The negative feedback between miR‐143 and DNMT3A regulates cisplatin resistance in ovarian cancer

Han, Xiao‐Jian; Liú, Dan; Zhou, Yuanyuan; Wang, Lijie; Hou, Huilian; Chen, He; Zhang, Lirui; Chen, Wei; Xu, Li; Zhao, Le

doi:10.1002/cbin.11486

Cited by 14 publications

(10 citation statements)

References 32 publications

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“…MiRNAs have been found to play a crucial role in the regulation of all major cellular functions, including cell proliferation, differentiation, and apoptosis, which are involved in various human diseases [ 4 ]. MiR-143 is widely distributed in mammalian tissues and serves an important role in a number of physiological processes, such as adipocyte and smooth muscle differentiation [ 5 , 6 , 7 ], tumorigenesis suppression [ 8 ], DNA methylation [ 9 , 10 , 11 , 12 ] and development of tissues and organs [ 13 ]. MiR-143 has been reported as a biomarker for the late stages of hepatocellular carcinoma and liver fibrosis [ 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

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Exploration of the Effect on Genome-Wide DNA Methylation by miR-143 Knock-Out in Mice Liver

Chen¹,

Luo²,

Liu³

et al. 2021

IJMS

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MiR-143 play an important role in hepatocellular carcinoma and liver fibrosis via inhibiting hepatoma cell proliferation. DNA methyltransferase 3 alpha (DNMT3a), as a target of miR-143, regulates the development of primary organic solid tumors through DNA methylation mechanisms. However, the effect of miR-143 on DNA methylation profiles in liver is unclear. In this study, we used Whole-Genome Bisulfite Sequencing (WGBS) to detect the differentially methylated regions (DMRs), and investigated DMR-related genes and their enriched pathways by miR-143. We found that methylated cytosines increased 0.19% in the miR-143 knock-out (KO) liver fed with high-fat diet (HFD), compared with the wild type (WT). Furthermore, compared with the WT group, the CG methylation patterns of the KO group showed lower CG methylation levels in CG islands (CGIs), promoters and hypermethylation in CGI shores, 5′UTRs, exons, introns, 3′UTRs, and repeat regions. A total of 984 DMRs were identified between the WT and KO groups consisting of 559 hypermethylation and 425 hypomethylation DMRs. Furthermore, DMR-related genes were enriched in metabolism pathways such as carbon metabolism (serine hydroxymethyltransferase 2 (Shmt2), acyl-Coenzyme A dehydrogenase medium chain (Acadm)), arginine and proline metabolism (spermine synthase (Sms), proline dehydrogenase (Prodh2)) and purine metabolism (phosphoribosyl pyrophosphate synthetase 2 (Prps2)). In summary, we are the first to report the change in whole-genome methylation levels by miR-143-null through WGBS in mice liver, and provide an experimental basis for clinical diagnosis and treatment in liver diseases, indicating that miR-143 may be a potential therapeutic target and biomarker for liver damage-associated diseases and hepatocellular carcinoma.

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Section: Introductionmentioning

confidence: 99%

“…Previous researches have shown that DNMT3a , a DNA methyltransferase contributing to de novo methylation, is a target of miR-143 [ 9 , 10 , 11 , 12 ]. These studies have reported on solid tumors of primary organs other than the liver.…”

Section: Introductionmentioning

confidence: 99%

Exploration of the Effect on Genome-Wide DNA Methylation by miR-143 Knock-Out in Mice Liver

Chen¹,

Luo²,

Liu³

et al. 2021

IJMS

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“…Double negative feedback of miR-29b and DNMT3A/3B promoted OC progression ( 29 ). Feedback between DNMT3A and miR-143 was a critical epigenetic regulator of cisplatin resistance in OCs ( 66 ). WTAP acting as an oncogenic factor promoted OC progression via WTAP-HBS1L/FAM76A axis ( 67 ).…”

Section: Discussionmentioning

confidence: 99%

Ovarian cancer subtypes based on the regulatory genes of RNA modifications: Novel prediction model of prognosis

Zheng

Zhan

2022

Front. Endocrinol.

