Purpose: Noninvasive and quantitative tracking of CD8+ T cells by PET has emerged as a potential technique to gauge response to immunotherapy. We apply an anti-CD8 cys-diabody, labeled with 64Cu, to assess the sensitivity of PET imaging of normal and diseased tissue.
Experimental Design: Radiolabeling of an anti-CD8 cys-diabody (169cDb) with 64Cu was developed. The accumulation of 64Cu-169cDb was evaluated with PET/CT imaging (0, 5, and 24 hours) and biodistribution (24 hours) in wild-type mouse strains (n = 8/group studied with imaging and IHC or flow cytometry) after intravenous administration. Tumor-infiltrating CD8+ T cells in tumor-bearing mice treated with CpG and αPD-1 were quantified and mapped (n = 6–8/group studied with imaging and IHC or flow cytometry).
Results: We demonstrate the ability of immunoPET to detect small differences in CD8+ T-cell distribution between mouse strains and across lymphoid tissues, including the intestinal tract of normal mice. In FVB mice bearing a syngeneic HER2-driven model of mammary adenocarcinoma (NDL), 64Cu-169cDb PET imaging accurately visualized and quantified changes in tumor-infiltrating CD8+ T cells in response to immunotherapy. A reduction in the circulation time of the imaging probe followed the development of treatment-related liver and splenic hypertrophy and provided an indication of off-target effects associated with immunotherapy protocols.
Conclusions: 64Cu-169cDb imaging can spatially map the distribution of CD8+ T cells in normal organs and tumors. ImmunoPET imaging of tumor-infiltrating cytotoxic CD8+ T cells detected changes in T-cell density resulting from adjuvant and checkpoint immunotherapy protocols in our preclinical evaluation. Clin Cancer Res; 24(20); 4976–87. ©2018 AACR.
Noninvasive molecular imaging techniques such as PET can provide the required specificity to distinguish immune system components in living organisms over the course of disease development, progression, and treatment. In this study, an anti-CD8 cys-diabody was labeled with 64Cu and used to study tissue-specific differences in immune cell density between mouse strains, within each mouse, and with response to treatment. The study presented here shows that immunoPET can be applied to map CD8+ T-cell density and suggests that this technique can be applied to a range of basic science and translational therapeutic applications. With the rapid proliferation of immune therapeutic strategies, such imaging techniques can play a key role in the design and evaluation of treatment protocols. Importantly, we detect dramatic changes in the liver, spleen, and tumor, demonstrating the importance of systemic, noninvasive imaging of efficacy and a potential role in evaluating side effects and toxicity. Most importantly, this new imaging probe facilitates serial imaging of T-cell distribution over the course of the treatment.
Immune responses are complex, involving multiple organs and tissues, and featuring a spectrum of cell types, including the innate and adaptive arms of the immune system. Current approaches for monitoring immune responses are powerful yet limited (1, 2). For example, blood cells and biomarkers can provide a wealth of information on immune status and responses, using techniques such as highly multiplexed flow cytometry, genomic/transcriptomic/proteomic profiling of immune cell subsets, and equally sophisticated assessment of soluble biomarkers (cytokines and other serum markers, circulating DNA, exosomes, etc.). However, analysis of blood and serum markers provides little specific information regarding spatial localization and interaction of key immune effector cells in situ. Instead, tissues obtained from limited clinical biopsies, or at necropsy in preclinical models, provide materials for analysis. In contrast, sensitive, noninvasive molecular imaging techniques such as PET can provide the required specificity to distinguish immune system components in living organisms over the course of disease development and progression, and during therapies that trigger immune responses (3, 4).
Checkpoint inhibitors are particularly promising components of current therapeutic strategies for cancer treatment (5–7). Monotherapeutic clinical trials with immune checkpoint inhibitors, such as antiprogrammed cell death protein-1 (αPD-1), antiprogrammed death-ligand1 (αPD-L1), and anticytotoxic T lymphocyte–associated protein 4 (αCTLA-4) have shown objective response rates from 5% to 60% in various solid cancers (8–11). Other immune checkpoints (e.g., TIM3, PD-L2, BTLA, LAG-3, TIGIT; ref. 12) and many costimulatory checkpoint molecules (e.g., ICOS, ICOSL, OX40, 4–1BB, CD27, CD28) have been discovered and are being developed as new drugs (13). Patient response remains limited in tumors lacking a robust T-cell infiltrate, and strategies to enhance the T-cell density are under evaluation (14). Multiple strategies to enhance response have been proposed, including additional systemic chemotherapies (15–17) or immunotherapies (18, 19) and focal therapies such as radiation or ablation (20–25). Preclinical models suggest that generating a robust antitumor innate immune activation may be necessary to overcome tumor-mediated immunosuppression. In particular, Toll-like receptor (TLR) activation yields increased antigen retention and results in more effective induction of CD8+ T-cell responses (26). In preclinical animal studies, combining checkpoint inhibitors with TLR9 agonists, such as CpG-oligodeoxynucleotides (CpG-ODN), enhanced the therapeutic response (27, 28).
Given the many emerging therapeutic options, noninvasive differentiation between responders and nonresponders in early treatment is important. Simply monitoring tumor size is a poor early indicator of response; efficacious therapy may increase tumor diameter due to enhancement of the tumor immune-infiltrate. An ideal monitoring technique for patients receiving immunotherapy would measure the immune response itself, and CD8+ T cells are of particular interest. The presence of tumor-infiltrating CD8+ T cells has in fact been suggested as a prognostic tool in colon cancer (29), non–small cell lung cancer, (30), ovarian cancer (31, 32), and melanoma (33). ImmunoPET, which combines the specificity of antibodies with the imaging advantages of PET, is therefore an attractive option. PET imaging of CD8+ T cells in a murine model (34) has been accomplished using a 64Cu-radiolabeled minibody (Mb, 80 kDa) engineered to selectively bind to CD8+ T cells. In addition, lymphoid organs have been visualized using a cys-diabody (cDb, 55 kDa) labeled with89Zr (t1/2 = 78.4 hours) and engineered for renal (rather than liver) clearance (35). With the 89Zr-malDFO-169cDb imaging probe, preclinical imaging detected intratumoral CD8+ T-cell responses to checkpoint immunotherapy (36). Other investigations have recently suggested PD-1 expression on CD8+ T cells as a prognostic biomarker in pancreatic ductal adenocarcinoma and imaging techniques to map T-cell markers are in development (37). Monitoring CD8+ T-cell density and phenotype is possible by biopsy, but biopsies cannot map the spatial heterogeneity or detect changes in localization of CD8+ T cells with time. PET imaging strategies can also inform biopsy by guiding tissue sampling to regions of enhanced or reduced T-cell density.
