Abnormally expressed long non-coding RNAs in prognosis of Osteosarcoma: A systematic review and meta-analysis

Chen, Delong; Wang, Haibin; Zhang, Meng; Jiang, Shan; Zhou, Chi; Fang, Bin; Chen, Peng

doi:10.1016/j.jbo.2018.09.005

Cited by 13 publications

(10 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…LncRNA UCA1, BCAR4, HULC, and MALAT1 are independent risk factors for poor overall survival rate in osteosarcoma patients. LncRNA DANCR, PARTICLE, HNF1A-AS1, XIST, CCAL and MEG3 can predict metastasis in osteosarcoma patients [11]. However, the role of UCA1 in regulating osteosarcoma invasion and migration remains unclear.…”

Section: Discussionmentioning

confidence: 99%

Long noncoding RNA UCA1 promotes osteosarcoma metastasis through CREB1-mediated epithelial-mesenchymal transition and activating PI3K/AKT/mTOR pathway

Feng³

et al. 2019

Journal of Bone Oncology

View full text Add to dashboard Cite

Highlights UCA1 is upregulated in both osteosarcoma tissues and cell lines. UCA1 promotes osteosarcoma metastasis both in vitro and in vivo. UCA1 increased CREB1 expression by functioning as a ceRNA of CREB1 against miR-582. The pro-metastasis role of UCA1 is achieved by promoting EMT. UCA1 enhances EMT through CREB1-mediated the PI3K/Akt/mTOR pathway.

show abstract

Section: Discussionmentioning

confidence: 99%

Long noncoding RNA UCA1 promotes osteosarcoma metastasis through CREB1-mediated epithelial-mesenchymal transition and activating PI3K/AKT/mTOR pathway

Feng³

et al. 2019

Journal of Bone Oncology

View full text Add to dashboard Cite

show abstract

“…MALAT-1 functions as a competitive endogenous RNA (ceRNA) by binding to different miRNAs that regulate the transcription of genes such as cell division cycle 2 (cdc2) through miR-1 in breast carcinoma cells [139], Slug through miR-204 in lung adenocarcinoma [140] and metalloproteinase-14 (MMP14), and Snail through miR-22 in melanoma [141]. MALAT-1 is highly expressed in osteosarcoma tissue samples and is correlated with metastatic dissemination and advanced clinical stage [142,143]. MALAT-1 acts through the PI3K/Akt pathway to promote osteosarcoma cell proliferation, migration, invasion, and pulmonary metastasis [87].…”

Section: Oncogenic Lncrnasmentioning

confidence: 99%

“…Furthermore, MALAT-1 knockdown or siRNA interference experiments, carried out by Dong et al and Cai et al, respectively, showed that MALAT1 inhibition suppressed osteosarcoma cell proliferation and metastasis via the PI3K/Akt and RhoA/ROCK signaling pathways by modulating the expression of MMP-9 metalloproteinase [85,87,88]. MALAT-1 is highly expressed in osteosarcoma tissue samples and is correlated with metastatic dissemination and advanced clinical stage [142,143].…”

Section: Lncrnas and Invasion/metastasis In Osteosarcomamentioning

confidence: 99%

“…Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is an oncogenic lncRNA that is overexpressed in various osteosarcoma cell lines such as U2OS, Saos-2, and HOS and in human osteosarcoma tissue samples as well. Its overexpression is highly related to the metastatic potential of the tumor [142,143]. MALAT1 acts through the PI3K/Akt and the RhoA/ROCK signaling pathway to promote osteosarcoma cell proliferation, migration, invasion, and pulmonary metastasis [87].…”

Section: Lncrnas As Therapeutic Targets In Osteosarcomamentioning

confidence: 99%

See 1 more Smart Citation

Long Noncoding RNAs in Osteosarcoma: Mechanisms and Potential Clinical Implications

