First evaluation of [ 68 Ga]Ga-NOTA-(TMVP1) 2 for imaging VEGFR-3 in ovarian cancer patients

First evaluation of [ 68 Ga]Ga-NOTA-(TMVP1) 2 for imaging VEGFR-3 in ovarian cancer patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article First evaluation of [ 68 Ga]Ga-NOTA-(TMVP1) 2 for imaging VEGFR-3 in ovarian cancer patients Xi Chen, Fei Li, Yao Si, Jun Dai, Ling Xi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5358746/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective To evaluate the safety and VEGFR-3 imaging effects of [ 68 Ga]Ga-NOTA-(TMVP1) 2 in ovarian cancer patients. Methods 13 patients with ovarian cancer were recruited and underwent radionuclide imaging with [ 68 Ga]Ga-NOTA-(TMVP1) 2 . The safety of [ 68 Ga]Ga-NOTA-(TMVP1) 2 was assessed in vivo (including vital signs, biochemical indices, ECG, allergic reactions, etc.) and its imaging effect on VEGFR-3 was explored. Results A total of 1 patient with primary ovarian cancer and 12 patients with recurrent ovarian cancer, with an age range of 41–54 years, were included in the study. 13 ovarian cancer patients had a total of 49 18 F-FDG-positive lesions, 63.3% of which were positive for [ 68 Ga]Ga-NOTA-(TMVP1) 2 . The higher expression of VEGFR-3 in [ 68 Ga]Ga-NOTA-(TMVP1) 2 -positive ovarian cancer lesions was found by immunohistochemical staining, which was positively correlated. Meanwhile, [ 68 Ga]Ga-NOTA-(TMVP1) 2 is a safe radiotracer as no significant side effects have been found in the human. Conclusions In conclusion, [ 68 Ga]Ga-NOTA-(TMVP1) 2 enables precise molecular imaging of VEGFR-3 in ovarian cancer patients with a favourable safety profile, providing a new tool for the in vivo assessment of VEGFR-3 in ovarian cancer. Figures Figure 1 Figure 2 Figure 3 Figure 4 Background The incidence rate of ovarian cancer has been on the rise year by year in recent years, and the death rate ranks first among malignant tumors of the female reproductive system. Ovarian cancer often has no obvious symptoms in the early stage, and about 75% of the patients are already in the advanced stage when they are diagnosed [ 1 , 2 ] . Metastasis is the leading cause of death in patients with advanced ovarian cancer [ 3 ] . There are 4 metastatic routes of ovarian cancer, including hematogenous metastasis, lymphatic metastasis, implantation metastasis and direct invasion. The incidence of lymph node metastasis in early-stage ovarian cancer (stage I, II) is around 15%, but lymph node metastasis occurs in 70% of patients with advanced ovarian cancer, making it a potential therapeutic target [ 4 – 6 ] . Lymph node metastasis in ovarian cancer is closely related to lymphangiogenesis, which is closely related to vascular endothelial growth factor receptor 3 (VEGFR-3) (also known as Flt-4). In most solid tumors, VEGFR-3 is highly expressed in the lymphatic epithelium, and its expression is significantly higher than that in adjacent paracancerous normal tissues [ 7 ] . Yokoyama et al. found that 90 and 72% of benign and borderline ovarian tumors failed to stain for VEGFR-3 in endothelial cells adjacent to tumor cells, respectively [ 8 ] . However, 57% of ovarian carcinomas stained positively for VEGFR-3 in endothelial cells adjacent to the carcinoma. The expression of VEGFR-3 in ovarian tumors correlates with their benignity and malignancy, suggesting that VEGFR-3 has an important role in the development of ovarian cancer. After co-culturing lymphocytes with ovarian cancer cells, the migration and metastasis of cancer cells were significantly enhanced, which might be triggered by activating the MMP-9/TIMP-2 pathway [ 9 ] . Overexpression of VEGFR-3 in ovarian cancer was found to correlate with debulking status and positive response to chemotherapy, and progression-free survival was significantly longer in women with low VEGFR-3 expression than in women with high VEGFR-3 expression [ 10 ] . In all, overexpression of VEGFR-3 reflects the aggressiveness of ovarian carcinoma spread and has a predictive value for identifying high-risk patients with poor prognosis. VEGFR-3 is known to be involved in tumorigenesis and lymphangiogenesis, and thus has the potential to be a molecular target for cancer therapy. Babaei et al. used a VEGFR-3 inhibitor to treat ovarian cancer and found that it increased cell cycle arrest and promoted apoptosis in OVCAR3 and SKOV3 cells by inhibiting the ERK-2 and AKT signaling pathways [ 11 ] . Cediranib, a broad-acting tyrosine kinase inhibitor (TKI), was also able to significantly inhibit ovarian cancer metastasis [ 12 ] . Therefore, monitoring VEGFR-3 expression in ovarian cancer is useful for assessing patient prognosis and guiding VEGFR-3-targeted therapy. A monoclonal antibody mF4-31C1-labeled radiotracer was constructed for tracer imaging of VEGFR-3 in ovarian cancer by Huhtala et al [ 13 ] . The antibody-labeled radiotracer required 48 hours after injection to be detected in ovarian cancer tissue, and the uptake rate was only 5.77 ± 0.62%ID/g. Peptide-based radiotracers have the advantage of rapid imaging and are typically ready for manipulation 30–60 minutes after injection [ 14 , 15 ] . Li et al. screened a peptide, WHWLPNLRHYAS, that binds specifically to VEGFR-3 with an affinity constant of 174.8 ± 31.1 µg/mL between them [ 16 ] . Further, our group was screening for a peptide with high affinity for VEGFR-3, TMVP1 [ 17 ] . TMVP1 has an affinity for VEGFR-3 of 6.73 µM/mL and has demonstrated the ability of this peptide radiotracer to image VEGFR-3 in patients with ovarian and cervical cancer. Nanoparticles prepared as fluorescent tracers using TMVP1 can be used for imaging and treatment of primary tumors and metastatic tumors in lymph nodes [ 18 ] . To further enhance the potential application of TMVP1, we designed it as a dimer ([ 68 Ga]Ga-NOTA-(TMVP1) 2 ) and demonstrated that the dimeric peptide had better VEGFR-3 targeting compared to the monomeric peptide [ 19 ] . In this study, we used [ 68 Ga]Ga-NOTA-(TMVP1) 2 radiotracer for the first time to assess the level of VEGFR-3 expression in patients with ovarian cancer, providing a new potential tool for evaluating ovarian cancer patients. Methods Patients Recruitments The clinical study was registered at Chinese Clinical Trial Registry (ChiCTR-DOD-17012458) and was approved by the Institutional Review Board (IRB) of Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (IRB protocol ZS-1128). All subjects signed an informed consent form. All procedures meet the ethical standards of the institutional and national research committees and comply with the 1964 Helsinki declaration and its subsequent amendments or similar ethical standards. Included patients were determined to have primary ovarian cancer or postoperative recurrence, were aged greater than or equal to 18 years, and were able to provide basic information and sign a written informed consent form. Patient exclusion criteria were pregnancy, breastfeeding, severe hepatic or renal disease (GFR < 60 ml/min/1.73m 2 or any hepatic enzyme level ≥ 2 times over the normal upper limit), severe allergy to radiographic contrast agents, claustrophobia, and