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Research ArticleBasic Science Investigation

Noninvasive PET Detection of CD69-Positive Immune Cells Before Signs of Clinical Disease in Inflammatory Arthritis

Emmi Puuvuori, Yunbing Shen, Gry Hulsart-Billström, Bogdan Mitran, Bo Zhang, Pierre Cheung, Olivia Wegrzyniak, Sofie Ingvast, Jonas Persson, Stefan Ståhl, Olle Korsgren, John Löfblom, Fredrik Wermeling and Olof Eriksson
Journal of Nuclear Medicine February 2024, 65 (2) 294-299; DOI: https://doi.org/10.2967/jnumed.123.266336
Emmi Puuvuori
1Science for Life Laboratory, Department of Medicinal Chemistry, Uppsala University, Uppsala, Sweden;
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Yunbing Shen
2Center for Molecular Medicine, Division of Rheumatology, Department of Medicine, Solna, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden;
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Gry Hulsart-Billström
1Science for Life Laboratory, Department of Medicinal Chemistry, Uppsala University, Uppsala, Sweden;
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Bogdan Mitran
1Science for Life Laboratory, Department of Medicinal Chemistry, Uppsala University, Uppsala, Sweden;
3Antaros Medical AB, Mölndal, Sweden;
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Bo Zhang
1Science for Life Laboratory, Department of Medicinal Chemistry, Uppsala University, Uppsala, Sweden;
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Pierre Cheung
1Science for Life Laboratory, Department of Medicinal Chemistry, Uppsala University, Uppsala, Sweden;
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Olivia Wegrzyniak
1Science for Life Laboratory, Department of Medicinal Chemistry, Uppsala University, Uppsala, Sweden;
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Sofie Ingvast
4Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden; and
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Jonas Persson
1Science for Life Laboratory, Department of Medicinal Chemistry, Uppsala University, Uppsala, Sweden;
5Department of Protein Science, Division of Protein Engineering, KTH Royal Institute of Technology, Stockholm, Sweden
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Stefan Ståhl
5Department of Protein Science, Division of Protein Engineering, KTH Royal Institute of Technology, Stockholm, Sweden
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Olle Korsgren
4Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden; and
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John Löfblom
5Department of Protein Science, Division of Protein Engineering, KTH Royal Institute of Technology, Stockholm, Sweden
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Fredrik Wermeling
2Center for Molecular Medicine, Division of Rheumatology, Department of Medicine, Solna, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden;
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Olof Eriksson
1Science for Life Laboratory, Department of Medicinal Chemistry, Uppsala University, Uppsala, Sweden;
3Antaros Medical AB, Mölndal, Sweden;
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Abstract

Rheumatoid arthritis (RA) is the most common inflammatory joint disease, and early diagnosis is key for effective disease management. CD69 is one of the earliest cell surface markers seen at the surface of activated immune cells, and CD69 is upregulated in synovial tissue in patients with active RA. In this study, we evaluated the performance of a CD69-targeting PET agent, [68Ga]Ga-DOTA-ZCAM241, for early disease detection in a model of inflammatory arthritis. Methods: A model of inflammatory arthritis was induced by transferring splenocytes from KRN T-cell receptor transgenic B6 mice into T-cell–deficient I-Ag7 major histocompatibility complex class II–expressing recipient mice. The mice were examined longitudinally by [68Ga]Ga-DOTA-ZCAM241 PET/CT before and 3, 7, and 12 d after induction of arthritis. Disease progression was monitored by clinical parameters, including measuring body weight and scoring the swelling of the paws. The uptake of [68Ga]Ga-DOTA-ZCAM241 in the paws was analyzed and expressed as SUVmean. Tissue biopsy samples were analyzed for CD69 expression by flow cytometry or immunostaining for a histologic correlate. A second group of mice was examined by a nonbinding, size-matched Affibody molecule as the control. Results: Clinical symptoms appeared 5–7 d after induction of arthritis. The uptake of [68Ga]Ga-DOTA-ZCAM241 in the joints was negligible at baseline but increased gradually after disease induction. An elevated PET signal was found on day 3, before the appearance of clinical symptoms. The uptake of [68Ga]Ga-DOTA-ZCAM241 correlated with the clinical score and disease severity. The presence of CD69-positive cells in the joints and lymph nodes was confirmed by flow cytometry and immunostaining. The uptake of the nonbinding tracer that was the negative control also increased gradually with disease progression, although to a lesser extent than with [68Ga]Ga-DOTA-ZCAM241. Conclusion: The uptake of [68Ga]Ga-DOTA-ZCAM241 in the inflamed joints preceded the clinical symptoms in the KRN T-cell transfer model of inflammatory arthritis, in accordance with immunostaining for CD69. [68Ga]Ga-DOTA-ZCAM241 is thus a promising PET imaging marker of activated immune cells in tissue during RA onset.

