Poor penetration of mAbs in solid tumors is explained, in part, by the binding site barrier hypothesis. Following extravasation, mAbs rapidly bind cellular antigens, leading to the observation that, at subsaturating doses, therapeutic antibody in solid tumors localizes around tumor vasculature. Here we report a unique strategy to overcome the binding site barrier through transient competitive inhibition of antibody–antigen binding. The anti-trastuzumab single domain antibody 1HE was identified through in vitro binding assays as a model inhibitor. Coadministration of 1HE did not alter the plasma pharmacokinetics of trastuzumab or ado-trastuzumab emtansine (T-DM1) in vivo. Administration of 1HE alone was rapidly eliminated with a terminal plasma half-life of 1.2 hours, while coadministrations of 1HE with trastuzumab had a terminal half-life of 56 hours. In mice harboring SKOV3 xenografts, coadministration of 1HE with trastuzumab led to significant increases in both penetration of trastuzumab from vasculature and the percentage of tumor area that stained positive for trastuzumab. 1HE coadministered with a single dose of T-DM1 to NCI-N87 xenograft–bearing mice significantly enhanced T-DM1 efficacy, increasing median survival. These results support the hypothesis that transient competitive inhibition can improve therapeutic antibody distribution in solid tumors and enhance antibody efficacy.

Significance:

This study describes the development of a transient competitive inhibition strategy that enhances the tumor penetration and efficacy of anticancer antibodies.

See related commentary by van Dongen, p. 3956

Interest in the development of targeted anticancer therapeutics such as mAbs and antibody–cytotoxin conjugates has grown rapidly over the past two decades. In total, 30 antibodies have received FDA approval for oncology indications with six currently in regulatory review and an additional 40 in late-stage clinical development (1). However, it is recognized that antibodies often exhibit only limited uptake and penetration in solid tumors, leading to suboptimal efficacy (2–4). Solid tumors are responsible for approximately 90% of the total deaths from cancer (5) and, consequently, methods to improve antibody efficacy against solid tumors may have great clinical impact.

Physical barriers present within solid tumors are well appreciated in impeding uptake and penetration of therapeutic antibodies. Poor distribution of mAbs within tumors has been attributed to many factors (2, 3, 6), and improved intratumoral distribution has been achieved with tumor matrix modulation (7–9) and vascular permeability enhancement (10–12). An impediment to antibody penetration that remains a significant challenge is the binding site barrier (BSB; refs. 13–15). The tumor penetration of high-affinity antibodies is limited by the successful binding of antibodies to cellular antigens at the point of extravasation, leading to antibody sequestration and suboptimal tumor exposure (14, 16–18). The BSB was first described more than 30 years ago (19); subsequently, a large number of experimental investigations and mathematical simulations have supported the BSB hypothesis (14–18, 20). Preclinical investigations have shown increased intratumoral distribution for low or intermediate affinity mAb and lower molecular weight constructs (e.g., sdAb, scFv, Fab; refs. 14, 17, 18, 21–25); however, clinical utility has not yet been established. The vast majority of anticancer antibody therapies on the market and in development are high-affinity, intact mAb, where distribution within solid tumors is often strongly impacted by the BSB phenomenon.

Recently, there has been substantial discussion of the impact of the BSB on the efficacy of antibody–drug conjugates (ADC; refs. 26–30). Because of dose-limiting toxicities, ADCs are administered at doses below levels required to saturate antigen throughout the tumor. Under these nonsaturating conditions, the impact of the BSB is most evident, and promotes substantial heterogeneity in antibody concentrations throughout tumors, with high concentrations near sites of extravasation, and with dramatically reducing ADC concentrations with increasing distance from tumor blood vessels. Because of the high potency of ADC, concentrations in excess of those required for cell killing are achieved near vessels, and concentrations far below those required for efficacy are found at locations distant from sites of extravasation (28). Consequently, at clinical ADC doses, the BSB results in excess delivery of ADC to tumor cells surrounding vasculature at the expense of poor total tumor exposure to ADC (28).

