ArticleMedical science monitor : international medical journal of experimental and clinical research2017
RNA-Sequence Analysis Reveals Differentially Expressed Genes (DEGs) in Patients Exhibiting Different Risks of Tumor Metastasis.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- Microbial metabolite 5-formamidoimidazole-4-carboxamide ribotide targets METTL1 to inhibit m7G modification of BRCA1 mRNA to inhibit high-grade serous ovarian cancer.Molecular medicine (Cambridge, Mass.) · 2025Article
- Identification of genes and pathways associated with menopausal status in breast cancer patients using two algorithms.BMC women's health · 2024Article
- Expression and Prognostic Value of m6A RNA Methylation-Related Genes in Thyroid Cancer.Iranian journal of public health · 2023Article
- Transcriptome Analysis Reveals the Response Mechanism ofInternational journal of molecular sciences · 2022Article
- Down-regulation of microRNA-144-3p and its clinical value in non-small cell lung cancer: a comprehensive analysis based on microarray, miRNA-sequencing, and quantitative real-time PCR data.Respiratory research · 2019Article
- Buyang Huanwu Tang alleviates inflammation and improves motor endplate functions in DSMA rat models by activating several biological molecules and associated signaling pathways.American journal of translational research · 2019Article
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Abstract
BACKGROUND Breast cancer is one of the most common malignancies in women. In a previous study, we found that for two patients who had a high risk of lymphatic metastasis, lymphatic metastasis did not occur; whereas, for two patients who had a low risk of lymphatic metastasis, lymphatic metastasis did occur. MATERIAL AND METHODS We analyzed the differential gene expressions of these four patients by RNA-sequence. The data (HRNM_T versus HRNM_N, LRYM_T versus LRYM_N, and HRNM_T versus LRYM_T) was then processed using differentially expressed genes (DEGs) analysis, functional analysis for DEGs, and PPI network construct. RESULTS For HRNM_T versus HRNM_N, there were 224 DEGs. There were 504 DEGs for LRYM_T versus LRYM_N, and 88 DEGs for LRYM_T versus LRYM_N. For HRNM_T versus HRNM_N, DEGs were up-regulated mainly in the cell cycle, the IL-17 signaling pathway, and the progesterone-mediated oocyte maturation; DEGs were down-regulated mainly in the IL-17 signaling pathway. For LRYM_T versus LRYM_N, DEGs were up-regulated mainly in protein digestion and absorption, and cytokine-cytokine receptor interaction; DEGs were down-regulated mainly in ECM-receptor interaction. For HRNM_T versus LRYM_T, DEGs were up-regulated mainly in the PPAR signaling pathway; DEGs were downregulated mainly in the adipocytokine signaling pathway. The DEGs were screened to construct PPI networks. CONCLUSIONS The GO and KEGG functional enrichments of HRNM_T versus HRNM_N, and LRYM_T versus LRYM_N were consistent with earlier studies. For HRNM_T versus LRYM_T, DEGs were up-regulated mainly in PPAR signaling; DEGs were down-regulated mainly in the adipocytokine pathway.
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