Flap endonuclease 1 Facilitated Hepatocellular Carcinoma Progression by Enhancing USP7/MDM2-mediated P53 Inactivation

Bian, Saiyan; Ni, Wenkai; Zhu, Mengqi; Zhang, Xue; Qiang, Yuwei; Zhang, Jianping; Ni, Zhiyu; Shen, Yiping; Qiu, Shi; Song, Qisheng; Xiao, Mingbing; Zheng, Wenjie

doi:10.7150/ijbs.68179

Cited by 34 publications

(21 citation statements)

References 33 publications

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“…Furthermore, Saiyan et al. ( 15 ) suggested that Flap endonuclease 1 Facilitated hepatocellular carcinoma progression by enhancing USP7/MDM2-mediated P53 inactivation. However, previous bioinformatics studies were relatively simple: no multi-omics integration analysis or assessment of tumor mutation burden (TMB) was used, or focusing on exploration of the single gene, or without experimental validation.…”

Section: Introductionmentioning

confidence: 99%

Identification of clinical prognostic features of esophageal cancer based on m6A regulators

et al. 2022

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BackgroundEsophageal cancer (ESCA) is a common malignancy with high morbidity and mortality. n6-methyladenosine (m6A) regulators have been widely recognized as one of the major causes of cancer development and progression. However, for ESCA, the role of regulators is unclear. The aim of this study was to investigate the role of m6A RNA methylation regulators in the immune regulation and prognosis of ESCA.MethodsRNA-seq data were downloaded using the Cancer Genome Atlas (TCGA) database, and the expression differences of m6A RNA methylation regulators in ESCA were analyzed. Further m6A methylation regulator markers were constructed, and prognostic and predictive values were assessed using survival analysis and nomograms. Patients were divided into low-risk and high-risk groups. The signature was evaluated in terms of survival, single nucleotide polymorphism (SNP), copy number variation (CNV), tumor mutation burden (TMB), and functional enrichment analysis (TMB). The m6A expression of key genes in clinical specimens was validated using quantitative reverse transcription polymerase chain reaction (qRT-PCR).ResultsIn ESCA tissues, most of the 23 regulators were significantly differentially expressed. LASSO regression analysis included 7 m6A-related factors (FMR1, RBMX, IGFBP1, IGFBP2, ALKBH5, RBM15B, METTL14). In addition, this study also identified that the risk model is associated with biological functions, including base metabolism, DNA repair, and mismatch repair. In this study, a nomogram was created to predict the prognosis of ESCA patients. Bioinformatics analysis of human ESCA and normal tissues was performed using qRT-PCR. Finally. Seven genetic features were found to be associated with m6A in ESCA patients. The results of this study suggest that three different clusters of m6A modifications are involved in the immune microenvironment of ESCA, providing important clues for clinical diagnosis and treatment.

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Section: Introductionmentioning

confidence: 99%

Identification of clinical prognostic features of esophageal cancer based on m6A regulators

et al. 2022

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“…FEN1 has been found to have abnormal expression or mutation in a variety of solid tumors, which has promoted the proliferation and migration of tumor cells [ 50 ]. FEN1 has also been found to be closely related to tumor chemotherapy resistance, and is considered to be a marker of metastasis and poor prognosis of various malignant tumors [ 61 ]. Therefore, FEN1 is considered to be an effective target for the treatment of tumors.…”

Section: Discussionmentioning

confidence: 99%

“…These breaks activated the G2/M checkpoint protein Chk1 and induced near-tetraploid aneuploidy, promoting the development of aneuploid cancers. Overexpression of FEN can promote the proliferation, cell cycle, migration or invasion, drug resistance, xenograft growth and epithelial mesenchymal transition (EMT) of hepatoma cells [ 61 ]. In addition, the abnormally high expression of IGF2BP2, a key gene in the m6A signaling pathway, was found in HCC cells.…”

