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. 2017 Nov 6;175(1):29–37. doi: 10.1111/bph.14067

Heterogeneous distribution of alectinib in neuroblastoma xenografts revealed by matrix‐assisted laser desorption ionization mass spectrometry imaging: a pilot study

Shoraku Ryu 1,3, Mitsuhiro Hayashi 1,2, Hiroaki Aikawa 1,2, Isamu Okamoto 4, Yasuhiro Fujiwara 5, Akinobu Hamada 1,2,3,6,✉
PMCID: PMC5740247  PMID: 29027209

Abstract

Background and Purpose

The penetration of the anaplastic lymphoma kinase (ALK) inhibitor alectinib in neuroblastomas and the relationship between alectinib and ALK expression are unknown. The aim of this study was to perform a quantitative investigation of the inter‐ and intra‐tumoural distribution of alectinib in different neuroblastoma xenograft models using matrix‐assisted laser desorption ionization MS imaging (MALDI‐MSI).

Experimental Approach

The distribution of alectinib in NB1 (ALK amplification) and SK‐N‐FI (ALK wild‐type) xenograft tissues was analysed using MALDI‐MSI. The abundance of alectinib in tumours and intra‐tumoural areas was quantified using ion signal intensities from MALDI‐MSI after normalization by correlation with LC‐MS/MS.

Key Results

The distribution of alectinib was heterogeneous in neuroblastomas. The penetration of alectinib was not significantly different between ALK amplification and ALK wide‐type tissues using both LC‐MS/MS concentrations and MSI intensities. Normalization with an internal standard increased the quantitative property of MSI by adjusting for the ion suppression effect. The distribution of alectinib in different intra‐tumoural areas can alternatively be quantified from MS images by correlation with LC‐MS/MS.

Conclusion and Implications

The penetration of alectinib into tumour tissues may not be homogenous or influenced by ALK expression in the early period after single‐dose administration. MALDI‐MSI may prove to be a valuable pharmaceutical method for elucidating the mechanism of action of drugs by clarifying their microscopic distribution in heterogeneous tissues.

Abbreviations

ALK

anaplastic lymphoma kinase

FA

formic acid

ITO

indium titanium oxide

MALDI‐MSI

matrix‐assisted laser desorption ionization MS imaging

ROIs

regions of interest

RTKIs

RTK inhibitors

RTKs

receptor TKs

α‐CHCA

α‐cyano‐4‐hydroxycinnamic acid

Introduction

In recent years, aberrant receptor TKs (RTKs) have been found to play an important role in oncogenesis, and they are considered as promising targets in cancer therapy (Hojjat‐Farsangi, 2014). RTK inhibitors (RTKIs) can selectively interfere with target RTKs, which are assumed to be located in tumour cells; thus, they have the potential to produce fewer adverse effects than cytotoxic chemotherapy (Arora and Scholar, 2005). The expression status of the target receptor may be able to predict the therapeutic response to RTKIs; however, conflicting results have been reported (Juergens et al., 2017). This indicates that there are additional factors affecting the response.

The complete penetration of a drug into tumours is very important to elicit the appropriate drug effect. However, knowledge of drug pharmacokinetics in tumour tissues and the relationship with target receptor expression is limited. PET imaging is a common tool in clinical and transitional research to assess drug uptake in tumours (Weissleder, 2006). EGFR inhibitors can be labelled with 11C or 18F to determine EGFR‐specific accumulation in tumours. Several studies have found that the uptake of EGFR inhibitors is higher in responsive tumours than in non‐responsive tumours and that it may correlate with the presence of the target RTK (Memon et al., 2011; Bahce et al., 2013). However, other studies have reported conflicting results, with no significant differences observed for the accumulation of EGFR inhibitors in various tumour models (Su et al., 2008; Slobbe et al., 2014). This disparity may be due to study differences in design, dosage parameters or tumour model. However, as the analytical method involves tracing the label rather than the drug itself, a common limitation for label‐based analysis, the physio‐chemical properties and metabolic stability of labelled drugs should also be taken into consideration during evaluation.

Therefore, label‐free analytical approaches are desirable in order to provide a more accurate assessment of tumour drug uptake. LC‐MS/MS is a commonly used label‐free method to measure the amount of a drug in tissues (Sharma et al., 2015; Suresh et al., 2017). However, the homogenization of tissues prior to analysis results in the loss of information on drug spatial distribution. In recent decades, MS imaging has become a rising method for tracing the spatial distribution for both parent drugs and metabolites in tissues without the need of labelling (Sugiura and Setou, 2010; Castellino et al., 2011; Cobice et al., 2015; Nilsson et al., 2015). The technology primarily used is matrix‐assisted laser desorption ionization MS imaging (MALDI‐ MSI), which has good sensitivity and can ionize compounds of low molecular weights to large biomolecules such as proteins. Indeed, MALDI‐MS has been used to investigate the localization of small‐molecule drugs at target receptor sites (Sugihara et al., 2014; Torok et al., 2015).

Anaplastic lymphoma kinase (ALK), a member of the insulin receptor superfamily of RTKs, has been demonstrated to be activated in cancers following gene amplification or mutation. The inhibition of ALK may be a potent therapeutic strategy for cancers with ALK alterations (Soda et al., 2007; Webb et al., 2009). Among ALK target small‐molecule RTK inhibitors (RTKIs), alectinib (CH5424802) is a second‐generation highly selective ALK inhibitor that was approved in Japan in 2014. Alectinib binds to the ATP‐binding site of ALK to competitively prevent the binding of ATP and has demonstrated selective anti‐tumour activities in ALK‐positive cancers (Sakamoto et al., 2011; Kodama et al., 2014).

In this study, we evaluated the penetration of alectinib in two different neuroblastoma xenografts, NB1 (ALK amplification) and SK‐N‐FI (ALK wild‐type), using MALDI‐MSI to evaluate the relationship between the distribution and the target receptor. We compared the ion response from MSI between the two different types of tumours and compared it to the amount measured by LC‐MS/MS. From our findings, we propose a method that can estimate the relative abundance of alectinib in tumour regions.

Methods

Animal experiments

Animal studies are reported in compliance with the ARRIVE guidelines (Kilkenny et al., 2010; McGrath and Lilley, 2015). Animal experiments were carried out in full compliance with the Guideline for Animal Experiments (Committee for Animal Experimentation of National Cancer Centre, Japan). All experimental animal protocols were approved by the Institutional Animal Ethics Committee of the National Cancer Centre (Permission Number: T14–024). Animal treatment experiments were performed by a contract research organization (K.A.C, Ltd., Kyoto, Japan).

Briefly, NB1 cells were cultured in RPMI/MEM with 10% FBS at 37°C. SK‐N‐FI cells were cultured in DMEM with 10% FBS at 37°C. Male BALB/c Slc‐nu/nu mice (5 weeks old) (Japan SLC, Inc., Shizuoka, Japan) were housed in specific pathogen‐free conditions. For animal welfare, the minimum number of experimental animals (a total of 10 mice) was used for this experiment to evaluate tissue drug distribution using MALDI‐MSI, with further validation by LC‐MS/MS. The bilateral xenograft model was established by inoculating 1.3 × 107 NB1 cells into the right flank and 2 × 107 SK‐N‐FI cells into the left flank s.c. in each mouse. Alectinib administration started at 2 weeks after cell inoculation. Alectinib was administered p.o. at doses of 4 and 20 mg·kg−1 respectively. At 0.5, 1, 1.5, 2, and 4 h after alectinib administration, mice were killed under anaesthesia with pentobarbital (Kyoritsu Seiyaku Corporation, Tokyo, Japan). Tumour tissues were dissected and rapidly placed in liquid nitrogen. Tumour tissues were stored at −80°C until analysis.

