
==== Front
Immunother Adv
Immunother Adv
immunotherapyadv
Immunotherapy Advances
2732-4303
Oxford University Press UK

10.1093/immadv/ltae006
ltae006
Review
AcademicSubjects/MED00730
Advancements in nuclear imaging using radiolabeled nanobody tracers to support cancer immunotherapy
https://orcid.org/0000-0002-6637-6217
Zeven Katty Conceptualization Writing—original draft Writing—review & editing Molecular Imaging and Therapy Research Group, Vrije Universiteit Brussel (VUB), Brussels, Belgium

Lauwers Yoline Conceptualization Writing—original draft Writing—review & editing Molecular Imaging and Therapy Research Group, Vrije Universiteit Brussel (VUB), Brussels, Belgium

De Mey Lynn Writing—original draft Molecular Imaging and Therapy Research Group, Vrije Universiteit Brussel (VUB), Brussels, Belgium
Nuclear Medicine Department, UZ Brussel, Brussels, Belgium

Debacker Jens M Molecular Imaging and Therapy Research Group, Vrije Universiteit Brussel (VUB), Brussels, Belgium
Nuclear Medicine Department, UZ Brussel, Brussels, Belgium

De Pauw Tessa Writing—original draft Molecular Imaging and Therapy Research Group, Vrije Universiteit Brussel (VUB), Brussels, Belgium

De Groof Timo W M Molecular Imaging and Therapy Research Group, Vrije Universiteit Brussel (VUB), Brussels, Belgium

Devoogdt Nick Conceptualization Supervision Writing—review & editing Molecular Imaging and Therapy Research Group, Vrije Universiteit Brussel (VUB), Brussels, Belgium

Katty Zeven, Yoline Lauwers, Timo W. M. De Groof and Nick Devoogdt contributed equally to this work.

Correspondence: Molecular Imaging and Therapy Research Group, Vrije Universiteit Brussel (VUB), Brussels 1090, Belgium. Email: Nick.Devoogdt@vub.be
2024
26 8 2024
26 8 2024
4 1 ltae00627 6 2024
23 8 2024
15 9 2024
© The Author(s) 2024. Published by Oxford University Press on behalf of the British Society for Immunology.
2024
https://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Summary

The evolving landscape of cancer immunotherapy has revolutionized cancer treatment. However, the dynamic tumor microenvironment has led to variable clinical outcomes, indicating a need for predictive biomarkers. Noninvasive nuclear imaging, using radiolabeled modalities, has aided in patient selection and monitoring of their treatment response. This approach holds promise for improving diagnostic accuracy, providing a more personalized treatment regimen, and enhancing the clinical response. Nanobodies or single-domain antibodies, derived from camelid heavy-chain antibodies, allow early timepoint detection of targets with high target-to-background ratios. To date, a plethora of nanobodies have been developed for nuclear imaging of tumor-specific antigens, immune checkpoints, and immune cells, both at a preclinical and clinical level. This review comprehensively outlines the recent advancements in nanobody-based nuclear imaging, both on preclinical and clinical levels. Additionally, the impact and expected future advancements on the use of nanobody-based radiopharmaceuticals in supporting cancer diagnosis and treatment follow-up are discussed.

Graphical Abstract

Graphical Abstract

nuclear imaging
nanobodies
immunotherapy
diagnostics
cancer
FWO 10.13039/501100003130 1S61021N 1S61023N
==== Body
pmcIntroduction

Over the past decades, a plethora of cancer immunotherapies have been developed. These include immune checkpoint inhibitors (ICIs) [1], adoptive cell transfer [2], cancer vaccines [3], cytokines [4], antibodies(-derivatives), and antibody-drug conjugates (ADCs) [5, 6]. While many are still in (pre-)clinical testing, several immunotherapies have gained clinical approval to treat certain malignancies [7].

Despite this success, only a small fraction of patients demonstrate a favorable immunotherapy response [8]. This limited efficacy is mediated by the inherent complexities and interplay between tumors and the immune system. To optimize cancer management, a comprehensive understanding of the molecular characteristics (i.e. cancer-specific targets) of both primary and secondary lesions is indispensable to predict or follow-up treatment responses [9]. Besides tumor-specific antigens, numerous factors within the tumor microenvironment (TME) contribute to cancer prognosis and therapy outcome and are employed as biomarkers [10, 11].

Currently, molecular characterization of tumor or TME-specific targets is performed primarily via histological analysis of biopsies, complemented by screening of circulating cancer markers when applicable [12]. However, these methods do not provide whole-body spatiotemporal information, as tumor lesions are often inaccessible, the TME is dynamic, and intra- and inter-tumoral heterogeneity exists among many cancer types [12]. To address these challenges, noninvasive imaging of tumor or TME-specific targets allows for whole-body visualization. This approach reveals spatiotemporal changes in these markers, facilitating the monitoring of immunotherapy responses and potentially advancing personalized treatment strategies [13].

A radionuclide-based imaging tracer typically consists of two components: a radionuclide coupled to a targeting moiety. These tracers are visualized using medical imaging modalities such as positron emission tomography (PET) and single photon emission computed tomography (SPECT) [14]. These modalities offer good spatial resolution and allow for the quantitative evaluation of tracer signals. Various radionuclides are available for PET and SPECT imaging. For PET imaging, commonly used radionuclides include 68Ga, 18F, 64Cu, and 89Zr. For SPECT imaging, 99mTc, 111In, and 131I are commonly used (Table 1) [14].

Table 1. Overview of radionuclides commonly used for PET and SPECT imaging and TRT of Nbs.

Radionuclide	Half-life
(t1/2)	Commonly used chelators or prosthetic groups	Decay mode	SPECT/PET/TRT	
Gallium-68 (68Ga)	68 min	NOTA/DOTA/NODAGA/THP	ε+β+ (100%)	PET	
Fluorine-18 (18F)	110 min	SFB/FPy-TFP
NOTA/RESCA (AI-18F)	β+ (100%)	PET	
Copper-64 (64Cu)	13 h	NOTA/DOTA/NODAGA/DTPA	ε+β+ (61.5%), β- (38.5%)	PET	
Zirconium-89 (89Zr)	4 days	DFO/DFO*	ε+β+ (100%)	PET	
Technetium-99m (99mTc)	6 h	NA Tricarbonyl chemistry	IT	SPECT	
Indium-111 (111In)	3 days	DOTA/DTPA	ε (100%)	SPECT	
Iodine-131 (131I)	8 days	SGMIB	β- (100%)	SPECT/TRT	
Bismuth-213 (213Bi)	46 min	DOTA/DTPA	β- (37.9%),
α (2.1%)	TRT	
Lutetium-177 (177Lu)	7 days	DOTA/DTPA	β- (100%)	SPECT/TRT	
Terbium-161 (161Tb)	7 days	DOTA/DTPA	β- (100%)	SPECT/TRT	
Actinium-225 (225Ac)	10 days	DOTA	α (100%)	TRT	
α: alpha decay; β+: beta plus decay; β-: beta minus decay; DFO: desferrioxamine; DOTA: 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid; DTPA: diethylenetriaminepentaacetic acid; ε: electron capture; Fpy-TFP: 6-[18 F]fluoronicotinyl-2,3,5,6-tetrafluorophenyl ester; [18F]SFB: N-succinimidyl-4-[18F]fluorobenzoate; IT: Isomeric transition; NODAGA: 1,4,7-triazacyclononane,1-glutaric acid-4,7-acetic acid; NOTA: 1,4,7-Triazacyclononane-1,4,7-triacetic acid; PEG: polyethylene glycol; PET: positron emission tomography; SGMIB: N-succinimidyl 4-guanidino-methyl-3-iodobenzoate; SPECT: single photon emission computed tomography; THP: tris(hydroxypyridinone; TRT: targeted-radionuclide therapies.

Moreover, numerous targeting moieties have been developed, each with specific characteristics. These include small molecules, peptides, scaffold proteins, antibody fragments, and monoclonal antibodies (mAbs) (Fig. 1). Numerous clinical trials are currently investigating mAb-based tracers to predict immune therapy responses. Additionally, radiolabeled mAbs have gained significant attention as therapeutic compounds in targeted-radionuclide therapies (TRT). For example, 90Y-labeled ibritumomab targeting CD20 for the treatment of B-cell lymphoma [15]. TRT enables the systemic delivery of cytotoxic radiation directly to the target, minimizing damage to surrounding cells and tissues. Other examples of therapeutic radionuclides applied in TRT are 131I, 213Bi, 177Lu, 161Tb, and 225Ac (Table 1) [15]. The combination of diagnostics and (radio)therapy has led to a new field known as (radio)theranostics, which aims to achieve controlled and personalized drug delivery while simultaneously visualizing therapy response through molecular imaging [15].

Figure 1. Overview of different targeting moieties for PET and SPECT imaging. Their unique characteristics (molecular weight and optimal imaging timepoint) and matching radionuclides are presented. 64Cu: copper-64; 18F: fluorine-18; Fab: antigen-binding fragment; 68Ga: gallium-68; 111In: indium-111; 131I: iodine-131; MW: molecular weight; Nb: nanobody; PET: positron emission tomography; ScFv: single-chain variable fragment; SPECT: single-photon emission computerized tomography; 99mTc: technetium-99m; 89Zr: zirconium-89. Created with BioRender.com.

However, the substantial size of mAbs (~150 kDa) and the presence of an Fc-domain inherently limit their tissue penetration capacity and extend their blood circulation time. Consequently, these characteristics result in low target-to-background ratios and low-contrast images during early imaging timepoints. As a result, imaging with mAb-based tracers typically occurs several days post-injection, necessitating the use of longer-lived radioisotopes such as 89Zr. This leads to an increased radiotoxicity compared to short-lived radioisotopes. Furthermore, the interval between tracer administration and imaging presents logistical challenges for patients and clinical practice. Moreover, the slow pharmacokinetics of mAbs are also suboptimal for the safety profile of TRT [16]. Consequently, smaller antibody fragments with more favorable characteristics for radiotheranostics are being explored.

