Prognostic Significance and Tumor Immune Microenvironment Heterogenicity of m5C RNA Methylation Regulators in Triple-Negative Breast Cancer

Huang, Zhidong; Pan, Junfan; Wang, Helin; Du, Xianqiang; Xu, Yu-sheng; Wang, Zhitang; Chen, Debo

doi:10.3389/fcell.2021.657547

Cited by 71 publications

(77 citation statements)

References 61 publications

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“…Previous studies showed the Aly/REF export factor (ALYREF) and Y-box binding protein 1 (YBX1) may act as significant readers for m5C, taking part in cancer-related biological processes ( Yang et al, 2017 ; Chen et al, 2019 ). NSUN2 (NOP2/Sun domain family, member 2), a major m5C-modifying methyltransferase (writer) of RNA, is highly expressed in various tumors such as the esophagus, liver, pancreas, cervix, prostate, kidney, bladder, thyroid, and breast cancers ( Okamoto et al, 2012 ; Huang et al, 2021 ). Recently, NSUN2 was reported to promote gastric cancer cell proliferation in a m5C-dependent manner ( Mei et al, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

5-Methylcytosine RNA Methyltransferases-Related Long Non-coding RNA to Develop and Validate Biochemical Recurrence Signature in Prostate Cancer

Wang

Zhong

Long

et al. 2021

Front. Mol. Biosci.

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The effects of 5-methylcytosine in RNA (m5C) in various human cancers have been increasingly studied recently; however, the m5C regulator signature in prostate cancer (PCa) has not been well established yet. In this study, we identified and characterized a series of m5C-related long non-coding RNAs (lncRNAs) in PCa. Univariate Cox regression analysis and least absolute shrinkage and selector operation (LASSO) regression analysis were implemented to construct a m5C-related lncRNA prognostic signature. Consequently, a prognostic m5C-lnc model was established, including 17 lncRNAs: MAFG-AS1, AC012510.1, AC012065.3, AL117332.1, AC132192.2, AP001160.2, AC129510.1, AC084018.2, UBXN10-AS1, AC138956.2, ZNF32-AS2, AC017100.1, AC004943.2, SP2-AS1, Z93930.2, AP001486.2, and LINC01135. The high m5C-lnc score calculated by the model significantly relates to poor biochemical recurrence (BCR)-free survival (p < 0.0001). Receiver operating characteristic (ROC) curves and a decision curve analysis (DCA) further validated the accuracy of the prognostic model. Subsequently, a predictive nomogram combining the prognostic model with clinical features was created, and it exhibited promising predictive efficacy for BCR risk stratification. Next, the competing endogenous RNA (ceRNA) network and lncRNA–protein interaction network were established to explore the potential functions of these 17 lncRNAs mechanically. In addition, functional enrichment analysis revealed that these lncRNAs are involved in many cellular metabolic pathways. Lastly, MAFG-AS1 was selected for experimental validation; it was upregulated in PCa and probably promoted PCa proliferation and invasion in vitro. These results offer some insights into the m5C's effects on PCa and reveal a predictive model with the potential clinical value to improve the prognosis of patients with PCa.

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Section: Discussionmentioning

confidence: 99%

5-Methylcytosine RNA Methyltransferases-Related Long Non-coding RNA to Develop and Validate Biochemical Recurrence Signature in Prostate Cancer

Wang

Zhong

Long

et al. 2021

Front. Mol. Biosci.

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“… 13 Huang et al discovered 11 m5C regulatory genes related to TNBC neoplasia in triple negative breast cancer (TNBC), which are related to the poor prognosis of NSUN2 and NSUN6 and TNBC. 14 Xue et al study in head and neck squamous cell carcinoma (HNSCC) showed that the m5C regulatory genes MAPK1, HRAS, RAC1, HIST1H4K and HIST1H3C are potential driving genes of HNSCC and are potentially related to the occurrence of HNSCC. 15 In addition, the demethylation of MAP2K3 is related to inflammation and immune regulation in HNSCC patients.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Analysis of 5-Methylcytosine Profiles of Messenger RNA in Human High-Grade Serous Ovarian Cancer by MeRIP Sequencing

