Depletion of TRRAP Induces p53‐Independent Senescence in Liver Cancer by Down‐Regulating Mitotic Genes

Kwan, Suet‐Yan; Sheel, Ankur; Song, Chun‐Qing; Zhang, Xiao‐Ou; Jiang, Tingting; Dang, Hien; Cao, Yusong; Özata, Deniz M.; Mou, Haiwei; Yin, Hao; Weng, Zhiping; Wang, Xin Wei; Xue, Wen

doi:10.1002/hep.30807

Cited by 52 publications

(43 citation statements)

References 52 publications

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“…The transcription factor and tumor suppressor p53 is closely related to DNA repair, cellular stress response, and cell cycle control [11,12]. In response to cellular stress signals, the tumor suppressor p53 activates a large number of genes responsible for cell cycle regulation, DNA repair, and apoptosis [13,14].…”

Section: Introductionmentioning

confidence: 99%

ZNF143 Suppresses Cell Apoptosis and Promotes Proliferation in Gastric Cancer via ROS/p53 Axis

Zhang

Song

et al. 2020

Disease Markers

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Aim. This study was aimed at identifying the role of zinc finger protein 143 (ZNF143) in gastric cancer (GC) progression. Methods. The impact of ZNF143 on the proliferation ability and apoptosis of GC cells was detected. The expression of ZNF143 and related targeted genes was determined using Western blot analysis. The reactive oxygen species (ROS) level of GC cells was examined using the ROS generation assay. The role of ZNF143 in the proliferation of GC cells in vivo was examined using tumor xenograft assay. Results. The ectopic overexpression of ZNF143 promoted the proliferation of GC cells, while its knockdown reduced the effect in vitro. The downregulation of ZNF143 facilitated cell apoptosis. ZNF143 decreased the ROS level in GC cells, resulting in the reduction of cell apoptosis. Transfection with p53 reversed the antiapoptotic effect of ZNF143, while pifithrin-α, a specific inhibitor of p53, reduced the apoptosis in ZNF143-knockdown GC cells. However, p53 had no influence on the ROS level in GC cells. p53 played a key role in inhibiting ROS generation in GC cells, thereby inhibiting apoptosis. The transplanted tumor weight and volume were higher in the ZNF143-overexpressed group than in the ZNF143-knockdown group in vivo. The expression of ZNF143 in the transplanted tumor correlated positively with the proliferation index of Ki67 and negatively with the expression of p53 and cell apoptosis. Conclusion. ZNF143, as a tumor oncogene, promoted the proliferation of GC cells both in vitro and in vivo, indicating that ZNF143 might function as a novel target for GC therapy.

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Section: Introductionmentioning

confidence: 99%

ZNF143 Suppresses Cell Apoptosis and Promotes Proliferation in Gastric Cancer via ROS/p53 Axis

Zhang

Song

et al. 2020

Disease Markers

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“…23 The competitive relationship influences the inhibition of miRNAs to mRNAs, resulting in downstream pathological processes like osteoarthritis, cerebral ischemia, and cancers. [24][25][26][27] However, the prognosis function of lncRNAs in breast cancer, especially luminal, is less known.…”

Section: Introductionmentioning

confidence: 99%

<p>Construction and Analysis of a Long Non-Coding RNA-Associated Competing Endogenous RNA Network Identified Potential Prognostic Biomarkers in Luminal Breast Cancer</p>

