LncRNA PVT1 Regulates miR-1207-5p to Affect Colon Cancer Proliferation and Migration via the Wnt6/β-catenin2 Pathway

LncRNA PVT1 promotes proliferation and migration in gallbladder adenocarcinoma by modulating miR-2355-5p/AGO1 axis

To investigate how lncRNA plasmacytoma variant translocation 1 (PVT1) contributed to the pathogenesis of gallbladder adenocarcinoma (GBA). Bioinformatics techniques were used to analyze differentially expressed lncRNA, and downstream miRNA and mRNA were identified using databases. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) and western blotting were utilized to analyze the RNA and protein expressions in different cells. The binding relationships between different genes were confirmed utilizing luciferase assay and RNA Immunoprecipitation (RIP) assay. Cell growth and migration were examined through CCK-8, colony formation, and Transwell assays. Several in vivo experiments were utilized to determine how the PVT1/miR-2355-5p/AGO1 pathway on tumor growth. Elevated PVT1 was observed in GBA cells, which may further aggravate cell malignant properties. Based on bioinformatics analysis, an interaction between miR-2355-5p and either PVT1 or AGO1 was identified, which was confirmed utilizing dual luciferase reporter assays and RIP assays. Silencing PVT1 (si-PVT1) led to a reduction in AGO1 expression, while depletion of miR-2355-5p reversed this effect. In vivo, PVT1 knockdown significantly inhibited tumor growth, an effect that was reversed by miR-2355-5p downregulation. This study showed that PVT1 facilitated GBA progression via the modulation of the miR-2355-5p/AGO1 axis. These findings underscored the potential therapeutic significance of targeting the lncRNA PVT1 in the treatment of GBA.

Emerging roles and biomarker potential of WNT6 in human cancers

The WNT6 ligand is a well-known activator of the WNT signaling pathway, considered a vital player in several important physiologic processes during embryonic development and maintaining homeostasis throughout life, regulating the proliferation and differentiation of multiple stem/progenitor cell types. More recently, as it is the case for many key molecular regulators of embryonic development, dysregulation of WNT6 has been implicated in cancer development and progression in multiple studies. In this review, we overview the most significant recent findings regarding WNT6 in the context of human malignancies, exploring its influence on multiple dimensions of tumor pathophysiology and highlighting the putative underlying WNT6-associated molecular mechanisms. We also discuss the potential clinical implications of WNT6 as a prognostic and therapeutic biomarker. This critical review highlights the emerging relevance of WNT6 in multiple human cancers, and its potential as a clinically-useful biomarker, addressing key unanswered questions that could lead to new opportunities in patient diagnosis, stratification, and the development of rationally-designed precision therapies.

Exploration of PVT1 as a biomarker in prostate cancer

Prostate cancer is a malignant tumor originating from the prostate gland, significantly affecting patients' quality of life and survival rates. Public data was utilized to identify differentially expressed genes (DEGs). Weighted gene co-expression network analysis was constructed to classify gene modules. Functional enrichment analysis was performed through Kyoto Encyclopedia of Genes and Genomes and gene ontology annotations, with results visualized using the Metascape database. Additionally, gene set enrichment analysis evaluated gene expression profiles and related pathways, constructed a protein-protein interaction network to predict core genes, analyzed survival data, plotted heatmaps and radar charts, and predicted microRNAs for core genes through miRTarBase. Two prostate cancer datasets (GSE46602 and GSE55909) were analyzed, identifying 710 DEGs. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed that DEGs were primarily involved in organic acid metabolism and the P53 signaling pathway. Gene set enrichment analysis and Metascape analyses further confirmed the significance of these pathways. After constructing the weighted gene co-expression network analysis network, 3 core genes (DDX21, NOP56, plasmacytoma variant translocation 1 [PVT1]) were identified. Survival analysis indicated that core genes are closely related to patient prognosis. Through comparative toxicogenomics database and miRNA prediction analysis, PVT1 was considered to play a crucial role in the development of prostate cancer. The PVT1 gene is highly expressed in prostate cancer and has the potential to become a diagnostic biomarker and therapeutic target for prostate cancer.