Sample preparation

Snap‐frozen tumour tissues were sectioned into four consecutive sections at 8 μm thickness. Haematoxylin and eosin (H&E) staining was performed for the first slice. The second and fourth slices were homogenized in 150 μL methanol, followed by 150 μL H2O in order to precipitate protein and extract alectinib. The third slice was mounted on an indium titanium oxide (ITO)‐coated glass slide (SI0100N, Mastunami Glass Ind., Ltd., Tokyo, Japan) for MALDI‐MSI analysis.

Mass spectrometry imaging

Tissue slices mounted on ITO glass slides were coated with matrix using a two‐step matrix application technique (Sugiura et al., 2006; Shimma et al., 2013). First, α‐cyano‐4‐hydroxycinnamic acid (α‐CHCA) was applied to the tissue surface at 250°C for 8 min using a sublimation apparatus (SVC‐700TMSG/7PS80, Sanyu electron, Tokyo, Japan). Matrix solution containing 10 mg·mL−1 α‐CHCA in 30% acetonitrile, 10% isopropanol and 0.1% formic acid (FA) was then sprayed stepwise to the sections using a sprayer (PS270, GSI Creos Corp., Tokyo, Japan). D8‐alectinib was added to the matrix solution to a final concentration of 10 μg·mL−1.

MALDI‐MSI analysis was performed in positive mode using iMScope (Shimadzu, Kyoto, Japan). Standard compounds of alectinib and D8‐alectinib were used to confirm the fragmentation and optimize the parameters for MS/MS measurement in MSI analysis. The mass spectrum was obtained over a 50–500 Da mass range at a resolution of 10 000 at m/z 1000. The raster size was set as 60 μm with 50 laser shots three times for each spot. Laser power (Nd:YAG, WL: 355 nm) was optimized at 40 for alectinib and 45 for D8‐alectinib. The isolation width for the precursor ion was set at ±1.5 Da. The MS/MS transitions for alectinib and D8‐alectinib were m/z 483.13 → 396.21 with collision energy at 50 V and m/z 491.31 → 396.21 with collision energy at 47 V respectively.

After analysis, imaging data were converted to imzML format using imaging MS solution ver.1.20 (Shimadzu, Japan) and then processed by Biomap software (Novartis, Basel, Switzerland). Images were constructed with the signal at m/z 396.21 ± 0.05 Da. Normalization was performed by dividing images of alectinib to D8‐alectinib as we have described previously (Aikawa et al., 2016). Ion data before and after normalization were extracted using a Biomap.

LC‐MS/MS analysis

Alectinib was measured using a Nexera X2 HPLC (Shimadzu, Co., Kyoto, Japan). An Xbridge C18 HPLC column (2.1 × 5.0 mm, 3.5 μm, Waters) was used for the separation of alectinib, and the column temperature was set at 40°C. Mobile phases A and B were 0.1% FA/ H2O and 0.1% FA/methanol respectively. Separation was performed using 50% B isocratic elution at a flow rate of 0.2 mL·min−1.

The selected reaction monitoring transition was m/z 483.2 → 396.0 for alectinib using a QTRAP4500 mass spectrometer (AB SCIEX, Framingham, MA, USA) with electrospray ionization in positive mode. The parameters were as follows: ion source temperature, 700°C; curtain gas, 30; nebulising gas (GS1), 60; turbo‐ionspray gas (GS2), 60; ionspray voltage, 4500 V; declustering potential, 121 V; collision energy, 35 V. Data were analysed using Analyst version 1.6.1 software (AB SCIEX).

The standard addition method was used to quantify the results to compensate for the matrix effect (Stuber and Reemtsma, 2004). The amount of alectinib in each tumour section was calculated by averaging the results from two serial sections.

Immunohistochemistry

Tumour sections were fixed in cold acetone at –30°C for 10 min and dried at room temperature. Sections were incubated with rabbit anti‐mouse ALK (D5F3) mAb (# 3633, Cell Signalling Technology, Tokyo, Japan) at a 1:500 dilution overnight at 4°C and washed with 1× TBS buffer. Signal Stain Boost IHC Detection Reagent (anti‐rabbit, Cell Signalling Technology, Tokyo, Japan) was added, and sections were incubated at room temperature for 30 min. After being reacted with 3,3′‐diaminobenzidine, sections were counterstained with haematoxylin. A BZ‐X710 microscope (Keyence, Itasca, IL, USA) was used for the observation and calculation of section areas.