  • rheumatoid arthritis
  • inflammatory arthritis
  • PET
  • CD69
  • inflammation

Rheumatoid arthritis (RA) affects 0.5%–1% of the global population, making it the most common inflammatory arthropathy worldwide (1). It is a complex autoimmune disease characterized by chronic inflammatory changes, including synovium hyperplasia, hypertrophy, and joint destruction. The chronic inflammation can cause the destruction of cartilage and bone, eventually leading to limitations, disabilities, loss of function, decreased quality of life, and possibly shortened life expectancy, mainly because of increased risk of cardiovascular disease and lymphoma (2,3).

The etiology of RA is linked to a complex combination of genetic and environmental factors. The strongest identified environmental influences are smoking and other forms of lung stress (4). Of the genetic risk factors, the most important for RA development are the shared epitope alleles, which reside in the major histocompatibility complex class II region (5). The major histocompatibility complex class II molecules are expressed at high levels on professional antigen-presenting cells, including dendritic cells, B cells, and macrophages that play a crucial role in adaptive immune responses such as T-cell activation (6,7).

Although cytokine inhibitors can alleviate the symptoms of RA, there is no available cure, making early identification and accurate monitoring of the disease activity the keys to effective personalized treatment to slow disease progression (8). The diagnosis of RA uses a combination of medical history, physical examination, and blood tests of, for example, erythrocyte sedimentation rate, C-reactive protein, rheumatoid factor, and anticyclic citrullinated peptides (9). However, disease progress is not similar in all patients, and the early changes in joint activity might not be detectable in blood samples. Established clinical imaging modalities such as radiographs, CT, ultrasound, and MRI visualize secondary changes in bone and joint structures, which usually occur at later stages of the disease. None of these modalities provide information about molecular alterations or the role of specific immune cells during disease development (10). To overcome these issues, molecular imaging approaches could be used to detect early molecular changes and alterations in the local inflammatory milieu that precede structural changes. PET is a noninvasive molecular imaging modality that is used in clinical routine for detection and staging in the oncologic setting. However, its applications in RA and inflammatory diseases are not widespread, mainly because of the lack of PET probes selective for immune cells. The metabolic PET marker [18F]FDG has been the most widely used so far for imaging of inflammation in RA patients (11,12). [18F]FDG studies have demonstrated the detection and quantification of several types of arthritis activity and displayed uptake in fibroblasts, neutrophils, and macrophages when exposed to the inflammatory cytokines tumor necrosis factor and interleukin 1. However, almost no uptake in T cells has been observed, and in nonsevere and remission patients, the results have been inconclusive (11,12). As a general marker for glucose metabolism, the common limitations of [18F]FDG include nonspecificity and false-positive findings in areas with high metabolic activity, such as the brain, heart, activated muscles, or brown adipose tissue and tumors.

Several other radiotracers, including those targeting macrophages, bone metabolism, vascular adhesion protein 1, angiogenesis, and cell proliferation, have been evaluated in RA (11–14). However, most of these radiotracers have been evaluated only in small patient cohorts or tested only preclinically and thus require further clinical evaluation (13–16). Thus, despite intense efforts in this area, there is an urgent need for PET imaging probes specific for noninvasive detection of immune cell activation in RA.

CD69 is an early activation antigen expressed by immune cells during activation. Limited expression is seen in peripheral blood leukocytes of healthy individuals. In contrast, increased expression is seen in T cells, B cells, and neutrophils in synovial tissue of RA patients, making it a promising target for studying aspects of the adaptive and innate immune reactions during RA onset and progression (17–20). Recently, radiolabeled antibodies directed toward CD69 were described and evaluated as imaging agents for detection of tumor-infiltrating activated immune cells in the oncologic context (21,22). However, antibodies are not ideal PET imaging agents because of their large size and slow clearance. Therefore, we have developed ZCAM241, a small protein based on the Affibody (Affibody AB) molecule scaffold with nanomolar affinity for human and murine CD69 (23).

In this study, we examined the potential of 68Ga-labeled ZCAM241 for early PET detection of activated immune cells in tissue in a mouse model of induced inflammatory arthritis.

MATERIALS AND METHODS

Chemical Synthesis and Radiolabeling of Affibody Molecules

ZCAM241 is an Affibody molecule selected for binding to the extracellular domain of human recombinant CD69 (Supplemental Table 1 [supplemental materials are available at http://jnm.snmjournals.org]) (23,24). The chemical synthesis and the 68Ga radiolabeling of DOTA-conjugated ZCAM241 and the nonbinding, size-matched Affibody molecule DOTA-ZAM106 as the control are described in detail in the supplemental materials.

In Vitro and In Vivo Characterization of [68Ga]Ga-DOTA-ZCAM241

Unlabeled ZCAM241 has been evaluated in detail, such as with respect to affinity toward CD69 (23). DOTA-ZCAM241 labeled with 111In has been studied for in vivo biodistribution and has demonstrated binding to, for example, activated human peripheral blood mononuclear cells (23). Here, we verified that radiolabeled [68Ga]Ga-DOTA-ZCAM241 retained the biodistribution, stability, and binding of previously evaluated radiolabeled analogs (supplemental materials; Supplemental Figs. 1–3).

