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Precision Medicine and Imaging

Exploitation of CD133 for the Targeted Imaging of Lethal Prostate Cancer

Paige M. Glumac, Joseph P. Gallant, Mariya Shapovalova, Yingming Li, Paari Murugan, Shilpa Gupta, Ilsa M. Coleman, Peter S. Nelson, Scott M. Dehm and Aaron M. LeBeau
DOI: 10.1158/1078-0432.CCR-19-1659 Published March 2020

Abstract

Purpose: Aggressive variant prostate cancer (AVPC) is a nonandrogen receptor–driven form of disease that arises in men in whom standard-of-care therapies have failed. Therapeutic options for AVPC are limited, and the development of novel therapeutics is significantly hindered by the inability to accurately quantify patient response to therapy by imaging. Imaging modalities that accurately and sensitively detect the bone and visceral metastases associated with AVPC do not exist.

Experimental Design: This study investigated the transmembrane protein CD133 as a targetable cell surface antigen in AVPC. We evaluated the expression of CD133 by microarray and IHC analysis. The imaging potential of the CD133-targeted IgG (HA10 IgG) was evaluated in preclinical prostate cancer models using two different imaging modalities: near-infrared and PET imaging.

Results: Evaluation of the patient data demonstrated that CD133 is overexpressed in a specific phenotype of AVPC that is androgen receptor indifferent and neuroendocrine differentiated. In addition, HA10 IgG was selective for CD133-expressing tumors in all preclinical imaging studies. PET imaging with [89Zr]Zr-HA10 IgG revealed a mean %ID/g of 24.30 ± 3.19 in CD133-positive metastatic lesions as compared with 11.82 ± 0.57 in CD133-negative lesions after 72 hours (P = 0.0069). Ex vivo biodistribution showed similar trends as signals were increased by nearly 3-fold in CD133-positive tumors (P < 0.0001).

Conclusions: To our knowledge, this is the first study to define CD133 as a targetable marker of AVPC. Similarly, we have developed a novel imaging agent, which is selective for CD133-expressing tumors, resulting in a noninvasive PET imaging approach to more effectively detect and monitor AVPC.

This article is featured in Highlights of This Issue, p. 979

Translational Relevance

An increasing number of men are developing a lethal, nonandrogen receptor (AR)–driven form of prostate cancer. Prostate-specific membrane antigen (PSMA)-targeted agents have made significant progress in imaging metastatic prostate adenocarcinoma; however, studies have demonstrated that non-AR–driven prostate cancer does not express PSMA. Thus, there is an urgent unmet need to identify novel antigens and targeted imaging agents for the detection and monitoring of this lethal form of prostate cancer. Our study has identified CD133 as a targetable antigen that is overexpressed on the surface of non-AR–driven, PSMA-negative prostate cancer. To image this subset of prostate cancer, a previously developed novel antibody for CD133 was labeled for near-infrared and PET imaging. Our CD133 probe was validated in imaging studies and shown to be highly selective for CD133-expressing prostate cancer cells, suggesting its potential as a noninvasive imaging agent for lethal, non-AR–driven disease.

Introduction

The management of patients with metastatic prostate cancer initially relies on inhibiting the androgen receptor (AR) signaling axis by androgen deprivation therapy (ADT) through surgical castration or gonadotropin-releasing hormone agonists. The therapeutic benefit of ADT is transient and patients inevitably develop disease recurrence, also known as castration-resistant prostate cancer (CRPC), which can occur as early as 18 months after the initiation of ADT (1–3). Driven by aberrant AR signaling, second-generation antiandrogens have had a profound effect in extending the lifespan of patients with CRPC (3). Unfortunately, many patients present with de novo resistance to these therapies and those that receive an initial benefit often develop acquired resistance rapidly through mechanisms such as AR amplification, mutation, and splice variant expression. Similarly, many men with de novo or acquired resistance to AR signaling inhibitors may display a non-AR–driven form of disease referred to as aggressive variant prostate cancer (AVPC; refs. 2, 4, 5). AVPC broadly encompasses CRPC that is non-AR–driven and may or may not express neuroendocrine markers or possess small-cell morphology (6, 7). This lethal subset of prostate cancer is characterized by high metastatic burden in both the bone and viscera, minimal response to therapy, and poor overall prognosis (8, 9).

Effective treatment options for AVPC currently do not exist and novel therapies are urgently needed. Critical to the development of novel therapies for AVPC is the ability to accurately image this disease in patients. For decades now, bone scintigraphy using [99mTc] methylene diphosphonate ([99mTc]Tc-MDP) has been the standard for imaging metastatic prostate cancer despite its limited sensitivity and specificity for cancerous lesions (10, 11). Furthermore, recent studies using the PET tracer, [18F]sodium fluoride (Na[18F]F), have demonstrated superior sensitivity for detecting bone lesions in patients with prostate cancer (11, 12). While this is successful for patients who present with bone metastases, a striking number of patients with AVPC also present with visceral disease, rendering bone scintigraphy and Na[18F]F PET imaging inadequate (13, 14). [18F]fluorodeoxyglucose ([18F]FDG) is commonly used in the clinic to image types of cancer that are dependent on glucose metabolism (15). However, [18F]FDG has performed poorly for imaging prostate cancer due to its unique metabolic properties that result in metastatic lesions with little avidity for glucose (15–17). Other PET imaging agents, such as [11C]acetate, [11C]/[18F]choline, and [18F]fluciclovine, have been employed to image prostate cancer biochemical recurrence (12, 18–20); however, these agents have yet to be investigated for AVPC. Recently, there has been much success imaging prostate-specific membrane antigen (PSMA) in bone and visceral metastases of patients with prostate adenocarcinoma using small-molecule PET radioligand probes (21). Several PSMA imaging studies have documented a lack of probe uptake in AR-negative metastatic lesions suggesting that AVPC does not express PSMA (22–24). Recently, a 68Ga-labeled gastrin-releasing peptide receptor (GRPR) antagonist demonstrated success at detecting prostate cancer in patients with biochemical recurrence by PET/MRI (25, 26). Given the overexpression of neuropeptides in neuroendocrine tumors, it is highly probable that such agents could be used to image AVPC with neuroendocrine-differentiation (27–29). Other imaging modalities such as MRI and CT have been useful in detecting metastatic disease, but tell nothing of the underlying biology of the cancer cell (30). Currently, however, there is no accurate imaging modality available for patients with AVPC.

The lack of targetable antigens specific to AVPC has complicated the development of an imaging agent for this disease subtype. The heavily glycosylated pentaspan transmembrane protein, CD133, has often been described as an antigen on the surface of both stem cells and cancer stem cells (31). In a previous study, we used human antibody phage display to identify a novel single-chain variable fragment (scFv) antibody for CD133, termed HA10 (32). Herein, we show that CD133 is highly overexpressed at the mRNA and protein level in a multitude of patients possessing AVPC with an AR-negative, neuroendocrine (NE) marker–positive (AR−/NE+) phenotype. By microarray analysis, we confirmed that CD133 and PSMA expression were inversely related and that AVPC is PSMA-negative. Moreover, we used a full-length human IgG version of HA10 to selectively identify CD133-positive cancer cells by near-infrared (NIR) optical and [89Zr]-PET imaging in subcutaneous tumor and metastatic mouse models of AVPC. Our findings identified CD133 as a novel, previously unknown marker of AR−/NE+ AVPC that can be exploited as an imaging target to assess and monitor disease progression. In addition, CD133-targeted imaging agents could aid in the development of novel therapeutics for a subtype of prostate cancer that is currently incurable by monitoring patient response to therapy.

