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Theranostics 2.0: Target-driven, artificial intelligence-enabled cancer therapy across tumor types - 29/11/25

Doi : 10.1016/j.diii.2025.07.003 
Jorge D. Oldan a, Anurag Anugu b, Md Zobaer Islam c, Alireza Amindarolzarbi d, Rudolf A. Werner e, Martin G. Pomper c, Lilja B. Solnes f, Frankis Almaguel g, Stergios Moschos h, Benjamin L Viglianti i, 1, Steven P. Rowe c, 1,
a Department of Radiology, University of North Carolina, Chapel Hill, NC, 27599, USA 
b Duke University, Durham, NC, 27708, USA 
c Department of Radiology, University of Texas Southwestern Medical Cetner, Dallas, TX, 75390, USA 
d Nuclear Medicine, University of Maryland, Baltimore, MD, 21250, USA 
e Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany 
f The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, 21234, USA 
g Loma Linda University Medical Center, Loma Linda, CA, 92354, USA 
h Division of Oncology, Department of Medicine, University of North Carolina, Chapel Hill, NC, 27599, USA 
i Department of Radiology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA 

Corresponding author.

Highlight

Theranostics combines targeted radiopharmaceuticals for imaging and diagnosis with similar therapeutic agents that are now a key pillar of systemic therapy for cancers.
Currently, theranostic agents are used in specific, narrow disease scenarios such as the treatment of gastroenteropancreatic neuroendocrine tumors and metastatic castration-resistant prostate cancer.
Theranostics is on the cusp of broader application, "agnostic" to the cell of origin, where tumors with the appropriate target expression will be treated with targeted radioligand therapies.

El texto completo de este artículo está disponible en PDF.

Abstract

To date, prospective, pivotal clinical trials in the theranostic space have focused on specific disease states. Those include leveraging positron emission tomography (PET) findings to optimize the second-line use of 177 Lu-DOTATATE in patients with metastatic and progressive neuroendocrine tumors or the use of prostate-specific membrane antigen (PSMA) PET findings to select patients with metastatic castration-resistant prostate cancer for treatment with 177 Lu-PSMA-617. However, we are entering an era where a broader understanding of the expression patterns of a wide variety of targets is beginning to be understood. As an example, PSMA PET has shown potential utility in the imaging of clear cell renal cell carcinoma and other malignancies with high rates of neovascularity. Many of the theranostic agents in the pipeline are designed to bind against " pan-cancer " targets such as fibrinogen-activating protein or the C-X-C motif chemokine receptor 4, or targets that become over-expressed in a broad variety of cancer states, such as those that target carbonic anhydrase IX. Artificial intelligence methods will assist us in appropriately selecting patients and in delivering predictive and prognostic imaging biomarkers. Given the wide potential applicability of emerging theranostic agents, it will be incumbent upon the field to carefully design clinical trials that will lead to regulatory approvals that will, in turn, permit broad use across a number of cancer types. In our future clinical practices, we will evolve to leverage precision medicine to identify target expression and deliver appropriate theranostic agents that are not limited to a specific cell of origin or disease state.

El texto completo de este artículo está disponible en PDF.

Keywords : Fibrinogen-activating protein, Prostate-specific membrane antigen, Radioligand therapy, Theranostics

Abbreviations : 3-pHPG, AI, CAIX, ccRCC, CT, CXCR4, FAP, FDA, FDG, GAN, MIBG, NEN, NET, PCa, PD, PET, PRLT, PRRT, PSMA, RCC, SSTR, VAE


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Vol 106 - N° 12

P. 413-420 - décembre 2025 Regresar al número
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