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Predicting efficacy of sunitinib in metastatic renal cell carcinoma

Authors :
Porta, Camillo
Ganini,Carlo
Source :
Current Biomarker Findings.
Publication Year :
2014
Publisher :
Dove Press, 2014.

Abstract

Carlo Ganini,1,* Camillo Porta1,2,* 1Medical Oncology, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Matteo University Hospital Foundation, 2Italian Group of Nephro-Oncology/Gruppo Italiano di Oncologia Nefrologica, Pavia, Italy *Both authors contributed equally to this paper Abstract: Renal cell carcinoma accounts for 3% of all solid neoplasms in adults. Once poorly treated due to its poorly understood pathogenesis, the discovery of the role played by the vascular endothelial growth factor pathway in renal cell carcinoma has led to development of a number of targeted therapies that have impacted on the natural history of the disease. One of the problems related to this apparent abundance of therapies is choice of a drug tailored to the individual patient. Of all the drugs available, sunitinib accounts for more than 50% of first-line therapy. Defining which group of patients will benefit from sunitinib using a predictive biomarker would be of great help for its clinical activity. Local efforts have identified biomarkers that are potentially predictive of the efficacy of sunitinib in patients with metastatic renal cancer, being either clinical (hypertension), cellular (such as circulating endothelial cells, circulating tumoral cells), or molecular (cytokines such as vascular endothelial growth factor, hepatocyte growth factor/scatter factor), but there is a desperate need to increase the numbers of patients in the studies being conducted to provide more valid and reproducible data of use in clinical decision-making regarding therapy. Keywords: kidney cancer, sunitinib, predictive biomarker, target therapy, tyrosine kinase inhibitor

Subjects

Subjects :
Current Biomarker Findings

Details

Language :
English
ISSN :
22302492
Database :
OpenAIRE
Journal :
Current Biomarker Findings
Accession number :
edsair.dovemedicalp..b8e8d958b574d760e50963f195c09e88