Materials and Methods

Cell culture

HEK293T cells were purchased from the ATCC and were maintained according to ATCC guidelines. CWR-R1 cells and luciferase-expressing CWR-R1-EnzR cells were obtained from Dr. Scott Dehm (Masonic Cancer Center, University of Minnesota, Minneapolis, MN) and Dr. Donald Vander Griend (Department of Pathology/Surgery, University of Illinois at Chicago, Chicago, IL), respectively. All parental cell lines were authenticated by short-tandem repeat profiling prior to manipulation. Parental CWR-R1 and CWR-R1-EnzR cells were lentivirally transduced to express CD133 as described previously (32). Expression of CD133 in transduced cell lines (CWR-R1CD133 and CWR-R1-EnzRCD133) was confirmed via qPCR and Western blot and compared with CD133-negative parental cell lines. All cells were grown in DMEM supplemented with 10% FBS, 1% antibiotic–antimycotic, and 1% glutamax and incubated at 37°C and 5% CO2. In addition, CD133-expressing cells were continuously supplemented with 3 μg/mL puromycin to ensure stable levels of CD133 expression.

Antibody production

The protocols for biopanning, ELISA screening, scFv expression and purification, as well as affinity/specificity characterization of the isolated scFv clone, HA10, were followed as described previously (32). The heavy-chain (354 bp) and light-chain (318 bp) variable domains of the HA10 sequence were cloned separately into pFUSE2ss-derived human IgG expression vectors (InVivoGen) and cotransfected into HEK293T cells according to the manufacturer's guidelines. Following incubation, the serum was collected, filtered through a 0.45-μm filter, and purified using an iTrap Protein A HP column (GE Healthcare). The eluate was collected and concentrated using a 50 kDa centrifugal filter. A final buffer exchange was performed into 1× PBS using a Sephadex G25 PD10 desalting column (GE Healthcare). The purity of the final HA10 human IgG was analyzed by reduced and nonreduced SDS-PAGE, and the concentration was measured on the basis of absorbance at 280 nm using a NanoDrop One UV-Vis Spectrophotometer (Thermo Fisher Scientific).

Genomic analysis

Microarray data in Fig. 1 was extracted from previously published studies of a set of metastatic tumors from men with CRPC and patient-derived xenograft (PDX) models of prostate cancer (33, 34). Both datasets are available in the Gene Expression Omnibus under accessions GSE77930 and GSE93809. Whole-exome sequencing of CRPC samples published in Beltran and colleagues (23) used in Fig. 2 was acquired from the cBioPortal for Cancer Genomics (35).

Figure 1.
Figure 1.

Gene signatures demonstrate that CD133 is overexpressed in an AR−/NE+ prostate cancer phenotype. A, CD133 (PROM1) expression was evaluated across prostate cancer tumors that displayed gene signatures signifying AR and NE status. B, CD133 expression in prostate cancer patient samples was significantly increased in patients with AR−/NE+ AVPC compared with other subtypes. C, Graph documenting a negative overall correlation between CD133 and AR expression in patient tumors. D, A negative overall correlation was also observed between CD133 and PSMA expression in patient tumors. E, CD133 expression was evaluated across 24 LuCaP PDX models. F, Quantification of CD133 expression in LuCaP PDX models was significantly increased in AR−/NE+ samples compared with AR+/NE− xenografts. G, A negative overall correlation was identified between CD133 and AR expression in the LuCaP PDX models.

Figure 2.
Figure 2.

IHC shows CD133 overexpression in neuroendocrine-differentiated tissue sections. A, Whole-exome sequencing analysis of metastatic biopsies from patients with CRPC with disease characterized histologically as adenocarcinoma or neuroendocrine, documenting upregulation of CD133 in the neuroendocrine-differentiated group. B, Quantitative analysis showed a significant increase in CD133 staining intensity from adenocarcinoma to neuroendocrine-differentiated tissue sections. C, Representative images of IHC staining at different magnifications for CD133, AR, and CHGA in liver biopsies from men with neuroendocrine-differentiated and adenocarcinoma CRPC.

IHC

Curated samples for analysis were obtained from the Prostate Cancer Biorepository Network (PCBN) and the University of Minnesota Masonic Cancer Center (Minneapolis, MN) using a University of Minnesota Human Subjects Division–approved IRB protocol for tissue acquisition (IRB#1604M86269) and with written patient consent. The tissue sections were stained for CD133 using the HA10 antibody in a rabbit scaffold as previously described (23). A pathologist reviewed the slides and assigned IHC scores as previously reported (36). The staining was assessed using a quasi-continuous scoring system by multiplying the optical density level (0– no stain, 1– faint stain, and 2- definitive stain) by the percentage of cells at each staining level. The sum of three multiplicands provided a final score for each sample ranging from 0 to 200. Intense staining ranged from 140 to 200, moderate from 70 to 140, weak from 1 to 70, and an absence of immunoreactivity was 0. The samples stained for CD133 were positive for chromogranin A (CHGA; scores ranging from 70 to 200; antibody – chromaganin A PB9097 Boster Biological Technology rabbit polyclonal) and absent for AR using an antibody that recognized the protein N-terminus (androgen receptor SP107 from Sigma. The AR−/CHGA+ (n = 25) soft-tissue metastases were liver (n = 14), lymph node (n = 3), lung (n = 2), retroperitoneal (n = 4), and pleural (n = 2) while the AR+/CHGA adenocarcinoma sections (n = 10) were liver (n = 6), lymph node (n = 2), and lung (n = 2).

Animal models

All animal studies were performed in athymic nu/nu mice (Envigo) following Institutional Animal Care and Use Committee (IACUC) approval at the University of Minnesota (Minneapolis, MN). For subcutaneous tumor implantation, animals (n = 3–4/group) received unilateral injections on the right shoulder of 1 × 106 CWR-R1 or CWR-R1CD133 cells (in 100 μL) in a 1:1 dilution of Matrigel (Corning) to 1× PBS. Tumors were measured twice weekly with calipers and volumes were calculated as length × width × height. For the intracardiac dissemination model, animals (n = 4/group) received injections of 2 × 105 CWR-R1-EnzR or CWR-R1-EnzRCD133 cells (in 100 μL) in 1× PBS directly into the left ventricle of the heart, with a 75% accuracy rate. Following the intracardiac injections, mice were weighed twice/week to assess overall health and bioluminescent imaging was performed once/week to evaluate tumor formation and growth.

In vivo fluorescent imaging

HA10 IgG was labeled with IRDye 800CW NHS Ester (LI-COR Biosciences) according to the manufacturer's instructions to develop a NIR imaging agent (NIR-HA10 IgG). Mice bearing subcutaneous tumors were imaged when all tumors in each group reached a threshold of 100 mm3. Each mouse was administered 1 nmol/L (155 μg) of NIR-HA10 IgG via tail vein and imaged at 1, 5, 24, 48, 72, 96, 120, and 144 hours postinjection. Following intracardiac dissemination, mice exhibiting sizeable metastatic lesions as indicated by bioluminescent imaging (BLI) were administered 1 nmol (155 μg) of NIR-HA10 IgG via tail vein and imaged at 24, 48, 72, and 144 hours. In both studies, animals were imaged using an IVIS Spectrum Scanner (Perkin Elmer) and euthanized at a fixed endpoint 6 days after the NIR-HA10 IgG injection or monitored for overall health and terminated when tumor volumes reached 1,000 mm3 or weight decreased more than 15%. To determine fluorescent intensity of subcutaneous xenografts, manually drawn regions-of-interest (ROI) were normalized to a background level of fluorescence on each mouse. To account for variability in size and luciferase expression of intracardiac tumors, a relative radiance unit was determined by dividing the total radiant efficiency of the NIR imaging by the total counts of the BLI signal and used to quantify differences in signal between CD133-positive and CD133-negative mice.

