Long noncoding RNA taurine-up regulated gene 1 for the prognosis of osteosarcoma

Ren, Zheng; Li, Chenyang; Gan, Yuling; Liu, Xiuxin; Liang, Fudong

doi:10.1097/md.0000000000026182

Cited by 5 publications

(3 citation statements)

References 24 publications

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“…Khan et al (22) showed that the 3-phosphoinositol-dependent protein kinase (PDK) can promote chondrocyte apoptosis in OA through the p38 MAPK signaling pathway (23,24), while Yang et al (25) found DUal-specificity phosphatase (DUSP) overexpression in OA inhibited the activation of MAPK signaling and the expression of the OA-associated matrix. Zhang et al (26) revealed the JAK/STAT signaling pathway was regulated by significantly upregulated by proinflammatory cytokine gene expression, while MMP-13 expression in the IL-1treated human chondrosarcoma cell lines induced JAK2 and STAT1/STAT2 activation and MMP-13 gene expression which was blocked by the pan-tyrosine kinase inhibitor AG490 (27)(28)(29)(30). However, it was also found that treatment of this chondrocyte line with IL-1 also activated p38-MAPK.…”

Section: Discussionmentioning

confidence: 99%

Screening and identification of osteoarthritis related differential genes and construction of a risk prognosis model based on bioinformatics analysis

You¹,

Liu²,

Tan³

2022

Ann Transl Med

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Background: Searching for the production mechanism of synovial lesions helps to find precise therapeutic targets and improve prognosis. The previous identification and screening of differential genes in osteoarthritis (OA) pathogenesis were well combined to further build a risk prognosis model of OA, which is beneficial to the diagnosis and treatment of patients with OA. Methods:The synovia-related chip data sets GSE82107, GSE12021, GSE55457, and GSE55235 were downloaded from the public database of Gene Expression Omnibus (GEO), and 40 cases of synovial tissues of OA and 36 cases of normal synovial tissues were included. R software was used to screen differentially expressed genes (DEGs), Gene Ontology (GO) functional enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The STRING online analysis tool and Cytoscape software were used to further screen key genes, and a prognostic model of OA susceptibility risk was constructed. Results:The results showed 1,921 differential genes, including 762 upregulated genes and 1,159 downregulated genes, which were mainly involved cell growth, cell adhesion, skeletal muscle growth, iron ion binding, ubiquitin protein ligase binding, and hormone receptor binding. Co-acquisition based on 10 key target genes of the protein interaction network, containing CTNNB1, GSK3B, STAT1, RHOC, HDAC9, PSEN1, KDM5C, BACE1, JAK3, and CUL1. The area under the concentration-time curve (AUC) was used to evaluate the prognostic model of OA risk, and the curve results showed that the prognostic model had high accuracy and validity (AUC =0.690).Conclusions: Bioinformatics analysis was applied to screen out the DEG profiles of OA. This may provide functional predictions to provide new ideas for treatment of the disease and may be a biological marker for its diagnosis and a potential target for treatment. The construction of the risk and prognosis model is beneficial to the risk assessment of rehabilitation function recovery of patients with OA, the evaluation of the severity of the disease and the subsequent treatment guidance.

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Section: Discussionmentioning

confidence: 99%

Screening and identification of osteoarthritis related differential genes and construction of a risk prognosis model based on bioinformatics analysis

You¹,

Liu²,

Tan³

2022

Ann Transl Med

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“…For example, during the last few years, a nuclear lncRNA called NEAT1 (Nuclear-Enriched Abundant Transcript 1) has recently gained considerable attention due to its important contributions to gene regulation through NEAT1-binding proteins, such as enzymes, transcription factors, and receptors [32,33]. RegRNA 2.0 [34] is an integrated web server for identifying functional RNA motifs in an input sequence, which is often used for predicting the potential binding of lncRNAs to transcriptional factors or microRNAs [35]. Here, we first identified that LOC339059 is a nuclear lncRNA via ISH, regarded as the gold-standard approach [36], in fixed cells and tumor tissues and then predicted potential binding factors using RegRNA 2.0.…”

