miR-655-3p inhibits cell migration and invasion by targeting pituitary tumor-transforming 1 in non-small cell lung cancer

Wang, Wei; Cao, Ranhua; Su, Wuyun; Li, Yulian; Yan, Haicheng

doi:10.1080/09168451.2019.1617109

Cited by 25 publications

(15 citation statements)

References 13 publications

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“…Hub genes and their corresponded target miRNAs are presented in Table . Finally, 31 miRNAs, whose functions were correlated with tumor progression (Chang et al, ; Chang et al, ; Chen et al, ; Gao et al, ; Gu et al, ; Han et al, ; He et al, ; Kucuksayan et al, ; Li, Ma, Zhang, Ji, & Jin, ; Li, Ran, et al, ; Li & He, ; Li, Fu, et al, ; Li, Cui, Li, Zhang, & Li, ; Liu et al, ; Liu, Liu, Deng, et al, ; Liu, Liu, & Lu, ; Liu, Liu, Zhang, Tong, & Gan, ; Liu, Miao, et al, ; Luo et al, ; Tang et al, ; Wang et al, ; Wang, Cao, Su, Li, & Yan, ; Wu et al, ; Wu, Mo, Wan, Dan, & Hu, ; Xia, Jing, Li, & Lv, ; Xu et al, ; Zeng et al, ; Zhang, Hao, et al, ; Zhang et al, , ; Zhu et al, ), drug resistance (Bian et al, ; Gao et al, ; Lin, Xie, Lu, Hu, & Chang, ; Pan, Chen, Shen, & Tantai, ; Su et al, ; Xu et al, ; Zhou, Wang, & Feng, ), radiosensitivity (Liu, Li, & Gao, ), recurrence (Sim et al, ) or autophagy (Pan et al, ) in lung cancer, were identified (Table ).…”

Section: Resultsmentioning

confidence: 99%

Common and distinct features of potentially predictive biomarkers in small cell lung carcinoma and large cell neuroendocrine carcinoma of the lung by systematic and integrated analysis

Dong

Liang

Zhai

et al. 2020

Molec Gen & Gen Med

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Background Large‐cell neuroendocrine carcinoma of the lung (LCNEC) and small‐cell lung carcinoma (SCLC) are neuroendocrine neoplasms. However, the underlying mechanisms of common and distinct genetic characteristics between LCNEC and SCLC are currently unclear. Herein, protein expression profiles and possible interactions with miRNAs were provided by integrated bioinformatics analysis, in order to explore core genes associated with tumorigenesis and prognosis in SCLC and LCNEC. Methods http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE1037 gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in LCNEC and SCLC, as compared with normal lung tissues, were selected using the GEO2R online analyzer and Venn diagram software. Gene ontology (GO) analysis was performed using Database for Annotation, Visualization and Integrated Discovery. The biological pathway analysis was performed using the FunRich database. Subsequently, a protein–protein interaction (PPI) network of DEGs was generated using Search Tool for the Retrieval of Interacting Genes and displayed via Cytoscape software. The PPI network was analyzed by the Molecular Complex Detection app from Cytoscape, and 16 upregulated hub genes were selected. The Oncomine database was used to detect expression patterns of hub genes for validation. Furthermore, the biological pathways of these 16 hub genes were re‐analyzed, and potential interactions between these genes and miRNAs were explored via FunRich. Results A total of 384 DEGs were identified. A Venn diagram determined 88 common DEGs. The PPI network was constructed with 48 nodes and 221 protein pairs. Among them, 16 hub genes were extracted, 14 of which were upregulated in SCLC samples, as compared with normal lung specimens, and 10 were correlated with the cell cycle pathway. Furthermore, 57 target miRNAs for 8 hub genes were identified, among which 31 miRNAs were correlated with the progression of carcinoma, drug‐resistance, radio‐sensitivity, or autophagy in lung cancer. Conclusion This study provided effective biomarkers and novel therapeutic targets for diagnosis and prognosis of SCLC and LCNEC.

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Section: Resultsmentioning

confidence: 99%

Common and distinct features of potentially predictive biomarkers in small cell lung carcinoma and large cell neuroendocrine carcinoma of the lung by systematic and integrated analysis

Dong

Liang

Zhai

et al. 2020

Molec Gen & Gen Med

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“…Currently, the aberrant expression of miR-655-3p was reported to associate with the behaviors of tumor cells. For instance, Wang et al reported that miR-655-3p was low expressed in non-small cell lung cancer, miR-655-3p mimics resulted in the impediment of cell metastasis [18]. Another study in hepatocellular carcinoma (HCC) demonstrated that the low expression of miR-655-3p in HCC promoted cell growth, metastasis [24].…”

