Clinicopathological Significance of Long Non-Coding RNA GHET1 in Human Cancers: A Meta-Analysis

Evaluating the expression of tumorigenic long noncoding RNAs in circulating exosomes isolated from non-small-cell lung cancer patients

Aim: To evaluate the correlation of long noncoding RNAs (lncRNAs) expression in circulating exosomes and the cancerous and noncancerous tissues in patients with non-small-cell lung carcinoma. Methods: The relative expression of the four lncRNAs including LUADT1, MALAT1, NEAT1 and MIAT between tumor tissue, adjacent noncancerous tissues and circulating exosomes were evaluated by quantitative reverse transcription PCR. Results & conclusion: The relative expression of the lncRNAs, including LUADT1, MALAT1 and NEAT1, was upregulated and MIAT was downregulated in tumor tissue compared with noncancerous tissue samples. The expression of lncRNAs in circulating exosomes was not significantly different from cancerous tissue. Our results indicate that the studied exosomal lncRNAs have a good potential to be further evaluated as prognostic/diagnostic biomarkers in patients with non-small-cell lung cancer.

Long non-coding RNA AC087388.1 as a novel biomarker in colorectal cancer

Background

Several investigations have reported diverse roles of long non-coding RNA (lncRNA) in biological processes, tumor development, and progression of colorectal cancer (CRC). In this study, we investigated the lncRNA AC087388.1 tumorigenic role in CRC cells.

Methods

The CRC tissues were collected at the Reza Radiotherapy and Oncology Center, Mashhad, Iran. The human SW-48 and HT-29 CRC cell lines were obtained from the national cell bank of Iran. The cells were cultured according to ATCC (the American Type Culture Collection) recommendations. Quantitative real-time PCR was applied to assess the RNA expression. ShRNA transfection was done to downregulate the target gene. MTT and apoptosis assays were conducted to evaluate cell proliferation and viability, respectively. Colony formation assay, wound healing assay, and invasion assay were applied to determine growth, motility, and invasion of the cells, respectively. ENCORI online tool was used as downstream enrichment analysis.

Results

Forty CRC patients were encompassed in this study. The results demonstrated that the lncRNA SLC16A1-AS1, AC087388.1, and ELFN1-AS1 were significantly overexpressed in the CRC tissues in comparison to their normal counterpart margins. All the lncRNAs have shown significant Area Under Curve (AUC) values in the patients. Downregulation of lncRNA AC087388.1 remarkably decreased the cell proliferation and viability of the CRC cells. In addition, the data demonstrated that the downregulation of lncRNA AC087388.1 significantly suppressed cell growth and colony formation capability in the cells. Also, downregulation of lncRNA AC087388.1 attenuated motility and invasion of CRC cells, and significantly decreased the expression of invasion genes. In-silico functional enrichment analysis indicated that the lncRNA AC087388.1 has contributed to crucial signaling pathways in tumorigenesis such as the p53 and Wnt signaling pathways, apoptosis, and cell cycle.

Conclusions

Altogether, we showed that lncRNA AC087388.1 has an oncogenic role in tumorigenesis of CRC, and it can be considered as a novel diagnostic and prognostic biomarker in CRC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09282-0.

Association between NEAT1 polymorphism and the risk of lung cancer: A protocol for systematic review and meta-analysis

BACKGROUND

Long noncoding RNAs play vital roles in development and progression of lung cancers. Nuclear paraspeckle assembly transcript 1 (NEAT1) polymorphisms were reported to be closely related to lung cancer susceptibility. Recently, numerous studies have been performed to detect the association between NEAT1 polymorphisms and lung cancer susceptibility. However, their results were inconsistent and controversial. So, we carried out a meta-analysis aiming to define the association exactly.

METHODS

Appropriate studies were retrieved from searching Web of Science, PubMed, Scopus, and Google scholar databases, updated January 31, 2021. The pooled odds ratios with 95% confidence intervals were calculated to estimate the strength of the association between NEAT1 polymorphisms and lung cancer risk. All of the data were analyzed with Stata 16.0.

RESULTS

The results of this meta-analysis will be submitted to a peer-reviewed journal for publication.

CONCLUSION

This meta-analysis will summarize the relationship between NEAT1 polymorphism and lung cancer.

Effects of long noncoding RNA on prognosis of oral squamous cell carcinoma: A protocol for systematic review and meta analysis

BACKGROUND

Long noncoding RNA (lncRNA) is reported to be upregulated in many tumors. Although the expression of lncRNA in oral squamous cell carcinoma has been assessed, the association between lncRNA expression and prognosis or clinicopathological feature still remains controversial. Therefore, we conducted a meta-analysis to verify whether lncRNA expression was related to prognosis or clinicopathological features in patients with oral squamous cell carcinoma.

