noncoding rnas
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2022 ◽  
Vol 23 (2) ◽  
pp. 930
Ba Da Yun ◽  
Ye Ji Choi ◽  
Seung Wan Son ◽  
Gabriel Adelman Cipolla ◽  
Fernanda Costa Brandão Berti ◽  

Circular RNAs (circRNAs) and long noncoding RNAs (lncRNAs) are differentially expressed in gastrointestinal cancers. These noncoding RNAs (ncRNAs) regulate a variety of cellular activities by physically interacting with microRNAs and proteins and altering their activity. It has also been suggested that exosomes encapsulate circRNAs and lncRNAs in cancer cells. Exosomes are then discharged into the extracellular environment, where they are taken up by other cells. As a result, exosomal ncRNA cargo is critical for cell–cell communication within the cancer microenvironment. Exosomal ncRNAs can regulate a range of events, such as angiogenesis, metastasis, immune evasion, drug resistance, and epithelial-to-mesenchymal transition. To set the groundwork for developing novel therapeutic strategies against gastrointestinal malignancies, a thorough understanding of circRNAs and lncRNAs is required. In this review, we discuss the function and intrinsic features of oncogenic circRNAs and lncRNAs that are enriched within exosomes.

2022 ◽  
Vol 2022 ◽  
pp. 1-11
Zhiqun Bai ◽  
Xuemei Wang ◽  
Zhen Zhang

Emerging evidence has indicated that aberrantly expressed long noncoding RNAs (lncRNAs) play a vital role in various biological processes associated with tumorigenesis. Leukemia inhibitory factor receptor antisense RNA1 (LIFR-AS1) is a recently identified lncRNA transcribed in an antisense manner from the LIFR gene located on human chromosome 5p13.1. LIFR-AS1 regulates tumor proliferation, migration, invasion, apoptosis, and drug resistance through different mechanisms. Its expression level is related to the clinicopathological characteristics of tumors and plays a key role in tumor occurrence and development. In this review, we summarize the role of LIFR-AS1 in the development and progression of different cancers and highlight the potential for LIFR-AS1 to serve as a biomarker and therapeutic target for a variety of human cancers.

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Xiaoting Zhang ◽  
Yue Su ◽  
Xian Fu ◽  
Jing Xiao ◽  
Guicheng Qin ◽  

Lung squamous cell carcinoma (LUSC) is the most common type of lung cancer accounting for 40% to 51%. Long noncoding RNAs (lncRNAs) have been reported to play a significant role in the invasion, migration, and proliferation of lung cancer tissue cells. However, systematic identification of lncRNA signatures and evaluation of the prognostic value for LUSC are still an urgent problem. In this work, LUSC RNA-seq data were collected from TCGA database, and the limma R package was used to screen differentially expressed lncRNAs (DElncRNAs). In total, 216 DElncRNAs were identified between the LUSC and normal samples. lncRNAs associated with prognosis were calculated using univariate Cox regression analysis. The overall survival (OS) prognostic model containing 10 lncRNAs and the disease-free survival (DFS) prognostic model consisting of 11 lncRNAs were constructed using a machine learning-based algorithm, systematic LASSO-Cox regression analysis. We found that the survival rate of samples in the high-risk group was lower than that in the low-risk group. Results of ROC curves showed that both the OS and DFS risk score had better prognostic effects than the clinical characteristics, including age, stage, gender, and TNM. Two lncRNAs (LINC00519 and FAM83A-AS1) that were commonly identified as prognostic factors in both models could be further investigated for their clinical significance and therapeutic value. In conclusion, we constructed lncRNA prognostic models with considerable prognostic effect for both OS and DFS of LUSC.

2022 ◽  
Vol 8 (1) ◽  
pp. 9
Jin Zhang ◽  
Abdallah M. Eteleeb ◽  
Emily B. Rozycki ◽  
Matthew J. Inkman ◽  
Amy Ly ◽  

Existing small noncoding RNA analysis tools are optimized for processing short sequencing reads (17–35 nucleotides) to monitor microRNA expression. However, these strategies under-represent many biologically relevant classes of small noncoding RNAs in the 36–200 nucleotides length range (tRNAs, snoRNAs, etc.). To address this, we developed DANSR, a tool for the detection of annotated and novel small RNAs using sequencing reads with variable lengths (ranging from 17–200 nt). While DANSR is broadly applicable to any small RNA dataset, we applied it to a cohort of matched normal, primary, and distant metastatic colorectal cancer specimens to demonstrate its ability to quantify annotated small RNAs, discover novel genes, and calculate differential expression. DANSR is available as an open source tool.

2022 ◽  
Vol 18 (1) ◽  
pp. e1009722
Jennifer Yihong Tan ◽  
Ana Claudia Marques

Pervasive enhancer transcription is at the origin of more than half of all long noncoding RNAs in humans. Transcription of enhancer-associated long noncoding RNAs (elncRNA) contribute to their cognate enhancer activity and gene expression regulation in cis. Recently, splicing of elncRNAs was shown to be associated with elevated enhancer activity. However, whether splicing of elncRNA transcripts is a mere consequence of accessibility at highly active enhancers or if elncRNA splicing directly impacts enhancer function, remains unanswered. We analysed genetically driven changes in elncRNA splicing, in humans, to address this outstanding question. We showed that splicing related motifs within multi-exonic elncRNAs evolved under selective constraints during human evolution, suggesting the processing of these transcripts is unlikely to have resulted from transcription across spurious splice sites. Using a genome-wide and unbiased approach, we used nucleotide variants as independent genetic factors to directly assess the causal relationship that underpin elncRNA splicing and their cognate enhancer activity. We found that the splicing of most elncRNAs is associated with changes in chromatin signatures at cognate enhancers and target mRNA expression. We provide evidence that efficient and conserved processing of enhancer-associated elncRNAs contributes to enhancer activity.

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