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 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.

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

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 Defining a murine ovarian cancer model for the evaluation of conditionally-replicative adenovirus (CRAd) virotherapy agents

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Rebeca González-Pastor ◽  
Ahmad Mohammad Ashshi ◽  
Adel Galal El-Shemi ◽  
Igor P. Dmitriev ◽  
Elena A. Kashentseva ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Cancer Model ◽  
Conditionally Replicative Adenovirus

scholarly journals An Advanced Orthotopic Ovarian Cancer Model in Mice for Therapeutic Trials

2016 ◽  
Vol 2016 ◽  
pp. 1-4 ◽  
Author(s):  
Ying Zhang ◽  
Li Luo ◽  
Xueling Zheng ◽  
Tinghe Yu
Keyword(s):  
Ovarian Cancer ◽  
Survival Time ◽  
Biological Behavior ◽  
In Vivo Model ◽  
Ovarian Cancer Cells ◽  
Recipient Mouse ◽  
Cancer Model ◽  
Therapeutic Trials ◽  
Tumor Fragment

A nude mouse received subcutaneous injection of human ovarian cancer cells HO-8910PM to form a tumor, and then the tumor fragment was surgically transplanted to the ovary of a recipient mouse to establish an orthotopic cancer model. Tumors occurred in 100% of animals. A mouse displayed an ovarian mass, ascites, intraperitoneal spread, and lung metastasis at natural death. The mean survival time was34.1±17.2days, with median survival time of 28.5 days. The findings indicated that the present mouse model can reflect the biological behavior of advanced human ovarian cancers. This in vivo model can be used to explore therapeutic means against chemoresistance and metastasis, and an effective treatment would prolong the survival time.

scholarly journals Targeting CD133 in an in vivo ovarian cancer model reduces ovarian cancer progression

2013 ◽  
Vol 130 (3) ◽  
pp. 579-587 ◽  
Author(s):  
Amy P.N. Skubitz ◽  
Elizabeth P. Taras ◽  
Kristin L.M. Boylan ◽  
Nate N. Waldron ◽  
Seunguk Oh ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Cancer Progression ◽  
Cancer Model
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