Identification of biomarkers associated with the recurrence of osteosarcoma using ceRNA regulatory network analysis

LncRNA SNHG1: role in tumorigenesis of multiple human cancers

Small nucleolar RNA host gene 1 (SNHG1) is an important member of the SNHG family. This family is composed of a group of host genes that can be processed into small nucleolar RNAs and play important biological functions. In an oncogenic role, the SNHG1 expression is increased in various cancers, which has immense application prospects in the diagnosis, treatment, and prognosis of malignant tumors. In this review, we have summarized the role and molecular mechanism of SNHG1 in the development of various cancers. In addition, we have emphasized the clinical significance of SNHG1 in cancers in our article. This molecule is expected to be a new marker for potential usage in the diagnosis, prognosis, and treatment of cancer.

Screening for MicroRNA combination with engineered exosomes as a new tool against osteosarcoma in elderly patients

The most common primary malignant bone sarcoma is Osteogenic sarcoma (OS) which has a bimodal age distribution. Unfortunately, the treatment of OS was less effective for elderly patients than for younger ones. The study aimed to explore a new microRNA (miRNA) which can bind to combining engineered exosomes for treatment of older OS patients. Based on GSE65071 and miRNet 2.0, two up-regulated miRNAs (miR-328, miR-107) and seven down-regulated miRNAs (miR-133b, miR-206, miR-1-3p, miR-133a, miR-449a, miR-181daysay, miR-134) were selected. Next, we used FunRich software to predict the up-stream transcription factors (TFs) of differentially expressed miRNAs (DE-miRNAs). By comparing target genes predicted from DE-miRNAs with differentially expressed genes, we identified 12 down-regulated and 310 up-regulated mRNAs. For KEGG analysis, the most enriched KEGG pathway was Cell cycle, Spliceosome, and Protein digestion and absorption. By using protein-protein interactions network, topological analysis algorithm and GEPIA database, miR-449a /CCNB1 axis was identified. Experiments in vitro were conducted to confirm the results too. MiRNA-449a is down-regulated in osteosarcoma and suppresses cell proliferation by targeting CCNB1. Our findings not only reveal a novel mechanism of miR-449a /CCNB1 in OS but also had laid the groundwork for further investigation and analysis in the field of exosome engineering.

Immuno-Modulatory Effects of Intervertebral Disc Cells

Low back pain is a highly prevalent, chronic, and costly medical condition predominantly triggered by intervertebral disc degeneration (IDD). IDD is often caused by structural and biochemical changes in intervertebral discs (IVD) that prompt a pathologic shift from an anabolic to catabolic state, affecting extracellular matrix (ECM) production, enzyme generation, cytokine and chemokine production, neurotrophic and angiogenic factor production. The IVD is an immune-privileged organ. However, during degeneration immune cells and inflammatory factors can infiltrate through defects in the cartilage endplate and annulus fibrosus fissures, further accelerating the catabolic environment. Remarkably, though, catabolic ECM disruption also occurs in the absence of immune cell infiltration, largely due to native disc cell production of catabolic enzymes and cytokines. An unbalanced metabolism could be induced by many different factors, including a harsh microenvironment, biomechanical cues, genetics, and infection. The complex, multifactorial nature of IDD brings the challenge of identifying key factors which initiate the degenerative cascade, eventually leading to back pain. These factors are often investigated through methods including animal models, 3D cell culture, bioreactors, and computational models. However, the crosstalk between the IVD, immune system, and shifted metabolism is frequently misconstrued, often with the assumption that the presence of cytokines and chemokines is synonymous to inflammation or an immune response, which is not true for the intact disc. Therefore, this review will tackle immunomodulatory and IVD cell roles in IDD, clarifying the differences between cellular involvements and implications for therapeutic development and assessing models used to explore inflammatory or catabolic IVD environments.

Comprehensive bioinformatic analyses of lncRNA-mediated ceRNA network for uterine corpus endometrial carcinoma

Background

Given that long non-coding RNAs (lncRNAs) involved in the tumor initiation or progression of the endometrium and that competing endogenous RNA (ceRNA) plays an important role in increasingly more biological processes, lncRNA-mediated ceRNA is likely to function in the pathogenesis of uterine corpus endometrial carcinoma (UCEC). Our present study aimed to explore the potential molecular mechanisms for the prognosis of UCEC through a lncRNA-mediated ceRNA network.

