Long non-coding RNA DIO3OS/let-7d/NF-κB2 axis regulates cells proliferation and metastasis of thyroid cancer cells

Decreased DIO3OS Expression Predicts Poor Prognosis in Hepatocellular Carcinoma and is Associated with Immune Infiltration

Hepatocellular carcinoma has become one of the most shared cancers in the whole world because of its high morbidity, poor survival rate, and low recovery rate. LncRNA DIO3 opposite strand upstream RNA (DIO3OS) has been reported to be obviously important in several human cancers, while its biological function in hepatocellular carcinoma (HCC) remains unclear. Here, DIO3OS gene expression data and clinical information of HCC patients were extracted from the Cancer Genome Atlas (TCGA) database and the university of California Santa Cruz (UCSC) Xena database. In our study, the Wilcoxon rank sum test was used to compare DIO3OS expression between healthy individuals and HCC patients. It was found that patients with HCC had significantly lower DIO3OS expression than healthy individuals. Furthermore, Kaplan-Meier curves and Cox regression analysis showed that high DIO3OS expression tended to predict better prognosis and higher survival rate in HCC patients. In addition, the gene set enrichment analysis (GSEA) assay was used to annotate the biological function of DIO3OS. It was found that DIO3OS was significantly correlated with immune invasion in HCC. This was also aided by the subsequent ESTIMATE assay. Our study provides a novel biomarker and therapeutic strategy for patients with hepatocellular carcinoma.

Long intergenic non-coding RNA DIO3OS promotes osteosarcoma metastasis via activation of the TGF-β signaling pathway: a potential diagnostic and immunotherapeutic target for osteosarcoma

BACKGROUND

The aim of this study was to determine the underlying potential mechanisms and function of DIO3OS, a lincRNA in osteosarcoma and clarify that DIO3OS can be used as a potential diagnostic biomarker and immunotherapeutic target.

METHODS

The expression matrix data and clinical information were obtained from XENA platform of UCSC and GEO database as the test cohorts. The external validation cohort was collected from our hospital. Bioinformatics analysis was used to annotate the biological function of DIO3OS. Immune infiltration and immune checkpoint analysis were applied to evaluate whether DIO3OS can be used as an immunotherapeutic target. ROC curves and AUC were established to assess the diagnostic value of DIO3OS for differentiating patients from other subtypes sarcoma. The expression analysis was detected by qRT-PCR, western blot, and immunohistochemical. Wound healing assay and Transwell assay were applied to determine the migration and invasion function of DIO3OS in osteosarcoma cell lines. The tail vein injection osteosarcoma cells metastases model was used in this research.

RESULTS

High expression of DIO3OS was identified as a risk lincRNA for predicting overall survival of osteosarcoma in test cohort. The outcomes of experiments in vitro and in vivo showed that low expression of DIO3OS limited osteosarcoma tumor metastasis with inhibiting TGF-β signaling pathway. Immune checkpoint genes (CD200 and TNFRSF25) expressions were inhibited in the low DIO3OS expression group. The DIO3OS expression can be applied to reliably distinguish osteosarcoma from lipomatous neoplasms, myomatous neoplasms, nerve sheath tumors, and synovial-like neoplasms. This result was further validated in the validation cohort.

CONCLUSIONS

In conclusion, our outcomes indicated that DIO3OS is a potential diagnostic and prognostic biomarker of osteosarcoma, emphasizing its potential as a target of immunotherapy to improve the treatment of osteosarcoma through TGF-β signaling pathway.

TRIAL REGISTRATION NUMBER

The present retrospectively study was approved by the Ethics Committee of The Second Affiliated Hospital of Nanchang University [Review (2020) No. (115)].

The Conserved LncRNA DIO3OS Restricts Hepatocellular Carcinoma Stemness by Interfering with NONO-Mediated Nuclear Export of ZEB1 mRNA

Hepatocellular carcinoma (HCC) is an aggressive and fatal disease caused by a subset of cancer stem cells (CSCs). It is estimated that there are approximately 100 000 long noncoding RNAs (lncRNAs) in humans. However, the mechanisms by which lncRNAs affect tumor stemness remain poorly understood. In the present study, it is found that DIO3OS is a conserved lncRNA that is generally downregulated in multiple cancers, including HCC, and its low expression correlates with poor clinical outcomes in HCC. In in vitro cancer cell lines and an in vivo spontaneous HCC mouse model, DIO3OS markedly represses tumor development via its suppressive role in CSCs through downregulation of zinc finger E-box binding homeobox 1 (ZEB1). Interestingly, DIO3OS represses ZEB1 post-transcriptionally without affecting its mRNA levels. Subsequent experiments show that DIO3OS interacts with the NONO protein and restricts NONO-mediated nuclear export of ZEB1 mRNA. Overall, these findings demonstrate that the DIO3OS-NONO-ZEB1 axis restricts HCC development and offers a valuable candidate for CSC-targeted therapeutics for HCC.

