Exploring the key genes and pathways of osteosarcoma with pulmonary metastasis using a gene expression microarray Article Swipe
Zhongju Shi
,
Hengxing Zhou
,
Bin Pan
,
Lu Lu
,
Zhijian Wei
,
Linlin Shi
,
Xue Yao
,
Yi Kang
,
Shiqing Feng
·
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.3892/mmr.2017.7577
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.3892/mmr.2017.7577
Osteosarcoma is a common and highly malignant tumour in children and teenagers that is characterized by drug resistance and high metastatic potential. Patients often develop pulmonary metastasis and have a low survival rate. However, the mechanistic basis for pulmonary metastasis remains unclear. To identify key gene and pathways associated with pulmonary metastasis of osteosarcoma, the authors downloaded the gene expression dataset GSE85537 and obtained the differentially expressed genes (DEGs) by analyzing high‑throughput gene expression in primary tumours and lung metastases. Subsequently, the authors performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses and a protein‑protein interaction (PPI) network was constructed and analyzed by Cytoscape software. In total, 2,493 genes were identified as DEGs. Of these, 485 genes (19.45%) were upregulated, and the remaining 2,008 genes (80.55%) were downregulated. The authors identified the predominant GO categories and KEGG pathways that were significantly over‑represented in the metastatic OS samples compared with the non‑metastatic OS samples. A PPI network was constructed, and the results indicated that ALB, EGFR, INS, IL6, CDH1, FYN, ERBB2, IL8, CXCL12 and RAC2 were the top 10 core genes. The enrichment analyses of the genes involved in the top three significant modules demonstrated that the DEGs were principally related to neuroactive ligand‑receptor interaction, the Rap1 signaling pathway, and protein digestion and absorption. Together, these data elucidated the molecular mechanisms of OS patients with pulmonary metastasis and provide potential therapeutic targets. However, further experimental studies are needed to confirm these results.
Related Topics
Concepts
KEGG
Biology
Gene
CDH1
Metastasis
Cancer research
FYN
Osteosarcoma
Microarray analysis techniques
Gene expression profiling
Gene expression
Signal transduction
Cancer
Computational biology
Genetics
Transcriptome
Cell
Proto-oncogene tyrosine-protein kinase Src
Cadherin
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3892/mmr.2017.7577
- http://www.spandidos-publications.com/10.3892/mmr.2017.7577/download
- OA Status
- bronze
- Cited By
- 35
- References
- 65
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2756839346
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2756839346Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3892/mmr.2017.7577Digital Object Identifier
- Title
-
Exploring the key genes and pathways of osteosarcoma with pulmonary metastasis using a gene expression microarrayWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2017Year of publication
- Publication date
-
2017-05-01Full publication date if available
- Authors
-
Zhongju Shi, Hengxing Zhou, Bin Pan, Lu Lu, Zhijian Wei, Linlin Shi, Xue Yao, Yi Kang, Shiqing FengList of authors in order
- Landing page
-
https://doi.org/10.3892/mmr.2017.7577Publisher landing page
- PDF URL
-
https://www.spandidos-publications.com/10.3892/mmr.2017.7577/downloadDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
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https://www.spandidos-publications.com/10.3892/mmr.2017.7577/downloadDirect OA link when available
- Concepts
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KEGG, Biology, Gene, CDH1, Metastasis, Cancer research, FYN, Osteosarcoma, Microarray analysis techniques, Gene expression profiling, Gene expression, Signal transduction, Cancer, Computational biology, Genetics, Transcriptome, Cell, Proto-oncogene tyrosine-protein kinase Src, CadherinTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
35Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 3, 2023: 4, 2022: 3, 2021: 7Per-year citation counts (last 5 years)
- References (count)
-
65Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.Kyoto | 88 |
| abstract_inverted_index.basis | 36 |
| abstract_inverted_index.genes | 67, 114, 122, 130, 191 |
| abstract_inverted_index.often | 23 |
| abstract_inverted_index.rate. | 32 |
| abstract_inverted_index.these | 220, 245 |
| abstract_inverted_index.three | 196 |
| abstract_inverted_index.(DEGs) | 68 |
| abstract_inverted_index.(KEGG) | 95 |
| abstract_inverted_index.CXCL12 | 177 |
| abstract_inverted_index.ERBB2, | 175 |
| abstract_inverted_index.common | 3 |
