Early detection of pulmonary arterial hypertension through [18F] positron emission tomography imaging with a vascular endothelial receptor small molecule

The objective of this study is to provide a positron emission tomography (PET) imaging modality targeting vascular endothelial growth factor receptors (VEGFR) for the early noninvasive detection and assessment of pulmonary arterial hypertension (PAH) severity. To validate the effectiveness of the [18F]VEGFR PET tracer, we utilized a monocrotaline (MCT)-induced PAH rat model. Molecular optical imaging, using a Cy5.5-conjugated VEGFR targeting agent, was employed to demonstrate the uptake of the agent at pulmonary arterioles, correlating with the onset and progression of PAH. Histological examinations of the MCT-PAH rat lung revealed a significant correlation between VEGFR2 expression and the pathogenesis of PAH. Molecular optical imaging demonstrated heightened uptake of the Cy5.5-conjugated VEGFR targeting agent at pulmonary arterioles, corresponding with the onset and progression of PAH. [18F]VEGFR PET showed increased lung uptake detectable in early-stage PAH before increase in pulmonary artery pressures, and this uptake correlated with increased PAH severity. Moreover, when compared to [18F]FDG PET, [18F]VEGFR PET exhibited markedly lower background cardiac signal, enhancing imaging sensitivity for lung abnormalities. Our study provides a compelling evidence for the potential utility of the innovative [18F]VEGFR PET tracer, in non-invasively detecting early signs of PAH, and monitoring its progression. The observed correlations between VEGFR2 expression, molecular optical imaging results, and [18F]VEGFR PET findings support the use of this tracer for early detection, and assessment of PAH severity. The lower background cardiac signal observed with [18F]VEGFR PET further enhances its imaging sensitivity, emphasizing its potential clinical significance.

64Cu/177Lu-DOTA-diZD, a Small-Molecule-Based Theranostic Pair for Triple-Negative Breast Cancer

Despite advances in targeted therapies, the prognosis for patients with triple-negative breast cancer (TNBC) is poor because there are few actionable molecular targets. The dependence of solid tumor growth on angiogenesis prompted our development of angiogenic-receptor-targeted radionuclide therapy (TRT) to treat TNBC by targeted delivery of therapeutic doses of ionizing radiation to tumors. A high-affinity vascular endothelial growth factor receptor (VEGFR)-targeted agent, diZD, was synthesized and labeled with 177Lu and 64Cu by 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) chelator giving the TRT agent, 177Lu-DOTA-diZD, and PET imaging agent, 64Cu-DOTA-diZD. We showed that "64Cu/177Lu"-DOTA-diZD radiotracers are a promising theranostic pair for TNBC. 4T1-bearing mice treated with 177Lu-DOTA-diZD-based TRT survived with a median of 28 days, which was significantly longer than that of control mice as 18 days. Anti-PD1 immunotherapy resulted in a shorter median survival of 16 days. This work presents for the first time that small-molecule VEGFR-oriented TRT is a promising therapeutic option to treat "immunogenic cold" TNBC.

CURATE.AI: Optimizing Personalized Medicine with Artificial Intelligence

The clinical team attending to a patient upon a diagnosis is faced with two main questions: what treatment, and at what dose? Clinical trials' results provide the basis for guidance and support for official protocols that clinicians use to base their decisions upon. However, individuals rarely demonstrate the reported response from relevant clinical trials, often the average from a group representing a population or subpopulation. The decision complexity increases with combination treatments where drugs administered together can interact with each other, which is often the case. Additionally, the individual's response to the treatment varies over time with the changes in his or her condition, whether via the indication or physiology. In practice, the drug and the dose selection depend greatly on the medical protocol of the healthcare provider and the medical team's experience. As such, the results are inherently varied and often suboptimal. Big data approaches have emerged as an excellent decision-making support tool, but their application is limited by multiple challenges, the main one being the availability of sufficiently big datasets with good quality, representative information. An alternative approach-phenotypic personalized medicine (PPM)-finds an appropriate drug combination (quadratic phenotypic optimization platform [QPOP]) and an appropriate dosing strategy over time (CURATE.AI) based on small data collected exclusively from the treated individual. PPM-based approaches have demonstrated superior results over the current standard of care. The side effects are limited while the desired output is maximized, which directly translates into improving the length and quality of individuals' lives.