Methods

The transcriptome profiles and corresponding clinical profiles of UCEC dataset were retrieved from Clinical Proteomic Tumor Analysis Consortium (CPTAC) and The Cancer Genome Atlas (TCGA) databases respectively. Differentially expressed genes (DEGs) in UCEC samples were identified via "Edge R" package. Then, an integrated bioinformatics analysis including functional enrichment analysis, tumor infiltrating immune cell (TIIC) analysis, Kaplan-Meier curve, Cox regression analysis were conducted to analyze the prognostic biomarkers.

Results

In the CPTAC dataset of UCEC, a ceRNA network comprised of 36 miRNAs, 123 lncRNAs and 124 targeted mRNAs was established, and 8 of 123 prognostic-related Differentially Expressed long noncoding RNAs (DElncRNAs) were identified. While in the TCGA dataset, a ceRNA network comprised of 38 miRNAs, 83 lncRNAs and 110 targeted mRNAs was established, and 2 of 83 prognostic-related DElncRNAs were identified. After filtered by risk grouping and Cox regression analysis, 10 prognostic-related lncRNAs including LINC00443, LINC00483, C2orf48, TRBV11-2, MEG-8 were identified. In addition, 33 survival-related Differentially Expressed messenger RNA (DEmRNAs) in two ceRNA networks were further validated in the Human Protein Atlas Portal (HPA) database. Finally, six lncRNA/miRNA/mRNA axes were established to elucidate prognostic regulatory roles in UCEC.

Conclusions

Several prognostic lncRNAs are identified and prognostic model of lncRNA-mediated ceRNA network is constructed, which promotes the understanding of UCEC development mechanisms and potential therapeutic targets.

Effects of Triiodothyronine on Human Osteoblast-Like Cells: Novel Insights From a Global Transcriptome Analysis

Background: Thyroid hormones play a significant role in bone development and maintenance, with triiodothyronine (T3) particularly being an important modulator of osteoblast differentiation, proliferation, and maintenance. However, details of the biological processes (BPs) and molecular pathways affected by T3 in osteoblasts remain unclear.

Methods: To address this issue, primary cultures of human adipose-derived mesenchymal stem cells were subjected to our previously established osteoinduction protocol, and the resultant osteoblast-like cells were treated with 1 nm or 10 nm T3 for 72 h. RNA sequencing (RNA-Seq) was performed using the Illumina platform, and differentially expressed genes (DEGs) were identified from the raw data using Kallisto and DESeq2. Enrichment analysis of DEGs was performed against the Gene Ontology Consortium database for BP terms using the R package clusterProfiler and protein network analysis by STRING.

Results: Approximately 16,300 genes were analyzed by RNA-Seq, with 343 DEGs regulated in the 1 nm T3 group and 467 upregulated in the 10 nm T3 group. Several independent BP terms related to bone metabolism were significantly enriched, with a number of genes shared among them (FGFR2, WNT5A, WNT3, ROR2, VEGFA, FBLN1, S1PR1, PRKCZ, TGFB3, and OSR1 for 1nM T3; and FZD1, SMAD6, NOG, NEO1, and ENG for 10 nm T3). An osteoblast-related search in the literature regarding this set of genes suggests that both T3 doses are unfavorable for osteoblast development, mainly hindering BMP and canonical and non-canonical WNT signaling.

Conclusions: Therefore, this study provides new directions toward the elucidation of the mechanisms of T3 action on osteoblast metabolism, with potential future implications for the treatment of endocrine-related bone pathologies.

