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. 2009 Dec 1;101(11):1876-83.
doi: 10.1038/sj.bjc.6605409. Epub 2009 Nov 10.

Identification of TNF-alpha and MMP-9 as potential baseline predictive serum markers of sunitinib activity in patients with renal cell carcinoma using a human cytokine array

J L Perez-Gracia  1 , C Prior, F Guillén-Grima, V Segura, A Gonzalez, A Panizo, I Melero, E Grande-Pulido, A Gurpide, I Gil-Bazo, A Calvo
Affiliations

Identification of TNF-alpha and MMP-9 as potential baseline predictive serum markers of sunitinib activity in patients with renal cell carcinoma using a human cytokine array

J L Perez-Gracia et al. Br J Cancer. .

Abstract

Background: Several drugs are available to treat metastatic renal-cell carcinoma (MRCC), and predictive markers to identify the most adequate treatment for each patient are needed. Our objective was to identify potential predictive markers of sunitinib activity in MRCC.

Methods: We collected sequential serum samples from 31 patients treated with sunitinib. Sera of six patients with extreme phenotypes of either marked responses or clear progressions were analysed with a Human Cytokine Array which evaluates 174 cytokines before and after treatment. Variations in cytokine signal intensity were compared between both groups and the most relevant cytokines were assessed by ELISA in all the patients.

Results: Twenty-seven of the 174 cytokines varied significantly between both groups. Five of them (TNF-alpha, MMP-9, ICAM-1, BDNF and SDF-1) were assessed by ELISA in 21 evaluable patients. TNF-alpha and MMP-9 baseline levels were significantly increased in non-responders and significantly associated with reduced overall survival and time-to-progression, respectively. The area under the ROC curves for TNF-alpha and MMP-9 as predictive markers of sunitinib activity were 0.83 and 0.77.

Conclusion: Baseline levels of TNF-alpha and MMP-9 warrant further study as predictive markers of sunitinib activity in MRCC. Selection of patients with extreme phenotypes seems a valid method to identify potential predictive factors of response.

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Figures

Figure 1
Figure 1
Cluster analysis of antibody-based cytokine microarray in patients treated with sunitinib. Fold-change between baseline levels and levels at the time of evaluation of response were analysed in three patients with response (left columns) and three patients with progression (right columns). The analysis shows that fold-change levels of 27 cytokines cluster responders from non-responders into two different groups.
Figure 2
Figure 2
Determination by ELISA of serum baseline levels of TNF-α (A) and MMP-9 (B) in MRCC patients treated with sunitinib. Inbox bars show median levels for each cytokine of each group of patients. (TNF-α: 20pg ml−1 for responders, and 103.3 pg ml−1 for non-responders; MMP-9: 3303.9 ng ml−1 for responders, and 4262.4 ng ml−1 for non-responders). A significant increase in non-responders compared with responders is found.
Figure 3
Figure 3
Kaplan–Meier plots of time-to-progression (A) and overall survival (B) in the complete group. Baseline levels of TNF-α above the median are significantly associated (P=0.045) with reduced overall survival (C). MMP-9 levels over the upper tercile are significantly associated (P=0.042) with decreased time-to-progression (D).
Figure 4
Figure 4
Sunitinib modulates serum levels of MMP-9 (A) BDNF (B), and SDF-1 (C). Both MMP-9 and BDNF levels are reduced by sunitinib, whereas treatment increases SDF-1 levels. *P<0.05.
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