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• W2409025151 abstract "In recent years, genome-wide RNA expression analysis has become a routine tool that offers a great opportunity to study and understand the key role of genes that contribute to carcinogenesis. Various microarray platforms and statistical approaches can be used to identify genes that might serve as prognostic biomarkers and be developed as antitumor therapies in the future. Metastatic renal cell carcinoma (mRCC) is a serious, life-threatening disease, and there are few treatment options for patients. In this study, we performed one-color microarray gene expression (4×44K) analysis of the mRCC cell line Caki-1 and the healthy kidney cell line ASE-5063. A total of 1,921 genes were differentially expressed in the Caki-1 cell line (1,023 upregulated and 898 downregulated). Gene Set Enrichment Analysis (GSEA) and Ingenuity Pathway Analysis (IPA) approaches were used to analyze the differential-expression data. The objective of this research was to identify complex biological changes that occur during metastatic development using Caki-1 as a model mRCC cell line. Our data suggest that there are multiple deregulated pathways associated with metastatic clear cell renal cell carcinoma (mccRCC), including integrin-linked kinase (ILK) signaling, leukocyte extravasation signaling, IGF-I signaling, CXCR4 signaling, and phosphoinositol 3-kinase/AKT/mammalian target of rapamycin signaling. The IPA upstream analysis predicted top transcriptional regulators that are either activated or inhibited, such as estrogen receptors, TP53, KDM5B, SPDEF, and CDKN1A. The GSEA approach was used to further confirm enriched pathway data following IPA." @default.
• W2409025151 created "2016-06-24" @default.
• W2409025151 creator A5027873051 @default.
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• W2409025151 creator A5064559051 @default.
• W2409025151 date "2016-08-01" @default.
• W2409025151 modified "2023-09-25" @default.
• W2409025151 title "Gene set enrichment analysis and ingenuity pathway analysis of metastatic clear cell renal cell carcinoma cell line" @default.
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• W2409025151 doi "https://doi.org/10.1152/ajprenal.00138.2016" @default.
• W2409025151 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/27279483" @default.
• W2409025151 hasPublicationYear "2016" @default.
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