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Updated: Jul 17, 2026
The Use of Reverse Phase Protein Arrays (RPPA) to Explore Protein Expression Variation within Individual Renal Cell Cancers
Published on: January 22, 2013
Prediction of in vitro response to interferon-alpha in renal cell carcinoma cell lines
Toru Shimazui1, Yoshihiro Ami, Kazuhiro Yoshikawa
1Department of Urology, Institute of Clinical Medicine, Graduate School of Comprehensive Human Sciences, University of Tsukuba1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan. torushim@md.tsukuba.ac.jp
Abstract:
We analyzed the correlation between interferon-alpha (IFNalpha) response and gene expression profiles to predict IFNalpha sensitivity and identified key molecules regulating the IFNalpha response in renal cell carcinoma (RCC) cell lines. To classify eight RCC cell lines of the SKRC series into three subgroups according to IFNalpha sensitivity, that is, sensitive, resistant and intermediate group, responses to IFNalpha (300-3000 IU/mL) were quantified by WST-1 assay. Microarray, followed by supervised hierarchical clustering analysis, was applied to selected genes according to IFNalpha sensitivity. In order to find alteration of expression profiles induced by IFNalpha, sequential microarray analyses were performed at 3, 6, and 12 h after IFNalpha treatment of RCC cell lines and mRNA expression level was confirmed using quantitative real time polymerase chain reaction. According to the sequential microarray analysis between IFNalpha-sensitive and -resistant line, seven genes were selected as candidates for IFNalpha-sensitivity-related genes in RCC cell lines. Among these seven genes, we further developed a model to predict tumor inhibition with four genes, that is, adipose differentiation-related protein, microphthalmia associated transcription factor, mitochondrial tumor suppressor 1, and troponin T1 using multiple linear regression analysis (coefficient=0.948, P=0.0291) and validated the model using other RCC cell lines including six primary cultured RCC cells. The expression levels of the combined selected genes may provide predictive information on the IFNalpha response in RCC. Furthermore, the IFNalpha response to RCC might be modulated by regulation of the expression level of these molecules.
Insights
Researchers identified key genes that predict interferon-alpha (IFNalpha) sensitivity in renal cell carcinoma (RCC). This discovery offers a new way to predict treatment response and potentially modulate IFNalpha therapy for RCC patients.
Area of Science:
- Oncology
- Molecular Biology
- Genetics
Background:
- Interferon-alpha (IFNalpha) is a therapeutic agent used in renal cell carcinoma (RCC) treatment.
- Predicting patient response to IFNalpha therapy is crucial for effective treatment strategies.
- Understanding the molecular mechanisms underlying IFNalpha response in RCC is essential.
Purpose of the Study:
- To analyze the correlation between IFNalpha response and gene expression profiles in RCC cell lines.
- To identify key molecules that regulate IFNalpha sensitivity and response in RCC.
- To develop a predictive model for IFNalpha sensitivity in RCC.
Main Methods:
- Classification of RCC cell lines into sensitive, resistant, and intermediate groups based on IFNalpha response quantified by WST-1 assay.
- Microarray analysis and supervised hierarchical clustering to identify IFNalpha-sensitivity-related genes.
- Quantitative real-time polymerase chain reaction to confirm mRNA expression levels.
- Development and validation of a predictive model using multiple linear regression analysis.
Main Results:
- Seven candidate genes associated with IFNalpha sensitivity in RCC cell lines were identified.
- A predictive model utilizing four genes (adipose differentiation-related protein, microphthalmia associated transcription factor, mitochondrial tumor suppressor 1, and troponin T1) was developed and validated.
- The model demonstrated a significant correlation (coefficient=0.948, P=0.0291) for predicting tumor inhibition.
Conclusions:
- The expression levels of the selected genes can predict IFNalpha response in RCC.
- IFNalpha response in RCC may be modulated by regulating the expression of these identified molecules.
- This study provides a foundation for personalized IFNalpha therapy in RCC patients.
