scholarly journals Establishment of two ovarian cancer orthotopic xenograft mouse models for in vivo imaging: A comparative study

2017 ◽  
Vol 51 (4) ◽  
pp. 1199-1208 ◽  
Author(s):  
Jing Guo ◽  
Jing Cai ◽  
Yunxia Zhang ◽  
Yapei Zhu ◽  
Ping Yang ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Comparative Study ◽  
Mouse Models ◽  
In Vivo Imaging ◽  
Orthotopic Xenograft

scholarly journals Molecular imaging and deep learning analysis of uMUC1 expression in response to chemotherapy in an orthotopic model of ovarian cancer

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Hongwei Zhao ◽  
Hasaan Hayat ◽  
Xiaohong Ma ◽  
Daguang Fan ◽  
Ping Wang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Ovarian Cancer ◽  
Deep Learning ◽  
Cancer Progression ◽  
In Vivo Imaging ◽  
Near Infrared ◽  
Response To Therapy ◽  
Response To Chemotherapy

Abstract Artificial Intelligence (AI) algorithms including deep learning have recently demonstrated remarkable progress in image-recognition tasks. Here, we utilized AI for monitoring the expression of underglycosylated mucin 1 (uMUC1) tumor antigen, a biomarker for ovarian cancer progression and response to therapy, using contrast-enhanced in vivo imaging. This was done using a dual-modal (magnetic resonance and near infrared optical imaging) uMUC1-specific probe (termed MN-EPPT) consisted of iron-oxide magnetic nanoparticles (MN) conjugated to a uMUC1-specific peptide (EPPT) and labeled with a near-infrared fluorescent dye, Cy5.5. In vitro studies performed in uMUC1-expressing human ovarian cancer cell line SKOV3/Luc and control uMUC1low ES-2 cells showed preferential uptake on the probe by the high expressor (n = 3, p < .05). A decrease in MN-EPPT uptake by SKOV3/Luc cells in vitro due to uMUC1 downregulation after docetaxel therapy was paralleled by in vivo imaging studies that showed a reduction in probe accumulation in the docetaxel treated group (n = 5, p < .05). The imaging data were analyzed using deep learning-enabled segmentation and quantification of the tumor region of interest (ROI) from raw input MRI sequences by applying AI algorithms including a blend of Convolutional Neural Networks (CNN) and Fully Connected Neural Networks. We believe that the algorithms used in this study have the potential to improve studying and monitoring cancer progression, amongst other diseases.

In Vivo Imaging Mouse Models of Breast Cancer

2008 ◽  
pp. 357-375
Author(s):  
Kathleen Gabrielson ◽  
Teresa Southard ◽  
Yi Xu ◽  
Frank C. Marini ◽  
Brett M. Hall ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Mouse Models ◽  
In Vivo Imaging

scholarly journals Preclinical orthotopic xenograft model of renal pelvis cancer in which cancer growth could be traced by an in vivo imaging system

2018 ◽  
Vol 26 (1) ◽  
pp. 138-139 ◽  
Author(s):  
Teruki Shimizu ◽  
Masatsugu Miyashita ◽  
Atsuko Fujihara ◽  
Fumiya Hongo ◽  
Osamu Ukimura ◽  
...  
Keyword(s):  
Renal Pelvis ◽  
In Vivo Imaging ◽  
Imaging System ◽  
Xenograft Model ◽  
Cancer Growth ◽  
Orthotopic Xenograft ◽  
Orthotopic Xenograft Model ◽  
In Vivo Imaging System

Preparation of Carbon Dots for Effective Fluorescence Imaging of Ovarian Cancer Cells and In Vivo Brain Imaging

NANO ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. 2050158
Author(s):  
Yinping Zhuang ◽  
Shaohui Zheng ◽  
Qi Liu ◽  
Kai Xu ◽  
Cuiping Han ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Brain Imaging ◽  
Cancer Cells ◽  
In Vivo Imaging ◽  
Carbon Dots ◽  
Photoluminescence Property ◽  
Ovarian Cancer Cells ◽  
Animal Imaging ◽  
One Step