Statistical analysis

Differences in ion intensities and the amounts of alectinib measured between NB1 and SK‐N‐FI inoculated bilaterally in the same mouse were analysed by paired t‐tests using JMP software ver. 13 (SAS Institute Japan, Tokyo, Japan). Differences were considered statistically significant when the P value <0.05. The data and statistical analysis comply with the recommendations on experimental design and analysis in pharmacology (Curtis et al., 2015).

Materials

Alectinib (Alecensa® tablet) was purchased from Chugai Pharmaceutical Co., Ltd. (Tokyo, Japan). D8‐alectinib was provided by Chugai Pharmaceutical Co., Ltd. (Tokyo, Japan). α‐CHCA was purchased from Sigma‐Aldrich (St. Louis, MO, USA). Formic acid (FA), acetonitrile, methanol, Mayer's haematoxylin solution and 1% eosin Y solution for H&E staining were purchased from Wako Pure Chemical Industries Ltd. (Osaka, Japan).

Nomenclature of targets and ligands

Key protein targets and ligands in this article are hyperlinked to corresponding entries in http://www.guidetopharmacology.org, the common portal for data from the IUPHAR/BPS Guide to PHARMACOLOGY (Southan et al., 2016), and are permanently archived in the Concise Guide to PHARMACOLOGY 2017/18 (Alexander et al., 2017).

Results

Identification of alectinib precursor and fragmentation ions by MALDI‐MSI

The precursor, fragment ion and mass spectra of alectinib and D8‐alectinib were confirmed from the tissue and shown in Supporting Information Figure S1. The monoisotopic mass of alectinib was detected at m/z 483.13. Fragmentation resulted in a fragment ion at m/z 396.21, which was reported in our previous study (Aikawa et al., 2016). For D8‐alectinib, the monoisotopic mass was at m/z 491.31, and the fragment ion was detected at m/z 396.21, which corresponds to the loss of a morpholine moiety similar to alectinib.

Alectinib distribution in neuroblastoma xenografts visualized by MALDI‐MSI

The distribution of alectinib at different time points was analysed in the NB1 and SK‐N‐FI bilateral xenograft models (Figure 1 and Supporting Information Figure S2). The MS images of D8‐alectinib showed that the ion suppression effects are heterogeneous in different regions within the same tissue section. The distribution of alectinib in tissues was different than that of D8‐alectinib, indicating that the heterogeneous distribution of alectinib is real and not a reflection of uneven ion suppression effects within tumour tissue sections. The normalized images were presented by dividing the signal intensity of alectinib by D8‐alectinib per pixel and confirmed the heterogeneous distribution of alectinib in tumour tissues.

Figure 1.

Figure 1

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Distribution of alectinib visualized from MS images of alectinib (m/z 396.21 ± 0.05), D8‐alectinib (m/z 396.21 ± 0.05) and alectinib normalized by D8‐alectinib at each time point after the administration of alectinib at 20 mg·kg−1 in (A) NB1 and (B) SK‐N‐FI tumour tissues.

MS images also showed a similar penetration in NB1 and SK‐N‐FI tumours. Expression of ALK was confirmed through immunohistochemical staining with the rabbit anti‐mouse ALK antibody (Supporting Information Figure S3). NB1 tumours showed a strong ALK‐positive stain, while SK‐N‐FI tumours were ALK‐negative.