Section: The Role Of Fen1 In Diseasesmentioning

confidence: 99%

Small-Molecule Inhibitors Targeting FEN1 for Cancer Therapy

Yang

Guo

2022

Biomolecules

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DNA damage repair plays a key role in maintaining genomic stability and integrity. Flap endonuclease 1 (FEN1) is a core protein in the base excision repair (BER) pathway and participates in Okazaki fragment maturation during DNA replication. Several studies have implicated FEN1 in the regulation of other DNA repair pathways, including homologous recombination repair (HRR) and non-homologous end joining (NHEJ). Abnormal expression or mutation of FEN1 in cells can cause a series of pathological responses, leading to various diseases, including cancers. Moreover, overexpression of FEN1 contributes to drug resistance in several types of cancers. All this supports the hypothesis that FEN1 could be a therapeutic target for cancer treatment. Targeting FEN1 has been verified as an effective strategy in mono or combined treatment of cancer. Small-molecule compounds targeting FEN1 have also been developed and detected in cancer regression. In this review, we summarize the recent development of small-molecule inhibitors targeting FEN1 in recent years, thereby expanding their therapeutic potential and application.

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“…Biomarkers commonly used as part of routine clinical practice can complement clinical examination and contribute to the management of various diseases. The advance of the new sequencing approach and access to some huge genetic and epigenetic databases including TCGA and GEO, are providing potential biomarkers options and the focus is shifting to a combination of several or more biomarkers, rather than a single marker that researchers have concentrated on in the past ( Conway and Wong, 2020 ; Vincent et al, 2020 ; Bian et al, 2022 ). In this study, we conducted an integrative analysis of gene expression and DNA methylation data, and identified the DMGs and DEGs between PD patients and healthy controls.…”

Section: Discussionmentioning

confidence: 99%

Integrative analysis of DNA methylation and gene expression data for the diagnosis and underlying mechanism of Parkinson’s disease

Ding

Liang²,

Guo³

et al. 2022

Front. Aging Neurosci.

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BackgroundParkinson’s disease (PD) is the second most common progressive neurodegenerative disorder and the leading cause of disability in the daily activities. In the management of PD, accurate and specific biomarkers in blood for the early diagnosis of PD are urgently needed. DNA methylation is one of the main epigenetic mechanisms and associated with the gene expression and disease initiation of PD. We aimed to construct a methylation signature for the diagnosis of PD patients, and explore the potential value of DNA methylation in therapeutic options.Materials and methodsWhole blood DNA methylation and gene expression data of PD patients as well as healthy controls were extracted from Gene Expression Omnibus database. Next, differentially expressed genes (DEGs) and differentially methylated genes (DMGs) between PD patients and healthy controls were identified. Least absolute shrinkage and selection operator cox regression analysis was carried out to construct a diagnostic signature based on the overlapped genes. And, the receiver operating characteristic (ROC) curves were drawn and the area under the curve (AUC) was used to assess the diagnostic performance of the signature in both the training and testing datasets. Finally, gene ontology and gene set enrichment analysis were subsequently carried out to explore the underlying mechanisms.ResultsWe obtained a total of 9,596 DMGs, 1,058 DEGs, and 237 overlapped genes in the whole blood between PD patients and healthy controls. Eight methylation-driven genes (HIST1H4L, CDC42EP3, KIT, GNLY, SLC22A1, GCM1, INO80B, and ARHGAP26) were identified to construct the gene expression signature. The AUCs in predicting PD patients were 0.84 and 0.76 in training dataset and testing dataset, respectively. Additionally, eight methylation-altered CpGs were also identified to construct the CpGs signature which showed a similarly robust diagnostic capability, with AUCs of 0.8 and 0.73 in training dataset and testing dataset, respectively.ConclusionWe conducted an integrated analysis of the gene expression and DNA methylation data, and constructed a methylation-driven genes signature and a methylation-altered CpGs signature to distinguish the patients with PD from healthy controls. Both of them had a robust prediction power and provide a new insight into personalized diagnostic and therapeutic strategies for PD.

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Flap endonuclease 1 Facilitated Hepatocellular Carcinoma Progression by Enhancing USP7/MDM2-mediated P53 Inactivation

Cited by 34 publications

References 33 publications

Identification of clinical prognostic features of esophageal cancer based on m6A regulators

Identification of clinical prognostic features of esophageal cancer based on m6A regulators

Small-Molecule Inhibitors Targeting FEN1 for Cancer Therapy

Integrative analysis of DNA methylation and gene expression data for the diagnosis and underlying mechanism of Parkinson’s disease

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