RESUMEN
Long non-coding RNAs (lncRNAs) have been identified as master gene regulators through various mechanisms such as transcription, translation, protein modification and RNA-protein complexes. LncRNA dysregulation is frequently associated with a variety of biological functions and human diseases including cancer. The p53 network is a key tumor-suppressive mechanism that transcriptionally activates target genes to suppress cellular proliferation in human malignancies. Recent research indicates that lncRNAs play an important role in the p53 signaling pathway. In this review, we summarize the current knowledge of lncRNAs in p53-relevant functions and provide an overview of how these altered lncRNAs contribute to tumor initiation and progression. We also discuss the association between lncRNA and up- or downstream genes of p53. These findings imply that lncRNAs can help identify cellular vulnerabilities that may prove to be promising potential biomarkers and therapeutic targets for cancer treatment.
Asunto(s)
Neoplasias , ARN Largo no Codificante , Humanos , ARN Largo no Codificante/genética , ARN Largo no Codificante/metabolismo , Proteína p53 Supresora de Tumor/genética , Proteína p53 Supresora de Tumor/metabolismo , Neoplasias/genética , Neoplasias/terapia , Transformación Celular Neoplásica/genética , Proliferación Celular/genética , Regulación Neoplásica de la Expresión GénicaRESUMEN
Lung cancer is the leading cause of cancer-related deaths worldwide. KRAS is the main oncogenic driver in lung cancer that can be activated by gene mutation or amplification, but whether long non-coding RNAs (lncRNAs) regulate its activation remains unknown. Through gain and loss of function approaches, we identified that lncRNA HIF1A-As2, a KRAS-induced lncRNA, is required for cell proliferation, epithelial-mesenchymal transition (EMT) and tumor propagation in non-small cell lung cancer (NSCLC) in vitro and in vivo. Integrative analysis of HIF1A-As2 transcriptomic profiling reveals that HIF1A-As2 modulates gene expression in trans, particularly regulating transcriptional factor genes including MYC. Mechanistically, HIF1A-As2 epigenetically activates MYC by recruiting DHX9 on MYC promoter, consequently stimulating the transcription of MYC and its target genes. In addition, KRAS promotes HIF1A-As2 expression via the induction of MYC, suggesting HIF1A-As2 and MYC form a double-regulatory loop to strengthen cell proliferation and tumor metastasis in lung cancer. Inhibition of HIF1A-As2 by LNA GapmeR antisense oligonucleotides (ASO) significantly improves sensitization to 10058-F4 (a MYC-specific inhibitor) and cisplatin treatment in PDX and KRASLSLG12D-driven lung tumors, respectively.
Asunto(s)
Carcinoma de Pulmón de Células no Pequeñas , Neoplasias Pulmonares , MicroARNs , ARN Largo no Codificante , Humanos , ARN Largo no Codificante/genética , ARN Largo no Codificante/metabolismo , Línea Celular Tumoral , Carcinoma de Pulmón de Células no Pequeñas/genética , Proteínas Proto-Oncogénicas p21(ras)/genética , Proteínas Proto-Oncogénicas p21(ras)/metabolismo , Retroalimentación , Neoplasias Pulmonares/genética , MicroARNs/genética , Proliferación Celular/genética , Regulación Neoplásica de la Expresión Génica , Subunidad alfa del Factor 1 Inducible por Hipoxia/genética , Subunidad alfa del Factor 1 Inducible por Hipoxia/metabolismoRESUMEN
The approximate entropy (ApEn), which is a new statistical method to measure the complexity of sequences, was introduced in this paper. First, the EOG artifact was removed from the EEG using the method of independent component analysis (ICA). Then ApEn was used to analyze the mental EEG signals to extract the features for pattern identification and task classification. The simulations showed that the classification accuracy is high and the proposed methods are effective.