The regulatory mechanism of LncRNA-mediated ceRNA network in osteosarcoma

Aberrantly expressed lncRNAs have been reported to be closely related to the oncogenesis and development of osteosarcoma. However, the role of a dysregulated lncRNA-miRNA-mRNA network in osteosarcoma in the same individual needs to be further investigated. Whole transcriptome sequencing was performed on the tumour tissues and matched paratumour tissues of three patients with confirmed osteosarcoma. Two divergent lncRNA-miRNA-mRNA regulatory networks were constructed in accordance with their biological significance. The GO and KEGG analysis results of the mRNAs in the two networks revealed that the aberrantly expressed lncRNAs were involved in regulating bone growth and development, epithelial cell proliferation, cell cycle arrest and the N-terminal acetylation of proteins. The survival analysis results of the two networks showed that patients with high expression of GALNT3, FAM91A1, STC2 and SLC7A1 end in poorer prognosis. Likewise, patients with low expression of IGF2, BLCAP, ZBTB47, THRB, PKIA and MITF also had poor prognosis. A subnetwork was then constructed to demonstrate the key genes regulated by aberrantly expressed lncRNAs at the posttranscriptional level via the ceRNA network. Aberrantly expressed lncRNAs in osteosarcoma tissues regulate genes involved in cellular proliferation, differentiation, angiogenesis and the cell cycle via the ceRNA network.

The Potential Role of Small Nucleolar RNAs in Cancers – An Evidence Map

Purpose

Cancer seriously endangers human health in every country of the world. New evidence shows that small nucleolar RNAs play important roles in tumorigenesis. Herein, we created this evidence map to systematically assess the impact of dysregulated snoRNAs on cancers.

Methods

We searched four databases to February 2022 using the keywords, “carcinoma”, “neoplasms”, “tumor”, “cancer”, “snoRNA”, and “small nucleolar rna”. The research data were independently screened by two reviewers. Bubble plot, mind map, heatmap were used to depict the relationship between snoRNAs and cancers.

Results

In total, 102 studies met the inclusion criteria and were analyzed in this evidence map. In this study, we found that dysregulated snoRNAs were statistically associated with the clinicopathological characteristics of cancer patients, and affected tumor cell phenotypes. Abnormally expressed snoRNAs were associated with poor survival in cancer patients. Current research confirmed that snoRNAs have good diagnostic efficiency for cancers. snoRNAs could modulate biological processes and signaling pathways of different cancer cells by altering rRNA, regulating mRNA, and recruiting protein factors.

Conclusion

Taken all together, ectopic snoRNAs may serve as new biomarkers for clinical assessment, diagnostic, prognostic prediction of cancer patients, and provide a potential therapeutic strategy for cancer treatment. This article provided a visual analysis of existing evidence on snoRNAs and cancers, which can offer useful information for different researchers interested in snoRNAs.

Screening of Significant Biomarkers Related to Prognosis of Cervical Cancer and Functional Study Based on lncRNA-associated ceRNA Regulatory Network

BACKGROUND

Cervical cancer (CESC), which threatens the health of women, has a very high recurrence rate.

PURPOSES

This study aimed to identify the signature long non-coding RNAs (lncRNAs) associated with the prognosis of CESC and predict the prognostic survival rate with the clinical risk factors.

METHODS

The CESC gene expression profiling data were downloaded from TCGA database and NCBI Gene Expression Omnibus. Afterwards, the differentially expressed RNAs (DERs) were screened using limma package of R software. R package "survival" was then used to screen the signature lncRNAs associated with independently recurrence prognosis, and a nomogram recurrence rate model based on these signature lncRNAs was constructed to predict the 3-year and 5-year survival probability of CESC. Finally, a competing endogenous RNAs (ceRNA) regulatory network was proposed to study the functions of these genes.

RESULTS

We obtained 305 DERs significantly associated with prognosis. Afterwards, a risk score (RS) prediction model was established using the screened 5 signature lncRNAs associated with independently recurrence prognosis (DLEU1, LINC01119, RBPMS-AS1, RAD21-AS1 and LINC00323). Subsequently, a nomogram recurrence rate model, proposed with Pathologic N and RS model status, was found to have a good prediction ability for CESC. In ceRNA regulatory network, LINC00323 and DLEU1 were hub nodes which targeted more miRNAs and mRNAs. After that, 15 GO terms and 3 KEGG pathways were associated with recurrence prognosis and showed that the targeted genes PTK2, NRP1, PRKAA1 and HMGCS1 might influence the prognosis of CESC.

CONCLUSION

The signature lncRNAs can help improve our understanding of the development and recurrence of CESC and the nomogram recurrence rate model can be applied to predict the survival rate of CESC patients in clinical practice.

