Whole-Genome DNA Methylation Profiling Identifies Epigenetic Signatures of Uterine Carcinosarcoma

Li, Jing; Xing, Xiaoyun; Li, Daofeng; Zhang, Bo; Mutch, David G.; Hagemann, Ian S.; Wang, Ting

doi:10.1016/j.neo.2016.12.009

Cited by 31 publications

(23 citation statements)

References 56 publications

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“…The decrease in the epigenetic aging rate after 60 years is evident using both the list of 8823 age-DMPs and the shorter list including 687 probes mapping on 75 age-DMRs. In addition to the robustness emerging from confirming the results with two different approaches, the latter signature is defined using a region-centric approach 18 22,23 or in other cancer types (NEFM, KCNG3, PRDM14, FOXD3, CELSR3, HEYL) [24][25][26][27][28][29][30] , suggesting a role of these genes in liver homeostasis.…”

Section: Discussionmentioning

confidence: 99%

Molecular Aging of Human Liver: An Epigenetic/Transcriptomic Signature

Bacalini

Franceschi

Gentilini

et al. 2018

The Journals of Gerontology: Series A

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The feasibility of liver transplantation from old healthy donors suggests that this organ is able to preserve its functionality during aging. To explore the biological basis of this phenomenon, we characterized the epigenetic profile of liver biopsies collected from 45 healthy liver donors ranging from 13 to 90 years old using the Infinium HumanMethylation450 BeadChip. The analysis indicates that a large remodeling in DNA methylation patterns occurs, with 8823 age-associated differentially methylated CpG probes. Notably, these age-associated changes tended to level off after the age of 60, as confirmed by Horvath's clock. Using stringent selection criteria we further identified a DNA methylation signature of aging liver including 75 genomic regions. We demonstrated that this signature is specific for liver compared to other tissues and that it is able to detect biological age-acceleration effects associated with obesity. Finally we combined DNA methylation measurements with available expression data. Although the intersection between the two omic characterizations was low, both approaches suggested a previously unappreciated role of epithelial-mesenchymal transition and Wnt signaling pathways in the aging of human liver.

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Section: Discussionmentioning

confidence: 99%

Molecular Aging of Human Liver: An Epigenetic/Transcriptomic Signature

Bacalini

Franceschi

Gentilini

et al. 2018

The Journals of Gerontology: Series A

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“…DNA methylation, as a major epigenetic modification, plays important roles in human diseases and aging ( 1 – 4 ), embryonic development of animals ( 5 – 8 ) as well as growth and development of plants ( 9 – 12 ). Recently, studies in human have found that DNA methylation biomarkers of aging are associated closely with mortality rates and incidence of cardio-metabolic disease ( 13 , 14 ).…”

Section: Introductionmentioning

confidence: 99%

MethBank 3.0: a database of DNA methylomes across a variety of species

Fang

et al. 2017

Nucleic Acids Research

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MethBank (http://bigd.big.ac.cn/methbank) is a database that integrates high-quality DNA methylomes across a variety of species and provides an interactive browser for visualization of methylation data. Here, we present an updated implementation of MethBank (version 3.0) by incorporating more DNA methylomes from multiple species and equipping with more enhanced functionalities for data annotation and more friendly web interfaces for data presentation, search and visualization. MethBank 3.0 features large-scale integration of high-quality methylomes, involving 34 consensus reference methylomes derived from a large number of human samples, 336 single-base resolution methylomes from different developmental stages and/or tissues of five plants, and 18 single-base resolution methylomes from gametes and early embryos at multiple stages of two animals. Additionally, it is enhanced by improving the functionalities for data annotation, which accordingly enables systematic identification of methylation sites closely associated with age, sites with constant methylation levels across different ages, differentially methylated promoters, age-specific differentially methylated cytosines/regions, and methylated CpG islands. Moreover, MethBank provides tools to estimate human methylation age online and to identify differentially methylated promoters, respectively. Taken together, MethBank is upgraded with significant improvements and advances over the previous version, which is of great help for deciphering DNA methylation regulatory mechanisms for epigenetic studies.

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“…Histologically, it is composed of an admixture of malignant epithelial and sarcomatous elements. The sarcoma component exhibits differentiation with histologic features of leiomyosarcoma, endometrial stromal sarcoma (ESS), or brosarcoma, or may resemble rhabdomyosarcoma, chondrosarcoma, osteosarcoma, or other heterologous sarcomas [25,26]. The low incidence and complex composition limit the researches.…”

Section: Discussionmentioning

confidence: 99%

HMMR Functions as a Prognostic Biomarker in Uterine Carcinosarcoma Identified by Comprehensive Bioinformatics Analysis

Sun¹,

Ma²,

Chen³

2020

Preprint

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BackgroundUterine carcinosarcoma (UCS) is a rare aggressive tumor with a high metastasis rate and poor prognosis. Bioinformatics analysis has been widely applied to screen and analyze genes in linkage to various types of cancer progression. This study aims to explore the molecular mechanism of UCS. MethodsFirst, transcriptional different expression data between UCS and normal samples were got from the GEPIA database. Subsequently, differentially expressed genes were analyzed through the Metascape with Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Then, the STRING website and Cytoscape software were applied to construct the protein-protein interaction network. Finally, the top 30 genes obtained through the MCC algorithm were selected as hub genes, which was finally validated in TIMER, and UALCAN databases. ResultsA total of 1894 DEGs (579 up-regulated and 1315 down-regulated) were identified, GO and KEGG functional enrichment analysis were performed for the DEGs. The PPI network was constructed based on DEGs, and four clusters were excavated for further analysis and the top 30 genes were identified as hub genes. Our data showed that the expression of HMMR is significantly higher in UCS tissues compared to the paired normal tissues (p<0.05) and the elevated expression of HMMR is related to poor prognosis in patients with UCS (p= 0.0031). TPX2, AURKA, BRCA1 and BARD1 are essential for the function of HMMR. TPX2 and AURKA were found to be significantly higher in UCS compared to the normal tissue (p<0.05), and there was a statistically significant positive correlation between the expression of HMMR and AURKA, TPX2, BRCA1, BARD1 in UCS (p=1.08e-07, p=1.62e-05, p=2.02e-3, p=6.54e-6). ConclusionsOur study suggested that HMMR may be a potential biomarker for predicting the prognosis of UCS patients.

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Whole-Genome DNA Methylation Profiling Identifies Epigenetic Signatures of Uterine Carcinosarcoma

Cited by 31 publications

References 56 publications

Molecular Aging of Human Liver: An Epigenetic/Transcriptomic Signature

Molecular Aging of Human Liver: An Epigenetic/Transcriptomic Signature

MethBank 3.0: a database of DNA methylomes across a variety of species

HMMR Functions as a Prognostic Biomarker in Uterine Carcinosarcoma Identified by Comprehensive Bioinformatics Analysis

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