| abstract_inverted_index.genes. | 185 |
| abstract_inverted_index.highly | 5 |
| abstract_inverted_index.needed | 242 |
| abstract_inverted_index.these, | 120 |
| abstract_inverted_index.total, | 112 |
| abstract_inverted_index.tumour | 7 |
| abstract_inverted_index.Genomes | 93 |
| abstract_inverted_index.authors | 55, 82, 135 |
| abstract_inverted_index.confirm | 244 |
| abstract_inverted_index.dataset | 60 |
| abstract_inverted_index.develop | 24 |
| abstract_inverted_index.further | 238 |
| abstract_inverted_index.modules | 198 |
| abstract_inverted_index.network | 103, 161 |
| abstract_inverted_index.pathway | 94 |
| abstract_inverted_index.primary | 75 |
| abstract_inverted_index.protein | 215 |
| abstract_inverted_index.provide | 233 |
| abstract_inverted_index.related | 205 |
| abstract_inverted_index.remains | 40 |
| abstract_inverted_index.results | 166 |
| abstract_inverted_index.samples | 152 |
| abstract_inverted_index.studies | 240 |
| abstract_inverted_index.tumours | 76 |
| abstract_inverted_index.(19.45%) | 123 |
| abstract_inverted_index.(80.55%) | 131 |
| abstract_inverted_index.GSE85537 | 61 |
| abstract_inverted_index.However, | 33, 237 |
| abstract_inverted_index.Patients | 22 |
| abstract_inverted_index.analyses | 97, 188 |
| abstract_inverted_index.analyzed | 107 |
| abstract_inverted_index.children | 9 |
| abstract_inverted_index.compared | 153 |
| abstract_inverted_index.identify | 43 |
| abstract_inverted_index.involved | 192 |
| abstract_inverted_index.obtained | 63 |
| abstract_inverted_index.ontology | 85 |
| abstract_inverted_index.pathway, | 213 |
| abstract_inverted_index.pathways | 47, 143 |
| abstract_inverted_index.patients | 228 |
| abstract_inverted_index.results. | 246 |
| abstract_inverted_index.samples. | 158 |
| abstract_inverted_index.survival | 31 |
| abstract_inverted_index.targets. | 236 |
| abstract_inverted_index.unclear. | 41 |
| abstract_inverted_index.Cytoscape | 109 |
| abstract_inverted_index.Together, | 219 |
| abstract_inverted_index.analyzing | 70 |
| abstract_inverted_index.digestion | 216 |
| abstract_inverted_index.expressed | 66 |
| abstract_inverted_index.indicated | 167 |
| abstract_inverted_index.malignant | 6 |
| abstract_inverted_index.molecular | 224 |
| abstract_inverted_index.performed | 83 |
| abstract_inverted_index.potential | 234 |
| abstract_inverted_index.pulmonary | 25, 38, 50, 230 |
| abstract_inverted_index.remaining | 128 |
| abstract_inverted_index.signaling | 212 |
| abstract_inverted_index.software. | 110 |
| abstract_inverted_index.teenagers | 11 |
| abstract_inverted_index.associated | 48 |
| abstract_inverted_index.categories | 140 |
| abstract_inverted_index.downloaded | 56 |
| abstract_inverted_index.elucidated | 222 |
| abstract_inverted_index.enrichment | 96, 187 |
| abstract_inverted_index.expression | 59, 73 |
| abstract_inverted_index.identified | 116, 136 |
| abstract_inverted_index.mechanisms | 225 |
| abstract_inverted_index.metastasis | 26, 39, 51, 231 |
| abstract_inverted_index.metastatic | 20, 150 |
| abstract_inverted_index.potential. | 21 |
| abstract_inverted_index.resistance | 17 |
| abstract_inverted_index.absorption. | 218 |
| abstract_inverted_index.constructed | 105 |
| abstract_inverted_index.interaction | 101 |
| abstract_inverted_index.mechanistic | 35 |
| abstract_inverted_index.metastases. | 79 |
| abstract_inverted_index.neuroactive | 207 |
| abstract_inverted_index.predominant | 138 |
| abstract_inverted_index.principally | 204 |
| abstract_inverted_index.therapeutic | 235 |
| abstract_inverted_index.Encyclopedia | 89 |
| abstract_inverted_index.Osteosarcoma | 0 |
| abstract_inverted_index.constructed, | 163 |
| abstract_inverted_index.demonstrated | 199 |
| abstract_inverted_index.experimental | 239 |
| abstract_inverted_index.interaction, | 209 |
| abstract_inverted_index.significant | 197 |
| abstract_inverted_index.upregulated, | 125 |
| abstract_inverted_index.Subsequently, | 80 |
| abstract_inverted_index.characterized | 14 |
| abstract_inverted_index.osteosarcoma, | 53 |
| abstract_inverted_index.significantly | 146 |
| abstract_inverted_index.differentially | 65 |
| abstract_inverted_index.downregulated. | 133 |
| abstract_inverted_index.non‑metastatic | 156 |
| abstract_inverted_index.high‑throughput | 71 |
| abstract_inverted_index.ligand‑receptor | 208 |
| abstract_inverted_index.protein‑protein | 100 |
| abstract_inverted_index.over‑represented | 147 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 9 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.7799999713897705 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.92942644 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |