miR‐4324‐RACGAP1‐STAT3‐ESR1 feedback loop inhibits proliferation and metastasis of bladder cancer

Ge, Qiangqiang; Lü, Mengxin; Ju, Lingao; Qian, Kaiyu; Wang, Gang; Wu, Chin Lee; Li, Xuefeng; Xiao, Yu; Wang, Xinghuan

doi:10.1002/ijc.32036

Cited by 48 publications

(39 citation statements)

References 38 publications

(75 reference statements)

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“…miR-4324 has been demonstrated to be abnormally expressed in several human cancers and to function as a tumor suppressor. [8][9][10][11] In this study, we showed that miR-4324 expression was reduced in CRC tissues and cell lines compared with normal tissues and cell line. We also showed that overexpression of miR-4324 inhibited CRC cell growth, migration, and invasion.…”

Section: Discussionmentioning

confidence: 63%

RETRACTED: miR-4324 functions as a tumor suppressor in colorectal cancer by targeting HOXB2

Zhu

Xing

et al. 2019

J Int Med Res

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Objective MicroRNAs (miRNAs) are reported to have crucial roles in human cancers; however, their role in colorectal cancer (CRC) remains largely unknown. Methods In this study, we analyzed the expression of miR-4324 in CRC cell lines using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). We also examined miR-4324 expression in CRC tumor tissues using a miRNA expression dataset obtained from the Gene Expression Omnibus. We validated the connection between miR-4324 and homeobox B2 (HOXB2) using a luciferase activity reporter assay and western blotting. The effects of miR-4324 and HOXB2 on CRC cell malignant behaviors in vitro were further investigated. Results miR-4324 expression was significantly decreased in both CRC tumor tissues and cell lines. Overexpression of miR-4324 suppressed CRC cell proliferation, migration, and invasion. In contrast, overexpression of HOXB2 promoted CRC malignant cell behaviors. Furthermore, we validated HOXB2 as a direct target of miR-4324. Conclusions miR-4324 expression was decreased in CRC. miR-4324 regulates CRC cell proliferation, migration, and invasion by targeting HOXB2.

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Section: Discussionmentioning

confidence: 63%

RETRACTED: miR-4324 functions as a tumor suppressor in colorectal cancer by targeting HOXB2

Zhu

Xing

et al. 2019

J Int Med Res

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“…Knocking out RACGAP1 in hepatocellular carcinoma cells hampered cytokinesis and induced cell apoptosis [38]. Upregulated RACGAP1 predicted the poor outcomes in patients with hepatocellular carcinoma [38], ovarian cancer [39], and bladder cancer [40]. However, there are no preclinical or clinical studies demonstrating the role of RACGAP1 in LUAD.…”

Section: Discussionmentioning

confidence: 99%

Identifying Tumorigenesis and Prognosis-Related Genes of Lung Adenocarcinoma: Based on Weighted Gene Coexpression Network Analysis

Qin

et al. 2020

BioMed Research International

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Lung adenocarcinoma is the most frequently diagnosed subtype of nonsmall cell lung cancer. The molecular mechanisms of the initiation and progression of lung adenocarcinoma remain to be further determined. This study aimed to screen genes related to the progression of lung adenocarcinoma. By weighted gene coexpression network analysis (WGCNA), we constructed a free-scale gene coexpression network to evaluate the correlations between multiple gene sets and patients’ clinical traits, then further identify predictive biomarkers. GSE11969 was obtained from the Gene Expression Omnibus (GEO) database which contained the gene expression data of 90 lung adenocarcinoma patients. Data of the Cancer Genome Atlas (TCGA) were employed as the validation cohort. After the average linkage hierarchical clustering, a total of 9 modules were generated. In the clinical significant module (R = 0.44, P<0.0001), we identified 29 network hub genes. Subsequent verification in the TCGA database showed that 11 hub genes (ANLN, CDCA5, FLJ21924, LMNB1, MAD2L1, RACGAP1, RFC4, SNRPD1, TOP2A, TTK, and ZWINT) were significantly associated with poor survival data of lung adenocarcinomas. Besides, the results of receiver operating characteristic curves indicated that the mRNA levels of this group of genes exhibited high specificity and sensitivity to distinguish malignant lesions from nonmalignant tissues. Apart from mRNA levels, we found that the protein abundances of these 11 genes were remarkably upregulated in lung adenocarcinomas compared with normal tissues. In conclusion, by the WGCNA method, a panel of 11 genes were identified as predictive biomarkers for tumorigenesis and poor prognosis of lung adenocarcinomas.

