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The Use of Reverse Phase Protein Arrays RPPA to Explore Protein Expression Variation within Individual Renal Cell Cancers
Published on: January 22, 2013
Abnormal gene expression profile reveals the common key signatures associated with clear cell renal cell carcinoma: a
H J Zhang1, Z Q Sun1, W Q Qian1
1Department of Urology, Huadong Hospital, Fudan University, Shanghai, China.
Abstract:
The aims of this study were to identify the common gene signatures of clear cell renal cell carcinoma (CCRCC), and to expand the respective protein-protein interaction networks associated with CCRCC regulation. For the latter, we utilized multiple gene expression data sets from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO), with which we could analyze the aberrant gene expression patterns at the transcriptome level that distinguish cancer from normal samples. We obtained the GSE781 and GSE6344 clear cell renal cell carcinoma gene expression datasets from GEO, which contained a total of 37 cancer and 37 normal samples. Subsequent R language analysis allowed identification of the differentially expressed genes. The genes that exhibited significant up or downregulation in cancers were entered into the Database for Annotation, Visualization, and Integrated Discovery to perform analysis of gene functional annotations, resulting in the generation of two protein-protein interaction networks that included the most significantly up or downregulated genes in CCRCC. These allowed us to identify the key factor genes, which could potentially be utilized to separate cancer versus normal samples. The differentially regulated genes are also highly likely to be functionally important regulatory factors in renal cell carcinoma: cell functions showing enrichment of these genes include amine biosynthetic and vitamin metabolic processes, ion binding, extracellular transport function, and regulation of biosynthesis. Together, the results from our study offer further reason to pursue diagnosis and therapy of CCRCC at the molecular level.
Insights
This study identified key gene signatures and protein networks in clear cell renal cell carcinoma (CCRCC). These findings highlight molecular targets for improved diagnosis and therapy of this kidney cancer.
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- Clear cell renal cell carcinoma (CCRCC) is a significant health concern.
- Understanding the molecular underpinnings of CCRCC is crucial for developing targeted therapies.
Purpose of the Study:
- To identify common gene expression signatures in CCRCC.
- To construct protein-protein interaction networks for CCRCC regulation.
- To discover potential molecular markers for distinguishing CCRCC from normal tissues.
Main Methods:
- Utilized gene expression datasets (GSE781, GSE6344) from the NCBI Gene Expression Omnibus (GEO).
- Analyzed transcriptome-level aberrant gene expression patterns using R language.
- Performed functional annotation and generated protein-protein interaction networks via DAVID.
Main Results:
- Identified differentially expressed genes in CCRCC compared to normal samples.
- Constructed two protein-protein interaction networks highlighting key regulatory genes.
- Found enriched gene functions related to biosynthesis, vitamin metabolism, ion binding, and extracellular transport.
Conclusions:
- The identified gene signatures and networks offer insights into CCRCC pathogenesis.
- Key factor genes could serve as biomarkers for CCRCC diagnosis.
- Molecular-level understanding supports the pursuit of novel CCRCC diagnostic and therapeutic strategies.
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