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Hum Pathol. 2012 Jul;43(7):1037-43. doi: 10.1016/j.humpath.2011.08.012. Epub 2011 Dec 26.

Assessment of the prognostic significance of endoglin (CD105) in clear cell renal cell carcinoma using automated image analysis.

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Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada, M5S 1A8.


The behavior of clear cell renal cell carcinoma can be difficult to predict. Angiogenesis has proven to be a useful prognostic indicator in different malignancies. Endoglin (CD105) is a new marker of angiogenesis found to have prognostic utility in various tumors. Here, we provide the first automated digital assessment of intratumoral microvascular density in clear cell renal cell carcinoma using endoglin and CD31 and assess their utility as predictors of clinical outcome. Both endoglin and CD31 expression showed association with advanced tumor stage (P = .025 and P = .011, respectively). There was a significant correlation between CD31 and tumor grade (P = .034). Kaplan-Meier survival curves showed that patients with higher endoglin expression had significantly shorter progression-free survival (P = .010). Patients with higher CD31 expression tended to have a worse prognosis, although this was not statistically significant (P = .082). In univariate analysis using endoglin as a continuous variable, increased endoglin was strongly associated with reduced survival (hazard ratio, 1.74; 95% CI, 1.39-2.18; P = <.001). CD31 also correlated with poor outcomes (hazard ratio, 1.52; 95% CI, 1.24-1.86; P = .001). There was no correlation between CD31 and endoglin expression (r = -0.090, P = .541). Receiver operating characteristic analysis showed the area under the curve to be 0.749 for endoglin and 0.550 for CD31. In conclusion, increased endoglin and CD31 expression are associated with a higher tumor stage and decreased progression-free survival. Our automated approach overcomes many limitations of manual quantification. Advances in digital assessment of immunohistochemical markers can be helpful in standardizing the evaluation of tumor biomarkers.

[Indexed for MEDLINE]

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