Here we report a strategy to overcome the BSB through transient competitive inhibition of mAb–antigen binding. We hypothesized that transient competitive inhibition of antibody binding to tumor antigens would increase the distribution of mAb within solid tumors, retaining the high tumor selectivity of a high-affinity mAb, while enabling the desirable within-tumor distribution characteristics of a low-affinity mAb (illustrated graphically in Fig. 1A and B). The anti-idiotypic anti-trastuzumab camelid single-domain antibody (sdAb), 1HE, reported by Alvarez-Reuda and colleagues for the development of a HER2 vaccine (31), was identified using in vitro binding assays as a lead inhibitor for experimental evaluation of the competitive inhibition strategy. 1HE coadministration did not alter the plasma pharmacokinetics of trastuzumab or T-DM1 in Swiss-Webster mice. When administered alone, 1HE was rapidly eliminated from plasma. However, when administered with trastuzumab, 1HE elimination was dramatically reduced, consistent with 1HE bound to trastuzumab being protected from kidney filtration and catabolism. In mouse xenograft models of HER2-positive carcinoma, 1HE coadministration significantly increased trastuzumab penetration within tumors and improved T-DM1 efficacy. Results that are provided here indicate that transient inhibition of HER2 binding allows trastuzumab to bypass the BSB, without losing the benefit of high-affinity HER2 binding. The competitive inhibition strategy, which may be applied to a wide range of high-affinity anticancer antibody therapies that are on the market and in current development, may be a clinically feasible approach to enhance the effectiveness of targeted therapies directed against solid tumors.

Materials

The human ovarian carcinoma cell line SKOV3 (HTB-77, RRID:CVCL_0532) was purchased from ATCC and the gastric carcinoma cell line NCI-N87 (CRL-5822, RRID:CVCL_WH01) was a generous gift from Dr. Dhaval Shah (Department of Pharmaceutical Sciences, University at Buffalo, Buffalo, NY). Cell lines were authenticated by ATCC using short tandem repeat profiling and were tested for Mycoplasma contamination using a Universal Mycoplasma Detection Kit (ATCC 30–1012K) in January of 2021. Cells were cultured following ATCC cell line–specific recommendations and were used within the first 10 passages following thawing. Trastuzumab and ado-trastuzumab emtansine were purchased from Millard Fillmore Memorial Hospital (Amherst, NY).

1HE expression and purification

The amino acid sequence for 1HE was obtained from the publication by Alvarez-Reuda and colleagues (31). A codon-optimized 1HE DNA sequence was synthesized by GeneArt, ligated into the plasmid pET22b(+) (Millipore-Sigma, 69744) at the XhoI and NdeI restriction enzyme sites, and transformed into the Escherichia coli strain SHuffle (New England Biolabs, C3029J). 1HE was produced in SHuffle cells following a standard recombinant expression protocol. Briefly, a glycerol stock of transformed SHuffle cells was removed from storage at −80°C and a small volume spread over a lysogeny broth (LB) agar plate with 100 μg/mL ampicillin. The next day a single colony was selected and inoculated into an LB medium starter culture with 100 μg/mL ampicillin and grown in a shaker incubator at 30°C for 18 hours. The starter culture was diluted 1 to 100 into LB medium with 100 μg/mL ampicillin and cells grown to an optical density of 0.6 to 0.8 at a wavelength of 600 nm and expression induced with 1 mm isopropyl β-d-1-thiogalactopyranoside (IPTG) for 18 hours at 16°C. Cells were pelleted, lysed using BugBuster (Millipore-Sigma, 70584), and 1HE purified from cell lysate with a 3 mL HisPur Ni-NTA spin column (Thermo Fisher Scientific, 88226) following manufacturer recommendations. Eluted protein was dialyzed into a 5 mmol/L disodium phosphate buffer pH 6.8 overnight and the dialyzed product flowed through a Bioscale Mini-CHT Type 1 cartridge (Bio-Rad, 7324324) using a BioLogic LP system (Bio-Rad). 1HE was eluted from the CHT column using a 100 mL gradient of 0% to 100% 500 mmol/L disodium phosphate at a flow rate of 2 mL/minute. Collected fractions were analyzed with SDS-PAGE and fractions containing 1HE combined and dialyzed into PBS pH 7.4 overnight.

Surface plasmon resonance

A SR7500DC surface plasmon resonance (SPR; Reichert) was utilized for kinetic binding assessment. Trastuzumab was immobilized on a CM5 chip (Reichert, part #: 13206066) through amine coupling. For all binding assessments, a mobile phase of 0.05% Tween-20 PBS pH 7.4 was used at a flow rate of 25 μL/minute. Binding kinetics for 1HE to trastuzumab was evaluated through injection of 1HE at concentrations of 1, 3, 7.5, 15, and 30 nmol/L for 2.5 minutes with a 10-minute dissociation. A second evaluation of 1HE–trastuzumab binding was completed with a 10-hour dissociation time with 1HE injections at concentrations of 10, 20, and 35 nmol/L. Association and dissociation rate constants were determined using a 1:1 Langmuir binding model in the biosensor data analysis software Scrubber (BioLogic Software).