Development of a Novel Immune Infiltration-Related ceRNA Network and Prognostic Model for Sarcoma

Due to the rarity and heterogeneity, it is challenging to explore and develop new therapeutic targets for patients with sarcoma. Recently, immune cell infiltration in the tumor microenvironment (TME) was widely studied, which provided a novel potential approach for cancer treatment. The competing endogenous RNA (ceRNA) regulatory network has been reported as a critical molecular mechanism of tumor development. However, the role of the ceRNA regulatory network in the TME of sarcoma remains unclear. In this study, gene expression data and clinical information were obtained from The Cancer Genome Atlas (TCGA) sarcoma datasets, and an immune infiltration-related ceRNA network was constructed, which comprised 14 lncRNAs, 13 miRNAs, and 23 mRNAs. Afterward, we constructed an immune infiltration-related risk score model based on the expression of IRF1, MFNG, hsa-miR-940, and hsa-miR-378a-5p, presenting a promising performance in predicting the prognosis of patients with sarcoma.

Knockdown of HCG18 Inhibits Cell Viability, Migration and Invasion in Pediatric Osteosarcoma by Targeting miR-188-5p/FOXC1 Axis

Understanding the underlying mechanisms of pediatric osteosarcoma (OS) migration and invasion is important for prognosis and treatment. We tried to measure the expression of long non-coding RNA HLA complex group 18 (HCG18) in OS and reveal its function in the malignant behaviors of OS cells. This study detected the expression of HCG18, miR-188-5p and forkhead box C1 (FOXC1) in OS tissues and cell lines by quantitative real-time PCR (qRT-PCR). The relevance between miR-188-5p and HCG18 or FOXC1 was affirmed by dual-luciferase reporter (DLR) assay. Cell viability was analyzed by MTT assay. Transwell assay was utilized to test cell invasion and migration. FOXC1 protein expression was detected by western blot. HCG18 expression was elevated in OS tissues, and enhanced HCG18 expression was related to metastasis. HCG18 silencing repressed the viability, migration and invasion of OS cells. Moreover, HCG18 interacted with miR-188-5p. MiR-188-5p up-regulation repressed cell viability, invasion and migration in OS cells. FOXC1, a known target of miR-188-5p, was negatively modulated by miR-188-5p. Furthermore, miR-188-5p inhibition or FOXC1 over-expression partially abolished the reduced of cell viability, invasion and migration mediated by HCG18 silencing in OS cell lines. This study revealed that HCG18 knockdown repressed the viability, invasion and migration of OS cells by targeting miR-188-5p and regulating FOXC1 expression. Thus, HCG18/ miR-188-5p/FOX may be a hopeful target for OS therapy.

Identification of Gene as Predictive Biomarkers for the Occurrence and Recurrence of Osteosarcoma

Purpose

Osteosarcoma is the most common malignant bone cancer affecting adolescents and young adults. This study aimed to screen potential diagnostic and therapeutic markers for osteosarcoma.

Methods

Differential expression analysis between osteosarcoma and control was performed in GSE99671, the differentially expressed genes (DEGs) were subjected to co-expression analysis. Enrichment analysis was employed to identify the biological functions and KEGG signaling pathways of module genes. In addition, a differential analysis was also performed between recurrent and non-recurrent osteosarcoma samples in GSE39055, and enrichment analysis was performed for DEGs. Further, Kaplan–Meier curve analysis was performed on the module genes, and receiver operating characteristic (ROC) curve was drawn. Comparison of the module with the highest correlation to osteosarcoma identified key genes. Cox regression model was utilized to identify the predictive ability of key genes for the prognosis of osteosarcoma.

Results

A total of 13 co-expression modules were identified from 4871 DEGs of GSE99671, module 1 had the highest positive correlation with osteosarcoma. Module genes were mainly enriched in autophagy and macrophage migration functions. A total of 1126 DEGs were obtained from GSE39055, significantly involved in neutrophil mediated immunity. Screening of genes with area under the ROC curve (AUC) values greater than 0.73 in both GSE99671 and GSE39055 identified 5 key genes when compared with genes from module 1. The nomogram results showed that ATF5, CHCHD8, ENOPH1, and LOC286367 might predict 5-year or 8-year survival time of osteosarcoma patients. The Cox model results confirmed that the signals of ATF5, CHCHD8, and LOC286367 were robust, and it may be used in the diagnosis, treatment, and prognosis of osteosarcoma.

Conclusion

We found that ATF5, CHCHD8, and LOC286367 can effectively identify osteosarcoma tumorigenesis and even recurrence status. This is helpful for early diagnosis and treatment, improving the clinical treatment of patients with osteosarcoma.