Comparing the abundance of alectinib in NB1 and SK‐N‐FI tumours

The average intensity per pixel, average intensity·mm−2, total intensity and maximum intensity of each MSI image were sorted using Biomap software (Novartis, Basel, Switzerland). The raw data in imzML format were imported to Biomap software, and images of alectinib and D8‐alectinib in tissue were constructed with the corresponding m/z values. We defined a rectangular region of interest (ROI) including the whole region. Then, by running the ROI statistics analysis, the detailed information on the pixel numbers (total and positive pixels) and intensities (mean, min, max, standard deviation, etc.) from the defined ROI can be obtained. The software added no unit to the intensity, and thus, we considered it to be arbitrary unit. The ion intensity data before and after normalization are summarized in Supporting Information Table S1. The average intensity of alectinib per mm2 between NB1 and SK‐N‐FI tissues after normalization was compared using paired t‐test (P = 0.5716) (Figure 2A). The mean amounts of alectinib (pg·mm−3) analysed by LC‐MS/MS in tumour section homogenates of NB1 and SK‐N‐FI were also compared (P = 0.5554) (Figure 2B). There were no significant differences in the amount of alectinib between NB1 tumours and SK‐N‐FI tumours using either method. These results indicate that the expression of ALK mutations does not affect the accumulation of alectinib in tumours during the early period (~4 h) after single‐dose administration.

Figure 2.

Figure 2

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Comparison of the amount of alectinib in paired NB1 and SK‐N‐FI tumour tissues from MS images and LC‐MS/MS. No significant difference was observed by the comparison (by the paired t‐test) of (A) the average intensity of alectinib·mm−2 by MALDI‐MSI and (B) the mean amount of alectinib·mm−3 in NB1 and SK‐N‐FI tumour tissues by LC‐MS/MS in the same mouse.

Evaluating ion signal intensities from MALDI‐MSI using LC‐MS/MS

The ion signal intensities of alectinib were plotted against amounts in section homogenates measured by LC‐MS/MS, and the correlations between them were evaluated. Before normalization with the internal standard, there was a linear relationship, but a relatively low correlation (R 2 = 0.5964), between the average ion signal intensities·mm−2 and the mean amount of alectinib (pg·mm−3) in tumour tissues (Figure 3A). After normalization by dividing with the internal standard, linearity improved and the coefficient of correlation increased to 0.833 (Figure 3B). Similar results were observed by plotting total signal intensities against concentrations per slice (pg·slice−1) (Supporting Information Figure S4). These results provide good evidence that adjustment using IS can be helpful for quantification by MSI.

Figure 3.

Figure 3

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Calibration curve plotted from average ion signal intensities·mm−2 against alectinib amount in pg·mm−3 measured by LC‐MS/MS. (A) Before normalization by IS and (B) after normalization by IS. Data were processed by use of a Biomap.

Since good linearity was obtained, it was possible for us to estimate the relative abundance of alectinib directly from MS images after normalization. We found a heterogeneous distribution of alectinib even within the same section. We circled some ROIs from different parts in NB1 and SK‐N‐FI tissue sections and integrated the ion signal intensities from each ROI. Triplicate analyses were conducted for each ROI to show the variations in image analysis (Figure 4 and Supporting Information Table S2). The amount of alectinib (pg·mm−3) was reverse calculated using the calibration curve demonstrated above. The average amount of alectinib in ROI1 in SK‐N‐FI tumour sections was near the level of ROI1 and ROI2 in NB1 tumour sections; however, ROI2 in SK‐N‐FI had a relatively low accumulation of alectinib. Using H&E staining, we were able to see that ROI1 and ROI2 in NB1 tumours have similar histopathological images. Interestingly, ROI1 and ROI2 in SK‐N‐FI tumours also showed similar histopathological characteristics where both were composed of tumour cells, stroma and necrotic areas. These results indicate that prior to tumour cell characteristics, additional factors such as the surrounding vascular system involving blood supply and the extracellular matrix structures involved in interstitial pressure may affect the penetration of alectinib in tumours.

Figure 4.

Figure 4

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Quantification of alectinib in tissue ROIs. MS images of (A) NB1 and (B) SK‐N‐FI tissue sections with the corresponding circled ROI1 (R1) and ROI2 (R2) being highlighted in red. H&E staining and enlarged images of R1 and R2 of (C) NB1 tumour section (after 1.5 h dosed at 20 mg·kg−1) and (D) SK‐N‐FI tumour section (after 1.5 h dosed at 20 mg·kg−1). (E) Average intensities·mm−2 and reverse calculated alectinib amount (pg·mm−3) in each ROI by triplicate analyses. Error bar: SD of triplicate analyses for each ROI.

