Blog

Synthesis and evaluation of anti-PD-L1-B11 antibody fragments for PET imaging of PD-L1 in breast cancer and melanoma tumor models | Scientific Reports

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Scientific Reports volume  14, Article number: 19561 (2024 ) Cite this article phage display libraries

T-lymphocytes or T-cells are part of our immune system that fight against foreign agents, germs, and diseases1. In human body, naïve T-cells circulate in the peripheral blood and lymphatics and on encountering foreign antigens presented by antigen presenting cells, naïve T cells get activated, self-proliferate, and differentiate into effector T-cells to mount a highly effective adaptive immune response against the foreign invaders1. Although activation of immune response is beneficial and needed to fight against any foreign invasion, overactivation or dysregulated immune response can be harmful as observed in autoimmune disorders2. To protect the body from dysregulated T-cell mediated immune response, immune regulators, such as cytotoxic T lymphocyte antigen 4 (CTLA4) or programmed death-1 receptor protein (PD-1)2, are present on the surface of T-cells. PD-1 receptor exerts its role of immune suppressor by binding its ligand, programmed death-ligand 1 (PD-L1), which is expressed in both hematopoietic and non-hematopoietic cells like T-cells, B-cells, macrophages, dendritic cells, antigen-presenting cells, vascular endothelial cells, fibroblastic reticular cells, astrocytes, neurons, cells in placenta, retina, lung, liver, skin and pancreatic islets3. Binding of the PD-1 receptor in T-cells to PD-L1 ligand initiates suppressive immune pathway in two ways: first by counteracting immune stimulatory signaling pathways in the activated T-cells and second, by preventing activation of new naïve T-cells3. Modulation of PD-L1 expression in variety of tissues has been reported to affect immune responses in autoimmune diseases, transplantation and pregnancy3. The existence of PD-1/PD-L1 interaction is crucial for balancing immune responses in healthy human body but cancer cells use it for its own advantage. High PD-L1 expression on cancer cells uses this PD-1/PD-L1 interaction to shield itself from the immune response by evading T-cell induced killing of cancer cells4,5,6,7,8,9.

As a result, high expression of PD-L1 on surface of tumor cells is associated with poor clinical outcome in variety of cancers such as gastric cancer, hepatocellular carcinoma, renal cell carcinoma, esophageal cancer, pancreatic cancer, ovarian cancer, and bladder cancer10,11. Various clinical trials have demonstrated immunotherapies that involve blocking interaction of PD-1 and PD-L1 using monoclonal antibodies (mAbs), and had shown an impressive long-term disease-free survival in patients with non-small-cell lung cancer (NSCLC)12,13, renal cell carcinoma (RCC)14, bladder cancer15 and breast cancer16.

Despite clinical success of PD-1/PD-L1 targeted immunotherapies, only 15–30% of cancer patients positively respond to the therapy17. Among these cancer patients, when stratified based on PD-L1 expression, PD-L1 positive tumors are known to respond better to PD-1/PD-L1 blockade therapy (~ 48% overall response rate) as compared to the PD-L1 negative tumors (~ 15% overall response rate)18. Moreover, a low PD-L1 expression has been observed in tumors with high tumor mutation burden, which is often associated with resistance to PD-1/PD-L1 blockade19. In addition, conventional chemotherapies and radiotherapies have been reported to increase PD-L1 expression in treated tumors, making them good candidates for PD-1/PD-L1 blockade therapy20,21. For effective management of cancer patients, knowing the PD-L1 expression in all metastases within a patient can be a predictive biomarker for PD-1/PD-L1 blockade therapy outcome and guide clinicians to PD-1/PD-L1 blockade versus other systemic therapies.

Currently, PD-L1 expression is detected by immunohistochemistry (IHC) following tumor biopsy and PD-L1 expression score from the IHC assay and is used as an eligibility criteria for PD-1/PD-L1 targeted therapeutics22,23. Although useful but IHC based assessment of PD-L1 expression is prone to error due to the heterogenous expression of PD-L1 in tumors and biopsy sampling error22,23. To overcome the current challenges in PD-L1 expression assessment for diagnostic and therapeutic monitoring, a non-invasive positron emission tomography (PET) imaging based assessment of PD-L1 expression will be highly valuable. This will allow more accurate assessment of PD-L1 expression of all metastases (quantitative) and metastatic lesion’s microenvironment (qualitative) and also enable detection of temporal changes in PD-L1 expression in tumor before and after therapy for prognosis of treatment and optimal patient management.

Previously, we radiolabeled the full length anti-PD-L1-B11 humanized variant HC4LC4 with Zr-89 as [89Zr]Zr-DFO-NCS-anti-PD-L1-B11 and tested for human PD-L1 (hPD-L1) imaging in PD-L1+ tumor models34. The [89Zr]Zr-DFO-NCS-anti-PD-L1-B11 showed higher uptake in PD-L1+ tumors than [89Zr]Zr-DFO-NCS-atezolizumab at day-3 and day-5 post-injection in a melanoma mouse model34. Apart from having higher uptake than [89Zr]Zr-DFO-NCS-atezolizumab, another advantage of [89Zr]Zr-DFO-NCS-anti-PD-L1-B11 was that it bound to the PD-L1 antigen at a different epitope than the atezolizumab and also potentially to other PD-L1 therapeutic antibodies, allowing use of [89Zr]Zr-DFO-NCS-anti-PD-L1-B11 for assessing PD-L1 expression during PD-L1 targeted therapeutics without any interference from the therapeutic antibodies34.

Our previous study with [89Zr]Zr-DFO-NCS-anti-PD-L1-B11 showed significantly higher tumor uptake at day-3 and day-5 post-injection in in vivo tumor model system. However, in a clinical setting, uptake time of 5–7 days post injection can be logistically difficult and inconvenient to the patients. Having a smaller antibody fragments with similar affinity but a shorter uptake time of 3–4 h would be ideal for a good PET imaging probe to assess PD-L1 expression35. Therefore, in this study, we designed, synthesized, radiolabeled, and evaluated three antibody fragments derived from humanized anti-PD-L1-B11 full length antibody, (i) B11-nanobody (~ 15 kDa), (ii) B11-scFv (~ 25 kDa) and (iii) B11-diabody (~ 50 kDa) (Fig. 1) as PET imaging probes for detection of PD-L1 expression in melanoma and breast cancer mouse models.

Illustration showing structure of anti-PD-L1-B11 variant HC4LC4 full length IgG (~ 150 kDa) and derived antibody fragments: B11-nanobody (~ 15 kDa), B11-scFv (~ 25 kDa) and B11-diabody (~ 50 kDa).

