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

Wang, Ke; Zhong, Weibo; Long, Zining; Guo, Yufei; Zhong, Chuanfan; Yang, Taowei; Wang, Shuo; Lai, Houhua; Lü, Jianming; Zheng, Pengxiang; Mao, Xiangming

doi:10.3389/fmolb.2021.775304

Cited by 23 publications

(13 citation statements)

References 68 publications

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“…These TNF-related lncRNAs were involved in carcinogenesis, and inflammatory and immune responses (22)(23)(24)(25). A number of studies have also demonstrated that some of TNF-related lncRNAs are closely associated with cancer proliferation and survival (32)(33)(34)(35)(36)(37)(38). Thus, we analyzed the expression patterns and clinical significance of TNFrelated lncRNAs in LUAD.…”

Section: Discussionmentioning

confidence: 99%

Tumor necrosis factor-related lncRNAs predict prognosis and immunotherapy response for patients with lung adenocarcinoma

Chen¹,

Wu²,

Wang³

et al. 2023

J Thorac Dis

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Background: Lung adenocarcinoma (LUAD) has become one of the most lethal cancers, for which the recurrence and survival rates remain unfavorable. The tumor necrosis factor (TNF) family is involved in tumorigenesis and tumor progression. Various long non-coding RNAs (lncRNAs) play important roles by mediating the TNF family in cancer. Therefore, this study aimed to construct a TNF-related lncRNA signature to predict prognosis and immunotherapy response in LUAD. Methods:The expression of TNF family members and their related lncRNAs in a total of 500 enrolled LUAD patients was collected from The Cancer Genome Atlas (TCGA). Univariate Cox and the least absolute shrinkage and selection operator (LASSO)-Cox analysis was used to construct a TNF family-related lncRNA prognostic signature. Kaplan-Meier (KM) survival analysis was used to evaluate survival status. The time-dependent area under the receiver operating characteristic (ROC) curve (AUC) values were used to assess the predictive value of the signature to 1-, 2-, and 3-year overall survival (OS). Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied to identify the signature-related biological pathways. Furthermore, tumor immune dysfunction and exclusion (TIDE) analysis was employed to evaluate immunotherapy response.Results: A total of 8 TNF-related lncRNAs significantly associated with OS of LUAD patients were used to construct a TNF family-related lncRNA prognostic signature. According to risk score, these patients were divided into high-and low-risk subgroups. The KM survival analysis indicated that patients in the high-risk group showed significantly less favorable OS than that of low-risk group. The AUC values in predicting 1-, 2-, and 3-year OS were 0.740, 0.738, and 0.758, respectively. Moreover, the GO and KEGG pathway analyses demonstrated that these lncRNAs were closely involved in immune-related signaling pathways. The further TIDE analysis indicated that high-risk patients had a lower TIDE score than that of low-risk patients, indicating that high-risk patients may be appropriate candidates for immunotherapy. Conclusions:For the first time, this study constructed and validated a prognostic predictive signature of LUAD patients based on TNF-related lncRNAs, and the signature showed good performance to predict immunotherapy response. Therefore, this signature may provide new strategies for individualized treatment of LUAD patients.

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Section: Discussionmentioning

confidence: 99%

Tumor necrosis factor-related lncRNAs predict prognosis and immunotherapy response for patients with lung adenocarcinoma

Chen¹,

Wu²,

Wang³

et al. 2023

J Thorac Dis

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“…Cumulative evidence over the two decades suggested that various types of RNA modifications, such as 5-methylcytosine (m 5 C), m 6 A, inosine (I), and 2′-O-methylation (2′-O-Me) are implicated in PCa (6,(36)(37)(38). Among them, 6 A has attracted the most attention due to the wide distribution of this modification across the human transcriptome.…”

Section: Discussionmentioning

confidence: 99%

The m6A methylation landscape, molecular characterization and clinical relevance in prostate adenocarcinoma

Peng

Gan

et al. 2023

Front. Immunol.

