Evidence map›Paper›PMID 42542881›Full record

ReviewInternational journal of nanomedicine2026

Resveratrol Nanoformulations for Cancer Management: A Comprehensive Review of Disease-Specific Strategies and Clinical Translational Barriers.

Huifang Yang, Zilin Cheng, Yilin Wang, Kexin Tang, Tongtong Zeng, Jing Guo

Abstract readReview
In one paragraph

Review in International journal of nanomedicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Huifang Yang *Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China.ORCID 0009-0007-7247-9486
Zilin Cheng *Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China.
Yilin WangHospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China.ORCID 0009-0004-5579-4837
Kexin TangHospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China.
Tongtong ZengHospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China.
Jing GuoHospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer remains a leading cause of mortality worldwide, highlighting the need for therapeutic strategies that reduce systemic toxicity and drug resistance. Resveratrol (RES), a natural polyphenolic stilbenoid, possesses antioxidant, anti-inflammatory, pro-apoptotic, anti-metastatic, and chemosensitizing activities. However, its clinical translation is limited by poor aqueous solubility, chemical instability, rapid metabolic clearance, and consequently low systemic bioavailability. Nanotechnology-based drug delivery systems provide a promising strategy to address these limitations. This review summarizes recent advances in RES-loaded nanoformulations, including polymeric nanoparticles, liposomes, solid lipid nanoparticles, micelles, inorganic nanocarriers, protein-based systems, and biomimetic vesicles. Their therapeutic performance is evaluated across prostate, lung, colorectal, breast, and other cancers, with attention to tumor targeting, controlled release, combination therapy, multidrug-resistance reversal, and modulation of cancer-relevant pathways such as NF-κB, p53, and PI3K/Akt/mTOR. Current oncology-related clinical evidence for RES is still largely based on conventional oral or micronized formulations. Translation of engineered RES nanocarriers therefore requires stronger evidence on scalable manufacturing, carrier-specific safety, heterogeneous tumor delivery, and biomarker-guided trial design. This review also introduces a semi-quantitative prioritization framework based on model-readiness, translational priority, and safety-alert scoring for future PBPK, PK-PD, nano-QSAR, and machine-learning analyses.

Indexed as

Nanoparticle Drug Delivery SystemNanoparticlesNeoplasmsResveratrolStilbenesAnimalsAntineoplastic AgentsHumansNanomedicineAntineoplastic AgentsNanoparticle Drug Delivery SystemResveratrolStilbenesbioavailabilitycancer therapyclinical translationdrug delivery systemsnanoparticlesresveratrol

Identifiers

PMID42542881
PMCPMC13428552

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.