Radiolabeling of trastuzumab and 1HE

Trastuzumab, T-DM1, and 1HE were radiolabeled with iodine-125 (125I) through a modified chloramine-T method described previously (32). Briefly, 40 μL of protein (1–2 mg/mL in pH 7.4 PBS) was combined with 10 μL of sodium125I (100 mCi/mL; PerkinElmer), and subsequently reacted with 20 μL of chloramine-T (1 mg/mL in pH 7.4 PBS). After 90 seconds, the reaction was terminated by the addition of 40 μL of 10 mg/mL potassium iodide. Immediately following the reaction, gel filtration (Sephadex G-25 column, GE Healthcare Bio-Sciences) was performed to separate 125I-labeled intact mAb from the mixture. The activity of the 125I-protein fraction was determined through gamma counting (LKB Wallac 1272) with purity assessed through thin layer chromatography (PE SiL-G, Whatman Ltd).

Assessment of 1HE inhibition on 125I-trastuzumab–HER2 binding

SKOV3 cells (ATCC, HTB-77) were grown in complete McCoy 5a media to confluency in a T75 flask and dissociated using 50 μmol/L ethylenediaminetetraacetic acid (EDTA). Cells were pelleted (200 RCF, 5 minutes) and resuspended in a 1% BSA PBS solution and pipetted into microcentrifuge tubes (1 million cells/mL). 125I-trastuzumab was added to each tube, at a concentration of 200 pmol/L, with increasing concentrations of 1HE. Cells were incubated at 4°C for 90 minutes to reach binding equilibrium followed by 4 washes with 1 mL of 1% BSA PBS buffer to remove nonspecific radioactivity. Cell-associated radioactivity was assessed through gamma counting. Cell-associated radioactivity normalized to a 125I-trastuzumab control (B/Bo) was fit to a 3-parameter logistic function in Graphpad Prism 7 (GraphPad).

Determination of 125I-1HE dissociation from immobilized trastuzumab

Trastuzumab was chemically conjugated to Dynabeads following manufacturer's recommendations (Thermo Fisher Scientific, 14321D). 125I-1HE was incubated with trastuzumab beads for 1 hour at a concentration of 10 nmol/L; subsequently, beads were washed 3× with 0.1% BSA-PBS and initial bound radioactivity determined through gamma-counting. 125I-1HE bound trastuzumab beads were incubated in triplicate with 0.1% BSA-PBS, 1 μmol/L unlabeled 1HE in 0.1% BSA-PBS, or 1 μmol/L T-DM1 in 0.1% BSA-PBS. The supernatant was removed and replaced with fresh buffer at 0.5, 1, 3, 6, 10, 18, 26, 43, and 66 hours, and remaining bound radioactivity determined at each time point.

Impact of 1HE on trastuzumab and T-DM1 plasma pharmacokinetics

Plasma pharmacokinetics of trastuzumab and T-DM1 with and without coadministration of 1HE were assessed in male Swiss-Webster mice 4 to 6 weeks of age (Envigo). Mouse studies were approved by the University at Buffalo Institutional Animal Care and Use Committee. Trastuzumab was given through penile vein injection at doses of 0.1, 1, and 10 mg/kg (5 mice/group) with and without 1HE in a 1:2 molar ratio (trastuzumab:1HE) with a tracer dose of 125I-trastuzumab (400 μCi/kg). T-DM1 was administered at a dose of 1.8 mg/kg with a tracer dose of 125I-T-DM1 (400 μCi/kg). 1HE was administered at a 10-fold molar excess through retro-orbital injection 15 minutes after T-DM1 injection with T-DM1 only control mice receiving a volume equivalent of PBS. Blood samples were collected through retro-orbital sampling using microcapillary tubes coated with ethylenediaminetetraacetic acid (EDTA). Plasma samples were collected following centrifugation (200 × g, 5 minutes), and trichloroacetic acid (TCA) precipitated as previously described (33). Plasma-associated radioactivity was determined through gamma-counting (LKB Wallac 1272, Wallac), with observed counts corrected for background radiation and radioactive decay. Noncompartmental analysis (WinNonlin 7, Phoenix, Pharsight Corporation) was used for calculation of the AUC 0 to 10 days after administration [AUC(0–10days)]. The observed AUC(0–10days) with and without 1HE coadministration was compared statistically using Student t test with Bonferroni correction for multiple comparisons in GraphPad Prism 7 (GraphPad).

