LAMTOR5 expression level is a biomarker for colorectal cancer and lncRNA LAMTOR5-AS1 predicting miRNA sponging effect

Inefficient splicing of long non-coding RNAs is associated with higher transcript complexity in human and mouse

Recent reports show that long non-coding RNAs (lncRNAs) have inefficient splicing and fewer alternative splice variants than mRNAs. Here, we have explored the efficiency of lncRNAs and mRNAs in producing various splice variants, given the number of exons in humans and mice. Intriguingly, lncRNAs produce more splice variants per exon, referred to as Transcript Complexity, than mRNAs. Most lncRNA splice variants are the product of the alternative last exon and exon skipping. LncRNAs and mRNAs with higher transcript complexity have shorter intron lengths. Longer exon length and GC/AG at 5'/3' splice sites are associated with higher transcript complexity in lncRNAs. Lastly, our results indicate that inefficient splicing of lncRNAs may facilitate multiple introns splicing and, thus, more spliced products per exon.

Molecular hallmarks of long non-coding RNAs in aging and its significant effect on aging-associated diseases

Aging is linked to the deterioration of many physical and cognitive abilities and is the leading risk factor for Alzheimer's disease. The growing aging population is a significant healthcare problem globally that researchers must investigate to better understand the underlying aging processes. Advances in microarrays and sequencing techniques have resulted in deeper analyses of diverse essential genomes (e.g., mouse, human, and rat) and their corresponding cell types, their organ-specific transcriptomes, and the tissue involved in aging. Traditional gene controllers such as DNA- and RNA-binding proteins significantly influence such programs, causing the need to sort out long non-coding RNAs, a new class of powerful gene regulatory elements. However, their functional significance in the aging process and senescence has yet to be investigated and identified. Several recent researchers have associated the initiation and development of senescence and aging in mammals with several well-reported and novel long non-coding RNAs. In this review article, we identified and analyzed the evolving functions of long non-coding RNAs in cellular processes, including cellular senescence, aging, and age-related pathogenesis, which are the major hallmarks of long non-coding RNAs in aging.

LncRNA LAMTOR5-AS1 sponges miR-210-3p and regulates cervical cancer progression

AIM

Cervical cancer has attracted increasing attention in recent years, and the incidence has shown a trend of younger age. Therefore, it is an effective method to regulate the progression of cervical cancer through new prognostic biomarkers. The purpose of this study was to evaluate the potential of lncRNA LAMTOR5-AS1 (LAMTOR5-AS1) as a prognostic biomarker and reveal its regulatory role in cervical cancer.

METHODS

A total of 120 patients with cervical cancer were selected as research subjects to verify the prognostic effect of LAMTOR5-AS1 in a series of experiments. The expression of LAMTOR5-AS1 in cervical cancer tissues and cells was determined by polymerase chain reaction assay. The proliferation, migration, and invasion ability of cervical cancer cells were evaluated by Cell Counting Kit-8 (CCK-8) and Transwell assay. Luciferase reporter gene detection was used to determine the mechanism of LAMTOR5-AS1 targeting miR-210-3p, and to reflect the prognostic value of LAMTOR5-AS1 according to statistical methods.

RESULTS

LAMTOR5-AS1 decreased in cervical cancer tissues, while miR-210-3p expression increased. In the study of cervical cancer cells, it was found that the LAMTOR5-AS1 sponge miR-210-3p was associated with the malignant progression of cervical cancer. Overexpression of LAMTOR5-AS1 could effectively inhibit the development of cervical cancer cells and might be chosen as a prognostic biomarker of cervical cancer.

CONCLUSIONS

LAMTOR5-AS1 sponges miR-210-3p and modulates the progression of cervical cancer, which predict the prognosis of cervical cancer patients.

miRNAs in Cancer (Review of Literature)

MicroRNAs (miRNAs) are short, noncoding, single-stranded RNA molecules that regulate gene expression at the post-transcriptional level by binding to mRNAs. miRNAs affect the course of processes of fundamental importance for the proper functioning of the organism. These processes include cell division, proliferation, differentiation, cell apoptosis and the formation of blood vessels. Altered expression of individual miRNAs has been shown in numerous cancers, which may indicate the oncogenic or suppressor potential of the molecules in question. This paper discusses the current knowledge about the possibility of using miRNA as a diagnostic marker and a potential target in modern anticancer therapies.

Prognostic Value of Macrophage-Associated Long Non-Coding RNA Expression for Hepatocellular Carcinoma

Background

There is ample evidence that macrophages play a crucial role in the biological processes of hepatocellular carcinoma (HCC). This study was designed to establish a novel macrophage-associated prognostic model for HCC.

Methods

Long non-coding RNA (lncRNA) microarrays and clinical data in The Cancer Genome Atlas (TCGA) database were analysed using a univariate Cox proportional regression model to select macrophage-associated prognostic lncRNAs. Multivariate Cox proportional regression models and survival analysis were used to establish a prognosis index (PI) model. Furthermore, to better understand the biological functions of differentially expressed macrophage-associated lncRNAs (MALs) in HCC, enrichment analysis was performed. Finally, the correlation between MALs and clinical features was further analysed in HCC.

Results

We identified eight MALs with significant prognostic values for HCC. Next, a PI model for HCC was developed, and patients were classified into the high-risk or low-risk group based on risk scores. The overall survival (OS) of high-risk patients was significantly shorter than that of low-risk patients (P < 0.001). Univariate and multivariate factors indicate that risk scores can be used as independent prognostic factors for patients with HCC. Multiple receiver operating characteristic (ROC) plots show that the area under the ROC curve (AUC) of the risk score is higher than that of other clinical features. The C-index of our nomogram was 0.768.

Conclusion

The PI model has a prognostic efficacy superior to that of other clinical features.