Discussion

Understanding drug delivery in tumours is crucial for understanding the proof of mechanism in drug development. RTKIs are promising anti‐tumour agents that selectively target receptors in tumours, with high specificity and low side effects. However, the uptake of RTKIs in tumours and the relationship to target receptor expression are difficult to elucidate using label‐based methods (Su et al., 2008; Memon et al., 2011; Bahce et al., 2013; Slobbe et al., 2014).

MALDI‐MSI is a robust label‐free method used as a tool to visualize drugs in tumours without labelling. There have been some attempts to evaluate drug distribution in tumours for RTKIs using this method (Castellino et al., 2011). However, reports on the relationship between RTKI distribution and target receptor status in tumours using MALDI‐MSI remain limited (Sugihara et al., 2014; Torok et al., 2015). In this study, we analysed the penetration of alectinib, a small‐molecule ALK‐specific inhibitor, in two neuroblastoma xenografts [ALK genetic amplification (NB1) and ALK wild‐type (SK‐N‐FI)] using MALDI‐MSI. NB1 has been shown to be sensitive to alectinib both in vitro and in vivo, but SK‐N‐FI is not (Sakamoto et al., 2011; Kodama et al., 2010). Both the ion responses from MSI and the amounts of alectinib measured from LC/MS/MS were compared in our study. No difference was observed in alectinib abundances between the two tumours within 4 h after administration at two dosages (4 and 20 mg·kg−1). Positive ALK expression in NB1 tumours and negative ALK expression in SK‐N‐FI tumours were confirmed using immunohistochemistry. Our results indicate that the penetration of alectinib into tumours in vivo is not driven by target ALK expression levels, at least in the early period after a single‐dose administration. Additional factors, such as dysfunctional vasculatures and irregular stroma distribution may influence the delivery of alectinib in tumours. However, it should be noted that since alectinib is a reversible inhibitor binding to the ALK kinase domain through hydrogen bonds, drug accumulation may be different after multiple‐dose administration, which needs further investigation.

In our present study, significant heterogeneity in alectinib distribution was observed in both tumour types. To verify the heterogeneity, a deuterated alectinib (D8‐alectinib) was added to the matrix solution and visualized concurrently. The distribution of D8‐alectinib was also heterogeneous but clearly different in tumours than that of alectinib. These findings confirmed that the heterogeneity is not a reflection of an irregular ion suppression effect derived from tissue endogenous components or the matrix preparation.

Adding a deuterated analyte into the matrix solution as an internal standard is also a solution occasionally used to correct for the ion suppression effect from a quantitative point of view (Sleno et al., 2006). The ion signal intensity in MALDI‐MSI is considered to be proportional to the relative abundance of a molecule. However, the most critical factor influencing tissue ion response is ion suppression effect. The endogenous components in a tissue sample, particularly the lipid and salts, can interfere with the ionization of analytes. This is known as the ion suppression effect, which is one form of matrix effect almost inherent to MS analysis. Since MALDI‐MSI for pharmacokinetics analyses the tissue section directly without removing endogenous matrics in tissue, the analysis can be more susceptible to the ion suppression effect. In addition, since the presence of endogenous components is heterogeneous across tissues, the ion suppression effect would occur and interfere with the ionization of analytes heterogeneously. Spotting serial dilutions of drug standards on control tissues, along with analysing dosed tissues, is another common approach used to compensate for ion suppression (Nilsson et al., 2010; Torok et al., 2015). However, this approach cannot reflect different ion suppressions across a heterogeneous tissue, and the choosing of control tissue should also be considered. Therefore, in this study, we applied isotopic alectinib into the matrix solution as an internal standard. We then sorted out the ion signal intensities of alectinib from tumours before and after normalization with IS and evaluated the quantitative properties of the intensity data by comparing the results of LC‐MS/MS concurrently. Although the ion intensities of drugs and endogenous components from tissues have been related to LC‐MS/MS in previous reports (Reyzer et al., 2003; Burnum et al., 2009; Hankin and Murphy, 2010; Koeniger et al., 2011), comparison of ion intensity data from anti‐cancer drugs using whole tumour slices before and after normalization with IS has not previously been attempted (Giordano et al., 2016).