Section: Discussionmentioning

confidence: 99%

“…The similar results about miR-3619-5p [6], miR-492 [15], and miR-758 [16] were also found in RB. MiR-655-3p has been reported to impact cell behaviors of tumor progression in ovarian cancer [17], non-small cell lung cancer [18]. ATPase family AAA domain containing 2 (ATAD2), located on human chromosome 8q24, is a member of the ATPase family containing an AAA domain which is vital for ATPase activity and protein assembly [19].…”

mentioning

confidence: 99%

Long non-coding RNA MALAT1 regulated ATAD2 to facilitate retinoblastoma progression by sponging miR-655-3p

Zhao¹,

Wang²,

Gao³

et al. 2020

Preprint

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Background: Long non-coding RNA (lncRNA) metastasis associated lung adenocarcinoma transcript 1 (MALAT1) was reported as an oncogene in many tumors including retinoblastoma (RB). This research mainly focused on the functions and mechanism of MALAT1 in RB.Methods: The levels of MALAT1, microRNA-655-3p (miR-655-3p), and ATPase family AAA domain containing 2 (ATAD2) in RB tissues and cells were measured by quantitative real-time polymerase chain reaction (qRT-PCR). The cell viability and apoptotic rate were monitored via cell counting kit 8 (CCK8) assay and flow cytometry, respectively. The protein levels of p21, CyclinD1, B-cell lymphoma-2 (Bcl-2), cleaved-casp-3, E-cadherin, Ncadherin, Vimentin, and ATAD2 were detected by Western blot assay. Transwell assay was performed to estimate the abilities of migration and invasion. The interactions between miR-655-3p and MALAT1 or ATAD2 were predicted by starBase. Dual-luciferase reporter assay was constructed to verify these interactions. The mice model experiments were established to validate the effects of MALAT1 in vivo.Results: MALAT1and ATAD2 were significantly increased while the level of miR-655-3p was remarkably decreased in RB tissues and cells. MALAT1 knockdown inhibited cell proliferation, metastasis, and epithelial-mesenchymal transition (EMT) but promoted apoptosis via miR-655-3p in vitro, and blocked xenograft tumor growth in vivo. MALAT1 was validated to sponge miR-655-3p and ATAD2 was verified as a candidate of miR-655-3p. MiR-655-3p overexpression inhibited cell proliferation but promoted apoptosis by targeting ATAD2. MALAT1 silencing affected cell behaviors by regulating ATAD2. MALAT1 depletion down-regulated ATAD2 expression via miR-655-3p in RB cells.Conclusion: MALAT1 positively regulated ATAD2 to accelerate cell proliferation but retard apoptosis by sponging miR-655-3p in RB cells.

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“…Functionally, miR-655-3p was found to inhibit cell proliferation in human lip cells (14). In addition, miR-655-3p restrained the migration and invasion of non-small cell lung cancer cells by targeting PTTG1 (15). Here, Frizzled-4 (FZD4) is predicted as the target of miR-655-3p.…”

Section: Introductionmentioning

confidence: 99%

lncRNA SNHG5 promotes cell proliferation, migration and invasion in oral squamous cell carcinoma by sponging miR‑655‑3p/FZD4 axis

Huo

Shao

et al. 2020

Oncol Lett

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Recently, previous studies have shown that long non-coding RNA (lncRNA) can act as a tumor promoter or inhibitor in the pathogenesis of oral squamous cell carcinoma (OSCC). However, the regulatory mechanism of lncRNA SNHG5 is unknown in OSCC. Therefore, the functional mechanism of lncRNA SNHG5 in OSCC was initially revealed in this study. Here, RT-qPCR and western blot analysis were used to assess mRNA and protein expression. The functional mechanism of SNHG5 was investigated by MTT, Transwell and luciferase reporter assays. The results showed that SNHG5 expression was upregulated in OSCC and promoted the viability, migration and invasion of OSCC cells. In addition, SNHG5 is the sponge of miR-655-3p in OSCC. And miR-655-3p was found to play an inhibitory effect in OSCC by interacting with SNHG5. Moreover, miR-655-3p directly targets FZD4 and negatively regulates its expression in OSCC. Functionally, FZD4 promoted the progression of OSCC by interacting with the SNHG5/miR-655-3p axis. In conclusion, lncRNA SNHG5 promotes cell proliferation, migration and invasion in OSCC by regulating miR-655-3p/FZD4 axis.

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miR-655-3p inhibits cell migration and invasion by targeting pituitary tumor-transforming 1 in non-small cell lung cancer

Cited by 25 publications

References 13 publications

Common and distinct features of potentially predictive biomarkers in small cell lung carcinoma and large cell neuroendocrine carcinoma of the lung by systematic and integrated analysis

Common and distinct features of potentially predictive biomarkers in small cell lung carcinoma and large cell neuroendocrine carcinoma of the lung by systematic and integrated analysis

Long non-coding RNA MALAT1 regulated ATAD2 to facilitate retinoblastoma progression by sponging miR-655-3p

lncRNA SNHG5 promotes cell proliferation, migration and invasion in oral squamous cell carcinoma by sponging miR‑655‑3p/FZD4 axis

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