Single domain antibodies (sdAbs) or nanobodies (Nbs), derived from heavy-chain-only antibodies of camelids, have emerged as promising imaging tools over the last decade [17]. Nbs are smaller compared to mAbs (12–15 kDa), yet share similar traits of high stability and solubility, while having better tissue and tumor penetration [18]. Typically, Nbs are generated after immunization of camelids with specific target antigens from certain species. Next, B lymphocytes are isolated to create an immune library. From this library, genes encoding antigen-specific Nbs are selected through several rounds of phage display, and antigen-specific Nbs are subsequently produced recombinantly in E. coli strains for further characterization and selection. This method, along with other methods used for generating Nb libraries, is extensively described in a review of Muyldermans [19]. Despite their camelid origin, Nbs demonstrate high homology with human antibody heavy chain variable domains, thereby minimizing their immunogenicity [20]. Moreover, when a high homology between the human and mouse sequences of a certain target exists, cross-reactive Nbs can be created, facilitating more straightforward clinical translation [21, 22]. Furthermore, Nbs undergo rapid clearance from the blood because their size is far below the renal clearance cut-off of ~60 kDa. These fast pharmacokinetics result in high tumor-to-background ratios as early as 1 h after tracer injection, significantly enhancing their diagnostic and therapeutic applications (e.g. TRT) compared to mAbs [23]. This rapid clearance of Nbs allows for the use of short-lived radionuclides such as 68Ga, and 18F for PET imaging and 99mTc for SPECT imaging [24, 25]. Additionally, short-lived radionuclides facilitate repeated imaging, which is ideal for monitoring therapeutic responses. However, in some cases, the rapid clearance of Nbs can result in lower tracer uptake. To address this, polyethylene glycol (PEG)ylation has been described in a few preclinical studies, where the conjugation to a 20 kDa PEG-moiety results in a longer serum half-life, leading to increased tracer uptake and improved imaging signals [26]. However, PEGylation increases the apparent size of the tracer, necessitating the use of longer-lived radionuclides. This ultimately results in a higher radiation dose, making it less favorable.

The selection of a radiolabeling method depends on the targeting moiety and the specific radionuclide being used. Radionuclides can be classified into two categories: radiometals (e.g. 68Ga, 64Cu) and radiohalogens (e.g. 18F, 131I). For radiometals, chelators such as NOTA, DOTA, DFO, and NODAGA are commonly used to form stable complexes with radionuclides [27, 28]. The selection of a chelator depends on the choice of radiometal, where characteristics such as half-life as well as the characteristic of the targeting moiety, such as (thermo)stability, functionalization strategies in case of biomolecules, impact the stability of the radiometal-chelator complex and prevent in vivo demetallation or transchelation.

Furthermore, radiolabeling can be either direct (single-step) or indirect (two-step using prosthetic groups). For instance, Nbs with a hexahistidine-tag can be directly labeled with 99mTc-tricarbonyl. In contrast, labeling Nbs with 18F requires the use of a prosthetic group such as succinimidyl-4-[18F]fluorobenzoate ([18F]SFB) because direct labeling with 18F requires harsh conditions that may damage the Nb’s functionality [29, 30]. The exception here is AI18F-RESCA, which allows for direct radiofluorination of heat-sensitive molecules [31]. Finally, radiolabeling of biomolecules with both radiometals or radiohalogens can be performed using random or site-specific functionalization strategies, each with its advantages and disadvantages. The most straightforward strategy is random labeling, whereby the radionuclide is linked to naturally occurring amino acids (such as lysines) from the targeting moieties. However, this results in a heterogeneous product with possibly varying pharmacokinetic properties limiting the possibility to perform side-by-side comparisons. In contrast, site-specific strategies (such as Sortase-A or maleimide-thiol mediated conjugation) introduce the radionuclide to a single and specific site to form a uniform product, improving reproducibility and maintaining the tracer’s affinity [32, 33]. However, site-specific labeling often requires engineering an extra tag, which can influence the production process [33]. Additionally, site-specific labeling can increase the production costs due to added components and purification steps compared to the random strategy.

Overall, the favorable properties of Nbs position them as attractive alternatives for radionuclide-based imaging. Several Nb-based imaging tracers have been evaluated (pre-)clinically with encouraging results.

This review provides a comprehensive overview of the recent advancements in Nb-based tracers tailored for human (h) and/or mouse (m) tumor-specific or TME-specific targets. Additionally, the impact and expected future advancements of noninvasive and nuclear imaging techniques in supporting cancer diagnosis and treatment follow-up are discussed.

Nanobody-based imaging of tumor-specific antigens

Many Nb-based tracers have been extensively investigated to visualize and molecularly characterize cancerous lesions for better diagnosis and therapy prediction, but only a few have progressed to clinical evaluation (Table 2). Some Nbs also demonstrated radiotheranostic potential when labeled with a therapeutic radionuclide. These include Nbs directed to cancer-specific antigens, the tumor stroma, the extracellular matrix (ECM), or the neo-vasculature. For example, Nbs against prostate-specific membrane antigen (PSMA) for targeting prostate cancer, fibroblast activation protein (FAP) to target cancer-associated fibroblasts or insulin-like growth factor binding protein-7 for the visualization of the neo-vasculature have been described [34]. In this review, we will highlight the human epidermal growth factor 2 (HER2) as a tumor-specific target. More information on different anti-cancer Nbs and their specifications can be found in another review [17].

Table 2. Radiolabeled nanobodies to image tumor-specific antigens under clinical investigation.

Target	Reactivity	Clone	Radionuclide
and chelator	Cancer type	Discovery stage	Reference	
HER2	Human	2Rs15d	99mTc, 68Ga-NOTA	HER2+ breast cancer	Clinical
Phase I	[36, 37, 44]	
				Breast cancer and HER2+ solid tumors	Clinical
Phase II	[38] NCT03924466	
				Brain-metastasized solid tumors	Clinical
Phase II	NCT03331601	
		NM-02	99mTc	Breast cancer	Clinical
Phase I	[39] NCT04040686	
				Breast cancer	Clinical
Phase I	[41] NCT04674722	
		MIRC208	99mTc	HER2+ cancer	Clinical
Phase I	[42] NCT04591652	
		MIRC213	99mTc	HER2+ breast cancer	Clinical
Phase I	NCT05622240	
			[18F]AlF (RESCA)	HER2+ cancer	First-in-human	[32]	
CEA	Human	HNI01	68Ga-THP	Colorectal cancer	Clinical
Phase I	[45]	
Trop2	Human	Trop2 Nb	68Ga-THP	Solid tumors	Clinical
Phase I	NCT06188468	
		T4	68Ga-NOTA	Solid tumors	Clinical
Phase I	[46] NCT06203574	
CLDN18.2	Human	ACN376	68Ga	Solid tumors	Clinical
Phase I	[47] NCT05436093	
CD38	Human	NB381	68Ga	Multiple myeloma	Clinical
Phase I	NCT06385652	
CEA: Carcinoembryonic antigen; CLDN18.2: Claudin18.2; 18F: fluorine-18; [18F]AlF: aluminum-[18F]fluoride; 68Ga: gallium-68; HER2: human epidermal growth factor 2; NOTA: 1,4,7-Triazacyclononane-1,4,7-triacetic acid; 99mTc: technetium-99m; THP: tris(hydroxypyridinone; Trop2: Tumor-associated calcium signal transducer 2.

Human epidermal growth factor 2

Among the ERBB/HER transmembrane tyrosine kinase receptor family, HER2 stands out as one of the most extensively studied cancer markers. HER2 is a key therapeutic target for breast cancer, although its overexpression is also observed in other malignancies, such as gastric and ovarian cancer. While HER2-overexpression is a known negative prognosticator in breast cancer patients, the introduction of the HER2-inhibiting mAbs (e.g. trastuzumab) has significantly changed the treatment regimen [35]. Initially, the therapeutic effects of HER2-targeting mAbs were demonstrated in lesions with high HER2-overexpression. However, novel HER2-targeting therapies, including ADCs and small-molecule tyrosine kinase inhibitors, have also shown therapeutic effects in patients with low HER2 expression [35].

To enable patient stratification for HER2-targeting therapies, several research groups have developed Nbs against HER2 for noninvasive SPECT or PET imaging of the spatiotemporal HER2 expression, and which are currently undergoing clinical testing. In 2011, the Nb 2Rs15d labeled with 99mTc was first described, showing high uptake in two HER2+ mouse tumor models at 1 h post-injection, while binding a distinct epitope from the anti-HER2 therapeutic mAbs trastuzumab and pertuzumab [36]. Currently, 2Rs15d is being evaluated clinically for HER2 PET imaging. Phase I results were published in 2016, with no AEs (2 h post-injection) and no detection of anti-drug antibodies (ADAs) up until three months after administering three different doses of 2Rs15d [37]. Moreover, tracer uptake in primary breast cancer lesions was visible in 13 out of 15 patients, with high accumulation also observed in the kidneys, liver, intestines, and HER2+ metastases at 1–1.5 h post-injection [37]. In a subsequent phase II study (n=20), the tracer showed its ability to assess intratumoral HER2 heterogeneity more effectively than [18F]FDG, proving its potential to follow-up HER2-targeted therapy response in the future (Fig. 2) [38]. Two additional phase II studies are currently ongoing to evaluate the tracer in non-breast tumors and breast cancer patients undergoing neoadjuvant therapy (NCT03924466), as well as in HER2+ brain metastases (NCT03331601).

Figure 2. Examples of the clinical applicability of nanobody-based nuclear imaging of human epidermal growth factor receptor 2. (A) [68Ga]Ga-NOTA-anti-HER2-sdAb (left) and [18F]FDG (right) maximum-intensity projection PET images of a patient with a HER2-positive (3+) invasive ductal breast carcinoma with [18F]FDG-avid lymph nodes in the mediastinum. The extent of disease to the cervical lymph nodes (arrow) was better delineated on [68Ga]Ga-NOTA-anti-HER2-Nb as compared to [18F]FDG PET. (B) Representative maximum-intensity projection images of [18F]FDG PET (left) and 99mTc-MIRC208 SPECT (right) in a patient with HER2 overexpression (3+). [18F]FDG: 18F-2-fluoro-2-deoxyglucose; 68Ga: gallium-68; Nb: nanobody; PET: positron emission tomography; SPECT: single-photon emission computerized tomography; 99mTc: techenetium-99m. Images have previously been published in an adapted form by: (A) JNM. Gondry et al. Phase II Trial Assessing the Repeatability and Tumor Uptake of [68Ga]Ga-HER2 Single-Domain Antibody PET/CT in Patients with Breast Carcinoma. J Nucl Med. 2024; 65(2):178-184. © SNMMI [38]; and (B) Theranostics. Liqiang et al. HER2-targeted dual radiotracer approach with clinical potential for noninvasive imaging of trastuzumab-resistance caused by epitope masking. Theranostics. 2022; 12(12):5551-5563 [42], under a CC BY 4.0 license.

