RESUMEN
Lung cancer is one of the most invasive cancers affecting over a million of the population. Non-small cell lung cancer (NSCLC) constitutes up to 85% of all lung cancer cases, and therefore, it is essential to identify predictive biomarkers of NSCLC for therapeutic purposes. Here we use a network theoretical approach to investigate the complex behavior of the NSCLC gene-regulatory interactions. We have used eight NSCLC microarray datasets GSE19188, GSE118370, GSE10072, GSE101929, GSE7670, GSE33532, GSE31547, and GSE31210 and meta-analyzed them to find differentially expressed genes (DEGs) and further constructed a protein-protein interaction (PPI) network. We analyzed its topological properties and identified significant modules of the PPI network using cytoscape network analyzer and MCODE plug-in. From the PPI network, top ten genes of each of the six topological properties like closeness centrality, maximal clique centrality (MCC), Maximum Neighborhood Component (MNC), radiality, EPC (Edge Percolated Component) and bottleneck were considered for key regulator identification. We further compared them with top ten hub genes (those with the highest degrees) to find key regulator (KR) genes. We found that two genes, CDK1 and HSP90AA1, were common in the analysis suggesting a significant regulatory role of CDK1 and HSP90AA1 in non-small cell lung cancer. Our study using a network theoretical approach, as a summary, suggests CDK1 and HSP90AA1 as key regulator genes in complex NSCLC network.
RESUMEN
Long non coding RNAs (lncRNAs) are non-protein or low-protein coding transcripts that contain more than 200 nucleotides. They representing a large share of the cell's transcriptional output, demonstrate functional attributes viz. tissue-specific expression, determination of cell fate, controlled expression, RNA processing and editing, dosage compensation, genomic imprinting, conserved evolutionary traits etc. These long non coding variants are well associated with pathogenicity of various diseases including the neurological disorders like Alzheimer's disease, schizophrenia, Huntington's disease, Parkinson's disease etc. Neurological disorders are widespread and there knowing the underlying mechanisms become crucial. The lncRNAs take part in the pathogenesis by a plethora of mechanisms like decoy, scaffold, mi-RNA sequestrator, histone modifiers and in transcriptional interference. Detailed knowledge of the role of lncRNAs can help to use them further as novel biomarkers for therapeutic aspects. Here, in this review we discuss regulation and functional roles of lncRNAs in eight neurological diseases and psychiatric disorders, and the mechanisms by which they act. With these, we try to establish their roles as potential markers and viable diagnostic tools in these disorders.
RESUMEN
Long non-coding RNAs (lncRNAs) are functionally versatile molecules that regulate gene expression at all levels of biological organization. RNA modulation, at the moment, has emerged as a powerful therapeutic technique to treat human diseases. Lately, lncRNAs have been acknowledged as key players in human metabolism and, indeed, implicated in the etiology of many common diseases other than cancers, where they can perhaps serve as reliable markers to determine disease status or assess outcomes of an intervention. Here, in this review, we cite examples of such lncRNAs, discuss their mechanistic role in human diseases and their genetic association, quote potential biomarkers found in human blood, summarize the methods for therapeutic targeting lncRNAs and examine the progress of lncRNA based drugs in clinical trials. Thus, we propose that lncRNAs serve as both a biomarker and an effective therapeutic target with promising clinical utility to manage human metabolic diseases.
