“ In particular, tumor-derived EVs (TEVs) exhibit intrinsic organotropism and participate in the establishment of premetastatic niches, making them promising vehicles for the targeted delivery of imaging probes to metastasis-prone tissues. ”
BUFFALO, NY – September 1, 2026 – A new review was published in Volume 17 of Oncotarget on August 28, 2026, titled “ Emerging biomedical imaging applications of tumor-derived extracellular vesicles for premetastatic niche detection: Biological rationale, engineering strategies, and translational challenges .”
The review was led by first author Omkar Dhaygude, who is affiliated with Johns Hopkins University . Corresponding authors Franck Housseau and John Michel are affiliated with Johns Hopkins University , with Housseau also affiliated with the Cancer Research Center of Lille in France .
Extracellular vesicles (EVs) are membrane-enclosed particles released by cells that transport proteins, lipids, nucleic acids, metabolites, and other molecular cargo. In cancer, tumor-derived extracellular vesicles (TEVs) can influence the tumor microenvironment and distant tissues by promoting processes such as angiogenesis, extracellular matrix remodeling, inflammatory signaling, immune evasion, and stromal reprogramming.
Of particular interest is the role of TEVs in establishing premetastatic niches—biological environments in distant organs that become permissive to metastatic cells before overt tumors are detectable. TEVs can carry organ-specific molecular signals, and their surface molecules may influence which tissues they reach. For example, previous experimental research has linked the integrins α6β4 and α6β1 with lung tropism, providing a biological rationale for using TEVs to direct imaging probes toward metastasis-prone organs.
This possibility could address an important limitation of conventional cancer imaging. Computed tomography and other anatomical methods are designed primarily to detect established structural lesions, whereas premetastatic niches are characterized by earlier molecular and microenvironmental alterations. The authors therefore examine whether TEV-associated imaging could provide information about metastatic conditioning before conventional imaging can identify overt metastatic lesions.
The review evaluates a range of imaging strategies, including fluorescence, bioluminescence, photoacoustic imaging, positron emission tomography (PET), single-photon emission computed tomography (SPECT), computed tomography (CT), and magnetic resonance imaging (MRI). Fluorescence and bioluminescence provide sensitive tools for studying EV trafficking in preclinical models, while PET/SPECT and MRI currently offer clearer routes toward potential clinical translation because of their deep-tissue and whole-body imaging capabilities.
Different engineering approaches can make TEVs detectable by these technologies. Vesicles can be radiolabeled for PET or SPECT, loaded with magnetic materials for MRI, or combined with high-density agents for CT. Nanoparticles, near-infrared fluorophores, and genetically encoded reporters have also enabled increasingly sophisticated tracking of EV biodistribution and organ tropism. Some photoacoustic approaches combine imaging with therapeutic functions, creating potential theranostic platforms.
However, the authors emphasize an important distinction: most existing studies visualize labeled or engineered EV-associated signals rather than the premetastatic niche itself. Accumulation of an imaging signal in the lung, liver, or another organ may reflect EV biodistribution, nonspecific uptake, label persistence, or clearance pathways rather than direct visualization of metastatic conditioning. Current EV imaging should therefore largely be considered a proxy for niche-related processes rather than a clinically validated method for detecting premetastatic niches.
“ Overall, EV-based imaging is best viewed as a promising but still evolving strategy whose future clinical value will depend on whether it can move beyond proof-of-concept biodistribution studies toward robust, tumor-specific, and clinically feasible approaches for premetastatic niches detections and early metastatic risk assessment .”
Several translational challenges must be addressed before this approach can reach clinical practice. Imaging labels may detach from EVs or persist after vesicle degradation, making it difficult to determine whether a detected signal represents intact, biologically active vesicles. Current approaches also struggle to distinguish TEVs from the much larger background of extracellular vesicles produced by normal host cells. Moreover, loading EVs with dyes, radionuclides, iron oxide particles, or other materials can alter their biological behavior and organ distribution.
Manufacturing presents additional obstacles, including low EV yields, heterogeneous preparations, inconsistent isolation methods, and difficulties producing reproducible clinical-grade EV formulations at scale. Future progress may depend on combining more tumor-specific EV biomarkers with clinically compatible imaging technologies and computational approaches capable of integrating multimodal signals. Artificial intelligence could assist with image analysis and feature extraction, but the authors stress that it cannot substitute for biological validation.
Overall, the review presents TEV-based imaging as a biologically compelling but predominantly preclinical approach for assessing early metastatic risk. Improving tumor specificity, label fidelity, biological integrity, standardization, and clinical-scale production will be necessary before TEV-based imaging can move from experimental biodistribution studies toward reliable detection of premetastatic changes in patients.
DOI: https://doi.org/10.18632/oncotarget.28916
Correspondence to: Franck Housseau – fhousse1@jhmi.edu , John Michel – jmiche14@jhmi.edu
Keywords : cancer, lung metastases, cancer imaging, theranostic, premetastatic niches, extra-cellular vesicles
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Oncotarget
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Emerging biomedical imaging applications of tumor-derived extracellular vesicles for premetastatic niche detection: Biological rationale, engineering strategies, and translational challenges
28-Aug-2026
Authors have no conflicts of interest to declare.