Besides 2Rs15d, three other HER2-targeting Nbs have undergone clinical translation to test their efficacy in diagnosing and monitoring HER2+ cancers undergoing targeted therapies: NM-02, MIRC208, and MIRC213. The phase I clinical trial with 99mTc-NM-02 displayed the tracers’ safety and potential to identify HER2 positivity [39]. A follow-up study using 99mTc- and Rhenium-188 (188Re, t1/2 = 17 h)-labeled NM02 for SPECT/CT and TRT, respectively, is ongoing (NCT04674722). A study with 131I-NM-02 also demonstrated a radiotheranostic potential [40]. The first results from the SPECT/CT evaluation with 99mTc-NM-02 revealed a positive correlation between uptake and HER2 expression in the untreated group (n = 24) while also showing a preliminary potential for the tracer to monitor the therapeutic effects of HER2-targeted therapy [41].

MIRC208 and MIRC213, target distinct epitopes of the HER2 protein with the respective purpose of patient selection and HER2 accessibility [42]. Both Nbs, labeled with 99mTc for SPECT imaging, are currently undergoing phase I trials. Initial results from two patients injected with 99mTc-MIRC208 demonstrated its preliminary toxicity profile and lesion accumulation (Fig. 2) (NCT04591652) [42]. Notably, a RESCA-coupled version of MIRC213 has recently been labeled with 18F for PET imaging, demonstrating its safety and proof-of-concept in six patients [32].

In addition to HER2-targeting Nbs, it is important to note that other HER2-targeting tracers, including mAbs, antibody derivatives, scaffold proteins, and peptides have demonstrated potential for patient stratification and therapy monitoring in the clinic. These tracers have been described in another review [43].

Nanobody-based imaging of the tumor microenvironment

Nanobody-based imaging of immune checkpoints

Immune checkpoints (ICs) are critical regulators of immune responses, maintaining homeostasis and preventing collateral damage. However, ICs can be exploited within the TME to induce an immune-suppressive environment, hindering anti-cancer immune responses [48]. Examples include cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and programmed death-1 (PD-1) along with one of its ligands (PD-L1). Following this discovery, IC-targeting mAbs have revolutionized immunotherapy [48]. Particularly, ICIs against PD-(L)1 have become the current standard of care for various cancers, including melanoma, head-and-neck, and non-small-cell lung carcinoma (NSCLC). Nevertheless, only a fraction (20–40%) of patients benefit from these therapies, with others either not responding or developing acquired resistance [49]. To address this, next-generation ICIs targeting novel ICs, including Lymphocyte-Activated Gene-3 (LAG-3), T cell receptor with Ig and ITIM domain (TIGIT), and T-cell immunoglobulin and mucin domain-containing protein 3 (TIM-3), have been developed to enlarge the treatment options [50]. Several radiolabeled Nbs specific for ICs have been developed to noninvasively image the dynamic IC expression within the TME and serve as diagnostic companions for patient stratification. Some of these Nbs also showed potent IC blockade capablities, indicating their potential for a theranostic approach (Table 3 and Fig. 4). Moreover, some of these Nbs can also predict ICI therapy response or resistance, as such enhance the outcomes of the treatment. Notably, therapy response prediction has also been demonstrated with other tracer formats such as mAbs, adnectins, and peptides [51].

Table 3. Overview of radiolabeled nanobodies in (pre-)clinical stage to image immune-associated targets.

Target	Reactivity	Clone	Radionuclide and chelator	Cancer type	Discovery stage	Reference	
PD-L1	Human	K2	99mTc, 68Ga	Melanoma cell line, breast cancer cell line	Preclinical	[33, 58]	
	Human	Nb109	68Ga	Glioblastoma cell line, Melanoma, Patient-derived lung cancer xenografts	Preclinical	[61–63]	
	Human	APN09	68Ga-NOTA, 99mTc	Lung adenocarcinoma cell line, NSCLC	Preclinical	[64, 92]	
			68Ga-THP	NSCLC	Clinical
Interventional	[64]
NCT05156515	
	Human	Nb1	68Ga	Solid tumors	Clinical Interventional	NCT06383598	
	Human	NM-01	99mTc	NSCLC	Clinical
Phase II	[65, 93] NCT04436406 & NCT04992715NCT02978196	
	Human	RW102	68Ga-NOTA	NSCLC	Clinical interventional	[67]
NCT06165874	
	Mouse	B3, A12	18F, 64Cu	Brown adipose tissue	Preclinical	[60, 94]	
	Mouse	A12	18F, 64Cu	Brown adipose tissue,
Melanoma cell line	Preclinical	[60, 94]	
	Mouse	C3, E2, E4, C7	99mTc	Lung epithelial carcinoma cell line	Preclinical	[56]	
	Mouse	MY1523	99mTc	Colorectal carcinoma cell line, Breast cancer cell line,
Non-Hodgkin lymphoma cell line	Preclinical	[59]	
PD-L2	Human	Mirc415	68Ga	Solid tumors	Clinical
Interventional	NCT05803746	
CTLA-4	Mouse	H11	18F, 89Zr	Melanoma cell line	Preclinical	[26]	
LAG-3	Human	3187	99mTc	Lung carcinoma cell line	Preclinical	[70]	
	Mouse	3132/3206	99mTc	Lung carcinoma cell line, Colorectal carcinoma cell line	Preclinical	[69, 71]	
TIGIT	Human	16925	99mTc	Lung carcinoma cell line	Preclinical	[74]	
	Human	Nb138	68Ga	Melanoma cell line	Preclinical	[75]	
	Mouse	16988	99mTc	Lung carcinoma cell line	Preclinical	[74]	
CD70	Human	CD70 VHH	68Ga	Renal cell carcinoma cell line, Lung adenocarcinoma cell line	Preclinical	[76]	
	Human	RCCB6	18F	Renal cell carcinoma	Clinical interventional	NCT06148220 [77]	
CD8	Mouse	VHH-X118	89Zr	Breast cancer cell line, melanoma cell line, Adenocarcinoma cell line, Pancreatic cancer cell line	Preclinical	[80, 81]	
	Human/Monkey	SNA006	68Ga-NOTA/NODAGA	hCD8 transfected adenocarcinoma cell line, Lung cancer, solid tumors	Preclinical
Clinical
Phase I	[27]
[28] NCT05126927	
	Human	VHH5v2	18F	T-cell Leukemia cell lines	Preclinical	[82]	
	Human/Monkey	hCD8β Nb	99mTc,
68Ga-NOTA, 64Cu-NOTA	Adenocarcinoma cell line	Preclinical	[83]	
CD4	Human	CD4-Nb1	64Cu-NODAGA	Leukemia cell line	Preclinical	[84]	
MHC-II	Mouse	VHH7	18F, 64Cu-NOTA,	Melanoma cell line, Pancreatic cancer cell line	Preclinical	[86, 95]	
	Mouse	DC8	18F	Melanoma cell line, Pancreatic cancer cell line	Preclinical	[95]	
CD11b	Mouse	DC13	18F,64Cu-NOTA,89Zr	Adenocarcinoma cell line, Melanoma cell line	Preclinical	[81, 86, 96]	
MMR	Mouse	Cl1	99mTc, 111In	Mammary adenocarcinoma cell line, Lung cancer cell line	Preclinical	[88, 97]	
	Human/Mouse	3.49	99mTc, [18F]SFB,68Ga-NOTA	Solid tumors, NSCLC, head and neck cancer, Solid malignancies undergoing ICI, Lymphoma	Clinical
Phase I/IIa	[21, 22, 89] NCT04168528
NCT05933239
NCT04758650	
Sirpα	Mouse	Nb15	99mTc	Glioblastoma cell line	Preclinical	[90]	
	Human	S36 Nb	64Cu-NODAGA	Adenocarcinoma cell line	Preclinical	[91]	
CTLA-4: cytotoxic T-lymphocyte-associated protein 4; 64Cu: copper-64; 8F: fluorine-18; [18F]SFB: succinimidyl-4-[18F]fluorobenzoate; 68Ga: gallium-68; ICI: immune checkpoint inhibitor; 111In: indium-111; LAG-3: Lymphocyte activated Gene-3; MHC-II: major histocompatibility complex II; MMR: macrophage mannose receptor; NODAGA: 1,4,7-triazacyclononane,1-glutaric acid-4,7-acetic acid, THP: tris(hydroxypyridinone); NOTA: 1,4,7-Triazacyclononane-1,4,7-triacetic acid; NSCLC: non-small cell lung cancer; PBMCs: peripheral blood mononuclear cells; PD-L1/2: programmed death-ligand 1/2; SIRPα: Signal regulatory protein α; 99mTc: technetium-99m; TIGIT: T cell receptor with Ig and ITIM domain; 89Zr: zirconium-89.

Figure 3. Examples of the clinical applicability of nanobody-based molecular imaging of programmed death ligand 1 and the macrophage mannose receptor (CD206). (A) Axial SPECT/CT (top) and corresponding CT-imaging (bottom) of the programmed death ligand 1 (PD-L1) targeting and 99mTc-labeled nanobody NM-01 in a patient with a high PD-L1-expressing primary non-small cell lung cancer (arrow). (B) Maximum-intensity projection [68Ga]Ga-NOTA-anti-CD206 Nb (MMR3.49) images of a non-small cell lung cancer patient at 1.5 h post-injection. CT: computed tomography; 68Ga: gallium-68; PET: positron emission tomography; SPECT: single-photon emission computerized tomography; 99mTc: technetium-99m. Images have previously been published in an adapted form by: (A) JNM. Xing et al. Early Phase I Study of a 99mTc-Labeled Anti-Programmed Death Ligand-1 (PD-L1) Single-Domain Antibody in SPECT/CT Assessment of PD-L1 Expression in Non-Small Cell Lung Cancer. J Nucl Med. 2019;60(9):1213-1220. © SNMMI [65]; and (B) JNM. Gondry et al. Phase I Study of [68Ga]Ga-Anti-CD206-sdAb for PET/CT Assessment of Protumorigenic Macrophage Presence in Solid Tumors (MMR Phase I). J Nucl Med. 2023;64(9):1378-1384. © SNMMI [22], under a CC BY 4.0 license.

