Evidence map›Paper›PMID 41534869›Full record

ReviewSeminars in liver disease2026

Patient-Derived Models of Liver Cancer to Inform Clinical Treatment Paradigms: Recent Updates.

Kelley Weinfurtner, Rudra Amin, Nicolas Skuli, Terence P Gade, David E Kaplan

Abstract readReview
In one paragraph

Review in Seminars in liver disease, 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

5 authors.

Kelley WeinfurtnerDivision of Gastroenterology and Hepatology, University of Pennsylvania, Philadelphia, Pennsylvania, United States.
Rudra AminDepartment of the Radiologic Sciences, Penn Image-Guided Interventions Lab, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, United States.
Nicolas SkuliDepartment of the Radiologic Sciences, Penn Image-Guided Interventions Lab, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, United States.
Terence P GadeDepartment of the Radiologic Sciences, Penn Image-Guided Interventions Lab, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, United States.
David E KaplanDivision of Gastroenterology and Hepatology, University of Pennsylvania, Philadelphia, Pennsylvania, United States.

Funding

NIH HHS CA220654P2VA I01-CX002010VA I01-CX002337VA I01-CX002542
6 · The paper itself

Abstract

Primary liver cancer remains a global health challenge due to rising incidence, limited curative options, and poor overall survival. Poor outcomes stem from tumor heterogeneity, limited efficacy of current therapies, and comorbid chronic liver disease. Despite recent advances in immunotherapy and combination treatments, response rates remain low, and predictive biomarkers are lacking. As a result, there is an urgent need for preclinical models that capture the molecular, cellular, and immune landscape of primary liver cancer. This review discusses the strengths and limitations of patient-derived models of liver cancer, including two-dimensional patient-derived cell lines (PDCL), three-dimensional (3D) patient-derived tumor organoids (PDTOs), and patient-derived xenografts (PDXs). While PDCLs and PDTOs enable high throughput studies, they lack a representative tumor microenvironment. PDXs, including PDXs in animals with humanized immune systems, may more effectively mimic tumor-environment interactions but are costly, complex, and still contain mouse stromal cells. Ex vivo tissue culture preserves tissue structure and cell-cell interactions in an immunocompetent environment; however, short duration of viable culture limits broader application. Continued innovation in the development of multicellular three-dimensional culture systems and in vivo humanization strategies will play a critical role in enabling the development of more personalized and effective therapies for primary liver cancer.

Indexed as

Liver NeoplasmsAnimalsHumansOrganoidsTumor Microenvironment

Identifiers

PMID41534869
PMCPMC13134922

What OpenQuestion holds

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LicenceCC BY
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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.