psychiatric disorders. Vital signs, physical examination, electrocardiogram, routine blood tests, liver function indices, and renal function indices were collected before and after [ 68 Ga]Ga-NOTA-(TMVP1) 2 injection. Examination Procedures No specific preparations are request for patients, which differ from [ 18 F]F-FDG PET/CT scan of fasting for 4 ~ 6 hours before check. Subjects were asked to urinate before examination. At 30–45 min after injection of [ 68 Ga]Ga-NOTA-(TMVP1) 2 intravenously, we proceeded a 10-min whole-body PET acquisition was obtained from the top head to the middle femur using 5 ~ 6 bed positions after a low-dose CT scan (120 kV, 35 mA, 3 mm layer, 512 ×512 matrix, 70 cm field of view) for attenuation correction. Regions of interest (ROIs) on the lesions or major organs were manually outlined by at least two nuclear medical physicians based on the contour of CT images. The results were recorded as the maximum standardized uptake value (SUVmax) and average standardized uptake value (SUVmean). Immunohistochemistry (IHC) staining IHC staining was performed to assess VEGFR-3 expression in ovarian cancer tissues. Briefly, samples were fixed with 4% paraformaldehyde, followed by paraffin embedding and sectioning. Tissue sections were deparaffinised and rehydrated and incubated in 3% H 2 O 2 for 20 minutes to block endogenous peroxidase activity. Bovine serum albumin was incubated on the sections to reduce non-specific binding, and then the sections were incubated with anti-VEGFR-3 primary antibody (Biolegend, 356202, 1:100) at 4°C overnight. Then, the cells were incubated with horseradish peroxidase-conjugated anti-mouse lgG for 30 min at 37 ℃ and stained with diaminobenzidine, followed by counterstaining with hematoxylin. Immunostaining scores were assessed by three independent observers based on staining intensity and percentage of VEGFR3 staining. Data Analysis The PET images were postprocessed by a Siemens MultiModality workplace (MMWP). The volume of interest of normal organs/tissues and the concerned lesions were manually drawn on the serial images and the workstation automatically obtained the radioactivity concentration and standardized uptake value (SUV) in the volumes of interest. Statistical analysis and time-activity curves was generated by the GraphPad Prism Software (version 5, Inc., USA). The character of [ 68 Ga]Ga-NOTA-(TMVP1) 2 and [ 18 F]F-FDG absorption in the lesions was identified by experienced physicians. Data are expressed as means ± SD. Means were compared using one-way analysis of variance (ANOVA) or Student’s t test. P values less than 0.05 were considered statistically significant. Results Clinical characteristics of the patients Between October 2016 and April 2017, 13 ovarian cancer patients (Table 1 ) were enrolled in the study. The ages of the 13 patients ranged from 32 to 54 years, with a mean age of 46.5 years. All patients weighed between 44 and 75 kg, with a mean weight of 57.5 kg, and no patient was overweight or underweight. Except for one patient who had primary ovarian cancer, all 12 patients had recurrent ovarian cancer after surgery. Table 1 Information of the patient No. Age Gender Weight (kg) Clinical diagnosis 1 45 Female 75 Recurrent ovarian cancer 2 49 Female 52 Recurrent ovarian cancer 3 44 Female 64 Recurrent ovarian cancer 4 32 Female 47 Recurrent ovarian cancer 5 42 Female 60 Primary ovarian cancer 6 51 Female 60 Recurrent ovarian cancer 7 52 Female 55 Recurrent ovarian cancer 8 41 Female 58 Recurrent ovarian cancer 9 54 Female 44 Recurrent ovarian cancer 10 47 Female 61 Recurrent ovarian cancer 11 50 Female 50 Recurrent ovarian cancer 12 49 Female 46 Recurrent ovarian cancer 13 49 Female 75 Recurrent ovarian cancer PET/CT imaging of [Ga]Ga-NOTA-(TMVP1) All ovarian cancer patients included in the study were scanned using [ 18 F]F-FDG, and identified as having 1 or more positive lesions.13 ovarian cancer patients were included in the study with a total of 44 [ 18 F]F-FDG positive lesions. Of these 44 18 F-FDG-positive lesions, 26 were positive for [ 68 Ga]Ga-NOTA-(TMVP1) 2 . Another 18 lesions were positive for 18 F-FDG but negative for [ 68 Ga]Ga-NOTA-(TMVP1) 2 (Table 2 ). Patient #2 was a patient with recurrent ovarian cancer, as shown in Fig. 1 , and [ 18 F]F-FDG showed recurrent ovarian cancer lesions in both the pelvis and vaginal stump. The radioactivity of the right pelvic intestinal surface metastases was significantly increased at [ 18 F]F-FDG, while the radioactivity of [ 68 Ga]Ga-NOTA-(TMVP1) 2 reached 2.53 for SUV max and 1.53 for SUV mean (Fig. 1 A). For the recurrent cancer of the vaginal stump in patient #2, the [ 68 Ga]Ga-NOTA-(TMVP1) 2 had an SUV max of 1.57 and an SUV mean of 1.07, thus judging that the lesion was also positive (Fig. 1 B). Patient #4 had recurrent ovarian cancer and CT showed significant thickening of the gastric wall in the greater curvature of the stomach (Fig. 2 ). [ 18 F]F-FDG uptake was positive in this lesion with a SUV max of 2.2. Meanwhile, the uptake of [ 68 Ga]Ga-NOTA-(TMVP1) 2 by the lesion was significantly higher, with increased radioactivity in the lesion, SUV max 2.5 and SUV mean 1.85. Patient #7, [ 18 F]F-FDG PET/CT showed multiple ovarian cancer metastases in the liver (Fig. 3 ). These metastases all had higher uptake of [ 18 F]F-FDG compared to the surrounding normal liver tissue. [ 68 Ga]Ga-NOTA-(TMVP1) 2 had a range of 2.64–3.93 for SUV max and 1.13–1.66 for SUV mean in metastatic cancer of the liver. The uptake of [ 68 Ga]Ga-NOTA-(TMVP1) 2 by these metastases was low relative to normal liver tissue, but increased relative to muscle, and was therefore nonetheless assessed as positive. Table 2 Uptake of [ 68 Ga]Ga-NOTA-(TMVP1) 2 by ovarian cancer lesions [ 68 Ga]Ga-NOTA-(TMVP1) 2 No. Site of lesion SUV max SUV mean Results 1 Liver 5.91 4.60 Negative 2 Pelvis 2.53 1.53 Positive Vaginal stump 1.57 1.07 Positive Retroperitoneal lymph nodes 1.16 0.80 Negative 3 Pelvis 2.84 2.01 Positive Liver 6.06 4.69 Negative 4 Lesser curvature of the stomach 2.50 1.85 Positive Greater curvature of the stomach 2.06 1.35 Positive 5 Uterine adnexa 2.79 1.67 Positive Pelvis 1.59 1.18 Positive Retroperitoneal lymph nodes 2.04 1.15 Positive 6 Para-abdominal aortic lymph nodes 1.58 1.06 Positive 1.42 1.02 Positive Mesenteric lymph nodes 0.71 0.68 Negative Pelvis 0.98 0.52 Negative 7 Liver 3.93 1.66 Positive 2.64 1.13 Positive Lung 1.21 0.87 Negative Para-abdominal aortic lymph nodes 1.94 1.12 Positive Pelvis 1.28 0.92 Negative 0.94 0.62 Negative 0.28 0.18 Negative 8 Splenic hilum 1.14 0.85 Positive 9 Cervical lymph nodes 1.84 1.22 Positive Paraesophageal 1.86 1.23 Negative Pancreas 2.71 1.58 Positive 10 Liver 3.93 3.05 Positive 5.53 4.15 Positive 5.90 4.60 Negative Pelvis 1.12 0.86 Negative 1.03 0.92 Negative 1.95 1.05 Negative 11 Hepatic peritoneum 4.03 2.47 Negative Pelvis 2.22 1.69 Positive 2.32 1.85 Positive 2.88 2.12 Positive 12 Spleen 2.88 1.59 Negative 13 Vaginal stump 3.32 1.83 Positive Axillary lymph nodes 1.74 1.11 Negative 1.95 1.28 Negative Retroperitoneal lymph nodes 1.98 1.06 Positive 2.51 1.52 Positive Abdominal incision 2.87 1.61 Positive