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“…18 To monitoring the recurrence and progression of BCa, the patients had to undergo cystoscopy after surgery, which will bring a huge mental and economic burden to the patient. [21][22][23] These biomarkers may contribute to the prediction of prognosis for BCa patients. [21][22][23] These biomarkers may contribute to the prediction of prognosis for BCa patients.…”

Section: Discussionmentioning

confidence: 99%

“…19,20 Our group has previously found some biomarkers related to BCa prognosis and carcinogenesis. [21][22][23] These biomarkers may contribute to the prediction of prognosis for BCa patients. Nevertheless, a single biomarker lacks sufficiently accuracy and effectiveness, the comprehensive methods combined several biomarkers can significantly improve the accuracy and effectiveness.…”

Section: Discussionmentioning

confidence: 99%

An outcome model for human bladder cancer: A comprehensive study based on weighted gene co‐expression network analysis

Xiong

Yuan

Xiong

et al. 2019

J Cellular Molecular Medi

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The precision evaluation of prognosis is crucial for clinical treatment decision of bladder cancer (BCa). Therefore, establishing an effective prognostic model for BCa has significant clinical implications. We performed WGCNA and DEG screening to initially identify the candidate genes. The candidate genes were applied to construct a LASSO Cox regression analysis model. The effectiveness and accuracy of the prognostic model were tested by internal/external validation and pan-cancer validation and time-dependent ROC. Additionally, a nomogram based on the parameter selected from univariate and multivariate cox regression analysis was constructed.Eight genes were eventually screened out as progression-related differentially expressed candidates in BCa. LASSO Cox regression analysis identified 3 genes to build up the outcome model in E-MTAB-4321 and the outcome model had good performance in predicting patient progress free survival of BCa patients in discovery and test set. Subsequently, another three datasets also have a good predictive value for BCa patients' OS and DFS. Time-dependent ROC indicated an ideal predictive accuracy of the outcome model. Meanwhile, the nomogram showed a good performance and clinical utility. In addition, the prognostic model also exhibits good performance in pan-cancer patients. Our outcome model was the first prognosis model for human bladder cancer progression prediction via integrative bioinformatics analysis, which may aid in clinical decision-making. K E Y W O R D S bladder cancer, Gene Expression Omnibus (GEO), LASSO, prognosis, WGCNA S U PP O RTI N G I N FO R M ATI O N Additional supporting information may be found online in the Supporting Information section. How to cite this article: Xiong Y, Yuan L, Xiong J, et al. An outcome model for human bladder cancer: A comprehensive study based on weighted gene co-expression network analysis.

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miR‐4324‐RACGAP1‐STAT3‐ESR1 feedback loop inhibits proliferation and metastasis of bladder cancer

Cited by 48 publications

References 38 publications

RETRACTED: miR-4324 functions as a tumor suppressor in colorectal cancer by targeting HOXB2

RETRACTED: miR-4324 functions as a tumor suppressor in colorectal cancer by targeting HOXB2

Identifying Tumorigenesis and Prognosis-Related Genes of Lung Adenocarcinoma: Based on Weighted Gene Coexpression Network Analysis

An outcome model for human bladder cancer: A comprehensive study based on weighted gene co‐expression network analysis

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