Adoptive T-Cell Transfer and Joint Evaluation

Experiments used 8- to 12-wk-old sex- and age-matched mice. KRN.B6 mice were generated and provided by Diane Mathis and Christophe Benoist (Harvard Medical School) (25). KRN.B6.CD45.1 mice were generated by crossing KRN.B6 mice with CD45.1 mice (stock number 002014, Jackson Laboratories). TCRb−/−I-Ab+/−I-Ag7+/− mice were generated by crossing B6.TCRb mice (TCRb−/− on C57BL/6 background; stock number 002118) with nonobese diabetic mice (stock number 001976, Jackson Laboratories). Primers used for genotyping are detailed in the supplemental materials. To induce disease, KRN.B6 splenocytes were prepared by pressing the spleen through a 40-µm cell strainer with a 3-mL syringe plunger. Roughly 2 × 107 cells were injected via the tail vein into TCRb−/−I-Ab+/−I-Ag7+/− recipient mice. The severity of arthritis was scored every 2–3 d by clinical examination of each paw and ankle (0, no swelling; 3, maximal swelling), adding up to a total clinical score (0–12) per mouse. The weight of the animals was monitored every 2–3 d. At the end of each experiment, different organs and blood were collected for further analysis.

[68Ga]Ga-DOTA-ZCAM241 PET/CT Imaging of Arthritic Mice

The animal experiments were authorized by the Animal Ethics Committee of the Swedish Animal Welfare Agency and performed according to institutional guidelines (Uppsala University Guidelines on Animal Experimentation, UFV 2007/724) and ARRIVE 2.0 guidelines.

The study design was a longitudinal imaging study to follow each mouse through 4 PET scans over 12 d, from before disease induction and during disease progression. The detailed ethical considerations and the in vivo study design are described in the supplemental materials.

Each mouse (5 female mice; weight, 20–23 g at the start of the study) was imaged by [68Ga]Ga-DOTA-ZCAM241 (target dose of 2 MBq) PET 4 times: before (baseline) and then 3, 7, and 12 d after induction of inflammatory arthritis (Supplemental Fig. 1B). The mice were euthanized after the last PET scan, and biopsy samples were taken.

A control study was conducted separately with the nonbinding Affibody molecule [68Ga]Ga-DOTA-ZAM106, using the same protocols for imaging, disease induction, and monitoring of clinical symptoms as described earlier for [68Ga]Ga-DOTA-ZCAM241. Briefly, [68Ga]Ga-DOTA-ZAM106 was evaluated by PET/CT (target injected dose, 2 MBq; same scanning protocol in 4 female mice; weight, 20–23 g at the start of the control study) at 4 time points (baseline and 3, 7, and 10 d after disease induction).

The PET scanning protocol, the image analysis methodology, and the histologic analysis of postmortem biopsy samples are described in detail in the supplemental materials.

Flow Cytometry

Single-cell suspensions from lymph organs were collected by pressing through a 40-μm cell strainer with a 3-mL syringe plunger. Single cells from the ankle joints of the hind paws were prepared by cutting joint tissue into small pieces in cold phosphate-buffered saline, vortexing, and filtering through a 40-μm cell strainer. Cells were filtered and stained with BioLegend’s CD19-Alexa647 (catalog number 115522), CD45.1-BV605 (catalog number 110738), CD45.2-BV785 (catalog number 109839), TCRβ-BV711 (catalog number 109243), and CD69-PE (catalog number 310905), as well as the Fixable Aqua Dead Cell Stain Kit (catalog number L34965; Invitrogen), for 30 min. After staining, cells were acquired using BD LSRFortessa. Generated flow cytometry standard files were analyzed by FlowJo version 10 (FlowJo).

RESULTS

Progression of Joint Disease

The disease development of the mice was monitored by scoring the swelling of the paws, including the ankle, and measuring the weight of the animals. The clinical score started to increase 7 d after injection of the model (Fig. 1A). Weight decreased 5 d after injection (Fig. 1B), reaching a maximum drop of approximately 10%. IgG anti-glucose phosphate isomerase (GPI) levels were significantly different between baseline and day 12 (Fig. 1C). The uptake in PET images was already visibly increasing on rear paws 3 d after injection (Fig. 2A) and in line with corresponding CD69 staining (Fig. 2B).

FIGURE 1.
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FIGURE 1.

(A) Quantification of joint inflammation (clinical score, 0–12; 0–3 points per paw) as part of characterizing induced joint inflammation in KRN T-cell adoptive transfer model. (B) Weight change presented as percentage of weight at day 0. (C) Serum IgG anti-GPI levels comparing day 0 and day 12. **P < 0.01, by unpaired t test (n = 5). GPI = glucose phosphate isomerase; OD = optical density.

FIGURE 2.
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FIGURE 2.