Cuproptosis-related lncRNAs predict prognosis and immune response of thyroid carcinoma

Objective: To estimate the survival and prognosis of patients with thyroid carcinoma (THCA) based on the Long non-coding RNA (lncRNA) traits linked to cuproptosis and to investigate the connection between the immunological spectrum of THCA and medication sensitivity. Methods: RNA-Seq data and clinical information for THCA were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We built a risk prognosis model by identifying and excluding lncRNAs associated with cuproptosis using Cox regression and LASSO methods. Both possible biological and immune infiltration functions were investigated using Principal Component Analysis (PCA), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and immunoassays. The sensitivity of the immune response to possible THCA medicines was assessed using ratings for tumor immune dysfunction and exclusion (TIDE) and tumor mutational burden (TMB). Results: Seven cuproptosis-related lncRNAs were used to construct our prognostic prediction model: AC108704.1, DIO3OS, AL157388.1, AL138767.3, STARD13-AS, AC008532.1, and PLBD1-AS1. Using data from TCGA's training, testing, and all groups, Kaplan-Meier and ROC curves demonstrated this feature's adequate predictive validity. Different clinical characteristics have varying effects on cuproptosis-related lncRNA risk models. Further analysis of immune cell infiltration and single sample Gene Set Enrichment Analysis (ssGSEA) supported the possibility that cuproptosis-associated lncRNAs and THCA tumor immunity were closely connected. Significantly, individuals with THCA showed a considerable decline in survival owing to the superposition effect of patients in the high-risk category and high TMB. Additionally, the low-risk group had a higher TIDE score compared with the high-risk group, indicating that these patients had suboptimal immune checkpoint blocking responses. To ensure the accuracy and reliability of our results, we further verified them using several GEO databases. Conclusion: The clinical and risk aspects of cuproptosis-related lncRNAs may aid in determining the prognosis of patients with THCA and improving therapeutic choices.

Methylation of N6 adenosine-related long noncoding RNA: effects on prognosis and treatment in 'driver-gene-negative' lung adenocarcinoma

The improvement of treatment for patients with 'driver-gene-negative' lung adenocarcinoma (LUAD) remains a critical problem to be solved. We aimed to explore the role of methylation of N6 adenosine (m6A)-related long noncoding RNA (lncRNA) in stratifying 'driver-gene-negative' LUAD risk. Patients negative for mutations in EGFR, KRAS, BRAF, HER2, MET, ALK, RET, and ROS1 were identified as 'driver-gene-negative' cases. RNA sequencing was performed in 46 paired tumors and adjacent normal tissues from patients with 'driver-gene-negative' LUAD. Twenty-three m6A regulators and relevant lncRNAs were identified using Pearson's correlation analysis. K-means cluster analysis was used to stratify patients, and a prognostic nomogram was developed. The CIBERSORT and pRRophetic algorithms were employed to quantify the immune microenvironment and chemosensitivity. We identified two clusters highly consistent with the prognosis based on their unique expression profiles for 46 m6AlncRNAs. A risk model constructed from nine m6A lncRNAs could stratify patients into high- and low-risk groups with promising predictive power (C-index = 0.824), and the risk score was an independent prognostic factor. The clusters and risk models were closely related to immune characteristics and chemosensitivity. Additional pan-cancer analysis using the nine m6AlncRNAs showed that the expression of DIO3 opposite strand upstream RNA (DIO3OS) is closely related to the immune/stromal score and tumor stemness in a variety of cancers. Our results show that m6AlncRNAs are a reliable prognostic tool and can aid treatment decision-making in 'driver-gene-negative' LUAD. DIO3OS is associated with the development of various cancers and has potential clinical applications.

