Visualization of Intratumor Pharmacokinetics of [fam-] Trastuzumab Deruxtecan (DS-8201a) in HER2 Heterogeneous Model Using Phosphor-integrated Dots Imaging Analysis

Remarkable progress in antibody engineering technologies has been made in recent years with regard to anticancer drugs, with the shift from small-molecule cytotoxic drugs to mAb drugs (1, 2). Research and development of antibody drugs such as antibody–drug conjugates (ADC), antibody-radionuclide conjugates, bispecific antibodies, immunoliposomes, and chimeric antigen receptor therapy are progressing at a rapid pace (3). Among these drug types, ADCs are particularly promising. ADCs are immunoconjugates comprised of a mAb tethered to a cytotoxic drug (known as the payload) via a chemical linker. The ADC is designed to deliver the payload selectively to target cancer cells (1–5).

[fam-] Trastuzumab deruxtecan (T-DXd, also known as DS-8201a) is a novel HER2-targeted ADC consisting of a humanized anti-HER2 antibody (trastuzumab), an enzymatically cleavable peptide-based linker, and a potent topoisomerase I inhibitor payload, exatecan derivative (DXd; ref. 6). In 2019, T-DXd was first approved in the United States for the treatment of HER2-positive unresectable or metastatic breast cancer following two more prior anti-HER2-based regimens (7). As of January 2021, it was also approved in Japan and the European Union for the treatment of breast cancer, and approved in Japan and the United States for the treatment of advanced or recurrent gastric cancer. Several clinical trials are underway for the treatment of various HER2-expressing or HER2-mutant solid tumors (8–11), and T-DXd has shown durable antitumor activity. In addition to nausea and myelosuppression, interstitial lung disease was observed in a subgroup of patients. Thus, attention to pulmonary symptoms and careful monitoring are required in patients treated with T-DXd.

The primary mechanism of action of T-DXd reportedly involves HER2-mediated internalization of T-DXd in target tissues followed by the release of DXd via digestion of the peptide linker. DXd induces DNA damage and apoptosis via inhibition of topoisomerase I (6). The primary advantage of T-DXd is that it is effective against tumors expressing low levels of HER2 that are refractory to trastuzumab or conventional trastuzumab-ADC (T-DM1; refs. 12–15). T-DXd has a higher drug-to-antibody ratio than T-DM1 (T-DXd: 7.7 vs. T-DM1: 3.4), and the payload, DXd, is more membrane permeable than Lys-SMCC-DM1 released from T-DM1. Highly membrane-permeable DXd can exert antitumor activity against neighboring cells via the so-called “bystander effect,” whereas Lys-SMCC-DM1, which is not membrane permeable, is rapidly metabolized. Although the bystander effect of T-DXd is understood on a phenomenological basis both in vitro and in vivo, the detailed intratumor pharmacokinetics and distribution of T-DXd remain unclear (13–15).

The most common method employed to assess a drug's pharmacokinetics is to evaluate blood or homogenized tumors using a quantitative approach such as LC/MS-MS. However, the drug concentration in blood does not always correlate with that in the tumor (16, 17). Also, these methods do not account for the heterogeneity of tumor tissues and the tumor microenvironment. A method enabling high spatial resolution analyses is required to evaluate intratumor pharmacokinetics in mouse tumor xenograft models. In this study, we utilized a novel imaging system using fluorescent nanoparticles [phosphor-integrated dots (PID)] as a label for immunostaining to elucidate the pharmacokinetics of T-DXd in tumor tissues. PIDs are homogeneous particles with a luminescent intensity approximately 30,000 times higher than that of conventional fluorescent dyes (18). In PID imaging, target antigens are detected by binding streptavidin-conjugated PIDs to biotin-conjugated antibodies. Although IHC is a qualitative evaluation, PID imaging enables quantitative analyses and comparisons between samples by detecting and counting PIDs using specialized software. PID-imaging analysis has been applied to the detection of biomarkers such as HER2 and programmed death-ligand 1 expressed in tumor tissues (19–21).