Here, we radiolabeled a 169cDb probe, which specifically targets CD8+ T cells, with 64Cu (t1/2 = 12.7 hours) and applied PET to image and quantify the CD8+ T-cell population in living subjects. Specifically, we sought to determine the accuracy and sensitivity of PET imaging in mapping of the normal endogenous T-cell distribution within various tissues, in quantification of the variability in T-cell distribution between subjects, in the detection of treatment-related hypertrophy associated with immunotherapy protocols, and in spatially mapping T-cell density over the course of immunotherapy.
Materials and Methods
64CuCl2 was purchased from Washington University School of Medicine (MIR Cyclotron Facility, St Louis, MO).
Metal-free ammonium citrate and sodium hydroxide were purchased from Sigma-Aldrich and prepared as a solution in double-distilled water. Centrifugal spin columns were purchased from Bio-Rad (Bio-Spin 6, MWCO <6 kDA). Dulbecco's PBS (DPBS, 1×) without calcium and magnesium was purchased from Thermo Fisher Scientific. CpG oligonucleotide 1826 was purchased from InvivoGen and anti–PD-1 (αPD-1) mAb was purchased from Bio X Cell (clone RMP1–14).
Modification of 169cDb
The modification of 169cDb followed a previously reported procedure (36). In brief, 169cDb (100–165 μg, MW: 54.1 kDa, 3.0–4.0 mg/mL) was diluted in DPBS (50 μL) and 0.1 mol/L tris(2-carboxyethyl)phosphine (TCEP, 10 equiv. of 169cDb, pH 7.0) in DPBS was added to the 169cDb solution in order to reduce disulfide bonds. Afterwards, the reaction was kept at room temperature for 30 minutes. TETA-maleimide (756.84 g/mol) in DPBS (5 equiv. of 169cDb, 1 μg/μL) was then added to the mixture and incubated for 2 hours at room temperature. The reaction mixture was filtered through a spin column (1,000 × g, 4 minutes) filled with 0.1 mol/L ammonium citrate (pH 7.5). The collected solution was finally eluted via gravity filtration through the spin column filled with 0.1 mol/L ammonium citrate (pH 7.5) to achieve complete buffer exchange. UV absorbance of each collected fraction (0.1 mL/fraction) was measured at 254 and 280 nm to measure the concentration of TETA-169cDb.
64Cu-labeling of TETA-169cDb
All radiolabeling experiments were conducted under a radiation use authorization approved by the University of California, Davis (Davis, CA). 64CuCl2 (82–144 kBq) in diluted 0.1 mol/L HCl was added to a solution of TETA-169cDb (67–104 μg) in 0.1 mol/L ammonium citrate buffer (pH 7.5, 0.1 mL). The pH was adjusted to 6 with 1 mol/L NaOH and kept at room temperature for 30 minutes. Reaction progress was monitored by instant thin layer chromatography (ITLC) with a 0.1 mol/L ammonium citrate eluent (pH 5.5). Following the addition of 0.1 mol/L EDTA (10 μL), the reaction mixture was kept at room temperature for an additional 10 minutes and filtered through a spin column (1,000 × g, 4 minutes) filled with DPBS. The filtered solution was then eluted via gravity filtration through the spin column. The early fraction with the highest radioactivity was diluted with DPBS to prepare the final dose concentration. The diluted solution was sterilized with a 0.2-μm filter. Radiochemical purity was determined with ITLC.
Protein gel electrophoresis
169cDb, TETA-169cDb, and 64Cu-169cDb were loaded into a 20 μL volume with Tris-Glycine SDS buffer and run on a 14% Tris-Glycine gel in an electrophoresis chamber filled with Tris-Glycine SDS buffer under 220 V for 40 minutes. The gel was washed with double-distilled water and protein bands were stained with SafeStain (Invitrogen). The gel was exposed on a Storage Phosphor Screen (Molecular Dynamics) for 6 hours and analyzed on a Storm 860 Imaging System (Amersham Biosciences).
Size exclusion chromatography analysis of 169cDb, TETA-169cDb, and 64Cu-169cDb
169cDb, TETA-169cDb, and 64Cu-169cDb were analyzed by HPLC connected to a size exclusion column (MWCO 1kDa–300 kDa, 300 × 7.8 mm) in a 1 mg/mL flow rate. UV absorbance and radioactivity were detected at 280 nm and with a flow counter, respectively.
Studies with imaging.
All animal experiments were conducted under an animal use protocol approved by the University of California, Davis, Institutional Animal Care and Use Committee. The 64Cu-169cDb evaluation in wild-type FVB, BALB/c, and C57BL/6 mice included 4- to 5-week-old female BALB/c mice (n = 4), 4- to 5-week-old female C57BL/6 mice (n = 4; The Jackson laboratory), and 4- to 5-week-old female FVB/n mice (n = 8: n = 4 in vivo, n = 4 ex vivo only as described in the Supplementary Material; Charles River Laboratories).
