論文

内容要旨

Single-Cell Screening of Tamoxifen Abundance and Effect Using
Mass Spectrometry and Raman-Spectroscopy（ 質量分析とラマン分光法によるタモキシフェンの量と効果の一細胞スクリーニング ）Analytical chemistry，91(4):2710-2718，2019．

主指導教員：檜山英三（自然科学研究支援開発センター
副指導教員：外丸祐介（自然科学研究支援開発センター
副指導教員：村上義昭（医系科学研究科教授生命科学）
教授生命科学）
准教授

外科学）

Ahmed Ali
（医歯薬保健学研究科医歯薬学専攻）

Cells are known to be inherently heterogeneous. This means that their response to external
stimuli like drugs varies from one cell to another. Despite this fact, current drug discovery
studies are done using ensemble-averaged measurements of cell populations. Thesemeasurements obfuscate any information about potential subpopulations, as well as singlecell variation. This information loss was cited as one of the reasons for the failure of phase
II clinical trials of the drugs. Therefore, it’s essential that cell heterogeneity is accounted forin future drug studies. To achieve this, the plethora of cellular interactions between the celland the drug must be accurately measured on the single-cell level (i.e. Drug-uptake, drugmetabolism, and drug-response).
To achieve this, I developed an integrated Raman spectroscopy and mass spectrometry(MS) platform. By integrating the two approaches into a cohesive platform, untargeted
analysis of the drug response can be done using Raman spectroscopy, with the added
possibility of quantifying the drug-uptake, and metabolism using mass spectrometry for
drug-treated cells that were previously measured by Raman. The possible correlation
between the drug-effect, and the drug or its metabolites’ concentration can also beinvestigated on the single-cell level.
In this study, HepG2 cells were treated with the anti-cancer drug, tamoxifen. Tamoxifen ismetabolized by HepG2 cells into its pharmacologically active metabolite 4-Hydroxytamoxifen (4-HT). It also has a toxic effect on the cell. HepG2 cells were divided into twogroups, treated and untreated cells. Treated cells were incubated with 10µM tamoxifen
dissolved in DMSO for 24 hours, while untreated cells were incubated with a corresponding
volume of DMSO as control. The experiment was repeated for three consecutive days. Inorder to minimize growth phase variations, a pilot study was done to synchronize thegrowth of cell populations across the three experiments.
Cells were cultured in glass-bottom grid dishes, which allowed us to perform Raman
measurements on a given cell while recording its location, followed by sampling the same
cell using a micromanipulator for subsequent MS analysis. Raman measurements wereperformed on individual cells in single-line exposure mode, with 10 seconds exposure time.
In each experiment, treated (80 - 120 cells) and untreated (35- 40 cells) cells were sampled,in total, 295 treated and 115 untreated cells were measured by Raman. Among these cells,
53 cells of similar dimensions were chosen for MS analysis. Hollow platinum coated glasscapillaries with bore-size of 2-4 µm attached to a micromanipulator were used to sample thecells after Raman measurements. Each cell was sampled, then the capillary wasdisconnected from the micro-manipulator, and the organic solvent was added to the otherend of the capillary. Finally, the capillary, along with its contents was attached to the nanospray source of the MS instrument (Thermo’s Q-Exactive) where single-cell MS
measurements were done.
Raman measurements revealed spectral differences between treated and untreated cells
which indicates that there are metabolic changes caused by the drug in the cells, most likeattributed to tamoxifen’s hepatotoxic effect. To know if Raman signature can accurately
predict if a given cell is affected by tamoxifen or not. The data from 2 experiments wereused as a training data set (n = 290 cells) in a PLS-DA model. The predictive ability of thismodel was then tested against the data obtained from the third experiment (n = 120 cells).
Our model was able to correctly classify cells treated with tamoxifen with 100% sensitivity,and 72% specificity. This shows that our experimental platform could accurately predict if
cells are affected by tamoxifen or not, even in new data obtained from separate experiments.
From this PLS-DA model, 13 peaks were isolated by calculating their VIP scores and foundto be significantly different in treated and untreated cells. These peaks are hypothesized tobe directly correlated to the drug-response on the single-cell level, therefore, they can beused as spectral biomarkers for the drug efficacy in future studies.
From the cells measured by Raman, 53 were picked up and measured by single-cell MS (31treated cells, and 22 untreated cells). Our MS method could successfully detect both thedrug, and its metabolite (4-HT) in single-cells treated with the drugs, the drug and its
metabolite peaks were not present in the control cells. The structures of tamoxifen and 4HT were confirmed by MS/MS analysis, therefore, showcasing the ability of our techniqueto monitor the drug and its metabolite on the single-cell level in a highly selective andsensitive manner. Furthermore, single-cell MS analysis revealed strong variation intamoxifen and 4-HT concentrations across single-cells, where they exhibited %RSD of 151%
and 238% respectively. The distribution of tamoxifen metabolism was also studied by
calculating the ratio of metabolized to unmetabolized tamoxifen where it exhibited 222%
RSD in its distribution. This perceived heterogeneity in the drug concentration could beexplained by variations in the drug-uptake, while 4-HT abundance variations could be
explained by variations in the uptake of its parent molecule, tamoxifen, as well as
variations in its metabolism.
In order to explore the potential relationship between the drug or its metabolite
concentration in single-cells and the drug-response, I studied possible correlations between
the Raman peaks obtained from the PLS-DA model which might represent the drug effect,
and the concentration of tamoxifen and 4-HT in single-cells. Among the 13 peaks chosenfrom the PLS-DA model, 6 correlated to either the drug, or its metabolite, or the ratio
between the drug and its metabolite (p < 0.05). Furthermore, the ratios between 20 Raman
peak pairs were found to be correlated with tamoxifen metabolism. These correlated peaks
correspond to fatty acids, lipids, and proteins. This corroborates with recent literature
about tamoxifen and 4-HT role in fatty acid oxidation, lipid metabolism, and membrane
dynamics.
In light of our results, the Raman-MS integration was capable of identifying the response of
single-cells to tamoxifen as well as quantifying the drug and its metabolite in the same cells,
therefore, achieving pharmacodynamics and pharmacokinetics monitoring on the single-celllevel for the first time.