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Purpose: The intracellular fraction of unbound compound (f u,cell ) is an important parameter for accurate prediction of drug binding to intracellular targets. f u,cell is the result of a passive distribution process of drug molecules partitioning into cellular structures. Initial observations in our laboratory showed an up to 10-fold difference in the f u,cell of a given drug for different cell types. We hypothesized that these differences could be explained by the phospholipid (PL) composition of the cells, since the PL cell membrane is the major sink of unspecific drug binding. Therefore, we determined the f u,cell of 19 drugs in cell types of different origin., Method: The cells were characterized for their total PL content and we used mass spectrometric PL profiling to delineate the impact of each of the four major cellular PL subspecies: phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylserine (PS) and phosphatidylinositol (PI). The cell-based experiments were compared to cell-free experiments that used beads covered by PL bilayers consisting of the most abundant PL subspecies., Results: PC was found to give the largest contribution to the drug binding. Improved correlations between the cell-based and cell-free assays were obtained when affinities to all four major PL subspecies were considered. Together, our data indicate that f u,cell is influenced by PL composition of cells., Conclusion: We conclude that cellular PL composition varies between cell types and that cell-specific mixtures of PLs can replace cellular assays for determination of f u,cell as a rapid, small-scale assay covering a broad dynamic range. Graphical Abstract.

The plasma protein binding capability of drug substances represents an important assay parameter in drug discovery and development. For very strong plasma protein binding molecules, however, the free fraction in plasma f u is very small and therefore difficult to determine with standard methods. To solve this problem, the EScalate equilibrium shift in vitro assay was developed. Escalating concentrations of plasma were found to shift the binding equilibrium in solution between the test item and immobilized human serum albumin. Following liquid chromatography coupled to mass spectrometry analysis of the samples, the test compound's f u in plasma is calculated with a 2-dimensional fitting procedure. Comparability of EScalate assay results was demonstrated for 4 extensively studied small molecule drugs (carbamazepine, desipramine, pyrimethamine, and warfarin) as well as for liraglutide, a fatty acid-conjugated peptide drug with very strong plasma protein binding. The results were in good agreement with published data. A free fraction of 0.51% was determined for liraglutide. Our results confirm the compound's very strong plasma protein binding properties in a novel and robust assay system., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Intracellular unbound drug concentrations are the pharmacologically relevant concentrations for targets inside cells. Intracellular drug concentrations are determined by multiple processes, including the extent of drug binding to intracellular structures. The aim of this study was to evaluate the effect of neutral lipid (NL) and phospholipid (PL) levels on intracellular drug disposition. The NL and/or PL content of 3T3-L1 cells were enhanced, resulting in phenotypes (in terms of morphology and proteome) reminiscent of adipocytes (high NL and PL) or mild phospholipidosis (only high PL). Intracellular bioavailability ( F ic ) was then determined for 23 drugs in these cellular models and in untreated wild-type cells. A higher PL content led to higher intracellular drug binding and a lower F ic . The induction of NL did not further increase drug binding but led to altered F ic due to increased lysosomal pH. Further, there was a good correlation between binding to beads coated with pure PL and intracellular drug binding. In conclusion, our results suggest that PL content is a major determinant of drug binding in cells and that PL beads may constitute a simple alternative to estimating this parameter. Further, the presence of massive amounts of intracellular NLs did not influence drug binding significantly.

Estimating the unbound fraction of drugs in brain has become essential for the evaluation and interpretation of the pharmacokinetics and pharmacodynamics of new central nervous system drug candidates. Dialysis-based methods are considered to be accurate for estimating the fraction unbound in brain; however, these techniques are hampered by a low throughput. In this study, we present a novel, matrix-free, high-throughput method for estimating the unbound fraction, based on a sample pooling approach combining the TRANSIL brain absorption assay with liquid chromatography-mass spectrometry. The base measurement of the TRANSIL approach is the affinity to brain membranes, and this method is used directly to predict the free fraction in brain. The method was evaluated by comparing the free fraction of drugs in brain [f(u,brain) (%)] obtained using the TRANSIL brain absorption assay and equilibrium dialysis methods for a test set of 65 drugs (27 marketed and 38 proprietary drugs). A good correlation (r(2) > 0.93) of f(u,brain) (%) between the TRANSIL brain absorption assay and equilibrium dialysis was observed. Moreover, we compared the lipid composition of rat and porcine brain and analyzed the influence of the brain albumin content on brain tissue binding measurement. The comparison of the lipid composition indicated only minor differences between rat and porcine brain, and albumin appears to have a low impact on brain tissue binding measurements. The TRANSIL brain absorption assay with sample pooling methodology not only significantly reduces the biological matrix required but also increases the throughput, compared with the conventional dialysis methods.