Fluorescent carbon dots (CDs) were prepared for targeted cancer imaging and in vivo imaging. The CDs were prepared via one-step hydrothermal pyrolysis of urea and sodium citrate dihydrate. The CDs revealed nice crystalline structure, excellent aqueous stability and good photoluminescence property and high quantum yield. The fluorescent images indicated that the anti-HE4-CDs were specifically internalized by the HO-8910 ovarian cancer cells. Furthermore, the CDs revealed vivid fluorescent signal in the animal imaging test and promising potential in brain imaging. Finally, the CDs also suggested low toxicity after treatment for 1 day, 7 days and 21 days. Therefore, the prepared CDs could be a promising imaging probe for targeted cancer cell imaging and in vivo imaging.

scholarly journals Investigation of Oncogenic Cooperation in Simple Liver-Specific Transgenic Mouse Models Using Noninvasive In Vivo Imaging

PLoS ONE ◽  
2013 ◽  
Vol 8 (3) ◽  
pp. e59869 ◽  
Author(s):  
Hye-Lim Ju ◽  
Sang Hoon Ahn ◽  
Do Young Kim ◽  
Sinhwa Baek ◽  
Sook In Chung ◽  
...  
Keyword(s):  
Transgenic Mouse ◽  
Mouse Models ◽  
In Vivo Imaging ◽  
Transgenic Mouse Models

Effect of therapeutic GAS6/AXL inhibition of tumor and stromal cells on DNA damage and response to chemotherapy in ovarian cancer.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e14676-e14676 ◽  
Author(s):  
Mary M Mullen ◽  
Elena Lomonosova ◽  
Hollie M Noia ◽  
Lei Guo ◽  
Lindsay Midori Kuroki ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Dna Damage ◽  
Neoadjuvant Chemotherapy ◽  
Cell Viability ◽  
Mouse Models ◽  
Stromal Cells ◽  
Predictive Biomarker ◽  
Response To Chemotherapy

e14676 Background: Ovarian cancer is the leading cause of death due to gynecologic malignancy. Biomarkers to predict chemoresponse and novel therapies to target these proteins would be practice changing. We aim to establish serum and tissue GAS6 as a predictive biomarker of chemoresponse and to determine if AXL inhibition through sequestration of its ligand, GAS6, with AVB-S6-500 (AVB) can improve chemoresponse. Methods: AVB was supplied by Aravive Biologics. High grade serous ovarian cancer (HGSOC) tumor samples were obtained pre- and post-neoadjuvant chemotherapy. AXL and GAS6 expression were evaluated by immunohistochemistry and serum concentration. In vitro viability and clonogenic assays were performed on chemoresistant tumor (OVCAR8, OVCAR5, COV62, and POV71-hTERT) and stromal cells (CAF86) treated with chemotherapy +/- AVB. Mouse models (OVCAR8, PDX, OVCAR5) were used to determine if the combination of chemotherapy + AVB reduced tumor burden. Immunofluorescent assays targeting ɣH2AX were used to evaluate DNA damage. Results: Patients with high pretreatment tumor GAS6 expression ( > 85%, n = 7) or serum GAS6 concentrations ( > 25ng/mL, n = 13) were more likely to be resistant to neoadjuvant chemotherapy than those with low tumor GAS6 expression ( < 45%, n = 4) (P = 0.010) or low serum GAS6 concentrations ( < 15ng/mL, n = 5) (P = 0.002). Carboplatin plus AVB (2µM, 5µM) and paclitaxel plus AVB (1µM) resulted in decreased cell viability and clonogenic growth compared to chemotherapy alone (p < 0.05) in all tumor and stromal cell lines. Synergism was seen between carboplatin+AVB and paclitaxel+AVB with a weighted combination index < 1. In vivo tumor mouse models treated with chemotherapy+AVB had significantly smaller subcutaneous and intraperitoneal (IP) tumors than those treated with chemotherapy alone (3.1mg vs 64mg, P = 0.003 OVCAR8; 62mg vs 157mg, P = 0.0108 PDX subcutaneous model; 0.05mg vs 0.3669mg, P < 0.001 OVCAR5 IP model). Increased DNA damage was noted in tumor and stromal cells treated with carboplatin+AVB compared to carboplatin alone (OVCAR8, COV362, CAF86 P < 0.001). Conclusions: High GAS6 is associated with lack of neoadjuvant chemoresponse in HGSOC patients. The combination of chemotherapy with AVB decreases tumor cell viability, tumor growth, and an increase in DNA damage response.

