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.

Urologic Oncology
|February 6, 2014
PubMed

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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