Analysis of Long Noncoding RNAs-Related Regulatory Mechanisms in Duchenne Muscular Dystrophy Using a Disease-Related lncRNA-mRNA Pathway Network

Xu, Bing; Zheng, Chunlei

doi:10.1155/2022/8548804

Cited by 3 publications

References 54 publications

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LncRNA 3222401L13Rik Is Up-regulated in Aging Astrocytes and Regulates Neuronal Support Function Through Interaction with Npas3

Schroeder,

Sakib,

Krüger

et al. 2024

Preprint

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Aging is linked to a decline in cognitive functions and significantly increases the risk of neurodegenerative diseases. While molecular changes in all central nervous system (CNS) cell types contribute to aging-related cognitive decline, the mechanisms driving disease development or offering protection remain poorly understood. Long non-coding RNAs (lncRNAs) have emerged as key regulators of cellular functions and gene expression, yet their roles in aging, particularly within glial cells, are not well characterized. In this study, we investigated lncRNA expression profiles in non-neuronal cells from aged mice. We identified 3222401L13Rik, a previously unstudied lncRNA enriched in glial cells, as being specifically upregulated in astrocytes during aging. Knockdown of 3222401L13Rik in primary astrocytes revealed its critical role in regulating genes essential for neuronal support and synapse organization. This function was also conserved in human iPSC-derived astrocytes. Additionally, we found that 3222401L13Rik mediates its cellular effects through interaction with the transcription factor Neuronal PAS Domain Protein 3 (Npas3), and that overexpression of Npas3 effectively rescued the functional deficits observed in astrocytes lacking 3222401L13Rik. Our findings suggest that upregulation of 3222401L13Rik in aging astrocytes acts as a compensatory mechanism to enhance neuronal and synaptic support, potentially delaying the onset of molecular and structural changes in both astrocytes and neurons. Strategies to boost 3222401L13Rik expression earlier in life may help mitigate age-associated loss of neuronal plasticity.

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LncRNA 3222401L13Rik Is Up-regulated in Aging Astrocytes and Regulates Neuronal Support Function Through Interaction with Npas3

Schroeder,

Sakib,

Krüger

et al. 2024

Preprint

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Confirmation Key Genes Associated with TNM Staging Classified as T3 and T4 in Lung Squamous Cell Carcinoma with Bioinformatics Analysis

Líu

et al. 2023

Preprint

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Background: Lung cancer is a high occurrence rate and mortality rate cancer. Non-small cell lung cancer (NSCLC) is confirmed in 80–85% of lung cancer cases. Lung squamous cell carcinoma (LUSC) is frequently diagnosed at the advanced stage with poor prognoses. The size of tumor was an important indicator of the prognosis. Methods: TCGA database and GEO database were performed to download transcriptome data and clinical information of LUSC. Firstly, we identified differentially expressed genes (DEGs) between TNM stage as T3-T4 and T1-T2 of LUSC patients in TCGA datasets. Furthermore, PPI was applied to identify proteins that interact actively during the process of tumorigenesis. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) were consulted to explore the enriched biological processes and pathways of the DEGs. After that, LASSO Cox regression algorithms were employed to confirm tumor size-related signature. In addition, survival analysis (including nomogram, Kaplan–Meier method, ROC curve, GSVA, and correlation matrix) was performed to achieve a accurate prognostic model. Finally, the GEO database was applied to check the tumor size-related prognostic features. Results: 1267 genes were identified as DEGs. And we can conclude that DEGs primarily concentrated in membranes, defence response to bacterium , transmembrane signaling receptor activity and olfactory transduction by the results from GO functions and KEGG pathways analysis. Five genes about tumour size-related risk signature including PCGF2, ULK3, MCRIP1,UCKL1, and CCDC18-AS1 were selected to forecast overall survival of LUSC patients. The credibility of prediction model was verified in GSE68825 and GSE68793. The LUSC patients were divided into low-risk score and high-risk score groups according to average value of risk score. Scatter plots show that patients in high-risk score group had shorter survival time. Conclusion: Our study identified five biomarkers that were related to tumor size in the LUSC. The prognostic model can efficiently predict the survival status of patients. In addition, the several biomarkers are conductive to further investigate therapies and forecast prognosis of LUSC.

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New Long Non-Coding Rnas in Lung Cancer Oncogenesis

Podlesnaya,

Kovaleva,

Petrenko

et al. 2023

Mol Med Rus

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This review is devoted to summarizing the available data on the expression of long non-coding RNAs (lncRNAs) in lung cancer cells and tissues, their role in tumorigenesis, association with clinical and morphological characteristics and disease prognosis. The purpose of this study is to search and describe new lncRNAs involved in the mechanisms of lung cancer progression. Material and methods. An analysis of scientific literature was carried out using the PubMed/Medline, RSCI/elibrary databases over the past 5 years. Results. Long non-coding RNAs are a promising tool for the diagnosis and treatment of cancer, including lung cancer. To date, a large number of lncRNAs have been described that are associated with lung cancer and/or involved in various mechanisms of disease progression. However, data on the role of each of them is fragmentary and further comprehensive studies of the functions of the identified lncRNAs in the pathogenesis of lung cancer are required.

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Analysis of Long Noncoding RNAs-Related Regulatory Mechanisms in Duchenne Muscular Dystrophy Using a Disease-Related lncRNA-mRNA Pathway Network

Cited by 3 publications

References 54 publications

LncRNA 3222401L13Rik Is Up-regulated in Aging Astrocytes and Regulates Neuronal Support Function Through Interaction with Npas3

LncRNA 3222401L13Rik Is Up-regulated in Aging Astrocytes and Regulates Neuronal Support Function Through Interaction with Npas3

Confirmation Key Genes Associated with TNM Staging Classified as T3 and T4 in Lung Squamous Cell Carcinoma with Bioinformatics Analysis

New Long Non-Coding Rnas in Lung Cancer Oncogenesis

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