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Modeling Spontaneous Metastatic Renal Cell Carcinoma (mRCC) in Mice Following Nephrectomy
11:27

Modeling Spontaneous Metastatic Renal Cell Carcinoma (mRCC) in Mice Following Nephrectomy

Published on: April 29, 2014

Anti-angiogenic therapy in the treatment of advanced renal cell cancer

Ruth E Board1, Fiona C Thistlethwaite, Robert E Hawkins

  • 1Cancer Research UK Department Medical Oncology, Christie Hospital, Manchester M20 4BX, UK. Ruth.Board@christie-tr.nwest.nhs.uk

Cancer Treatment Reviews
|October 31, 2006
PubMed

Insights

Metastatic renal cell cancer, often resistant to chemotherapy, shows promise with new targeted therapies. These treatments focus on blocking cancer growth factors like vascular endothelial growth factor (VEGF), offering hope for improved patient outcomes.

Area of Science:

  • Oncology
  • Molecular Biology
  • Genetics

Background:

  • Metastatic renal cell cancer (mRCC) presents a significant clinical challenge due to poor prognosis and resistance to conventional chemotherapy.
  • Tumorigenesis in most mRCC cases involves von Hippel-Lindau (VHL) gene inactivation, leading to increased proangiogenic factors such as vascular endothelial growth factor (VEGF).

Purpose of the Study:

  • To review recent clinical trial evidence on novel therapeutic agents targeting VEGF and related pathways in metastatic renal cell cancer.
  • To highlight the revolutionary potential of these targeted therapies in mRCC treatment.

Main Methods:

  • Review of clinical trial data and scientific literature.
  • Analysis of therapeutic strategies targeting the VHL/VEGF pathway in renal cell carcinoma.

Main Results:

  • Targeted therapies inhibiting VEGF and related proangiogenic pathways have demonstrated encouraging clinical results in mRCC.
  • These agents represent a paradigm shift from traditional chemotherapy approaches.

Conclusions:

  • Targeted therapies offer a promising new avenue for treating metastatic renal cell cancer.
  • Further clinical investigation of these agents is crucial for optimizing mRCC management.

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