Osteosarcoma transcriptome data exploration reveals STC2 as a novel risk indicator in disease progression
Abstract 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, partl...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-02-01
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| Series: | BMC Medical Genomics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12920-023-01456-4 |
| _version_ | 1797863281346478080 |
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| author | Ziyue Wang Zixin Zeng Feng Gao Ziwei Gui Juan Du Ningning Shen Yangwei Shang Zhiqing Yang Lifang Shang Rong Wei Wenxia Ma Chen Wang |
| author_facet | Ziyue Wang Zixin Zeng Feng Gao Ziwei Gui Juan Du Ningning Shen Yangwei Shang Zhiqing Yang Lifang Shang Rong Wei Wenxia Ma Chen Wang |
| author_sort | Ziyue Wang |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-04-09T22:34:03Z |
| format | Article |
| id | doaj.art-99bd500d9b404467a638466e256e8c11 |
| institution | Directory Open Access Journal |
| issn | 1755-8794 |
| language | English |
| last_indexed | 2024-04-09T22:34:03Z |
| publishDate | 2023-02-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Genomics |
| spelling | doaj.art-99bd500d9b404467a638466e256e8c112023-03-22T12:38:00ZengBMCBMC Medical Genomics1755-87942023-02-0116111710.1186/s12920-023-01456-4Osteosarcoma transcriptome data exploration reveals STC2 as a novel risk indicator in disease progressionZiyue Wang0Zixin Zeng1Feng Gao2Ziwei Gui3Juan Du4Ningning Shen5Yangwei Shang6Zhiqing Yang7Lifang Shang8Rong Wei9Wenxia Ma10Chen Wang11Department of Pathology, Beijing Shijitan Hospital, Capital Medical UniversityBasic Medical school of ShanXi Medical UniversityDepartment of Orthopedics, The Six Clinical Medical School of ShanXi Medical UniversityBasic Medical school of ShanXi Medical UniversityDepartment of Pathology, The Second Hospital of ShanXi Medical UniversityDepartment of Pathology, The Second Hospital of ShanXi Medical UniversityDepartment of Pathology, The Second Hospital of ShanXi Medical UniversityDepartment of Pathology, The Second Hospital of ShanXi Medical UniversityDepartment of Pathology, The Second Hospital of ShanXi Medical UniversityDepartment of Pathology, The Second Hospital of ShanXi Medical UniversityDepartment of Pathology, The Second Hospital of ShanXi Medical UniversityDepartment of Pathology, The Second Hospital of ShanXi Medical UniversityAbstract 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.https://doi.org/10.1186/s12920-023-01456-4OsteosarcomaSTC2 geneBioinformatic analysisRisk indicatorMolecular precise medicine |
| spellingShingle | Ziyue Wang Zixin Zeng Feng Gao Ziwei Gui Juan Du Ningning Shen Yangwei Shang Zhiqing Yang Lifang Shang Rong Wei Wenxia Ma Chen Wang Osteosarcoma transcriptome data exploration reveals STC2 as a novel risk indicator in disease progression BMC Medical Genomics Osteosarcoma STC2 gene Bioinformatic analysis Risk indicator Molecular precise medicine |
| 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 | Osteosarcoma STC2 gene Bioinformatic analysis Risk indicator Molecular precise medicine |
| url | https://doi.org/10.1186/s12920-023-01456-4 |
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