ELELAB/Moonlight2R) and BioCondcutor (https://bioconductor.org/packages/release/bioc/html/Moonlight2R.html) and the associated case studies presented in this study are available on GitHub (https://github.com/ELELAB/Moonlight2_GMA_case_studies) and OSF (https://osf.io/j4n8q/).

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DNA methylation variation along the cancer epigenome and the identification of novel epigenetic driver events

Cited by 13 publications

References 68 publications

Pancancer Analyses Reveal Genomics and Clinical Characteristics of the SETDB1 in Human Tumors

Pancancer Analyses Reveal Genomics and Clinical Characteristics of the SETDB1 in Human Tumors

Regulation of protein complex partners as a compensatory mechanism in aneuploid tumors

Revealing cancer driver genes through integrative transcriptomic and epigenomic analyses with Moonlight

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