Bioconjugation and radiochemistry

For nuclear imaging studies, HA10 IgG was conjugated to p-SCN-Bn-Deferoxamine (DFO, Macrocyclic) as described previously (37). Zirconium-89 (89Zr) was purchased from the University of Wisconsin Medical Physics Department. Once received, [89Zr]Zr-oxalate (277 MBq) in 1.0 mol/L oxalic acid (600 μL) was adjusted to pH 6.8–7.5 with 1.0 mol/L Na2CO3. To radiolabel the IgG, the DFO–HA10 IgG conjugate (400 μL, 3.49 mg/mL, 1.4 mg of mAb) in 0.5 mol/L HEPES (pH 7.5) was added to the neutralized [89Zr]Zr-oxalate solution and incubated at room temperature with gentle agitation for 1 hour. The labeled product was purified using a size-exclusion PD-10 column preequilibrated with PBS buffer. Crude and purified samples were analyzed by radio-TLC using 50 mmol/L EDTA (pH 5.0) as the eluent. The specific activity of [89Zr]Zr-HA10 IgG was calculated to be 85 MBq/mg and the radiochemical purity was >98%. The isotype control antibody was labeled using an identical procedure with a specific activity of 103 MBq/mg and radiochemical purity of 95%. Size-Exclusion HPLC analysis with a radioactive detector was not performed on any of the radiolabeled products.

Immunoreactivity

The immunoreactivity of [89Zr]Zr-HA10 IgG was assessed by using antigen-specific cellular binding assays using the CD133-transduced cell line (CWR-R1-EnzRCD133) and the non–CD133-expressing parental cell line (CWR-R1-EnzR). CWR-R1-EnzR and CWR-R1-EnzRCD133 cells were suspended in microcentrifuge tubes at concentrations of 0.5, 1, 2, 3, 4, and 5 × 106 cells/mL in 500 μL of 1× PBS. Aliquots of [89Zr]Zr-HA10 IgG (50 μL, 0.93 MBq) in 1% BSA were added to each cell suspension (final volume 550 μL) and incubated at room temperature with gentle agitation for 1 hour. Cells were resuspended and washed twice with ice-cold 1× PBS. The supernatant was removed and the [89Zr] radioactivity of the cell pellets were counted using a HIDEX Automatic Gamma Counter (HIDEX). The count data was background-corrected and the immunoreactive fraction of [89Zr]Zr-HA10 IgG was assessed by comparing the total number of counts in the cell suspensions by control samples.

Stability studies

The stability of [89Zr]Zr-HA10 IgG with respect to change in radiochemical purity was evaluated at 0, 48, 96, and 144 hours following purification. For the stability studies, 1.3 MBq of [89Zr]Zr-HA10 IgG was added to 500 μL of 1% BSA in 1× PBS and incubated at room temperature. The radiochemical purity of 5 μL of [89Zr]Zr-HA10 IgG was assessed at each time point by radio-TLC.

Biodistribution

Acute in vivo biodistribution studies were conducted to evaluate the uptake of [89Zr]Zr-HA10 IgG in mice bearing subcutaneous CWR-R1-EnzR (100–500 mm3) or CWR-R1-EnzRCD133 (100–500 mm3) tumors. Mice were randomized before the study and administered [89Zr]Zr-HA10 IgG (0.37–0.55 MBq, 1–2 μg of mAb, in 100 μL of 1× PBS for injection) via tail vein injection. Mice (n = 3–4/group) were euthanized by cervical dislocation at 24 and 72 hours postinjection. Ten organs (including the tumor) were removed, rinsed in water, dried in air for 5 minutes, weighed, and counted on an automatic gamma-counter (Hidex) for accumulation of [89Zr] radioactivity. The total number of counts (counts per minute, cpm) of each organ was compared with a standard syringe of known activity and mass. Count data were background- and decay-corrected, and the percentage injected dose per gram (%ID/g) for each tissue sample was calculated by normalization to the total amount of activity injected into each mouse.

In vivo PET/CT imaging

PET imaging experiments were conducted on an Inveon μPET/CT Scanner (Siemens Medical Solutions). Mice were administered [89Zr]Zr-HA10 IgG formulations (5.5–7.4 MBq, 25–30 μg of mAb, in 200 μL of 1× PBS) via tail vein injection. Mice were anesthetized by inhalation of 2% isoflurane and PET images were recorded at time points between 24 and 144 hours postinjection. PET list-mode data were acquired for 30 minutes using a gamma ray energy window of 350–650 keV and a coincidence timing window of 3.438 ns. CT acquisition was performed for 5 minutes at 80 kVp, 500 μA, 384 ms per step, and 340 steps covering 220 degrees. CT images were reconstructed using a Hu scaled Feldkamp algorithm resulting in 192 × 192 matrix and PET utilized Ordered Subset Expectation Maximization (OSEM-3D) with 18 subsets and 2 iterations resulting in a 128 × 128 matrix. Two-dimensional (2D) images were prepared in Inveon Research Workplace and quantified using AMIDE. An empirically determined system calibration factor was used to convert voxel count rates to activity concentrations and the resulting image data were normalized to the administered activity to parameterize images in terms of %ID/g. Drawn ellipsoid ROIs were used to determine the mean %ID/g in various tumors. The PET tracers Na[18F]F and [18F]2-fluorodeoxyglucose ([18F]FDG) were purchased from the Department of Radiology at the University of Minnesota (Minneapolis, MN). Both tracers were administered via tail vein (9 MBq per mouse) and imaged 1 hour postinjection.

Statistical analysis

All statistical analyses were performed using GraphPad 7.04. qRT-PCR and luciferase assay experiments prior to xenograft implantation were repeated three times with three technical replicates each time; all results were represented as mean ± SEM. IHC scores were compared using a Mann–Whitney t test to account for differences in sample size. Patient microarray data were analyzed using a one-way ANOVA, which was corrected for multiple comparisons using Sidak hypothesis testing and LuCaP microarray data were analyzed using a Welch t test. Pearson's correlation coefficient was used to study the relationships between the genes shown in scatterplots. Animal studies were performed with n = 3–4 and signals intensities were quantified as mean ± SEM. Statistical significance was determined using a two-way ANOVA and corrected for multiple comparisons using Sidak hypothesis testing. The symbols used to represent the P values were as follows: ns, P > 0.05; *, P ≤ 0.05; **, P ≤ 0.01; ***, P ≤ 0.001; ****, P ≤ 0.0001.

Results

CD133 is overexpressed in AR−/NE+ prostate cancer

Our initial studies on CD133 suggested an inverse relationship between the expression of AR and CD133 in a limited number of samples by IHC (32). To assess whether CD133 overexpression was associated with a particular prostate cancer phenotype, we investigated CD133 as well as gene signatures of AR status and NE differentiation in gene expression microarray data of 171 CRPC tumors from 63 rapid autopsy subjects at the University of Washington (Seattle, WA; Fig. 1A; refs. 6, 23, 33). The gene that encodes CD133, PROM1, displayed the highest level of expression in AR−/NE+ tissues (P < 0.0001, Fig. 1B). CD133 and AR expression exhibited a moderate inverse correlation (Pearson correlation = −0.5989, Fig. 1C). Similarly, expression of the prototypical AR-related genes, KLK3 and FOLH1, which encode for PSA and PSMA, respectively, were also inversely correlated to CD133 expression (Pearson correlation = −0.4789, Supplementary Fig. S1A; Pearson correlation = −0.5042; Fig. 1D).

Because early passages of PDX models display similar morphology to the original tumors from which they are derived (38), 24 early-passage LuCaP xenografts were investigated for expression of CD133. Only four PDX models displayed an AR−/NE+ gene signature and three (75%) of these models showed overexpression of PROM1 (Fig. 1E), which was statistically significant when compared with the AR+/NE− PDX models (P < 0.0001, Fig. 1F). Complimentary to the gene expression in patient samples, CD133 exhibited a very strong inverse correlation to both AR and KLK3 in the PDX models (Pearson correlation = −0.886, Fig. 1G; Pearson correlation = −0.8565; Supplementary Fig. S1B).