The three fragments of humanized anti-PD-L1-B11 variant HC4LC4 (~ 150 kDa): B11-diabody (~ 50 kDa), B11-scFv (~ 25 kDa) and B11-nanobody (~ 15 kDa) were successfully synthesized. The interaction of hPD-L1 with a well-known antibody atezolizumab, parent anti-PD-L1-B11 full-length humanized antibody variant HC4LC4, B11-diabody, B11-scFvand B11-nanobody were assessed, and their kinetic parameters are compared and summarized in Table 1. The equilibrium dissociation constant (KD = kd/ka) for HC4LC4 with hPD-L1 was found to be in nM range (KD = 0.629 nM), typical for a high affinity interaction, similar to KD (0.19–0.43 nM) observed for the atezolizumab and hPD-L1 interaction34,36. The equilibrium dissociation constant of the interaction between largest fragment, B11-diabody (~ 50 kDa) and hPD-L1 was 1.38 nM, which was relatively lower but in nanomolar range. The B11-scFv, which was smaller in size (~ 25 kDa) than B11-diabody (~ 50 kDa) showed significantly lower affinity towards PD-L1 (KD = 25.1 nM). On the other hand, the smallest of the three fragments, B11-nanobody (~ 15 kDa) showed no binding to hPD-L1. Other kinetic parameters were also compared such as the association and dissociation rate constants. The association rate constant (ka) of B11-diabody and B11-scFv with hPD-L1 were similar to HC4LC4 and atezolizumab’s interactions with hPD-L1 suggesting that the rate of formation of complex with the antibody fragments and hPD-L1 did not change as compared to the full-length antibody. On the other hand, if we concentrate on dissociation rates of various antibody fragments and full-length antibody with hPD-L1, the highest dissociation rate constant (kd) was observed for the B11-scFv than for the B11-diabody and then for full length humanized anti-PD-L1-B11 variant HC4LC4 making B11-scFv less desirable than B11-diabody as an imaging probe.

The binding affinity of an antibody to its target antigen is dependent on electrostatic interactions, hydrophobic interactions and inter-molecular forces like hydrogen bonds and Van der Waals forces37. Out of the three antibody fragments evaluated in this study, scFv and nanobody are monovalent with one antigen-binding site compared to its parent full-length IgG, which is bivalent with two antigen-binding sites. Monovalent and bivalent antibodies or antibody fragment(s) can have different electrostatic and hydrophobic interactions with the same antigen. This phenomenon is known as “avidity effect”. We think, “avidity effect” is the plausible reason for low to no binding affinity of B11-scFv and B11-nanobody to hPD-L1, influencing binding affinities of monovalent antibodies or antibody fragments towards their antigen38,39.

A PET imaging probe developed based on smaller fragment will be cleared faster from the body but a high binding affinity with tumor antigen is needed which depends on the association and dissociation rate of the interactions. A threshold binding affinity will allow enough time to visualize the expression of PD-L1 (antigen) on the tumor even with faster clearance. There is a well-documented relationship between size of the antibody fragments and kinetic parameters that plays a role in determining the clearance rate of the administered antibody fragment, the rate of uptake and retention of the antibody fragments in the tumor35,40. As a consequence, it was prudent to test all three antibody fragments as PD-L1 imaging probes. Therefore, all three fragments of humanized anti-PD-L1-B11 antibody were radiolabeled and evaluated.

Conjugation of B11-antibody fragments were performed as described in method section and characterized by MALDI-TOF (Supplementary Information, Figs. S1–S3). Based on MALDI-TOF analysis, the B11-diabody itself had a molecular weight of ~ 48.93 kDa, which increased to ~ 49.59 kDa after p-SCN-Bn-NOTA conjugation due to the formation of B11-diabody-Bn-NOTA. On a careful MALDI-TOF data analysis, we found an average of ~ 1.5 molecules of p-SCN-Bn-NOTA were conjugated to each molecule of B11-diabody. It is possible that some of the B11-diabody molecules were conjugated with only one molecule of p-SCN-Bn-NOTA and some others were conjugated with two of the p-SCN-Bn-NOTA resulting in an average of ~ 1.5 molecules of p-SCN-Bn-NOTA conjugation per B11-diabody molecule. In the case of B11-scFv, we observed a molecular weight of ~ 25.23 kDa for B11-scFv and ~ 25.80 kDa for B11-scFv-Bn-NOTA suggesting 1:1 conjugation between B11-scFv and p-SCN-Bn-NOTA. In the case of B11-nanobody, we observed a molecular weight of ~ 13.53 kDa for B11-nanobody and ~ 13.98 kDa for B11-nanobody-Bn-NOTA suggesting 1:1 conjugation. After conjugation and purification, 64Cu was chelated to the purified NOTA conjugated antibody fragments in a sodium acetate buffer at pH 5.0 for 10 min and repurified using a size exclusion PD-10 column to separate unchelated 64Cu from [64Cu]Cu-NOTA-B11-antibody fragments. The radiolabeling efficiency of > 99% was achieved after 10 min of incubation for all NOTA-Bn-NCS conjugated antibody fragments (Table 2).

After PD-10 column purification, > 99% radiochemical purity was achieved for all [64Cu]Cu-NOTA-B11-antibody fragments with specific activity and molar activity as shown in Table 3. The representative radioactive thin layer chromatography (r-TLC) graphs for assessing radiochemical purities of Cu-64 chelated antibody fragments are shown in the Supplementary Information, Fig. S4.

The radiochemical stability of [64Cu]Cu-NOTA-B11-diabody was tested in phosphate buffered saline (n = 1), mouse serum (n = 2) and human serum (n = 2) at 0 h, 2 h, 4 h, 8 h and 24 h post incubation time points by r-TLC. The [64Cu]Cu-NOTA-B11-diabody showed relatively better stability in phosphate buffered saline over mouse or human sera at earlier timepoints (up to 2 h) but showed overall better stability in sera than in the phosphate buffered saline for the remaining tested time period after 4 h as summarized in Fig. 2A with < 7% loss of intact [64Cu]Cu-NOTA-B11-diabody at 24 h of incubation. The radiochemical stability of [64Cu]Cu-NOTA-B11-scFv and [64Cu]Cu-NOTA-B11-nanobody were also tested in mouse and human sera. Both [64Cu]Cu-NOTA-B11-scFv and [64Cu]Cu-NOTA-B11-nanobody showed high stability overtime with < 5% loss of intact [64Cu]Cu-NOTA-B11-scFv and < 1% loss of [64Cu]Cu-NOTA-B11-nanobody in the sera over 24 h incubation (Fig. 2B,C).