In this study, we attempted to selectively visualize the spatial distribution of the anticancer agent T-DXd and to quantify the agent using the PID-imaging system. First, PID imaging of the T-DXd components trastuzumab [molecular weight (MW): 156,000 Da] and DXd (MW: 493.48 Da) was evaluated using serial sections of T-DXd–treated tumors of xenograft models. The PID distribution of trastuzumab and DXd correlated with the HER2 expression level. A detailed comparison between trastuzumab and DXd indicated that the trastuzumab-PID distribution matched almost perfectly with the HER2-positive areas. In contrast, DXd-PID exhibited widespread distribution in the surrounding HER2-negative areas via the so-called “bystander effect.” This DXd was thought to be free DXd cleaved from T-DXd in the tumor cells. In this study, we successfully visualized the intratumor distribution and mechanism of action of T-DXd while maintaining tumor heterogeneity and the tumor microenvironment. PID imaging is a simple method that can be widely applied to the study of antibody drugs. We are convinced that PID imaging is an ideal tool in drug development for elucidating the mechanism of action, particularly with regard to the rapidly growing number of antibody-based drugs.

T-DXd (DS-8201a) and control IgG-DXd were obtained dissolved in DMSO at concentrations of 20.6 and 10.74 mg/mL, respectively, from Daiichi Sankyo Co., Ltd. Each drug was stored in a −80°C deep freezer until used in animal experiments, and then diluted with saline (Otsuka Pharmaceutical) to the required concentration at the time of use. Free DXd, the standard for LC/MS-MS analysis, was obtained from Daiichi Sankyo and dissolved in DMSO at a concentration of 100 mg/mL.

The human gastric carcinoma cell line NCI-N87 (HER2: 3+) and three human breast carcinoma cell lines, BT474 (HER2: 3+), MCF7 (HER2: 1+), and MDA-MB-468 (HER2: 0) were purchased from the ATCC. Short tandem repeat (STR) profiles of each cell line were confirmed by an external agency (BEX) as completely matching the ATCC database. NCI-N87, MDA-MB-468, and BT474 cells were cultured in RPMI1640 (Thermo Fisher Scientific) supplemented with 10% heat-inactivated FBS (Thermo Fisher Scientific) and 1% penicillin/streptomycin (Sigma-Aldrich). MCF7 cells were cultured in DMEM (Thermo Fisher Scientific) supplemented with 10% heat-inactivated FBS and 1% penicillin/streptomycin. All cells were cultured at 37°C under a 5% CO₂ atmosphere and used in the experiments at fewer than 15 passages. Tests for Mycoplasma using MycoAleart (Lonza) were negative, most recently in October 2020.

All animal experiments were reviewed and approved by the ethics committees at the National Cancer Center and were performed according to the guidelines of the Committee for Animal Experimentation of the National Cancer Center (T17-073, T19-008).

To establish a cell line–derived xenograft model (CDX), 4-week-old female SCID-beige (CB17.Cg-Prkdc^scidLyst^bg-J/CrlCrlj) mice were obtained from Charles River Laboratories Japan. The mice were maintained in specific pathogen–free cages under a 12-hour/12-hour light/dark cycle. All models were established by subcutaneous injection in the flanks of the mice. The HER2 heterogeneous model was established by injecting a mixture of 50 μL of cell suspension (3.3 × 10⁶ NCI-N87 and 6.7 × 10⁶ MDA-MB-468) and 50 μL of Matrigel growth factor reduced and phenol-red free type (Corning; Fig. 3A). The HER2 homogeneous model was generated by injecting 6.7 × 10⁶ NCI-N87 and MDA-MB-468 cells, each with an equal volume of Matrigel, into both shoulders of each mouse (Fig. 5A). The BT474 and MCF7 CDXs were established by injecting 1.0 × 10⁷ cells, each with an equal volume of Matrigel. When the tumor volume exceeded 300 mm³, T-DXd was administered intravenously at a dose of 4 mg/kg and a volume of 5 mL/kg. As a vehicle, normal saline was given at the same volume as the ADC. According to designed schedules, tumor samples were harvested and embedded using optimal cutting temperature (OCT) compound (Sakura Finetek). The OCT blocks were immediately frozen with dry ice–hexane and stored in a −80°C deep freezer until used in experiments.