Identification of lncRNA biomarkers in hepatocellular carcinoma by comprehensive analysis of the lncRNA-mediated ceRNA network

Growing evidence implicates that miRNAs can interact with long non-coding RNAs (lncRNAs) to regulate target mRNAs through competitive interactions. However, this mechanism that regulate tumorigenesis and cancer progression remains largely unexplored. Long non-coding RNAs (lncRNAs) act as competing endogenous RNAs (ceRNAs), which play a significant role in regulating gene expression. The purpose of our study was to determine potential lncRNA biomarkers to predict the prognosis of HCC by comprehensive analysis of a ceRNA network. The edgeR package was used to obtain the differentially expressed RNA datasets by analyzing 370 HCC tissues and 50 adjacent non-HCC tissues from The Cancer Genome Atlas (TCGA). Through investigating the differentially expressed between HCC tissues and adjacent non-HCC tissues, a total of 947 lncRNAs, 52 miRNAs, and 1,650 mRNAs were obtained. The novel constructed ceRNA network incorporated 99 HCC-specific lncRNAs, four miRNAs, and 55 mRNAs. Survival analysis identified 22 differentially expressed mRNAs, four miRNAs, and nine lncRNAs which were associated with overall survival (OS) time in HCC (p < 0.05), and further exploration was performed to assess the correlation of these differentially expressed genes with tumor stage. The Interpretation of the potential functions of these differentially expressed genes in HCC was realized by Gene ontology (GO) and KEGG pathway enrichment analyses. Seven lncRNAs were confirmed based on univariate Cox regression analysis, lasso COX regression analysis and multivariate Cox regression analysis to construct a predictive model in HCC patients which were related to the prognosis of OS. In summary, ceRNAs contributed to explore the mechanism of tumorigenesis and development, and a model with seven lncRNAs might be potential biomarker to predict the prognosis of HCC. These findings supported the need to studies on the mechanisms involved in the regulation of HCC by ceRNAs.

Analysis of Competitive Endogenous Mechanism and Survival Prognosis of Serum Exosomes in Ovarian Cancer Patients Based on Sequencing Technology and Bioinformatics

Background: We determined the competitive endogenous in serum exosomes of ovarian cancer patients via sequencing technology and raw signal analysis. We performed an in-depth study of the potential mechanisms of ovarian cancer, predicted potential therapeutic targets and performed survival analysis of the potential targets.

Methods: Serum exosomes from three ovarian cancer patients were used as the experimental group, serum exosomes from three patients with uterine fibroids were used as the control group, and whole transcriptome analysis of serum exosomes was performed to identify differentially expressed long noncoding RNAs (lncRNAs) and mRNAs in ovarian cancer. The miRcode database and miRNA target gene prediction website were used to predict the target genes. Cytoscape software was used to generate a competing endogenous RNA (ceRNA) network of competitive endogenous mechanism of serum exosomes in ovarian cancer, and the R language was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of the target genes. Finally, the TCGA website was used to download clinical and expression data related to ovarian cancer, and the common potential target genes obtained previously were analyzed for survival.

Results: A total of 117 differentially expressed lncRNAs as well as 513 differentially expressed mRNAs (p < 0.05, |log2 fold change (FC)|≥ 1.0) were obtained by combining sequencing data and raw signal analysis, and 841 predicted target genes were reciprocally mapped by combining the data from the miRcode database and miRNA target gene prediction website, resulting in 11 potential target genes related to ovarian cancer (FGFR3, BMPR1B, TRIM29, FBN2, PAPPA, CCDC58, IGSF3, FBXO10, GPAM, HOXA10, and LHFPL4). Survival analysis of the above 11 target genes revealed that the survival curve was statistically significant (p < 0.05) for HOXA10 but not for the other genes. Through enrichment analysis, we found that the above target genes were mainly involved in biological processes such as regulation of transmembrane receptor protein kinase activity, structural molecule activity with elasticity, transforming growth factor-activated receptor activity, and GABA receptor binding and were mainly enriched in signaling pathways regulating stem cell pluripotency, bladder cancer, glycerolipid metabolism, central carbon metabolism of cancer, and tyrosine stimulation to EGFR in signaling pathways such as resistance to enzyme inhibitors.

Conclusions: The serum exosomal DIO3OS-hsa-miR-27a-3p-HOXA10 competitive endogenous signaling axis affects ovarian cancer development and disease survival by targeting dysregulated transcriptional pathways in cancer.