Further highlighting the association of CD133 with NE-differentiated prostate cancer, whole-exome sequencing, published by Beltran and colleagues (23), of patients with CRPC with adenocarcinoma (n = 34) and neuroendocrine prostate cancer (n = 15) showed an upregulation of CD133 in NE-differentiated disease (Fig. 2A; P < 0.001). Having elucidated the relationship between AR status, NE differentiation, and CD133 at the mRNA level, we next used IHC with our HA10 scFv in a rabbit scaffold to investigate CD133 protein expression in soft-tissue metastases. Patient tissues (n = 35) were classified as either adenocarcinoma (n = 10) when sections were AR+/CHGA− or neuroendocrine AVPC (n = 25) when sections were AR−/CHGA+. All of the adenocarcinoma tissue sections were negative when stained for CD133 (Fig. 2B and C). Contrarily, 92% (23/25) of the neuroendocrine AVPC tissue sections displayed intense staining and the remaining 8% (2/25) displayed moderate staining for CD133 (Fig. 2B). Scoring of the staining intensity in all samples revealed that CD133 expression was significantly different between patients with adenocarcinoma and neuroendocrine AVPC (P < 0.0001).

Detecting CD133 in vivo by NIR optical imaging

The HA10 scFv was expressed as a full-length bivalent human IgG (IgG1 scaffold) and labeled with the NIR fluorophore IRDye 800CW (NIR-HA10 IgG) for NIR optical imaging. NIR optical imaging was initially used as a proof-of-concept to document the specific localization of the antibody and acquire pharmacokinetic properties allowing for the informed selection of the appropriate radioisotope for PET imaging. Because no immortalized prostate cancer cell lines uniformly express CD133, model systems were developed. The human prostate cancer cell lines CWR-R1 and luciferase-expressing CWR-R1-EnzR were transduced to express CD133. CD133 expression in each cell line was quantified by qPCR (Supplementary Fig. S2A and S2B). Mice bearing either subcutaneous CWR-R1 (n = 4) or CWR-R1CD133 (n = 4) tumors were administered 1 nmol of NIR-HA10 IgG via tail vein and imaged at 1, 5, 24, 48, 72, 96, 120, and 144 hours. As early as 24 hours postinjection of NIR-HA10 IgG, increased uptake in the CD133-positive CWR-R1CD133 tumors was observed compared with the CD133-negative tumors (Fig. 3A). Localization of the antibody to CD133-positive tumor remained present up to 144 hours. A small amount of nonspecific localization due to the enhanced permeability retention (EPR) effect was observed in the CWR-R1 tumors; however, the antibody cleared by 72 hours postinjection. Similar EPR effects have been observed with the PSMA-targeted antibody and it is still considered specific enough for clinical translation as a theranostic agent (39). Average fluorescent intensity in CD133-positive tumors remained significantly higher than CD133-negative tumors from 24 to 72 hours (Fig. 3B). After the final 144-hour time point, the tumors and organs of the mice were excised and imaged by NIR (Fig. 3A). NIR imaging demonstrated a strong signal in the CWR-R1CD133 tumors, which was not present in the CWR-R1 tumors, verifying that the NIR-HA10 IgG was retained by the tumor and able to selectively detect CD133 up to 144 hours postinjection. Nonspecific localization of NIR-HA10 IgG in secondary tissue was not observed in the ex vivo analysis. A nonspecific human IgG1 mAb was also labeled with IRDye-800CW and administered via tail vein to CWR-R1 (n = 4) and CWR-R1CD133 (n = 4) subcutaneous xenograft mice as an isotype control (Fig. 3C and D). No localization of the isotype control antibody to the tumors was observed in the xenografts at the imaging time points and by ex vivo analysis at 144 hours postinjection. The CWR-R1CD133 and CWR-R1 tumors used in this study were fixed, sectioned, and stained for CD133 with HA10 in a rabbit scaffold for IHC. CWR-R1CD133 sections displayed high levels of CD133 expression across the entire tumor by IHC, indicating stable CD133 expression following xenograft implantation, while immunoreactivity was absent in the CWR-R1 tumor sections (Fig. 3E).

Figure 3.
Figure 3.

NIR-HA10 IgG is selective for CD133-positive tumors. A, NIR imaging of mice bearing either CD133-positive (CWR-R1CD133) or CD133-negative (CWR-R1) subcutaneous tumors. Mice received 1 nmol/L of NIR-HA10 IgG via tail vein and then were imaged serially at the designated times. Ex vivo analysis of tumor and secondary organs imaged at 144 hours. Key: 1, tumor; 2, liver; 3, stomach; 4, intestines; 5, kidneys; 6, pancreas; 7, spleen; 8, heart; 9, lungs; 10, prostate. B, Quantitative analysis of the subcutaneous tumors from the NIR optical imaging experiment displayed significantly higher signals between 24 and 72 hours postinjection. Values represent mean ± SEM of 4 animals/group. C, NIR imaging of CWR-R1CD133 and CWR-R1 xenografts with the IRDye 800CW–labeled isotype control antibody (NIR-Isotype Control IgG; 1 nmol/L per mouse) documenting a lack of tumor uptake by imaging and ex vivo analysis. D, Quantitative analysis of the subcutaneous tumors from the NIR optical imaging experiment injected with the NIR-Isotype Control IgG. Values represent mean ± SEM of 4 animals/group. E, IHC images (40×) of CD133-positive (CWR-R1-EnzRCD133) or CD133-negative (CWR-R1-EnzR) tumors (left: H&E, right: CD133). F, NIR optical imaging of representative mice possessing CWR-R1-EnzRCD133 or CWR-R1-EnzR metastatic tumors. Mice received 1 nmol of NIR-HA10 IgG via tail vein and were then imaged at designated times. G, Quantitative analysis of metastatic tumors from mice used in F displayed a significantly higher signal at 48 hours postinjection. Values represent mean ± SEM of 3–4 animals/group.

The ability of NIR-HA10 IgG to detect small, dispersed CD133-postive lesions in complex microenvironments was next tested in a metastasis model. To create an appropriate spontaneous metastasis model, mice received intracardiac injections of either luciferase-expressing CWR-R1-EnzR (n = 4) or luciferase-expressing CWR-R1-EnzRCD133 (n = 3) cells. The luciferase activity of the cells was assessed 1–3 days prior to injection in all mouse models (Supplementary Fig. S2C). Bioluminescent imaging was performed on the mice once per week to assess lesion formation and size. Once mice in each group had at least one sizeable tumor (>3 × 105 total counts), they received 1 nmol of NIR-HA10 IgG via tail vein. NIR optical imaging was then conducted at 24, 48, 72, and 144 hours postinjection (Fig. 3F). Comparable with the subcutaneous model, the signal was highly visible and specific for CD133-positive tumors at 24 hours, remained high for up to 72 hours, and was still detectable at 144 hours. The quantitative analysis supported this observation demonstrating a significant difference in relative radiance at 48 hours (P = 0.0383) and a noticeable decline in signal between 72 and 144 hours in CD133-positive tumors (Fig. 3G). Furthermore, the relative radiance signal remained low in the all of the CD133-negative tumors with minimal tumor or mouse variability, suggesting that the NIR-HA10 IgG is highly selective for CD133-positive tumors.

PET/CT imaging of CD133

The results of the NIR optical imaging studies suggested that longitudinal PET-imaging studies could be performed using radiolabeled HA10 IgG. Therefore, we decided to use the long-lived positron-emitting radioisotope [89Zr] (t1/2 = 3.3 days) for imaging. In addition, PET imaging with [89Zr]ZrDFO-conjugated antibodies, including studies with the PSMA-targeted antibody J591, are commonplace in the clinic (39–42). HA10 IgG was first conjugated to DFO and radiolabeled with [89Zr]oxalate at room temperature under slightly alkaline conditions using modified methods from Zeglis and colleagues (37). Purity was assessed by radio-TLC and peaks were compared with a pure [89Zr4+] standard (Supplementary Fig. S3A). Only [89Zr]Zr-HA10 IgG sample preparations, which resulted in a purity of >98% and a specific activity of >74MBq/mg were used for future analyses.