Figure 4. Overview of radiolabeled nanobodies targeting different receptors within the TME. Both markers of immune cell populations and immune checkpoint molecules are presented. CTLA-4: Cytotoxic T-lymphocyte associated protein 4; 64Cu: copper-64; 18F: fluorine-18; 68Ga: gallium-68; 111In: indium-111; LAG-3: Lymphocyte-activation gene 3; MHC-II: major histocompatibility complex II; MMR: macrophage mannose receptor; PD-1: Programmed cell death protein 1; PD-L1/2: Programmed death-ligand 1/2; PET: positron emission tomography; SIRPα: Signal regulatory protein α; SPECT: single-photon emission computerized tomography; TAM: tumor-associated macrophage; 99mTc: technetium-99m; TCR: T-cell receptor; TIGIT: T cell immunoreceptor with immunoglobulin and ITIM domain; 89Zr: zirconium-89. Created with BioRender.com.

CTLA-4

CTLA-4 belongs to the CD28 immunoglobulin subfamily, mainly expressed on regulatory T-cells (Treg) and activated T cells. It modulates T-cell activation and proliferation by competing with the immune-activating receptor CD28 for binding to the costimulatory ligands B7-1 and B7-2 [52]. The first-generation ICI, ipilimumab, was approved by the FDA in 2011 to treat advanced-stage melanoma, demonstrating increased overall survival. Yet, only a subset of patients exhibits a positive response, with over 80% of patients experiencing drug-related AEs [53]. Therefore, selecting patients who most likely benefit from anti-CTLA-4 therapy is crucial. Multiple studies have already reported on mAb- or antibody derivative-based diagnostic imaging of CTLA-4 [53]. However, only a few anti-CTLA-4 Nbs have been described. The majority are primarily explored for their therapeutic potential. Only one mCTLA-4-specific Nb (H11) was studied for in vivo PET imaging in syngeneic mouse tumor models. PET/CT imaging showed specific tracer accumulation within the TME of B16-F10 melanoma tumor-bearing mice at 90 min and 24 h post-injection with the 18F-labeled or 89Zr-labeled Nb H11, respectively [26].

PD-L1/2

The interaction of PD-L1 and PD-L2 with PD-1 induces immune tolerance and promotes tumor escape. While predominantly expressed on tumor cells, PD-L1 is also found on macrophages, activated T cells, B cells, and brown adipose tissue [54]. Three mAbs against PD-L1 have already gained FDA approval: avelumab, atezolizumab, and durvalumab. Many studies have confirmed the correlation between PD-L1 expression and the prognosis of anti-PD-(L)1 therapy [55].

Several researchers have developed Nbs against mPD-L1 and hPD-L1 for noninvasive imaging. One research group demonstrated high target-to-background ratios in PD-L1-overexpressing tumor-bearing mice with multiple mPD-L1 Nbs (C3, C7, E2, and E4) and one hPD-L1 Nb (K2) following 99mTc-labeling via SPECT/CT imaging. These tracers could distinguish between PD-L1-high and -low expressing tumors already at 1 h post-injection [56]. Additionally, the 99mTc-labeled Nb C7 was used to visualize the spatiotemporal expression of mPD-L1 in mRNA-vaccinated B16 tumor-bearing mice, showing significant PD-L1-upregulation as early as one day post-vaccination, suggesting a potential synergy between cancer vaccination and PD-L1-blockade [30]. Finally, Nb K2 was evaluated as a PET tracer upon 68Ga-labeling. The 68Ga-labeled K2 demonstrated excellent in vivo targeting capabilities similar to its SPECT equivalent in melanoma and breast tumors with low kidney retention [33, 57, 58]. Another group also developed a 99mTc-labeled mPD-L1 tracer (Nb MY1523), showing potential for evaluating dynamic PD-L1 expression in vivo, and its ability to follow-up therapy responses [59].

Several other PD-L1-specific Nb-based PET tracers have been reported. For instance, mPD-L1-specific Nbs B3 and A12, labeled with 18F and 64Cu, showed specific accumulation in brown adipose tissue, indicating a metabolic role for PD-L1 [60]. Additionally, 68Ga-labeled anti-hPD-L1 Nbs Nb109 and APN09 demonstrated effective PD-L1-targeting in various tumor models and patient-derived lung xenografts. These Nbs enable specific detection of endogenous PD-L1 and dynamic changes in its expression, offering the potential for personalized treatment regimens and prognostic efficacy assessment [61–64]. Following positive preclinical results, 68Ga-labeled Nb APN09 entered a phase I clinical trial (NCT05156515), where PET/CT imaging with [68Ga]Ga-THP-APN09 in nine NSCLC patients showed a positive correlation between PD-L1 expression and tracer accumulation in tumors [64]. 99mTc-NM-01 is another Nb-based PD-L1 tracer being clinically evaluated for SPECT/CT imaging in NSCLC patients (NCT02978196). Clinical results show no drug-related AEs, adequate dosimetry, and tracer accumulation at the tumor site correlating with PD-L1 expression (Fig. 3A) [65]. KN035, a PD-L1 Nb showing therapeutic effect was also explored for its diagnostic potential. 89Zr-labeled KN035 was evaluated in patients with PD-L1-positive solid tumors, showing the detection of metastatic foci and the ability to monitor and predict the site of adverse reactions in antitumor immunotherapy. This further demonstrated the theranostic potential of this Nb [66]. Recently, some other PD-L1-specific Nbs have entered clinical testing as well. These include the [68Ga]Ga-Nb-1 for PET/CT imaging of patients with solid tumors (NCT06383598), and the [68Ga]Ga-NOTA-RW102 along with its derivative for PET/CT imaging in NSCLC patients (NCT06165874) [67].

In addition to PD-L1, PD-L2, a less extensively studied ligand of PD-1, is also under clinical investigation. A study is ongoing to target PD-L2 in patients diagnosed with various solid malignancies undergoing surgery or biopsy, using the 68Ga-labeled Nb Mirc415, and results are awaited (NCT05803746).

Next-generation immune checkpoints

LAG-3 is an example of a next-generation IC exhibiting high expression, for instance in exhausted T cells [68]. To date, a few Nb-based tracers have been developed specifically for h/mLAG-3. Upon 99mTc-labeling, anti-hLAG-3 Nb 3187 and anti-mLAG-3 Nbs 3206 and 3132 demonstrated specific tumor uptake in LAG-3-overexpressing tumor-bearing mice. Additionally, tracer accumulation was detected in peripheral organs containing LAG-3-expressing cells, such as spleen and lymph nodes [69, 70]. Furthermore, the mLAG-3-specific Nb 3132 was able to quantify dynamic LAG-3 expression within the TME and tumor-draining lymph nodes of PD-1-treated MC38 tumor-bearing mice, revealing a compensatory LAG-3 upregulation as a consequence of PD-1 blockade [71].

Another IC discovered in 2009 is TIGIT. The TIGIT pathway is known to mediate both innate and adaptive immune responses and contribute to effector cell exhaustion [72]. Although numerous clinical trials are investigating TIGIT-targeting therapies, current findings indicate varying efficacy, necessitating further evaluation of the significance of TIGIT immunotherapies [73]. Currently, TIGIT diagnostic tracers are still in preclinical development. Recently, two 99mTc-labeled Nb-based SPECT tracers (anti-mTIGIT Nb 16988 and anti-hTIGIT Nb 16925) were developed. These 99mTc-labeled Nbs showed specific uptake in TIGIT-expressing TC-1 tumors at 1 h post-injection, serving as a proof-of-concept for future applications [74]. Another study reported a 68Ga-labeled Nb-based hTIGIT tracer (Nb138) for PET imaging, showing specific uptake from 0.5 h up to 2 h post-injection in A375 melanoma-bearing nude mice [75]. With continuous research on novel ICs, many other Nbs targeting ICs will likely emerge in the near future.

In addition to the inhibitory ICs, the costimulatory receptor CD70 has emerged as an attractive target for immunotherapies. CD70 overexpression has been observed in various solid and hematological malignancies, resulting in immune evasion and tumor progression [76]. Several mAbs and drug-conjugates have already been developed and are currently undergoing clinical evaluation. To allow CD70 visualization, 68Ga-labeled NOTA-conjugated anti-hCD70 Nb demonstrated specific uptake in a CD70high renal carcinoma model [76]. Recently, a first-in-human study has been reported with 18F- labeled CD70-specific Nb RCCB6 for PET/CT imaging of patients with clear cell renal cell carcinoma [77].

Nanobody-based imaging of immune cell populations

Efforts have also been made to track immune cell dynamics to predict or follow-up immunotherapy response. Several Nbs against markers specific for T-cell populations, including CD8+ cytotoxic T cells (CTLs) and CD4+ T-helper (Th) cells, as well as myeloid cells, including macrophages, have been evaluated as diagnostic tracers for this purpose (Table 3 and Fig. 4).

T-cell imaging

Numerous T-cell-based immunotherapies have found their way to the clinic [78]. Moreover, numerous studies have linked the presence of T-cell populations, specifically CTLs, in the TME with enhanced therapy responses [79]. Therefore, noninvasive tracking of T-cell populations has gained more interest over time. To date, four anti-CD8 Nb-based tracers were developed and tested (pre-)clinically. The first reported Nb visualizing mCTLs (VHH-X118) was described in 2017, showing a sub-nanomolar affinity for mCD8α [80]. Upon PEGylation and 89Zr-labeling, VHH-X118 could visualize intratumoral CTLs in a B16 melanoma and a Panc02 pancreatic tumor at 24 h and 48 h post-injection. Furthermore, CTL dynamics and intratumoral biodistribution allowed us to predict therapy response, revealing a correlation between a more uniform distribution of CTLs and a favorable therapy response [81]. More recently, the 68Ga-labeled anti-hCD8α tracer SNA006 showed specific and rapid accumulation in hCD8-overexpressing MC38 tumor-bearing mice already at 0.5 h post-injection [27, 28]. To facilitate further clinical translation of 68Ga-labeled SNA006, two doses (25 µg/kg and 150 µg/kg) were tested in non-human primates to monitor the tracer’s safety and biodistribution at multiple timepoints up to 4 h post-injection. Interestingly, the lowest dose resulted in the highest uptake in CD8-rich organs such as the spleen, bone marrow, and lymph nodes. Additionally, preliminary results from a phase I study (NCT05126927) showed a linear correlation between tracer uptake and CD8 expression. While these initial clinical findings are promising, larger cohort studies are required to establish significant correlations between CD8 expression and tracer uptake to use the tracer for therapy prediction [28].