For subsequent tissue analyses, 8-μm-thick serial sections were sliced using a cryomicrotome (Leica Biosystems). PID imaging was performed as described previously (15). After pre-fixation with 4% paraformaldehyde (PFA) and blocking with KM001 (Konica Minolta), each primary antibody was reacted overnight at 4°C. The anti-DXd mAb (provided by Daiichi Sankyo Co., Ltd.) detects both DXd conjugated to the antibody and free DXd (not conjugated with antibody) and was used at a concentration of 0.25 μg/mL for payload imaging. Biotinylated anti-human IgG1 Fcγ (Jackson Immuno Research, in-house biotinylated) was used at a concentration of 0.125 μg/mL to detect trastuzumab. For DXd imaging analyses, 2 μg/mL biotinylated goat anti-rabbit IgG secondary antibody (LO-RG-1, Bio-Rad) was incubated following reaction with 0.03 nmol/L streptavidin-conjugated PID fluorescent nanoparticles (streptavidin-PID; Konica Minolta) dispersed in KM001. For trastuzumab analysis, after washing the primary antibody, the streptavidin-PID was reacted directly. As post-fixation, samples were treated with 4% PFA for 10 minutes at room temperature and then counterstained with hematoxylin and mounted using marinol (Muto Pure Chemicals). For observation and image acquisition, a Nanozoomer S60 (Hamamatsu Photonics), BZ-X710 microscope (Keyence), and BX63 microscope (Olympus) were used. Automatic recognition and quantification of PID were carried out using an exclusive PID analysis system developed by Konica Minolta.

IHC analysis of HER2 was conducted using an HRP/DAB detection system. Frozen sections were fixed with 4% PFA for 10 minutes prior to immersion in 0.3% H₂O₂ in methanol for 10 minutes to block endogenous peroxidases. After treatment with blocking solution for 30 minutes at room temperature, the primary antibody, anti-HER2 mAb (4B5; Roche), was added and incubated for 1 hour at room temperature. After washing, goat anti-rabbit IgG secondary antibody (#8114s; Cell Signaling Technology) was reacted for 30 minutes at room temperature, followed by detection using a DAB substrate kit (#8059, Cell Signaling Technology). The H-score of each cell line was assessed by pathologists, as reported previously (22), using tissues that had not been treated with T-DXd.

The concentrations of trastuzumab and DXd in plasma and tumor tissues were determined using an LC/MS-MS method. Tumor tissue lysate was obtained by homogenizing tumors in PBS containing n-octyl-1-thio-β-D-gulucopyranoside, and protein was quantified using a micro–bicinchonic acid assay kit (Thermo Fisher Scientific). For trastuzumab, trypsin was digested using a ProteinWorks Auto-express Digest Kit (Waters). For free DXd, solid-phase extraction with OASIS MCX μelution (Waters) was performed according to each kit's instructions. Samples were filtered using Ultrafree-MC SV (Merck Millipore). For trastuzumab, trypsin was digested using an nSMOL antibody BA Kit (Shimadzu) according to a previous report (23). An LCMS-8050 (Shimadzu) and Q-TRAP-5500 (AB SCIEX) was used to analyze trastuzumab and DXd, respectively. FTISADTSK (485.2 > 721.1) and IYPTNGYTR (543.3 > 404.8) were measured in plasma and tumor tissue lysates as surrogate peptides of trastuzumab. The measurement conditions for DXd were set based on a previous report (24).