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BackgroundDespite the recent progress of therapeutic strategies in treating prostate cancer (PCa), the majority of patients still eventually relapse, experiencing dismal outcomes. Therefore, it is of utmost importance to identify novel viable targets to increase the effectiveness of treatment. The present study aimed to investigate the potential relationship between N6-methyladenosine (m6A) RNA modification and PCa development and determine its clinical relevance.MethodsThrough systematic analysis of the TCGA database and other datasets, we analyzed the gene expression correlation and mutation profiles of m6A-related genes between PCa and normal tissues. Patient samples were divided into high- and low-risk groups based on the results of Least Absolute Shrinkage and Selection Operator (LASSO) Cox analysis. Subsequently, differences in biological processes and genomic characteristics of the two risk groups were determined, followed by functional enrichment analysis and gene set enrichment (GSEA) analysis. Next, we constructed the protein-protein interaction (PPI) network of differentially expressed genes between patients in high- and low-risk groups, along with the mRNA-miRNA-lncRNA network. The correlation analysis of tumor-infiltrating immune cells was further conducted to reveal the differences in immune characteristics between the two groups.ResultsA variety of m6A-related genes were identified to be differentially expressed in PCa tissues as compared with normal tissues. In addition, the PPI network contained 278 interaction relationships and 34 m6A-related genes, and the mRNA-miRNA-lncRNA network contained 17 relationships, including 91 miRNAs. Finally, the immune characteristics analysis showed that compared with the low-risk group, the levels of M1 and M2 macrophages in the high-risk group significantly increased, while the levels of mast cells resting and T cells CD4 memory resting significantly decreased.ConclusionsThis study provides novel findings that can further the understanding of the role of m6A methylation during the progression of PCa, which may facilitate the invention of targeted therapeutic drugs.

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“…The ceRNA regulatory role of long non-coding RNA (lncRNA) in T2D has been identified ( Lin et al, 2017 ). Recent studies revealed that m5C-related lncRNA signatures play important role in human cancers ( Wang et al, 2021 ; Zheng et al, 2022 ). In this study, we constructed a ceRNA interaction network.…”

Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of key m5C modification-related genes in type 2 diabetes

Song

Jiang

et al. 2022

Front. Genet.

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Background: 5-methylcytosine (m5C) RNA methylation plays a significant role in several human diseases. However, the functional role of m5C in type 2 diabetes (T2D) remains unclear.Methods: The merged gene expression profiles from two Gene Expression Omnibus (GEO) datasets were used to identify m5C-related genes and T2D-related differentially expressed genes (DEGs). Least-absolute shrinkage and selection operator (LASSO) regression analysis was performed to identify optimal predictors of T2D. After LASSO regression, we constructed a diagnostic model and validated its accuracy. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to confirm the biological functions of DEGs. Gene Set Enrichment Analysis (GSEA) was used to determine the functional enrichment of molecular subtypes. Weighted gene co-expression network analysis (WGCNA) was used to select the module that correlated with the most pyroptosis-related genes. Protein-protein interaction (PPI) network was established using the STRING database, and hub genes were identified using Cytoscape software. The competitive endogenous RNA (ceRNA) interaction network of the hub genes was obtained. The CIBERSORT algorithm was applied to analyze the interactions between hub gene expression and immune infiltration.Results: m5C-related genes were significantly differentially expressed in T2D and correlated with most T2D-related DEGs. LASSO regression showed that ZBTB4 could be a predictive gene for T2D. GO, KEGG, and GSEA indicated that the enriched modules and pathways were closely related to metabolism-related biological processes and cell death. The top five genes were identified as hub genes in the PPI network. In addition, a ceRNA interaction network of hub genes was obtained. Moreover, the expression levels of the hub genes were significantly correlated with the abundance of various immune cells.Conclusion: Our findings may provide insights into the molecular mechanisms underlying T2D based on its pathophysiology and suggest potential biomarkers and therapeutic targets for T2D.

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

Cited by 23 publications

References 68 publications

Tumor necrosis factor-related lncRNAs predict prognosis and immunotherapy response for patients with lung adenocarcinoma

Tumor necrosis factor-related lncRNAs predict prognosis and immunotherapy response for patients with lung adenocarcinoma

The m6A methylation landscape, molecular characterization and clinical relevance in prostate adenocarcinoma

Comprehensive analysis of key m5C modification-related genes in type 2 diabetes

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