Stability of (A) [64Cu]Cu-NOTA-B11-diabody in phosphate buffered saline, mouse and human sera, (B) [64Cu]Cu-NOTA-B11-scFv in mouse and human sera, and (C) [64Cu]Cu-NOTA-B11-nanobody in mouse and human sera.

The high stability of [64Cu]Cu-NOTA-B11-diabody, [64Cu]Cu-NOTA-B11-scFv and [64Cu]Cu-NOTA-B11-nanobody in mouse and human sera were encouraging and out of the three, in terms of specific activity or molar activity, [64Cu]Cu-NOTA-B11-diabody was the highest followed by [64Cu]Cu-NOTA-B11-nanobody and [64Cu]Cu-NOTA-B11-scFv making [64Cu]Cu-NOTA-B11-diabody a promising candidate for PD-L1 imaging than other two antibody fragments. To determine the effect of radiolabeling on structural integrity of B11-diabody, SDS-PAGE was performed in reducing conditions and visualized by silver staining and autoradiography. No negative effect was observed on the structural integrity of [64Cu]Cu-NOTA-B11-diabody as the [64Cu]Cu-NOTA-B11-diabody migrated to the expected molecular weight of ~ 25 kDa in reducing conditions (Fig. 3 and Supplementary Information, Fig. S5).

(A) Cropped silver stained SDS-PAGE of diabody (25 kDa; Lane 2) and (B) autoradiograph picture of [64Cu]Cu-NOTA-B11-diabody (25 kDa; Lane 2). Original SDS-PAGE gel and autoradiograph are presented in Supplementary Fig. S5.

Two different sets of cancer cells, mouse melanoma (B6-F10) and mouse breast cancer cells (EO771) were used to test the PD-L1 mediated uptake capability of [64Cu]Cu-NOTA-B11-diabody, [64Cu]Cu-NOTA-B11-scFv and [64Cu]Cu-NOTA-B11-nanobody in cells. In the melanoma cell line set, we used PD-L1 negative, B16-F10 PD-L1KO cells as negative control and hPD-L1 expressing B16-F10 hPD-L1+ cells as a positive control, whereas in breast cancer cell lines set, PD-L1 negative EO771 PD-L1KO was used as a negative control and hPD-L1 overexpressing, EO771 hPD-L1+ was used as a positive control. The absence of expression of PD-L1 antigen in EO771 PD-L1KO and B16-F10 PD-L1KO, overexpression of hPD-L1 in EO771 hPD-L1+ and positive expression of hPD-L1 in B16-F10 hPD-L1+ were confirmed by flow cytometry as summarized in the Figs. 4 and 5.

Flow cytometry histograms showing expression of hPD-L1 in (A1) B16-F10 PD-L1KO, (A2) B16-F10 hPD-L1+, (B1) EO771 PD-L1KO, and (B2) EO771 hPD-L1+ cells. Positive expression of hPD-L1 was observed in B16-F10 hPD-L1+ and EO771 hPD-L1+ cells. No hPD-L1 expression was observed in B16-F10 PD-L1KO and EO771 PD-L1KO cells.

Mean fluorescence intensity of B16-F10 hPD-L1+ and EO771 hPD-L1+ cells stained with isotype control and anti-PD-L1. The EO771 hPD-L1+ cells showed higher expression of hPD-L1 as compared to B16-F10 hPD-L1+ cells.

Higher uptake of [64Cu]Cu-NOTA-B11-diabody (0.76 ± 0.01%, n = 3) was observed in B16-F10 hPD-L1+ cells as compared to [64Cu]Cu-NOTA-B11-scFv (0.42 ± 0.02%, n = 3) (Table 4). Observed uptake results are consistent with the kinetic data of the antibody and antibody fragments (Table 1), where B11-diabody showed higher affinity towards PD-L1 as compared to B11-scFv. It was encouraging to observe that the uptake of radiolabeled antibody fragments was specific to PD-L1 antigen as there was significantly lower uptake of [64Cu]Cu-NOTA-B11-diabody and [64Cu]Cu-NOTA-B11-scFv in the B16-F10 PD-L1KO cells as compared to the B16-F10 hPD-L1+ cells. The decreased uptake of [64Cu]Cu-NOTA-B11-diabody and [64Cu]Cu-NOTA-B11-scFv in the B16-F10 hPD-L1+ cells upon blocking with anti-PD-L1 HC4LC4 IgG also corroborated the PD-L1 selective uptake of radiolabeled anti-PD-L1 diabody and scFv fragments (Table 4). The uptake of [64Cu]Cu-NOTA-B11-nanobody in the B16-F10 hPD-L1+ cells seems to be non-PD-L1 specific as upon blocking with parent anti-PD-L1 HC4LC4 IgG had no effect on uptake of [64Cu]Cu-NOTA-B11-nanobody in the B16-F10 hPD-L1+ cells (Table 4). Additionally, a high uptake of [64Cu]Cu-NOTA-B11-nanobody in the B16-F10 hPD-L1KO cells (0.40 ± 0.01%) (Table 4) further corroborates its non PD-L1 specific uptake.

The uptake of [64Cu]Cu-NOTA-B11-diabody was also assessed in the EO771 PD-L1KO breast cancer cells and hPD-L1 overexpressing EO771 hPD-L1+ breast cancer cells. A significantly higher uptake of [64Cu]Cu-NOTA-B11-diabody was observed in EO771 hPD-L1+ cells (2.48 ± 0.05%/106 cells/2 h; n = 3) as compared to EO771 PD-L1KO cells (0.68 ± 0.02%/106 cells/2 h; n = 3) (Fig. 6). Additionally uptake profile of [64Cu]Cu-NOTA-B11-diabody in the B16-F10 hPD-L1+ cells (0.76 ± 0.01%/106 cells/2 h ; n = 3) (Fig. 6), and in EO771 hPD-L1+ cells (2.48 ± 0.05%/106 cells/2 h; n = 3) were found to be consistent with PD-L1 expression as observed by the flow cytometry (Figs. 4 and 5).

Uptake of [64Cu]Cu-NOTA-B11-diabody in (A) B16-F10 PD-L1KO cancer cells and B16-F10 hPD-L1+ cells and in (B) EO771 PD-L1KO and hPD-L1 overexpressing EO771 hPD-L1+ cells. #p < 0.05 B16-F10 hPD-L1+ vs B16-F10 PD-L1KO (n = 3), *p < 0.05 EO771 hPD-L1+ vs EO771 PD-L1KO (n = 3).

