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pmid:35296631

Identification of Key Genes Associated with Brain Metastasis from Breast Cancer: A Bioinformatics Analysis.

Cheng Zeng · Mingxi Lin · Yizi Jin · Jian Zhang

Medical science monitor : international medical journal of experimental and clinical research · 2022 doi:10.12659/MSM.935071

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Identification of Key Genes Associated with Brain Metastasis from Breast Cancer: A Bioinformatics Analysis.
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Cheng Zeng
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Mingxi Lin
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Yizi Jin
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Jian Zhang
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Medical science monitor : international medical journal of experimental and clinical research
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2022
abstract
BACKGROUND As the second most frequent factor of brain metastasis worldwide, breast cancer and its pathogenesis have been researched intensively. Nevertheless, the molecular mechanisms of brain metastasis from breast cancer (BMBC) remain uncertain. The purpose of this study was to explore the key genes concerning the prognosis of BMBC and identify their predictive value. MATERIAL AND METHODS Obtained from the Gene Expression Omnibus (GEO) database, microarray datasets GSE125989, GSE52604, and GSE159956 were used to identify the differentially expressed genes (DEGs) and perform function enrichment analysis. RESULTS Of a total of 240 DEGs, 113 genes were upregulated and 127 genes were downregulated. The protein-protein interaction (PPI) was performed through STRING, and 29 hub genes were screened through Cytoscape. After being examined through the cBioportal online platform and the Oncomine database, 8 key genes were finally obtained, including COL14A1, COL3A1, COL6A3, THY1, MMP14, GAP43, PTPRN, and SNAP25. In the validation dataset GSE46928, COL14A1 was shown to have predictive significance of brain metastasis in breast cancer. CONCLUSIONS The key genes explored in this article could assist in identifying the molecular mechanism of BMBC. Also, COL14A1, COL3A1, COL6A3, THY1, MMP14, GAP43, PTPRN, and SNAP25 might be candidate targets for diagnosis and treatment of BMBC, and COL3A1 might have predictive value.
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After being examined through the cBioportal online platform and the Oncomine database, 8 key genes were finally obtained, including COL14A1, COL3A1, COL6A3, THY1, MMP14, GAP43, PTPRN, and SNAP25.
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Finally, to judge the predictive value of the 8 identified hub genes, we performed survival analysis on the GSE159956 dataset and found that COL3A1 was statistically significant, as shown in Figure 7.
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Nevertheless, the molecular mechanisms of brain metastasis from breast cancer (BMBC) remain uncertain. The purpose of this study was to explore the key genes concerning the prognosis of BMBC and identify their predictive value. MATERIAL AND METHODS Obtained from the Gene Expression Omnibus (GEO) database, microarray datasets GSE125989, GSE52604, and GSE159956 were used to identify the differentially expressed genes (DEGs) and perform function enrichment analysis. RESULTS Of a total of 240 DEGs, 113 genes were upregulated and 127 genes were downregulated. The protein-protein interaction (PPI) was performed through STRING, and 29 hub genes were screened through Cytoscape. After being examined through the cBioportal online platform and the Oncomine database, 8 key genes were finally obtained, including COL14A1, COL3A1, COL6A3, THY1, MMP14, GAP43, PTPRN, and SNAP25. In the validation dataset GSE46928, COL14A1 was shown to have predictive significance of brain metastasis in breast cancer. CONCLUSIONS The key genes explored in this article could assist in identifying the molecular mechanism of BMBC. Also, COL14A1, COL3A1, COL6A3, THY1, MMP14, GAP43, PTPRN, and SNAP25 might be candidate targets for diagnosis and treatment of BMBC, and COL3A1 might have predictive value.", "claims": [{"id": "claim-method", "statement": "The differentially expressed genes (DEGs) between primary breast cancer and BMBC were inspected by the LIMMA package of R in datasets GSE125989 and GSE52604. 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