Inguinal lymph nodes 2.42 1.51 Positive Summary 44 lesions 59.1% (Positive) Association of [Ga]Ga-NOTA-(TMVP1) uptake and expression of VEGFR-3 Of the 13 patients with ovarian cancer, 5 underwent surgery. Independent diagnosis was made by two pathologists and confirmed the pathologic type of ovarian plasmacytoid cystadenocarcinoma in all five patients. Immunohistochemical staining was used to detect the expression level of VEGFR-3 in a total of 15 ovarian cancer tissues from these five patients (Fig. 4 ). Immunohistochemical results showed that these ovarian cancer lesions had varying degrees of VEGFR-3 expression, and 70% of the lesions were determined to be VEGFR-3 positive. Also, these VEGFR-3-positive ovarian cancer lesions were positive for [ 68 Ga]Ga-NOTA-(TMVP1) 2 uptake. Discussion TMVP1 is a target peptide that we have previously screened for VEGFR-3. To further optimise and enhance the affinity of TMVP1 for VEGFR-3, we designed a radionuclide probe based on TMVP1 dimer, [ 68 Ga]Ga-NOTA-(TMVP1) 2 [ 19 ] . It nearly doubled the affinity for VEGFR-3 over TMVP1. In 5 healthy volunteers and 8 patients with cervical cancer, [ 68 Ga]Ga-NOTA-(TMVP1) 2 demonstrated a favourable safety profile, with no side effects or allergies noted. In patients with cervical cancer, 81.8% of lesions [ 68 Ga]Ga-NOTA-(TMVP1) 2 showed medium- and high-intensity radiation signals. This molecular imaging agent is able to accurately assess the VEGFR-3 status of cervical cancer and provides a good tool for anti-VEGFR-3 therapy in cervical cancer. Ovarian cancer is the cancer with the highest mortality rate among gynaecological malignancies, and currently, its standard clinical treatment options are tumor cytoreduction and chemotherapy [ 20 , 21 ] . With the arrival of precision medicine, molecular targeted therapy has gradually entered people's vision and plays an increasingly important role in the field of anti-ovarian cancer [ 22 , 23 ] . Molecular targeted therapy is to intervene in the key targets in the process of tumor development and other important effects, such as bevacizumab for anti-angiogenic therapy and so on [ 24 – 26 ] . In general, the status of ovarian cancer target molecules needs to be evaluated before targeted therapy is administered; for example, the application of PARP inhibitors is predicated on a mutation in the BRCA gene [ 27 – 29 ] . VEGFR-3 has been reported to be closely associated with lymphangiogenesis, as well as lymphatic metastasis, in ovarian cancer [ 7 , 12 ] . The use of the VEGFR inhibitor Cediranib significantly inhibited ovarian cancer metastasis and is a potential treatment. Significant inhibition of tumour growth as well as metastasis was achieved by adenovirus-based anti-VEGFR1-3 combination therapy [ 30 ] . IHC staining allows assessment of VEGFR-3 expression status in isolated ovarian cancer tissues, whereas molecular assessment in vivo requires imaging techniques such as PET/CT. In this study, we used [ 68 Ga]Ga-NOTA-(TMVP1) 2 to evaluate VEGFR-3 in a total of 44 lesions in 9 ovarian cancer patients. The results showed that 26 out of 44 ovarian cancer lesions had positive VEGFR-3 expression, which may suggest that they are capable of receiving anti-VEGFR-3 therapy. The aim of this study is to provide a preliminary assessment of the role of [ 68 Ga]Ga-NOTA-(TMVP1) 2 in imaging and analysing VEGFR-3 in ovarian cancer, as well as its safety in vivo. This study confirms the feasibility of VEGFR-3 imaging assessment, but there are some limitations. The most important point is that the number of cases is only 13, which is not enough to illustrate the accuracy of the [ 68 Ga]Ga-NOTA-(TMVP1) 2 assessment. Conclusion In this study, we used [ 68 Ga]Ga-NOTA-(TMVP1) 2 to assess VEGFR-3 status in 13 ovarian cancer patients. Twenty-six out of a total of 44 ovarian cancer lesions showed positivity for VEGFR-3, and these lesions exhibited moderate-high radioactivity. The expression level of VEGFR-3 in five ovarian cancer patients was detected by immunohistochemical staining and the association between radioactivity and VEGFR-3 was established. In conclusion, [ 68 Ga]Ga-NOTA-(TMVP1) 2 provides a new tool for VEGFR-3 in ovarian cancer patients. Declarations Author contributions X.C. and F.L. study design, image interpretation and data analysis. X.C., Y.S. and F.L. patient management, clinical data collection, image interpretation, and critical review of the results. J.D. and L.X. study design, supervision of the analysis, and manuscript writing. All authors read and approved the final manuscript. Acknowledgements This study was funded by the National Natural Science Foundation of China (81802608, 22104040 and 82272628) and Knowledge Innovation Program of Wuhan-Shuguang Project (280) Data availability The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request. Ethics approval The study was conducted in accordance with the ethical standards of the 1964 Declaration of Helsinki and later amendments. The clinical study was registered at Chinese Clinical Trial Registry (ChiCTR-DOD-17012458) and was approved by the Institutional Review Board (IRB) of Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (IRB protocol ZS-1128). Consent to participate Written informed consent to use data for research purposes was obtained from all patients. Competing interests The authors declare no competing interests. References Webb PM, Jordan SJ. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5358746","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":372654052,"identity":"b515adee-7f10-4fb0-8dc0-f53e83eb3440","order_by":0,"name":"Xi Chen","email":"","orcid":"","institution":"Huazhong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Xi","middleName":"","lastName":"Chen","suffix":""},{"id":372654053,"identity":"c3ac313e-c05c-403c-8836-1fc1180d01c4","order_by":1,"name":"Fei Li","email":"","orcid":"","institution":"Huazhong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Fei","middleName":"","lastName":"Li","suffix":""},{"id":372654055,"identity":"ab3dd4a4-7063-43af-a26f-48f235188ce9","order_by":2,"name":"Yao Si","email":"","orcid":"","institution":"Huazhong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Yao","middleName":"","lastName":"Si","suffix":""},{"id":372654056,"identity":"890a55ee-bf8e-460e-8dbc-0e9423efed9c","order_by":3,"name":"Jun Dai","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIiWNgGAWjYBACxgYGBgkGAxsGxhkMIBYIJBClJU0CqIWxgSgtDBCzD0sASZB2IrQwz8g9eONHwfk65tkN7A8scw4z8LPnGDD83IHHYTPyki17DG5LMM45wNggue0wg2TPGwPG3jP4tOSYSfCAtMxIgGgxuJFjwMzYhl+L5B+Dcwgt9sRokeYxOIBkiwQhLT1vjK1lDJIlG2ckNs6Q3JbOI3HmWcHBXjxaDNtzDG+++WPHbzgj+cBnyW3WcvztyRsf/MSnpQHOYGxgBsYQD4hzALcGBgZ5ZAbjB3xKR8EoGAWjYMQCAC/OTiw5o9b7AAAAAElFTkSuQmCC","orcid":"","institution":"Huazhong University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Jun","middleName":"","lastName":"Dai","suffix":""},{"id":372654058,"identity":"1ca48ff9-9ecd-412f-aa30-b9e165d015bc","order_by":4,"name":"Ling Xi","email":"","orcid":"","institution":"Huazhong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Ling","middleName":"","lastName":"Xi","suffix":""}],"badges":[],"createdAt":"2024-10-30 06:23:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5358746/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5358746/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":70211734,"identity":"8b188a2a-3eb3-4563-b51a-4ebf7aab0ce7","added_by":"auto","created_at":"2024-11-29 14:41:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":165328,"visible":true,"origin":"","legend":"\u003cp\u003eUptake of [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e by patient #2. (A) Increased radioactivity uptake of [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e by right pelvic intestinal surface metastases, SUV\u003csub\u003emax\u003c/sub\u003e =2.53, SUV\u003csub\u003emean\u003c/sub\u003e =1.53. (B) Increased uptake of [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e by vaginal stump lesions, SUV\u003csub\u003emax\u003c/sub\u003e =1.57, SUV\u003csub\u003emean\u003c/sub\u003e =1.07. Red arrows indicate ovarian cancer lesions.