Based on the in vitro results, both [64Cu]Cu-NOTA-B11-diabody and [64Cu]Cu-NOTA-B11-scFv could be a promising imaging candidates, while [64Cu]Cu-NOTA-B11-nanobody seemed to be less desirable than the two. To further test their performance, the radiolabeled PD-L1 targeting PET probes, [64Cu]Cu-NOTA-B11-diabody, [64Cu]Cu-NOTA-B11-scFv and [64Cu]Cu-NOTA-B11-nanobody, were evaluated in a PD-L1 KO mouse tumor model bearing subcutaneous B16-F10 PD-L1KO and B16-F10 hPD-L1+ tumors. The uptake was assessed in major organs and tumors at multiple time points after tail vein injection. In this model, only B16-F10 hPD-L1+ tumors expressed hPD-L1 and there was no background mouse PD-L1 expression or hPD-L1 expression in the mouse and B16-F10 PD-L1KO tumors. Among the three, uptake of [64Cu]Cu-NOTA-B11-nanobody was assessed by PET imaging at 2 h, 4 h and 6 h after tail vein injection, which is consistent with the time frame in which nanobody based PET probes are able to visualize tumors expressing their target antigens41. The administered [64Cu]Cu-NOTA-B11-nanobody was rapidly excreted with majority of the radioactivity in kidney (SUV = 20.54 ± 2.46, n = 6) and bladder (SUV = 6.99 ± 2.58, n = 6) as early as 2 h after tail vein injection with no uptake in B16-F10 PD-L1KO and B16-F10 hPD-L1+ tumors (Supplementary Information, Table S1 and Fig. S6). In the case of [64Cu]Cu-NOTA-B11-scFv, uptake of [64Cu]Cu-NOTA-B11-scFv was assessed by PET imaging at 2 h, 4 h, 6 h and 24 h after tail vein injection. The majority of uptake was observed in liver, kidney and bladder as early as 2 h post-injection and continued until 4 h post injection (Supplementary Information, Table S2 and Fig. S7). At 6 h and 24 h post-injection, majority of the radioactivity shifted to kidney and bladder showing slower clearance of [64Cu]Cu-NOTA-B11-scFv as compared to [64Cu]Cu-NOTA-B11-nanobody (Supplementary Information, Table S1, Table S2 and Figs. S7–S9). No uptake of [64Cu]Cu-NOTA-B11-scFv was observed in the B16-F10 PD-L1KO and B16-F10 hPD-L1+ tumors (Supplementary Information, Fig. S7). Comparing the B11-scFv and B11-nanobody based PET probes, although [64Cu]Cu-NOTA-B11-scFv showed slower clearance that [64Cu]Cu-NOTA-B11-nanobody, the higher affinity of [64Cu]Cu-NOTA-B11-scFv for hPD-L1 as compared to [64Cu]Cu-NOTA-B11-nanobody was not sufficient to allow appreciable tumor uptake in PD-L1 expressing tumor. The performance of [64Cu]Cu-NOTA-B11-diabody was tested in both melanoma and breast cancer tumor models. In the melanoma tumor model, the animal underwent PET scan at 0 h, 2 h, 4 h, 6 h, 24 h and 48 h post-injection of [64Cu]Cu-NOTA-B11-diabody. High PET signal was observed in heart at 0 h post-injection representing blood pool activity which was drastically decreased at 2 h post-injection and continued to decrease at successive time point post-injection as shown in Fig. 7. At all-time points post-injection, [64Cu]Cu-NOTA-B11-diabody was majorly taken up by kidney, bladder and liver (Figs. 7, 8 and Supplementary Information, Table S3).

Representative PET images showing biodistribution of [64Cu]Cu-NOTA-B11-diabody in PD-L1KO mouse bearing B16-F10 PD-L1KO and B16-F10 hPD-L1+ melanoma tumors.

Uptake of [64Cu]Cu-NOTA-B11-diabody in organs at multiple time points post-injection with major accumulation of the administered [64Cu]Cu-NOTA-B11-diabody in liver, kidney and bladder in PD-L1KO mouse bearing B16-F10 PD-L1KO and B16-F10 hPD-L1+ melanoma tumors.

In the melanoma tumor models, [64Cu]Cu-NOTA-B11-diabody was able to differentiate between B16-F10 hPD-L1+ tumors and B16-F10 PD-L1KO tumors at 4 h post-injection (Figs. 7 and 9). The SUVmax for B16-F10 hPD-L1+ tumors was 1.06 ± 0.33 (n = 4) which was higher than SUVmax for B16-F10 PD-L1KO, 0.82 ± 0.28 (n = 4) with p = 0.006 (paired Student t-test), The SUVmax Tumor:Muscle ratio of [64Cu]Cu-NOTA-B11-diabody in B16-F10 hPD-L1+ tumors was ~ 1.3× more than SUVmax Tumor: Muscle ratio observed in B16-F10 PD-L1KO tumors at 4 h post-injection (paired Student t-test; p value = 0.0092) (Figs. 7 and 9).

Uptake of [64Cu]Cu-NOTA-B11-diabody in B16-F10 PD-L1KO and B16-F10 hPD-L1+ melanoma tumors. *p = 0.0092 B16-F10 hPD-L1+ vs B16-F10 PD-L1KO (n = 4).

Whereas, in animals bearing breast cancer tumors, at 4 h post-injection, no statistical difference (paired Student t-test) was observed in the SUVmax for hPD-L1 overexpressing, EO771 hPD-L1+ tumor (3.15 ± 0.38; n = 6) and SUVmax for EO771 PD-L1KO tumor (2.74 ± 0.37; n = 6). On the other hand, statistical difference was observed between SUVmax Tumor: Muscle ratio in EO771 hPD-L1+ and EO771 PD-L1KO tumor by paired Student t-test (p = 0.025; n = 6).The SUVmax Tumor: Muscle ratio of [64Cu]Cu-NOTA-B11-diabody in EO771 hPD-L1+ tumors was ~ 1.7× more than SUVmax Tumor: Muscle ratio in EO771 PD-L1KO tumors at 4 h post-injection (Figs. 10 and 11). The ~ 1.7× difference in uptake of [64Cu]Cu-NOTA-B11-diabody in EO771 PD-L1KO and EO771 hPD-L1+ tumor which is higher than ~ 1.3× observed for B16-F10 PD-L1KO and B16-F10 hPD-L1+. It was expected as EO771 hPD-L1+ had higher expression of hPD-L1 than B16-F10 hPD-L1+ as shown by FACS (Figs. 4 and 5). This suggested that [64Cu]Cu-NOTA-B11-diabody was capable in differentiating tumors with variable PD-L1 expression. It was encouraging to observe that [64Cu]Cu-NOTA-B11-diabody was able to differentiate between PD-L1 negative tumor and PD-L1 expressing tumor at 4 h post-injection, which was not possible in the case of full length antibody based PET probes29,31,34 and required more than 4 days’ time after injection for getting a high tumor:background contrast for visualization of PD-L1 expression. Obtained result showed the utility of [64Cu]Cu-NOTA-B11-diabody in detecting differences in PD-L1 expression on the same day of tracer injection as compared to full length IgG based PET probes.