In the brain the expression of transforming growth factor beta1 (TGF-beta1) is involved both in neuroprotective and neurodegenerative processes. Recently, we have established a transgenic mouse model with inducible neuron-specific expression of TGF-beta1 based on the tetracycline-regulated gene expression system. A long-term expression of TGF-beta1 results in persisting perivascular thioflavin-positive depositions, which did not disappear even though the transgene synthesis was repressed completely by administration of doxycycline. Formation and composition of these depositions are hardly elucidated. The aim of this study was to identify TGF-beta1 responding genes potentially participating in forming these depositions. To address this problem we have compared the cortical mRNA expression pattern of TGF-beta1 expressing mice with mice impeded to express the transgenic protein using oligonucleotide microarray analysis. Differential gene expression was further characterized by quantitative real-time reverse transcription-polymerase chain reaction including animals, where the long-lasting TGF-beta1 expression was repressed. While no change of amyloid precursor protein RNA expression level was detected, various genes strongly involved in calcium homeostasis, tissue mineralization or vascular calcification were identified differentially expressed. It is suggested, that these genes might contribute to the perivascular depositions in the TGF-beta1 expressing mice.

Pancreatic ductal adenocarcinoma is the eighth most common cancer with the lowest overall 5-year relative survival rate of any tumor type today. Expression profiling using microarrays has been widely used to identify genes associated with pancreatic cancer development. To extract maximum value from the available gene expression data, we applied a meta-analysis to search for commonly differentially expressed genes in pancreatic ductal adenocarcinoma. We obtained data sets from four different gene expression studies on pancreatic cancer. We selected a consensus set of 2984 genes measured in all four studies and applied a meta-analysis approach to evaluate the combined data. Of the genes identified as differentially expressed, several were validated using RT-PCR and immunohistochemistry. Additionally, we used a class discovery algorithm to identify a gene expression signature. Our meta-analysis revealed that the pancreatic cancer gene expression data sets shared a significant number of up- and downregulated genes, independent of the technology used. This interstudy crossvalidation approach generated a set of 568 genes that were consistently and significantly dysregulated in pancreatic cancer. Of these, 364 (64.1%) were upregulated and 204 (35.9%) were downregulated in pancreatic cancer. Only 127 (22%) were described in the published individual analyses. Functional annotation of the genes revealed that genes presumably associated with the cell adhesion-mediated drug resistance pathway are frequently overexpressed in pancreatic cancer. Meta-analysis is an important tool for the identification and validation of differentially expressed genes. These could represent good candidates for novel diagnostic and therapeutic approaches to pancreatic cancer.

Sepsis is a common and serious health problem whereby improvements in diagnosis are crucial in increasing survival rates. To test whether profiling transcription is applicable to sepsis diagnosis, we analyzed whole blood using a microarray containing probes for 340 genes relevant to inflammation. The patient's gene expression pattern was highly homogenous, resulting in 69% of differentially expressed genes. With a positive predictive value of 98%, a list of 50 differentially expressed genes was compiled, and randomly chosen transcripts were confirmed by PCR. Here, we present the first evidence that microarrays can identify typical gene expression profiles in the blood of patients with severe sepsis. Regardless of the heterogeneity of the patients, we observed a striking correlation between the conventional diagnostic classification and our approach. The unity of responses suggests that the principle of this multiparameter approach can be adapted to early stage sepsis diagnosis.