scholarly journals High-affinity Near-infrared Fluorescent Small-molecule Contrast Agents for In Vivo Imaging of Prostate-specific Membrane Antigen

2005 ◽  
Vol 4 (4) ◽  
pp. 7290.2005.05163 ◽  
Author(s):  
Valerie Humblet ◽  
Rena Lapidus ◽  
Larry R. Williams ◽  
Takashi Tsukamoto ◽  
Camilo Rojas ◽  
...  

Surgical resection remains a definitive treatment for prostate cancer. Yet, prostate cancer surgery is performed without image guidance for tumor margin, extension beyond the capsule and lymph node positivity, and without verification of other occult metastases in the surgical field. Recently, several imaging systems have been described that exploit near-infrared (NIR) fluorescent light for sensitive, real-time detection of disease pathology intraoperatively. In this study, we describe a high-affinity (9 nM), single nucleophile-containing, small molecule specific for the active site of the enzyme PSMA. We demonstrate production of a tetra-sulfonated heptamethine indocyanine NIR fluorescent derivative of this molecule using a high-yield LC/MS purification strategy. Interestingly, NIR fluorophore conjugation improves affinity over 20-fold, and we provide mechanistic insight into this observation. We describe the preparative production of enzymatically active PSMA using a baculovirus expression system and an adenovirus that co-expresses PSMA and GFP. We demonstrate sensitive and specific in vitro imaging of endogenous and ectopically expressed PSMA in human cells and in vivo imaging of xenograft tumors. We also discuss chemical strategies for improving performance even further. Taken together, this study describes nearly complete preclinical development of an optically based small-molecule contrast agent for image-guided surgery.

2019 ◽  
Vol 55 (42) ◽  
pp. 5851-5854 ◽  
Author(s):  
Lianhua Liu ◽  
Yaping Yuan ◽  
Yuqi Yang ◽  
Michael T. McMahon ◽  
Shizhen Chen ◽  
...  

A fluorinated aza-BODIPY derivative BDPF was developed as a small molecule contrast agent, which displayed highly efficient near infrared fluorescence/photoacoustic/19F MR tri-modality tumor imaging.


2020 ◽  
Vol 48 (6) ◽  
pp. 2657-2667
Author(s):  
Felipe Montecinos-Franjola ◽  
John Y. Lin ◽  
Erik A. Rodriguez

Noninvasive fluorescent imaging requires far-red and near-infrared fluorescent proteins for deeper imaging. Near-infrared light penetrates biological tissue with blood vessels due to low absorbance, scattering, and reflection of light and has a greater signal-to-noise due to less autofluorescence. Far-red and near-infrared fluorescent proteins absorb light >600 nm to expand the color palette for imaging multiple biosensors and noninvasive in vivo imaging. The ideal fluorescent proteins are bright, photobleach minimally, express well in the desired cells, do not oligomerize, and generate or incorporate exogenous fluorophores efficiently. Coral-derived red fluorescent proteins require oxygen for fluorophore formation and release two hydrogen peroxide molecules. New fluorescent proteins based on phytochrome and phycobiliproteins use biliverdin IXα as fluorophores, do not require oxygen for maturation to image anaerobic organisms and tumor core, and do not generate hydrogen peroxide. The small Ultra-Red Fluorescent Protein (smURFP) was evolved from a cyanobacterial phycobiliprotein to covalently attach biliverdin as an exogenous fluorophore. The small Ultra-Red Fluorescent Protein is biophysically as bright as the enhanced green fluorescent protein, is exceptionally photostable, used for biosensor development, and visible in living mice. Novel applications of smURFP include in vitro protein diagnostics with attomolar (10−18 M) sensitivity, encapsulation in viral particles, and fluorescent protein nanoparticles. However, the availability of biliverdin limits the fluorescence of biliverdin-attaching fluorescent proteins; hence, extra biliverdin is needed to enhance brightness. New methods for improved biliverdin bioavailability are necessary to develop improved bright far-red and near-infrared fluorescent proteins for noninvasive imaging in vivo.


2016 ◽  
Author(s):  
Alysha Bhatti ◽  
Almeida Gilberto Serrano de ◽  
Serena Tommasini Ghelfi ◽  
Alwyn Dart ◽  
Anabel Varela-Carver ◽  
...  

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Hongwei Zhao ◽  
Hasaan Hayat ◽  
Xiaohong Ma ◽  
Daguang Fan ◽  
Ping Wang ◽  
...  

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.


NeuroImage ◽  
2008 ◽  
Vol 41 ◽  
pp. T90 ◽  
Author(s):  
Sean R. Donohue ◽  
S.J. Finnema ◽  
P. Truong ◽  
J. Andersson ◽  
B. Gulyás ◽  
...  

Nano Letters ◽  
2021 ◽  
Author(s):  
Alexander M. Saeboe ◽  
Alexey Yu. Nikiforov ◽  
Reyhaneh Toufanian ◽  
Joshua C. Kays ◽  
Margaret Chern ◽  
...  

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