The stability of [89Zr]Zr-HA10 IgG was determined by radio-TLC after incubation in 1% BSA in PBS for up to 144 hours at room temperature (Supplementary Fig. S3B). The radiochemical purity remained above 96% at all the time points, indicating a <2% decrease at any given time. Thus, [89Zr]Zr-HA10 IgG was expected to remain intact in vivo on the time scale described in our PET imaging studies. Similarly, immunoreactivity was measured by an antigen-specific in vitro cellular association assay using CWR-R1-EnzR and CWR-R1-EnzRCD133 cells (Supplementary Fig. S3C). The immunoreactive fraction of [89Zr]Zr-HA10 IgG was directly proportional to the number of CD133-positive cells in the sample and displayed a strong linear relationship in the CD133-positive cell line (R2 = 0.9588). CD133-negative control cells showed no binding to [89Zr]Zr-HA10 IgG (R2 = 0.0003), further demonstrating the specificity of [89Zr]Zr-HA10 IgG for CD133-expressing cells.

The ability of [89Zr[Zr]-HA10 IgG to detect CD133-postive cancer cells in vivo was first tested in mice bearing subcutaneous CWR-R1CD133 (n = 3) or parental CWR-R1 (n = 3) tumors. Mice were injected with 5.5 MBq (67 μg, 84 MBq/mg) via tail vein and imaged by μPET/CT at 24, 48, 72, and 144 hours (Fig. 4A). Transverse 2D images of the CWR-R1CD133 xenografts showed the highest signals in the tumor compared with the CWR-R1 xenografts, which showed high liver uptake. In addition, three-dimensional (3D) reconstructions were generated to assess [89Zr]Zr-HA10 IgG uptake across multiple planes. Tumor margins were well defined in CWR-R1CD133 images between 24 and 72 hours, which was not observed in the CD133-negative xenografts. Both groups of mice displayed nearly complete clearance at 144 hours. Time activity curves were generated from the PET images to display the mean %ID/g of [89Zr] uptake in the CD133-positive versus CD133-negative groups of tumor-bearing mice (Fig. 4B). A significant difference was observed at the 24- and 48-hour time points with mean %ID/g values averaging 28.96 ± 0.92 (CWR-R1CD133) and 18.97 ± 1.56 (CWR-R1) at 24 hours (P = 0.0003) and 23.60 ± 2.04 (CWR-R1CD133) and 15.94 ± 1.89 (CWR-R1) at 48 hours (P = 0.0041).

Figure 4.
Figure 4.

[89Zr]Zr-HA10 IgG displays significantly higher uptake in CD133-positive tumors. A, Reconstructed 3D and 2D PET/CT images of mice bearing either CD133-positive (CWR-R1CD133) or CD133-negative (CWR-R1) subcutaneous tumors. Mice received 5.5 MBq of [89Zr]Zr-HA10 IgG via tail vein and then were imaged at the designated times. B, Quantitative analysis of subcutaneous tumors from mice used in A displayed significantly higher signals at 24 and 48 hours postinjection. Values represent mean ± SEM of 3 animals/group. C, Ex vivo biodistribution of [89Zr]Zr-HA10 IgG in all tissues of mice bearing subcutaneous CWR-R1-EnzRCD133 or CWR-R1-EnzR tumors. Mice were injected with 0.37–0.55 MBq of [89Zr]Zr-HA10 IgG via tail vein prior to sacrifice at the designated time points. Values represent mean ± SEM of 3–4 animals. D, 2D PET/CT images of CWR-R1CD133 and CWR-R1 xenograft mice imaged with the [89Zr]-labeled isotype control antibody (5.5 MBq) at different time points and FDG (9 MBq) at 1 hour postinjection via tail vein.

Ex vivo biodistribution was performed to evaluate overall distribution and potential off-target effects of [89Zr]Zr-HA10 IgG (Fig. 4C; Supplementary Table S1). The data reveal that distribution of [89Zr]Zr-HA10 IgG was comparable in all organs between the two groups, with the exception of the tumors. Uptake in the liver, the main clearance organ for full-length immunoglobulins, and the spleen where immunoglobulins are known to localize nonspecifically was observed in the models at the time points analyzed as anticipated (43, 44). At 24 hours, [89Zr] uptake was higher in CD133-positive tumors at a level which was considered insignificant, but at 72 hours the average %ID/g of [89Zr] uptake was approximately 3-fold higher in CD133-positive tumors (P < 0.0001). Similarly, minimal [89Zr] uptake was observed in various other organs. These data correlate well with the PET imaging data and suggest that CD133 is a promising antigen that can be selectively targeted for the imaging of CD133-expressing tumors. The isotype control antibody was radiolabeled with [89Zr] and injected into CWR-R1CD133 (n = 3) and CWR-R1 (n = 3) subcutaneous xenografts [Fig. 4D; 5.5 MBq (53 μg, 103 MBq/mg)]. Imaging at 24, 48, and 72 hours postinjection documented insignificant localization to the tumors. In the 2D-reconstructed views, liver uptake was primarily observed. CWR-R1CD133 (n = 2) and CWR-R1 (n = 2) mice were also injected with the commonly used PET tracer [18F]FDG (9 MBq). Poor uptake and tumor specificity of [18F]FDG was observed further highlighting the need for new imaging agents for prostate cancer.

The diagnostic potential of [89Zr]Zr-HA10 IgG was further investigated by μPET/CT imaging in mice bearing spontaneous metastatic lesions. Following intracardiac injection with luciferase expressing CWR-R1-EnzRCD133 or CWR-R1-EnzR cells, mice underwent bioluminescent imaging once per week to monitor spontaneous lesion development and growth. At approximately 3.5 weeks postinjection, the remaining healthy CD133-positive (n = 2) and CD133-negative (n = 2) mice had developed multiple metastatic lesions in or around the bone (Fig. 5A). Mice were injected with 7.4 MBq (22 μg, 350 MBq/mg) of [89Zr]Zr-HA10 IgG via tail vein and imaged by μPET/CT at 24 and 72 hours. 2D and 3D images revealed a high level of [89Zr] distribution at 24 hours in both groups of mice, while [89Zr] uptake at 72 hours was exclusively observed in the tumors of CD133-positive mice. Quantification of the mean %ID/g of [89Zr] uptake in the tumors confirmed these results by showing that there was no significant difference at 24 hours despite higher signals in the CD133-positive tumors, 27.41 ± 2.50 versus 19.35 ± 2.63 (Fig. 5B). At 72 hours, the mean %ID/g in the tumors was significantly different among the two groups, 24.30 ± 3.19 and 11.82 ± 0.57, respectively (P = 0.0069). Imaging of a CD133-postive dissemination model mice (representative image of n = 2) with Na[18F]F (9 MBq) documented localization to the bone and a lack of tumor specificity (Fig. 5C).

Figure 5.
Figure 5.

[89Zr]Zr-HA10 IgG can selectively detect CD133-positive metastatic prostate cancer tumors by PET/CT imaging. A, PET/CT imaging of representative mice bearing either CD133-positive (CWR-R1-EnzRCD133) or CD133-negative (CWR-R1-EnzR) metastatic tumors. Mice received 7.4 MBq of [89Zr]Zr-HA10 IgG via tail vein and then were imaged at the designated times. B, Quantitative analysis of metastatic tumors from mice used in A displayed significantly higher signals at 72 hours postinjection. Values represent mean ± SEM of 4 tumors/group from 2 animals/group. C, Imaging of a CD133-positive (CWR-R1-EnzRCD133) metastatic model mouse with Na[18F]F (9 MBq) 1 hour postinjection.