Representative PET images showing biodistribution of [64Cu]Cu-NOTA-B11-diabody in PD-L1KO mouse bearing EO771 PD-L1KO and EO771 hPD-L1+ breast cancer tumors.

Uptake of [64Cu]Cu-NOTA-B11-diabody in EO771 PD-L1KO and EO771 hPD-L1+ breast cancer tumors. *p = 0.0493 EO771 hPD-L1+ vs EO771 PD-L1KO (n = 6).

We have successfully synthesized B11-nanobody, B11-scFv and B11-diabody from the full-length anti-PD-L1 B11 IgG antibody, radiolabeled them with 64Cu in a good yield and evaluated them in breast cancer and melanoma models. Among the tested humanized antibody fragments, B11-diabody was found to be more promising as compared to the B11-scFv and B11-nanobody. Our finding showed that [64Cu]Cu-NOTA-B11-diabody can be used as a PET imaging probe to detect differences in PD-L1 expression in tumors as early as 4 h post-injection allowing faster assessment of PD-L1 expression in tumors as compared to PET imaging probe developed based on the full length IgG. Faster PET imaging-based assessment of PD-L1 expression is of high clinical value and perceived to help oncologists in a better patient centric management of anti-PD-L1 immunotherapies.

64Cu was purchased from the University of Wisconsin-Madison. The silica gel radioactive thin layer chromatography (r-TLC) was purchased from Agilent Technologies, Santa Clara, CA. p-SCN-Bn-NOTA (B-605) was purchased from Macrocylics, Plano, TX. The trace metal grade sodium carbonate, sodium citrate dihydrate, sodium acetate trihydrate and phosphate buffered saline were purchased from Sigma Aldrich, St. Louis, MO. PD-10 Desalting Columns containing Sephadex G-25 resin were obtained from Cytiva, Marlborough, MA.

E0771 mouse triple-negative breast cancer cell line was obtained from Robin L. Anderson at Olivia Newton-John Cancer Research Institute (Heidelberg, Australia)42 and B16-F10 mouse melanoma cell line was obtained from American Type Culture Collection, Manassas, VA. PD-L1 was knocked-out by CRISPR/Cas9 technology from EO771 and B16-F10 cells to generate PD-L1 negative EO771-PD-L1KO42 and B16-F10-PD-L1KO43 cells at Mayo Clinic Rochester in the Dr. H. Dong’s laboratory. hPD-L1 was expressed in EO771-PD-L1KO and B16-F10-PD-L1KO cell line to generate human PDL1 expressing EO771 hPD-L1+42 and B16-F10 hPD-L1+43 cells.

PD-L1 knockout (KO) C57BL/6 mice were produced at Mayo Clinic and maintained in the animal facility at the Department of Comparative Medicine, Mayo Clinic Rochester. At the time of injection, the animals bearing breast cancer tumors were females with body weight of 32.7 ± 9.4 g (n = 6) and animals bearing melanoma tumors were in 1:1 male and female ratio, and body weight of 30.44 ± 6.52 g (n = 16).

PD-L1 knockout (KO) C57BL/6 mice were injected subcutaneously with 0.5 × 106 B16-F10 hPD-L1+ cells or EO771 hPD-L1+ in the right flank and 0.5 × 106 B16-F10-PD-L1KO cells or EO771-PD-L1KO in the left flank. Perpendicular tumor diameters were measured using a digital caliper and tumor sizes were calculated as length × width. On day 6, when primary tumors were palpable, animals were randomly assigned to groups.

The MALDI-TOF analysis of antibody fragments was performed at the Mass Spectrometry Facility, School of Chemical Sciences, University of Illinois at Urbana-Champaign.

The murine monoclonal antibody, anti-PD-L1-B11 that targets hPD-L1 were generated as previously described34. The sequence of murine monoclonal antibody, anti-PD-L1-B11 variant HC4LC434 was used to generate B11-nanobody, B11-scFv and B11-diabody by Fusion Antibodies Ltd. (Belfast, UK). The analysis of kinetic parameters was performed in triplicate for each antibody fragment by Fusion Antibodies Ltd. (Belfast, UK) on Octet® Bio-Layer Interferometry (BLI) systems (Sartorius, Fremont, CA).

The assessment of expression of PD-L1 antigen in mouse breast cancer cells (EO771) with hPD-L1 (EO771 hPD-L1+) and without hPD-L1 expression (EO771 PD-L1KO) or mouse melanoma cancer cells (B16-F10) with hPD-L1 (B16-F10 hPD-L1+) and without hPD-L1 expression (B16-F10 PD-L1KO) were performed by fluorescence-activated cell sorting (FACS). The cells were stained with fluorescent control and anti-PD-L1 antibody clone: 29E.2A3 (BioLegend, SanDiego, CA). After staining, cells were washed three times with wash buffer (1× PBS, 2 mM EDTA, and 3% FBS) before analysis. At least 1 × 105 viable cells were live gated on FACS Cailbur (BD Biosciences) instrumentation. FACS analysis was performed using FlowJo software (Tree Star, Ashland, OR).

