Noncoding RNAs: New regulatory code in chondrocyte apoptosis and autophagy

Jiang, Siyu; Liu, Yi; Xu, Billian; Zhang, Yan; Ye, Min

doi:10.1002/wrna.1584

Cited by 60 publications

(38 citation statements)

References 171 publications

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“…Qian et al [ 46 ] found that the lnc-HLA-DQA1-5 (ENST00000419852, HLA-DQB1-AS1) expression in patients with smoking chronic obstructive pulmonary disease (COPD) was increased compared to controls and speculated that it played a crucial role in the pathogenesis in smoking COPD. Admittedly, accumulating evidence supported that there were many differentially expressed lncRNAs in KOA cartilage [ 35 , 47 ] and that lncRNAs were involved in the formation, proliferation, apoptosis, and autophagy of chondrocytes [ 47 , 48 ]. For example, FOXD2-AS1 induced the proliferation of chondrocytes in OA by sponging miR-27a-3p [ 49 ], lncRNA-CIR regulated the apoptosis of chondrocytes in OA [ 50 ], and overexpression of lncRNA-ROR significantly promoted the viability of OA chondrocytes and regulated the autophagy and apoptosis of chondrocytes through p53 and HIF1 α [ 51 ].…”

Section: Discussionmentioning

confidence: 99%

Identification of lncRNA and mRNA Biomarkers in Osteoarthritic Degenerative Meniscus by Weighted Gene Coexpression Network and Competing Endogenous RNA Network Analysis

Zhao

Su²,

Jiao³

et al. 2020

BioMed Research International

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Background. Long noncoding RNAs (lncRNAs) play a crucial role in varieties of biological processes. This study is aimed at investigating meniscal degeneration-specific lncRNAs and mRNAs and their related networks in knee osteoarthritis (KOA). Methods. The dataset GSE98918, which included 24 meniscus samples and related clinical data, was downloaded from the Gene Expression Omnibus database. The differentially expressed lncRNAs and mRNAs in the meniscus between KOA and control groups were identified. Based on the enriched differentially expressed lncRNAs and mRNAs, we constructed the coexpression network using WGCNA (weighted correlation network analysis) and identified the critical module related to KOA. For mRNAs in the key module, gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were carried out using the DAVID database. A competing endogenous RNA network (ceRNA) based on the screened mRNAs, lncRNAs, and related miRNAs was constructed to reveal presumptive biomarkers further. Finally, the hub lncRNAs and mRNAs were screened, and the diagnostic value was evaluated using a receiver operating characteristic (ROC) curve. Hub mRNAs were validated using the dataset GSE113825. Results. We screened 208 significantly differentially expressed lncRNAs and mRNAs in menisci between the KOA and non-KOA samples, which were enriched in sixteen modules using WGCNA, especially the green module. Coexpression network based on the enriched differentially expressed lncRNAs and mRNAs in the green module uncovered 5 lncRNAs and 56 mRNAs. The lncRNA-miRNA-mRNA ceRNA network revealed that lnc-HLA-DQA1-5, lnc-RP11-127H5.1.1-1, lnc-RTN2-1, IGFBP4 (insulin-like growth factor binding protein 4), and KLF2 (Kruppel-like factor 2) were significantly correlated with the meniscus degeneration of KOA. ROC curve analysis revealed that these hub lncRNAs and mRNAs showed excellent diagnostic value for KOA. Conclusions. These hub lncRNAs and mRNAs were potential prognostic biomarkers for the meniscus degeneration of KOA. Further studies are required to validate these new biomarkers and better understand the pathological process of the meniscus degeneration of KOA.

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Section: Discussionmentioning

confidence: 99%

Identification of lncRNA and mRNA Biomarkers in Osteoarthritic Degenerative Meniscus by Weighted Gene Coexpression Network and Competing Endogenous RNA Network Analysis

Zhao

Su²,

Jiao³

et al. 2020

BioMed Research International

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“…The role of circRNAs in the pathogenesis of OA has drawn increasing attention (17,27,28). Previous studies revealed that circRNAs play regulatory roles in cartilage ECM degradation, in ammatory response in chondrocytes, and apoptosis (12,29). This study investigated the pathogenesis of OA from the perspective of the regulation of HA metabolism by circRNAs.…”

Section: Discussionmentioning

confidence: 99%

CircHYBID Regulates Hyaluronan Metabolism in Chondrocytes by Promoting the Expression of the hsa-miR-29b-3p Target Gene TGF-β1