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BackgroundOvarian cancer (OC) is a female reproductive system tumor. RNA modifications play key roles in gene expression regulation. The growing evidence demonstrates that RNA methylation is critical for various biological functions, and that its dysregulation is related to the progression of cancer in human.MethodOC samples were classified into different subtypes (Clusters 1 and 2) based on various RNA-modification regulatory genes (RRGs) in the process of RNA modifications (m1A, m6A, m6Am, m5C, m7G, ac4C, m3C, and Ψ) by nonnegative matrix factorization method (NMF). Based on differently expressed RRGs (DERRGs) between clusters, a pathologically specific RNA-modification regulatory gene signature was constructed with Lasso regression. Kaplan-Meier analysis and receiver operating characteristic (ROC) curves were used to evaluate the prognostic ability of the identified model. The correlations of clinicopathological features, immune subtypes, immune scores, immune cells, and tumor mutation burden (TMB) were also estimated between different NMF clusters and riskscore groups.ResultsIn this study, 59 RRGs in the process of RNA modifications (m1A, m6A, m6Am, m5C, m7G, ac4C, m3C, and Ψ) were obtained from TCGA database. These RRGs were interactional, and sample clusters based on these regulators were significantly correlated with survival rate, clinical characteristics (involving survival status and pathologic stage), drug sensibility, and immune microenvironment. Furthermore, Lasso regression based on these 21 DERRGs between clusters 1 and 2 constructed a four-DERRG signature (ALYREF, ZC3H13, WTAP, and METTL1). Based on this signature, 307 OC patients were classified into high- and low-risk groups based on median value of riskscores from lasso regression. This identified signature was significantly associated with overall survival, radiation therapy, age, clinical stage, cancer status, and immune cells (involving CD4+ memory resting T cells, plasma cells, and Macrophages M1) of ovarian cancer patients. Further, GSEA revealed that multiple biological behaviors were significantly enriched in different groups.ConclusionsOC patients were classified into two subtypes per these RRGs. This study identified four-DERRG signature (ALYREF, ZC3H13, WTAP, and METTL1) in OC, which was an independent prognostic model for patient stratification, prognostic evaluation, and prediction of response to immunotherapy in ovarian cancer by classifying OC patients into high- and low-risk groups.

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“…While these two miRNAs have already been separately linked to EMT or DNMTs regulation in various tumours (32,42), here we assess the importance of the interplay between these factors in the transition, as well as the ability of miR-429 to directly target DNMT3A. Feedback loops between DNMT3A and miRNAs have already been demonstrated in various cancers; the DNMT3A/miR-200c loop has a relevant role during carcinogenesis and progression in gastric cancer (49), while a negative feedback between miR-143 and DNMT3A regulates cisplatin resistance in ovarian cancer (50).…”

Section: Discussionmentioning

confidence: 99%

DNMT3A epigenetically regulates key microRNAs involved in epithelial-to-mesenchymal transition in prostate cancer

et al. 2021

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Epithelial-to-Mesenchymal Transition (EMT) is involved in prostate cancer metastatic progression, and its plasticity suggests epigenetic implications. Deregulation of DNMTs and several miRNAs plays a relevant role in EMT, but their interplay has not been clarified yet. In this study we provide evidence that DNMT3A interaction with several miRNAs has a central role in an ex-vivo EMT prostate cancer model obtained via exposure of PC3 cells to conditioned media from cancer-associated fibroblasts (CM-CAFs). The analysis of the alterations of the miRNA profile shows that miR-200 family (miR-200a/200b/429, miR-200c/141), miR-205, and miR-203, known to modulate key EMT factors, are downregulated and hyper-methylated at their promoters. DNMT3A (mainly isoform a) is recruited onto these miRNA promoters, coupled with the increase of H3K27me3/H3K9me3 and/or the decrease of H3K4me3/H3K36me3. Most interestingly, our results reveal the differential expression of two DNMT3A isoforms (a and b) during ex-vivo EMT and a regulatory feedback loop between miR-429 and DNMT3A that can promote and sustain the transition toward a more mesenchymal phenotype. We demonstrate the ability of miR-429 to target DNMT3A 3’UTR and modulate the expression of EMT factors, in particular ZEB1. Survey of the PRAD-TCGA data set shows that patients expressing an EMT-like signature are indeed characterized by down-regulation of the same miRNAs with a diffused hyper-methylation at miR-200c/141 and miR-200a/200b/429 promoters. Finally, we show that miR-1260a also targets DNMT3A, although it does not seem involved in EMT in prostate cancer.

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The negative feedback between miR‐143 and DNMT3A regulates cisplatin resistance in ovarian cancer

Cited by 14 publications

References 32 publications

Exploration of the Effect on Genome-Wide DNA Methylation by miR-143 Knock-Out in Mice Liver

Exploration of the Effect on Genome-Wide DNA Methylation by miR-143 Knock-Out in Mice Liver

Ovarian cancer subtypes based on the regulatory genes of RNA modifications: Novel prediction model of prognosis

DNMT3A epigenetically regulates key microRNAs involved in epithelial-to-mesenchymal transition in prostate cancer

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