scholarly journals 304. Therapeutic Efficacy of a Mesothelin Promoter-Based Conditionally Replicative Adenovirus Monitored by In Vivo Imaging of an Ovarian Cancer Model

2006 ◽  
Vol 13 ◽  
pp. S116
Author(s):  
Yuko Tsuruta ◽  
Larisa Pereboeva ◽  
Martina Breidenbach ◽  
Daniel T. Rein ◽  
Masaharu Nakayama ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
In Vivo Imaging ◽  
Therapeutic Efficacy ◽  
Cancer Model ◽  
Conditionally Replicative Adenovirus

scholarly journals Monitoring protein aggregation and toxicity in Alzheimer’s disease mouse models using in vivo imaging

Methods ◽  
2011 ◽  
Vol 53 (3) ◽  
pp. 201-207 ◽  
Author(s):  
Tara L. Spires-Jones ◽  
Alix de Calignon ◽  
Melanie Meyer-Luehmann ◽  
Brian J. Bacskai ◽  
Bradley T. Hyman
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Protein Aggregation ◽  
Mouse Models ◽  
In Vivo Imaging

Non-invasive monitoring of patient-derived orthotopic xenograft: An optimal system for rapid in vivotesting.

2016 ◽  
Vol 34 (4_suppl) ◽  
pp. 235-235
Author(s):  
Mayrim V. Rios Perez ◽  
Michael Pratt ◽  
Ya'an Kang ◽  
Jason B. Fleming
Keyword(s):  
Tumor Growth ◽  
Mouse Models ◽  
Response To Therapy ◽  
Ductal Adenocarcinoma ◽  
In Vivo Models ◽  
Treatment Groups ◽  
Non Invasive ◽  
Orthotopic Xenograft ◽  
Metastatic Burden

235 Background: Heterotopic patient-derived xenografts (PDX) have been used to assess response to therapy however they underrepresent the role of tumor microenvironment and rarely develop metastasis, both of which are overcome by orthotopic models. Fluorescent orthotopic mouse models require invasive measures to determine tumor bioluminescence. Ultrasonography (US) is a cost-effective, non-invasive imaging technique that has been used in genetically engineered mouse models of pancreatic cancer for a three-dimensional (3D) acquisition of tumor volume, which allows rapid and safe in vivo drug testing. We intend to demonstrate that this technique allows real time monitoring of in vivo response to therapy using patient-derived orthotopic xenograft (PDOX) of pancreatic ductal adenocarcinoma (PDAC). Methods: A non-survival study using PDOX was designed with control (n = 5) and treatment (n = 5) groups. Weekly 3D US images were obtained pre and post-treatment over 4 weeks. Tumor growth curves were generated to monitor progression of disease. Metastatic burden was determined during necropsy. Results: One mouse was excluded from control and treatment groups due to baseline tumor size exceeding 300mm3 and drug toxicity, respectively. Pre-treatment average tumor volumes for control and treatment groups were (36±12)mm3 and (34±12)mm3, respectively. No difference was found in average tumor growth over time between groups (p = 0.9120). A 20% tumor regression was observed per group. Both groups exhibited gross metastasis to spleen, peritoneum, and omentum. Liver, periportal metastasis and local extension to the gastrointestinal and genitourinary system were present on the treatment group. Conclusions: This study describes a rapid technique for in vivo drug response by using 3D US to monitor PDOX; failure of response to therapy correlated with metastatic burden observed. PDOX regression could be explained by tumor heterogeneity. PDOX models, as challenging as they could be, remain to be necessary in vivo models to show therapeutic response to human PDAC, which could be easily monitored using 3D US imaging.

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