Exonuclease 1 (Exo1) Participates in Mammalian Non-Homologous End Joining and Contributes to Drug Resistance in Ovarian Cancer

He, Dongxu; Li, Tao; Sheng, Minjia; Yang, Ben

doi:10.12659/msm.918751

Cited by 28 publications

(23 citation statements)

References 50 publications

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“…DNA topoisomerase 2-alpha ( TOP2A ), exodeoxyribonuclease 1 ( EXO1 ), serine/threonine-protein kinase Nek2 ( NEK2 ), baculoviral IAP repeat-containing protein 5 ( BIRC5 ), hyaluronan mediated motility receptor ( HMMR ), structural maintenance of chromosomes protein 4 ( SMC4 ), bloom syndrome protein ( BLM ), casein kinase I isoform epsilon ( CSNK1E ), cytoskeleton-associated protein 5 ( CKAP5 ), and inner centromere protein ( INCENP ) were identified as the hub genes based on the degrees of nodes which were more than 10 ( Figure 2 a) [ 11 ]. TOP2A , EXO1 , NEK2 , BIRC5 , SMC4 , BLM , CSNK1E , CKAP5 , and INCENP were related to DNA replication and cell division, and HMMR was related to cell motility [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 ]. The detailed functions of the hub genes are described in the discussion section and Supplementary Table S3 .…”

Section: Resultsmentioning

confidence: 99%

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Analysis of m6A RNA Methylation-Related Genes in Liver Hepatocellular Carcinoma and Their Correlation with Survival

Zhu

et al. 2021

IJMS

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N6-methyladenosine (m6A) modification on RNA plays an important role in tumorigenesis and metastasis, which could change gene expression and even function at multiple levels such as RNA splicing, stability, translocation, and translation. In this study, we aim to conduct a comprehensive analysis on m6A RNA methylation-related genes, including m6A RNA methylation regulators and m6A RNA methylation-modified genes, in liver hepatocellular carcinoma, and their relationship with survival and clinical features. Data, which consist of the expression of widely reported m6A RNA methylation-related genes in liver hepatocellular carcinoma from The Cancer Genome Atlas (TCGA), were analyzed by one-way ANOVA, Univariate Cox regression, a protein–protein interaction network, gene enrichment analysis, feature screening, a risk prognostic model, correlation analysis, and consensus clustering analysis. In total, 405 of the m6A RNA methylation-related genes were found based on one-way ANOVA. Among them, DNA topoisomerase 2-alpha (TOP2A), exodeoxyribonuclease 1 (EXO1), ser-ine/threonine-protein kinase Nek2 (NEK2), baculoviral IAP repeat-containing protein 5 (BIRC5), hyaluronan mediated motility receptor (HMMR), structural maintenance of chromosomes protein 4 (SMC4), bloom syndrome protein (BLM), ca-sein kinase I isoform epsilon (CSNK1E), cytoskeleton-associated protein 5 (CKAP5), and inner centromere protein (INCENP), which were m6A RNA methylation-modified genes, were recognized as the hub genes based on the protein–protein interaction analysis. The risk prognostic model showed that gender, AJCC stage, grade, T, and N were significantly different between the subgroup with the high and low risk groups. The AUC, the evaluation parameter of the prediction model which was built by RandomForest, was 0.7. Furthermore, two subgroups were divided by consensus clustering analysis, in which stage, grade, and T differed. We identified the important genes expressed significantly among two clusters, including uridine-cytidine kinase 2 (UCK2), filensin (BFSP1), tubulin-specific chaperone D (TBCD), histone-lysine N-methyltransferase PRDM16 (PRDM16), phosphorylase b ki-nase regulatory subunit alpha (PHKA2), serine/threonine-protein kinase BRSK2 (BRSK2), Arf-GAP with coiled-coil (ACAP3), general transcription factor 3C polypep-tide 2 (GTF3C2), and guanine nucleotide exchange factor MSS4 (RABIF). In our study, the m6A RNA methylation-related genes in liver hepatocellular carcinoma were analyzed systematically, including the expression, interaction, function, and prognostic values, which provided an important theoretical basis for m6A RNA methylation in liver cancer. The nine important m6A-related genes could be prognostic markers in the survival time of patients.

