The Identification of RNA Modification Gene PUS7 as a Potential Biomarker of Ovarian Cancer

Li, Huimin; Chen, Lin; Han, Yunsong; Zhang, Fangfang; Wang, Yanyan; Han, Yali; Wang, Yange; Wang, Qiang; Guo, Xiangqian

doi:10.3390/biology10111130

Cited by 19 publications

(16 citation statements)

References 42 publications

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“…The application of PUS7 inhibitors inhibited tumorigenesis and prolonged the life span of tumor-bearing mice ( Cui et al, 2021 ). In ovarian cancer, both mRNA and protein expression of PUS7 were higher in cancer tissues than in normal tissues ( Li et al, 2021 ). All these emerging findings showed the potential of PUSs as cancer biomarkers.…”

Section: Introductionmentioning

confidence: 99%

Integrative multiomics evaluation reveals the importance of pseudouridine synthases in hepatocellular carcinoma

et al. 2022

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Background: The pseudouridine synthases (PUSs) have been reported to be associated with cancers. However, their involvement in hepatocellular carcinoma (HCC) has not been well documented. Here, we assess the roles of PUSs in HCC.Methods: RNA sequencing data of TCGA-LIHC and LIRI-JP were downloaded from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), respectively. GSE36376 gene expression microarray was downloaded from the Gene Expression Omnibus (GEO). Proteomics data for an HBV-related HCC cohort was obtained from the CPTAC Data Portal. The RT-qPCR assay was performed to measure the relative mRNA expression of genes in clinical tissues and cell lines. Diagnostic efficiency was evaluated by the ROC curve. Prognostic value was assessed using the Kaplan-Meier curve, Cox regression model, and time-dependent ROC curve. Copy number variation (CNV) was analyzed using the GSCA database. Functional analysis was carried out with GSEA, GSVA, and clusterProfiler package. The tumor microenvironment (TME) related analysis was performed using ssGSEA and the ESTIMATE algorithm.Results: We identified 7 PUSs that were significantly upregulated in HCC, and 5 of them (DKC1, PUS1, PUS7, PUSL1, and RPUSD3) were independent risk factors for patients’ OS. Meanwhile, the protein expression of DKC1, PUS1, and PUS7 was also upregulated and related to poor survival. Both mRNA and protein of these PUSs were highly diagnostic of HCC. Moreover, the CNV of PUS1, PUS7, PUS7L, and RPUSD2 was also associated with prognosis. Further functional analysis revealed that PUSs were mainly involved in pathways such as genetic information processing, substance metabolism, cell cycle, and immune regulation.Conclusion: PUSs may play crucial roles in HCC and could be used as potential biomarkers for the diagnosis and prognosis of patients.

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Section: Introductionmentioning

confidence: 99%

Integrative multiomics evaluation reveals the importance of pseudouridine synthases in hepatocellular carcinoma

et al. 2022

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“…m 6 A methyltransferases and demethyltransferases were also involved in ovarian cancer progression through m 6 A-dependent or independent regulation 11,14 . A previous study identi ed pseudouridine synthase 7 (PUS7) that catalyzed RNA pseudouridine might be a potential biomarker of ovarian cancer, but its underlying mechanisms were not explored 51 . Our previous analysis of m 5 C modi cation genes in ovarian cancer showed that a signature constructed based on m 5 C modi cation genes could predict the poor prognosis of ovarian cancer 52 .…”

Section: Discussionmentioning

confidence: 99%

m5C RNA modiﬁcation upregulates E2F1 expression dependently on YBX1 phase separation and promotes tumor progression in ovarian cancer

Liu

Wei

et al. 2023

Preprint

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5-methylcytosine (m5C) is a common RNA modification that modulates gene expression at the post-transcriptional level, but the cross-talk between m5C RNA modification and biomolecule condensation as well as transcription factor-mediated transcriptional regulation in ovarian cancer remains poorly understood. In this study, we uncover that the RNA methytransferase NSUN2 facilitates m5C modification of mRNA and forms a positive feedback regulatory loop with the transcription factor E2F1 in ovarian cancer. Specifically, NSUN2 promotes m5C modification of E2F1 mRNA and enhances its stability, and E2F1 binds to NSUN2 promoter followed by the activated transcription reciprocally. The RNA binding protein YBX1 acts as the m5C reader and is involved in NSUN2-mediated E2F1 regulation. m5C modification promotes YBX1 phase separation that upregulates E2F1 expression. In ovarian cancer, NSUN2 and YBX1 are amplified and upregulated, and higher expressions of NSUN2 and YBX1 predict a worse prognosis for ovarian cancer patients. Moreover, E2F1 transcriptionally regulates the expression of oncogenes MYBL2 and RAD54L, driving ovarian cancer progression. Thus, our study delineates a NSUN2-E2F1-NSUN2 circuitry regulated by m5C modification dependently on YBX1 phase separation, and the identified previously unknown pathway can be a promising target for ovarian cancer treatment.

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“…Overexpression of FTO significantly promoted viability and autophagy, but reduced apoptosis in OCs ( 30 ). A bioinformatics analysis suggested that PUS7 was a potential marker for diagnosis and target for OC treatment ( 84 ). TET3 blocked epithelial-mesenchymal transition induced by TGF-β1 through demethylating miR-30d precursor gene promoter to suppress OCs ( 85 ).…”

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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The Identification of RNA Modification Gene PUS7 as a Potential Biomarker of Ovarian Cancer

Cited by 19 publications

References 42 publications

Integrative multiomics evaluation reveals the importance of pseudouridine synthases in hepatocellular carcinoma

Integrative multiomics evaluation reveals the importance of pseudouridine synthases in hepatocellular carcinoma

m5C RNA modiﬁcation upregulates E2F1 expression dependently on YBX1 phase separation and promotes tumor progression in ovarian cancer

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

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