ReviewJournal of nanobiotechnology2026
Recent advances in nanomaterial-based precision medicine for orthotopic tumor therapy.
Review in Journal of nanobiotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Delivering Degradation: Nanomedicine and Programmable Proximity Platforms for Targeted Protein Degradation.Pharmaceutics · 2026Review
- Supramolecular coordination nanoplatform amplifies oxidative stress to overcome ferroptosis resistance in gallbladder cancer.Journal of nanobiotechnology · 2026Article
- Application Advances of Gold Nanoparticles in Cancer Theranostics: From Physicochemical Mechanisms to Multifunctional Nanoplatforms.International journal of molecular sciences · 2026Review
- Macrophage polarization in gynecologic malignancies: key signaling pathways and clinical perspectives.Frontiers in immunology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
The escalating global burden of cancer, marked by high incidence and mortality, necessitates more effective therapeutic strategies. A major bottleneck in clinical translation is the long-standing reliance on subcutaneous tumor models, which fail to recapitulate the complex physiological and pathological features of human malignancies. These ectopic models lack organ-specific barriers-such as the prostatic capsule, cervicovaginal mucus, and dense desmoplastic stroma-and cannot reproduce authentic metastatic niches or immune heterogeneity. Consequently, this review advocates a paradigm shift toward orthotopic-TME-informed nanomedicine design. We systematically evaluate recent progress in nanotherapeutics across twelve major malignancies, categorized into three strategic domains: (i) barrier-penetrating platforms engineered to navigate organ-specific physical and biochemical constraints; (ii) metastasis-targeted delivery systems that exploit native lymphovascular pathways; and (iii) microenvironment-responsive mechanisms that adapt to localized stimuli such as hypoxia and acidity. By integrating data from a wide range of studies, we highlight how orthotopic models provide a more rigorous platform for assessing drug penetration and therapeutic efficacy than conventional subcutaneous models. Furthermore, we critically discuss existing challenges, including manufacturing scalability, the bio-nano interface, and long-term toxicological safety. Looking forward, we propose a strategic roadmap that emphasizes the use of patient-derived orthotopic xenografts (PDOX), multi-omics data integration, and the development of closed-loop adaptive nanosystems. By aligning nanomaterial properties with constraints inherent to the orthotopic microenvironment, this review aims to provide a blueprint for the next generation of precision oncology platforms that can successfully bridge the gap from bench to bedside.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.