MiR-592 activates the mTOR kinase, ERK1/ERK2 kinase signaling and imparts neuronal differentiation signature characteristic of Group 4 medulloblastoma

Paul, Raikamal; Bapat, Purna; Deogharkar, Akash; Kazi, Sadaf; Singh, Satish K.; Gupta, Tejpal; Jalali, Rakesh; Epari, Sridhar; Moiyadi, Aliasgar; Shetty, Prakash; Shirsat, Neelam

doi:10.1093/hmg/ddab264

Cited by 3 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…MiR-592 suppresses the malignant phenotypes of thyroid cancer through the regulation of lncRNA NEAT1 and downregulation of NOVA1 [34]. A miR-592-mediated activation of mTOR (mammalian target of rapamycin), ERK1/ERK2 signaling, and neuronal differentiation impart group 4 medulloblastoma characteristics [35]. It has been found that lncRNA MEF2C-AS1 inhibits cervical cancer by targeting RSPO1 by suppressing miR-592 [36].…”

Section: Discussionmentioning

confidence: 99%

Identification of m7G Methylation-Related miRNA Signature Associated with Survival and Immune Microenvironment Regulation in Uterine Corpus Endometrial Carcinoma

Chen

Sun

Hou

et al. 2022

BioMed Research International

View full text Add to dashboard Cite

Background. N7-methylguanosine (m7G) has been implicated in the development of cancer. The role of m7G-related miRNAs in the survival prediction of UCEC patients has not been investigated. Current research was the first to construct an m7G-related miRNA model to accurately predict the survival of patients with uterine corpus endometrial carcinoma (UCEC) and to explore immune cell infiltration and immune activity in the tumor microenvironment. Methods. RNA-seq data and clinical information of UCEC patients were derived from The Cancer Genome Atlas (TCGA) database. Using the TargetScan online database, we predicted miRNAs linked to the m7G-related genes and identified miRNAs which were significantly associated with the survival in UCEC patients and constructed a risk scoring model. The TCGA-UCEC cases were scored according to the risk model, and the high- and low-risk groups were divided by the median risk value. Gene enrichment analysis and immune cell infiltration and immune function analysis were performed using “clusterProfiler” and “GSVA” packages in R. Results. The survival prediction model consisted of 9 miRNAs, namely, hsa-miR-1301, hsa-miR-940, hsa-miR-592, hsa-miR-3170, hsa-miR-876, hsa-miR-215, hsa-miR-934, hsa-miR-3920, and hsa-miR-216b. Survival of UCEC patients in the high-risk group was worse than that in the low-risk group ( p < 0.001 ). The receiver operating characteristic (ROC) curve showed that the model had good predictive performance, and the area under the curve was 0.800, 0.690, and 0.705 for 1-, 3-, and 5-year survival predictions, respectively. There were differences in the degree of immune cell infiltration and immune activity between the low-risk and high-risk groups. The expression levels of the identified differentially expressed genes correlated with the susceptibility to multiple anticancer drugs. Conclusions. The survival prediction model constructed based on 9 m7G-related miRNAs had good predictive performance.

show abstract

Section: Discussionmentioning

confidence: 99%

Identification of m7G Methylation-Related miRNA Signature Associated with Survival and Immune Microenvironment Regulation in Uterine Corpus Endometrial Carcinoma

Chen

Sun

Hou

et al. 2022

BioMed Research International

View full text Add to dashboard Cite

show abstract

“…Small RNA RNU6B (U6) (RiboBio, Guangzhou, China) was used as a control for the expression of miRNA ( Li et al, 2022a ). Primer sequences are summarized in previous studies, including miR-139-5p ( Li et al, 2022b ), hsa-miR-326 ( Wei et al, 2022 ), miR-10b-5p ( Niu et al, 2021 ), miR-500a-3p ( Long et al, 2022 ), and miR-592 ( Paul et al, 2021 ).…”

Section: Methodsmentioning

confidence: 99%

Construction of a Necroptosis-Related miRNA Signature for Predicting the Prognosis of Patients With Hepatocellular Carcinoma