Identifying biomolecules and constructing a prognostic risk prediction model for recurrence in osteosarcoma

INTRODUCTION

Osteosarcoma is a high-morbidity bone cancer with an unsatisfactory prognosis. The aim of this study is to develop novel potential prognostic biomarkers and construct a prognostic risk prediction model for recurrence in osteosarcoma.

METHODS

By analyzing microarray data, univariate and multivariate Cox regression analyses were performed to screen prognostic RNA signatures and to build a prognostic model. The RNA signatures were validated using Kaplan-Meier curves. Then, we developed and validated a nomogram combining age, recurrence, metastatic, and Prognostic score (PS) models to predict the individual's overall survival at the 3- and 5-year points. Pathway enrichment of RNA was conducted based on the significant co-expressed RNAs.

RESULTS

A total of 319 mRNAs and 14 lncRNAs were identified in the microarray data. One lncRNA (LINC00957) and six mRNAs (METL1, CA9, B3GALT4, ALDH1A1, LAMB3, and ITGB4) were identified as RNA signatures and showed good performances in survival prediction for both the training and validation cohorts. Cox regression analysis showed that the seven RNA signatures could independently predict overall survival. Furthermore, age, recurrence, metastatic, and PS models were identified as independent prognostic factors via univariate and multivariate Cox analyses (P < 0.05) and included in the prognostic nomogram. The C-index values for the 3- and 5-year overall survival predictions of the nomogram were 0.809 and 0.740, respectively.

CONCLUSIONS

The current study provides the novel potential of seven RNA candidates as prognostic biomarkers. Nomograms were constructed to provide accurate and individualized survival prediction for recurrence in osteosarcoma patients.

Identification and Analysis of Three Hub Prognostic Genes Related to Osteosarcoma Metastasis

Osteosarcoma (OS) often occurs in children and often undergoes metastasis, resulting in lower survival rates. Information on the complexity and pathogenic mechanism of OS is limited, and thus, the development of treatments involving alternative molecular and genetic targets is hampered. We categorized transcriptome data into metastasis and nonmetastasis groups, and 400 differential RNAs (230 messenger RNAs (mRNAs) and 170 long noncoding RNAs (lncRNAs)) were obtained by the edgeR package. Prognostic genes were identified by performing univariate Cox regression analysis and the Kaplan-Meier (KM) survival analysis. We then examined the correlation between the expression level of prognostic lncRNAs and mRNAs. Furthermore, microRNAs (miRNAs) corresponding to the coexpression of lncRNA-mRNA was predicted, which was used to construct a competitive endogenous RNA (ceRNA) regulatory network. Finally, multivariate Cox proportional risk regression analysis was used to identify hub prognostic genes. Three hub prognostic genes (ABCG8, LOXL4, and PDE1B) were identified as potential prognostic biomarkers and therapeutic targets for OS. Furthermore, transcriptions factors (TFs) (DBP, ESX1, FOS, FOXI1, MEF2C, NFE2, and OTX2) and lncRNAs (RP11-357H14.16, RP11-284N8.3, and RP11-629G13.1) that were able to affect the expression levels of genes before and after transcription were found to regulate the prognostic hub genes. In addition, we identified drugs related to the prognostic hub genes, which may have potential clinical applications. Immunohistochemistry (IHC) and quantitative real-time polymerase chain reaction (qRT-PCR) confirmed that the expression levels of ABCG8, LOXL4, and PDE1B coincided with the results of bioinformatics analysis. Moreover, the relationship between the hub prognostic gene expression and patient prognosis was also validated. Our study elucidated the roles of three novel prognostic biomarkers in the pathogenesis of OS as well as presenting a potential clinical treatment for OS.

