Long noncoding RNA SLC9A3‑AS1 increases E2F6 expression by sponging microRNA‑486‑5p and thus facilitates the oncogenesis of nasopharyngeal carcinoma

Necroptosis-related lncRNA-based novel signature to predict the prognosis and immune landscape in soft tissue sarcomas

BACKGROUND

Necroptosis-related long noncoding RNAs (lncRNAs) play crucial roles in cancer initiation and progression. Nevertheless, the role and mechanism of necroptosis-related lncRNAs in soft tissue sarcomas (STS) is so far unknown and needs to be explored further.

METHODS

Clinical and genomic data were obtained from the UCSC Xena database. All STS patients' subclusters were performed by unsupervised consensus clustering method based on the prognosis-specific lncRNAs, and then assessed their survival advantage and immune infiltrates. In addition, we explored the pathways and biological processes in subclusters through gene set enrichment analysis. At last, we established the necroptosis-related lncRNA-based risk signature (NRLncSig) using the least absolute shrinkage and selection operator (LASSO) method, and explored the prediction performance and immune microenvironment of this signature in STS.

RESULTS

A total of 911 normal soft tissue samples and 259 STS patients were included in current study. 39 prognosis-specific necroptosis-related lncRNAs were selected. Cluster 2 had a worse survival than the cluster 1 and characterized by different immune landscape in STS. A worse outcome in the high-risk group was observed by survival analysis and indicated an immunosuppressive microenvironment. The ROC curve analyses illustrated that the NRLncSig performing competitively in prediction of prognosis for STS patients. In addition, the nomogram presents excellent performance in predicting prognosis, which may be more beneficial towards STS patients' treatment.

CONCLUSIONS

Our result indicated that the NRLncSig could be a good independent predictor of prognosis, and significantly connected with immune microenvironment, thereby providing new insights into the roles of necroptosis-related lncRNAs in STS.

Identification of important modules and biomarkers in tuberculosis based on WGCNA

Background

Tuberculosis (TB) is a significant public health concern, particularly in China. Long noncoding RNAs (lncRNAs) can provide abundant pathological information regarding etiology and could include candidate biomarkers for diagnosis of TB. However, data regarding lncRNA expression profiles and specific lncRNAs associated with TB are limited.

Methods

We performed ceRNA-microarray analysis to determine the expression profile of lncRNAs in peripheral blood mononuclear cells (PBMCs). Weighted gene co-expression network analysis (WGCNA) was then conducted to identify the critical module and genes associated with TB. Other bioinformatics analyses, including Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and co-expression networks, were conducted to explore the function of the critical module. Finally, real-time quantitative polymerase chain reaction (qPCR) was used to validate the candidate biomarkers, and receiver operating characteristic analysis was used to assess the diagnostic performance of the candidate biomarkers.

Results

Based on 8 TB patients and 9 healthy controls (HCs), a total of 1,372 differentially expressed lncRNAs were identified, including 738 upregulated lncRNAs and 634 downregulated lncRNAs. Among all lncRNAs and mRNAs in the microarray, the top 25% lncRNAs (3729) and top 25% mRNAs (2824), which exhibited higher median expression values, were incorporated into the WGCNA. The analysis generated 16 co-expression modules, among which the blue module was highly correlated with TB. GO and KEGG analyses showed that the blue module was significantly enriched in infection and immunity. Subsequently, considering module membership values (>0.85), gene significance values (>0.90) and fold-change value (>2 or < 0.5) as selection criteria, the top 10 upregulated lncRNAs and top 10 downregulated lncRNAs in the blue module were considered as potential biomarkers. The candidates were then validated in an independent validation sample set (31 TB patients and 32 HCs). The expression levels of 8 candidates differed significantly between TB patients and HCs. The lncRNAs ABHD17B (area under the curve [AUC] = 1.000) and ENST00000607464.1 (AUC = 1.000) were the best lncRNAs in distinguishing TB patients from HCs.