For 64Cu-169cDb evaluation in tumor-bearing FVB mice, FVB/n mice (n = 18; Charles River Laboratories) were orthotopically transplanted with syngeneic NDL tumor biopsies (∼1 mm3) bilaterally into the #4 and #9 inguinal mammary fat pads as described previously (38). Tumor sizes were monitored with ultrasound twice a week. Once tumors reached approximately 0.5 cm in the largest tumor diameter (∼3 weeks posttransplantation), mice were randomized into groups including multiple-treatment (MT), single-treatments (ST) and nontreatment controls (NT). For MT (CpG + αPD-1) mice (n = 4), CpG was injected into a single tumor on days 27, 30, and 34 after tumor implantation and αPD-1 was injected on days 27 and 34 followed by PET at day 36. ST studies included a single dose each of CpG + αPD-1 (n = 4 mice), CpG only (n = 3) or αPD-1 only (n = 3) on day 30 after tumor implant followed by PET on day 36. For all groups, αPD-1 was injected intraperitoneally (200 μg in 50 μL) and CpG was injected intratumorally (100 μg in 50 μL) into a single tumor. NT control mice (n = 4) received no immunotherapy treatment. Tumor diameters were measured weekly with standard ultrasound (Siemens Sequoia 512).
Studies with flow cytometry.
From wild-type mice (FVB and BALB/c): axillary (n = 2 nodes/mouse), inguinal (n = 2 nodes/mouse), or cervical (n = 2 nodes/mouse) lymph nodes were harvested from 6-week-old wild-type FVB (n = 4) and BALB/c (n = 4) mice. Flow cytometric analysis of immune cell populations in lymph nodes was performed when all wild-type mice were 6 weeks old.
From FVB mice bearing tumors: Bilateral NDL-tumor mice (n = 11) received a single injection of anti–PD-1 (ST αPD-1, n = 4) or CpG + αPD-1 (ST CpG + αPD-1, n = 4) on day 30 after tumor transplantation, or no treatment (NT, n = 3). For all relevant groups, anti–PD-1 mAb was injected intraperitoneally at a dose of 200 μg and CpG was injected intratumorally into a single tumor at a dose of 100 μg. Flow cytometric analysis of immune cell populations in tumors, inguinal lymph nodes, and spleen was performed on day 37 after tumor transplantation, as described in the Supplementary Methods.
PET/CT scans and biodistribution
Mice were anesthetized with 3.0% isoflurane in oxygen and maintained under 1.5% to 2.0% isoflurane. 64Cu-169cDb (4.15 ± 1.11 μg/animal, 6.78 ± 1.22 MBq/animal) was administered by tail vein injection and PET imaging was conducted on an Inveon DPET small-animal PET scanner (Siemens Medical Solutions USA) for 30 minutes at 0, 5, and 24 hours postinjection. After each PET scan, the animals were moved to a small-animal Inveon MM CT system (Siemens Medical Solutions USA) and a CT scan was conducted to obtain anatomical information for coregistration of PET/CT images. Whole-body activity was measured between scans with a gamma-counter (Capintec, Inc). After the final imaging time point, mice were euthanized by cervical dislocation under deep isoflurane. Blood, urine, and organs (thymus, bone, stomach, intestine, liver, spleen, kidneys, heart, lungs, thigh muscle), lymph nodes (inguinal, axillary, mesenteric, cervical), and tumors were harvested for biodistribution analysis using a 1470 automatic gamma counter (PerkinElmer), after which organs weights were taken on a microbalance. In some cases, organs were briefly scanned to obtain ex vivo PET data and organs were evaluated with histologic stains.
Region-of-interest analysis and time–activity curves
All PET images were reconstructed with the maximum a posteriori (MAP) reconstruction algorithm and analyzed with AsiPro software (Siemens Medical Solutions Inc.) and Inveon Research Workspace 4.2 (Siemens Medical Solutions Inc.). Regions of interest (ROI) of bilateral tumors and blood were drawn after the coregistration of PET/CT images. To obtain the time–activity curve (TAC) of blood, blood radioactivity at 0 (30 minutes segmented to 6 frames), 5, and 24 hours were fitted with one-phase decay curve with Prism 6 for Mac OS. Radioactivity density was presented as percent injected dose per cubic centimeter (%ID/cc)
Tissues for microscopic analysis were fixed overnight in 10% buffered formalin and transferred to 70% ethanol the next day. A Tissue-Tek VIP autoprocessor (Sakura) was used to process samples for paraffin embedding. Tissue blocks were sectioned to 4-μm sections and were mounted on glass slides. Samples were then stained with hematoxylin and eosin (H&E) or were processed for IHC using a rat anti-mouse CD8a primary antibody (1:500; 14–0808, eBioscience) or goat anti-mouse PECAM-1 (CD31) primary antibody (1:1,600; SC-1506, Santa Cruz Biotechnology). All IHC was performed manually without the use of an automated immunostainer. Antigen retrieval was performed using a Decloaking Chamber (Biocare Medical) with citrate buffer at pH 6.0, 125°C and pressure to 15 psi. The total time slides were in the chamber was 45 minutes. Incubation with the primary antibody was performed at room temperature overnight in a humidified chamber. Normal goat or horse serum were used for blocking. Biotinylated goat anti-rat (CD8a; 1:500; Vector Labs) and biotinylated horse anti-goat (CD31; 1:1,000; Vector Labs) were the secondary antibodies used with a Vectastain ABC Kit Elite and a Peroxidase Substrate Kit DAB (both from Vector Labs) used for amplification and visualization of signal, respectively. Stained slides were scanned on an AT2 Scanscope (Leica Biosystems) and digital images viewed using the Imagescope program (Leica Biosystems).
Statistical significance was determined with either an unpaired t test with Welch correction or an ordinary one-way ANOVA with Tukey multiple comparison test, which was performed in GraphPad Prism software (Prism 6.0). Statistical significance is presented as *, P ≤ 0.05; **, P ≤ 0.01; ***, P ≤ 0.001; and ****, P ≤ 0.0001.