The B11 antibody fragments (B11-diabody, B11-scFv and B11-nanobody) was first conjugated with a bifunctional chelator p-SCN-Bn-NOTA using 1:6 equivalent of B11-antibody fragments to p-SCN-Bn-NOTA in a phosphate buffered saline medium of pH 9.0 at 37 °C for 60 min followed by an additional incubation at 25 °C for 10 h in a thermomixer. After final incubation, the NOTA conjugated B11-antibody fragments were separated from unreacted p-SCN-Bn-NOTA using PD-10 Desalting Column. The purified NOTA-B11-antibody fragment fraction was identified by assessing protein concentration in different fractions by Bradford assay44. The fractions with high protein concentration were freeze-dried and reconstituted in water at a final protein concentration of 5 mg/mL for NOTA-B11-scFv and NOTA-B11-diabody and 10 mg/mL for NOTA-B11-nanobody. The conjugation of p-SCN-Bn-NOTA to B11-antibody fragments were characterized by MALDI-TOF. The chelation of 64Cu with NOTA-B11-antibody fragments were performed in 0.20 M sodium acetate buffer pH 5.0 for 10 min. The chelation efficiencies were assessed by r-TLC with 0.10 M sodium citrate pH 5.0 as r-TLC mobile phase and analyzed using r-TLC scanner (Eckert and Ziegler, Valencia, CA). The amount of radioactivity and NOTA-B11-antibody fragments used in multiple chelation reactions are summarized in Table 5. After chelation, the [64Cu]Cu-NOTA-antibody fragments were purified using PD-10 Desalting column and obtained fraction with a high specific activity was used for stability, in vitro and in vivo studies.

Stability of [64Cu]Cu-NOTA-B11-antibody fragments were assessed in phosphate buffered saline, human and mouse sera. To perform this stability assay, [64Cu]Cu-NOTA-B11-diabody (~ 22.16 µCi or 0.82 MBq), [64Cu]Cu-NOTA-B11-scFv (~ 10.54 µCi 0.39 MBq) and [64Cu]Cu-NOTA-B11-nanobody (~ 36.76 µCi or 1.36 MBq) was mixed with phosphate buffered saline, human or mouse serum in 1:1 v:v ratio in a microcentrifuge tube. Resultant mixtures were incubated at 25 °C for 24 h. To assess the stability of [64Cu]Cu-antibody fragments, ~ 0.5 μL incubation mixture was taken out each time from the whole mixture at 0 h, 2 h, 4 h, 8 h, 24 h timepoints, and analyzed on a r-TLC using 0.10 M sodium citrate pH 5.0 as a mobile phase. The origin (Rf = ~ 0) represented intact [64Cu]Cu-antibody fragment and solvent front (Rf = ∼ 1) represented unchelated 64Cu.

The SDS-PAGE was performed as per the established protocol45,46. The diabody and [64Cu]Cu-NOTA-B11-diabody were diluted with 2× Laemmli sample buffer (1:1, v:v) (Bio-Rad laboratories, Hercules, CA) + 1× NuPAGE Sample Reducing Agent (Life Technologies Corporation, Carlsbad CA). The diluted protein samples were reduced at 80 °C for 3 min. The reduced proteins were resolved by one-dimensional SDS-PAGE in 10.0% Mini-PROTEAN TGX Gel (Bio-Rad laboratories, Hercules, CA) using 1× Tris–Glycine-SDS running buffer. After electrophoresis, autoradiography was performed for detecting [64Cu]Cu-NOTA-B11-diabody in the gel using a Cyclone Plus Storage Phosphor System (PerkinElmer Corporation, Waltham, MA) and visualized by Image J software47. Following electrophoresis, gels were silver stained using the ProteoSilver Plus Silver Stain Kit (Sigma, St. Louis, MO).

For in vitro uptake assay, EO771 PD-L1KO and B16-F10 PD-L1KO cancer cells, B16-F10 hPD-L1+ cells and EO771 hPD-L1+ cells were plated in a 6-well plate at a concentration of 1 × 106 cells/well. After overnight culture, [64Cu]Cu-NOTA-B11-diabody (~ 7.1 pmol/well; 48.93 GBq/µmol), [64Cu]Cu-NOTA-B11-scFv (~ 7.0 pmol/well; 49.09 GBq/µmol), [64Cu]Cu-NOTA-B11-nanobody (~ 7.2 pmol/well; 9.97 GBq/µmol) were added to each well and cells were incubated for 2 h at 37 °C. Following incubation with radiolabeled antibody fragments, the cells were washed with cold hanks buffered salt solution (HBSS) three times. After washing, the cells were lysed in 1 mL of 0.3 N NaOH and 1% sodium dodecyl sulfate and total cellular radioactivity was determined by gamma counting. The uptake was expressed as % dose/1 × 106 cells.

In each animal, [64Cu]Cu-NOTA-B11-diabody (48.81 ± 12.56 µCi or 1.81 ± 0.46 MBq; 0.70 ± 0.26 µg protein; n = 10), [64Cu]Cu-NOTA-B11-scFv (20.29 ± 4.81 µCi or 0.75 ± 0.18 MBq; 1.72 ± 0.38 µg protein; n = 6), [64Cu]Cu-NOTA-B11-nanobody (67.91 ± 3.32 µCi or 2.51 ± 0.12 MBq; 4.78 ± 0.25 µg protein; n = 6) were injected via tail vein injection. All the animals were anesthetized for tail vein injection and PET imaging using an induction dose of 3% isoflurane and a maintenance dose of 2–3% isoflurane, which was administered via isoflurane vaporizer. All anesthetized animals were kept warm during imaging using a heat supported imaging chamber. For PET imaging studies, each animal underwent a 10 min static PET scan at different time points post-injection on a small animal micro-PET/X-ray system, Genesys 4 (Sofie BioSystems, Dulles, VA, USA). After final imaging, all the animals were euthanized by the cardiectomy. Obtained PET images were reconstructed using the Genesys 4 imaging software installed on the imaging system. Reconstructed images were visualized, analyzed, and scaled to the SUV using image analysis software, MIM 7.2.7 software (MIM Software Inc., Cleveland, OH, USA), where;

The SUV data was presented as a coronal sectional maximum intensity projection image generated using the MIM 7.2.7 software (MIM Software Inc., Cleveland, OH, USA).

The obtained PET imaging data was analyzed using Microsoft Excel program and the uptake values were compared using paired Student’s t-test analysis. Differences in uptake values were considered statistically significant when p value < 0.05. GraphPad Prism version 10.0.3 for Windows (GraphPad Software, Boston MA) was used for preparing graphs in this study.

All the animal studies were performed after approval from the Institutional Animal Care and Use Committee (IACUC) of the Mayo Clinic. All methods performed in this study were in accordance with the Institutional Animal Care and Use Committee’s (IACUC) guidelines and regulation, which is a part of the Public Health Service (PHS) Policy on Humane Care and Use of Laboratory Animals and the Guide for the Care and Use of Laboratory Animals of the Office of the Laboratory Animal Welfare (OLAW) of the United States. These guidelines are equivalent to the ARRIVE guidelines and therefore all methods were performed in accordance with the ARRIVE guidelines.

All data generated or analyzed during this study are included in this manuscript and in its supplementary information.

