The deubiquitinase USP10 regulates KLF4 stability and suppresses lung tumorigenesis

Wang, Xinyun; Xia, Shilin; Li, Hongchang; Li, Chaonan; Chao, Yulin; Zhang, Lingqiang; Han, Chuanchun

doi:10.1038/s41418-019-0458-7

Cited by 70 publications

(54 citation statements)

References 52 publications

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“…The expression of MFAP4 is negatively regulated by miR-147b in LUAD cells [ 36 ]. The deubiquitinase USP10 moderates KLF4 stability and suppresses lung tumorigenesis [ 37 ]. Although researchers have reported on some miRNAs and genes in ceRNA networks, further experimental methods are still required to reveal the efficacy and mechanisms of these ceRNA networks in regulating LUAD.…”

Section: Discussionmentioning

confidence: 99%

Potential Prognostic Biomarkers of Lung Adenocarcinoma Based on Bioinformatic Analysis

Hou

Cheng

2021

BioMed Research International

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Lung adenocarcinoma (LUAD), which accounts for 60% of non-small-cell lung cancers, is poorly diagnosed and has a low average 5-year survival rate (approximately 20%). It remains the leading cause of cancer-related deaths worldwide. Studies on long noncoding RNAs (lncRNAs) in LUAD-related competing endogenous RNA (ceRNA) networks are limited. We aimed to identify novel prognostic biomarkers for LUAD using bioinformatic tools and data analysis. We systemically integrated differentially expressed genes and clinically significant modules using weighted correlation network analysis. We performed a functional analysis of the collected candidate genes and explored three LUAD-related genes (VWF, PECAM1, and COL1A1) associated with the overall survival rates of patients with LUAD. Based on Cox proportional hazards analysis of candidate mRNAs and lncRNAs together with differentially expressed microRNAs, we constructed ceRNA networks, obtained 12 lncRNAs in the ceRNA networks, and revealed seven novel lncRNAs AC021016.2, AC079630.1, AC116407.1, AC125807.2, AF131215.5, LINC01936, and RHOXF1-AS1. These lncRNAs were found to be associated with overall survival rates and are suitable for the prediction of prognosis by Kaplan-Meier survival and receiver operating characteristic curve analyses. In particular, three lncRNAs—AF131215.5, AC125807.2, and LINC01936—showed an independent prognostic value of overall survival for patients with LUAD. We evaluated the diagnostic capabilities of seven lncRNAs for patients with LUAD using principal component analysis and the Gene Set Variation Analysis index. lncRNAs and crucial genes could be effectively used for distinguishing LUAD tumors from normal tissues in the Gene Expression Omnibus profile. In particular, AC021016.2 showed a significant prognostic value in the validation dataset. Our findings reveal the significance of exploring lncRNAs in cancer-related ceRNAs using bioinformatic strategies.

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Section: Discussionmentioning

confidence: 99%

Potential Prognostic Biomarkers of Lung Adenocarcinoma Based on Bioinformatic Analysis

Hou

Cheng

2021

BioMed Research International

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“…A recent study has shown that MAPK9 activity played an indispensable part in invasiveness and BRAFi resistance of melanoma cell ( 47 ). As for USP10, decreased expression of USP10 has been proved to be an indicator of poor prognosis in lung cancer and epithelial ovarian cancer ( 48 , 49 ). Moreover, numerous studies have demonstrated that USP10 inhibited mTOR activation and promoted oncogene-induced senescence to exert a tumor-suppressive effect ( 50 , 51 ).…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of Autophagy-Related Gene Signature and Nomogram for Predicting Survival in Oral Squamous Cell Carcinoma