The results of PID quantification are presented as the mean and SEM obtained from at least five fields (∼22,800 μm²/field of view) of view in each tissue section. All statistical analyses of drug distribution and PID count were carried out by Turkey–Kramer test and Mann–Whitney U test using GraphPad Prism, version 8 (GraphPad Software).

PID imaging of the T-DXd components trastuzumab and DXd was evaluated using serial sections (Fig. 1A). A xenograft model using NCI-N87 (HER2: 3+) HER2-positive gastric cancer cells was examined 24 hours after administration of 4 mg/kg T-DXd or saline as a vehicle control. PID imaging of trastuzumab and DXd was conducted using 8-μm-thick frozen serial sections. To detect the parent antibody, trastuzumab, anti-trastuzumab idiotype antibodies (HCA176, HCA177), and anti-human IgG1 were examined. The anti-human IgG1 with the highest signal-to-noise ratio was adopted for subsequent experiments (Fig. 1B). To detect DXd, an anti-DXd mAb was used after confirmation that the signal-to-noise ratio was sufficient (Fig. 1B). Conditions for the use of each antibody are shown in Table 1.

The intratumor distribution of trastuzumab and DXd 24 hours after administration of 1, 4, and 7 mg/kg of T-DXd to mice in which BT474 (HER2: 3+) HER2-positive breast cancer cells were transplanted is shown in Fig. 2A. The mean trastuzumab-PID and DXd-PID counts were 29.5, 59.6, and 72.3 units/100 μm² and 51.7, 97.6, and 87.0 units/100 μm² doses of 1, 4, and 7 mg/kg, respectively (Fig. 2B). The tumor tissue distribution of trastuzumab and DXd at doses of 4 and 7 mg/kg was comparable (P = 0.504 and 0.581, respectively).

Next, we evaluated the intratumor distribution of trastuzumab and DXd after administration of T-DXd at a dose of 4 mg/kg to three breast cancer cell lines exhibiting different HER2 expression levels: MDA-MB-468 (HER2: 0), MCF7 (HER2: 1+), and BT474 (HER2: 3+; Fig. 2C). The stained slides were also evaluated by H-score (Supplementary Table S1), and the results were concordant with those obtained with the standard HER2 scoring method. The mean trastuzumab-PID counts were 1.8, 13.8, and 59.6 units/100 μm², and the mean DXd-PID counts were 2.7, 16.0, and 97.6 units/100 μm² in MDA-MB-468, MCF7, and B474 cells, corresponding to the HER2 expression level (Fig. 2D).

To further evaluate the specific action of T-DXd on the HER2 antigen, PID imaging was used to examine the pharmacokinetic profile 24 hours after administration of 4 mg/kg of either control IgG-DXd (DXd conjugated to humanized IgG1, which does not recognize HER2) or T-DXd to NCI-N87 cells. In the control IgG-DXd group, the distribution of trastuzumab-PID and DXd-PID was minimal in HER2-positive areas. In contrast, in the T-DXd group, a strong distribution of both trastuzumab-PID and DXd-PID in HER2-positive areas was observed (Fig. 2E). The distribution of T-DXd to tumor cells was confirmed to be a HER2-mediated antigen-antibody response.