(A) PET images of [68Ga]Ga-DOTA-ZCAM241 uptake at baseline and 3, 7, and 12 d after injection as inflammatory arthritis developed in single representative individual mouse. Images are normalized to SUV of 0.5 for direct comparison between time points. (B) CD69 immunofluorescence Sytox (Thermo Fisher Scientific) staining of joints of representative animals during matching time points.

[68Ga]Ga-DOTA-ZCAM241 Uptake Increased During Progression of Inflammatory Arthritis

The in vitro and in vivo characterization of [68Ga]Ga-DOTA-ZCAM241 in healthy animals demonstrated suitable biodistribution (Supplemental Figs. 2 and 3A–3C; details in supplemental materials) and retained binding toward CD69 (Supplemental Fig. 3D). These results guided the design of the imaging protocol in the arthritic mice.

The PET images were quantified by calculating the SUVmean of the rear joints. As seen visually in Figure 2, the SUV increased gradually and almost linearly from day 0 (SUVmean, 0.21 ± 0.04, n = 5) to day 3 (SUVmean, 0.69 ± 0.25, n = 5), day 7 (SUVmean, 1.06 ± 0.09, n = 5), and day 12 (SUVmean, 1.53 ± 0.12, n = 5; Fig. 3A). The SUVmean of each mouse is displayed in Figure 3B, where all animals followed similar uptake pattern. Most variation was noticeable at the day 3 time point, where 1 animal (mouse 2; Fig. 3B) exhibited a higher increase in joint uptake than the rest of the animals. The ratio of [68Ga]Ga-DOTA-ZCAM241 uptake to baseline demonstrated a similar increase with time from induction of disease (Fig. 3C). In addition, the ratio of [68Ga]Ga-DOTA-ZCAM241 uptake to baseline demonstrated a positive correlation with the clinical score of the joints (r = 0.82, P < 0.0001; Fig. 3D).

FIGURE 3.
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FIGURE 3.

[68Ga]Ga-DOTA-ZCAM241 uptake expressed as SUVmean (each point represents average and SD of 5 scans) over time in joints either at group level (A) or in individuals (B). Error bars for day 0 time point in A are too small to be visualized. Asterisks indicate significance compared with baseline at day 0. (C) Uptake of [68Ga]Ga-DOTA-ZCAM241 expressed as ratio at each time point compared with baseline in individuals. (D) Correlation of uptake of [68Ga]Ga-DOTA-ZCAM241 in joints with clinical score. ***P < 0.001. ****P < 0.0001. M1–M5 = mouse 1 to mouse 5.

Uptake of the Control Nonbinding Peptide [68Ga]Ga-DOTA-ZAM106 in Inflammatory Arthritis

The ratio of [68Ga]Ga-DOTA-ZAM106 uptake to baseline also increased over time (Supplemental Fig. 4A), although to a lesser extent than for [68Ga]Ga-DOTA-ZCAM241. The correlation between [68Ga]Ga-DOTA-ZAM106 uptake ratio to baseline and clinical score of the joints indicated a positive connection (r = 0.87, P < 0.0001; Supplemental Fig. 4B) but was less pronounced than for [68Ga]Ga-DOTA-ZCAM241. The disease progression in the mice being investigated with the control nonbinding peptide [68Ga]Ga-DOTA-ZAM106 was similar to that monitored by clinical symptoms such as swelling of the paws and weight changes (Supplemental Figs. 4C and 4D). Histology of the joints demonstrated the presence of CD69-positive cells after euthanasia at the day 10 time point (Supplemental Fig. 4D).

Expression of CD69 in the Lymph Nodes Was Higher Than in the Joints

Besides analysis in the joints, CD69 expression levels were analyzed in different cell populations and organs (axillary, brachial, inguinal, mesenteric, and popliteal lymph nodes, as well as the spleen and joints) on day 12. The representative histogram gating is presented as viable singlets in Figure 4A, and quantification of the plots is presented in Figure 4B. The frequency of B cells and T cells in the CD69-positive viable singlet gate is shown in Figure 4C, and the quantification of plots is shown in Figure 4D. Fluorescence staining of the lymph nodes at baseline (Supplemental Fig. 4A) and 12 d after injection of arthritis induction (Supplemental Fig. 4B) demonstrated increased expression of CD69, in line with flow cytometry results. [68Ga]Ga-DOTA-ZCAM241 uptake of the right (SUVmean, 3.6 ± 1.09) and left (SUVmean, 3.3 ± 0.72) axillary lymph nodes was strong 12 d after disease induction, higher than the background uptake in muscle (SUVmean, 0.45 ± 0.34; Fig. 4E) and consistent with the presence of CD69-positive cells seen by flow cytometry at the same time point.

FIGURE 4.
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FIGURE 4.