et al. 2020

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Background: Autophagy, a highly conserved self-digesting process, has been deeply involved in the development and progression of oral squamous cell carcinoma (OSCC). However, the prognostic value of autophagy-related genes (ARGs) for OSCC still remains unclear. Our study set out to develop a multigene expression signature based on ARGs for individualized prognosis assessment in OSCC patients. Methods: Based on The Cancer Genome Atlas (TCGA) database, we identified prognosis-related ARGs through univariate COX regression analysis. Then we performed the least absolute shrinkage and selection operator (LASSO) regression analysis to identify an optimal autophagy-related multigene signature with the subsequent validation in testing set, GSE41613 and GSE42743 datasets. Results: We identified 36 prognosis-related ARGs for OSCC. Subsequently, the multigene signature based on 13 prognostic ARGs was constructed and successfully divided OSCC patients into low and high-risk groups with significantly different overall survival in TCGA training set (p < 0.0001). The autophagy signature remained as an independent prognostic factor for OSCC in univariate and multivariate Cox regression analyses. The area under the curve (AUC) values of the receiver operating characteristic (ROC) curves for 1, 3, and 5-year survival were 0.758, 0.810, 0.798, respectively. Then the gene signature was validated in TCGA testing set, GSE41613 and GSE42743 datasets. Moreover, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and single-sample gene set enrichment analysis (ssGSEA) revealed the underlying biological characteristics and signaling pathways associated with this signature in OSCC. Finally, we constructed a nomogram by combining the gene signature with multiple clinical parameters (age, gender, TNM-stage, tobacco, and alcohol history). The concordance index (C-index) and calibration plots demonstrated favorable predictive performance of our nomogram.

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“…In HCC the activity of KLF4 is regulated at the level of protein stability [ 51 ], alternative splicing [ 57 ], physical association with other proteins [ 56 ], as well as by various genetic and epigenetic mechanisms. In NSCLC the mechanisms of regulation of KLF4 activity include protein stability [ 71 ] and subcellular localization [ 72 ]. The latter is also important in prostate cancer [ 98 ].…”

Section: Discussionmentioning

confidence: 99%

“…In lung adenocarcinoma, which is one of the subtypes of NSCLC, the activity of KLF4 is regulated at the level of protein stability. Loss of ubiquitin-specific peptidase 10 (USP10) promotes lung tumorigenesis via the downregulation of KLF4 [ 71 ]. At the molecular level, USP10 deubiquitinates KLF4 and in this way it blocks KLF4 degradation.…”

Section: Lung Cancermentioning

confidence: 99%

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Recent Discoveries on the Involvement of Krüppel-Like Factor 4 in the Most Common Cancer Types

Taracha-Wisniewska

Kotarba

Dworkin

et al. 2020

IJMS

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Krüppel-like factor 4 (KLF4) is a transcription factor highly conserved in evolution. It is particularly well known for its role in inducing pluripotent stem cells. In addition, KLF4 plays many roles in cancer. The results of most studies suggest that KLF4 is a tumor suppressor. However, the functioning of KLF4 is regulated at many levels. These include regulation of transcription, alternative splicing, miRNA, post-translational modifications, subcellular localization, protein stability and interactions with other molecules. Simple experiments aimed at assaying transcript levels or protein levels fail to address this complexity and thus may deliver misleading results. Tumor subtypes are also important; for example, in prostate cancer KLF4 is highly expressed in indolent tumors where it impedes tumor progression, while it is absent from aggressive prostate tumors. KLF4 is important in regulating response to many known drugs, and it also plays a role in tumor microenvironment. More and more information is available about upstream regulators, downstream targets and signaling pathways associated with the involvement of KLF4 in cancer. Furthermore, KLF4 performs critical function in the overall regulation of tissue homeostasis, cellular integrity, and progression towards malignancy. Here we summarize and analyze the latest findings concerning this fascinating transcription factor.

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The deubiquitinase USP10 regulates KLF4 stability and suppresses lung tumorigenesis

Cited by 70 publications

References 52 publications

Potential Prognostic Biomarkers of Lung Adenocarcinoma Based on Bioinformatic Analysis

Potential Prognostic Biomarkers of Lung Adenocarcinoma Based on Bioinformatic Analysis

Development and Validation of Autophagy-Related Gene Signature and Nomogram for Predicting Survival in Oral Squamous Cell Carcinoma

Recent Discoveries on the Involvement of Krüppel-Like Factor 4 in the Most Common Cancer Types

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