A third 18F-labeled anti-hCD8α tracer (VHH5v2) was recently developed, allowing rapid detection of differences in endogenous CD8 expression across three xenograft models. Notable, the tracer visualized both intermediate and low CD8-expressing tumors as early as 10 min post-injection and remained stable throughout the 1-h imaging experiment [82].

All the previous PET tracers target the α-chain, which can form CD8α homodimers on cells other than T cells. In a recent study, a Nb against the β-chain of the hCD8 protein was developed, showing more specific targeting of CTLs compared to the anti-hCD8α Nbs. Upon 99mTc- or 68Ga-labeling, this anti-hCD8β Nb showed specific targeting of CTLs (1 h post-injection) in CD8-rich organs and MC38 tumors in hCD8 transgenic mice. Furthermore, the Nb demonstrated its capability to visualize T-cell dynamics over time in the same mouse model. Its prognostic value was further confirmed by correlating intratumoral CTLs at early timepoints and tumor growth over time. Finally, a proof-of-concept study in non-human primates showed a good biodistribution profile at 1 h after administration of 500 µg of 64Cu-Nb [83].

Besides CD8+ T cells, CD4+ Th cells also play an essential role in initiating immune responses. To date, one 64Cu-labeled Nb targeting hCD4+ Th cells has been described with optimal signal-to-background ratios 3 h post-injection in various CD4-rich organs in hCD4 knock-in mice [84]. However, the marker CD4 has also been found on other cell types besides CD4+ Th cells (Tregs, peripheral monocytes, and other antigen-presenting cells). Therefore, to specifically target CD4+ Th cells, more specific markers in addition to CD4 are warranted [84].

Myeloid cells

A dual role in the TME can be attributed to myeloid lineage cells, consisting of monocytes, macrophages, dendritic cells, and granulocytes, identified by cell surface markers CD11b or MHC class II [85]. These myeloid cells can either aid tumor cells in maintaining tissue homeostasis and modulating T-cell responses or engage in direct or indirect tumor cell elimination by activating CTLs [85]. Consequently, two anti-mMHC-II Nbs (VHH7 and DC8) and one anti-mCD11b Nb clone (DC13) were generated to visualize myeloid cells. Specific binding of the 18F-labeled Nbs (VHH7 and DC13) to MHC-II+ cells and CD11b+ cells in both early and late-stage melanoma 1.5 h post-injection was reported [86]. Furthermore, PET/CT imaging with a 89Zr-PEGylated-DC13 tracer version allowed the stratification of PD-1 responders from non-responders, with responders showing a more uniform tracer distribution within the tumor than non-responders [81].

Tumor-associated macrophages (TAMs)

TAMs display a diverse spectrum of markers indicative of either anti- or pro-tumoral phenotypes, with the latter correlating with poor prognosis across various cancer types [87]. A well-studied pro-tumoral TAM marker is the macrophage mannose receptor (MMR), also known as CD206. The first reported anti-mMMR Nb (Cl1), after being labeled with 99mTc and 111In, showed macrophage-specific uptake in mouse breast and lung tumors. A high accumulation was also observed in macrophage-rich organs such as the spleen and liver. Co-administration of an excess of unlabeled bivalent anti-mMMR Nb effectively blocked the extra-tumoral binding sites and significantly increased the tumor-to-blood ratio [88]. For clinical translation, a m/h cross-reactive clone (MMR3.49) with comparable binding affinity and tumor-targeting potential was generated and characterized. Recently, a phase I study performed with the 68Ga-labeled MMR3.49 showed overall low total tumor uptake levels in six patients. However, patients with the highest uptake later developed progressive disease, suggesting a predictive value for the tracer (Fig. 3B) [22]. Currently, two phase II studies are ongoing in patients with different malignancies (NCT05933239 & NCT04758650) [21, 22, 89].

Along the same line, the myeloid-specific IC signal regulatory protein alpha (SIRPα) was shown to be expressed on tumor oligodendrocytes, type 2 conventional DCs, monocytes, and TAMs. In 2021, imaging of SIRPα-expressing cells in an intracranial glioblastoma mouse model using a 99mTc-labeled anti-mSIRPα Nb (Nb15) was shown even without additional permeabilization of the blood–brain barrier. A similar result, as seen with the MMR Nb was observed with accumulation in the tumor, as well as in the liver and spleen [90]. More recently, the potential of an anti-hSIRPα Nb was assessed in an immunocompetent mouse model. MC38 adenocarcinoma cells overexpressing hCD47 (MC38-hCD47+) were inoculated into hSIRPα/hCD47 knock-in mice and wild-type mice. The 64Cu-Nb showed rapid accumulation within the tumor of the hSIRPα/hCD47 knock-in mice via PET/MRI shortly after injection (6 min) and remained stable for 6 h. A 3-fold higher uptake in the MC38-hCD47+ tumor of hSIRPα/hCD47KI mice compared to wild-type mice was shown 3 h post-injection [91]. These Nbs could help improve or predict macrophage-targeting therapies employing SIRPα in the future.

Discussion

Current conventional approaches to monitor treatment response and tumor progression include immunohistochemistry and 18F-2-fluoro-2-deoxyglucose ([18F]FDG)-PET. [18F]FDG-PET is the most widely used imaging method in clinical practice. However, FDG only monitors alterations in glucose metabolism (i.e. malignant cells) but does not provide information on the molecular characteristics of the tumor. Furthermore, immune cell activation, due to immunotherapy response or inflammation, will also be detected with [18F]FDG-PET, resulting in false-positive results [98]. In contrast, lesions with lower metabolic activity will not be detected via [18F]FDG-PET [98]. Due to these inherent limitations, research has focused on the development of more tumor-specific imaging agents. Multiple tracers have been developed with several ones being clinically tested or even approved. A key example is the FDA-approved PSMA-targeting tracer, [68Ga]Ga-PSMA-11, for imaging of metastatic castration-resistant prostate cancer, showing a higher prognostic value compared to [18F]FDG-PET to stratify patients for PSMA-targeted therapy [99].

In contrast to tumor-specific antigen imaging, imaging of the TME is still in an earlier research phase, with only a few tracers being clinically tested. However, imaging of immunotherapy responses may hold great prognostic or predictive value. To date, imaging of ICIs or general immune cell populations for patient stratification, response monitoring, and drug resistance prediction has been the main focus. Here, Nb-based tracers have shown their added value. It seems logical that in the future, more novel Nb-based tracers will be developed against newly discovered ICIs and other immune cell populations (e.g. mast cells, neutrophils, basophils, and eosinophils). In addition, some of the current immune cell markers used (e.g. CD8α, MMR, and SIRPα) are not exclusively expressed on specific immune cell subsets, which may hamper their diagnostic potential. Also here, the development of novel and more specific (Nb-based) immunotracers against these immune subsets could be beneficial and result in enhanced prognostic or predictive potential.

Recent advances in spatial omics technologies have shown the dynamic nature of the TME and the importance of the interplay between different immune cell populations in the TME. This complex and dynamic environment suggests that a single tracer may not be sufficient to predict or follow-up immunotherapy responses. To this end, multiplex imaging, by combining different PET and/or SPECT tracers, could give more insight into the TME. Here, Nb-based tracers could be essential due to their inherent short in vivo half-life, resulting in the ability to perform multiple scans in a short timeframe. Multiple options are possible, including subsequent imaging of two PET tracers, one PET and one SPECT Nb-based tracer, or simultaneous imaging of two SPECT Nb-based tracers. While nuclear multiplex imaging is still in its infancy, it is not unlikely that this approach may hold great value in the immune-imaging field.

Employing nuclear imaging to monitor the spatiotemporal changes of TME-specific markers and predict immunotherapy response has gained interest in recent years. Currently, only a few imaging agents have been tested (pre-)clinically and shown predictive value during ICI, including tracers against CD69 (an immune activation marker) [100], granzyme B (a downstream effector of CTLs) [101], and CD8α [81]. Beyond monitoring ICI response, it would also be interesting to monitor other immunotherapies with Nb-based immunotracers, such as CAR-T cell therapy and cancer vaccines. CAR-T cell therapy is one of the most promising immunotherapies, showing remarkable results in hematological cancers, though its efficacy in solid tumors is still limited [102]. Currently, bioluminescent and PET/CT imaging are being exploited to track CAR-T-cell distribution, aiding in the interpretation of therapy responses and limitations. Nb-based tracers targeting CD8, T-cell activation, and exhaustion markers enable multiple timepoint imaging with short-lived radionuclides for PET/CT imaging. This approach paves the way for tracking CAR-T-cell dynamics, infiltration, and accumulation over time. Furthermore, these insights could support the development of effective strategies for treating solid tumors with CAR-T cell therapy.

Another promising immunotherapy is the delivery of tumor-specific antigens to the patient’s body through cancer vaccines to elicit an immune response. Although eight of them have been approved by the FDA, none have demonstrated a significant clinical impact yet [103]. Nbs can be employed to either investigate the migration route of these tumor-specific antigens to the tumor or visualize the response of antigen-specific CTLs. Overall, Nb-based imaging of cancer vaccines could potentially provide insights into the immune responses evoked by the tumor-specific antigens, thereby aiding in the design of better vaccines.

To date, multiple groups have been pursuing the clinical translation of Nb-based tracers. This is quite remarkable since diagnostic tracers are less economically interesting compared to therapeutic Nbs. However, this is most likely due to less strict clinical trial requirements including single-(micro)dosing and overall lower costs. Furthermore, the clinical translation of Nb-based tracers compared to mAb-based tracers offers some additional benefits, mainly due to their smaller size. This includes the use of short-living isotopes, resulting in reduced patient radiation burden and the possibility of same-day imaging. Furthermore, the ability to use bacteria or yeast as GMP production vectors, compared to mammalian cells for mAb-based tracers, and the need for lower quantities of product lowers the overall cost as well. However, the non-human origin of Nbs must be considered with respect to immunogenicity even with the fact that Nbs are generally considered low-immunogenic [20]. As such, a thorough immunogenicity assessment for each Nb is required and humanization of Nbs has been proposed as a strategy to facilitate clinical translation of Nb-based tracers [23].

To conclude, nuclear imaging offers a unique window into the complex interplay between tumors and the immune system, providing valuable insights to guide treatment decisions and explore new targets for future immunotherapies. Nbs hold promise as versatile nuclear imaging agents, demonstrating their value in (radio)theranostics and their efficacy in monitoring immunotherapy responses. This could help address future clinical questions in the field of immune-imaging.