Integrated Analysis of Competing Endogenous RNAs Network Reveals Potential Signatures in Osteosarcoma Development

The purpose of this work was to extract key players such as mRNAs and long non-coding RNA (lncRNAs) in the etiopathogenesis of osteosarcoma (OS). The sequencing analyses (mRNAs and lncRNAs) of OS were conducted followed by differentially expressed mRNAs and lncRNAs (DEmRNAs and DElncRNAs) identification between U-2OS cells with has-miR-590-5p overexpression and negative control cells. Following this, the co-expression and functional enrichment analyses of DEmRNAs and DElncRNAs were carried out. Also, the miRNAs-DElncRNAs-DEmRNAs regulatory network was constructed with DElncRNAs-miRNAs and DElncRNAs-DEmRNAs pairs after the target gene analysis of miRNA. In addition, the ceRNA-has-miR-590-5p was further extracted based on the has-miR-590-5p-DElncRNAs and DElncRNAs-DEmRNAs interactions. Finally, the results of the bioinformatics analysis was verified by reverse-transcription polymerase chain reaction (RT-PCR). Totally, 980 DEmRNAs (539 up-regulated DEmRNAs and 441 down-regulated DEmRNAs) and 682 DElncRNAs (352 up-regulated DElncRNAs and 330 down-regulated DElncRNAs) were extracted between cells with hsa-miR-590-5p overexpression and normal cells. The functional analyses suggested that up-regulated genes were significantly enriched in several GO terms such as signal transduction and cytokine-cytokine receptor interaction pathway while down-regulated genes (SCUBE3, HIST1H4E and EDIL3) were associated with calcium ion binding, cell surface function and nucleosome assembly. Additionally, the miRNAs-DEmRNAs-DEmRNAs network represented 220 pairs among 41 miRNAs, 38 DElncRNAs and 61 DEmRNAs. Furthermore, the ceRNA-hsa-miR-590-5p network consisted of 70 interaction pairs including hsa-miR-590-5p-SCUBE3-CTB-113D17.1, hsa-miR-590-5p-EDIL3-CTB-113D17.1 and hsa-miR-590-5p-HIST1H4E-CTB-113D17.1) among hsa-miR-590-5p, 30 DEmRNAs and 4 down-regulated DElncRNAs. Meanwhile, the RT-PCR results incidated that compared with the blank (KB) and negative control (NC) group, the mRNA expression of SCUBE3, HIST1H4E, and EDIL3 were significantly descreased in mimics group (P value <0.05). The lncRNA CTB-113D17.1 might implicate with OS development probably via serving as a hsa-miR-590-5p sponge to regulate gene targets (SCUBE3, EDIL3 and HIST1H4E), which will facilitate the deep understandings of OS progression.

Alterations in DNA methylation profiles in cancellous bone of postmenopausal women with osteoporosis

Osteoporosis is characterized by systemic microarchitecture impairment and bone loss, which ultimately lead to fragility fractures. This disease is most common in older people, especially in postmenopausal women. Cancellous bone is affected by osteoporosis earlier than cortical bone, and DNA methylation microarray analysis of the hip cancellous bone of patients with osteoarthritis revealed differential methylation. In view of the important role of cancellous bone in bone development, we examined genome‐wide DNA methylation profiles in the cancellous bone from patients with postmenopausal osteoporosis versus healthy postmenopausal women using Illumina 850K methylation microarray analysis. Under a threshold of P < 0.05, we obtained a total of 8973 differentially methylated genes, such as SOX6, ACE, SYK and TGFB3. Under a threshold of P < 0.05 and |△β| > 0.2, a total of 17 and 34 key differentially methylated genes were further identified at the promoter region and cytosine‐ phosphate‐ guanine (CpG) islands (such as PRKCZ, GNA11 and COL4A1), respectively. PLEKHA2, PLEKHB1, PNPLA7, SCD, MGST3 and TSNAX were the most common differentially methylated genes at both the promoter region and CpG islands. Five important signaling pathways, including the calcium signaling pathway, the cyclic guanosine phospho‐protein kinase G (cGMP‐PKG) signaling pathway, endocytosis, the Rap1 signaling pathway and the AMPK signaling pathway were identified. Our study may be suitable as a basis for exploring the mechanisms underlying osteoporosis in postmenopausal women.

MicroRNAs signatures, bioinformatics analysis of miRNAs, miRNA mimics and antagonists, and miRNA therapeutics in osteosarcoma

MicroRNAs (miRNAs) involved in key signaling pathways and aggressive phenotypes of osteosarcoma (OS) was discussed, including PI3K/AKT/MTOR, MTOR AND RAF-1 signaling, tumor suppressor P53- linked miRNAs, NOTCH- related miRNAs, miRNA -15/16 cluster, apoptosis related miRNAs, invasion-metastasis-related miRNAs, and 14Q32-associated miRNAs cluster. Herrin, we discussed insights into the targeted therapies including miRNAs (i.e., tumor-suppressive miRNAs and oncomiRNAs). Using bioinformatics tools, the interaction network of all OS-associated miRNAs and their targets was also depicted.