Li¹,

Zhang²,

Huang³

2021

CMAR

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Background Accumulating evidence has indicated that methylation status is closely related to tumourigenesis and a few aggressive features of diverse cancers. However, as an important methylation regulation modification, the distribution of 5-methylcytosine (m5C) in high-grade serous ovarian cancer (HGSOC) remains unclear. Materials and Methods We collected three pairs of human HGSOC tissues and adjacent non-tumour tissues to analyse the transcriptome-wide m5C methylation of messenger RNAs (mRNAs) by methylated RNA immunoprecipitation sequencing. Gene ontology (GO) enrichment analysis and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis were performed to eExplore the potential biological functions of these genes and important cancer pathways. We used immunohistochemistry to analyse the expression of the m5C modification regulatory gene MAP2K3 in 80 HGSOC tissue samples, and their associations with clinical parameters were analyzed using the Spearman-rho test. Univariate and multivariate Cox regression analyses were performed to identify potential prognostic factors. Kaplan–Meier analysis was performed to analyze overall survival. Results We identified 2050 dysregulated m5C peaks, 1767 of which were significantly upregulated, while 283 were significantly downregulated. GO enrichment analysis showed that genes altered by the m5C peak played a key role in system development, transporter complex, and transporter activity. KEGG pathway analysis revealed that these genes were enriched in some important pathways in cancer regulation, such as inflammatory mediator regulation of the TRP channels pathway, Wnt signalling pathway, and focal adhesion pathways. In addition, through joint analysis of MeRIP-seq and RNA-seq data, we identified 125 differentially methylated m5C peaks and synchronous differentially expressed genes. These genes play key roles in cell growth, maintenance, plasma membranes, and cell adhesion molecule activity. Immunohistochemical staining results showed that high expression of MAP2K3 was significantly correlated with CA125 level (p < 0.001), tumour size (p = 0.001), lymph node metastasis (p = 0.008), depth of myometrial invasion (p < 0.001), and FIGO stage (p < 0.001), indicating a poor prognosis. Conclusion Our results reveal the different distribution patterns of m5C in HGSOC and adjacent tissues and the possible involvement of m5C in HGSOC cell functions. Our study provides new insights into the epi-transcriptomic dysregulation of m5C in the tumourigenesis of HGSOC.

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“…Recent research showed that m5C-related genes could regulate tumor immune microenvironment in breast cancer ( 40 ). LncRNAs are also known to be involved in regulating tumor-infiltrating lymph cells in malignant tumors ( 41 ).…”

Section: Discussionmentioning

confidence: 99%

Prognostic Risk Model and Tumor Immune Environment Modulation of m5C-Related LncRNAs in Pancreatic Ductal Adenocarcinoma

et al. 2021

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RNA methylation modification is a key process in epigenetics that regulates posttranscriptional gene expression. With advances in next-generation sequencing technology, 5-methylcytosine (m5C) modification has also been found in multiple RNAs. Long non-coding RNAs (lncRNAs) were proved to have a key role in cancer progression and closely related to the tumor immune microenvironment. Thus, based on the PDAC patients’ clinical information and genetic transcriptome data from the TCGA database, we performed a detailed bioinformatic analysis to establish a m5C-related lncRNA prognostic risk model for PDAC patients and discovered the relationship between the risk model and PDAC immune microenvironment. Pearson correlation coefficient analysis was applied to conduct a m5C regulatory gene and m5C-related lncRNA co-expression network. Expression of m5C-related lncRNAs screened by univariate regression analysis with prognostic value showed a significant difference between pancreatic cancer and normal tissues. The least absolute shrinkage and selection operator (LASSO) Cox regression method was applied to determine an 8-m5C-related lncRNA prognostic risk model. We used principal component analysis to indicate that the risk model could distinguish all the samples clearly. The clinical nomogram also accurately predicted 1-, 1.5-, 2-, and 3-year survival time among PDAC patients. Additionally, this risk model was validated in the entire group and sub-test groups using KM analysis and ROC analysis. Combined with the clinical characteristics, the risk score was found to be an independent factor for predicting the survival of PDAC patients. Furthermore, the association between the risk model and tumor immune microenvironment was evaluated via the ESTIMATE R package and CIBERSORT method. Consequently, the results indicated that immune cells were associated with m5C-related lncRNA risk model scores and had different distribution in the high- and low-risk groups. Based on all these analyses, the m5C-related lncRNA risk model could be a reliable prognostic tool and therapeutic target for PDAC patients.

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Prognostic Significance and Tumor Immune Microenvironment Heterogenicity of m5C RNA Methylation Regulators in Triple-Negative Breast Cancer

Cited by 71 publications

References 61 publications

5-Methylcytosine RNA Methyltransferases-Related Long Non-coding RNA to Develop and Validate Biochemical Recurrence Signature in Prostate Cancer

5-Methylcytosine RNA Methyltransferases-Related Long Non-coding RNA to Develop and Validate Biochemical Recurrence Signature in Prostate Cancer

Comprehensive Analysis of 5-Methylcytosine Profiles of Messenger RNA in Human High-Grade Serous Ovarian Cancer by MeRIP Sequencing

Prognostic Risk Model and Tumor Immune Environment Modulation of m5C-Related LncRNAs in Pancreatic Ductal Adenocarcinoma

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