Acknowledgements

The Editor-in-Chief, Tim Elliott, and handling editor, Doreen Lau, would like to thank the following reviewers, Weijun Wei and an anonymous reviewer, for their contribution to the publication of this article.

Abbreviations

α Alpha decay

ADAs Anti-drug antibodies

ADCs Antibody-drug conjugates

AEs Adverse events

β+ Beta plus decay

β- Beta minus decay

CEA Carcinoembryonic antigen

CLDN18.2 Claudin18.2

CTLs CD8+ cytotoxic T cells

CTLA-4 Cytotoxic T-lymphocyte-associated protein 4

64Cu copper-64

DCs Dendritic cells

DFO Desferrioxamine

DOTA 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid

DTPA Diethylenetriaminepentaacetic acid

ε Electron capture

ECM Extracellular matrix

18F Fluorine-18

Fab Antigen-binding fragment

FAP Fibroblast activation protein

[18F]AlF Aluminum-[18F]fluoride

Fpy-TFP 6-[18F]fluoronicotinyl-2,3,5,6-tetrafluorophenyl ester

[18F]SFB N-succinimidyl-4-[18F]fluorobenzoate

68Ga Gallium-68

HER2 Human epidermal growth factor 2

ICs Immune checkpoints

ICIs Immune checkpoint inhibitors

111In Indium-111

131I Iodine-131

IT Isomeric transition

LAG-3 Lymphocyte-Activated Gene-3

mAbs Monoclonal antibodies

MHC-II Major histocompatibility complex II

MMR Macrophage mannose receptor

MW Molecular weight

Nbs Nanobodies

NODAGA 1,4,7-triazacyclononane,1-glutaric acid-4,7-acetic acid

NOTA 1,4,7-Triazacyclononane-1,4,7-triacetic acid

NSCLC Non-small-cell lung carcinoma

PBMCs Peripheral blood mononuclear cells

PD-1 Programmed death-1

PD-L1/2 Programmed death-ligand 1/2

PEG Polyethylene glycol

PET Positron emission tomography

PSMA Prostate-specific membrane antigen

ScFv Single-chain variable fragment

sdAb Single domain antibody

SGMIB N-succinimidyl 4-guanidino-methyl-3-iodobenzoate

SIRPα Signal regulatory protein alpha

SPECT Single photon emission computed tomography

TAM Tumor-associated macrophage

99mTc Technetium-99m

TCR T-cell receptor

Th cells CD4+ T-helper cells

THP Tris(hydroxypyridinone

TIGIT T cell receptor with Ig and ITIM domain

TIM-3 Mucin domain-containing protein 3

TME Tumor microenvironment

Tregs Regulatory T cells

Trop2 Tumor-associated calcium signal transducer 2

TRT Targeted-radionuclide therapies

89Zr Zirconium-89

Author contributions

Katty Zeven (Conceptualization, Writing—original draft, Writing—review & editing), Yoline Lauwers (Conceptualization, Writing—original draft, Writing—review & editing), Lynn De Mey (Writing—original draft), Jens Debacker (Writing—original draft, Writing—review & editing), Tessa De Pauw (Writing—original draft), Timo De Groof (Conceptualization, Supervision, Writing—review & editing), and Nick Devoogdt (Conceptualization, Supervision, Writing—review & editing)

Funding

This work was funded by the Strategic Research Programme and Wetenschappelijk Fonds Willy Gepts from the Vrije Universiteit Brussel. This work is also supported by Kom op Tegen Kanker (Stand up to Cancer, the Flemish cancer society) and Research Foundation Flanders (FWO) research project (G087524N) and by a Kom op tegen Kanker fellowship grant (projectID: 13022). Timo W.M. De Groof is funded by a post-doctoral fellowship (12ZO723N) from the Research Foundation Flanders (FWO), Belgium. Katty Zeven is funded with a personal grant from the FWO (1S61021N and 1S61023N).

Conflict of interest

Nick Devoogdt is co-founder of the companies Precirix and Abscint.
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References

