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Identification of two novel lipid metabolism-related long non-coding RNAs (SNHG17 and LINC00837) as potential signatures for osteosarcoma prognosis and precise treatment.

Authors :
Tang, Zhifang
Feng, Hanzhen
Shu, Longjun
Guo, Minzheng
Qi, Baochuang
Pu, Luqiao
Shi, Hongxin
Ren, Junxiao
Li, Chuan
Source :
BMC Medical Genomics. 5/25/2023, Vol. 16 Issue 1, p1-14. 14p.
Publication Year :
2023

Abstract

Objective: Dysregulated lipid metabolism enhances the development and advancement of many cancers, including osteosarcoma (OS); however, the underlying mechanisms are still largely unknown. Therefore, this investigation aimed to elucidate novel potential lipid metabolism-related long non-coding RNAs (lncRNAs) that regulate OS development and provide novel signatures for its prognosis and precise treatment. Materials and methods: The GEO datasets (GSE12865 and GSE16091) were downloaded and analyzed using R software packages. Immunohistochemistry (IHC) was used to evaluate protein levels in OS tissues while real-time qPCR was used to measure lncRNA levels, and MTT assays were used to assess OS cell viability. Results: Two lipid metabolism-associated lncRNAs (LM-lncRNAs), small nucleolar RNA host gene 17 (SNHG17) and LINC00837, were identified as efficient and independent prognostic indicators for OS. In addition, further experiments confirmed that SNHG17 and LINC00837 were significantly elevated in OS tissues and cells than para-cancerous counterparts. Knockdown of SNHG17 and LINC00837 synergistically suppressed the viability of OS cells, whereas overexpression of the two lncRNAs promoted OS cell proliferation. Moreover, bioinformatics analysis was conducted to construct six novel SNHG17-microRNA-mRNA competing endogenous RNA (ceRNA) networks, and three lipid metabolism-associated genes (MIF, VDAC2, and CSNK2A2) were found to be abnormally upregulated in OS tissues, suggesting that they were potential effector genes of SNHG17. Conclusion: In summary, SNHG17 and LINC00837 were found to promote OS cell malignancy, suggesting their use as ideal biomarkers for OS prognosis and treatment. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17558794
Volume :
16
Issue :
1
Database :
Academic Search Index
Journal :
BMC Medical Genomics
Publication Type :
Academic Journal
Accession number :
163913819
Full Text :
https://doi.org/10.1186/s12920-023-01553-4