Molecular Fundamentals of the Revolution in the Treatment of Renal Cell Carcinoma


  • Ece Konaç
  • Sinan Sözen

Received Date: 18.02.2015 Accepted Date: 18.03.2015 Bull Urooncol 2015;14(3):181-187

In multifactorial diseases like cancer, although patients may respond to the initial treatment, they may later develop acquired resistance against the drugs used in the treatment. Particularly the undeniable coexistence of a patient’s genetic resistance and acquired resistance remains an important field for future investigation. Renal cell carcinoma (RCC) which does not present a uniform malignant phenotype indicates high heterogeneity involving various cancer types that arise from the nephron. Another very important feature of RCC is that it is resistant to radiotherapy and/or chemotherapy. RCC can now be recognized on genetic and epigenetic level owing to growing number of molecular biology researches in the context of genomic medicine. Elicitation of the molecular dysregulations which exist in a wide range of disorders from single-nucleotide polymorphisms to major chromosomal defects observed in RCC can only be possible if high-throughput techniques like microarray-based genetic copy number analysis are utilized for genome-wide association studies. Gene expression signatures have also been referred to in identifying unique RCC sub-types, thus shedding light on pathogenesis. Abnormalities on molecular level are on a parallel course with not only the morphological features of the tumor but also its behavior and response to the treatment. Therefore, personalized treatment awareness in RCC is of paramount importance. In this study, in light of the question “Is genomic analysis promising as a first step towards personalized treatment?” we aimed to review potential diagnostic, prognostic and predictive biomarkers associated in recent literature with RCC sub-types as well as the translational research which could have important impacts on the future therapeutic approaches.

Keywords: Renal cell carcinoma, molecular biologic analysis, tailored drug therapy

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