1. Ribas A , WolchokJD. Cancer immunotherapy using checkpoint blockade. Science 2018; 359 (6382 ):1350–5. 10.1126/science.aar4060 29567705
2. Adu-Berchie K , BrockmanJM, LiuY et al . Adoptive T cell transfer and host antigen-presenting cell recruitment with cryogel scaffolds promotes long-term protection against solid tumors. Nat Commun 2023; 14 (1 ):3546. 10.1038/s41467-023-39330-7 37322053
3. Lin MJ , Svensson-ArvelundJ, LubitzGS et al . Cancer vaccines: the next immunotherapy frontier. Nat Cancer 2022; 3 (8 ):911–26. 10.1038/s43018-022-00418-6 35999309
4. Berraondo P , SanmamedMF, OchoaMC et al . Cytokines in clinical cancer immunotherapy. Br J Cancer 2019; 120 (1 ):6–15. 10.1038/s41416-018-0328-y 30413827
5. Zahavi D , WeinerL. Monoclonal antibodies in cancer therapy. Antibodies (Basel) 2020; 9 (3 ):34. 10.3390/antib9030034 32698317
6. Jin S , SunY, LiangX et al . Emerging new therapeutic antibody derivatives for cancer treatment. Signal Transduct Target. Ther. 2022; 7 (1 ):39. 10.1038/s41392-021-00868-x 35132063
7. Lu Y , ZhangX, NingJ et al . Immune checkpoint inhibitors as first-line therapy for non-small cell lung cancer: a systematic evaluation and meta-analysis. Hum Vaccin Immunother 2023; 19 (1 ):2169531. 10.1080/21645515.2023.2169531 36715018
8. Haslam A , PrasadV. Estimation of the percentage of US patients with cancer who are eligible for and respond to checkpoint inhibitor immunotherapy drugs. JAMA Netw Open 2019; 2 (5 ):e192535. 10.1001/jamanetworkopen.2019.2535 31050774
9. Šutić M , VukićA, BaranašićJ et al . Diagnostic, predictive, and prognostic biomarkers in Non-Small Cell Lung Cancer (NSCLC) Management. J Pers Med 2021; 11 (11 ):1102. 10.3390/jpm11111102 34834454
10. Li HX , WangS-Q, LianZ-X et al . Relationship between tumor infiltrating immune cells and tumor metastasis and its prognostic value in cancer. Cells 2022; 12 (1 ):64. 10.3390/cells12010064 36611857
11. Lu J , XuY, WuY et al . Tumor-infiltrating CD8+ T cells combined with tumor-associated CD68+ macrophages predict postoperative prognosis and adjuvant chemotherapy benefit in resected gastric cancer. BMC Cancer 2019; 19 (1 ):920. 10.1186/s12885-019-6089-z 31521128
12. Sankar K , YeJC, LiZ et al . The role of biomarkers in personalized immunotherapy. Biomark Res 2022; 10 (1 ):32. 10.1186/s40364-022-00378-0 35585623
13. Arnouk S , De GroofTWM, Van GinderachterJA. Imaging and therapeutic targeting of the tumor immune microenvironment with biologics. Adv Drug Deliv Rev 2022; 184 :114239. 10.1016/j.addr.2022.114239 35351469
14. Kazim M , YooE. Recent Advances in the development of non-invasive imaging probes for cancer immunotherapy. Angew Chem Int Ed Engl 2024; 63 (2 ):e202310694. 10.1002/anie.202310694 37843426
15. Funeh CN , BridouxJ, ErtveldtT et al . Optimizing the safety and efficacy of bio-radiopharmaceuticals for cancer therapy. Pharmaceutics 2023; 15 (5 ):1378. 10.3390/pharmaceutics15051378 37242621
16. Harmand TJ , IslamA, PisheshaN et al . Nanobodies as in vivo, non-invasive, imaging agents. RSC Chem Biol 2021; 2 (3 ):685–701. 10.1039/d1cb00023c 34212147
17. Cong Y , DevoogdtN, LambinP et al . Promising diagnostic and therapeutic approaches based on VHHs for cancer management. Cancers (Basel) 2024; 16 (2 ):371. 10.3390/cancers16020371 38254860
18. Muyldermans S. Nanobodies:natural single-domain antibodies. Annu Rev Biochem 2013; 82 :775–97. 10.1146/annurev-biochem-063011-092449 23495938
19. Muyldermans S. A guide to: generation and design of nanobodies. FEBS J 2021; 288 (7 ):2084–102. 10.1111/febs.15515 32780549
20. Ackaert C , SmiejkowskaN, XavierC et al . Immunogenicity risk profile of nanobodies. Front Immunol 2021; 12 :632687. 10.3389/fimmu.2021.632687 33767701
21. Xavier C , BlykersA, LaouiD et al . Clinical Translation of [(68)Ga]Ga-NOTA-anti-MMR-sdAb for PET/CT Imaging of Protumorigenic Macrophages. Mol Imaging Biol 2019; 21 (5 ):898–906. 10.1007/s11307-018-01302-5 30671739
22. Gondry O , XavierC, RaesL et al . Phase I Study of [(68)Ga]Ga-Anti-CD206-sdAb for PET/CT Assessment of Protumorigenic Macrophage Presence in Solid Tumors (MMR Phase I). J Nucl Med 2023; 64 (9 ):1378–84. 10.2967/jnumed.122.264853 37474271
23. Vaneycken I , GovaertJ, VinckeC et al . In vitro analysis and in vivo tumor targeting of a humanized, grafted nanobody in mice using pinhole SPECT/micro-CT. J Nucl Med 2010; 51 (7 ):1099–106. 10.2967/jnumed.109.069823 20554727
24. Hassanzadeh-Ghassabeh G , DevoogdtN, De PauwP et al . Nanobodies and their potential applications. Nanomedicine (Lond) 2013; 8 (6 ):1013–26. 10.2217/nnm.13.86 23730699
25. Goel S , EnglandCG, ChenF et al . Positron emission tomography and nanotechnology: a dynamic duo for cancer theranostics. Adv Drug Deliv Rev 2017; 113 :157–76. 10.1016/j.addr.2016.08.001 27521055
26. Ingram JR , BlombergOS, RashidianM et al . Anti-CTLA-4 therapy requires an Fc domain for efficacy. Proc Natl Acad Sci U S A 2018; 115 (15 ):3912–7. 10.1073/pnas.1801524115 29581255
27. Zhao H , WangC, YangY et al . ImmunoPET imaging of human CD8(+) T cells with novel (68)Ga-labeled nanobody companion diagnostic agents. J Nanobiotechnology 2021; 19 (1 ):42. 10.1186/s12951-021-00785-9 33563286
28. Wang Y , WangC, HuangM et al . Pilot study of a novel nanobody (68) Ga-NODAGA-SNA006 for instant PET imaging of CD8(+) T cells. Eur J Nucl Med Mol Imaging 2022; 49 (13 ):4394–405. 10.1007/s00259-022-05903-9 35829748
29. Vaidyanathan G , McDougaldD, ChoiJ et al . Preclinical evaluation of 18F-labeled anti-HER2 nanobody conjugates for imaging HER2 receptor expression by immuno-PET. J Nucl Med 2016; 57 (6 ):967–73. 10.2967/jnumed.115.171306 26912425
30. Ertveldt T , MeulewaeterS, De VlaeminckY et al . Nanobody-mediated SPECT/CT imaging reveals the spatiotemporal expression of programmed death-ligand 1 in response to a CD8. Theranostics 2023; 13 (15 ):5483–500. 10.7150/thno.85106 37908728
31. Cleeren F , LecinaJ, BridouxJ et al . Direct fluorine-18 labeling of heat-sensitive biomolecules for positron emission tomography imaging using the Al 18 F-RESCA method. Nat Protoc 2018; 13 (10 ):2330–47. 10.1038/s41596-018-0040-7 30250289
32. Qin X , GuoX, LiuT et al . High in-vivo stability in preclinical and first-in-human experiments with [(18)F]AlF-RESCA-MIRC213: a (18)F-labeled nanobody as PET radiotracer for diagnosis of HER2-positive cancers. Eur J Nucl Med Mol Imaging 2023; 50 (2 ):302–13. 10.1007/s00259-022-05967-7 36129493
33. Bridoux J , BroosK, LecocqQ et al . Anti-human PD-L1 nanobody for immuno-PET imaging: validation of a conjugation strategy for clinical translation. Biomolecules 2020; 10 (10 ):1388. 10.3390/biom10101388 33003481
34. Iqbal U , AlbaghdadiH, LuoY et al . Molecular imaging of glioblastoma multiforme using anti-insulin-like growth factor-binding protein-7 single-domain antibodies. Br J Cancer 2010; 103 (10 ):1606–16. 10.1038/sj.bjc.6605937 20959824
35. Zhu K , YangX, TaiH et al . HER2-targeted therapies in cancer: a systematic review. Biomarker Res 2024; 12 (1 ):16. 10.1186/s40364-024-00565-1
36. Vaneycken I , DevoogdtN, Van GassenN et al . Preclinical screening of anti-HER2 nanobodies for molecular imaging of breast cancer. FASEB J 2011; 25 (7 ):2433–46. 10.1096/fj.10-180331 21478264
37. Keyaerts M , XavierC, HeemskerkJ et al . Phase I Study of 68Ga-HER2-Nanobody for PET/CT Assessment of HER2 expression in breast carcinoma. J Nucl Med 2016; 57 (1 ):27–33. 10.2967/jnumed.115.162024 26449837
38. Gondry O , CaveliersV, XavierC et al . Phase II trial assessing the repeatability and tumor uptake of [(68)Ga]Ga-HER2 single-domain antibody PET/CT in patients with breast carcinoma. J Nucl Med 2024; 65 (2 ):178–84. 10.2967/jnumed.123.266254 38302159
39. Zhao L , LiuC, XingY et al . Development of a (99m)Tc-labeled single-domain antibody for SPECT/CT Assessment of HER2 expression in breast cancer. Mol Pharm 2021; 18 (9 ):3616–22. 10.1021/acs.molpharmaceut.1c00569 34328338
40. Zhao L , GongJ, QiQ et al . 131I-Labeled Anti-HER2 nanobody for targeted radionuclide therapy of HER2-positive breast cancer. Int J Nanomedicine 2023; 18 :1915–25. 10.2147/IJN.S399322 37064291
41. Zhao L , XingY, LiuC et al . Detection of HER2 expression using (99m)Tc-NM-02 nanobody in patients with breast cancer: a non-randomized, non-blinded clinical trial. Breast Cancer Res 2024; 26 (1 ):40. 10.1186/s13058-024-01803-y 38459598
42. Li L , LiuT, ShiL et al . HER2-targeted dual radiotracer approach with clinical potential for noninvasive imaging of trastuzumab-resistance caused by epitope masking. Theranostics 2022; 12 (12 ):5551–63. 10.7150/thno.74154 35910795
43. Gao F , LiuF, WangJ et al . Molecular probes targeting HER2 PET/CT and their application in advanced breast cancer. J Cancer Res Clin Oncol 2024; 150 (3 ):118. 10.1007/s00432-023-05519-y 38466436
44. Xavier C , VaneyckenI, D'huyvetterM et al . Synthesis, preclinical validation, dosimetry, and toxicity of 68Ga-NOTA-anti-HER2 Nanobodies for iPET imaging of HER2 receptor expression in cancer. J Nucl Med 2013; 54 (5 ):776–84. 10.2967/jnumed.112.111021 23487015
45. Li L , LinX, WangL et al . Immuno-PET of colorectal cancer with a CEA-targeted [68 Ga]Ga-nanobody: from bench to bedside. Eur J Nucl Med Mol Imaging 2023; 50 (12 ):3735–49. 10.1007/s00259-023-06313-1 37382662
46. Huang W , LiangC, ZhangY et al . ImmunoPET imaging of Trop2 expression in solid tumors with nanobody tracers. Eur J Nucl Med Mol Imaging 2024; 51 (2 ):380–94. 10.1007/s00259-023-06454-3 37792026
47. Qi C , GuoR, ChenY et al . Whole-Body PET imaging rapidly targets claudin18.2 in lesions in gastrointestinal cancer patients. J Nucl Med 2024; 65 (6 ):856–63. 10.2967/jnumed.123.267110 38604764
48. Sharma P , SiddiquiBA, AnandhanS et al . The next decade of immune checkpoint therapy. Cancer Discov 2021; 11 (4 ):838–57. 10.1158/2159-8290.CD-20-1680 33811120
49. Twomey JD , ZhangB. Cancer immunotherapy update: FDA-approved checkpoint inhibitors and companion diagnostics. AAPS J 2021; 23 (2 ):39. 10.1208/s12248-021-00574-0 33677681
50. Dhasmana A , DhasmanaS, HaqueS et al . Next-generation immune checkpoint inhibitors as promising functional molecules in cancer therapeutics. Cancer Metastasis Rev 2023; 42 (3 ):597–600. 10.1007/s10555-023-10139-6 37728815
51. Badenhorst M , WindhorstAD, BeainoW. Navigating the landscape of PD-1/PD-L1 imaging tracers: from challenges to opportunities. Front Med (Lausanne) 2024; 11 :1401515. 10.3389/fmed.2024.1401515 38915766
52. Walker LS , SansomDM. The emerging role of CTLA4 as a cell-extrinsic regulator of T cell responses. Nat Rev Immunol 2011; 11 (12 ):852–63. 10.1038/nri3108 22116087
53. Ehlerding EB , LeeHJ, JiangD et al . Antibody and fragment-based PET imaging of CTLA-4+ T-cells in humanized mouse models. Am J Cancer Res 2019; 9 (1 ):53–63.30755811