As shown in the results, ion signal intensities after normalization with D8‐alectinib showed an improved correlation (R 2 = 0.833) to the measured amounts of alectinib in serial sections by LC‐MS/MS. There is still room for improvement in the correlation, given that there was only one animal for each group and the manual spraying method was partly used. Our results provide good evidence that adjustment by adding an internal standard is helpful in compensating for heterogeneous ion suppression effects and is appropriate for relative quantification when using MALDI‐MSI.

To quantify drugs in different tissue areas, laser microdissections followed by LC‐MS/MS analysis are generally performed. It is usually used to validate the heterogeneous penetration of drugs in tissues since LC‐MS/MS is a sensitive and specific method for drug quantification (Goodwin et al., 2010; Aikawa et al., 2016). However, it represents a time‐consuming process where target regions are isolated from tissue slices under microscopy and one needs to consider the lowest limit of quantification. In this study, we quantified alectinib in different areas of tumours based on ion intensity data in ROIs, as ion intensities after IS normalization have a good correlation with the drug amount in tissue. Thus, it is possible to evaluate the relative abundance of alectinib in various regions of a tumour without laborious laser microdissection. Our results showed that alectinib accumulates differently in different regions of the tumour. We speculated that the heterogeneous distribution may be due to heterogeneous histopathological constituents and related the ROIs to H&E images. However, unexpectedly, there was no apparent difference in tissue constituents between ROIs. Our results suggested that, prior to tissue compositions, other surrounding factors such as vascular factors involving blood flow or stroma structures involved in interstitial pressure may influence the delivery of alectinib in tumours during the early stage after administration. The direct relationship between drug exposure in regions to histological images (e.g. H&E, IHC) may provide insights into drug delivery, which may lead to a greater understanding of impaired therapeutic effects.

In conclusion, our study evaluated the distribution of alectinib in tumour tissues with different ALK expression status using MALDI‐MSI. Our results demonstrate that the distribution of alectinib is heterogeneous even in xenografted tumours, indicating that the distribution of drugs in patient tumours is more complex than previously thought. It could be useful to evaluate the drug exposure at tumour sites when estimating anti‐tumour activity in early clinical trials and clinical practice because the regions with no or rare drug penetration may relate to the failure or resistance of the therapy. Clinical tissue samples are generally limited; therefore, MSI can be suitable for therapeutic drug monitoring to evaluate drug distribution based on the histology without the need for laser microdissection. Further pharmacological examinations in preclinical and clinical stages using MALDI‐MSI are required. There was no correlation between ALK expression levels and alectinib penetration in tumours in the early period after single‐dose administration. We also confirmed the quantitative property of ion responses from tumour sections by comparing results with those of LC‐MS/MS, with normalization to an internal standard. The relative quantification of alectinib in different areas of tumour sections was estimated based on ion signal intensities in ROIs, suggesting a possibility for the direct comparison of intra‐ and inter‐tumours quantitatively without laser microdissections. MALDI‐MSI may prove to be a very useful, convenient and promising tool in elucidating the proof of mechanism by clarifying the accumulation of drugs in tumours visually and quantitatively and should contribute to drug development in the near future.

Author contributions

S.R. performed tissue sectioning, staining, LC‐MS/MS and MALDI‐MSI data acquisition, data analysis and wrote the manuscript. M.H. performed the analysis and interpretation of data and wrote and revised the manuscript. H.A. designed the animal experiments. A.H., I.O. and Y.F. supervised the study and revised the manuscript.