\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5358746/v1/25905d948599506826d9b4be.png"},{"id":70211733,"identity":"23c402e5-070c-40f3-b071-284f9415411c","added_by":"auto","created_at":"2024-11-29 14:41:23","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":180174,"visible":true,"origin":"","legend":"\u003cp\u003eUptake of [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e by patient #4. CT showed thickening of the gastric wall at the greater curvature of the stomach. The uptake of \u003csup\u003e18\u003c/sup\u003eF-FDG was increased at the lesion, SUV\u003csub\u003emax\u003c/sub\u003e 2.2. The [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e radioactivity was increased at the lesion, SUV\u003csub\u003emax\u003c/sub\u003e 2.5, SUV\u003csub\u003emean\u003c/sub\u003e 1.85.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5358746/v1/82e814badcf63c1cdb72b2a7.jpeg"},{"id":70211735,"identity":"2198503f-e41c-4231-933c-3a0e34dbc173","added_by":"auto","created_at":"2024-11-29 14:41:23","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":422710,"visible":true,"origin":"","legend":"\u003cp\u003eUptake of [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e by ovarian cancer liver metastases. \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT images showed enlarged liver and increased radioactivity of ovarian cancer liver metastases. The uptake of [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e by normal liver tissue had a SUV\u003csub\u003emax\u003c/sub\u003e of 5.55 and a SUV\u003csub\u003emean\u003c/sub\u003e of 3.45. The uptake of [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e by ovarian cancer liver metastases was low, with a SUV\u003csub\u003emax\u003c/sub\u003e of 2.64-3.93 and a SUV\u003csub\u003emean\u003c/sub\u003e of 1.13-1.66.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5358746/v1/38eced0e7096005e6b642352.jpeg"},{"id":70211736,"identity":"da42ddd7-dbfc-412b-82cb-6b147c6290c0","added_by":"auto","created_at":"2024-11-29 14:41:23","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":307426,"visible":true,"origin":"","legend":"\u003cp\u003e(A) VEGFR-3 expression in the primary lesion of ovarian cancer. (B) VEGFR-3 expression in ovarian cancer liver metastases.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5358746/v1/9f391f23f783d502f7f79a72.jpeg"},{"id":73714559,"identity":"93385e2c-2695-4f5a-8012-07b260a035e3","added_by":"auto","created_at":"2025-01-13 23:16:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1869077,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5358746/v1/ba01b9ff-4dd3-4572-b164-5bf460962f40.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"First evaluation of [ 68 Ga]Ga-NOTA-(TMVP1) 2 for imaging VEGFR-3 in ovarian cancer patients","fulltext":[{"header":"Background","content":"\u003cp\u003eThe incidence rate of ovarian cancer has been on the rise year by year in recent years, and the death rate ranks first among malignant tumors of the female reproductive system. Ovarian cancer often has no obvious symptoms in the early stage, and about 75% of the patients are already in the advanced stage when they are diagnosed \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. Metastasis is the leading cause of death in patients with advanced ovarian cancer \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. There are 4 metastatic routes of ovarian cancer, including hematogenous metastasis, lymphatic metastasis, implantation metastasis and direct invasion. The incidence of lymph node metastasis in early-stage ovarian cancer (stage I, II) is around 15%, but lymph node metastasis occurs in 70% of patients with advanced ovarian cancer, making it a potential therapeutic target \u003csup\u003e[\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eLymph node metastasis in ovarian cancer is closely related to lymphangiogenesis, which is closely related to vascular endothelial growth factor receptor 3 (VEGFR-3) (also known as Flt-4). In most solid tumors, VEGFR-3 is highly expressed in the lymphatic epithelium, and its expression is significantly higher than that in adjacent paracancerous normal tissues \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Yokoyama et al. found that 90 and 72% of benign and borderline ovarian tumors failed to stain for VEGFR-3 in endothelial cells adjacent to tumor cells, respectively \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. However, 57% of ovarian carcinomas stained positively for VEGFR-3 in endothelial cells adjacent to the carcinoma. The expression of VEGFR-3 in ovarian tumors correlates with their benignity and malignancy, suggesting that VEGFR-3 has an important role in the development of ovarian cancer. After co-culturing lymphocytes with ovarian cancer cells, the migration and metastasis of cancer cells were significantly enhanced, which might be triggered by activating the MMP-9/TIMP-2 pathway \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Overexpression of VEGFR-3 in ovarian cancer was found to correlate with debulking status and positive response to chemotherapy, and progression-free survival was significantly longer in women with low VEGFR-3 expression than in women with high VEGFR-3 expression \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. In all, overexpression of VEGFR-3 reflects the aggressiveness of ovarian carcinoma spread and has a predictive value for identifying high-risk patients with poor prognosis. VEGFR-3 is known to be involved in tumorigenesis and lymphangiogenesis, and thus has the potential to be a molecular target for cancer therapy. Babaei et al. used a VEGFR-3 inhibitor to treat ovarian cancer and found that it increased cell cycle arrest and promoted apoptosis in OVCAR3 and SKOV3 cells by inhibiting the ERK-2 and AKT signaling pathways \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Cediranib, a broad-acting tyrosine kinase inhibitor (TKI), was also able to significantly inhibit ovarian cancer metastasis \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. Therefore, monitoring VEGFR-3 expression in ovarian cancer is useful for assessing patient prognosis and guiding VEGFR-3-targeted therapy.