1HE plasma pharmacokinetics

1HE pharmacokinetics were assessed following a 1 mg/kg dose in male Swiss-Webster mice 4 to 6 weeks of age (Envigo). Blood samples were collected at 5, 20, 60,180, and 360 minutes after injection through retro-orbital or submandibular sampling and plasma samples collected following centrifugation [200 rotational centrifugal force (RCF), 5 minutes]. 1HE time points were quantified using the indirect ELISA protocol provided in the Supplementary Data. ELISA variability and recovery values are provided in Supplementary Table S1. 1HE plasma pharmacokinetics with trastuzumab was evaluated at a trastuzumab to 1HE ratio of 1:0.2 with a 125I-1HE (400 μCi/kg) tracer dose. Of note, the ratio of 1:0.2 trastuzumab to unlabeled 1HE was used to ensure the availability of free trastuzumab sites for binding to 125I-1HE. Blood samples were collected through retro-orbital sampling using microcapillary tubes coated with EDTA. Plasma samples were collected following centrifugation (200 RCF, 5 minutes), and TCA precipitated. Following TCA precipitation, plasma-associated radioactivity was determined through gamma-counting with observed counts corrected for background radiation and radioactive decay.

Assessment of trastuzumab penetration in SKOV3 xenografts

Male NOD-SCID mice (Charles River) were subcutaneously injected with two million SKOV3 cells in DPBS in the right flank. Once tumors reached an average size of 200 mm3, the mice were intravenously injected with 2 mg/kg trastuzumab alone or with 1HE in a 1:2 molar ratio (trastuzumab:1HE; n = 3/group). Twenty-four hours after intravenous injection the xenografts were resected, cryosectioned, and trastuzumab and tumor vasculature fluorescently stained. The complete staining protocol is provided in the Supplementary Data. Tumor sections were imaged using an EVOS Fl autofluorescent microscope (Thermo Fisher Scientific) using an identical automated imaging method for each slice. Three tumor sections per tumor were analyzed to obtain trastuzumab penetration values using an image analysis protocol and algorithm that is described and provided in the Supplementary Data.

T-DM1 efficacy

Male NU/J mice, 4 to 6 weeks old (The Jackson Laboratory), were injected subcutaneously in the right flank with 5 million NCI-N87 cells in 200 μL of a 1:1 Matrigel (Thermo Fisher Scientific, CB-40234): RPMI1640 solution. Tumor size was measured using digital calipers with tumor volume calculated using the formula: tumor volume = 0.5 × a2 × b, where a is tumor width and b tumor length. Once tumor volumes reached an average of approximately 250 mm3 mice were split into four groups: saline vehicle (n = 7), trastuzumab 10 mg/kg (n = 7), T-DM1 1.8 mg/kg (n = 9) and T-DM1:1HE 1.8 mg/kg (n = 9). Mice were injected through retro-orbital injection with T-DM1 with either 1HE (10-fold molar excess) or saline administered 15 minutes after T-DM1. Tumor volumes were monitored every two days, and mice sacrificed once tumors reached a terminal volume of 1,200 mm3. Kaplan–Meier survival curves were generated in GraphPad Prism 7 and compared using the log-rank test at a significance level of P ≤ 0.008.

1HE–trastuzumab binding assays

The initial SPR assessment for 1HE–trastuzumab binding resulted in a best-fit koff rate of 4.8 × 10−4 sec−1; however, biphasic binding kinetics were observed (Fig. 2, top left). Biphasic binding kinetics may be the result of heterogeneity within the purified 1HE preparation or heterogenous immobilization of trastuzumab on the SPR chip, leading to partial occlusion of the 1HE binding site on trastuzumab. Gel-based analysis indicated 1HE was >90% pure with only a single peak observed following SEC and HIC runs (Supplementary Fig. S1A and S1B), therefore the biphasic kinetics were likely the result of heterogenous trastuzumab immobilization. To further characterize 1HE-trastuzumab dissociation kinetics, a secondary SPR evaluation with a 10-hour dissociation time was employed. The resultant data led to a best-fit koff value of 7.2 × 10−6 sec−1 (Fig. 2, bottom left). We hypothesize that the initial koff estimate of 4.8 × 10−4 sec−1 overpredicts the true dissociation rate because early phases of dissociation are dominated by dissociation of 1HE from partially blocked trastuzumab binding sites. Of note, it is possible that the 10-hour dissociation koff of 7.2 × 10−6 sec−1 underpredicts the true dissociation rate constant due to mass-transport limitations and due to rebinding of 1HE and trastuzumab within the SPR assay run. To further evaluate trastuzumab–1HE binding, a competitive cell-based assay was conducted (Fig. 2, top right). 1HE led to a concentration-dependent reduction in the amount of trastuzumab bound to cellular HER2, indicating 1HE is a competitive inhibitor of trastuzumab–HER2 binding. The observed half-maximal inhibition constant (IC50) of 124 pmol/L for 1HE was approximately equal to approximately 50% of the concentration of trastuzumab added (200 pmol/L), consistent with a 1HE–trastuzumab binding KD ≤124 pmol/L. A secondary evaluation of 1HE–trastuzumab dissociation kinetics was performed using 125I-1HE bound to trastuzumab-immobilized Dynabeads (Fig. 2, bottom right). To prevent rebinding, bound 125I-1HE was dissociated in solutions of either 1 μmol/L T-DM1 or 1 μmol/L unlabeled 1HE, with the percent radioactivity over time fit to a monophasic decline function. Similar rate constants were observed between the T-DM1 and 1HE groups with koff rates of 1.6 × 10−5 sec−1 and 1.7 × 10−5 sec−1, respectively. Trastuzumab-bound 125I-1HE incubated in the control buffer had 62% of the initial bound radioactivity remaining at 66 hours, indicating that dissociated 125I-1HE rebound trastuzumab during the incubations.

