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pmid:35686034
Identification and Verification of Key Tumor Genes Associated with Diagnosis and Prognosis of Breast Cancer Based on Bioinformatics Analysis.
Feng Yu · Xian-Jun Pan · Jie Luo
Disease markers · 2022 doi:10.1155/2022/9041466
Paper
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Experiment
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Data
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Analysis
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Execution
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Complete file
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Two mRNA expression data (GSE29431 and GSE42568) were acquired from the GEO database. The determination of differently expressed genes (DEGs) between BC specimens and nontumor specimens was completed via the LIMMA package of R. GO annotation and KEGG pathway enrichment analyses were applied to explore the function of DEGs. Kaplan-Meier methods were used to determine the prognostic value of DEGs in BC using TCGA datasets. The diagnostic value of the survival-related DGEs were confirmed using ROC assays in two GEO datasets. RT-PCR was used to examine the expression of the critical genes in BC cells and normal breast cells. CCK-8 experiments were applied to explore the function of the critical genes in BC cells. In this study, we identified 31 DEGs between BC specimens and nontumor specimens. KEGG analysis revealed 31 DEGs were involved in PPAR signal path, AMPK signal path, glycerolipid metabolism, adipocytokine signaling pathway, phenylalanine metabolism, tyrosine metabolic process, and glycine, serine, and threonine metabolic process. Four DEGs including CRYAB, DEFB132, MAOA, and RBP4 were observed to be associated with clinical outcome of BC patients. Their diagnostic values were also confirmed in both GSE29431 and GSE42568 datasets. In addition, we analyzed TCGA datasets and confirmed that the results were consistent with GEO datasets. Finally, the results of RT-PCR confirmed that the expression of CRYAB and RBP4 was distinctly downregulated in BC cells. CCK-8 analysis revealed that overexpression of CRYAB and RBP4 distinctly suppressed the proliferation of BC cells. Overall, our findings suggested CRYAB and RBP4 as critical genes for the diagnosis and prognosis of BC patients. 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