Comprehensive Assessment of the Relationship Between MicroRNA-124 and the Prognostic Significance of Cancer

NEAT1 promotes retinoblastoma progression via modulating miR-124

The long noncoding RNA nuclear-enriched abundant transcript 1 (NEAT1) is reportedly involved in the initiation and progression of cancers of several types. However, the role, expression status, and the detailed mechanism of NEAT1 in retinoblastoma (RB) yet need to be unraveled. We explored the role and the mechanism of NEAT1 activity in RB. Our data show enhanced NEAT1 expression in RB-affected tissues compared with the corresponding control. Functional experiments reveal that a NEAT1 knockdown in RB cells significantly inhibits proliferation, cycle progression, and facilitates apoptosis and caspase-3 and -9 activities. Besides that, miR-124 was predicted to be a target of NEAT1 and its reduced expression, as well as the inverse correlation of NEAT1 with miR-124, was observed in RB-affected tissues. Further, luciferase and RNA immunoprecipitation (RIP) assays confirmed the interaction between NEAT1 and miR-124. Rescue experiments confirmed that the inhibition of miR-124 could reverse the effect of NEAT1 on RB cell proliferation, cycle arrest, apoptosis, and caspase-3 and -9 activities. Thus, NEAT1 promotes RB progression by sponging miR-124, providing a therapeutic target for RB.

SNP mutation-related genes in breast cancer for monitoring and prognosis of patients: A study based on the TCGA database

Advances in cancer biology have allowed early diagnosis and more comprehensive treatment of breast cancer (BC). However, it remains the most common cause of cancer death in women worldwide because of its strong invasiveness and metastasis. In‐depth study of the molecular pathogenesis of BC and of relevant prognostic markers would improve the quality of life and prognosis of patients. In this study, bioinformatics analysis of SNP‐related data from BC patients provided in the TCGA database revealed that six mutant genes (NCOR1, GATA3, CDH1, ATM, AKT1, and PTEN) were significantly associated with the corresponding expression levels of the proteins. The proteins were involved in multiple pathways related to the development of cancer, including the PI3K‐Akt signaling pathway, pertinent microRNAs, and the MAPK signaling pathway. In addition, overall survival and recurrence‐free survival analysis revealed the close associations of the expression of GATA3, NCOR1, CDH1, and ATM with survival of BC patients. Therefore, detecting these gene mutations and exploring their corresponding expression could be valuable in predicting the prognosis of patients. The results of the high‐throughput data mining provide important fundamental bioinformatics information and a relevant theoretical basis for further exploring the molecular pathogenesis of BC and assessing the prognosis of patients.