Long non-coding RNA MEG3 is involved in osteogenic differentiation and bone diseases (Review)

Osteogenic differentiation originating from mesenchymal stem cells (MSCs) requires tight co-ordination of transcriptional factors, signaling pathways and biomechanical cues. Dysregulation of such reciprocal networks may influence the proliferation and apoptosis of MSCs and osteoblasts, thereby impairing bone metabolism and homeostasis. An increasing number of studies have shown that long non-coding (lnc)RNAs are involved in osteogenic differentiation and thus serve an important role in the initiation, development, and progression of bone diseases such as tumors, osteoarthritis and osteoporosis. It has been reported that the lncRNA, maternally expressed gene 3 (MEG3), regulates osteogenic differentiation of multiple MSCs and also acts as a critical mediator in the development of bone formation and associated diseases. In the present review, the proposed mechanisms underlying the roles of MEG3 in osteogenic differentiation and its potential effects on bone diseases are discussed. These discussions may help elucidate the roles of MEG3 in osteogenic differentiation and highlight potential biomarkers and therapeutic targets for the treatment of bone diseases.

Competitive endogenous RNA (ceRNA) regulation network of lncRNAs, miRNAs, and mRNAs in Wilms tumour

Background

Competitive endogenous RNAs (ceRNAs) have revealed a new mechanism of interaction between RNAs. However, an understanding of the ceRNA regulatory network in Wilms tumour (WT) remains limited.

Methods

The expression profiles of mRNAs, miRNAs and lncRNAs in Wilms tumour samples and normal samples were obtained from the Therapeutically Applicable Research to Generate Effective Treatment (TARGET) database. The EdgeR package was employed to identify differentially expressed lncRNAs, miRNAs and mRNAs. Functional enrichment analyses via the ClusterProfile R package were performed, and the lncRNA–miRNA–mRNA interaction ceRNA network was established in Cytoscape. Subsequently, the correlation between the ceRNA network and overall survival was analysed.

Results

A total of 2037 lncRNAs, 154 miRNAs and 3609 mRNAs were identified as differentially expressed RNAs in Wilms tumour. Of those, 205 lncRNAs, 26 miRNAs and 143 mRNAs were included in the ceRNA regulatory network. The results of Gene Ontology (GO) analysis revealed that the differentially expressed genes (DEGs) were mainly enriched in terms related to response to mechanical stimuli, transcription factor complexes, and transcription factor activity (related to RNA polymerase II proximal promoter sequence-specific DNA binding). The results of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that the DEGs were mainly enriched in pathways related to the cell cycle. The survival analysis results showed that 16 out of the 205 lncRNAs, 1 out of 26 miRNAs and 5 out of 143 mRNAs were associated with overall survival in Wilms tumour patients (P < 0.05).

Conclusions

CeRNA networks play an important role in Wilms tumour. This finding might provide effective, novel insights for further understanding the mechanisms underlying Wilms tumour.

Exploration and validation of downregulated microRNA-199a-3p, downstream messenger RNA targets and transcriptional regulation in osteosarcoma