Pennock, N. D. et al. T cell responses: Naive to memory and everything in between. Adv. Physiol. Educ. 37, 273–283 (2013).

Article  PubMed  PubMed Central  Google Scholar 

Qin, W. et al. The diverse function of PD-1/PD-L pathway beyond cancer. Front. Immunol. 10, 2298 (2019).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Beenen, A. C., Sauerer, T., Schaft, N. & Dörrie, J. Beyond cancer: Regulation and function of PD-L1 in health and immune-related diseases. Int. J. Mol. Sci. 23, 8599 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Dong, H. et al. Tumor associated B7–H1 promotes T-cell apoptosis: A potential mechanism of immune evasion. Nat. Med. 8, 793–800 (2002).

Article  CAS  PubMed  Google Scholar 

Tamura, H. et al. Marrow stromal cells induce B7–H1 expression on myeloma cells, generating aggressive characteristics in multiple myeloma. Leukemia 27, 464–472 (2013).

Article  CAS  PubMed  Google Scholar 

Thompson, R. H., Dong, H. & Kwon, E. D. Implications of B7–H1 expression in clear cell carcinoma of the kidney for prognostication and therapy. Clin. Cancer Res. 13, 709s–715s (2007).

Article  CAS  PubMed  Google Scholar 

Thompson, R. H. et al. Costimulatory B7–H1 in renal cell carcinoma patients: Indicator of tumor aggressiveness and potential therapeutic target. Proc. Natl. Acad. Sci. USA 101, 17174–17179 (2004).

Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

Thompson, R. H. et al. Tumor B7–H1 is associated with poor prognosis in renal cell carcinoma patients with longterm follow-up. Cancer Res. 66, 3381–3385 (2006).

Article  CAS  PubMed  Google Scholar 

Collins, M., Ling, V. & Carreno, B. M. The B7 family of immune-regulatory ligands. Genome Biol. 6, 223 (2005).

Article  PubMed  PubMed Central  Google Scholar 

Wang, X., Teng, F., Kong, L. & Yu, J. PD-L1 expression in human cancers and its association with clinical outcomes. Onco Targets Ther. 9, 5023–5039 (2016).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zou, W. & Chen, L. Inhibitory B7-family molecules in the tumour microenvironment. Nat. Rev. Immunol. 8, 67–477 (2008).

Gulley, J. L. et al. Avelumab for patients with previously treated metastatic or recurrent non-small-cell lung cancer (JAVELIN Solid Tumor): Dose-expansion cohort of a multicentre, open-label, phase 1b trial. Lancet Oncol. 18, 599–610 (2017).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Antonia, SJ et al. Overall survival with durvalumab after chemoradiotherapy in stage III NSCLC. N. Engl. J. Med. 379, 2342–2350 (2018).

Article  CAS  PubMed  Google Scholar 

McDermott, D. F. et al. Atezolizumab, an anti-programmed death-ligand 1 antibody, in metastatic renal cell carcinoma: Long-term safety, clinical activity, and immune correlates from a phase Ia study. J. Clin. Oncol. 34, 833–842 (2016).

Article  CAS  PubMed  Google Scholar 

Powles, T. et al. MPDL3280A (anti-PD-L1) treatment leads to clinical activity in metastatic bladder cancer. Nature 515, 558–562 (2014).

Article  ADS  CAS  PubMed  Google Scholar 

Chen, F. et al. Clinical progress of PD-1/L1 inhibitors in breast cancer immunotherapy. Front. Oncol. 11, 724424 (2022).

Article  PubMed  PubMed Central  Google Scholar 

Sun, J. Y. et al. Resistance to PD-1/PD-L1 blockade cancer immunotherapy: Mechanisms, predictive factors, and future perspectives. Biomark. Res. 8, 35 (2020).

Article  PubMed  PubMed Central  Google Scholar 

Sunshine, J. & Taube, J. M. PD-1/PD-L1 inhibitors. Curr. Opin. Pharmacol. 23, 32–38 (2015).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Lei, Q., Wang, D., Sun, K., Wang, L. & Zhang, Y. Resistance mechanisms of anti-PD1/PDL1 therapy in solid tumors. Front. Cell Dev. Biol. 8, 672 (2020).

Article  ADS  PubMed  PubMed Central  Google Scholar 

Guo, L. et al. Variation of programmed death ligand 1 expression after platinum-based neoadjuvant chemotherapy in lung cancer. J. Immunother. 42, 215–220 (2019).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wang, N. H. et al. Radiation-induced PD-L1 expression in tumor and its microenvironment facilitates cancer-immune escape: A narrative review. Ann. Transl. Med. 10, 1406 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ilie, M. et al. Comparative study of the PD-L1 status between surgically resected specimens and matched biopsies of NSCLC patients reveal major discordances: A potential issue for anti-PD-L1 therapeutic strategies. Ann. Oncol. 27, 147–153 (2016).

Article  CAS  PubMed  Google Scholar 

Patel, S. P. & Kurzrock, R. PD-L1 expression as a predictive biomarker in cancer immunotherapy. Mol. Cancer Ther. 14, 847–856 (2015).

Article  CAS  PubMed  Google Scholar 

Brown, E. L., DeWeerd, R. A., Zidel, A. & Pereira, P. M. R. Preclinical antibody-PET imaging of PD-L1. Front. Nucl. Med. 2, 953202 (2022).

Zhou, X. et al. First-in-humans evaluation of a PD-L1-binding peptide PET radiotracer in non-small cell lung cancer patients. J. Nucl. Med. 63, 536–542 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Niemeijer, A. N. et al. Whole body PD-1 and PD-L1 positron emission tomography in patients with non-small-cell lung cancer. Nat. Commun. 9, 4664 (2018).

Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

Giesen, D. et al. Probody therapeutic design of 89Zr-CX-072 promotes accumulation in PD-L1-expressing tumors compared to normal murine lymphoid tissue. Clin. Cancer Res. 26, 3999–4009 (2020).

Article  CAS  PubMed  Google Scholar 

Ruijter, L. K. et al. First-in-human study of the biodistribution and pharmacokinetics of 89Zr-CX-072, a novel immunopet tracer based on an anti-PD-L1 probody. Clin. Cancer Res. 27, 5325–5333 (2021).

Bensch, F. et al. 89Zr-atezolizumab imaging as a non-invasive approach to assess clinical response to PD-L1 blockade in cancer. Nat. Med. 24, 1852–1858 (2018).