Conflict of interest

A.H. received a grant from Shimadzu Corporation, Daiichi Sankyo Company, Chugai Pharmaceutical and AstraZeneca. Other authors declare no conflicts of interest.

Declaration of transparency and scientific rigour

This Declaration acknowledges that this paper adheres to the principles for transparent reporting and scientific rigour of preclinical research recommended by funding agencies, publishers and other organisations engaged with supporting research.

Supporting information

Figure S1 Precursor, fragment ion and MS/MS spectra of (A) alectinib at m/z 483.13 → m/z 396.21 and (B) D8‐ alectinib at m/z 491.31 → 396.21 confirmed from the tissue. Y axis: Average intensity (arbitrary unit).

Figure S2 MSI images of alectinib (m/z 396.21 ± 0.05), D8‐alectinib (m/z 396.21 ± 0.05) and alectinib normalized by D8‐alectinib at each time point after administration of alectinib at 4 mg·kg−1.

Figure S3 Expression of anaplastic lymphoma kinase (ALK) were confirmed through immunohistochemicalstaining with rabbit anti‐mouse ALK antibody. (A) NB1 tumour (after 2 hdosed at 20 mg·kg−1) with ALK amplification was ALK‐positive, and (B) SK‐N‐FItumor (after 2 h dosed at 20 mg·kg−1) which is a ALK wide type was ALK‐negative.

Figure S4 Calibration curve plotted by total ion signal intensities against concentrations per slice (pg･slice−1) measured by LC–MS/MS analysis. (A) Before normalization by IS, (B) After normalization by IS. Data were processed by Biomap.

Table S1 The intensity data before and after normalization with internal standard. (A) Before normalization; (B) After normalization.

Table S2 The results of ROI analysis by triplicate analyses. (Unit of intensity: arbitrary unit).

Click here for additional data file. (1MB, pdf)

Acknowledgements

We thank N. Ohtsuka, M. Ohuchi and T. Yoshino for their assistance in experiments.

This work was supported in part by the Accelerating Regulatory Science Initiative, Ministry of Health, Labour and Welfare, Japan and the Project for Cancer Research and Therapeutic Evolution (16cm0106223h0001) from the Japan Agency for Medical Research and development, AMED.

Ryu, S. , Hayashi, M. , Aikawa, H. , Okamoto, I. , Fujiwara, Y. , and Hamada, A. (2018) Heterogeneous distribution of alectinib in neuroblastoma xenografts revealed by matrix‐assisted laser desorption ionization mass spectrometry imaging: a pilot study. British Journal of Pharmacology, 175: 29–37. doi: 10.1111/bph.14067.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Figure S1 Precursor, fragment ion and MS/MS spectra of (A) alectinib at m/z 483.13 → m/z 396.21 and (B) D8‐ alectinib at m/z 491.31 → 396.21 confirmed from the tissue. Y axis: Average intensity (arbitrary unit).

Figure S2 MSI images of alectinib (m/z 396.21 ± 0.05), D8‐alectinib (m/z 396.21 ± 0.05) and alectinib normalized by D8‐alectinib at each time point after administration of alectinib at 4 mg·kg−1.

Figure S3 Expression of anaplastic lymphoma kinase (ALK) were confirmed through immunohistochemicalstaining with rabbit anti‐mouse ALK antibody. (A) NB1 tumour (after 2 hdosed at 20 mg·kg−1) with ALK amplification was ALK‐positive, and (B) SK‐N‐FItumor (after 2 h dosed at 20 mg·kg−1) which is a ALK wide type was ALK‐negative.

Figure S4 Calibration curve plotted by total ion signal intensities against concentrations per slice (pg･slice−1) measured by LC–MS/MS analysis. (A) Before normalization by IS, (B) After normalization by IS. Data were processed by Biomap.

Table S1 The intensity data before and after normalization with internal standard. (A) Before normalization; (B) After normalization.

Table S2 The results of ROI analysis by triplicate analyses. (Unit of intensity: arbitrary unit).

Click here for additional data file. (1MB, pdf)

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