Conclusion

This study characterized the lncRNA profiles of TB patients and identified a significant module associated with TB as well as novel potential biomarkers for TB diagnosis.

MiRNA signatures in nasopharyngeal carcinoma: molecular mechanisms and therapeutic perspectives

Nasopharyngeal carcinoma (NPC) is a prevalent cancerous tumor that affects the head and neck region. Recent studies have provided compelling evidence indicating the significant involvement of microRNAs (miRNAs) in the development and progression of NPC. This review aims to present a comprehensive summary of the current knowledge regarding miRNA signatures in NPC, encompassing their expression patterns, molecular mechanisms, and potential therapeutic implications. Initially, the article outlines the aberrant expression of miRNAs in NPC and elucidates their roles in tumor initiation, invasion, and metastasis. Subsequently, the underlying molecular mechanisms of miRNA-mediated regulation of NPC-associated signaling pathways are discussed. Additionally, the review highlights the potential clinical applications of miRNAs as diagnostic and prognostic biomarkers, as well as their therapeutic potential in NPC treatment. In conclusion, this review underscores the critical involvement of miRNAs in NPC pathogenesis and underscores their promise as novel therapeutic targets for combating this devastating disease.

lncRNA SLC9A3-AS1 Promotes Oncogenesis of NSCLC via Sponging microRNA-760 and May Serve as a Prognosis Predictor of NSCLC Patients

Background

Non-small cell lung cancer (NSCLC) is a prevalent type of lung cancer worldwide. Long noncoding RNA (lncRNA) SLC9A3-AS1 is reported to play a carcinogenic role in nasopharyngeal carcinoma, but its full-scale role in NSCLC remains elusive.

Methods

SLC9A3-AS1 expression was detected in serum and tissue of NSLCC patients and NSCLC cell lines. The effects of SLC9A3-AS1 on NSCLC proliferation, migration and invasion were evaluated using CCK-8 and transwell assays. In addition, the potential downstream molecules of SLC9A3-AS1 were searched and explored by bioinformatics analysis, RT-qPCR, dual-luciferase reporter, and rescue experiments.

Results

SLC9A3-AS1 was upregulated in NSCLC tissues and cell lines. SLC9A3-AS1 possessed a favorable ability in diagnosing NSCLC. A high level of SLC9A3-AS1 was associated with poor prognosis in NSCLC patients. Functionally, SLC9A3-AS1 knockdown inhibited cell proliferation, migration, and invasion of NSCLC cells. Mechanistically, SLC9A3-AS1 acted as competing endogenous RNA for miR-760 to regulate NSCLC progression. In addition, rescue assay showed that downregulation of miR-760 could reverse the modulatory activity of SLC9A3-AS1 knockdown on NSCLC cells.

Conclusion

SLC9A3-AS1 was upregulated in NSCLC, and SLC9A3-AS1 knockdown hindered NSCLC progression through targeting miR-760, suggesting that it may prove to be a novel biomarker and therapeutic target for NSCLC.

Long non-coding RNA RGMB-AS1 represses nasopharyngeal carcinoma progression via binding to forkhead box A1

Long non-coding RNA RGMB-AS1 (RGMB antisense RNA 1) plays a crucial role in tumor progression. However, its underlying mechanism in nasopharyngeal carcinoma (NPC) remains unclear. In this study, we analyzed the clinical significance of lncRNA RGMB-AS1 as a possible potential marker in NPC, and investigated the effect and mechanism of lncRNA RGMB-AS1 on proliferation, migration and epithelial mesenchymal transformation (EMT) of NPC by directly binding Forkhead box A1 (FOXA1) in vitro and in vivo. In conclusion, LncRNA RGMB-AS1 inhibits malignant behaviors and EMT by regulating FOXA1, and lncRNA RGMB-AS1 may be an important indicator of clinical prognosis.