Ogitani and colleagues previously demonstrated that T-DXd has a cytotoxic effect on a NCI-N87 (positive) and MDA-MB-468 (negative) mixed “HER2 heterogeneous model” (15). We used this heterogeneous model to analyze the spatial pharmacokinetics of trastuzumab and DXd after administration of 4 mg/kg of T-DXd (Fig. 3A). Whole-slide images of HER2, trastuzumab, and DXd in tumor cross-sections are shown in Fig. 3B. The HER2 expression level in the HER2 heterogeneous model tended to decrease in a time-dependent manner (Fig. 3B and C). We also confirmed that trastuzumab-PID and DXd-PID accumulation was higher in HER2-positive areas. The mean trastuzumab-PID and DXd-PID counts in HER2-positive areas were 0.2, 143.3, 183.5, 127.4, and 116.3 units/100 μm² and 0.7, 133.0, 232.2, 157.8, and 147.1 units/100 μm² at 0, 6, 24, 72, and 96 hours, respectively (Fig. 3D). Trastuzumab-PID and DXd-PID accumulation reached maximum levels 24 hours after dosing. Plasma and tumor tissue concentrations in the xenograft model were examined using an LC/MS-MS method to verify this result. The concentrations of trastuzumab and DXd tended to decrease in a time-dependent manner (Fig. 4). Figure 3E shows an enlarged view of the distribution of trastuzumab-PID and DXd-PID at 24 and 72 hours. At 24 hours, HER2 expression coincided with the trastuzumab distribution, and DXd exhibited a tendency to spread out from the trastuzumab distribution. By comparison, at 72 hours, HER2 expression matched the trastuzumab distribution, but DXd exhibited a tendency to spread further from HER2-positive areas to HER2-negative areas. We also examined the distribution of DXd based on whether the HER2-negative area was adjacent to the HER2-positive area and found that DXd was more abundant in adjacent HER2-positive areas (Fig. 3F). The mean DXd-PID counts in HER2-negative areas adjacent and not adjacent to HER2-positive areas were 41.9 and 5.1 units/100 μm², respectively (Fig. 3G). Taken together, these data suggest that the DXd released from the antibody spread to the HER2-negative areas.

To investigate the intratumor pharmacokinetics of T-DXd when HER2-positive and HER2-negative tumors are separated, we established HER2 homogeneous model mice by transplanting NCI-N87 and MDA-MB-468 cells into the left and right shoulder, respectively (Fig. 5A). At 24 and 72 hours after administration of T-DXd, an extremely high distribution of both trastuzumab-PID and DXd-PID was observed in HER2-positive NCI-N87 tumors, whereas little distribution was observed in HER2-negative MDA-MB-468 tumors (Fig. 5B and C). The mean DXd-PID count in MDA-MB-468 tumors was 1.8 units/100 μm², significantly lower than that in HER2-negative areas in the HER2 heterogeneous model (P = 0.0013).

T-DXd, a novel ADC targeting HER2, is a breakthrough drug for treating tumors with heterogeneous HER2 expression that are resistant to conventional anti-HER2 therapy. In this study, we evaluated the intratumor pharmacokinetics of T-DXd in mouse xenograft models by PID imaging targeting the parent antibody trastuzumab and the payload DXd. Our analyses confirmed that the distribution of T-DXd in tumor tissue is dependent on HER2 expression level using three xenograft models exhibiting varying HER2 expression. In the HER2 heterogeneous model, the trastuzumab distribution was consistent with HER2 expression, whereas DXd was distributed in HER2-negative areas. As DXd was not distributed in HER2-negative tumors transplanted separately from HER2-positive tumors, we concluded that DXd distribution in HER2-negative areas required these areas be adjacent to HER2-positive areas. These results enable visualization of the pharmacologic mechanism of T-DXd, which exerts cytotoxic activity against both HER2-positive and HER2-negative cells after HER2-selective distribution.

For an ADC to exhibit efficacy, it must reach tumor cells and release its payload. Therefore, pharmacokinetic analyses of ADCs require a high-resolution method in which target antigen expression is spatially maintained instead of conventional analyses of blood or target tumors. There have been some reports of pharmacokinetic studies of ADCs using drugs labeled with radioisotopes or fluorescent dyes (25–28) and mass spectrometry imaging [i.e., matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI)] (29–31). When using a labeled drug, the possibility that the label may alter the drug's original kinetics must be considered. Also, labeled drugs are typically visualized by PET or MRI, but the resolution of these techniques is low; thus, analysis at the cellular level is difficult. MALDI-MSI is a revolutionary technique that can detect unlabeled drugs. Nevertheless, it is not suitable for analyzing large molecules that are difficult to ionize, such as antibodies. The sensitivity of MALDI-MSI for the analysis of payloads is often insufficient, so it has not been widely used to analyze ADC kinetics.