Effects of 1HE administration on the plasma pharmacokinetics of trastuzumab and T-DM1

Trastuzumab was administered to non–tumor bearing mice, with and without 1HE, and plasma pharmacokinetics were assessed (Fig. 3, left). Noncompartmental analysis of the plasma pharmacokinetic time profiles indicated there was no significant difference in the AUC(0–10days) for trastuzumab administered alone or with 1HE at doses of 0.1, 1, and 10 mg/kg (Table 1). The clinically approved antibody–drug conjugate of trastuzumab, T-DM1, was also administered with and without 1HE and plasma pharmacokinetics was assessed. Mild precipitation was observed when 1HE and T-DM1 were combined in a single solution; therefore, 1HE was administered at a 10-fold molar excess to T-DM1, 15-minutes after T-DM1 administration. Although the observed precipitation requires further evaluation, coadministration of 1HE with T-DM1 at a dose of 1.8 mg/kg did not significantly impact T-DM1 plasma pharmacokinetics (Fig. 3; Table 1).

Plasma pharmacokinetics of 1HE with and without trastuzumab coadministration

1HE administered to Swiss-Webster mice was rapidly eliminated, with less than 5% of the initial plasma concentration remaining 20 minutes after injection and a terminal elimination half-life of 1.2 hours. The 3- and 6-hour time points were below the lower limit of quantification in plasma (50 ng/mL). Coadministration of 1HE with trastuzumab led to a significant decrease in the elimination of 1HE, with a terminal elimination half-life of 56 hours. The plasma time profile for 1HE alone (1 mg/kg) and 1HE:trastuzumab (0:2:1 ratio) are provided in the right panel of Fig. 3. Plasma time profiles are plotted as the fraction of the initial plasma time point sample remaining (C/C0).

Impact of 1HE coadministration on trastuzumab distribution in SKOV3 xenografts

SKOV3 xenografts from mice administered 2 mg/kg trastuzumab alone and with 1HE (1:2 trastuzumab:1HE molar ratio) were fluorescently stained ex vivo to detect trastuzumab and tumor vasculature. Entire tumor sections were imaged under identical intensities. A representative tumor section from each xenograft bearing mouse that was treated with trastuzumab or trastuzumab:1HE is provided in Supplementary Figs. S2 and S3, respectively. Consistent with previous studies that have assessed trastuzumab tumor distribution at subsaturating doses (13), trastuzumab (green) was restricted around vasculature (red) with only a fraction of the total tumor area staining positive for trastuzumab (Fig. 4A). Tumor sections obtained from mice administered trastuzumab:1HE demonstrated a more homogeneous staining pattern, with a greater percentage of the tumor area staining positive for trastuzumab (Fig. 4B). To enhance visualization of the between-group differences, tumor slices from trastuzumab and trastuzumab:1HE-treated mice were converted to black and white images, with black shading applied to regions demonstrating fluorescence exceeding a threshold of two times background (Fig. 4C and D). Nine tumor slices from three xenografts were analyzed quantitively per group, with results provided in Table 2. 1HE coadministration significantly increased the percent of the tumor area that stained positive for trastuzumab from 26.52% (SD: 8.11%) for trastuzumab alone to 43.32% (SD: 11.42%) for trastuzumab:1HE. The mean fluorescence intensity (MFI) was not significantly different between the groups, whereas the MFI for all pixels two times above background was significantly higher for the trastuzumab-only group at 34 MFI (SD: 5) versus 27 MFI (SD: 3) for trastuzumab:1HE. This observation is consistent with 1HE coadministration leading to an equivalent mass of trastuzumab being spread over a greater area. A MATLAB algorithm was used to obtain the mean distance of all tumor pixels from vasculature (penetration distance limit) and the mean penetration distance of trastuzumab-positive pixels from the vasculature. The trastuzumab and trastuzumab:1HE groups had similar penetration limits of 68.60 μm (SD, 15.65) and 64.54 μm (SD, 5.04), respectively. 1HE coadministration significantly increased the penetration distance for trastuzumab-associated pixels that had a fluorescence intensity two times background from 41.30 μm (SD, 6.70) to 58.24 μm (SD, 5.40) and the penetration distance weighted to the pixel fluorescence intensity from 39.38 μm (SD, 5.89) to 51.51 μm (SD, 5.15). Figure 4E shows the fluorescence staining intensity of trastuzumab pixels as a function of distance from the nearest vasculature pixel. The trastuzumab and trastuzumab:1HE groups have similar fluorescence intensities up to 30 μm, whereas the trastuzumab:1HE tumors have greater fluorescence intensities between 30 μm and 250 μm from the vasculature.

