A NOVEL APPROACH OF MALDI DRUG IMAGING, IMMUNOHISTOCHEMISTRY, AND DIGITAL IMAGE ANALYSIS FOR DRUG DISTRIBUTION STUDIES IN TISSUES
Katharina Huber, Annette Feuchtinger, Daniela Martina Borgmann, Zhoulei Li, Michaela Aichler, Stefanie M. Hauck, Horst Zitzelsberger, Markus Schwaiger, Ulrich Keller, and Axel Walch. (28-09-2014).Anal. Chem., Just Accepted Manuscript, 2014, DOI: 10.1021/ac502177y
Research Area C
Drug efficacy strongly depends on the presence of the drug substance at the target site. As vascularization is an important factor for the distribution of drugs in tissues, we analyzed drug distribution as a function of blood vessel localization in tumor tissue. In order to explore distribution of the anti-cancer drugs afatinib, erlotinib, and sorafenib, a combined approach of matrix-assisted laser desorption/ionization (MALDI) drug imaging and immunohistochemical vessel staining was applied and examined by digital image analysis. Two xenograft models were investigated: (1) mice carrying squamous cell carcinoma (FaDu) xenografts (ntumor=13) were treated with afatinib or erlotinib, and (2) sarcoma (A673) xenograft bearing mice (ntumor=8) received sorafenib treatment. MALDI drug imaging revealed a heterogeneous distribution of all anti-cancer drugs. The tumor regions containing high drug levels were associated with a higher degree of vascularization than the regions without drug signals (p<0.05). When correlating the impact of blood vessel size to drug abundance in the sarcoma model, a higher amount of small vessels was detected in the tumor regions with high drug levels compared to the tumor regions with low drug levels (p<0.05). With the analysis of co-registered MALDI imaging and CD31 immunohistochemical data by digital image analysis, we demonstrate for the first time the potential of correlating MALDI drug imaging and immunohistochemistry. Here we describe a specific and precise approach for correlating histological features and pharmacokinetic properties of drugs at microscopic level, that will provide information for the improvement of drug design, administration formula or treatment schemes.