Novel Approach of MALDI Drug Imaging, Immunohistochemistry, and Digital Image Analysis for Drug Distribution Studies in Tissues
Author(s) -
Katharina J. Huber,
Annette Feuchtinger,
Daniela Borgmann,
Zhoulei Li,
Michaela Aichler,
Stefanie M. Hauck,
Horst Zitzelsberger,
Markus Schwaiger,
Ulrich Keller,
Axel Walch
Publication year - 2014
Publication title -
analytical chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.117
H-Index - 332
eISSN - 1520-6882
pISSN - 0003-2700
DOI - 10.1021/ac502177y
Subject(s) - sorafenib , immunohistochemistry , drug , distribution (mathematics) , chemistry , pathology , erlotinib , cd31 , mass spectrometry imaging , pharmacokinetics , afatinib , pharmacology , cancer research , cancer , medicine , hepatocellular carcinoma , epidermal growth factor receptor , mass spectrometry , mathematical analysis , mathematics , chromatography
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. To explore distribution of the anticancer 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. The following 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 anticancer 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 coregistered 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, which will provide information for the improvement of drug design, administration formula or treatment schemes.
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