PID imaging is a type of immunostaining most commonly used to detect biomarkers in oncologic diagnosis. Immunostaining using PID as a label provides high resolution and enables quantification by taking advantage of PID's extremely high fluorescence intensity and homogeneity. Furthermore, the versatility of IHC makes PID imaging a suitable method for evaluating various tumor antigens and anticancer drugs.

It has been speculated that HER2-dependent binding to tumor cells, internalization, and enzyme-dependent linker cleavage are required for DXd to be released from T-DXd (6). Recently, however, it was reported that the payload can be released through phagocytosis by macrophages or other tumor microenvironment factors without antigen-dependent internalization (32, 33). Our experiments confirmed that the accumulation of DXd-PID is correlated with the level of HER2 expression in three breast cancer cell lines. We also confirmed that there was no accumulation of DXd-PID in HER2-negative tumors in the HER2 homogeneous model. Furthermore, little distribution of DXd was observed in tumor cells treated with control IgG-DXd, in which the anti-HER2 antibody of T-DXd (HER2 specific) was modified to anti-human IgG (HER2 nonspecific). Therefore, in our animal model, the intratumor accumulation of DXd is HER2-dependent, and the effect of extracellular cleavage of DXd may not be significant. Indeed, Takegawa and colleagues reported a correlation between tumor HER2 expression level and the efficacy of T-DXd (34). Sharma and colleagues and Li and colleagues reported a correlation between ADC target antigen expression level and the amount of internalized payload (35, 36). Ogitani and colleagues reported that control IgG-DXd exhibited no efficacy against HER2-positive and HER2 heterogeneous models where T-DXd was highly effective (14, 15). Our results are consistent with their reports and suggest that the main pathway of DXd release, at least in our animal models, involves internalization by HER2-positive cells.

The bystander effect has attracted considerable attention as an antitumor mechanism of ADCs, in addition to the cytocidal effect of the payload (1, 37, 38). The bystander effect occurs when payloads released in target antigen-positive cells also affect surrounding antigen-negative tumor cells and the tumor microenvironment. DXd, the payload of T-DXd, has an extremely high membrane permeability compared with DM-1, the payload of T-DM1. Hence, it was reported that T-DXd exhibits the bystander effect in tumors with HER2 heterogeneity and exhibits therapeutic efficacy in tumors expressing low levels of HER2, in which the efficacy of conventional anti-HER2 therapy is insufficient (12–15). As a result of PID imaging using a HER2 heterogeneous model, it was confirmed that the trastuzumab distribution correlated with HER2 expression level. Simultaneously, the distribution of DXd also extended to HER2-negative areas adjacent to HER2-positive areas. Moreover, in a model in which HER2-positive and HER2-negative tumors were separated, there was essentially no DXd distributed on the HER2-negative tumor side. These results provide visualization of the bystander effect, in which T-DXd binds to HER2-positive cells via trastuzumab and the released DXd acts directly on HER2-negative cells adjacent to HER2-positive cells.

Traditionally, the concentrations of antibody and payload in plasma and tumors have been analyzed by LC/MS-MS as a conventional analysis. This method has some disadvantages, such as the loss of locational information mentioned above and histologic effects (e.g., necrosis) and blood contamination due to processing the tumor in bulk. In our study, the concentrations of trastuzumab and DXd tended to decrease in a time-dependent manner. In contrast, PID imaging showed drug distribution in HER2-positive areas even at the time the concentration measured by LC/MS-MS was declining. These results suggest that cellular level rather than bulk analyses, that is, taking into account the location and intensity of antigen expression, are important to evaluate the intratumor pharmacokinetics of ADCs.