Article  CAS  PubMed  Google Scholar 

Jagoda, E. M. et al. Immuno-PET imaging of the programmed cell death-1 ligand (PD-L1) using a zirconium-89 labeled therapeutic antibody, avelumab. Mol. Imaging 18, 1536012119829986 (2019).

Article  PubMed  PubMed Central  Google Scholar 

Smit, J. et al. PD-L1 PET/CT imaging with radiolabeled durvalumab in patients with advanced-stage non-small cell lung cancer. J. Nucl. Med. 63, 686–693 (2022).

Contreras-Sandoval, A. M. et al. Correlation between anti-PD-L1 tumor concentrations and tumor-specific and nonspecific biomarkers in a melanoma mouse model. Oncotarget 7, 76891–76901 (2016).

Enninga, E. A. L. et al. Immune checkpoint molecules soluble program death ligand 1 and galectin-9 are increased in pregnancy. Am. J. Reprod. Immunol. 79, e12795 (2018).

Bansal, A. et al. Non-invasive immunoPET imaging of PD-L1 using anti-PD-L1-B11 in breast cancer and melanoma tumor model. Nucl. Med. Biol. 100–101, 4–11 (2021).

Xenaki, K. T., Oliveira, S. & van Bergen En Henegouwen, P. M. P. Antibody or antibody fragments: Implications for molecular imaging and targeted therapy of solid tumors. Front. Immunol. 8, 1287 (2017).

Article  PubMed  PubMed Central  Google Scholar 

Chatterjee, S., Lesniak, W. G. & Nimmagadda, S. Noninvasive imaging of immune checkpoint ligand PD-L1 in tumors and metastases for guiding immunotherapy. Mol. Imaging 16, 1536012117718459 (2017).

Article  PubMed  PubMed Central  Google Scholar 

Janeway, C. A. J. et al. The interaction of the antibody molecule with specific antigen. In Immunobiology: The Immune System in Health and Disease 5th edn (Garland Science, 2001).

Horáček, J., Garrett, S. D., Skládal, P. & Morgan, M. R. A. Characterization of the interactions between immobilized parathion and the corresponding recombinant scfv antibody using a piezoelectric biosensor. Food Agric. Immunol. 10, 363–374 (1998).

Vauquelin, G. & Charlton, S. J. Exploring avidity: Understanding the potential gains in functional affinity and target residence time of bivalent and heterobivalent ligands. Br. J. Pharmacol. 168, 1771–1785 (2013).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Adams, G. P. et al. Increased affinity leads to improved selective tumor delivery of single-chain Fv antibodies. Cancer Res. 58, 485–490 (1998).

Rashidian, M. & Ploegh, H. Nanobodies as non-invasive imaging tools. Immunooncol. Technol. 7, 2–14 (2020).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Chen, C. et al. PD-L1 tumor-intrinsic signaling and its therapeutic implication in triple-negative breast cancer. JCI Insight 6, e131458 (2021).

Article  PubMed  PubMed Central  Google Scholar 

Tu, X. et al. PD-L1 (B7–H1) competes with the RNA exosome to regulate the DNA damage response and can be targeted to sensitize to radiation or chemotherapy. Mol. Cell 74, 1215-1226.e4 (2019).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Bradford, M. M. A rapid and sensitive for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal. Biochem. 72, 248–254 (1976).

Article  CAS  PubMed  Google Scholar 

Schägger, H. & von Jagow, G. Tricine-sodium dodecyl sulfate-polyacrylamide gel electrophoresis for the separation of proteins in the range from 1 to 100 kDa. Anal. Biochem. 166, 368–379 (1987).

Taubel, J. C. et al. Design, synthesis, and preliminary evaluation of [68Ga]Ga-NOTA-insulin as a PET probe in an Alzheimer’s disease mouse model. Bioconjug. Chem. 33, 892–906 (2022).

Article  PubMed  PubMed Central  Google Scholar 

Schneider , CA , Rasband , WS & Eliceiri , KW NIH Image to ImageJ: 25 years of image analysis . Nat. Methods 9, 671–675 (2012).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Research reported in this publication was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health of the USA (Award Numbers grant UL1TR002494 and UL1TR002377). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Additional support was provided from the Minnesota Partnership for Biotechnology and Medical Genomics through the Translational Product Development Fund (TPDF) to MKP as a Principal Investigator. This study was also partially supported by the Department of Radiology, Division of Nuclear Medicine, Mayo Clinic, Rochester, MN USA to MKP as a Principal Investigator.

Division of Nuclear Medicine, Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA

Aditya Bansal, Manasa Kethamreddy & Mukesh K. Pandey

Department of Urology, Mayo Clinic, Rochester, MN, 55905, USA

Roxane R. Lavoie, Fabrice Lucien & Haidong Dong

Office of Translation to Practice, Mayo Clinic, Rochester, MN, 55905, USA

Department of Immunology, Mayo Clinic, Rochester, MN, 55905, USA

Fabrice Lucien & Haidong Dong

Department of Radiation Oncology, Mayo Clinic, Rochester, MN, 55905, USA

You can also search for this author in PubMed  Google Scholar

You can also search for this author in PubMed  Google Scholar

You can also search for this author in PubMed  Google Scholar

You can also search for this author in PubMed  Google Scholar

You can also search for this author in PubMed  Google Scholar

You can also search for this author in PubMed  Google Scholar

You can also search for this author in PubMed  Google Scholar

You can also search for this author in PubMed  Google Scholar

A.B.: Performed radiolabeling, animal model generation, imaging studies, data analysis and contributed to manuscript writing. R.R.L.: Performed culture of cancer cells, animal model generation and flow cytometry, data analysis and contributed to manuscript writing. F.L.: Guided the study and edited the manuscript. M.K.: Performed imaging studies, data analysis and contributed to manuscript writing. B.W.: Guided the study and edited manuscript writing. H.D.: Guided the study and edited the manuscript. S.S.P.: Guided the study and edited the manuscript. M.K.P.: Designed the study, garnered the funds, guided the study, and edited the manuscript.

Correspondence to Mukesh K. Pandey.

H.D. is the inventor of anti-PD-L1-B11 antibody and related intellectual property disclosed to Mayo Clinic.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Bansal, A., Lavoie, R.R., Lucien, F. et al. Synthesis and evaluation of anti-PD-L1-B11 antibody fragments for PET imaging of PD-L1 in breast cancer and melanoma tumor models. Sci Rep 14, 19561 (2024). https://doi.org/10.1038/s41598-024-70385-8

DOI: https://doi.org/10.1038/s41598-024-70385-8

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Scientific Reports (Sci Rep) ISSN 2045-2322 (online)

ngs sequencing Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.