Impact of 1HE coadministration on T-DM1 efficacy in NCI-N87 xenograft–bearing mice

T-DM1 is effective when occupying only a fraction of available binding sites on the gastric carcinoma cell line NCI-N87 (28). NCI-N87 xenograft–bearing mice were administered T-DM1 at a dose of 1.8 mg/kg with and without 1HE to assess the impact of 1HE on T-DM1 efficacy. NCI-N87 has been reported to be resistant to trastuzumab monotherapy (28); therefore, trastuzumab was included as an additional control group for model validation. Resulting tumor growth and survival curves are shown in the left and right panels of Fig. 5, respectively. Trastuzumab did not significantly extend lifespan in comparison to the control group (P = 0.68). T-DM1 alone did not significantly improve survival from the saline group (P = 0.033) or the trastuzumab group (P = 0.27). T-DM1 coadministered with 1HE had a significant increase in survival from T-DM1 alone (P = 0.005) and both the trastuzumab (P = 0.004) and saline groups (P < 0.0001).

Here we describe a strategy to overcome the BSB for trastuzumab through competitive inhibition of HER2 binding. The BSB has been implicated as a primary obstacle to therapeutic antibody distribution within solid tumors. Despite the BSB being first characterized in the early 1990s (16, 19), this barrier remains a significant challenge. Coadministration of a transient inhibitor of antibody–antigen binding was hypothesized to provide the distributional advantage of an untargeted antibody with the tumor selectivity of a high-affinity antibody. Trastuzumab was chosen as a model antibody for experimental validation of the competitive inhibition strategy. Trastuzumab is widely used for the treatment of breast and gastric cancer, and ado-trastuzumab emtansine and trastuzumab deruxtecan are FDA-approved antibody–drug conjugates. In addition, trastuzumab has been previously shown to have limited tumor penetration due to high-affinity HER2 binding (13, 18). The competitive inhibitor 1HE is a camelid single-domain antibody (VHH) that was reported by Alvarez-Reuda and colleagues, in efforts to generate a HER2 vaccine (31). Using in vitro binding assays, we identified 1HE as a lead inhibitor for the competitive inhibition strategy. SPR and radiolabeled dissociation studies indicate 1HE-bound trastuzumab with a dissociation half-life between 12 to 27 hours, and that 1HE inhibited trastuzumab binding to cells that overexpress HER2.

Several pharmacokinetic assumptions of our competitive inhibition hypothesis required experimental validations. First, it was assumed trastuzumab's plasma pharmacokinetics are not altered by 1HE. In the early development of the competitive inhibition strategy, our laboratory observed that soluble carcinoembryonic antigen (CEA) increased the elimination of T84.66, leading to a two-fold decrease in T84.66 tumor exposure (34). This is consistent with the observation that shed mesothelin significantly decreased the efficacy of an anti-mesothelin immunotoxin (35), despite simulations predicting an increase in immunotoxin efficacy with shed antigen due to improved tumor distribution (36). Plasma pharmacokinetic investigations in mice, shown here, indicate trastuzumab and T-DM1 coadministered with 1HE have equivalent plasma pharmacokinetics as the free antibody. The second pharmacokinetic assumption was that the in vivo dissociation of 1HE from trastuzumab is consistent with the binding kinetics obtained through SPR and radiolabeled dissociation studies. This assumption is critical as a long half-life of inhibition is necessary for trastuzumab to extravasate and diffuse to poorly vascularized regions prior to 1HE dissociation. If 1HE were to dissociate from trastuzumab faster in vivo than in vitro, for example, due to plasma instability of 1HE, then significant enhancements in trastuzumab distribution would not be obtained. The observed terminal half-life of trastuzumab in Swiss-Webster mice was 12.6 days, which is much longer than the binding half-life of 1HE to trastuzumab (between 12 and 27 hours, based on in vitro binding assays). 1HE administered with trastuzumab had a terminal half-life of 57 hours, far greater than the half-life of 1HE administered alone. The observed terminal plasma half-life of 1HE administered with trastuzumab exceeds the binding dissociation half-life due to the rebinding of 1HE and trastuzumab in vivo.

