Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UNIPROT:O76050 (neu)
 3,969 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

While screening for protein kinases expressed in the murine mammary gland, we identified previously a Ca2+/calmodulin-dependent kinase, Pnck, that is most closely related to CaMKI. In this report, we show that Pnck is temporally regulated during murine mammary development with highest levels of expression observed late in pregnancy, concomitant with the decreased cellular proliferation and terminal differentiation of the mammary epithelium. Consistent with this finding, Pnck is up-regulated in confluent mammary epithelial cells and is down-regulated as serum-starved cells are stimulated to reenter the cell cycle. In the mammary gland, Pnck is expressed in an epithelial-specific and markedly heterogeneous manner, suggesting that the expression of this kinase may be restricted to a particular mammary epithelial cell type. Potentially related to its heterogeneous in vivo expression pattern, Pnck expression is oncogene-associated in murine epithelial cell lines derived from mammary tumors arising in different transgenic mouse models of breast cancer; cell lines derived from mammary tumors initiated by c-myc or int-2/Fgf3 express Pnck, whereas cell lines initiated by neu or H-ras do not. In an analogous manner, expression of the human homologue of Pnck is restricted to a subset of human breast cancer cell lines. Moreover, PNCK was found to be highly overexpressed in a subset of human primary human breast cancers compared with benign mammary tissue. Together, our data suggest that Pnck may play a role in mammary development, and that expression of this kinase may be restricted to a mammary epithelial cell type that is transformed in a subset of human breast cancers.
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PMID:The caM kinase, Pnck, is spatially and temporally regulated during murine mammary gland development and may identify an epithelial cell subtype involved in breast cancer. 1103 5

Triple-negative breast cancer (TNBC) is characterized by a deficiency in the estrogen receptor (ER), progesterone receptor (PR) and HER2/neu genes. Patients with TNBC have an increased likelihood of distant recurrence and mortality, compared with patients with other subtypes of breast cancer. The current study aimed to identify novel biomarkers for TNBC. Weighted gene co-expression network analysis (WGCNA) was applied to construct gene co-expression networks; these were used to explore the correlation between mRNA profiles and clinical data, thus identifying the most significant co-expression network associated with the American Joint Committee on Cancer-TNM stage of TNBC. Using RNAseq datasets from The Cancer Genome Atlas, downloaded from the University of California, Santa Cruz, WGCNA identified 23 modules via K-means clustering. The most significant module consisted of 248 genes, on which gene ontology analysis was subsequently performed. Differently Expressed Gene (DEG) analysis was then applied to determine the DEGs between normal and tumor tissues. A total of 42 genes were positioned in the overlap between DEGs and the most significant module. Following survival analysis, 5 genes [GIPC PDZ domain containing family member 1 (GIPC1), hes family bHLH transcription factor 6 (HES6), calmodulin-regulated spectrin-associated protein family member 3 (KIAA1543), myosin light chain kinase 2 (MYLK2) and peter pan homolog (PPAN)] were selected and their association with the American Joint Committee on Cancer-TNM diagnostic stage was investigated. The expression level of these genes in different pathological stages varied, but tended to increase in more advanced pathological stages. The expression of these 5 genes exhibited accurate capacity for the identification of tumor and normal tissues via receiver operating characteristic curve analysis. High expression of GIPC1, HES6, KIAA1543, MYLK2 and PPAN resulted in poor overall survival (OS) in patients with TNBC. In conclusion, via unsupervised clustering methods, a co-expressed gene network with high inter-connectivity was constructed, and 5 genes were identified as biomarkers for TNBC.
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PMID:Prognostic genes of triple-negative breast cancer identified by weighted gene co-expression network analysis. 3189 23