Discussion

The emergence of non-AR–driven disease in patients with CRPC has steadily increased after the introduction of AR signaling inhibitors such as abiraterone and enzalutamide. At this stage of disease, survival is poor and therapies that dramatically prolong life do not exist. While new therapies are in demand, new imaging agents to monitor disease progression and response to therapy are also needed. PSMA-targeted radiotracers that have shown promise at detecting bone and visceral metastases in patients with adenocarcinoma are ineffective due to the lack of PSMA expression in non-AR–driven prostate cancer. As such, novel antigens and targeted imaging agents are needed to aid in the detection and monitoring of this subtype of disease. In this study, we have identified CD133 as a new targetable antigen that is overexpressed in one of these non–PSMA-expressing patient populations and developed a novel antibody-based imaging agent that can accurately detect CD133 in preclinical models of prostate cancer. To our knowledge, this is the first study demonstrating that CD133 is a marker for AR−/NE+ AVPC. Furthermore, despite the use of preclinical CD133-targeted PET imaging in other cancers (45), this is the first time that CD133 has been targeted for imaging of prostate cancer.

Our targeted agent, HA10 IgG, showed significant selectivity and sensitivity for CD133-expressing tumors using multiple imaging modalities and cancer models, verifying the specificity of the antibody–antigen interaction. Because of the fact that no prostate cancer cell lines express significant levels of endogenous CD133, we had to use models engineered to express CD133. Although artificial, the IHC staining intensities of CD133 in AVPC biopsies and our engineered models (Figs. 2C and 3E) were similar suggesting that CD133 expression in our models was representative of CD133 expression in patients with AVPC. Interestingly, subcutaneous xenograft models in both the NIR and PET imaging studies displayed better tumoral uptake at earlier time points (between 24 and 48 hours, Figs. 3A and 4A), whereas, metastatic xenografts displayed better uptake at slightly later time points (between 48 and 72 hours, Figs. 3D and 5A). It has been shown that different prostate cancer xenografts exhibit varying degrees of vasculature as determined by tumor–stromal interaction, size, and site of the tumor (46). Differences in these factors are likely to account for the slightly different uptake kinetics exhibited by the HA10 IgG. In addition, PET imaging revealed that [89Zr]Zr-HA10 IgG tumoral uptake varied within the CD133-positive metastatic tumors. While all CD133-positive tumors were visible at 72 hours in the 2D images, only some tumors were visible in the 3D reconstruction after background normalization, suggesting there was less [89Zr]Zr-HA10 IgG uptake in some of the metastatic lesions. Because of the high signals in the small spinal tumor and large mandibular tumor, we postulated that size and anatomic location were not the primary causes of this occurrence. We also determined that CD133 expression is stable following implantation of the xenografts, however, we did not rule out that the metastatic process and tumor microenvironment of the secondary site may have altered the tumor phenotype and resulted in less [89Zr]Zr-HA10 IgG uptake. Multiple studies have suggested that preclinical metastatic models may lack the ability to faithfully mimic the tumor microenvironment during metastasis (47–49), which may explain the reduced PET signal in some of the CD133-positive metastatic lesions.

In conclusion, this study illustrates the importance of identifying new antigens for targeted imaging and treatment monitoring of patients with AVPC. Our data show that patients with AVPC with an AR−/NE+ phenotype possess high levels of the surface protein, CD133. Our previous studies show that the epitope our antibody recognizes on CD133 is not highly expressed in early stages of prostate cancer or healthy tissues (32), demonstrating its promise as targetable marker for patients with late-stage AVPC. Furthermore, our data show that CD133 can be exploited for improved imaging using a novel antibody developed by our lab. HA10 IgG was specific for CD133-positive tumors by various imaging modalities, including clinically relevant modality PET/CT imaging. These encouraging results indicate that [89Zr]Zr-HA10 IgG displays high potential as a radiotracer for noninvasive immunoPET imaging of patients with AR−/NE+ AVPC.

Disclosure of Potential Conflicts of Interest

No potential conflicts of interest were disclosed.

Authors' Contributions

Conception and design: P.M. Glumac, J.P. Gallant, A.M. LeBeau

Development of methodology: P.M. Glumac, J.P. Gallant, Y. Li, A.M. LeBeau

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): P.M. Glumac, J.P. Gallant, P. Murugan, S. Gupta, I.M. Coleman, P.S. Nelson

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): P.M. Glumac, J.P. Gallant, M. Shapovalova, P. Murugan, I.M. Coleman, A.M. LeBeau

Writing, review, and/or revision of the manuscript: P.M. Glumac, J.P. Gallant, Y. Li, S. Gupta, I.M. Coleman, P.S. Nelson, S.M. Dehm, A.M. LeBeau

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): P.M. Glumac, J.P. Gallant

Study supervision: S.M. Dehm, A.M. LeBeau

Acknowledgments

The authors acknowledge the University Imaging Centers at the University of Minnesota (Minneapolis, MN) for their technical advice and coordination of various imaging equipment. In particular, the authors thank Adrienne Sherman for her confocal microscopy assistance and Dr. Thomas Pengo for his advice and training regarding the medical imaging data analysis. They thank the University of Minnesota's Research Animal Resources Staff for assisting with research animal maintenance and include a special thanks to Dr. Nathan Koewler for his help in producing their intracardiac mouse model. They are also grateful to Colleen Forster and the rest of the Biorepository and Laboratory Services Division at the University of Minnesota (Minneapolis, MN) for their histology and pathology support. The authors are extremely grateful to Dr. Joshua M. Lang of the Carbone Cancer Center at the University of Wisconsin (Madison, WI) and Dr. John K. Lee of the Fred Hutchinson Cancer Research Center (Seattle, WA) for their assistance with this project. This work was supported by a Prostate Cancer Foundation Young Investigator Award (to A.M. LeBeau), Prostate Cancer Foundation Challenge Awards (to A.M. LeBeau and S.M. Dehm), the Minnesota Partnership for Biotechnology and Medical Genomics Infrastructure Award (MNP IF 16.05; to A.M. LeBeau), NIH/NCI CA090628 Paul Calabresi K12 Award (to A.M. LeBeau), NIH/NCI R01 CA237272 (to A.M LeBeau), NIH/NCI R01 CA233562 (to A.M LeBeau), and NIH/NCI R01 CA174777 (to S.M. Dehm). The Prostate Cancer Biorepository Network is funded by the Department of Defense Prostate Cancer Research Program Awards (W81XWH-14-2-0182, W81XWH-14-2-0183, W81XWH-14-2-0185, W81XWH-14-2-0186, and W81XWH-15-2-0062).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Footnotes

  • Note: Supplementary data for this article are available at Clinical Cancer Research Online (http://clincancerres.aacrjournals.org/).

  • Clin Cancer Res 2020;26:1054–64

  • Received May 24, 2019.
  • Revision received September 21, 2019.
  • Accepted November 7, 2019.
  • Published first November 15, 2019.