Fluorescence microscopy is one of the most common techniques used for the evaluation of antibody distribution in tumors (13, 15, 17, 28). A limitation of fluorescence microscopy is the potential for bias resulting from manual selection of tumor regions. Several studies have limited user bias through imaging of entire tumor slices and/or quantitative image analysis. Rhoden and colleagues developed a MATLAB program that analyzed entire tumor sections and reported antibody fluorescence as a function of distance from the nearest blood vessel (15). Lee and colleagues used a custom image analysis algorithm in the Image-Pro software to evaluate the impact of antibody dose and time after administration on the tumor penetration of trastuzumab and cetuximab (13). Here, we analyzed entire tumor sections from SKOV3 xenograft bearing mice administered trastuzumab or trastuzumab:1HE, using a combination of ImageJ and an in-house MATLAB algorithm. 1HE coadministration led to significant increases in the percent of the tumor section that stained positive for trastuzumab [26.52% (SD, 8.11) to 43.32% (SD, 11.42)] and the penetration distance of trastuzumab from vasculature [41.30 μm (SD, 6.70) to 58.24 μm (SD, 5.40)]. The values for the trastuzumab:1HE-treated tumors are likely close to the upper limit. The maximum percent of the tumor area that can stain positive for trastuzumab is equal to the fraction of the tumor volume composed of antigen-expressing tumor cells. The tumor interstitial space has been reported to be between 20% and 60% of the total tumor volume (37); therefore, it is reasonable to assume the 43% positive staining area for the trastuzumab:1HE group is close to the cellular fraction of the tumor slice. The upper limit for trastuzumab's penetration distance is equal to the mean distance of all tumor pixels from the vasculature, which was 68.60 μm (SD, 15.65) and 64.54 μm (SD, 5.04) for the trastuzumab and trastuzumab:1HE groups. As a percent of the maximum penetration distance, the trastuzumab group was 61% while the trastuzumab:1HE group was 90%. In this study, both functional and collapsed tumor vessels were stained; as a result, the true penetration limit is likely larger than the listed values, as only 10% to 50% of tumor vasculature is functional (38). Therefore, although 1HE significantly improved trastuzumab's penetration distance, the increase may be more dramatic than what the image analysis values suggest.

Antibody–drug conjugates can efficiently kill high antigen–expressing tumor cells, even when only a fraction of cellular antigens are occupied, due to the potency of the drug payload (39). Recently, it was predicted through mathematical modeling that T-DM1 with a lower drug–antibody ratio (DAR) would be more effective than a higher DAR due to the distribution benefit gained by spreading an equivalent mass of cytotoxic drug over a higher antibody dose (27). To validate this prediction, T-DM1 was given with free trastuzumab (effectively lowering the DAR) to mice bearing trastuzumab-resistant NCI-N87 xenografts (28). T-DM1 given alone was restricted to the perivasculature, whereas T-DM1 given with carrier trastuzumab was homogenously distributed, leading to an improvement in the antitumor effect of T-DM1 (28). Singh and colleagues evaluated the trastuzumab/T-DM1 coadministration approach in multiple xenograft models and with multiple ratios of trastuzumab to T-DM1 (29). Trastuzumab coadministration with T-DM1 resulted in a synergistic interaction in mice bearing NCI-N87 xenografts; however, a less than additive effect was observed with trastuzumab coadministration in mice bearing the low HER2–expressing cell line MDA-MB-453 (29). Ponte and colleagues applied the coadministration approach to an anti-folate receptor alpha antibody conjugated to DM4 or to a potent DNA alkylator in multiple xenograft models using multiple ratios of mAb:ADC (40). Enhancement of ADC efficacy was dependent on the tumor antigen expression, payload potency, and on the ratio of unconjugated mAb:ADC (40). It is appreciated that using a carrier dose of unconjugated antibody to increase ADC efficacy is difficult to implement in the clinic (28, 29, 30, 40). Patient-specific ratios of unconjugated antibody to ADC would be required due to patient-to-patient variability in HER2 receptor number, which can be difficult to quantify using current IHC scores. Relative to the approach of overcoming the BSB for ADC with coadministration of saturating doses of “naked” antibody, use of anti-idiotype inhibitors, such as 1HE, provides advantages. First, the time course of inhibition of ADC binding is primarily dictated by the dissociation half-life of the anti-idiotype inhibitor and obviates the need for patient-specific optimization of mAb:ADC dosing ratios. Second, optimal dosing of naked antibody is highly dependent on tumor characteristics (size, vascularity) and, in situations where multiple tumors are present with varying size (e.g., large tumors and smaller metastases), it may be impossible to promote ADC distribution in large tumors without completely inhibiting ADC binding in small tumors (28). There is no similar concern relating to the use of anti-idiotype inhibitors to overcome the BSB, as the dissociation half-life of the inhibitor may be controlled to be far shorter than the plasma elimination half-life of the ADC.

