Prognostic and Predictive Markers, and Stratifications Tables, for the Detection and Treatment of Renal Cell Carcinoma

  • Helen Davis Bondarenko
  • Raisa S. Pompe
  • Emanuele Zaffuto
  • Shahrokh F. Shariat
  • Pierre I. Karakiewicz
Living reference work entry

Abstract

Despite knowledge of disease stage, grade, and histological subtype (HS), patient outcome in RCC remains elusive. Therefore, a vast number of predictive and prognostic models as well as biological markers have been proposed. Many show promise in stratifying the survival curves or discriminating between stage distributions, while others achieved independent predictor status in specific end points of interest.

There is an increased interest in composite biomarker, such as the BioScore (Parker et al., Cancer 115(10):2092–2103, 2009), which has increased accuracy compared to other models. The search continues for an ideal model that is relevant, simple to use and understand, and that will be able to distinguish between different patient diseases and characteristics. The future in prognostic factors and predictive models lies in finding biomarkers that will assist in choosing select target therapies, immunotherapies, and chemotherapies. To improve patient prognosis, treatment sequences, with targeted agents and novel drugs, need to be individualized by using the patient’s genomic classifications.

Presently, Immune oncology agents (IO), notably immune checkpoint inhibitors targeting PD-1, are the most promising in treatment of RCC. It is postulated that a preestablished immune response can optimize immune checkpoint inhibition therapy. Therefore, even though past studies found few desired results, vaccinations may hold the key to future therapeutic success (Curtis et al., Curr Oncol Rep 18(9):57, 2016; Hammers H, Curr Opin Urol 26(6):543–547, 2016).

This chapter will focus on prognostic models specifically for metastatic RCC and models for all types of RCC. Second, this chapter will focus on molecular biomarkers, including tissue-based biomarkers, blood-based biomarkers, and immune system biomarkers.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Helen Davis Bondarenko
    • 1
  • Raisa S. Pompe
    • 2
  • Emanuele Zaffuto
    • 3
  • Shahrokh F. Shariat
    • 5
  • Pierre I. Karakiewicz
    • 4
  1. 1.Department of UrologyUniversity of Montreal Health CentreMontrealCanada
  2. 2.Martini-Klinik Prostate Cancer CenterUniversity Hospital Hamburg-EppendorfHamburgGermany
  3. 3.Division of Oncology/Unit of UrologyUrological Research Institute, IRCCS Ospedale San RaffaeleMilanItaly
  4. 4.Cancer Prognostics and Health Outcomes UnitUniversity of Montreal Health CenterMontrealCanada
  5. 5.Departement of UrologyWeill Cornell Medical CenterNew YorkUSA

Section editors and affiliations

  • Mario W. Kramer
    • 1
  • Axel S. Merseburger
    • 2
  1. 1.Klinik für UrologieLübeckGermany
  2. 2.Department of UrologyUniversity Hospital Schleswig-HolsteinLübeckGermany

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