Section: Discussionmentioning

confidence: 99%

Long Non-Coding RNA LOC339059 Attenuates IL-6/STAT3-Signaling-Mediated PDL1 Expression and Macrophage M2 Polarization by Interacting with c-Myc in Gastric Cancer

Han,

Ding,

Wang

et al. 2023

Cancers

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Background: Long non-coding RNA (lncRNA) was identified as a novel diagnostic biomarker in gastric cancer (GC). However, the functions of lncRNAs in immuno-microenvironments have not been comprehensively explored. In this study, we explored a critical lncRNA, LOC339059, that can predict the clinical prognosis in GC related to the modulation of PD-L1 and determined its influence upon macrophage polarization via the IL-6/STAT3 pathway. Methods: To date, accumulating evidence has demonstrated that the dysregulation of LOC339059 plays an important role in the pathological processes of GC. It acts as a tumor suppressor, regulating GC cell proliferation, migration, invasion, tumorigenesis, and metastasis. A flow cytometry assay showed that the loss of LOC339059 enhanced PDL1 expression and M2 macrophage polarization. RNA sequencing, RNA pull-down, RNA immunoprecipitation, Chip-PCR, and a luciferase reporter assay revealed the pivotal role of signaling alternation between LOC339059 and c-Myc. Results: A lower level of LOC339059 RNA was found in primary GC tissues compared to adjacent tissues, and such a lower level is associated with a poorer survival period (2.5 years) after surgery in patient cohorts. Moreover, we determined important immunological molecular biomarkers. We found that LOC339059 expression was correlated with PD-L1, CTLA4, CD206, and CD204, but not with TIM3, FOXP3, CD3, C33, CD64, or CD80, in a total of 146 GC RNA samples. The gain of LOC339059 in SGC7901 and AGS inhibited biological characteristics of malignancy, such as proliferation, migration, invasion, tumorigenesis, and metastasis. Furthermore, our data gathered following the co-culture of THP-1 and U937 with genomic GC cells indicate that LOC339059 led to a reduction in the macrophage cell ratio, in terms of CD68+/CD206+, to 1/6, whereas the selective knockdown of LOC339059 promoted the abovementioned malignant cell phenotypes, suggesting that it has a tumor-suppressing role in GC. RNA-Seq analyses showed that the gain of LOC339059 repressed the expression of the interleukin family, especially IL-6/STAT3 signaling. The rescue of IL-6 in LOC339059-overexpressing cells reverted the inhibitory effects of the gain of LOC339059 on malignant cell phenotypes. Our experiments verified that the interaction between LOC339059 and c-Myc resulted in less c-Myc binding to the IL-6 promoter, leading to the inactivation of IL-6 transcription. Conclusions: Our results establish that LOC339059 acts as a tumor suppressor in GC by competitively inhibiting c-Myc, resulting in diminished IL-6/STAT3-signaling-mediated PDL1 expression and macrophage M2 polarization.

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“…This article also presents several tables that summarize other recent studies on exosomal miRNAs in OS therapy, an overall view for targeted OS treatment as well as good biomarker for OS cells. More recently, the application of artificial intelligence, such as machine learning or bioinformatic tools, using Exo, have demonstrated promising results on the identification of predictive and prognostic markers for OS [15][16][17]. Although some new technologies are being developed in recent years, current methods used for the isolation and characterization of Exo are, often, used for prognostic and diagnostic purposes.…”

Section: Commentarymentioning

confidence: 99%

Commentary on “Osteosarcoma from the Unknown to the Use of Exosomes as a Versatile and Dynamic Therapeutic Approach”

Figueiras

2023

J Cell Immunol

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Long noncoding RNA taurine-up regulated gene 1 for the prognosis of osteosarcoma

Cited by 5 publications

References 24 publications

Screening and identification of osteoarthritis related differential genes and construction of a risk prognosis model based on bioinformatics analysis

Screening and identification of osteoarthritis related differential genes and construction of a risk prognosis model based on bioinformatics analysis

Long Non-Coding RNA LOC339059 Attenuates IL-6/STAT3-Signaling-Mediated PDL1 Expression and Macrophage M2 Polarization by Interacting with c-Myc in Gastric Cancer

Commentary on “Osteosarcoma from the Unknown to the Use of Exosomes as a Versatile and Dynamic Therapeutic Approach”

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