Labeling and characterization of TETA-169cDb
169cDb was site-specifically modified with TETA-maleimide (Fig. 1A) conjugated to cysteine, as previously demonstrated for nanoparticles (39). Following this step, the chelator-to-protein ratio of TETA-169cDb, as calculated from the peak intensity of MALDI mass, was 1.3:1 (Supplementary Fig. S1). Recovery yield of TETA-169cDb after two in situ isolations using a spin column was 74% ± 12%. Incorporation of 64Cu into isolated TETA-169cDb in citrate buffer gave 64Cu-169cDb at a yield of 66% ± 9% (n = 4, decay corrected) and a radiochemical purity of >99% in ITLC. Specific activity of 64Cu-169cDb was 1.77 ± 0.60 MBq/μg at the end of synthesis. SDS-PAGE gel electrophoresis of 169cDb (Fig. 1B, lane 1), TETA-169cDb (Fig. 1B, lane 2), and 64Cu-169cDb (Fig. 1B, lane 3 and 3a) demonstrated that 169cDb was reduced and modified to TETA-169cDb, as shown by the slightly higher molecular weight band of TETA-169cDb (lane 2) compared with that of 169cDb at approximately 25 kDa (lane 1). Autoradiography showed both monomeric and dimeric forms of 64Cu-169cDb (Fig. 1B, lane 3a). The elution profiles (Fig. 1C) of 169cDb (top), TETA-169cDb (middle), and 64Cu-169cDb (bottom) from the size exclusion column showed that the divalent diabody was not disrupted after modification and 64Cu labeling.
64Cu-169cDb in wild-type FVB, BALB/c, and C57BL/6 mice depicts strain variation in CD8+ T-cell distribution in lymph nodes and gut
CD8+ T-cell imaging was first evaluated in FVB, BALB/c, and C57BL/6 mice of similar age and body weight (Supplementary Table S1) following intravenous injection of 3.72 ± 0.30 μg of 64Cu-169cDb (7.46 ± 0.53 MBq/animal). Projected PET/CT images acquired at 24 hours (Fig. 2A) showed that 64Cu-169cDb primarily accumulated in the lymphoid organs [lymph nodes (white arrows), spleen (blue capital S)], kidney (blue capital K), and in the small intestine (yellow capital I and arrow) of all three strains. Pharmacokinetic parameters (K value) were largely similar among the strains (Supplementary Table S2); however, in the lymph nodes (pooled from axillary, inguinal, cervical, and mesenteric lymph nodes), accumulation of 64Cu-169cDb was lower in BALB/c (46.0 ± 13.2 %ID/g) as compared with FVB (68.8 ± 17.3 %ID/g) and C57BL/6 mice (66.0 ± 15.5 %ID/g; Fig. 2B). The differences in the 64Cu-169cDb accumulation as a function of mouse strain were then validated by flow cytometry. The number of T cells (5.43 × 106 ± 1.57 × 106 FVB vs. 2.86 × 106 ± 0.95 × 106 BALB/c, P = 0.0001, Fig. 2C), the fraction of T cells as a percentage of live cells (76.7% ± 5.1% FVB vs. 69.4% ± 3.4% BALB/c, P = 0.0006, Fig. 2D) and the number of CD8+ T cells (1.51 × 106 ± 0.42 × 106 FVB vs. 0.87 × 106 ± 0.30 × 106 BALB/c, P = 0.0004, Fig. 2E) in the pooled nodes were all significantly greater in the FVB as compared with the BALB/c strain. The ratio of diabody accumulation in the FVB versus BALB/c strains assessed with PET was similar to the ratio of the number of CD8+ T cells quantified by flow cytometry (FVB ∼1.5-fold higher than BALB/c in both assays). Furthermore, two reasons for the enhanced accumulation of the diabody in the FVB mice were evident. First, the FVB lymph nodes were larger (5.89 ± 1.07 mg FVB vs. 4.96 ± 1.72 mg BALB/c) and contained a greater number of leukocytes (6.2 × 106 ± 1.8 × 106 FVB vs. 3.6 × 106 ± 1.1 × 106 BALB/c, P = 0.0005). Second, T cells constituted a larger fraction of the leukocytes in the FVB lymph nodes (87% of the leukocytes).
At 24 hours after injection, accumulation of 64Cu-169cDb in the proximal intestinal tract (adjacent to the stomach) was also clearly visualized in the 3D-rotational image of the whole mouse (Supplementary Video S1). Ex vivo PET images of the intestines from FVB mice, acquired after cleaning the intestine lumen, confirmed an intestinal accumulation of 64Cu-169cDb (Supplementary Fig. S2A, Supplementary Method S2). Quantification of radioactivity in specific sections of the intestinal tract using a well counter demonstrated the highest accumulation of 64Cu-169cDb in the duodenum (nearly 10 %ID/g) and a gradual decrease from the jejunum to the ileum (∼3.5 %ID/g; Supplementary Fig. S2B). Radioactivity in both the intestine and in the feces was similar at 5 (5.14 ± 1.20 %ID/g) and 24 (6.07 ± 0.39 %ID/g) hours. Radioactivity is excreted in the feces but also accumulates within the intestinal tract. In an additional study (Supplementary Table S3), we did not clear the intestines of feces, but in either case, the distribution of accumulation was very similar, and the presence of the discrete foci represented by the feces did not preclude imaging of the distribution of T cells. In the study without clearing intestinal contents, 24-hour accumulation in C57BL/6 mice was, for example, approximately 14 %ID/g in the duodenum decreasing to approximately 6 %ID/g in the ileum (Supplementary Table S3).
