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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
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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10210430/ https://www.ncbi.nlm.nih.gov/pubmed/37231440 http://dx.doi.org/10.1186/s12920-023-01553-4 |
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author | Tang, Zhifang Feng, Hanzhen Shu, Longjun Guo, Minzheng Qi, Baochuang Pu, Luqiao Shi, Hongxin Ren, Junxiao Li, Chuan |
author_facet | Tang, Zhifang Feng, Hanzhen Shu, Longjun Guo, Minzheng Qi, Baochuang Pu, Luqiao Shi, Hongxin Ren, Junxiao Li, Chuan |
author_sort | Tang, Zhifang |
collection | PubMed |
description | 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-023-01553-4. |
format | Online Article Text |
id | pubmed-10210430 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-102104302023-05-26 Identification of two novel lipid metabolism-related long non-coding RNAs (SNHG17 and LINC00837) as potential signatures for osteosarcoma prognosis and precise treatment Tang, Zhifang Feng, Hanzhen Shu, Longjun Guo, Minzheng Qi, Baochuang Pu, Luqiao Shi, Hongxin Ren, Junxiao Li, Chuan BMC Med Genomics Research 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-023-01553-4. BioMed Central 2023-05-25 /pmc/articles/PMC10210430/ /pubmed/37231440 http://dx.doi.org/10.1186/s12920-023-01553-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Tang, Zhifang Feng, Hanzhen Shu, Longjun Guo, Minzheng Qi, Baochuang Pu, Luqiao Shi, Hongxin Ren, Junxiao Li, Chuan Identification of two novel lipid metabolism-related long non-coding RNAs (SNHG17 and LINC00837) as potential signatures for osteosarcoma prognosis and precise treatment |
title | Identification of two novel lipid metabolism-related long non-coding RNAs (SNHG17 and LINC00837) as potential signatures for osteosarcoma prognosis and precise treatment |
title_full | Identification of two novel lipid metabolism-related long non-coding RNAs (SNHG17 and LINC00837) as potential signatures for osteosarcoma prognosis and precise treatment |
title_fullStr | Identification of two novel lipid metabolism-related long non-coding RNAs (SNHG17 and LINC00837) as potential signatures for osteosarcoma prognosis and precise treatment |
title_full_unstemmed | Identification of two novel lipid metabolism-related long non-coding RNAs (SNHG17 and LINC00837) as potential signatures for osteosarcoma prognosis and precise treatment |
title_short | Identification of two novel lipid metabolism-related long non-coding RNAs (SNHG17 and LINC00837) as potential signatures for osteosarcoma prognosis and precise treatment |
title_sort | identification of two novel lipid metabolism-related long non-coding rnas (snhg17 and linc00837) as potential signatures for osteosarcoma prognosis and precise treatment |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10210430/ https://www.ncbi.nlm.nih.gov/pubmed/37231440 http://dx.doi.org/10.1186/s12920-023-01553-4 |
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