Evidence map›Paper›PMID 42245685›Full record

ArticleFrontiers in oncology2026

Nanomaterial-based strategies to overcome sorafenib resistance in hepatocellular carcinoma: from mechanistic insights to translational applications.

Jinbang Huang, Shi Huang, Wenjing Chen, Shunsheng Wang, Zhihao Zuo, Xinyan Wu, Gang Deng

Abstract read
In one paragraph

Article in Frontiers in oncology, 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

7 authors.

Jinbang Huang *Department of General Surgery, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.
Shi Huang *Clinical Medical College, Southwest Medical University, Luzhou, China.
Wenjing Chen *Clinical Medical College, Southwest Medical University, Luzhou, China.
Shunsheng WangClinical Medical College, Southwest Medical University, Luzhou, China.
Zhihao ZuoThe First Clinical College of Chongqing Medical University, Chongqing, China.
Xinyan WuCollege of Food Science and Nutritional Engineering, China Agricultural University, Beijing, China.
Gang DengDepartment of General Surgery, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is the most common histological subtype of primary liver cancer and a leading cause of cancer-related mortality. Although immunotherapy combinations have expanded systemic treatment options for advanced HCC, sorafenib remains clinically relevant in select patient populations and provides a mechanistically informative model for treatment resistance. Sorafenib resistance arises from interrelated processes, including insufficient intratumoral drug exposure, hypoxia-driven escape signaling, ABC transporter-mediated drug efflux, epithelial-mesenchymal transition, MAPK and PI3K/AKT/mTOR pathway compensation, ferroptosis dysregulation, and immunosuppressive microenvironment remodeling. Based on these mechanisms, we propose a mechanism-driven nanomedicine framework that integrates sorafenib delivery with targeted resistance-axis intervention, rather than focusing only on drug solubility, circulatory stability, or tumor accumulation. Representative strategies include ligand-targeted nanocarriers, CXCR4-directed delivery systems, the synchronous co-delivery of sorafenib with pathway inhibitors or nucleic acid regulators, ferroptosis-modulating nanodrugs, and tumor microenvironment (TME)-responsive delivery systems. Among these, biomimetic membrane-modified smart responsive platforms are particularly noteworthy because they can convert HCC microenvironmental features, such as elevated glutathione (GSH), immunosuppressive tumor-associated macrophage (TAM) accumulation, and ferroptosis resistance, into triggers for drug release, dual targeting, and resistance regulation. Artificial intelligence and machine learning may further support resistance-pattern prediction, patient stratification, nanoplatform selection, and formulation optimization. Overall, sorafenib nanomedicine may integrate drug delivery optimization, resistance intervention, and patient stratification into a unified therapeutic framework with improved mechanistic specificity and translational potential for sorafenib-resistant HCC.

Indexed as

clinical translationhepatocellular carcinomananomaterialssorafenib resistancetargeted delivery

Identifiers

PMID42245685
PMCPMC13229793

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.