NF-κB as a regulator of cancer metastasis and therapy response: A focus on epithelial-mesenchymal transition

Metastasis of tumor cells is a complex challenge and significantly diminishes the overall survival and prognosis of cancer patients. The epithelial-to-mesenchymal transition (EMT) is a well-known mechanism responsible for the invasiveness of tumor cells. A number of molecular pathways can regulate the EMT mechanism in cancer cells and nuclear factor-kappaB (NF-κB) is one of them. The nuclear translocation of NF-κB p65 can induce the transcription of several genes involved in EMT induction. The present review describes NF-κB and EMT interaction in cancer cells and their association in cancer progression. Due to the oncogenic role NF-κB signaling, its activation enhances metastasis of tumor cells via EMT induction. This has been confirmed in various cancers including brain, breast, lung and gastric cancers, among others. The ZEB1/2, transforming growth factor-β, and Slug as inducers of EMT undergo upregulation by NF-κB to promote metastasis of tumor cells. After EMT induction driven by NF-κB, a significant decrease occurs in E-cadherin levels, while N-cadherin and vimentin levels undergo an increase. The noncoding RNAs can potentially also function as upstream mediators and modulate NF-κB/EMT axis in cancers. Moreover, NF-κB/EMT axis is involved in mediating drug resistance in tumor cells. Thus, suppressing NF-κB/EMT axis can also promote the sensitivity of cancer cells to chemotherapeutic agents.

Expression Profiles and Potential Functions of Long Non-Coding RNAs in the Heart of Mice With Coxsackie B3 Virus-Induced Myocarditis

Aims

Long non-coding RNAs (lncRNAs) are critical regulators of viral infection and inflammatory responses. However, the roles of lncRNAs in acute myocarditis (AM), especially fulminant myocarditis (FM), remain unclear.

Methods

FM and non-fulminant myocarditis (NFM) were induced by coxsackie B3 virus (CVB3) in different mouse strains. Then, the expression profiles of the lncRNAs in the heart tissues were detected by sequencing. Finally, the patterns were analyzed by Pearson/Spearman rank correlation, Kyoto Encyclopedia of Genes and Genomes, and Cytoscape 3.7.

Results

First, 1,216, 983, 1,606, and 2,459 differentially expressed lncRNAs were identified in CVB3-treated A/J, C57BL/6, BALB/c, and C3H mice with myocarditis, respectively. Among them, 88 lncRNAs were commonly dysregulated in all four models. Quantitative real-time polymerase chain reaction analyses further confirmed that four out of the top six commonly dysregulated lncRNAs were upregulated in all four models. Moreover, the levels of ENSMUST00000188819, ENSMUST00000199139, and ENSMUST00000222401 were significantly elevated in the heart and spleen and correlated with the severity of cardiac inflammatory infiltration. Meanwhile, 923 FM-specific dysregulated lncRNAs were detected, among which the levels of MSTRG.26098.49, MSTRG.31307.11, MSTRG.31357.2, and MSTRG.32881.28 were highly correlated with LVEF.

Conclusion

Expression of lncRNAs is significantly dysregulated in acute myocarditis, which may play different roles in the progression of AM.

Long Intergenic Non-Coding RNAs in HNSCC: From "Junk DNA" to Important Prognostic Factor

Head and neck squamous cell carcinoma is one of the most common and fatal cancers worldwide. Even a multimodal approach consisting of standard chemo- and radiotherapy along with surgical resection is only effective in approximately 50% of the cases. The rest of the patients develop a relapse of the disease and acquire resistance to treatment. Especially this group of individuals needs novel, personalized, targeted therapy. The first step to discovering such solutions is to investigate the tumor microenvironment, thus understanding the role and mechanism of the function of coding and non-coding sequences of the human genome. In recent years, RNA molecules gained great interest when the complex character of their impact on our biology allowed them to come out of the shadows of the "junk DNA" label. Furthermore, long non-coding RNAs (lncRNA), specifically the intergenic subgroup (lincRNA), are one of the most aberrantly expressed in several malignancies, which makes them particularly promising future diagnostic biomarkers and therapeutic targets. This review contains characteristics of known and validated lincRNAs in HNSCC, such as XIST, MALAT, HOTAIR, HOTTIP, lincRNA-p21, LINC02487, LINC02195, LINC00668, LINC00519, LINC00511, LINC00460, LINC00312, and LINC00052, with a description of their prognostic abilities. Even though much work remains to be done, lincRNAs are important factors in cancer biology that will become valuable biomarkers of tumor stage, outcome prognosis, and contribution to personalized medicine.