Osteosarcoma (OS) is a primary bone tumor with a high incidence and mortality in children and adolescents. Emerging evidence shows that microRNAs (miRNAs) participate in biological tumor mechanisms by targeting downstream messenger RNAs (mRNAs). This article aimed to investigate the potential regulatory targets of microRNA-199a-3p (miR-199a-3p) in OS and to contribute to the understanding of miR-199a-3p-related OS regulatory mechanisms. MicroRNA-related Gene Expression Omnibus (GEO) chips, ArrayExpress chips and literature data were used to determine the expression of miR-199a-3p in OS and pooled to explore its potential clinical value. To investigate the target genes of miR-199a-3p further, we integrated the results from the following three-part gene study: Twelve online prediction tools were used to predict the target genes of miR-199a-3p; the GEO GSE89370 chip transfected with miRSelect pEP-miR-199a-3p was used to analyze the downregulated differentially expressed genes (DEGs) in OS cells; and highly expressed DEGs were derived from an in-house microarray generated from three pairs of clinical OS and normal tissue samples acquired through our department. Then, we analyzed the target genes using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases and the protein-protein interaction (PPI) network to further identify the primary target genes. In addition, we constructed transcription factor (TF)-miRNA-joint gene feed-forward regulatory loops (FFLs) with Circuits DB using miR-199a-3p as the core. A comprehensive meta-analysis of a hub of miR-199a-3p targeted genes was performed to integrate expression level, summary ROC (sROC) curves and survival analysis results from the GEO data for verification and exploration. Finally, the expression levels of the hub genes were verified in OS tissues and U2OS cells by immunohistochemistry (IHC) and immunocytochemistry (ICC). Data on miR-199a-3p expression were obtained from three data sets (GSE65071, GSE69524, and PMID 21666078), which showed low miR-199a-3p expression levels in OS tissues. The combined data indicated the same tendency, with the SMD of the random effect model, as shown in forest plots, being -2.8 (95% CI: -4.49, -1.11). In addition, we determined that miR-199a-3p may serve as a molecular marker useful for distinguishing OS tissues from normal tissues with high sensitivity and specificity, with the measured outcomes being 0.94 (95% CI: 0.80, 0.99) and 0.96 (95% CI: 0.78, 1.00), respectively. In addition, 391 genes were considered targets of miR-199a-3p in OS, and the enrichment analysis indicated that these targets were mainly enriched in proteoglycans in cancer and in spliceosomes. Four genes, CDKI, CCNB1, AURKA and NEK2, were regarded as hub targets based on the PPI data. Subsequently, TF-miRNA-joint genes FFLs were constructed in Circuits DB and included 17 TFs and 82 joint targets. These joint targets were mainly enriched in spliceosomes. UBE2D1 and RBM25 were regarded as hub joint targets based on the enrichment analysis. All selected target genes were further verified to ensure that they were upregulated in OS and to determine their prognostic significance. At the experimental verification level, the CDK1 protein was confirmed to be positively expressed in the cytoplasm of OS tissues and the U2OS cell line. Our study verified that miR-199a-3p was obviously downregulated in OS. CDK1, CCNB1, NEK2, AURKA, UBE2D1 and RBM25 were identified as potential target genes of miR-199a-3p in OS.

Knockdown of lncRNA HOXA-AS2 Inhibits Viability, Migration and Invasion of Osteosarcoma Cells by miR-124-3p/E2F3

Background

Osteosarcoma (OS) is one of the most frequent bone malignancies. Long noncoding RNAs (lncRNAs) have been revealed to participate in many cancers, including OS. This study aimed to explore the biological function of lncRNA homeobox A cluster antisense RNA2 (HOXA-AS2) and its potential mechanism in OS progression.

Methods

Twenty-seven OS patients were recruited for this study. U2OS and MG-63 cells were cultured for in vitro analyses. The levels of HOXA-AS2, microRNA-124-3p (miR-124-3p) and E2F transcription factor 3 (E2F3) were measured by quantitative real-time polymerase chain reaction or Western blot. OS progression was investigated by cell viability, migration and invasion using cell counting kit-8 or trans-well assay. The interaction among HOXA-AS2, miR-124-3p and E2F3 was explored by bioinformatics analysis, luciferase reporter assay, RNA immunoprecipitation and biotinylated RNA pull-down. Xenograft model was established by injecting U2OS cells into nude mice.

Results

HOXA-AS2 expression was increased in OS tissues and cells and associated with poor survival of patients. Knockdown of HOXA-AS2 inhibited cell viability, migration and invasion in OS cells. miR-124-3p could bind with HOXA-AS2 and its deficiency reversed the suppressive role of HOXA-AS2 knockdown. Moreover, E2F3 acted as a target of miR-124-3p and positively regulated by HOXA-AS2. Silence of E2F3 suppressed OS progression, which was abolished by miR-124-3p exhaustion. Interference of HOXA-AS2 attenuated U2OS xenograft tumor growth via upregulating miR-124-3p and downregulating E2F3.

Conclusion

HOXA-AS2 silence impeded OS progression possibly by functioning as a decoy of miR-124-3p to target E2F3, indicating novel evidence of HOXA-AS2 as a promising therapeutic target of OS.