Results of immunotherapy in NDL tumor-bearing FVB mice
Previously, we investigated tumor infiltration of CD8+ T cells in FVB mice bearing the syngeneic orthotropic neu exon deletion line (NDL) model of breast cancer (40, 41). We found that 7 days of immunotherapy with a TLR9 agonist (CpG-ODN, CpG) and checkpoint inhibitor (anti–PD-1: αPD-1) increased the number of CD8+ T cells in tumors of the CpG + αPD-1–treated group (42, 43). In the current study, we followed a multiple-treatment protocol (MT) of CpG + αPD-1 adapted from our previous tumor-priming studies (42, 43), a single-treatment protocol (ST) of CpG + αPD-1, CpG, or αPD-1, and a control protocol (no-treatment cohort, NT) as indicated in Fig. 3A. In FVB mice bearing bilateral tumors transplanted in the fourth and ninth mammary fat pads, CpG was injected intratumorally into one of the two tumors and αPD-1 was injected intraperitoneally. Tumor size and average body weight in the five experimental groups are summarized in Fig. 3B and Supplementary Table S4 and S5. At day 34 posttransplantation, all treatments significantly reduced growth compared with the nontreated control. The treated tumors ranged in volume from 0.296 to 0.011 cm3 and had a mean volume of 0.076 ± 0.049 cm3. The mean weight of the MT tumors was the smallest among all groups and was significantly smaller than the NT and ST (αPD-1) cohorts (Fig. 3C). Upon hematoxylin and eosin (H&E) staining, the MT protocol resulted in a significant reduction in viable tumor, with extensive necrosis and loss of cell–cell integrity within the lesions. Particularly within the MT-treated tumors, an extensive inflammatory reaction surrounded the lesion (Supplementary Fig. S3). Necrosis was also evident in the directly treated and distant tumors following the ST (CpG + αPD-1) protocol, and in the directly treated ST (CpG) tumors.
Single immunotherapy treatments enhance T-cell density, and enhancement is imaged with 64Cu-169cDb
CD8+ T-cell imaging of NDL tumor-bearing mice after immunotherapy was performed by systemic administration of 64Cu-169cDb (intravenous injection, 4.44 ± 1.35 μg/animal, 6.33 ± 1.34 MBq/animal). The 64Cu-169cDb distribution in FVB mice with bilateral NDL tumors was then assessed for the various treatments. Compared with NT and MT mice (Fig. 4A and B), tumor accumulation of 64Cu-169cDb was enhanced on PET/CT slice images (yellow arrows) in ST mice (Fig. 4C–E) at both 5 and 24 hours. Radioactivity was greatest in the rim of all tumors and was greater in the rim of ST tumors (Fig. 4C–E, bottom transverse images) compared with NT and MT tumors (Fig. 4A and B, bottom transverse images), especially at 24 hours. CD8+ T cells were observed in the tumors of MT mice; however, a significant fraction of the MT tumors was necrotic, without apparent functional vasculature (Supplementary Fig. S3).
Radioactivity of tumors excised at 24 hours was greater in ST mice (CpG + αPD-1: 3.91 ± 0.64 %ID/g, CpG: 3.51 ± 1.08 %ID/g, and αPD-1: 4.54 ± 0.32 %ID/g) than in NT mice (2.43 ± 0.51 %ID/g) and MT mice (1.75 ± 0.60 %ID/g; Fig. 4F; Supplementary Table S7). Thus, the accumulation of the probe increased 1.4- to 1.9-fold in the ST mice compared with the NT mice. We compared the imaging results to estimates of changes in CD8+ T cells obtained by flow cytometry (Fig. 4G). Within the tumor, CD8+ T cells as a fraction of CD45+ cells were 5.1%, 9.5%, and 15.1% in the NT, αPD-1, and CpG + αPD-1–treated groups and therefore increased by 1.9- and 3-fold compared with nontreated tumors, respectively (Fig. 4G). When CD8+ T cells were estimated as a fraction of live cells, the increase was 1.7- and 4.6-fold for αPD-1 and CpG + αPD-1–treated tumors, respectively, as compared with the NT control (data not shown).
At the time of injection, radioactivity (%ID/g and SUV) in the MT and ST (CpG + αPD-1) groups was reduced as compared with the NT group, likely resulting from a reduced blood volume within these treated tumors (Supplementary Fig. S4A and S4D). Results from ROI image analysis of tumors at 5 and 24 hours after 64Cu-169cDb injection (Supplementary Fig. S4B, S4C, S4E, and S4F) were similar to the biodistribution of 64Cu-169cDb in the tumor at 24 hours (Fig. 4F). As a function of time, radioactivity increased between 0 and 5 hours in all treatment groups and decreased between 5 and 24 hours (Fig. 4H). Although not significant, the accumulation of radioactivity in tumors receiving a direct CpG injection was slightly lower than that in the noninjected contralateral tumor of each treated animal (Supplementary Fig. S5).
A comparison of the PET images with CD8a IHC from the MT tumors confirmed the ability of PET imaging to spatially map the regions of necrosis and viable tumor with ongoing CD8+ T-cell infiltration (Fig. 5). Regions of viable tumor T-cell infiltration and with dimensions on the order of 2 mm correspond to regions in the IHC in both the contralateral and CpG-injected tumors. H&E staining of tumors from NT and ST (αPD-1) mice indicate a greater blood volume as compared with tumors treated with CpG (Supplementary Fig. S6, top row). In addition, CD31 staining of tumor vasculature also validated the greater endothelial surface area within tumors from NT mice and ST (αPD-1) mice (Supplementary Fig. S6, middle row). In agreement with the observed tumor accumulation of the 64Cu-169cDb probe, IHC using a CD8+ T-cell staining antibody in tumor tissue confirmed the enhanced infiltration of CD8+ T cells in the tumors of ST mice compared with those of NT mice (Supplementary Fig. S6, bottom row). IHC indicated a greater density of infiltrating CD8+ T cells (arrows) near blood vessels in the tumors from MT and ST mice than in NT mice (Supplementary Fig. S6, bottom row).