Liao

Zhang

Chen

et al. 2020

Preprint

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Background: Hyaluronan (HA) metabolism by chondrocytes is essential for cartilage development and homeostasis. However, the function of circular RNAs (circRNAs)in HA metabolism is limited. In this study, we profiled the role of the novel HA-related circRNA circHYBID in the progression of osteoarthritis.Methods: The function of circHYBID in HA metabolism in chondrocytes was investigated using gain-of-function experiments. The mechanism of HA-binding protein involved in hyaluronan depolymerization (HYBID) was confirmed through bioinformatics analysis and luciferase assays. The expression correlation of the circHYBID–hsa-miR-29b-3p–transforming growth factor (TGF)-β1 axis was examined by qRT-PCR and western blotting. CircHYBID, TGF-β1, and HA levels in cartilage samples were evaluated using immunohistochemistry. ELISA assay was used to assess HA accumulation in chondrocyte supernatant.Results: CircHYBID expression was significantly downregulated in damaged cartilage samples comparing with that in the corresponding intact cartilage samples. CircHYBID expression was inversely correlated with the Mankin score and positively correlated with HA expression. Interleukin-1β stimulation in chondrocytes downregulated circHYBID expression and decreased HA accumulation. Gain-of-function experiments revealed that circHYBID overexpression in chondrocytes increased HA accumulation by regulating HA synthase 2 and HYBID expression. Further mechanism analysis illustrated that circHYBID upregulated TGF-β1 expression by sponging hsa-miR-29b-3p. Conclusions: Our results describe a novel HA-related circRNA that could promote the synthesis and accumulation of HA. The circHYBID–hsa-miR-29b-3p–TGF-β1 axis may play a powerful regulatory role in HA metabolism and Osteoarthritis (OA) progression. Thus, these findings will provide new perspectives for studies on OA pathogenesis, and circHYBID may serve as a potential target for OA therapy.

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“…On the contrary, once the tumor is formed, autophagy plays an oncogenic function that provides cancer cells with needed survival contexts, such as nutrition to resist stress (especially after chemotherapy treatment) (Kimmelman and White, 2017). The specific roles of autophagy in tumors depend on tumor type and tumor heterogeneity, which is regulated by multiple proteins and non-coding RNAs (ncRNAs) (Jiang et al, 2020;Perez-Montoyo, 2020).…”

Section: Introductionmentioning

confidence: 99%

The Role of Autophagy in Gastric Cancer Chemoresistance: Friend or Foe?

Tang

et al. 2020

Front. Cell Dev. Biol.

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Gastric cancer is the third most common cause of cancer-related death worldwide. Drug resistance is the main inevitable and vital factor leading to a low 5-year survival rate for patients with gastric cancer. Autophagy, as a highly conserved homeostatic pathway, is mainly regulated by different proteins and non-coding RNAs (ncRNAs) and plays dual roles in drug resistance of gastric cancer. Thus, targeting key regulatory nodes in the process of autophagy by small molecule inhibitors or activators has become one of the most promising strategies for the treatment of gastric cancer in recent years. In this review, we provide a systematic summary focusing on the relationship between autophagy and chemotherapy resistance in gastric cancer. We comprehensively discuss the roles and molecular mechanisms of multiple proteins and the emerging ncRNAs including miRNAs and lncRNAs in the regulation of autophagy pathways and gastric cancer chemoresistance. We also summarize the regulatory effects of autophagy inhibitor and activators on gastric cancer chemoresistance. Understanding the vital roles of autophagy in gastric cancer chemoresistance will provide novel opportunities to develop promising therapeutic strategies for gastric cancer.

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Noncoding RNAs: New regulatory code in chondrocyte apoptosis and autophagy

Cited by 60 publications

References 171 publications

Identification of lncRNA and mRNA Biomarkers in Osteoarthritic Degenerative Meniscus by Weighted Gene Coexpression Network and Competing Endogenous RNA Network Analysis

Identification of lncRNA and mRNA Biomarkers in Osteoarthritic Degenerative Meniscus by Weighted Gene Coexpression Network and Competing Endogenous RNA Network Analysis

CircHYBID Regulates Hyaluronan Metabolism in Chondrocytes by Promoting the Expression of the hsa-miR-29b-3p Target Gene TGF-β1

The Role of Autophagy in Gastric Cancer Chemoresistance: Friend or Foe?

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Noncoding RNAs: New regulatory code in chondrocyte apoptosis and autophagy

Cited by 60 publications

References 171 publications

Identification of lncRNA and mRNA Biomarkers in Osteoarthritic Degenerative Meniscus by Weighted Gene Coexpression Network and Competing Endogenous RNA Network Analysis

Identification of lncRNA and mRNA Biomarkers in Osteoarthritic Degenerative Meniscus by Weighted Gene Coexpression Network and Competing Endogenous RNA Network Analysis

CircHYBID&nbsp;Regulates Hyaluronan Metabolism in Chondrocytes by Promoting the Expression of the hsa-miR-29b-3p Target Gene TGF-β1

The Role of Autophagy in Gastric Cancer Chemoresistance: Friend or Foe?

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CircHYBID Regulates Hyaluronan Metabolism in Chondrocytes by Promoting the Expression of the hsa-miR-29b-3p Target Gene TGF-β1