CD69 expression analysis in different cell populations on day 12. (A) Representative histogram plot of CD69 expression in different lymph organs (axillary, brachial, inguinal, mesenteric, and popliteal lymph nodes, as well as spleen and joints). Gate shows viable singlets. (B) Quantification of plots in A, with CD69-positive percentage of viable singlets (n = 3). (C) Representative plot showing frequency of B cells and T cells in CD69-positive viable singlet gate. (D) Quantification of plots in C, with percentage of B cells and T cells in CD69-positive viable singlet gate (n = 3). (E) SUVmean uptake of left and right axillary lymph nodes and muscle at day 12. ***P < 0.001, by ANOVA (n = 5). Axi = axillary; Bra = brachial; Freq. = frequency; Ingu = inguinal, LN = lymph node; Mes = mesenteric; Pop = popliteal; TCRβ = T-cell receptor β.

DISCUSSION

Appropriate diagnosis and prediction of the disease progression of the individual RA patient are fundamental for successful treatment, because the outcome of RA can be vastly heterogeneous. New drugs and treatment modalities, such as emerging biologics, are associated with high costs and potential serious side effects for the patient. An established PET tracer for sensitive detection of activated immune cells in RA could offer prognostic value by identifying subclinical activity in individuals at an early stage of disease development, predicting flares in patients with established disease, and serving as a tool for early monitoring of drug response. Early detection is central to the development of potential preventative and curative treatments. To accomplish this, several immune cell activation markers could be considered potential targets for probes, such as surface markers for T-cell subpopulations (26). Accordingly, PET radiotracers have been developed to enable preclinical in vivo detection of, for example, CD69 (21–23), inducible T-cell costimulator (27), OX40 (28), granzyme B (29), and interferon-γ (30). So far, these techniques have not been applied specifically in models of inflammatory arthritis.

In this study, we wanted to assess PET tracer [68Ga]Ga-DOTA-ZCAM241 uptake in a mouse model of inflammatory arthritis. The model we used is a KRN T-cell transfer model, in which splenic KRN T cells are injected into T-cell–deficient mice. The KRN T-cell transfer model has been reported to be reproducible and show clinical signs of disease onset 7 d after the transfer, with infiltration of macrophages and neutrophils into the joints, as well as cartilage damage and bone resorption. T cells have not been detected in the joints but have been reported to be present in the popliteal lymph nodes (23). Disease severity usually reaches a maximum peak after around 2 wk of induction (23). Similarly, in this study, we observed that the mice developed clinical symptoms in the form of swelling of the joints around day 7, but the average weight decreased a little earlier, on day 5. The uptake of [68Ga]Ga-DOTA-ZCAM241 in the joints was already visually apparent on PET images 3 d after induction of the model, which is earlier than the clinical signs started appearing. The largest variability in SUV uptake between individual animals was also on day 3, which could refer to the variation in magnitude of the initial immune reaction. Otherwise, the animals followed approximately the same pattern of disease progression. [68Ga]Ga-DOTA-ZCAM241 uptake gradually increased with time, which is consistent with the increasing severity of the inflammation and the correlation between SUV ratio and clinical score.

The uptake of [68Ga]Ga-DOTA-ZCAM241 was low in or absent from the joints before disease induction (SUVmean, ∼0.2; Fig. 3A), but it increased almost 10-fold 12 d after injection (SUVmean, ∼1.5). The uptake of [68Ga]Ga-DOTA-ZCAM241 in the lymph nodes on day 12 was even stronger, with SUVmean greater than 3 (Fig. 4E). However, because of the small size of the animal model compared with the resolution of the scanner, as well as the proximity of high focal uptake in the kidneys, it was difficult to measure the CD69 signal from the lymph nodes in vivo. Thus, the absolute values of the uptake of [68Ga]Ga-DOTA-ZCAM241 in the lymph nodes should be considered with caution. Still, the relative uptake patterns are in agreement with the flow cytometry data, which indicate a higher proportion of CD69-positive immune cells in the lymph nodes than in the joints (Fig. 4B). In addition, flow cytometry analysis of the lymph nodes identified that the main CD69-expressing cells were B cells, followed by T cells. This is in line with the interaction of autoreactive B cells and T cells, resulting in IgG anti-GPI production that is central to this disease model (25).

Strong inflammation in tissue involves not only recruitment of immune cells but also increased perfusion and vascular permeability. The last 2 factors are known to potentially contribute to increased nonspecific PET tracer uptake in tissue. Thus, it is important to control for nonspecific uptake in sites of inflammation.

After analysis of [68Ga]Ga-DOTA-ZCAM241, we proceeded to investigate in another batch of animals the uptake of the nonbinding Affibody molecule [68Ga]Ga-DOTA-ZAM106 as a control, using the same experimental setup. The uptake of [68Ga]Ga-DOTA-ZAM106 followed the same pattern by increasing in the joints with time, but it was lower than with [68Ga]Ga-DOTA-ZCAM241. This indicates that there is a separate mechanism for nonspecific uptake, likely because of increased perfusion and permeability resulting from the inflammatory environment. Therefore, there is most likely a nonspecific component for the uptake of [68Ga]Ga-DOTA-ZCAM241, in addition to binding to CD69-positive immune cells in tissue. However, the animal model of inflammatory arthritis used in this study exhibits stronger and more acute inflammation than the usually chronic and low-intensive process seen in RA in humans. Thus, it can be expected that the nonspecific uptake of [68Ga]Ga-DOTA-ZCAM241 resulting from increased perfusion and vascular permeability would be less pronounced in patients.

