The search for a predictive tissue biomarker for response to colon cancer therapy with bevacizumab
25 November 2016
UAntwerpen - Campus Drie Eiken - Building Q - Promotiezaal - Universiteitsplein 1 - 2610 Antwerp (Wilrijk) (route: UAntwerpen, Campus Drie Eiken
4:00 PM - 6:00 PM
Guido De Meyer
PhD defence Koen Marien - Department Pharmaceutical Sciences
Bevacizumab is the first anti-angiogenic therapy approved for the treatment of metastatic colorectal cancer. However, the cost is high and not all patients are responsive. Therefore, a predictive biomarker is of utmost importance.
In Chapter 1, we reviewed those factors that are candidate protein biomarkers, expressed in tumor tissue and detectable by immunohistochemistry. In Chapter 2 the research questions are described. All materials and methods used during this doctoral research are included in Chapter 3. The pre-analytical phase of samples is discussed in Chapter 4. The duration and environmental temperature of the ischemic period during surgery, fixation and stabilization of a sample can influence the quality of staining of a given marker. We stained samples for different angiogenesis-related markers and measured these with object-based image analysis. The most important result was that CD31 staining can be performed successfully on samples with highly variable pre-analytical conditions. This in contrast to Ki67, NRP1 and phosphorylated v-akt murine thymoma viral oncogene homolog (AKT) which were affected by cold ischemia time (Ki67, phosphorylated AKT) or temperature (Ki67), or stabilization time (NRP1). Another challenge of immunohistochemistry is its quantification, which is discussed in Chapter 5. As angiogenesis is often measured by counting the number of microvessels in regions of tumor tissue, we validated this method. We concluded that it is possible to have an unbiased result by our method. We also compared this manual vessel counting method to an automated object-based image analysis. The results give the impression that automated microvessel density measurement is feasible. Furthermore, we introduce a new dimension to CD31 as a marker in angiogenesis which goes beyond straightforward vessel counting.
This new method can differentiate vessel patterns in different histopathological growth patterns of metastatic colorectal cancer in liver. In Chapter 6 we focused on the immune contexture in different histopathological growth patterns of metastatic colorectal cancer in liver. As histopathological growth patterns respond differentially to anti-angiogenic therapy, we may be the first to associate specific biomarkers with a response to anti-angiogenic treatment. We further discussed the results of these studies in Chapter 7 and make a proposal for a predictive biomarker setup based on these results.