There are some limitations to this study. One is the misalignment of tissues due to evaluation of serial sections. Thus, using 8-μm-thick sections for HER2, trastuzumab, and DXd detection can result in a gap of approximately 16μm. Second, the anti-DXd antibody cannot distinguish between antibody-conjugated DXd and released free DXd. It would be necessary to create antibodies against the linker to distinguish antibody-conjugated DXd from total DXd mixtures (antibody conjugated and free payload). Third, our study used fixed tumor sections at each timepoint, making it difficult to capture continuous phenomena. To confirm the continuous pharmacokinetics and cytotoxic effects, live imaging and other techniques will be needed. Finally, all of the above experiments involved animal models, and thus it will be necessary to validate the phenomena observed in clinical studies.

In summary, the intratumor pharmacokinetics of T-DXd were revealed at high resolution using PID imaging. Furthermore, we also demonstrated that PID imaging is useful for elucidating the unique pharmacologic mechanisms of ADCs, such as the “bystander effect.” PID imaging is an extremely versatile method that can be used to detect proteins in general. In the future, imaging pharmacokinetic analysis is expected to become a useful tool for understanding pharmacologic action in the field of drug development, especially in the rapidly growing antibody engineering. PID imaging is also expected to be employed clinically as a system for microlevel assessment of delivery to tumor target sites in individual patients.

S. Yagishita reports grants from Boehringer Ingelheim outside the submitted work. T. Nishikawa reports personal fees from Eisai, AstraZeneca, and Takeda outside the submitted work. T. Jikoh reports personal fees from Daiichi Sankyo Co., Ltd. during the conduct of the study and personal fees from Daiichi Sankyo Co., Ltd. outside the submitted work. Y. Yatabe reports personal fees from MSD, Chugai-pharma, AstraZeneca, Thermo Fisher Science, and ArcherDx outside the submitted work. K. Yonemori reports personal fees from Eisai, Pfizer, Takeda, Chugai, AstraZeneca, Novartis, and Ono outside the submitted work. K. Hasegawa reports grants from Daiichi-Sankyo during the conduct of the study, as well as grants and personal fees from Daiichi-Sankyo, MSD, Chugai, Eisai, and Takeda; grants from Ono; and personal fees from AstraZeneca, Genmab, and Mochida outside the submitted work. A. Hamada reports grants from Daiichi Sankyo and Konica Minolta during the conduct of the study and grants from Eisai, Eli Lilly, Sysmex, Chugai, and Chordia Therapeutics outside the submitted work. No disclosures were reported by the other authors.

M. Suzuki: Conceptualization, data curation, software, formal analysis, validation, investigation, visualization, methodology, writing–original draft, project administration, writing–review and editing. S. Yagishita: Conceptualization, data curation, supervision, investigation, project administration, writing–review and editing. K. Sugihara: Conceptualization, resources, validation, investigation, methodology. Y. Ogitani: Conceptualization, resources, validation, investigation, methodology, writing–review and editing. T. Nishikawa: Conceptualization, data curation, writing–review and editing. M. Ohuchi: Conceptualization, formal analysis, validation, investigation, methodology, writing–review and editing. T. Teishikata: Data curation, formal analysis, methodology, writing–review and editing. T. Jikoh: Conceptualization, resources, validation, investigation, writing–review and editing. Y. Yatabe: Data curation, formal analysis, supervision, methodology, writing–review and editing. K. Yonemori: Data curation, supervision, investigation, writing–review and editing. K. Tamura: Conceptualization, data curation, supervision, investigation, writing–review and editing. K. Hasegawa: Conceptualization, data curation, supervision, investigation, writing–review and editing. A. Hamada: Conceptualization, data curation, supervision, funding acquisition, investigation, project administration, writing–review and editing.

This work was supported in part by the Daiichi Sankyo Research grant (A. Hamada) and the National Cancer Center Research and Development Fund (A. Hamada). We would like to thank Konica Minolta Co., Ltd., for technical advice on PID imaging. We thank Yoko Urasaki and Masako Soma of Daiichi Sankyo Co., Ltd., for technical support regarding the analytic system. Similarly, we thank Haruka Harada for assistance with animal experiments and imaging analyses.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.