Treatment with CpG affects 64Cu-169cDb distribution and pharmacokinetics in lymph nodes, spleen, and liver of NDL tumor-bearing mice
The pharmacokinetics were then assessed through projection imaging, where 64Cu-169cDb accumulation in the lymph nodes (white arrows), liver (blue capital L), and spleen (blue capital S) was apparent (Fig. 6A–E). Most importantly, accumulation of the 64Cu-169cDb was evident in the lymph nodes (Fig. 6A–E, white arrow). High intestinal radioactivity (indicated by capital I and yellow arrows) was observed in NT (Fig. 6A) and ST mice (Fig. 6C–E) but not in MT mice (Fig. 6B). Pharmacokinetic parameters from blood ROI analysis (Supplementary Table S6; Fig. 6F, K value, half-life, and AUC) showed that the blood clearance of 64Cu-169cDb was increased for the MT group (t1/2 = 41.3 minutes, k = 0.0168/minute) as compared with the NT (t1/2 = 63.3 minutes, k = 0.0111/minute) and ST groups [which include 1: CpG + αPD-1 (t1/2 = 59.7 minutes, k = 0.0116/minute), 2: CpG (t1/2 = 82.2 minutes, k = 0.0084/minute), and 3: αPD-1 (t1/2 = 66.7 minutes, k = 0.0104/minute)]. Slightly higher blood radioactivity in MT mice was observed at 24 hours (Fig. 6G; Supplementary Table S7). As compared with NT and ST mice, PET/CT projection images of MT mice acquired at 5 hours after 64Cu-169cDb administration (left images in all frames) showed a higher intensity in the liver (white capital L; Fig. 6A–E).
The differences in liver and spleen radioactivity resulted at least in part from treatment-related hypertrophy (Supplementary Fig. S7A–S7K). Changes in the spleen morphology as a function of the treatment groups were evident on optical imaging (Supplementary Fig. S7A–S7E) and were confirmed by the ex vivo weight (Supplementary Fig. S7F). For the MT cohort, the spleens were 2.4-fold heavier compared with the NT group (P < 0.01; Supplementary Fig. S7F), and the splenic volume of ST mice (Supplementary Fig. S7C–S7E, and S7F) was similar to the NT group. Total accumulation (%ID) in the spleen at 24 hours did not differ significantly among the groups (Supplementary Fig. S7G). Radioactive density (%ID/g) was enhanced in the spleen of ST mice (CpG + αPD-1: 27.58 ± 2.49 %ID/g, P < 0.0001 and αPD-1: 39.52 ± 5.37 %ID/g, P < 0.01) as compared with the NT mice (19.37 ± 4.55 %ID/g, P < 0.05), confirming the higher splenic image intensity observed in these mice at 24 hours. Splenic radioactive density was reduced in the MT mice (9.28 ± 1.94 %ID/g) as compared with the NT group and single treatments incorporating αPD-1 (Supplementary Fig. S7H; Supplementary Table S7).
The livers of MT mice were also 1.95-fold heavier (2.76 ± 0.38 g) as compared with the livers (1.41 ± 0.10 g) from NT mice (P < 0.01; Supplementary Fig. S7I). Even a single treatment of CpG + αPD-1 resulted in an increased average liver weight relative to NT mice (Supplementary Fig. S7I). The resulting total accumulation (%ID) of radioactivity in the liver was greatly enhanced in the MT group and was enhanced in the ST (CpG + αPD-1) and ST (CpG) groups, each as compared with the NT cohort (Supplementary Fig. S7J). Radioactive density (%ID/g) was enhanced in the liver of ST (αPD-1) mice as compared with the NT group, with a general, but not significant, trend toward enhanced density across the treated groups (Supplementary Fig. S7K; Supplementary Table S7).
The impact of treatment was also evident in liver and spleen histopathology (Supplementary Fig. S8). In the MT cohort, extensive extramedullary hematopoiesis and perivascular accumulation of granulocytes were evident upon liver H&E staining (Supplementary Fig. S8A, top rows). CD8+ T cells infiltrated in greater numbers near liver veins and sinusoids in MT mice as compared with liver tissue from NT mice (Supplementary Fig. S8A, bottom row). The spleens from MT mice contained larger areas of red and white pulp (Supplementary Fig. S8B, top rows). Splenic CD8a staining (Supplementary Fig. S8B, bottom row) showed more CD8+ cells in the periarterial lymphatic sheaths of MT mice than those in the NT mice. H&E and CD8a staining of liver and spleen from MT and NT mice were also examined to determine whether treatment-related remodeling of the liver and spleen was independent of the administration of the imaging probe. H&E images obtained from the liver and spleen of NT mice after the administration of 169cDb confirmed that the hepatosplenomegaly did not result from 169cDb but rather from the acute effect of intratumoral injection of CpG (data not shown).
Lymph nodes in the MT mice were also enlarged (Supplementary Fig. S7L). The total accumulation in lymph nodes from ST mice was enhanced as compared with the NT and MT mice (Supplementary Fig. S7M), and the mean density was greater in the ST, as compared with the NT and MT, mice (Supplementary Fig. S7N).
Tracking radioactivity within the intestines
We also investigated the intestinal radioactivity that was observed in the projected PET/CT images (Fig. 6A–E). The lower accumulation of 64Cu-169cDb in the intestine of MT mice was confirmed by the organ distribution of radioactivity (Supplementary Fig. S9). As we previously observed in the intestines of wild-type mice (Supplementary Fig. S2), 64Cu-169cDb radioactivity in all groups was the highest in the duodenum and gradually decreased from the jejunum to the colon.
Here, we successfully developed 64Cu-169cDb as an immunoPET imaging agent targeting CD8+ T cells. Previously, studies of immunoPET using mAbs used positron emitters, such as I-124 (100.2 hours) and Zr-89 (78.4 hours), which have relatively long half-lives because of the extended blood residual time of mAbs. In comparison, 169cDb engineered from an anti-CD8 antibody circulates for a period of hours in the blood (36). Thus, we developed a labeling method for 169cDb using 64Cu (t1/2 = 12.7 hours). The use of 64Cu reduces radiation exposure compared with 89Zr-DFO and the t1/2 (12.7 hours) of 64Cu was also more suitable than shorter lived PET isotopes (18F or 68Ga). The chelator-to-protein ratio of TETA-169cDb (1.3:1 in our study) was similar to the dye-to-protein ratio (1.5:1) previously achieved with a maleimide-fluorescent dye (36). After labeling with 64Cu, 64Cu-TETA-169cDb retained the CD8+ binding shown in ref. 36 with 89Zr-169cDb. The radiochemical purity of 64Cu-169cDb (>99%) was comparable with that of 89Zr-169cDb.
