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Systemic analysis of the expression and prognostic significance of PAKs in breast cancer.
Dang, Yifang; Guo, Ying; Ma, Xiaoyu; Chao, Xiaoyu; Wang, Fei; Cai, Linghao; Yan, Zhongyi; Xie, Longxiang; Guo, Xiangqian.
Affiliation
  • Dang Y; Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Henan University, Kaifeng 475004, China. Electronic address: dangyif
  • Guo Y; Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Henan University, Kaifeng 475004, China. Electronic address: 1419593
  • Ma X; Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Henan University, Kaifeng 475004, China. Electronic address: 7715827
  • Chao X; Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Henan University, Kaifeng 475004, China. Electronic address: 1511290
  • Wang F; Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Henan University, Kaifeng 475004, China. Electronic address: 1610911
  • Cai L; Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Henan University, Kaifeng 475004, China. Electronic address: lihcais
  • Yan Z; Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Henan University, Kaifeng 475004, China. Electronic address: 1019014
  • Xie L; Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Henan University, Kaifeng 475004, China. Electronic address: xielong
  • Guo X; Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Henan University, Kaifeng 475004, China. Electronic address: xqguo@h
Genomics ; 112(3): 2433-2444, 2020 05.
Article in En | MEDLINE | ID: mdl-31987914
PAKs (p21-activated kinases) are reported to play crucial roles in a variety of cellular processes and participate in the progression of human cancers. However, the expression and prognostic values of PAKs remain poorly explored in breast cancers. In our study, we examined the mRNA and protein expression levels of PAKs and the prognostic value. We also analyzed the interaction network, genetic alteration, and functional enrichment of PAKs. The results showed that the mRNA levels of PAK1, PAK2, PAK4 and PAK6 were significantly up-regulated in breast cancer compared with normal tissues, while the reverse trend for PAK3 and PAK5 was found, furthermore, the proteins expression of PAK1, PAK2 and PAK4 in breast cancer tissues were higher than that in normal breast tissues. Survival analysis revealed breast cancer patients with low mRNA expression of PAK3 and PAK5 showed worse RFS, conversely, elevated PAK4 levels predicted worse RFS. In addition, the breast cancer patients with PAKs genetic alterations correlated with worse OS. These results indicated that PAKs might be promising potential biomarkers for breast cancer.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Breast Neoplasms / P21-Activated Kinases Type of study: Prognostic_studies Limits: Female / Humans Language: En Journal: Genomics Journal subject: GENETICA Year: 2020 Type: Article
Fulltext
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PubMed Links
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Breast Neoplasms / P21-Activated Kinases Type of study: Prognostic_studies Limits: Female / Humans Language: En Journal: Genomics Journal subject: GENETICA Year: 2020 Type: Article