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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
Emerging molecular classification in renal cell carcinoma: implications for drug development
Kathryn E Hacker1, W Kimryn Rathmell
1Department of Genetics, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, 450 West Drive, CB 7295, Chapel Hill, NC 27599, USA.
Abstract:
In the past decade, progress has been made in the development of targeted therapies for advanced renal cell carcinoma (RCC). However, as multiple therapeutic choices become available to clinicians, we currently lack effective indicators that allow physicians to choose the best treatment option for specific patients. For approved targeted therapies, potential molecules that could indicate drug effectiveness in a specific tumor follow naturally from both the therapeutic mechanism and the previously elucidated tumor biology. However, in advanced RCC, the use of these molecules as biomarkers for treatment selection has shown equivocal results and requires further investigation. In addition to looking at specific molecular targets, subclassification of tumors based on their molecular characteristics may also allow stratification of patients based on therapeutic benefits, providing information for treatment selection. Furthermore, the continued development of such tumor classification schemes will hopefully uncover other molecular targets that warrant development as future RCC therapies. The use of molecular classification of patients' tumors for treatment selection will provide the opportunity to increase the effectiveness of currently available therapies for advanced RCC and to judiciously pursue promising options for future RCC therapies.
Insights
Identifying effective biomarkers is crucial for selecting targeted therapies in advanced renal cell carcinoma (RCC). Molecular subclassification of tumors may improve patient stratification and treatment selection for better outcomes.
Area of Science:
- Oncology
- Molecular Biology
- Translational Medicine
Background:
- Targeted therapies have advanced treatment for advanced renal cell carcinoma (RCC).
- Current challenges include a lack of effective biomarkers to guide personalized treatment selection.
- Existing biomarkers for targeted therapies in advanced RCC have yielded equivocal results, necessitating further research.
Purpose of the Study:
- To address the need for effective indicators in selecting targeted therapies for advanced renal cell carcinoma (RCC).
- To explore molecular subclassification of tumors as a strategy for patient stratification and treatment selection.
- To identify potential new molecular targets for future RCC therapies.
Main Methods:
- Review of current literature on targeted therapies and biomarkers in advanced renal cell carcinoma.
- Analysis of the role of molecular tumor characteristics in predicting therapeutic benefits.
- Exploration of subclassification schemes for patient stratification.
Main Results:
- Biomarkers derived from therapeutic mechanisms and tumor biology show promise but require further investigation in advanced RCC.
- Molecular subclassification of tumors offers a potential strategy for stratifying patients based on expected therapeutic benefits.
- Development of tumor classification schemes may reveal novel molecular targets for future RCC therapies.
Conclusions:
- Molecular classification of tumors is essential for optimizing treatment selection in advanced renal cell carcinoma.
- This approach can enhance the effectiveness of current therapies and guide the development of future treatments.
- Personalized medicine strategies based on molecular profiling are key to improving outcomes for advanced RCC patients.
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