Limitations of the current study include the lack of blocking studies in a subset of animals. However, there is a lack of available CD69-specific binders and inhibitors or endogenous ligands, and before the discovery of ZCAM241, only monoclonal or polyclonal antibodies toward CD69 were available. Thus, no ligands are suitable for in vivo blocking, except for the CD69-targeting Affibody molecule ZCAM241. ZCAM241 may also block potential off-target binding; thus, blocking with an unrelated binder is usually recommended for validation of PET tracers. Because of the lack of a suitable blocking ligand different from the Affibody molecule, we opted to use the nonbinding, size-matched Affibody molecule [68Ga]Ga-DOTA-ZAM106 to estimate the nonspecific uptake, as is often done in similar situations.

Another limitation is that the [68Ga]Ga-DOTA-ZCAM241 and [68Ga]Ga-DOTA-ZAM106 PET scans were performed on different groups of animals, which may have different severity levels of inflammatory arthritis. This was done to decrease the number of PET scans and tracer injections to which each animal was subjected. It was considered better for the study design to obtain tracer uptake at 4 time points in 2 groups than to obtain 2 scans using 2 tracers (the active and the control nonbinding PET probes). However, the selected model is known for its reproducibility, which was confirmed by the similar outcome of clinical scores; thus, the PET data from both groups should be comparable.

For future studies, binding of [68Ga]Ga-DOTA-ZCAM241 should be further investigated with blocking studies to confirm the proportion of binding in the inflamed joints that is specific and the proportion that results from nonspecific capillary leakage. In addition, a study in a larger animal model, such as a pig, could provide more information about lymph node uptake because of the larger distance between tissues, minimizing the spillover from excretory organs.

CONCLUSION

Increased uptake of the CD69-directed peptide [68Ga]Ga-DOTA-ZCAM241 was seen in the paws of mice with induced inflammatory arthritis, which preceded the appearance of clinical symptoms. [68Ga]Ga-DOTA-ZCAM241 is thus a potential candidate for PET imaging of activated immune cells during RA onset.

KEY POINTS

QUESTION: Can activated immune cells be visualized in inflammatory arthritis using a CD69-targeting PET tracer?

PERTINENT FINDINGS: CD69-directed peptide [68Ga]Ga-DOTA-ZCAM241 displayed increased uptake in the paws of mice with induced inflammatory arthritis, which preceded the appearance of clinical symptoms. [68Ga]Ga-DOTA-ZCAM241 accumulation in the paws was strong and consistent with disease duration, whereas a nonspecific control peptide demonstrated only low binding.

IMPLICATIONS FOR PATIENT CARE: [68Ga]Ga-DOTA-ZCAM241 is a potential candidate for clinical PET imaging of activated immune cells in the joints during onset of, for example, RA.

DISCLOSURE

The study was funded by JDRF (1-SRA-2020-973-S-B), the Science for Life Laboratory, the Swedish Research Council (2020-02312 to Olof Eriksson, 2019-05115 to John Löfblom, 2019-01415 to Olle Korsgren, and 2021-03178 to Fredrik Wermeling), the Swedish Cancer Society (CAN 2017/649 and 20 1090 PjF to John Löfblom and 20 1114 PjF and 22 0546 SIA to Fredrik Wermeling), Vinnova (2019/00104 to John Löfblom), the China Scholarship Council (to Yunbing Shen), ExoDiab, the Novo Nordisk Foundation, an EFSD/Novo Nordisk grant, the Ernfors Family Fund, Barndiabetesfonden, Diabetesfonden, Diabetes Wellness, the Sten A. Olssons Foundation, Helmsley Charitable Trust, and the Juvenile Diabetes Foundation International. John Löfblom, Jonas Persson, Stefan Ståhl, Olof Eriksson, and Olle Korsgren are inventors of a patent covering ZCAM241. Bogdan Mitran and Olof Eriksson are employees of Antaros Medical AB. Olof Eriksson and Olle Korsgren are shareholders of Antaros Tracer AB. No other potential conflict of interest relevant to this article was reported.

ACKNOWLEDGMENTS

The Preclinical PET/MRI Platform, Sofie Ingvast, Athanisios Bitzios, and Bogdan Mitran are acknowledged for expert technical assistance.

Footnotes

  • ↵* Contributed equally to this work.

  • ↵† Contributed equally to this work.

  • Published online Nov. 30, 2023.

  • © 2024 by the Society of Nuclear Medicine and Molecular Imaging.

