Prognostic value and therapeutic potential of the long noncoding RNA TP73-AS1 in cancers: A systematic review and meta-analysis

Non-coding RNAs and gastrointestinal cancers prognosis: an umbrella review of systematic reviews and meta-analyses of observational studies

Aim

Provide an overview and a systematic evaluation of the evidence quality on the association between non-coding RNAs (ncRNAs) and prognosis value for gastrointestinal cancers (GICs).

Methods

We searched the literature from three electronic databases: Pubmed, Embase, and Web of science, then carefully screened and extracted the primary information and results from the included articles. We use A measurable systematic review and meta-analysis evaluation tool (AMSTAR2) to evaluate the quality of methodology and then use the Grading of Recommendations Assessment 2, Development and Evaluation guideline (GRADE) make sure the reliability of the meta-analysis.

Results

Overall, 182 meta-analyses from 58 studies were included in this study. Most of these studies are of low or very low quality. Using the scoring tool, we found that only two meta-analyses were rated as high reliability, and 17 meta-analyses were rated as medium reliability.

Conclusions

Although ncRNA has good prognostic value in some studies, only a tiny amount of evidence is highly credible at present. More research is needed in the future.

PROSPERO registration number

CRD42022382296.

Diagnostic value of circulating lncRNAs for gastric cancer: A systematic review and meta-analysis

Objective

With the prevalence of next-generation sequencing (NGS) technology, a large number of long non-coding RNAs (lncRNAs) have attracted tremendous attention and have been the topic of extensive research on gastric cancer (GC). It was revealed that lncRNAs not only participate in the transduction of various signaling pathways, thus influencing GC genesis and development, but also have the potential for GC diagnosis. Therefore, we aimed to conduct a meta-analysis of previous studies on GC.

Materials and methods

An electronic search was made before August 2021 on databases including PubMed, Embase, and Web of Science. Relevant articles that compare lncRNA expression in GC patients and healthy controls were summarized. We conducted a meta-analysis with the objective of evaluating the ability of lncRNAs in diagnosing GC.

Results

A total of 40 original research studies including 6,772 participants were discussed in this meta-analysis. The overall sensitivity, specificity, and the area under the curve (AUC) were 0.78 (95% CI: 0.75-0.81), 0.79 (95% CI: 0.74-0.83), and 0.85 (95% CI: 0.81-0.87), respectively. The value of pooled diagnostic odds ratios (DORs) was 13.00 (95% CI: 10.00-17.00).

Conclusions

This meta-analysis revealed that serum or plasma lncRNAs have high sensitivity and specificity, which makes lncRNAs clinically feasible in diagnosing GC. The results from this meta-analysis demonstrated that peripheral blood lncRNAs may become novel noninvasive biomarkers in the foreseeable future. At the same time, it should be noted that a greater number of blood samples and more evidence from rigorous multicenter clinical studies are necessary to justify their applicability as cancer biomarkers.

PCAT6 may be a new prognostic biomarker in various cancers: a meta-analysis and bioinformatics analysis

Background

LncRNA prostate cancer-associated transcript 6 (PCAT6) has been reported to be dysregulated in several cancers and is associated with tumor progression. Here, we have performed a meta-analysis to assess the general prognostic role of PCAT6 in malignancies.

Methods

Four public databases (Embase, Pubmed, Web of Science, Cochrane Library) were used to identify eligible studies, then data was extracted and associations between prognostic indicators and clinical characteristics were combined to estimate hazard ratio (HR) or odds ratio (OR) with a 95% confidence interval (CI). Publication bias was measured using the Begg's test, and the stability of the combined results was measured using sensitivity analysis. Subsequently, results were validated using Gene Expression Profiling Interactive Analysis (GEPIA) and the National Genomics Data Center (NGDC).

Results

Ten studies were considered eligible for inclusion. In total, 937 patients and eight types of cancer were included. Our results revealed that overexpression of PCAT6 was significantly associated with a shorter OS (HR = 1.82; 95% CI, [1.40, 2.38]; P < 0.0001) and progression-free survival (PFS) (HR = 1.66; 95% CI, [1.22, 2.25]; P < 0.0001) in cancer patients, and that PCAT6 overexpression was significantly associated with individual tumor clinicopathological parameters, including TNM stage (OR = 0.29; 95% CI, [0.09, 0.94]; P = 0.04), gender (OR = 1.84; 95% CI, [1.31, 2.59]; P = 0.0005), and whether the tumor was metastatic (OR = 5.02; 95% CI, [1.36, 18.57]; P = 0.02). However, PCAT6 overexpression was not correlated with patient age and tumor differentiation. PCAT6 expression was significantly up-regulated in four types of cancer, which was validated using the GEPIA cohort. Combining OS and disease-free survival (DFS) of these four types of cancer revealed a shorter OS and DFS in patients with PCAT6 overexpression. PCAT6 expression in various types of cancer was also validated in NGDC. A total of eight cancers were analyzed and PCAT6 was highly expressed in all eight cancers. Further functional predictions suggest that PCAT6 is correlated with tumor prognosis, and that PCAT6 may be useful as a new tumor-specific marker.