Valavanis¹,

Stanc²

2019

Osteosarcoma – Diagnosis, Mechanisms, and Translational Developments

View full text Add to dashboard Cite

Long noncoding RNAs (lncRNAs) are noncoding transcripts consisting of a diverse class of long RNAs of more than 200 nucleotides in length. Recent studies have shown that lncRNAs are involved in cell signal transduction pathways, cell cycle and cell death regulation, chromatin remodeling, and gene expression regulation at the transcriptional and posttranscriptional levels. They are also involved in the metastatic process of different types of tumors, such as urothelial carcinoma, colon carcinoma, breast carcinoma, lung carcinoma, and hepatocellular carcinoma. In addition, lncRNAs demonstrate precise expression patterns in specific tissues and cells and therefore play important roles in cell differentiation and tissue development. In this chapter, we review the molecular mechanisms of lncRNA cell functions and their involvement in the pathogenesis, progression, and metastasis of osteosarcoma, a rare bone tumor of childhood and adolescence. We also review emerging clinical implications of lncRNA use as potential prognostic biomarkers and therapeutic targets, as well as their putative involvement in drug resistance, in osteosarcoma progression, and in therapeutic interventions.

show abstract

“…It has very important biological functions and is another important area in the bioinformatics field [2], [3]. Studies show that lncRNA is closely correlated with many diseases, such as lung cancer [4], [5], Alzheimer's disease [6], osteosarcoma [7], breast cancer [8], gastric cancer [9], colon cancer [10], prostate cancer [11], cervical cancer [12], etc. At present, more and more researchers are engaged in research in this area, which is an important molecular target in the diagnosis and treatment of disease.…”

Section: Introductionmentioning

confidence: 99%

Logistic Regression Analysis for LncRNA-Disease Association Prediction Based on Random Forest and Clinical Stage Data

Wang

Zhang

2020

IEEE Access

View full text Add to dashboard Cite

An increasing amount of studies have found that LncRNA plays an important role in various life processes of the body. In current prediction research on lncRNA-disease associations, correlation analysis of disease prognosis is overlooked. In this study, a logistic regression prediction model based on tumor clinical stage data and the expression quantity of lncRNA transcript is constructed. The proposed model is based on unknown human lncRNA-disease associations combining with the clinical stage data. Firstly, the importance of the characteristic variable is calculated by the proposed CVS g C-RF algorithm. Secondly, 95 lncRNAs, which are most closely related to prostate cancer, are calculated from 480 alternative lncRNAs by CASO and CVS e-CS-CF. On the basis of the above 95 lncRNAs, the CSPA-PL algorithm is used to select a further 22 lncRNAs that are most closely related to the tumor clinical stage for prostate cancer. Finally, 22 lncRNAs are used to construct a logistic regression prediction model. Additionally, this method is applied to lung cancer data; 16 lncRNAs are selected to construct a logistic regression prediction model for lung cancer. Experimental results show that the best results for ROC Area, the accuracy and recall rate of the prediction model are achieved by the proposed method for prostate cancer and lung cancer, which provides a promising basis for subsequent prediction studies of lncRNA-disease associations. INDEX TERMS LncRNA-disease association, random forest, logistic regression analysis, clinical stage data.

show abstract

Abnormally expressed long non-coding RNAs in prognosis of Osteosarcoma: A systematic review and meta-analysis

Cited by 13 publications

References 43 publications

Long noncoding RNA UCA1 promotes osteosarcoma metastasis through CREB1-mediated epithelial-mesenchymal transition and activating PI3K/AKT/mTOR pathway

Long noncoding RNA UCA1 promotes osteosarcoma metastasis through CREB1-mediated epithelial-mesenchymal transition and activating PI3K/AKT/mTOR pathway

Long Noncoding RNAs in Osteosarcoma: Mechanisms and Potential Clinical Implications

Logistic Regression Analysis for LncRNA-Disease Association Prediction Based on Random Forest and Clinical Stage Data

Contact Info

Product

Resources

About