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Section: Resultsmentioning

confidence: 99%

“…EXO1 genes which are related to mismatch repairing were recognized as the new cancer driver genes in a recent study, which are closely related to m6A RNA methylation-related genes [ 15 ].…”

Section: Discussionmentioning

confidence: 99%

Analysis of m6A RNA Methylation-Related Genes in Liver Hepatocellular Carcinoma and Their Correlation with Survival

Zhu

et al. 2021

IJMS

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“… 40 Moreover, cell cycle-associated proteins have been shown to modulate the effectiveness of radiation and chemotherapy. 41 , 42 Several SNPs of EXO1 have been confirmed to be associated with radiotherapy or chemotherapy resistance, such as radiotherapy resistance in glioblastoma cell lines, 38 chemotherapy resistance in ovarian cancer, 43 and resistance to cisplatin treatment in NSCLC patients. 44 And in our study, we found that EXO1 was highly expressed in TP53-mutant group compared with TP53-wild-type group in LUAD.…”

Section: Discussionmentioning

confidence: 99%

Exonuclease 1 (EXO1) is a Potential Prognostic Biomarker and Correlates with Immune Infiltrates in Lung Adenocarcinoma

Zhou¹,

Feng²,

Chen³

et al. 2021

OTT

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Background Exonuclease 1 (EXO1) has been identified to be highly expressed in different human malignancies, but its expression and prognostic role in lung adenocarcinoma (LUAD) remain unknown. Materials and Methods Two independent cohorts extracted from public databases and one cohort from our center were analyzed in this study. Expression levels of EXO1 in LUAD tissues and paired para-cancer tissues were detected. The prognostic value of EXO1 in LUAD patients was evaluated in the three cohorts. Enrichment analyses were performed to explore the possible underlying biological pathways. Moreover, we also explored the correlations between EXO1 and tumor-infiltrating immune cells and evaluated the impact of EXO1 knock-down on the migration of lung cancer cells. Results In this study, we found that EXO1 was highly expressed in LUAD tissues compared with para-cancerous tissues in public databases ( p < 0.01), which was consistent with our data ( p < 0.01). Survival analysis indicated that high expression of EXO1 was associated with poor prognosis in LUAD ( p < 0.01). Enrichment analyses indicated that biological pathways like cell cycle regulation, DNA damage and repair, immune response, neuroactive ligand-receptor interaction, may be associated with EXO1 aberrant expression. Moreover, high expression of EXO1 was correlated with decreased infiltrating B cells ( p < 0.01) and CD4+ T cells ( p < 0.01) levels, and low infiltrating levels of B cells ( p < 0.01) and dendritic cells (DCs) ( p < 0.05) indicated poor overall survival (OS) in LUAD. Additionally, in vitro experiments suggested that knockdown of EXO1 may inhibit the migratory ability of lung cancer cells. Conclusion In conclusion, EXO1 is a potential prognostic biomarker in LUAD, and correlates with infiltrating levels of immune cells in the tumor microenvironment. Further prospective validation of EXO1 in lung cancer is warranted.

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“…Centromere protein I (CENPI) is a structural component of the kinetochore, required for timely progression through G2 phase, mitosis, and chromosome stability [48,49]. Exonuclease I (EXO1) contributes to the regulation of the cell cycle checkpoints, the maintenance of the replication fork, DNA repair, and genomic instability [50,51]. Kinetochore scaffold 1 (KNL1) is essential in spindle assembly checkpoints, chromosome segregation, and kinetochore-microtubule attachments [52,53].…”

Section: Discussionmentioning

confidence: 99%

In Silico Methods for the Identification of Diagnostic and Favorable Prognostic Markers in Acute Myeloid Leukemia

Yilmaz

Toy

Marquardt

et al. 2021

IJMS

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Acute myeloid leukemia (AML), the most common type of acute leukemia in adults, is mainly asymptomatic at early stages and progresses/recurs rapidly and frequently. These attributes necessitate the identification of biomarkers for timely diagnosis and accurate prognosis. In this study, differential gene expression analysis was performed on large-scale transcriptomics data of AML patients versus corresponding normal tissue. Weighted gene co-expression network analysis was conducted to construct networks of co-expressed genes, and detect gene modules. Finally, hub genes were identified from selected modules by applying network-based methods. This robust and integrative bioinformatics approach revealed a set of twenty-four genes, mainly related to cell cycle and immune response, the diagnostic significance of which was subsequently compared against two independent gene expression datasets. Furthermore, based on a recent notion suggesting that molecular characteristics of a few, unusual patients with exceptionally favorable survival can provide insights for improving the outcome of individuals with more typical disease trajectories, we defined groups of long-term survivors in AML patient cohorts and compared their transcriptomes versus the general population to infer favorable prognostic signatures. These findings could have potential applications in the clinical setting, in particular, in diagnosis and prognosis of AML.

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Exonuclease 1 (Exo1) Participates in Mammalian Non-Homologous End Joining and Contributes to Drug Resistance in Ovarian Cancer

Cited by 28 publications

References 50 publications

Analysis of m6A RNA Methylation-Related Genes in Liver Hepatocellular Carcinoma and Their Correlation with Survival

Analysis of m6A RNA Methylation-Related Genes in Liver Hepatocellular Carcinoma and Their Correlation with Survival

Exonuclease 1 (EXO1) is a Potential Prognostic Biomarker and Correlates with Immune Infiltrates in Lung Adenocarcinoma

In Silico Methods for the Identification of Diagnostic and Favorable Prognostic Markers in Acute Myeloid Leukemia

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