References

  1. 1.↵
    1. Nevedomskaya E,
    2. Baumgart SJ,
    3. Haendler B
    . Recent advances in prostate cancer treatment and drug discovery. Int J Mol Sci 2018;19:pii:E1359.
    OpenUrl
  2. 2.↵
    1. Rickman DS,
    2. Beltran H,
    3. Demichelis F,
    4. Rubin MA
    . Biology and evolution of poorly differentiated neuroendocrine tumors. Nat Med 2017;23:1–10.
    OpenUrlCrossRefPubMed
  3. 3.↵
    1. Wadosky KM,
    2. Koochekpour S
    . Molecular mechanisms underlying resistance to androgen deprivation therapy in prostate cancer. Oncotarget 2016;7:64447–70.
    OpenUrl
  4. 4.↵
    1. Yap TA,
    2. Smith AD,
    3. Ferraldeschi R,
    4. Al-Lazikani B,
    5. Workman P,
    6. de Bono JS
    . Drug discovery in advanced prostate cancer: translating biology into therapy. Nat Rev Drug Discov 2016;15:699–718.
    OpenUrlCrossRef
  5. 5.↵
    1. Nouri M,
    2. Caradec J,
    3. Lubik AA,
    4. Li N,
    5. Hollier BG,
    6. Takhar M,
    7. et al.
    Therapy-induced developmental reprogramming of prostate cancer cells and acquired therapy resistance. Oncotarget 2017;8:18949–67.
    OpenUrl
  6. 6.↵
    1. Bluemn EG,
    2. Coleman IM,
    3. Lucas JM,
    4. Coleman RT,
    5. Hernandez-Lopez S,
    6. Tharakan R,
    7. et al.
    Androgen receptor pathway-independent prostate cancer is sustained through FGF signaling. Cancer Cell 2017;32:474–89.
    OpenUrlCrossRef
  7. 7.↵
    1. Beltran H,
    2. Tomlins S,
    3. Aparicio A,
    4. Arora V,
    5. Rickman D,
    6. Ayala G,
    7. et al.
    Aggressive variants of castration-resistant prostate cancer. Clin Cancer Res 2014;20:2846–50.
    OpenUrlAbstract/FREE Full Text
  8. 8.↵
    1. Aparicio AM,
    2. Harzstark AL,
    3. Corn PG,
    4. Wen S,
    5. Araujo JC,
    6. Tu SM,
    7. et al.
    Platinum-based chemotherapy for variant castrate-resistant prostate cancer. Clin Cancer Res 2013;19:3621–30.
    OpenUrlAbstract/FREE Full Text
  9. 9.↵
    1. Vlachostergios PJ,
    2. Puca L,
    3. Beltran H
    . Emerging variants of castration-resistant prostate cancer. Curr Oncol Rep 2017;19:32.
    OpenUrl
  10. 10.↵
    1. Sheikhbahaei S,
    2. Jones KM,
    3. Werner RA,
    4. Salas-Fragomeni RA,
    5. Marcus CV,
    6. Higuchi T,
    7. et al.
    (18)F-NaF-PET/CT for the detection of bone metastasis in prostate cancer: a meta-analysis of diagnostic accuracy studies. Ann Nucl Med 2019;33:351–61.
    OpenUrl
  11. 11.↵
    1. Wondergem M,
    2. van der Zant FM,
    3. Knol RJJ,
    4. Burgers AMG,
    5. Bos SD,
    6. de Jong IJ,
    7. et al.
    (99m)Tc-HDP bone scintigraphy and (18)F-sodiumfluoride PET/CT in primary staging of patients with prostate cancer. World J Urol 2018;36:27–34.
    OpenUrl
  12. 12.↵
    1. Lindenberg L,
    2. Choyke P,
    3. Dahut W
    . Prostate cancer imaging with novel PET tracers. Curr Urol Rep 2016;17:18.
    OpenUrl
  13. 13.↵
    1. Lindenberg ML,
    2. Turkbey B,
    3. Mena E,
    4. Choyke PL
    . Imaging locally advanced, recurrent, and metastatic prostate cancer: a review. JAMA Oncol 2017;3:1415–22.
    OpenUrl
  14. 14.↵
    1. Halabi S,
    2. Kelly WK,
    3. Ma H,
    4. Zhou H,
    5. Solomon NC,
    6. Fizazi K,
    7. et al.
    Meta-analysis evaluating the impact of site of metastasis on overall survival in men with castration-resistant prostate cancer. J Clin Oncol 2016;34:1652–9.
    OpenUrlAbstract/FREE Full Text
  15. 15.↵
    1. Zhu A,
    2. Lee D,
    3. Shim H
    . Metabolic positron emission tomography imaging in cancer detection and therapy response. Semin Oncol 2011;38:55–69.
    OpenUrlCrossRefPubMed
  16. 16.↵
    1. Phelps ME
    . Positron emission tomography provides molecular imaging of biological processes. Proc Natl Acad Sci U S A 2000;97:9226–33.
    OpenUrlAbstract/FREE Full Text
  17. 17.↵
    1. Liu Y,
    2. Zuckier LS,
    3. Ghesani NV
    . Dominant uptake of fatty acid over glucose by prostate cells: a potential new diagnostic and therapeutic approach. Anticancer Res 2010;30:369–74.
    OpenUrlAbstract/FREE Full Text
  18. 18.↵
    1. Dusing RW,
    2. Peng W,
    3. Lai SM,
    4. Grado GL,
    5. Holzbeierlein JM,
    6. Thrasher JB,
    7. et al.
    Prostate-specific antigen and prostate-specific antigen velocity as threshold indicators in 11C-acetate PET/CTAC scanning for prostate cancer recurrence. Clin Nucl Med 2014;39:777–83.
    OpenUrlCrossRefPubMed
  19. 19.↵
    1. Umbehr MH,
    2. Muntener M,
    3. Hany T,
    4. Sulser T,
    5. Bachmann LM
    . The role of 11C-choline and 18F-fluorocholine positron emission tomography (PET) and PET/CT in prostate cancer: a systematic review and meta-analysis. Eur Urol 2013;64:106–17.
    OpenUrlCrossRefPubMed
  20. 20.↵
    1. Turkbey B,
    2. Mena E,
    3. Shih J,
    4. Pinto PA,
    5. Merino MJ,
    6. Lindenberg ML,
    7. et al.
    Localized prostate cancer detection with 18F FACBC PET/CT: comparison with MR imaging and histopathologic analysis. Radiology 2014;270:849–56.
    OpenUrlCrossRefPubMed
  21. 21.↵
    1. Pandit-Taskar N,
    2. O'Donoghue JA,
    3. Durack JC,
    4. Lyashchenko SK,
    5. Cheal SM,
    6. Beylergil V,
    7. et al.
    A phase I/II study for analytic validation of 89Zr-J591 immunoPET as a molecular imaging agent for metastatic prostate cancer. Clin Cancer Res 2015;21:5277–85.
    OpenUrlAbstract/FREE Full Text
  22. 22.↵
    1. Tosoian JJ,
    2. Gorin MA,
    3. Rowe SP,
    4. Andreas D,
    5. Szabo Z,
    6. Pienta KJ,
    7. et al.
    Correlation of PSMA-targeted (18)F-DCFPyL PET/CT findings with immunohistochemical and genomic data in a patient with metastatic neuroendocrine prostate cancer. Clin Genitourin Cancer 2017;15:e65–e8.
    OpenUrl
  23. 23.↵
    1. Beltran H,
    2. Prandi D,
    3. Mosquera JM,
    4. Benelli M,
    5. Puca L,
    6. Cyrta J,
    7. et al.
    Divergent clonal evolution of castration-resistant neuroendocrine prostate cancer. Nat Med 2016;22:298–305.
    OpenUrlCrossRefPubMed
  24. 24.↵
    1. Parimi V,
    2. Goyal R,
    3. Poropatich K,
    4. Yang XJ
    . Neuroendocrine differentiation of prostate cancer: a review. Am J Clin Exp Urol 2014;2:273–85.
    OpenUrlPubMed
  25. 25.↵
    1. Minamimoto R,
    2. Sonni I,
    3. Hancock S,
    4. Vasanawala S,
    5. Loening A,
    6. Gambhir SS,
    7. et al.
    Prospective evaluation of (68)Ga-RM2 PET/MRI in patients with biochemical recurrence of prostate cancer and negative findings on conventional imaging. J Nucl Med 2018;59:803–8.
    OpenUrlAbstract/FREE Full Text
  26. 26.↵
    1. Baratto L,
    2. Duan H,
    3. Laudicella R,
    4. Toriihara A,
    5. Hatami N,
    6. Ferri V,
    7. et al.