et al. 2022

View full text Add to dashboard Cite

Background: Many miRNAs have been demonstrated to be associated with the prognosis of hepatocellular carcinoma (HCC). However, how to combine necroptosis-related miRNAs to achieve the best predictive effect in estimating HCC patient survival has not been explored.Methods: The mRNA and miRNA expression profile were downloaded from a public database (TCGA-LIHC cohort). Necroptosis-related genes were obtained from previous references, and necroptosis-related miRNAs were identified using Pearson analysis. Subsequently, differential expression miRNAs (DEms) were identified in HCC and paracancer normal samples based on necroptosis-related miRNA expression. The whole set with HCC was randomized into a training set and testing set (1:1). LASSO-Cox regression analysis was used to construct an miRNA signature. Multiple statistical methods were used to validate the clinical benefit of signature in HCC patients, including receiver operator characteristic (ROC) curves, Kaplan–Meier survival analyses, and decision curve analysis (DCA). The downstream target genes of miRNAs were obtained from different online tools, and the potential pathways involved in miRNAs were explored. Finally, we conducted RT-qPCR in SK-HEP-1, THLE-3, and HUH-7 cell lines for miRNAs involved in the signature.Results: The results showed that a total of eight specific necroptosis-related miRNAs were screened between HCC and adjacent tissues in the training set. Subsequently, based on the aforementioned miRNAs, 5-miRNA signature (miR-139-5p, hsa-miR-326, miR-10b-5p, miR-500a-3p, and miR-592) was generated by LASSO-Cox regression analysis. Multivariate Cox regression analysis showed that the risk scores were independent prognostic indicators in each set. The area under curves (AUCs) of 1 year, 3 years, 5 years, and 7 years were high in each set (AUC >0.7). DCA analysis also revealed that the risk score had a potential benefit than other clinical characteristics. Meanwhile, survival analysis showed that the high-risk group showed low survival probabilities. Moreover, the results of enrichment analysis showed that specific miRNAs were mainly enriched in the cAMP signaling pathway and TNF signaling pathway. Finally, the results of RT-qPCR were consistent with the prediction results in public databases.Conclusion: Our study establishes a robust tool based on 5-necroptosis-related miRNAs for the prognostic management of HCC patients.

show abstract

“…10 In recent years, studies on breast cancer, gastric cancer, non-small cell lung cancer, lung adenocarcinoma, colorectal cancer, liver cancer, medulloblastoma, and glioma have shown that MicroRNA-592 (miR-592) may be involved in tumorigenesis and play an important regulator of gene expression, which may be a new therapeutic target for tumors or a prognostic and monitoring indicator. 11–19…”

Section: Introductionmentioning

confidence: 99%

MicroRNA-592 Inhibits the Growth of Ovarian Cancer Cells by Targeting ERBB3

Jin

Zhang²,

Yang

et al. 2023

Technol Cancer Res Treat

View full text Add to dashboard Cite

Objectives: Ovarian cancer is the most lethal gynecologic malignancy, and targeted therapy for different pathological types and molecular phenotypes is urgent to be studied. Studies have shown that MicroRNA-592 (miR-592) plays an important negative regulatory role in the occurrence of gastrointestinal malignancies, breast cancer, non-small cell lung cancer, and glioma, but the expression of miR-592 in ovarian cancer and the mechanism of action are still unclear. Methods: The expressions of miR-592 were examined by RT-PCR and Western Blot. Cell viability and migratory capacity were detected by CCK-8 and transwell assay. TargetScan ( http://www.targetscan.org ) was analyzed to predict potential targets of miR-592. Then Dual-luciferase reporter gene assay was performed to verify the targeting relationship between miR-592 and ERBB3. A mouse xenograft model was applied to confirm the effect of miR-592. Results: In our study, we found that the expression of miR-592 is reduced in epithelial ovarian cancer tissues. The exogenous expression of miR-592 inhibits the proliferation, migration, and invasion in epithelial ovarian cancer tumor cells. Furthermore, the exogenous expression of miR-592 inhibits tumor growth in the nude mouse xenograft model. Therefore, miR-592 may play a role of tumor suppressor miRNA in the occurrence and development of ovarian cancer. Further experiments demonstrated that tumor-related ERBB3 is a target gene mediated by miRNA-592. The dual-luciferase reporter system was used to identify miRNA-592 target genes; qPCR and Western Blot were used to detect the expression of ERBB3. Mechanical experiments confirmed that miRNA-592 negatively regulated ERBB3.Conclusion: Together, these findings identify a heretofore unrecognized link between miR-592 and ERBB3 and suggest that targeting on miR-592 warrants attention as a novel and potential therapeutic strategy for ovarian cancer.

show abstract

MiR-592 activates the mTOR kinase, ERK1/ERK2 kinase signaling and imparts neuronal differentiation signature characteristic of Group 4 medulloblastoma

Cited by 3 publications

References 0 publications

Identification of m7G Methylation-Related miRNA Signature Associated with Survival and Immune Microenvironment Regulation in Uterine Corpus Endometrial Carcinoma

Identification of m7G Methylation-Related miRNA Signature Associated with Survival and Immune Microenvironment Regulation in Uterine Corpus Endometrial Carcinoma

Construction of a Necroptosis-Related miRNA Signature for Predicting the Prognosis of Patients With Hepatocellular Carcinoma

MicroRNA-592 Inhibits the Growth of Ovarian Cancer Cells by Targeting ERBB3

Contact Info

Product

Resources

About