Zhou¹,

Cheng²,

Luo³

et al. 2020

OTT

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Purpose: To construct a competing endogenous RNA (ceRNA) topology network of RNAseq data and micro RNA-seq (miRNA-seq) data to identify key prognostic long non-coding RNA (lncRNAs) in luminal breast cancer, and validate the results by human luminal breast cancer samples. Materials and Methods: The RNA-seq data and miRNA-seq data of luminal A breast cancer in the The Cancer Genome Atlas (TCGA) database were downloaded and compared with those in the miRcode database to obtain lncRNA-miRNA relationship pairs. Final target genes were predicted by all three databases (miRDB, miRTarBase, and TargetScan), thereby obtaining the miRNA-messenger RNA (miRNA-mRNA) relationship pairs and a ceRNA topology network was constructed, then mRNA enrichment analysis, ceRNA topological and stability analysis, univariate and multivariate Cox regression analysis were performed. Overall survival (OS) was evaluated and the key prognostic RNAs were identified. The expression difference between normal and tumor, as well as the correlation of high expression in tumor with pathological parameters (Ki-67, Grade, tumor diameter) were validated by human breast cancer specimens. Results: A ceRNA topology network was constructed and six lncRNAs were finally identified (The higher expression of PART1, IGF2.AS, WT1.AS, OIP5.AS1, and SLC25A5. AS1 was associated with poor prognosis while AL035706.1 was adverse) and the poor prognostic ones were higher expressed in tumor tissue and correlated with a higher Ki-67 (>10%), tumor grades (II, III) and tumor diameters (>1.5 cm). Using six lncRNAs, we constructed a prognostic model, which performed well for the classification of prognosis in the module. Conclusion: We identified and verified six biomarkers (OS-predicting) in luminal breast cancer, which significantly enriched the prediction and potential targets of this subtype.

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“…Moreover, TRRAP induced HCC cell proliferation by upregulating mitotic gene TOP2A, which provided a potential therapeutic strategy for HCC [55]. Ayuko Saeki et al have detected some polymorphic base changes of CDC20 in HCC cell lines or specimens [56].…”

Section: Discussionmentioning

confidence: 99%

Identifying Potential Prognostic Biomarkers Associated With Clinicopathologic Characteristics of Hepatocellular Carcinoma by Bioinformatics Analysis

Huang

Yao

Lai

et al. 2021

Preprint

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Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide. However, the molecular mechanisms of HCC remain largely unknown so far. Methods: To unravel the underlying carcinogenic mechanisms, we utilized Robust Rank Aggregation analysis (RRA) to identify a set of overlapping differentially expressed genes (DEGs) from 5 microarray datasets on Gene Expression Omnibus (GEO) database. Enriched Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of DEGs were conducted. The protein‐protein interaction (PPI) network was constructed and Cytoscape V3.8.0 was used for selecting hub genes. The expression of hub genes was validated in TCGA datasets and HCC samples in our center by qPCR and immunohistochemistry analysis. Results: Totally 126 DEGs were identified. GO and KEGG pathways of DEGs mostly associated with “organelle fission”, “nuclear division” and “caffeine metabolism. Ten hub genes (BUB1B, CDKN3, CCNB1, CCNB2, CDK1, TOP2A, CDC20, MELK, NUSAP1, AURKA) were selected. Overall survival (OS) and progression-free survival (PFS) analysis suggested the good value of these genes for HCC diagnosis and prognosis. These genes were upregulated in HCC samples from TCGA, which were associated with higher tumor grades and possibly resulted from hypomethylation. Moreover, these hub genes were markedly dysregulated in HCC samples in our center and significantly associated with clinicopathologic characteristics of HCC patients. Conclusions: In conclusion, our study identified several hub genes as novel candidate biomarkers for diagnosis and prognosis of HCC, which may provide new insight into HCC pathogenesis in order to search for better treatments.

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Depletion of TRRAP Induces p53‐Independent Senescence in Liver Cancer by Down‐Regulating Mitotic Genes

Cited by 52 publications

References 52 publications

ZNF143 Suppresses Cell Apoptosis and Promotes Proliferation in Gastric Cancer via ROS/p53 Axis

ZNF143 Suppresses Cell Apoptosis and Promotes Proliferation in Gastric Cancer via ROS/p53 Axis

<p>Construction and Analysis of a Long Non-Coding RNA-Associated Competing Endogenous RNA Network Identified Potential Prognostic Biomarkers in Luminal Breast Cancer</p>

Identifying Potential Prognostic Biomarkers Associated With Clinicopathologic Characteristics of Hepatocellular Carcinoma by Bioinformatics Analysis

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