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Osteosarcoma transcriptome data exploration reveals STC2 as a novel risk indicator in disease progression

BACKGROUND: Osteosarcoma has been the most common primary bone malignant tumor in children and adolescents. Despite the considerable improvement in the understanding of genetic events attributing to the rapid development of molecular pathology, the current information is still lacking, partly due to...

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Autores principales: Wang, Ziyue, Zeng, Zixin, Gao, Feng, Gui, Ziwei, Du, Juan, Shen, Ningning, Shang, Yangwei, Yang, Zhiqing, Shang, Lifang, Wei, Rong, Ma, Wenxia, Wang, Chen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9942349/
https://www.ncbi.nlm.nih.gov/pubmed/36803385
http://dx.doi.org/10.1186/s12920-023-01456-4
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author Wang, Ziyue
Zeng, Zixin
Gao, Feng
Gui, Ziwei
Du, Juan
Shen, Ningning
Shang, Yangwei
Yang, Zhiqing
Shang, Lifang
Wei, Rong
Ma, Wenxia
Wang, Chen
author_facet Wang, Ziyue
Zeng, Zixin
Gao, Feng
Gui, Ziwei
Du, Juan
Shen, Ningning
Shang, Yangwei
Yang, Zhiqing
Shang, Lifang
Wei, Rong
Ma, Wenxia
Wang, Chen
author_sort Wang, Ziyue
collection PubMed
description BACKGROUND: Osteosarcoma has been the most common primary bone malignant tumor in children and adolescents. Despite the considerable improvement in the understanding of genetic events attributing to the rapid development of molecular pathology, the current information is still lacking, partly due to the comprehensive and highly heterogeneous nature of osteosarcoma. The study is to identify more potential responsible genes during the development of osteosarcoma, thus identifying promising gene indicators and aiding more precise interpretation of the disease. METHODS: Firstly, from GEO database, osteosarcoma transcriptome microarrays were used to screen the differential expression genes (DEGS) in cancer comparing to normal bone samples, followed by GO/KEGG interpretation, risk score assessment and survival analysis of the genes, for the purpose of selecting a credible key gene. Further, the basic physicochemical properties, predicted cellular location, gene expression in human cancers, the association with clinical pathological features and potential signaling pathways involved in the key gene’s regulation on osteosarcoma development were in succession explored. RESULTS: Based on the selected GEO osteosarcoma expression profiles, we identified the differential expression genes in osteosarcoma versus normal bone samples, and the genes were classified into four groups based on the difference level, further genes interpretation indicated that the high differently level (> 8 fold) genes were mainly located extracellular and related to matrix structural constituent regulation. Meanwhile, module function analysis of the 67 high differential level (> 8 fold) DEGS revealed a 22-gene containing extracellular matrix regulation associated hub gene cluster. Further survival analysis of the 22 genes revealed that STC2 was an independent prognosis indicator in osteosarcoma. Moreover, after validating the differential expression of STC2 in cancer vs. normal tissues using local hospital osteosarcoma samples by IHC and qRT-PCR experiment, the gene’s physicochemical property revealed STC2 as a cellular stable and hydrophilic protein, and the gene’s association with osteosarcoma clinical pathological parameters, expression in pan-cancers and the probable biological functions and signaling pathways it involved were explored. CONCLUSION: Using multiple bioinformatic analysis and local hospital samples validation, we revealed the gain of expression of STC2 in osteosarcoma, which associated statistical significantly with patients survival, and the gene’s clinical features and potential biological functions were also explored. Although the results shall provide inspiring insights into further understanding of the disease, further experiments and detailed rigorous clinical trials are needed to reveal its potential drug-target role in clinical medical use. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-023-01456-4.
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spelling pubmed-99423492023-02-22 Osteosarcoma transcriptome data exploration reveals STC2 as a novel risk indicator in disease progression Wang, Ziyue Zeng, Zixin Gao, Feng Gui, Ziwei Du, Juan Shen, Ningning Shang, Yangwei Yang, Zhiqing Shang, Lifang Wei, Rong Ma, Wenxia Wang, Chen BMC Med Genomics Research BACKGROUND: Osteosarcoma has been the most common primary bone malignant tumor in children and adolescents. Despite the considerable improvement in the understanding of genetic events attributing to the rapid development of molecular pathology, the current information is still lacking, partly due to the comprehensive and highly heterogeneous nature of osteosarcoma. The study is to identify more potential responsible genes during the development of osteosarcoma, thus identifying promising gene indicators and aiding more precise interpretation of the disease. METHODS: Firstly, from GEO database, osteosarcoma transcriptome microarrays were used to screen the differential expression genes (DEGS) in cancer comparing to normal bone samples, followed by GO/KEGG interpretation, risk score assessment and survival analysis of the genes, for the purpose of selecting a credible key gene. Further, the basic physicochemical properties, predicted cellular location, gene expression in human cancers, the association with clinical pathological features and potential signaling pathways involved in the key gene’s regulation on osteosarcoma development were in succession explored. RESULTS: Based on the selected GEO osteosarcoma expression profiles, we identified the differential expression genes in osteosarcoma versus normal bone samples, and the genes were classified into four groups based on the difference level, further genes interpretation indicated that the high differently level (> 8 fold) genes were mainly located extracellular and related to matrix structural constituent regulation. Meanwhile, module function analysis of the 67 high differential level (> 8 fold) DEGS revealed a 22-gene containing extracellular matrix regulation associated hub gene cluster. Further survival analysis of the 22 genes revealed that STC2 was an independent prognosis indicator in osteosarcoma. Moreover, after validating the differential expression of STC2 in cancer vs. normal tissues using local hospital osteosarcoma samples by IHC and qRT-PCR experiment, the gene’s physicochemical property revealed STC2 as a cellular stable and hydrophilic protein, and the gene’s association with osteosarcoma clinical pathological parameters, expression in pan-cancers and the probable biological functions and signaling pathways it involved were explored. CONCLUSION: Using multiple bioinformatic analysis and local hospital samples validation, we revealed the gain of expression of STC2 in osteosarcoma, which associated statistical significantly with patients survival, and the gene’s clinical features and potential biological functions were also explored. Although the results shall provide inspiring insights into further understanding of the disease, further experiments and detailed rigorous clinical trials are needed to reveal its potential drug-target role in clinical medical use. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-023-01456-4. BioMed Central 2023-02-20 /pmc/articles/PMC9942349/ /pubmed/36803385 http://dx.doi.org/10.1186/s12920-023-01456-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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
Wang, Ziyue
Zeng, Zixin
Gao, Feng
Gui, Ziwei
Du, Juan
Shen, Ningning
Shang, Yangwei
Yang, Zhiqing
Shang, Lifang
Wei, Rong
Ma, Wenxia
Wang, Chen
Osteosarcoma transcriptome data exploration reveals STC2 as a novel risk indicator in disease progression
title Osteosarcoma transcriptome data exploration reveals STC2 as a novel risk indicator in disease progression
title_full Osteosarcoma transcriptome data exploration reveals STC2 as a novel risk indicator in disease progression
title_fullStr Osteosarcoma transcriptome data exploration reveals STC2 as a novel risk indicator in disease progression
title_full_unstemmed Osteosarcoma transcriptome data exploration reveals STC2 as a novel risk indicator in disease progression
title_short Osteosarcoma transcriptome data exploration reveals STC2 as a novel risk indicator in disease progression
title_sort osteosarcoma transcriptome data exploration reveals stc2 as a novel risk indicator in disease progression
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9942349/
https://www.ncbi.nlm.nih.gov/pubmed/36803385
http://dx.doi.org/10.1186/s12920-023-01456-4
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