    Physiological (68)Ga-RM2 uptake in patients with biochemically recurrent prostate cancer: an atlas of semi-quantitative measurements. Eur J Nucl Med Mol Imaging 2020;47:115–22.
    OpenUrl
  27. 27.↵
    1. Iagaru A
    . Will GRPR compete with PSMA as a target in prostate cancer? J Nucl Med 2017;58:1883–4.
    OpenUrlFREE Full Text
  28. 28.↵
    1. Rezazadeh F,
    2. Sadeghzadeh N
    . Tumor targeting with (99m) Tc radiolabeled peptides: clinical application and recent development. Chem Biol Drug Des 2019;93:205–21.
    OpenUrl
  29. 29.↵
    1. Moody TW,
    2. Ramos-Alvarez I,
    3. Jensen RT
    . Neuropeptide G protein-coupled receptors as oncotargets. Front Endocrinol 2018;9:345.
    OpenUrl
  30. 30.↵
    1. Pesapane F,
    2. Czarniecki M,
    3. Suter MB,
    4. Turkbey B,
    5. Villeirs G
    . Imaging of distant metastases of prostate cancer. Med Oncol 2018;35:148.
    OpenUrl
  31. 31.↵
    1. Glumac PM,
    2. LeBeau AM
    . The role of CD133 in cancer: a concise review. Clin Transl Med 2018;7:18.
    OpenUrl
  32. 32.↵
    1. Glumac PM,
    2. Forster CL,
    3. Zhou H,
    4. Murugan P,
    5. Gupta S,
    6. LeBeau AM
    . The identification of a novel antibody for CD133 using human antibody phage display. Prostate 2018;78:981–91.
    OpenUrl
  33. 33.↵
    1. Kumar A,
    2. Coleman I,
    3. Morrissey C,
    4. Zhang X,
    5. True LD,
    6. Gulati R,
    7. et al.
    Substantial interindividual and limited intraindividual genomic diversity among tumors from men with metastatic prostate cancer. Nat Med 2016;22:369–78.
    OpenUrlCrossRefPubMed
  34. 34.↵
    1. Zhang X,
    2. Coleman IM,
    3. Brown LG,
    4. True LD,
    5. Kollath L,
    6. Lucas JM,
    7. et al.
    SRRM4 expression and the loss of REST activity may promote the emergence of the neuroendocrine phenotype in castration-resistant prostate cancer. Clin Cancer Res 2015;21:4698–708.
    OpenUrlAbstract/FREE Full Text
  35. 35.↵
    1. Gao J,
    2. Aksoy BA,
    3. Dogrusoz U,
    4. Dresdner G,
    5. Gross B,
    6. Sumer SO,
    7. et al.
    Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal 2013;6:pl1.
    OpenUrlAbstract/FREE Full Text
  36. 36.↵
    1. Roudier MP,
    2. Winters BR,
    3. Coleman I,
    4. Lam HM,
    5. Zhang X,
    6. Coleman R,
    7. et al.
    Characterizing the molecular features of ERG-positive tumors in primary and castration resistant prostate cancer. Prostate 2016;76:810–22.
    OpenUrl
  37. 37.↵
    1. Zeglis BM,
    2. Lewis JS
    . The bioconjugation and radiosynthesis of 89Zr-DFO-labeled antibodies. J Vis Exp 2015;96:52521.
    OpenUrl
  38. 38.↵
    1. Nguyen HM,
    2. Vessella RL,
    3. Morrissey C,
    4. Brown LG,
    5. Coleman IM,
    6. Higano CS,
    7. et al.
    LuCaP prostate cancer patient-derived xenografts reflect the molecular heterogeneity of advanced disease and serve as models for evaluating cancer therapeutics. Prostate 2017;77:654–71.
    OpenUrl
  39. 39.↵
    1. Holland JP,
    2. Divilov V,
    3. Bander NH,
    4. Smith-Jones PM,
    5. Larson SM,
    6. Lewis JS
    . 89Zr-DFO-J591 for immunoPET of prostate-specific membrane antigen expression in vivo. J Nucl Med 2010;51:1293–300.
    OpenUrlAbstract/FREE Full Text
  40. 40.↵
    1. Borjesson PK,
    2. Jauw YW,
    3. Boellaard R,
    4. de Bree R,
    5. Comans EF,
    6. Roos JC,
    7. et al.
    Performance of immuno-positron emission tomography with zirconium-89-labeled chimeric monoclonal antibody U36 in the detection of lymph node metastases in head and neck cancer patients. Clin Cancer Res 2006;12:2133–40.
    OpenUrlAbstract/FREE Full Text
  41. 41.↵
    1. Perk LR,
    2. Stigter-van Walsum M,
    3. Visser GW,
    4. Kloet RW,
    5. Vosjan MJ,
    6. Leemans CR,
    7. et al.
    Quantitative PET imaging of Met-expressing human cancer xenografts with 89Zr-labelled monoclonal antibody DN30. Eur J Nucl Med Mol Imaging 2008;35:1857–67.
    OpenUrlCrossRefPubMed
  42. 42.↵
    1. Dijkers EC,
    2. Oude Munnink TH,
    3. Kosterink JG,
    4. Brouwers AH,
    5. Jager PL,
    6. de Jong JR,
    7. et al.
    Biodistribution of 89Zr-trastuzumab and PET imaging of HER2-positive lesions in patients with metastatic breast cancer. Clin Pharmacol Ther 2010;87:586–92.
    OpenUrlCrossRefPubMed
  43. 43.↵
    1. LeBeau AM,
    2. Sevillano N,
    3. Markham K,
    4. Winter MB,
    5. Murphy ST,
    6. Hostetter DR,
    7. et al.
    Imaging active urokinase plasminogen activator in prostate cancer. Cancer Res 2015;75:1225–35.
    OpenUrlAbstract/FREE Full Text
  44. 44.↵
    1. LeBeau AM,
    2. Duriseti S,
    3. Murphy ST,
    4. Pepin F,
    5. Hann B,
    6. Gray JW,
    7. et al.
    Targeting uPAR with antagonistic recombinant human antibodies in aggressive breast cancer. Cancer Res 2013;73:2070–81.
    OpenUrlAbstract/FREE Full Text
  45. 45.↵
    1. Gaedicke S,
    2. Braun F,
    3. Prasad S,
    4. Machein M,
    5. Firat E,
    6. Hettich M,
    7. et al.
    Noninvasive positron emission tomography and fluorescence imaging of CD133+ tumor stem cells. Proc Natl Acad Sci U S A 2014;111:E692–701.
    OpenUrlAbstract/FREE Full Text
  46. 46.↵
    1. Burrell JS,
    2. Walker-Samuel S,
    3. Boult JK,
    4. Baker LC,
    5. Jamin Y,
    6. Halliday J,
    7. et al.
    Investigating the vascular phenotype of subcutaneously and orthotopically propagated PC3 prostate cancer xenografts using combined carbogen ultrasmall superparamagnetic iron oxide MRI. Top Magn Reson Imaging 2016;25:237–43.
    OpenUrl
  47. 47.↵
    1. Song H,
    2. Shahverdi K,
    3. Huso DL,
    4. Wang Y,
    5. Fox JJ,
    6. Hobbs RF,
    7. et al.
    An immunotolerant HER-2/neu transgenic mouse model of metastatic breast cancer. Clin Cancer Res 2008;14:6116–24.
    OpenUrlAbstract/FREE Full Text
  48. 48.↵
    1. Werbeck JL,
    2. Thudi NK,
    3. Martin CK,
    4. Premanandan C,
    5. Yu L,
    6. Ostrowksi MC,
    7. et al.
    Tumor microenvironment regulates metastasis and metastasis genes of mouse MMTV-PymT mammary cancer cells in vivo. Vet Pathol 2014;51:868–81.
    OpenUrlCrossRefPubMed
  49. 49.↵
    1. Wang M,
    2. Zhao J,
    3. Zhang L,
    4. Wei F,
    5. Lian Y,
    6. Wu Y,
    7. et al.
    Role of tumor microenvironment in tumorigenesis. J Cancer 2017;8:761–73.
    OpenUrlCrossRef
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Exploitation of CD133 for the Targeted Imaging of Lethal Prostate Cancer
Paige M. Glumac, Joseph P. Gallant, Mariya Shapovalova, Yingming Li, Paari Murugan, Shilpa Gupta, Ilsa M. Coleman, Peter S. Nelson, Scott M. Dehm and Aaron M. LeBeau
Clin Cancer Res March 1 2020 (26) (5) 1054-1064; DOI: 10.1158/1078-0432.CCR-19-1659
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