We then demonstrated that immunoPET imaging after systemic administration of 64Cu-169cDb can be used to (i) detect differences in CD8+ T-cell distribution across normal subjects and in tumor-infiltrating CD8+ T cells within a murine model of breast cancer receiving immunotherapy; (ii) map the distribution of CD8+ T cells within normal tissues such as the intestine; and (iii) visualize the effects of multi-dose immunotherapy on diabody circulation and tumor viability. Most importantly, this new imaging probe facilitates serial imaging of T-cell distribution over the course of the treatment. We compared results acquired following single or multiple treatments with immunotherapy and found that immunoPET can be combined with anatomic imaging to map viable tumor and regions of T-cell infiltration. We previously applied a similar immunotherapy strategy to that used here in ref. 42 and demonstrated enhanced survival was associated with the enhanced CD8+ T-cell infiltration. We have now shown that the imaging strategy accurately quantified the enhanced infiltration.
This technology could in the future be applied to assess CD8+ T-cell infiltration as a function of time and treatment. Biopsy could potentially be directed to regions with enhanced infiltration to further probe the immunocyte populations. In both preclinical and clinical studies, the baseline T-cell infiltration can vary widely; therefore, the ability to noninvasively assess density before and during treatment is important (14, 42).
In addition to the strategy described here, multiple probes are under development for imaging CD8+ T-cell activation, including probes for IFNγ (44) and granzyme B (45). Imaging of T-cell activation is of great interest; however, there are advantages to imaging the infiltration of T cells (instead of or in addition to imaging of activation). First, in our preclinical work, we find that the increase in infiltrating T cells can be quite large with a successful immunotherapy protocol and therefore can provide a sensitive and potentially early biomarker for the success of an immunotherapy regimen. Furthermore, in flow cytometry assays of CpG and αPD-1 therapy (43), the fraction of cells producing IFNγ at a single time point is small (a few percent), and therefore, the sensitivity of a probe of activation may be lower. Second, activation of specific markers can be short lived following a specific immunotherapy regimen, and therefore, the timing of probes for T-cell activation may require optimization for an individual treatment protocol. Therefore, the imaging of infiltration could provide a useful surrogate. In addition, PET imaging strategies that allow for the imaging of multiple targets are also under development and may facilitate imaging of both infiltration and activation in the future. Dual-tracer PET/CT imaging is advancing with new detector and processing capabilities facilitating simultaneous imaging acquisition from multiple targets (46). A lower dose of radioactivity can be used with total-body PET scanners and may allow serial PET scans of infiltrating CD8+ T cells and activation markers (47).
Sensitivity and specificity of the imaging strategy
We evaluated the pharmacokinetics of 64Cu-169cDb in multiple mouse strains (FVB, BALB/c, and C57BL/6) and found that the blood clearance of the probe was similar (Supplementary Fig. S10). The blood radioactivity we observed was also similar to that previously observed in wild-type AKR mice at 22 hours after administration of 89Zr-malDFO-169cDb (36), indicating that the stability of 64Cu-169cDb is comparable with 89Zr-malDFO-169cDb. The accumulation of the 64Cu-169cDb in the pooled lymph nodes (47–86 %ID/g) and the spleen (62–81 %ID/g) was greater than that of 89Zr-malDFO-169cDb in all mouse strains studied (lymph nodes: 37–42 %ID/g, spleen: 23 %ID/g). Furthermore, the muscle accumulation of 64Cu-169cDb diabody was lower in all three strains than that observed with 89Zr-malDFO-169cDb in AKR. Although the lymphatic-to-muscle ratio and detection sensitivity observed here were greater than those reported in the 89Zr-malDFO-169cDb study, the difference in the injected dose (here the dose was lower) precludes a direct comparison of the performance. Blocking studies, included in ref. 36, demonstrated the specificity of the diabody, with a reduction in accumulation in the lymphatic organs and intestine in response to diabody injection.
Using invasive methods, Pinchuk and colleagues reported that the CD8+ T-cell population in the spleen of C57BL/6 mice was greater than in BALB/c mice (48). We similarly observed a reduced accumulation of 64Cu-169cDb in the spleen, lymph nodes, and intestine of BALB/c mice compared with the other mouse strains tested. We confirmed the differences in CD8+ T cells between mouse strains using flow cytometry and validated that approximately 1.5 ratio in diabody accumulation was indicative of the cell populations.
In humans and mice, the CD8+ lymphocyte population in the gut is highest in the proximal small intestine (49, 50). We also observed that intestinal radioactivity (%ID/g at 24 hours) decreased from the duodenum to the ileum, which implies that mapping of the T-cell distribution within the intestine is feasible and a 64Cu-169cDb probe could potentially be used to investigate CD8+-related bowel disease (51, 52).
Effects of multi-dose immunotherapy on perfusion and tumor viability
Because of the low objective response rate of single checkpoint inhibitor therapy, more recent therapies use combination protocols including multiple chemotherapy or immunotherapy components (53–55), surgical removal and/or ablation of the tumor by radiation (56, 57) or ultrasound therapy (42). Here, our immunoPET study sought to quantify tumor-infiltrating CD8+ T cells after single or combination immunotherapy with CpG and αPD-1. CpG triggers an immunomodulatory response that expands CD8+ T cells (58, 59) and αPD-1, an immune checkpoint inhibitor, increases the frequency of tumor-infiltrating CD8+ T cells (60, 61). In our results from CD8 IHC staining of tumors, CD8+ T cells were more evident in tumors from treated mice than in tumors from NT mice. 64Cu-169cDb accumulation measured by gamma counter and ROI analyses of tumors at 5 and 24 hours also demonstrated higher infiltration of CD8+ T-cell populations in tumors from ST mice as compared with NT mice.
