4.8 Article

Glucose-Functionalized Liposomes for Reducing False Positives in Cancer Diagnosis

Journal

ACS NANO
Volume 15, Issue 1, Pages 1301-1309

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acsnano.0c08530

Keywords

liposomes; glucose; tumor; inflammation; false positives

Funding

  1. Israel Innovation Authority's Magneton program [66024]
  2. Ministry of Science, Technology Space, Israel

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This study developed a novel liposome technology coated with glucose and copper chelator for specific tumor uptake, showing potential for clinical translation with existing PET imaging systems to reduce false positives in cancer diagnosis. The liposomes were preferentially uptaken by cancer cells with high metabolic activity and accumulated in tumor tissue while avoiding inflammation regions in vivo.
Fluorodeoxyglucose-positron emission tomography (F-18-FOG-PET) is a powerful tool for cancer detection, staging, and follow-up. However, F-18-FDG-PET imaging has high rates of false positives, as it cannot distinguish between tumor and inflammation regions that both feature increased glucose metabolic activity. In the present study, we engineered liposomes coated with glucose and the chelator dodecane tetraacetic acid (DOTA) complexed with copper, to serve as a diagnostic technology for differentiating between cancer and inflammation. This liposome technology is based on FDA-approved materials and enables complexation with metal cations and radionuclides. We found that these liposomes were preferentially uptaken by cancer cell lines with high metabolic activity, mediated via glucose transporter-1. In vivo, these liposomes were avidly uptaken by tumors, as compared to liposomes without glucose coating. Moreover, in a combined tumor-inflammation mouse model, these liposomes accumulated in the tumor tissue and not in the inflammation region. Thus, this technology shows high specificity for tumors while evading inflammation and has potential for rapid translation to the clinic and integration with existing PET imaging systems, for effective reduction of false positives in cancer diagnosis.

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