54. Han Y , LiuD, LiL. PD-1/PD-L1 pathway: current researches in cancer. Am J Cancer Res 2020; 10 (3 ):727–42.32266087
55. Tunger A , SommerU, WehnerR et al . The evolving landscape of biomarkers for Anti-PD-1 or Anti-PD-L1 Therapy. J Clin Med 2019; 8 (10 ):1534. 10.3390/jcm8101534 31557787
56. Broos K , KeyaertsM, LecocqQ et al . Non-invasive assessment of murine PD-L1 levels in syngeneic tumor models by nuclear imaging with nanobody tracers. Oncotarget 2017; 8 (26 ):41932–46. 10.18632/oncotarget.16708 28410210
57. Broos K , LecocqQ, KeersmaeckerBD et al . Single domain antibody-mediated blockade of programmed death-ligand 1 on dendritic cells enhances CD8 T-cell activation and cytokine production. Vaccines (Basel) 2019; 7 (3 ):85. 10.3390/vaccines7030085 31394834
58. Broos K , LecocqQ, XavierC et al . Evaluating a single domain antibody targeting Human PD-L1 as a nuclear imaging and therapeutic agent. Cancers (Basel) 2019; 11 (6 ):872. 10.3390/cancers11060872 31234464
59. Gao H , WuY, ShiJ et al . Nuclear imaging-guided PD-L1 blockade therapy increases effectiveness of cancer immunotherapy. J ImmunoTher Cancer 2020; 8 (2 ):e001156. 10.1136/jitc-2020-001156 33203663
60. Ingram JR , DouganM, RashidianM et al . PD-L1 is an activation-independent marker of brown adipocytes. Nat Commun 2017; 8 (1 ):647. 10.1038/s41467-017-00799-8 28935898
61. Lv G , SunX, QiuL et al . PET imaging of tumor PD-L1 expression with a highly specific nonblocking single-domain antibody. J Nucl Med 2020; 61 (1 ):117–22. 10.2967/jnumed.119.226712 31253743
62. Liu Q , JiangL, LiK et al . Immuno-PET imaging of 68 Ga-labeled nanobody Nb109 for dynamic monitoring the PD-L1 expression in cancers. Cancer Immunol Immunother 2021; 70 (6 ):1721–33. 10.1007/s00262-020-02818-y 33386467
63. Liu Q , WangX, YangY et al . Immuno-PET imaging of PD-L1 expression in patient-derived lung cancer xenografts with [68 Ga]Ga-NOTA-Nb109. Quant Imaging Med Surg 2022; 12 (6 ):3300–13. 10.21037/qims-21-991 35655844
64. Ma X , ZhouX, HuB et al . Preclinical evaluation and pilot clinical study of [68 Ga]Ga-THP-APN09, a novel PD-L1 targeted nanobody radiotracer for rapid one-step radiolabeling and PET imaging. Eur J Nucl Med Mol Imaging 2023; 50 (13 ):3838–50. 10.1007/s00259-023-06373-3 37555904
65. Xing Y , ChandG, LiuC et al . Early Phase I Study of a (99m)Tc-labeled anti-programmed death ligand-1 (PD-L1) single-domain antibody in SPECT/CT assessment of PD-L1 expression in non-small cell lung cancer. J Nucl Med 2019; 60 (9 ):1213–20. 10.2967/jnumed.118.224170 30796165
66. He H , QiX, FuH et al . Imaging diagnosis and efficacy monitoring by [89 Zr]Zr-DFO-KN035 immunoPET in patients with PD-L1-positive solid malignancies. Theranostics 2024; 14 (1 ):392–405. 10.7150/thno.87243 38164149
67. Zhang Y , CaoM, WuY et al . Preclinical development of novel PD-L1 tracers and first-in-human study of [68 Ga]Ga-NOTA-RW102 in patients with lung cancers. J ImmunoTher Cancer 2024; 12 (4 ):e008794. 10.1136/jitc-2024-008794 38580333
68. Ruffo E , WuRC, BrunoTC et al . Lymphocyte-activation gene 3 (LAG3): The next immune checkpoint receptor. Semin Immunol 2019; 42 :101305. 10.1016/j.smim.2019.101305 31604537
69. Lecocq Q , ZevenK, De VlaeminckY et al . Noninvasive imaging of the immune checkpoint LAG-3 using nanobodies, from development to pre-clinical use. Biomolecules 2019; 9 (10 ):548. 10.3390/biom9100548 31569553
70. Lecocq Q , DebieP, PuttemansJ et al . Evaluation of single domain antibodies as nuclear tracers for imaging of the immune checkpoint receptor human lymphocyte activation gene-3 in cancer. EJNMMI Res 2021; 11 (1 ):115. 10.1186/s13550-021-00857-9 34727262
71. Lecocq Q , AwadRM, De VlaeminckY et al . Single-domain antibody nuclear imaging allows noninvasive quantification of LAG-3 expression by tumor-infiltrating leukocytes and predicts response of immune checkpoint blockade. J Nucl Med 2021; 62 (11 ):1638–44. 10.2967/jnumed.120.258871 33712537
72. Chauvin JM , ZarourHM. TIGIT in cancer immunotherapy. J ImmunoTher Cancer 2020; 8 (2 ):e000957. 10.1136/jitc-2020-000957 32900861
73. Rousseau A , ParisiC, BarlesiF. Anti-TIGIT therapies for solid tumors: a systematic review. ESMO Open 2023; 8 (2 ):101184. 10.1016/j.esmoop.2023.101184 36933320
74. Zeven K , De GroofTWM, CeuppensH et al . Development and evaluation of nanobody tracers for noninvasive nuclear imaging of the immune-checkpoint TIGIT. Front Immunol 2023; 14 :1268900. 10.3389/fimmu.2023.1268900 37799715
75. Rong Guo DW , JiangD, AnR. 68Ga-labeled anti-human TIGIT nanobody for immuno-PET imaging of TIGIT expression in cancer. Soc Nucl. Med. 2023; 13 (1 ):38. 10.1186/s13550-023-00982-7
76. Dewulf J , FlieswasserT, DelahayeT et al . Site-specific 68 Ga-labeled nanobody for PET imaging of CD70 expression in preclinical tumor models. EJNMMI Radiopharm Chem 2023; 8 (1 ):8. 10.1186/s41181-023-00194-3 37093350
77. Wu Q , WuY, ZhangY et al . ImmunoPET/CT imaging of clear cell renal cell carcinoma with [18 F]RCCB6: a first-in-human study. Eur J Nucl Med Mol Imaging 2024; 51 (8 ):2444–57. 10.1007/s00259-024-06672-3 38480552
78. Raskov H , OrhanA, ChristensenJP et al . Cytotoxic CD8(+) T cells in cancer and cancer immunotherapy. Br J Cancer 2021; 124 (2 ):359–67. 10.1038/s41416-020-01048-4 32929195
79. Waldman AD , FritzJM, LenardoMJ. A guide to cancer immunotherapy: from T cell basic science to clinical practice. Nat Rev Immunol 2020; 20 (11 ):651–68. 10.1038/s41577-020-0306-5 32433532
80. Rashidian M , IngramJR, DouganM et al . Predicting the response to CTLA-4 blockade by longitudinal noninvasive monitoring of CD8 T cells. J Exp Med 2017; 214 (8 ):2243–55. 10.1084/jem.20161950 28666979
81. Rashidian M , LaFleurMW, VerschoorVL et al . Immuno-PET identifies the myeloid compartment as a key contributor to the outcome of the antitumor response under PD-1 blockade. Proc Natl Acad Sci U S A 2019; 116 (34 ):16971–80. 10.1073/pnas.1905005116 31375632
82. Sriraman SK , DaviesCW, GillH et al . Development of an (18)F-labeled anti-human CD8 VHH for same-day immunoPET imaging. Eur J Nucl Med Mol Imaging 2023; 50 (3 ):679–91. 10.1007/s00259-022-05998-0 36346438
83. De Groof, T.W., Lauwers, Y., De Pauw, T.et al . Specific Imaging of CD8+ T-Cell Dynamics with a Nanobody Radiotracer against Human CD8B. Eur J Nucl Med Mol Imaging 2024. 10.1007/s00259-024-06896-3.
84. Traenkle B , KaiserPD, PezzanaS et al . Single-Domain Antibodies for Targeting, Detection, and In Vivo Imaging of Human CD4(+) Cells. Front Immunol 2021; 12 :799910. 10.3389/fimmu.2021.799910 34956237
85. Awad RM , De VlaeminckY, MaebeJ et al . Turn back the TIMe: targeting tumor infiltrating myeloid cells to revert cancer progression. Front Immunol 2018; 9 :1977. 10.3389/fimmu.2018.01977 30233579
86. Rashidian M , KeliherEJ, BilateAM et al . Noninvasive imaging of immune responses. Proc Natl Acad Sci USA 2015; 112 (19 ):6146–51. 10.1073/pnas.1502609112 25902531
87. Petty AJ , YangY. Tumor-associated macrophages: implications in cancer immunotherapy. Immunotherapy 2017; 9 (3 ):289–302. 10.2217/imt-2016-0135 28231720
88. Movahedi K , SchoonoogheS, LaouiD et al . Nanobody-based targeting of the macrophage mannose receptor for effective in vivo imaging of tumor-associated macrophages. Cancer Res 2012; 72 (16 ):4165–77. 10.1158/0008-5472.CAN-11-2994 22719068
89. Blykers A , SchoonoogheS, XavierC et al . PET imaging of macrophage mannose receptor-expressing macrophages in tumor stroma using 18F-radiolabeled camelid single-domain antibody fragments. J Nucl Med 2015; 56 (8 ):1265–71. 10.2967/jnumed.115.156828 26069306
90. De Vlaminck K , RomãoE, PuttemansJ et al . Imaging of glioblastoma tumor-associated myeloid cells using nanobodies targeting signal regulatory protein alpha. Front Immunol 2021; 12 :777524. 10.3389/fimmu.2021.777524 34917090
91. Wagner TR , BlaessS, LeskeIB et al . Two birds with one stone: human SIRPα nanobodies for functional modulation and in vivo imaging of myeloid cells. Front Immunol 2023; 14 :1264179. 10.3389/fimmu.2023.1264179 38164132
92. Hu B , MaX, ShiL et al . Noninvasive evaluation of tumoral PD-L1 using a novel 99m Tc-labeled nanobody tracer with rapid renal clearance. Mol Pharm 2024; 21 (4 ):1977–86. 10.1021/acs.molpharmaceut.3c01219 38395797
93. Hughes DJ , ChandG, JohnsonJ et al . Inter-rater and intra-rater agreement of [99mTc]-labelled NM-01, a single-domain programmed death-ligand 1 (PD-L1) antibody, using quantitative SPECT/CT in non-small cell lung cancer. EJNMMI Research 2023; 13 (1 ):51. 10.1186/s13550-023-01002-4 37256434
94. Carmès L , BortG, LuxF et al . AGuIX nanoparticle-nanobody bioconjugates to target immune checkpoint receptors. Nanoscale 2024; 16 (5 ):2347–60. 10.1039/d3nr04777f 38113032
95. Rashidian M , KeliherE, DouganM et al . The use of (18)F-2-fluorodeoxyglucose (FDG) to label antibody fragments for immuno-PET of pancreatic cancer. ACS Cent Sci 2015; 1 (3 ):142–7. 10.1021/acscentsci.5b00121 26955657
96. Rashidian M , WangL, EdensJG et al . Enzyme-mediated modification of single-domain antibodies for imaging modalities with different characteristics. Angew Chem Int Ed Engl 2016; 55 (2 ):528–33. 10.1002/anie.201507596 26630549
97. Bolli E , D'HuyvetterM, MurgaskiA et al . Stromal-targeting radioimmunotherapy mitigates the progression of therapy-resistant tumors. J Control Release 2019; 314 :1–11. 10.1016/j.jconrel.2019.10.024 31626860
98. Long NM , SmithCS. Causes and imaging features of false positives and false negatives on F-PET/CT in oncologic imaging. Insights Imaging 2011; 2 (6 ):679–98. 10.1007/s13244-010-0062-3 22347986
99. Pathmanandavel S , CrumbakerM, NguyenA et al . The prognostic value of posttreatment (68)Ga-PSMA-11 PET/CT and (18)F-FDG PET/CT in metastatic castration-resistant prostate cancer treated with (177)Lu-PSMA-617 and NOX66 in a Phase I/II Trial (LuPIN). J Nucl Med 2023; 64 (1 ):69–74. 10.2967/jnumed.122.264104 35738906
100. Edwards KJ , ChangB, BabazadaH et al . Using CD69 PET imaging to monitor immunotherapy-induced immune activation. Cancer Immunol Res 2022; 10 (9 ):1084–94. 10.1158/2326-6066.CIR-21-0874 35862229
101. Larimer BM , Wehrenberg-KleeE, DuboisF et al . Granzyme B PET imaging as a predictive biomarker of immunotherapy response. Cancer Res 2017; 77 (9 ):2318–27. 10.1158/0008-5472.CAN-16-3346 28461564
102. Guzman G , ReedMR, BielamowiczK et al . CAR-T therapies in solid tumors: opportunities and challenges. Curr Oncol Rep 2023; 25 (5 ):479–89. 10.1007/s11912-023-01380-x 36853475
103. Janes ME , GottliebAP, ParkKS et al . Cancer vaccines in the clinic. Bioeng Transl Med 2024; 9 (1 ):e10588. 10.1002/btm2.10588 38193112