Conclusions

LncRNA PCAT6 is highly expressed in multiple cancer types and its upregulation was significantly associated with patient prognosis and poorer clinical features, thereby suggesting that PCAT6 may be a novel prognostic factor in multiple cancer types.

TP73-AS1 is induced by YY1 during TMZ treatment and highly expressed in the aging brain

Aging is a factor associated with poor prognosis in glioblastoma (GBM). It is therefore important to understand the molecular features of aging contributing to GBM morbidity. TP73-AS1 is a long noncoding RNA (lncRNA) over expressed in GBM tumors shown to promote resistance to the chemotherapeutic temozolomide (TMZ), and tumor aggressiveness. How the expression of TP73-AS1 is regulated is not known, nor is it known if its expression is associated with aging. By analyzing transcriptional data obtained from natural and pathological aging brain, we found that the expression of TP73-AS1 is high in pathological and naturally aging brains. YY1 physically associates with the promoter of TP73-AS1 and we found that along with TP73-AS1, YY1 is induced by TMZ. We found that the TP73-AS1 promoter is activated by TMZ, and by YY1 over expression. Using CRISPRi to deplete YY1, we found that YY1 promotes up regulation of TP73-AS1 and the activation of its promoter during TMZ treatment. In addition, we identified two putative YY1 binding sites within the TP73-AS1 promoter, and used mutagenesis to find that they are essential for TMZ mediated promoter activation. Together, our data positions YY1 as an important TP73-AS1 regulator, demonstrating that TP73-AS1 is expressed in the natural and pathological aging brain, including during neurodegeneration and cancer. Our findings advance our understanding of TP73-AS1 expression, bringing forth a new link between TMZ resistance and aging, both of which contribute to GBM morbidity.

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.

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.

Downregulation of microRNA-320a inhibits proliferation and induces apoptosis of retinoblastoma cells via targeting TUSC3

MicroRNA (miR)-320a is specific to vertebrates and has been indicated to serve a role in a number of cancer types, such as gastric, colorectal, pancreatic and ovarian cancer. miR-320a has been reported to be expressed at high levels in retinoblastoma tissues; however its role and mechanism of function in retinoblastoma remain to be elucidated. The aim of the present study was to investigate the role of miR-320a in retinoblastoma cells and the underlying mechanisms. The expression of miR-320a in retinoblastoma cell lines Y79 and WERI-Rb-1, and normal human retinal pigment epithelial cell line ARPE-19 was examined via reverse transcription-quantitative PCR (RT-qPCR). TargetScan bioinformatics analysis and dual-luciferase reporter assay were used to predict and reveal the target gene of miR-320a. Target gene expression was detected via RT-qPCR in retinoblastoma cell lines and ARPE-19 cells. Subsequently, gain- or loss-of-function experiments for miR-320a and tumor suppressor candidate 3 (TUSC3) were performed to study the role of miR-320a/TUSC3 in retinoblastoma cells. Cell viability and apoptosis were assessed via MTT and flow cytometry analysis, respectively. Compared with ARPE-19 cells, miR-320a was prominently expressed in retinoblastoma cell lines. TUSC3 was predicted to be a target gene of miR-320a. Compared with ARPE-19 cells, the expression of TUSC3 in retinoblastoma cell lines was reduced. The results of MTT and flow cytometry analysis revealed that overexpression of TUSC3 reduced the viability of retinoblastoma cells and induced apoptosis. Additional analysis indicated that miR-320a inhibitor enhanced the expression of the target gene TUSC3, thereby inhibiting retinoblastoma cell viability and inducing apoptosis. The effects of miR-320a inhibitor on retinoblastoma cells were inhibited by TUSC3-short hairpin RNA. miR-320a regulated the viability and apoptosis of retinoblastoma cells via targeting TUSC3. Therefore, the present study provided a reference for investigating a potential target for the clinical treatment of retinoblastoma.