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Published on: September 8, 2023
Molecular markers to predict response to therapy
Jesus Garcia-Donas1, Cristina Rodriguez-Antona, Eric Jonasch
1Genitourinary Tumors Programme Centro Integral Oncologico Clara Campal CIOCC, Madrid, Spain.
Abstract:
Currently approved treatments for metastatic renal cell carcinoma (RCC) include vascular endothelial growth factor (VEGF)-blocking agents, mammalian target of rapamycin (mTOR) inhibitors, and cytokine therapy. In the near future, we are likely to add immune checkpoint blocking agents to this list. As we develop treatment platforms around each therapeutic class, determining which drug is best for a particular patient becomes increasingly important. At this point, we do not have validated predictive biomarkers for patients with RCC. Here, we discuss the logistical challenges surrounding biomarker development, summarize the current crop of biomarker candidates, and explore potential avenues for the development of more effective predictive tools for patients with advanced RCC.
Insights
Predictive biomarkers are needed for metastatic renal cell carcinoma (RCC) treatments. This review discusses challenges and candidates for developing better biomarkers to personalize advanced RCC therapy.
Area of Science:
- Oncology and Translational Medicine
- Biomarker Discovery and Development
Background:
- Current treatments for metastatic renal cell carcinoma (RCC) include VEGF inhibitors, mTOR inhibitors, and cytokine therapy.
- Immune checkpoint inhibitors are expected to become a significant addition to the therapeutic landscape for advanced RCC.
- Personalized medicine approaches are crucial, but validated predictive biomarkers for patient selection are currently lacking in RCC.
Purpose of the Study:
- To address the urgent need for validated predictive biomarkers in advanced renal cell carcinoma (RCC).
- To discuss the logistical hurdles in developing and implementing predictive biomarkers for RCC treatment selection.
- To review existing biomarker candidates and explore future directions for enhancing predictive tools in advanced RCC.
Main Methods:
- Literature review and synthesis of current research on biomarker development in RCC.
- Analysis of logistical challenges in biomarker assay validation and clinical integration.
- Exploration of emerging biomarker candidates and potential predictive strategies for advanced RCC.
Main Results:
- Significant challenges exist in the development and validation of predictive biomarkers for RCC.
- Several biomarker candidates are under investigation, but none are yet validated for routine clinical use.
- The current therapeutic landscape for RCC is evolving, increasing the demand for personalized treatment selection.
Conclusions:
- Validated predictive biomarkers are essential for optimizing treatment selection in advanced renal cell carcinoma (RCC).
- Overcoming logistical challenges in biomarker development is critical for clinical implementation.
- Further research into novel biomarker candidates and strategies is needed to advance personalized medicine in RCC.
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