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Renal carcinoma pharmacogenomics and predictors of response: Steps toward treatment individualization
Jesus Garcia-Donas1, Juan Francisco Rodriguez-Moreno2, Nuria Romero-Laorden2
1Genitourinary Tumors Unit Centro Integral Oncologico Clara Campal (CIOCC), Madrid, Spain; Prostate Cancer and Genitourinary Tumors Programme, Spanish National Cancer Research Centre (CNIO), Madrid, Spain.
Abstract:
Molecular knowledge has deeply affected the treatment and outcome of kidney cancer in recent years, and several therapeutic options have become available. However, there are no validated biomarkers to select the best drug for each patient. Already published studies and ongoing investigations could change this scenario in the near future. Regarding antiangiogenic drugs, several works on single nucleotide polymorphisms have achieved promising results, with some SNPs predicting resistance to sunitinib and pazopanib being validated. If more evidence is gained, it could prompt prospective studies exploring a molecularly driven selection of treatment. Another relevant line of investigation for antiangiogenic drugs is the cytokines and antiangiogenic factors. Different studies have found that cytokines and antiangiogenic factors are able to predict the outcome of patients treated with sunitinib, pazopanib, or sorafenib. Issues regarding the thresholds of normality and the best time for assessment are pending, but the communicated results are encouraging. Less evidence is available for mammalian target of rapamycin inhibitors but recent data support a key role of the phosphoinositide 3-kinase/Akt pathway in clear cell renal cell carcinoma and points toward poor response to angiogenic drugs when the pathway is activated. Whether modern phosphoinositide 3-kinase inhibitors could be the best option for these patients is a question that should be addressed. Additionally, a new class of immunomodulators, like anti-programmed death 1 drugs, has demonstrated to achieve long-lasting stabilizations even in some patients with no radiological response or early progression. This is a singular situation where the identification of reliable predictors of efficacy will be key in the development of these drugs in renal cell carcinoma. Finally, germline mutations of the c-Met gene have been proposed as the first predictor of response to targeted therapies in papillary renal cell carcinoma. As a conclusion, translational research will be a cornerstone to move a next step forward in kidney cancer.
Insights
Identifying biomarkers is crucial for selecting the best kidney cancer treatment. Ongoing research into genetic markers, cytokines, and molecular pathways shows promise for personalized antiangiogenic and immunomodulatory therapies.
Area of Science:
- Oncology
- Molecular Biology
- Translational Research
Background:
- Recent advances in molecular knowledge have expanded kidney cancer treatment options.
- Validated biomarkers for selecting optimal therapies are currently lacking.
- Personalized medicine approaches are needed to improve treatment outcomes.
Purpose of the Study:
- To review current research on molecular biomarkers for kidney cancer treatment selection.
- To highlight promising predictive markers for antiangiogenic drugs, mTOR inhibitors, and immunotherapies.
- To emphasize the role of translational research in advancing kidney cancer care.
Main Methods:
- Review of published studies and ongoing investigations on molecular predictors.
- Analysis of genetic polymorphisms (SNPs) associated with drug response.
- Evaluation of cytokines, antiangiogenic factors, and signaling pathways (PI3K/Akt).
- Assessment of immunomodulators (anti-PD-1) and targeted therapies (c-Met inhibitors).
Main Results:
- Single nucleotide polymorphisms (SNPs) show potential in predicting resistance to sunitinib and pazopanib.
- Cytokines and antiangiogenic factors may predict outcomes for patients on sunitinib, pazopanib, or sorafenib.
- The PI3K/Akt pathway activation is linked to poor response to antiangiogenic drugs in clear cell renal cell carcinoma.
- Germline c-Met mutations are potential predictors for targeted therapy in papillary renal cell carcinoma.
- Anti-PD-1 immunotherapies can achieve durable responses, but predictors of efficacy are needed.
Conclusions:
- Translational research is essential for developing molecularly driven treatment selection in kidney cancer.
- Further evidence is required to validate biomarkers and establish clinical utility.
- Future directions include prospective studies for personalized treatment strategies and identifying predictors for immunotherapy response.
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