\u003c/p\u003e \u003cp\u003eA monoclonal antibody mF4-31C1-labeled radiotracer was constructed for tracer imaging of VEGFR-3 in ovarian cancer by Huhtala et al \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. The antibody-labeled radiotracer required 48 hours after injection to be detected in ovarian cancer tissue, and the uptake rate was only 5.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62%ID/g. Peptide-based radiotracers have the advantage of rapid imaging and are typically ready for manipulation 30\u0026ndash;60 minutes after injection \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Li et al. screened a peptide, WHWLPNLRHYAS, that binds specifically to VEGFR-3 with an affinity constant of 174.8\u0026thinsp;\u0026plusmn;\u0026thinsp;31.1 \u0026micro;g/mL between them \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. Further, our group was screening for a peptide with high affinity for VEGFR-3, TMVP1 \u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. TMVP1 has an affinity for VEGFR-3 of 6.73 \u0026micro;M/mL and has demonstrated the ability of this peptide radiotracer to image VEGFR-3 in patients with ovarian and cervical cancer. Nanoparticles prepared as fluorescent tracers using TMVP1 can be used for imaging and treatment of primary tumors and metastatic tumors in lymph nodes \u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. To further enhance the potential application of TMVP1, we designed it as a dimer ([\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e) and demonstrated that the dimeric peptide had better VEGFR-3 targeting compared to the monomeric peptide \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. In this study, we used [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e radiotracer for the first time to assess the level of VEGFR-3 expression in patients with ovarian cancer, providing a new potential tool for evaluating ovarian cancer patients.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients Recruitments\u003c/h2\u003e \u003cp\u003e The clinical study was registered at Chinese Clinical Trial Registry (ChiCTR-DOD-17012458) and was approved by the Institutional Review Board (IRB) of Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (IRB protocol ZS-1128). All subjects signed an informed consent form. All procedures meet the ethical standards of the institutional and national research committees and comply with the 1964 Helsinki declaration and its subsequent amendments or similar ethical standards.\u003c/p\u003e \u003cp\u003e Included patients were determined to have primary ovarian cancer or postoperative recurrence, were aged greater than or equal to 18 years, and were able to provide basic information and sign a written informed consent form. Patient exclusion criteria were pregnancy, breastfeeding, severe hepatic or renal disease (GFR\u0026thinsp;\u0026lt;\u0026thinsp;60 ml/min/1.73m\u003csup\u003e2\u003c/sup\u003e or any hepatic enzyme level\u0026thinsp;\u0026ge;\u0026thinsp;2 times over the normal upper limit), severe allergy to radiographic contrast agents, claustrophobia, and psychiatric disorders. Vital signs, physical examination, electrocardiogram, routine blood tests, liver function indices, and renal function indices were collected before and after [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e injection.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eExamination Procedures\u003c/h3\u003e\n\u003cp\u003eNo specific preparations are request for patients, which differ from [\u003csup\u003e18\u003c/sup\u003eF]F-FDG PET/CT scan of fasting for 4\u0026thinsp;~\u0026thinsp;6 hours before check. Subjects were asked to urinate before examination. At 30\u0026ndash;45 min after injection of [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e intravenously, we proceeded a 10-min whole-body PET acquisition was obtained from the top head to the middle femur using 5\u0026thinsp;~\u0026thinsp;6 bed positions after a low-dose CT scan (120 kV, 35 mA, 3 mm layer, 512 \u0026times;512 matrix, 70 cm field of view) for attenuation correction. Regions of interest (ROIs) on the lesions or major organs were manually outlined by at least two nuclear medical physicians based on the contour of CT images. The results were recorded as the maximum standardized uptake value (SUVmax) and average standardized uptake value (SUVmean).\u003c/p\u003e\n\u003ch3\u003eImmunohistochemistry (IHC) staining\u003c/h3\u003e\n\u003cp\u003eIHC staining was performed to assess VEGFR-3 expression in ovarian cancer tissues. Briefly, samples were fixed with 4% paraformaldehyde, followed by paraffin embedding and sectioning. Tissue sections were deparaffinised and rehydrated and incubated in 3% H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e for 20 minutes to block endogenous peroxidase activity. Bovine serum albumin was incubated on the sections to reduce non-specific binding, and then the sections were incubated with anti-VEGFR-3 primary antibody (Biolegend, 356202, 1:100) at 4\u0026deg;C overnight. Then, the cells were incubated with horseradish peroxidase-conjugated anti-mouse lgG for 30 min at 37 ℃ and stained with diaminobenzidine, followed by counterstaining with hematoxylin. Immunostaining scores were assessed by three independent observers based on staining intensity and percentage of VEGFR3 staining.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eThe PET images were postprocessed by a Siemens MultiModality workplace (MMWP). The volume of interest of normal organs/tissues and the concerned lesions were manually drawn on the serial images and the workstation automatically obtained the radioactivity concentration and standardized uptake value (SUV) in the volumes of interest. Statistical analysis and time-activity curves was generated by the GraphPad Prism Software (version 5, Inc., USA). The character of [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e and [\u003csup\u003e18\u003c/sup\u003eF]F-FDG absorption in the lesions was identified by experienced physicians. Data are expressed as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Means were compared using one-way analysis of variance (ANOVA) or Student\u0026rsquo;s t test. P values less than 0.05 were considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eClinical characteristics of the patients\u003c/h2\u003e \u003cp\u003eBetween October 2016 and April 2017, 13 ovarian cancer patients (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) were enrolled in the study. The ages of the 13 patients ranged from 32 to 54 years, with a mean age of 46.5 years. All patients weighed between 44 and 75 kg, with a mean weight of 57.5 kg, and no patient was overweight or underweight. Except for one patient who had primary ovarian cancer, all 12 patients had recurrent ovarian cancer after surgery.