The functions and mechanisms of long non-coding RNA in colorectal cancer

CRC poses a significant challenge in the global health domain, with a high number of deaths attributed to this disease annually. If CRC is detected only in its advanced stages, the difficulty of treatment increases significantly. Therefore, biomarkers for the early detection of CRC play a crucial role in improving patient outcomes and increasing survival rates. The development of a reliable biomarker for early detection of CRC is particularly important for timely diagnosis and treatment. However, current methods for CRC detection, such as endoscopic examination, blood, and stool tests, have certain limitations and often only detect cases in the late stages. To overcome these constraints, researchers have turned their attention to molecular biomarkers, which are considered a promising approach to improving CRC detection. Non-invasive methods using biomarkers such as mRNA, circulating cell-free DNA, microRNA, LncRNA, and proteins can provide more reliable diagnostic information. These biomarkers can be found in blood, tissue, stool, and volatile organic compounds. Identifying molecular biomarkers with high sensitivity and specificity for the early and safe, economic, and easily measurable detection of CRC remains a significant challenge for researchers.

Prediction of lncRNA and disease associations based on residual graph convolutional networks with attention mechanism

LncRNAs are non-coding RNAs with a length of more than 200 nucleotides. More and more evidence shows that lncRNAs are inextricably linked with diseases. To make up for the shortcomings of traditional methods, researchers began to collect relevant biological data in the database and used bioinformatics prediction tools to predict the associations between lncRNAs and diseases, which greatly improved the efficiency of the study. To improve the prediction accuracy of current methods, we propose a new lncRNA-disease associations prediction method with attention mechanism, called ResGCN-A. Firstly, we integrated lncRNA functional similarity, lncRNA Gaussian interaction profile kernel similarity, disease semantic similarity, and disease Gaussian interaction profile kernel similarity to obtain lncRNA comprehensive similarity and disease comprehensive similarity. Secondly, the residual graph convolutional network was used to extract the local features of lncRNAs and diseases. Thirdly, the new attention mechanism was used to assign the weight of the above features to further obtain the potential features of lncRNAs and diseases. Finally, the training set required by the Extra-Trees classifier was obtained by concatenating potential features, and the potential associations between lncRNAs and diseases were obtained by the trained Extra-Trees classifier. ResGCN-A combines the residual graph convolutional network with the attention mechanism to realize the local and global features fusion of lncRNA and diseases, which is beneficial to obtain more accurate features and improve the prediction accuracy. In the experiment, ResGCN-A was compared with five other methods through 5-fold cross-validation. The results show that the AUC value and AUPR value obtained by ResGCN-A are 0.9916 and 0.9951, which are superior to the other five methods. In addition, case studies and robustness evaluation have shown that ResGCN-A is an effective method for predicting lncRNA-disease associations. The source code for ResGCN-A will be available at https://github.com/Wangxiuxiun/ResGCN-A .

LncRNA-PVT1 was identified as a key regulator for TMZ resistance and STAT-related pathway in glioma

BACKGROUND

PVT1, a previously uncharacterized lncRNA, was identified as a critical regulator involved in multiple functions in tumor, including cell proliferation, cell motility, angiogenesis and so on. However, the clinical significance and underlying mechanism of PVT1 was not be fully explored in glioma.

METHODS

In this study, 1210 glioma samples with transcriptome data from three independent databases (CGGA RNA-seq, TCGA RNA-seq and GSE16011 cohorts) were enrolled in this study. Clinical information and genomic profiles containing somatic mutations and DNA copy numbers were collected from TCGA cohort. The R software was performed for statistical calculations and graphics. Furthermore, we validated the function of PVT1 in vitro.

RESULTS

The results indicated that higher PVT1 expression was associated with aggressive progression of glioma. Cases with higher PVT1 expression always accompanied by PTEN and EGFR alteration. In addition, functional analyses and western blot results suggested that PVT1 inhibited the sensitivity of TMZ chemotherapy via JAK/STAT signaling. Meanwhile, knockdown of PVT1 increased the sensitivity of TZM chemotherapy in vitro. Finally, high PVT1 expression was associated with reduced survival time and may serve as a strong prognostic indicator for gliomas.

CONCLUSIONS

This study demonstrated that PVT1 expression strongly correlated with tumor progression and chemo-resistance. PVT1 may become a potential biomarker for the diagnosis and treatment in glioma.