REFERENCES

  1. 1.↵
    1. Almutairi K,
    2. Nossent J,
    3. Preen D,
    4. Keen H,
    5. Inderjeeth C
    . The global prevalence of rheumatoid arthritis: a meta-analysis based on a systematic review. Rheumatol Int. 2021;41:863–877.
    OpenUrlPubMed
  2. 2.↵
    1. Catrina AI,
    2. Svensson CI,
    3. Malmström V,
    4. Schett G,
    5. Klareskog L
    . Mechanisms leading from systemic autoimmunity to joint-specific disease in rheumatoid arthritis. Nat Rev Rheumatol. 2017;13:79–86.
    OpenUrlCrossRefPubMed
  3. 3.↵
    1. de Almeida DE,
    2. Ling S,
    3. Holoshitz J
    . New insights into the functional role of the rheumatoid arthritis shared epitope. FEBS Lett. 2011;585:3619–3626.
    OpenUrlCrossRefPubMed
  4. 4.↵
    1. Klareskog L,
    2. Catrina AI
    . Autoimmunity: lungs and citrullination. Nat Rev Rheumatol. 2015;11:261–262.
    OpenUrlCrossRefPubMed
  5. 5.↵
    1. Scherer HU,
    2. Häupl T,
    3. Burmester GR
    . The etiology of rheumatoid arthritis. J Autoimmun. 2020;110:102400.
    OpenUrl
  6. 6.↵
    1. Klareskog L,
    2. Forsum U,
    3. Scheynius A,
    4. Kabelitz D,
    5. Wigzell H
    . Evidence in support of a self-perpetuating HLA-DR-dependent delayed-type cell reaction in rheumatoid arthritis. Proc Natl Acad Sci USA. 1982;79:3632–3636.
    OpenUrlAbstract/FREE Full Text
  7. 7.↵
    1. Ting JPY,
    2. Trowsdale J
    . Genetic control of MHC class II expression. Cell. 2002;109(suppl):S21–S33.
    OpenUrlCrossRefPubMed
  8. 8.↵
    1. van der Krogt JMA,
    2. van Binsbergen WH,
    3. van der Laken CJ,
    4. Tas SW
    . Novel positron emission tomography tracers for imaging of rheumatoid arthritis. Autoimmun Rev. 2021;20:102764.
    OpenUrl
  9. 9.↵
    1. Kay J,
    2. Upchurch KS
    . ACR/EULAR 2010 rheumatoid arthritis classification criteria. Rheumatology (Oxford). 2012;51(suppl 6):Svi5–Svi9.
    OpenUrl
  10. 10.↵
    1. Heidari B
    . Rheumatoid arthritis: early diagnosis and treatment outcomes. Caspian J Intern Med. 2011;2:161–170.
    OpenUrl
  11. 11.↵
    1. Jamar F,
    2. van der Laken CJ,
    3. Panagiotidis E,
    4. et al
    . Update on imaging of inflammatory arthritis and related disorders. Semin Nucl Med. 2023;53:287–300.
    OpenUrl
  12. 12.↵
    1. Matsui T,
    2. Nakata N,
    3. Nagai S,
    4. et al
    . Inflammatory cytokines and hypoxia contribute to 18F-FDG uptake by cells involved in pannus formation in rheumatoid arthritis. J Nucl Med. 2009;50:920–926.
    OpenUrlAbstract/FREE Full Text
  13. 13.↵
    1. Narayan N,
    2. Owen DR,
    3. Taylor PC
    . Advances in positron emission tomography for the imaging of rheumatoid arthritis. Rheumatology. 2017;56:1837–1846.
    OpenUrl
  14. 14.↵
    1. Fuchs K,
    2. Kohlhofer U,
    3. Quintanilla-Martinez L,
    4. et al
    . In vivo imaging of cell proliferation enables the detection of the extent of experimental rheumatoid arthritis by 3′-deoxy-3′-18F-fluorothymidine and small-animal PET. J Nucl Med. 2013;54:151–158.
    OpenUrlAbstract/FREE Full Text
  15. 15.
    1. Brenner W
    . 18F-FDG PET in rheumatoid arthritis: there still is a long way to go. J Nucl Med. 2004;45:927–929.
    OpenUrlFREE Full Text
  16. 16.↵
    1. Viitanen R,
    2. Moisio O,
    3. Lankinen P,
    4. et al
    . First-in-humans study of 68Ga-DOTA-Siglec-9, a PET ligand targeting vascular adhesion protein 1. J Nucl Med. 2021;62:577–583.
    OpenUrlAbstract/FREE Full Text
  17. 17.↵
    1. Rincón-Arévalo H,
    2. Burbano C,
    3. Atehortúa L,
    4. et al
    . Modulation of B cell activation by extracellular vesicles and potential alteration of this pathway in patients with rheumatoid arthritis. Arthritis Res Ther. 2022;24:169.
    OpenUrl
  18. 18.
    1. Afeltra A,
    2. Galeazzi M,
    3. Ferri GM,
    4. et al
    . Expression of CD69 antigen on synovial fluid T cells in patients with rheumatoid arthritis and other chronic synovitis. Ann Rheum Dis. 1993;52:457–460.
    OpenUrlAbstract/FREE Full Text
  19. 19.
    1. Ortiz AM,