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInformation of the patient\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWeight (kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eClinical diagnosis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRecurrent ovarian cancer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRecurrent ovarian cancer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRecurrent ovarian cancer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRecurrent ovarian cancer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePrimary ovarian cancer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRecurrent ovarian cancer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRecurrent ovarian cancer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRecurrent ovarian cancer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRecurrent ovarian cancer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRecurrent ovarian cancer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRecurrent ovarian cancer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRecurrent ovarian cancer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRecurrent ovarian cancer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePET/CT imaging of [Ga]Ga-NOTA-(TMVP1)\u003c/h3\u003e\n\u003cp\u003eAll ovarian cancer patients included in the study were scanned using [\u003csup\u003e18\u003c/sup\u003eF]F-FDG, and identified as having 1 or more positive lesions.13 ovarian cancer patients were included in the study with a total of 44 [\u003csup\u003e18\u003c/sup\u003eF]F-FDG positive lesions. Of these 44 \u003csup\u003e18\u003c/sup\u003eF-FDG-positive lesions, 26 were positive for [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e. Another 18 lesions were positive for \u003csup\u003e18\u003c/sup\u003eF-FDG but negative for [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Patient #2 was a patient with recurrent ovarian cancer, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, and [\u003csup\u003e18\u003c/sup\u003eF]F-FDG showed recurrent ovarian cancer lesions in both the pelvis and vaginal stump. The radioactivity of the right pelvic intestinal surface metastases was significantly increased at [\u003csup\u003e18\u003c/sup\u003eF]F-FDG, while the radioactivity of [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e reached 2.53 for SUV\u003csub\u003emax\u003c/sub\u003e and 1.53 for SUV\u003csub\u003emean\u003c/sub\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). For the recurrent cancer of the vaginal stump in patient #2, the [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e had an SUV\u003csub\u003emax\u003c/sub\u003e of 1.57 and an SUV\u003csub\u003emean\u003c/sub\u003e of 1.07, thus judging that the lesion was also positive (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Patient #4 had recurrent ovarian cancer and CT showed significant thickening of the gastric wall in the greater curvature of the stomach (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). [\u003csup\u003e18\u003c/sup\u003eF]F-FDG uptake was positive in this lesion with a SUV\u003csub\u003emax\u003c/sub\u003e of 2.2. Meanwhile, the uptake of [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e by the lesion was significantly higher, with increased radioactivity in the lesion, SUV\u003csub\u003emax\u003c/sub\u003e 2.5 and SUV\u003csub\u003emean\u003c/sub\u003e 1.85. Patient #7, [\u003csup\u003e18\u003c/sup\u003eF]F-FDG PET/CT showed multiple ovarian cancer metastases in the liver (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These metastases all had higher uptake of [\u003csup\u003e18\u003c/sup\u003eF]F-FDG compared to the surrounding normal liver tissue. [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e had a range of 2.64\u0026ndash;3.93 for SUV\u003csub\u003emax\u003c/sub\u003e and 1.13\u0026ndash;1.66 for SUV\u003csub\u003emean\u003c/sub\u003e in metastatic cancer of the liver. The uptake of [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e by these metastases was low relative to normal liver tissue, but increased relative to muscle, and was therefore nonetheless assessed as positive.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUptake of [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e by ovarian cancer lesions\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e[\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSite of lesion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSUV\u003csub\u003emax\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSUV\u003csub\u003emean\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eResults\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePelvis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVaginal stump\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetroperitoneal lymph nodes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePelvis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLesser curvature of the stomach\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGreater curvature of the stomach\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUterine adnexa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePelvis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetroperitoneal lymph nodes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePara-abdominal aortic lymph nodes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMesenteric lymph nodes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePelvis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLung\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePara-abdominal aortic lymph nodes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePelvis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSplenic hilum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCervical lymph nodes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParaesophageal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePancreas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eLiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePelvis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHepatic peritoneum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePelvis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpleen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVaginal stump\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAxillary lymph nodes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRetroperitoneal lymph nodes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbdominal incision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInguinal lymph nodes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSummary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 lesions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59.1% (Positive)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eAssociation of [Ga]Ga-NOTA-(TMVP1) uptake and expression of VEGFR-3\u003c/h3\u003e\n\u003cp\u003eOf the 13 patients with ovarian cancer, 5 underwent surgery. Independent diagnosis was made by two pathologists and confirmed the pathologic type of ovarian plasmacytoid cystadenocarcinoma in all five patients. Immunohistochemical staining was used to detect the expression level of VEGFR-3 in a total of 15 ovarian cancer tissues from these five patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Immunohistochemical results showed that these ovarian cancer lesions had varying degrees of VEGFR-3 expression, and 70% of the lesions were determined to be VEGFR-3 positive. Also, these VEGFR-3-positive ovarian cancer lesions were positive for [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e uptake.