The competitive inhibition approach is analogous to the probody approach, developed by CytomX, in which an antibody paratope is masked by a covalently linked peptide that contains a protease recognition sequence (41, 42). Probodies improve the tumor selectivity of antibody therapy by limiting antibody binding to antigens that are expressed in healthy tissues through tumor-selective activation following protease cleavage of the masking agent in the tumor interstitial space (41, 42). Probodies may facilitate improved tumor penetration, as masked antibodies can diffuse greater distances prior to protease-mediated unmasking; however, to our knowledge, enhanced tumor penetration of probodies relative to their parent mAb has not been thoroughly investigated. In addition, in contrast to the enhanced efficacy that is observed with free mAb coadministration and our competitive inhibition strategy, the efficacy of probody–drug conjugates has been reported as being equivalent to the parent ADC (42). A key difference between the two strategies is the probody approach is dependent on tumor protease activity, whereas the competitive inhibition approach is independent of tumor physiology. Tumor protease expression is variable between patients and tumor types (43, 44); therefore, the cleavage site of the masking sequence needs to be matched to the protease activity of the tumor (41). In a phase I/II clinical trial with the probody–drug conjugate CX-2009, the observed unmasked fraction of CX-2009 in a panel of patient tumor biopsies varied between 3% and 53% (45). In contrast, the competitive inhibition strategy is primarily time dependent and is not expected to vary significantly from patient to patient. Unlike probodies, coadministered competitive inhibitors are not expected to decrease the on-target, off-site binding of an antibody therapy as competitive inhibitor dissociation occurs at the same rate in healthy tissues as the tumor space. From a commercial standpoint, the probody strategy is attractive as it requires the development of a single entity. In contrast, if the competitive inhibition approach is applied to a new antibody therapy, this would require the development of two entities (antibody/inhibitor). Therefore, the competitive inhibition strategy may best apply to already approved therapies (i.e., T-DM1) where the competitive inhibitor can be considered as an adjuvant. The commercial development of an anti-trastuzumab inhibitor is particularly attractive as there are two trastuzumab ADCs that are FDA approved (ado-trastuzumab emtansine, trastuzumab deruxtecan) and a third in phase III clinical trials (trastuzumab duocarmazine; ref. 46).

Although the effects observed following 1HE treatment are quite encouraging, we hypothesize that the results are far from optimal. Further improvements in tumor penetration of trastuzumab and efficacy of T-DM1 may be obtained through the optimization of 1HE affinity and dosing ratios. Mechanistic mathematical modeling may be applied to identify ideal inhibitor characteristics (e.g., optimizing the kinetics of inhibitor–antibody binding). As shown in our prior publications (32, 47), our physiologically based mechanistic mathematical models accurately predict the plasma and tissue disposition of antibodies, including nonlinear dose-dependent mAb disposition in tumors and in human patients. The mechanistic nature of the models facilitates consideration of physiological variables (e.g., tumor size, antigen density, internalization kinetics) and drug characteristics (e.g., affinity, dissociation rate constants) and, thus, enables the in silico exploration of relationships between inhibitor/mAb characteristics and metrics of interest (e.g., tumor disposition, tumor selectivity, time-averaged receptor occupancy).

The work shown here presents a new strategy to bypass the BSB and improve antibody tumor distribution, without requirements of altering the native structure, affinity, or dosing protocol of the antibody. Transient competitive inhibition is a unique and elegant strategy that we believe can be easily adapted to any antibody therapeutic directed against solid tumor antigens. We have demonstrated competitive inhibition can improve trastuzumab distribution in solid tumors and improve T-DM1 efficacy in a mouse xenograft model.

B.M. Bordeau reports a patent for PCT/US2020/050159 pending. J.P. Balthasar reports grants from NIH/NCI during the conduct of the study; grants from AbbVie, CSL-Behring, Genentech, Janssen, Merck, and Roche; grants and personal fees from Amgen, Eli Lilly, and Sanofi, personal fees from Pfizer; and a patent for PCT/US2020/050159 pending. No disclosures were reported by the other authors.

B.M. Bordeau: Conceptualization, formal analysis, investigation, methodology, writing–original draft, writing–review and editing. Y. Yang: Investigation, methodology. J.P. Balthasar: Conceptualization, supervision, funding acquisition, methodology, writing–review and editing.

The authors thank Mason McComb for his assistance with the tumor distribution algorithm. This work was funded by the NIH/NCI (grants CA204192 and CA246785).

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.

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