METHODS

We searched Embase, PubMed, Web of Science, Cochrane library, Chinese National Knowledge Infrastructure, and Wanfang databases from inception to February 2021. The language included Chinese and English. The published literature on lncRNA expression and prognosis or clinicopathological characteristics of patients with oral squamous cell carcinoma was statistically analyzed. The combination of hazard ratios (HRs), odds ratios (OR), and 95% confidence intervals (95% CIs) were applied to evaluate the effects of lncRNA on the prognosis and clinicopathological features of oral squamous cell carcinoma.

RESULTS

This study could provide a comprehensive review of the available evidence of lncRNA on the prognosis and clinicopathological features of oral squamous cell carcinoma.

CONCLUSION

The conclusion of our study will provide the updated evidence to judge the lncRNA on the prognosis and clinicopathological features of oral squamous cell carcinoma.

Prognostic value of long noncoding RNA urothelial carcinoma-associated 1 in esophageal carcinoma: A protocol for meta-analysis, TCGA data and bioinformatics analysis

BACKGROUND

Currently, an increasing number of long noncoding RNAs (LncRNAs) have been reported to be abnormally expressed in human carcinomas and play a vital role in tumourigenesis. Some studies have been carried out to investigate the influence of the expression of LncRNA human urothelial carcinoma associated 1 (UCA1) on prognosis and clinical significance in patients with esophageal cancer, but the results are contradictory and uncertain. A meta-analysis and was conducted with controversial data to accurately assess the issue. We collected relevant TCGA data to further testify the result. In addition, bioinformatics analysis was conducted to investigate the mechanism and related pathways of LncRNA UCA1 in esophageal carcinoma.

METHODS

Wanfang, Chinese Biomedical Literature Database, Chinese National Knowledge Infrastructure, the Chongqing VIP Chinese Science and Technology Periodical Database, PubMed, Embase, and Web of Science were thoroughly searched for relevant information. Two reviewers independently performed data extraction and literature quality evaluation. Odd ratio and its 95% confidence intervals were applied to evaluate the relationship between LncRNA UCA1 and clinicopathological characteristics of esophageal carcinoma patients. Hazard ratios and its 95% confidence intervals were adopted to assess the prognostic effects of LncRNA UCA1 on overall survival and disease-free survival. Meta-analysis was performed with Stata 14.0 software. To further assess the function of LncRNA UCA1 in esophageal carcinoma, relevant data from The Cancer Genome Atlas (TCGA) database was collected. Three databases, miRWalk, TargetScan, and miRDB, were used for prediction of target genes. Genes present in these 3 databases were considered as predicted target genes of LncRNA UCA1. Venny 2.1 were used for intersection analysis. Subsequently, GO, KEGG, and PPI network analysis were conducted based on the overlapping target genes of LncRNA UCA1 to explore the possible molecular mechanism in esophageal carcinoma.

RESULTS

This study provides a high-quality medical evidence for the correlation between LncRNA UCA1 expression and overall survival, and between disease-free survival and clinicopathological features. Based on bioinformatics analysis, this study enhanced the understanding of the mechanism and related pathways of LncRNA UCA1 in esophageal carcinoma.

CONCLUSION

The study provides updated evidence to evaluate whether the expression of LncRNA UCA1 is in association with poor prognosis in patients with esophageal carcinoma.

ETHICS AND DISSEMINATION

The private information from individuals will not be published. This systematic review also should not damage participants' rights. Ethical approval is not available. The results may be published in a peer-reviewed journal or disseminated in relevant conferences.

OSF REGISTRATION NUMBER

DOI 10.17605/OSF.IO/8MCHW.

Long noncoding RNA GAS8-AS1: A novel biomarker in human diseases

Long non-coding RNAs (lncRNAs) represent a group of ncRNAs with more than 200 nucleotides. These RNAs can specifically regulate gene expression at both the transcriptional and the post-transcriptional levels, and increasing evidence indicates that they play vital roles in a variety of disease-related cellular processes. The lncRNA GAS8 antisense RNA 1 (GAS8-AS1, also known as C16orf3) is located in the second intron of GAS8 and has been reported to be both abnormally expressed in several diseases and closely correlated with many clinical characteristics. GAS8-AS1 has been shown to affect many biological functions, including cell proliferation, migration, invasiveness, and autophagy using several signaling pathways. In this review, we have summarized current studies on GAS8-AS1 roles in disease and discuss its potential clinical utility. GAS8-AS1 may be a promising biomarker for both diagnoses and prognoses, and a novel target for many disease therapies.