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTMVP1 is a target peptide that we have previously screened for VEGFR-3. To further optimise and enhance the affinity of TMVP1 for VEGFR-3, we designed a radionuclide probe based on TMVP1 dimer, [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. It nearly doubled the affinity for VEGFR-3 over TMVP1. In 5 healthy volunteers and 8 patients with cervical cancer, [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e demonstrated a favourable safety profile, with no side effects or allergies noted. In patients with cervical cancer, 81.8% of lesions [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e showed medium- and high-intensity radiation signals. This molecular imaging agent is able to accurately assess the VEGFR-3 status of cervical cancer and provides a good tool for anti-VEGFR-3 therapy in cervical cancer.\u003c/p\u003e \u003cp\u003eOvarian cancer is the cancer with the highest mortality rate among gynaecological malignancies, and currently, its standard clinical treatment options are tumor cytoreduction and chemotherapy \u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. With the arrival of precision medicine, molecular targeted therapy has gradually entered people's vision and plays an increasingly important role in the field of anti-ovarian cancer \u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. Molecular targeted therapy is to intervene in the key targets in the process of tumor development and other important effects, such as bevacizumab for anti-angiogenic therapy and so on \u003csup\u003e[\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e–\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. In general, the status of ovarian cancer target molecules needs to be evaluated before targeted therapy is administered; for example, the application of PARP inhibitors is predicated on a mutation in the BRCA gene \u003csup\u003e[\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e–\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eVEGFR-3 has been reported to be closely associated with lymphangiogenesis, as well as lymphatic metastasis, in ovarian cancer \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. The use of the VEGFR inhibitor Cediranib significantly inhibited ovarian cancer metastasis and is a potential treatment. Significant inhibition of tumour growth as well as metastasis was achieved by adenovirus-based anti-VEGFR1-3 combination therapy \u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e. IHC staining allows assessment of VEGFR-3 expression status in isolated ovarian cancer tissues, whereas molecular assessment in vivo requires imaging techniques such as PET/CT. In this study, we used [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e to evaluate VEGFR-3 in a total of 44 lesions in 9 ovarian cancer patients. The results showed that 26 out of 44 ovarian cancer lesions had positive VEGFR-3 expression, which may suggest that they are capable of receiving anti-VEGFR-3 therapy.\u003c/p\u003e \u003cp\u003eThe aim of this study is to provide a preliminary assessment of the role of [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e in imaging and analysing VEGFR-3 in ovarian cancer, as well as its safety in vivo. This study confirms the feasibility of VEGFR-3 imaging assessment, but there are some limitations. The most important point is that the number of cases is only 13, which is not enough to illustrate the accuracy of the [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e assessment.\u003c/p\u003e "},{"header":"Conclusion","content":"\u003cp\u003eIn this study, we used [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e to assess VEGFR-3 status in 13 ovarian cancer patients. Twenty-six out of a total of 44 ovarian cancer lesions showed positivity for VEGFR-3, and these lesions exhibited moderate-high radioactivity. The expression level of VEGFR-3 in five ovarian cancer patients was detected by immunohistochemical staining and the association between radioactivity and VEGFR-3 was established. In conclusion, [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e provides a new tool for VEGFR-3 in ovarian cancer patients.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eX.C. and F.L. study design, image interpretation and data analysis. X.C., Y.S. and F.L. patient management, clinical data collection, image interpretation, and critical review of the results. J.D. and L.X. study design, supervision of the analysis, and manuscript writing. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the National Natural Science Foundation of China (81802608, 22104040 and 82272628) and Knowledge Innovation Program of Wuhan-Shuguang Project (280)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the ethical standards of the 1964 Declaration of Helsinki and later amendments. The clinical study was registered at Chinese Clinical Trial Registry (ChiCTR-DOD-17012458) and was approved by the Institutional Review Board (IRB) of Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (IRB protocol ZS-1128).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWritten informed consent to use data for research purposes was obtained from all patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWebb PM, Jordan SJ. Global epidemiology of epithelial ovarian cancer. Nat Rev Clin Oncol. 2024;21:1\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLheureux S, Braunstein M, Oza AM. Epithelial ovarian cancer: Evolution of management in the era of precision medicine. CA Cancer J Clin. 2019;69:280\u0026ndash;304.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYousefi M, Dehghani S, Nosrati R, et al. Current insights into the metastasis of epithelial ovarian cancer - hopes and hurdles. Cell Oncol. 2020;43:515\u0026ndash;38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBalbi G, Manganaro MA, Monteverde A, et al. Ovarian cancer: lymph node metastases. Eur J Gynaecol Oncol. 2009;30:289\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKleppe M, Wang T, Gorp TV, et al. Lymph node metastasis in stages I and II ovarian cancer: a review. Gynecol Oncol. 2011;123:610\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNomura H, Tsuda H, Susumu N, et al. Lymph node metastasis in grossly apparent stages I and II epithelial ovarian cancer. Int J Gynecol Cancer. 2010;20:341\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmith NR, Baker D, James NH, et al. Vascular endothelial growth factor receptors VEGFR-2 and VEGFR-3 are localized primarily to the vasculature in human primary solid cancers. Clin Cancer Res. 2010;16:3548\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYokoyama Y, Charnock-Jones DS, Licence D, et al. Vascular endothelial growth factor-D is an independent prognostic factor in epithelial ovarian carcinoma. Brit J Cancer. 