    2. Laffon A,
    3. Gonzalez-Alvaro I
    . CD69 expression on lymphocytes and interleukin-15 levels in synovial fluids from different inflammatory arthropathies. Rheumatol Int. 2002;21:182–188.
    OpenUrlCrossRefPubMed
  20. 20.↵
    1. Atzeni F,
    2. Del Papa N,
    3. Sarzi-Puttini P,
    4. Bertolazzi F,
    5. Minonzio F,
    6. Capsoni F
    . CD69 expression on neutrophils from patients with rheumatoid arthritis. Clin Exp Rheumatol. 2004;22:331–334.
    OpenUrlPubMed
  21. 21.↵
    1. Nisnboym M,
    2. Vincze SR,
    3. Xiong Z,
    4. et al
    . Immuno-PET imaging of CD69 visualizes T-cell activation and predicts survival following immunotherapy in murine glioblastoma. Cancer Res Commun. 2023;3:1173–1188.
    OpenUrl
  22. 22.↵
    1. Edwards KJ,
    2. Chang B,
    3. Babazada H,
    4. et al
    . Using CD69 PET imaging to monitor immunotherapy-induced immune activation. Cancer Immunol Res. 2022;10:1084–1094.
    OpenUrl
  23. 23.↵
    1. Persson J,
    2. Puuvuori E,
    3. Zhang B,
    4. et al
    . Discovery, optimization and biodistribution of an Affibody molecule for imaging of CD69. Sci Rep. 2021;11:19151.
    OpenUrl
  24. 24.↵
    1. Ståhl S,
    2. Gräslund T,
    3. Eriksson Karlström A,
    4. Frejd FY,
    5. Nygren PÅ,
    6. Löfblom J
    . Affibody molecules in biotechnological and medical applications. Trends Biotechnol. 2017;35:691–712.
    OpenUrlCrossRef
  25. 25.↵
    1. LaBranche TP,
    2. Hickman-Brecks CL,
    3. Meyer DM,
    4. et al
    . Characterization of the KRN cell transfer model of rheumatoid arthritis (KRN-CTM), a chronic yet synchronized version of the K/BxN mouse. Am J Pathol. 2010;177:1388–1396.
    OpenUrlCrossRefPubMed
  26. 26.↵
    1. Shipkova M,
    2. Wieland E
    . Surface markers of lymphocyte activation and markers of cell proliferation. Clin Chim Acta. 2012;413:1338–1349.
    OpenUrlCrossRefPubMed
  27. 27.↵
    1. Xiao Z,
    2. Mayer AT,
    3. Nobashi TW,
    4. Gambhir SS
    . ICOS is an indicator of T-cell-mediated response to cancer immunotherapy. Cancer Res. 2020;80:3023–3032.
    OpenUrlAbstract/FREE Full Text
  28. 28.↵
    1. Alam IS,
    2. Mayer AT,
    3. Sagiv-Barfi I,
    4. et al
    . Imaging activated T cells predicts response to cancer vaccines. J Clin Invest. 2018;128:2569–2580.
    OpenUrlPubMed
  29. 29.↵
    1. Larimer BM,
    2. Wehrenberg-Klee E,
    3. Dubois F,
    4. et al
    . Granzyme B PET imaging as a predictive biomarker of immunotherapy response. Cancer Res. 2017;77:2318–2327.
    OpenUrlAbstract/FREE Full Text
  30. 30.↵
    1. Gibson HM,
    2. McKnight BN,
    3. Malysa A,
    4. et al
    . IFNγ PET imaging as a predictive tool for monitoring response to tumor immunotherapy. Cancer Res. 2018;78:5706–5717.
    OpenUrlCrossRefPubMed
  • Received for publication July 12, 2023.
  • Revision received October 10, 2023.
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Journal of Nuclear Medicine: 65 (2)
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Noninvasive PET Detection of CD69-Positive Immune Cells Before Signs of Clinical Disease in Inflammatory Arthritis
Emmi Puuvuori, Yunbing Shen, Gry Hulsart-Billström, Bogdan Mitran, Bo Zhang, Pierre Cheung, Olivia Wegrzyniak, Sofie Ingvast, Jonas Persson, Stefan Ståhl, Olle Korsgren, John Löfblom, Fredrik Wermeling, Olof Eriksson
Journal of Nuclear Medicine Feb 2024, 65 (2) 294-299; DOI: 10.2967/jnumed.123.266336

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Noninvasive PET Detection of CD69-Positive Immune Cells Before Signs of Clinical Disease in Inflammatory Arthritis
Emmi Puuvuori, Yunbing Shen, Gry Hulsart-Billström, Bogdan Mitran, Bo Zhang, Pierre Cheung, Olivia Wegrzyniak, Sofie Ingvast, Jonas Persson, Stefan Ståhl, Olle Korsgren, John Löfblom, Fredrik Wermeling, Olof Eriksson
Journal of Nuclear Medicine Feb 2024, 65 (2) 294-299; DOI: 10.2967/jnumed.123.266336
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  • rheumatoid arthritis
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