H&E and CD31 staining demonstrated necrosis and a reduced vascular volume in all CpG-treated tumors relative to contralateral tumors. Although the accumulation of 64Cu-169cDb between CpG-treated and contralateral tumors was not significantly different, the trend toward a reduced accumulation of 64Cu-169cDb in CpG-treated tumors versus contralateral tumors could also be related to antivascularization and the necrosis of the directly treated tumors observed on H&E. Furthermore, the tumor accumulation of 64Cu-169cDb in ST mice with αPD-1 was higher than in ST mice treated with CpG + αPD-1 (P < 0.05). This may result from the longer circulation time of 64Cu-169cDb in ST (αPD-1) mice.
Multiple treatments with CpG + αPD-1 slowed tumor growth and enhanced the IHC estimates of the CD8+ T-cell population in the tumor margin as compared with the NT cohort. The total accumulation of 64Cu-169cDb in the MT group was similar to that of the NT group. The reason for this, we believe, is 2-fold. First, multiple treatments with CpG + αPD-1 resulted in extensive tumor necrosis with a decrease in the blood volume within the treated tumors. A reduction in microvessel density (62, 63) has been reported previously with such a protocol. Here, we demonstrate that PET imaging can map the regions of necrosis and of enhanced accumulation, and this spatial mapping will be critically important in the interpretation of the treatment efficacy. Second, CpG treatment (58, 64) caused hypertrophy of the liver and spleen, which reduced the circulation time of 64Cu-169cDb and therefore decreased the potential accumulation in target sites. This is particularly evident in the reduced accumulation within lymph nodes following the MT protocol. In fact, the AUC of the blood activity for MT-treated mice was 68%, 74%, and 74% of AUC of that for the ST αPD-1, CpG, CpG + αPD-1–treated mice. Because of the combination of the decrease in blood circulation of the probe, the tumor necrosis, and the reduction in the vascular volume, the tumor accumulation of 64Cu-169cDb in MT mice was 38%, 49%, and 44% of that observed for ST (αPD-1), (CpG), and (CpG + αPD-1) mice, respectively. Liver hypertrophy and the resulting changes in circulation and accumulation of immunotherapeutic agents have implications for therapeutic efficacy. Changes in the diabody pharmacokinetics resulting from treatment with CpG are likely to be replicated with other immunotherapy-related antibodies. The imaging agent described here has the potential to highlight such changes and thus detect off-target systemic effects. Future human studies of immunotherapy protocols with imaging probes must account for the impact of tumor necrosis and liver hypertrophy when present.
The advantages of imaging methods to track specific immune cell populations include the ability to spatially map the distribution of a specific population and to repeat the study over time. However, using PET, one or at best two populations can be assessed. Other markers of response include multiplexed IHC, circulating cytokines, flow cytometry, and RNA sequencing of samples obtained from tumor or blood can provide substantial additional information regarding response. Thus, multiple techniques may be required to provide sufficient information to fully assess response. Furthermore, additional imaging studies of alternate immunotherapy protocols are required in order to determine where the CD8+ T-cell diabody is best applied.
We conclude that the 64Cu-169cDb has the potential to quantify CD8+ T-cell density within and between subjects. This imaging agent can be applied to monitor the effects of immunotherapy on the distribution of T cells within a therapeutic regimen. Early-stage immunoPET imaging of tumor-infiltrating cytotoxic CD8+ T cells, particularly in combination with imaging of tumor necrosis, may aid in the assessment of efficacy. Our results demonstrate that toxicity inducing a hypertrophy of liver and spleen must be considered in the analysis of immunoPET imaging data. Assessment of liver and spleen hypertrophy on anatomic imaging can inform the interpretation of such data.
Disclosure of Potential Conflicts of Interest
A.M. Wu is a consultant/advisory board member for ImaginAB, Inc., Blueline Biosciences, and Avidity Nanomedicines. No potential conflicts of interest were disclosed by the other authors.
Conception and design: J.W. Seo, M.T. Silvestrini, A.D. Borowsky, A.M. Wu, K.W. Ferrara
Development of methodology: J.W. Seo, R. Tavaré, A.D. Borowsky, K.W. Ferrara
Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): J.W. Seo, L.M. Mahakian, M.T. Silvestrini, S. Tam, E.S. Ingham, A.D. Borowsky, K.W. Ferrara
Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): J.W. Seo, E.S. Ingham, A.D. Borowsky, A.M. Wu, K.W. Ferrara
Writing, review, and/or revision of the manuscript: J.W. Seo, R. Tavaré, L.M. Mahakian, M.T. Silvestrini, S. Tam, E.S. Ingham, A.D. Borowsky, A.M. Wu, K.W. Ferrara
Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): E.S. Ingham, F.B. Salazar, K.W. Ferrara
Study supervision: K.W. Ferrara
This project was supported by NIHR01CA210553 (to J.W. Seo and K.W. Ferrara), NIHR01CA134659 (to M.T. Silvestrini, E.S. Ingham, S. Tam, L.M. Mahakian, and K.W. Ferrara), and NIHR01CA199658 (to E.S. Ingham, S. Tam, L.M. Mahakian, and K.W. Ferrara) and by a pilot grant from the University of California-Davis Center for Molecular and Genomic Imaging (http://bme.ucdavis.edu/cmgi/). A.M. Wu is a member of the UCLA Jonsson Comprehensive Cancer Center (NIH P30 CA 016042). The authors appreciate the assistance of Susannah Bloch in the preparation of the manuscript. This project was also supported by the University of California Davis Flow Cytometry Shared Resource Laboratory and with technical assistance from Bridget McLaughlin and Jonathan Van Dyke. UC Davis core resources are funded from the NCI P30 CA093373 (Cancer Center) and NIH NCRR C06-RR12088, S10 OD018223, S10 RR12964, and S10 RR 026825 grants.
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