2003;88:237\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang S, Zhu X, Cai L, et al. Role of tumor-associated lymphatic endothelial cells in metastasis: a study of epithelial ovarian tumor in vitro. Cancer Sci. 2010;101:679\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlasa-Mazurkiewicz D, Jarząb M, Milczek T, et al. Clinical significance of VEGFR-2 and VEGFR-3 expression in ovarian cancer patients. Pol J Pathol. 2011;62:31\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBabaei Z, Panjehpour M, Parsian H, et al. SAR131675 exhibits anticancer activity on human ovarian cancer cells through inhibition of VEGFR-3/ERK1/2/AKT signaling pathway. Cell Signal. 2023;111:110856.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDecio A, Taraboletti G, Patton V, et al. Vascular endothelial growth factor c promotes ovarian carcinoma progression through paracrine and autocrine mechanisms. Am J Pathol. 2014;184:1050\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuhtala T, Laakkonen P, Sallinen H, et al. In vivo SPECT/CT imaging of human orthotopic ovarian carcinoma xenografts with 111In-labeled monoclonal antibodies. Nucl Med Biol. 2010;37:957\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKręcisz P, Czarnecka K, Kr\u0026oacute;licki L, et al. Radiolabeled peptides and antibodies in medicine. Bioconjug Chem. 2021;32:25\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOpalinska M, Hubalewska-Dydejczyk A, Sowa-Staszczak A. Radiolabeled peptides: Current and new perspectives. Q J Nucl Med Mol Imaging. 2017;61:153\u0026ndash;67.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShi LF, Wu Y, Li CY. Identification of high-affinity VEGFR3-binding peptides through a phage-displayed random peptide library. J Gynecol Oncol. 2015;26:327\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi F, Zhang Z, Cai J, et al. Primary preclinical and clinical evaluation of \u003csup\u003e68\u003c/sup\u003eGa-DOTA-TMVP1 as a novel VEGFR-3 PET imaging radiotracer in gynecological cancer. Clin Cancer Res. 2020;26:1318\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang X, Dai G, Jiang G, et al. A TMVP1-modified near-infrared nanoprobe: molecular imaging for tumor metastasis in sentinel lymph node and targeted enhanced photothermal therapy. J Nanobiotechnol. 2023;21:130.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen X, Zhang Z, Wang L, et al. Homodimeric peptide radiotracer [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e for VEGFR-3 imaging of cervical cancer patients. Eur J Nucl Med Mol Imaging. 2024;51:2338\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKonstantinopoulos PA, Matulonis UA. Clinical and translational advances in ovarian cancer therapy. Nat Cancer. 2023;4:1239\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang L, Wang X, Zhu X, et al. Drug resistance in ovarian cancer: from mechanism to clinical trial. Mol Cancer. 2024;23:66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorand S, Devanaboyina M, Staats H, et al. Ovarian cancer immunotherapy and personalized medicine. Int J Mol Sci. 2021;22:6532.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDiab Y, Muallem MZ. Therapy in ovarian cancer. A comprehensive systematic review of literature. Anticancer Res. 2017;37:2809\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNakai H, Matsumura N. The roles and limitations of bevacizumab in the treatment of ovarian cancer. Int J Clin Oncol. 2022;27:1120\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKuroki L, Guntupalli SR. Treatment of epithelial ovarian cancer. BMJ. 2022;371:m3773.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRichardson DL, Eskander RN, O'Malley DM. Advances in ovarian cancer care and unmet treatment needs for patients with platinum resistance: A narrative review. JAMA Oncol. 2023;9:851\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMirza MR, Coleman RL, Gonz\u0026aacute;lez-Mart\u0026iacute;n A, et al. The forefront of ovarian cancer therapy: update on PARP inhibitors. Ann Oncol. 2020;31:1148\u0026ndash;59.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoschetta M, George A, Kaye SB, et al. BRCA somatic mutations and epigenetic BRCA modifications in serous ovarian cancer. Ann Oncol. 2016;27:1449\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu Y, Xu S, Cheng S, et al. Clinical application of PARP inhibitors in ovarian cancer: from molecular mechanisms to the current status. J Ovarian Res. 2023;16:6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSallinen H, Anttila M, Narvainen J, et al. Antiangiogenic gene therapy with soluble VEGFR-1, -2, and \u0026ndash;\u0026thinsp;3 reduces the growth of solid human ovarian carcinoma in mice. Mol Ther. 2009;17:278\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5358746/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5358746/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo evaluate the safety and VEGFR-3 imaging effects of [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e in ovarian cancer patients.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e13 patients with ovarian cancer were recruited and underwent radionuclide imaging with [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e. The safety of [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e was assessed in vivo (including vital signs, biochemical indices, ECG, allergic reactions, etc.) and its imaging effect on VEGFR-3 was explored.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 1 patient with primary ovarian cancer and 12 patients with recurrent ovarian cancer, with an age range of 41\u0026ndash;54 years, were included in the study. 13 ovarian cancer patients had a total of 49 \u003csup\u003e18\u003c/sup\u003eF-FDG-positive lesions, 63.3% of which were positive for [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e. The higher expression of VEGFR-3 in [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e -positive ovarian cancer lesions was found by immunohistochemical staining, which was positively correlated. Meanwhile, [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e is a safe radiotracer as no significant side effects have been found in the human.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eIn conclusion, [\u003csup\u003e68\u003c/sup\u003eGa]Ga-NOTA-(TMVP1)\u003csub\u003e2\u003c/sub\u003e enables precise molecular imaging of VEGFR-3 in ovarian cancer patients with a favourable safety profile, providing a new tool for the in vivo assessment of VEGFR-3 in ovarian cancer.\u003c/p\u003e","manuscriptTitle":"First evaluation of [ 68 Ga]Ga-NOTA-(TMVP1) 2 for imaging VEGFR-3 in ovarian cancer patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-29 14:41:19","doi":"10.21203/rs.3.rs-5358746/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"50173c7e-8f27-45f6-b633-e9dc5d1cec66","owner":[],"postedDate":"November 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-13T23:08:19+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-29 14:41:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5358746","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5358746","identity":"rs-5358746","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}