MiR-139-5p Inhibits the Development of Gastric Cancer through Targeting TPD52

Retracted: MiR-139-5p Inhibits the Development of Gastric Cancer through Targeting TPD52

[This retracts the article DOI: 10.1155/2022/4033373.].

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

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.

Role of NRF2 in Ovarian Cancer

Among gynaecologic malignancies, ovarian cancer is one of the most dangerous, with a high fatality rate and relapse due to the occurrence of chemoresistance. Many researchers demonstrated that oxidative stress is involved in tumour occurrence, growth and development. Nuclear factor erythroid 2-related factor 2 (NRF2) is an important transcription factor, playing an important role in protecting against oxidative damage. Increased levels of Reactive Oxygen Species (ROS) activate NRF2 signalling, inducing the expression of antioxidant enzymes, such as haem oxygenase (HO-1), catalase (CAT), glutathione peroxidase (GPx) and superoxide dismutase (SOD), that protect cells against oxidative stress. However, NRF2 activation in cancer cells is responsible for the development of chemoresistance, inactivating drug-mediated oxidative stress that normally leads to cancer cells’ death. In this review, we report evidence from the literature describing the effect of NRF2 on ovarian cancer, with a focus on its function in drug resistance, NRF2 natural and synthetic modulators and its protective function in normal ovarian preservation.