Evidence map›Paper›PMID 40548062›Full record

ReviewGenes & diseases2025

Patient-derived xenograft models: Current status, challenges, and innovations in cancer research.

Minqi Liu, Xiaoping Yang

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Genes & diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
–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

27 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Review
  6. Review
  7. Organoid technology in cancer research.Molecular biomedicine · 2026
    Review
  8. Review
  9. Neuropeptide Y as a Neuro-Immune Checkpoint in Cancer.Journal of neuroimmune pharmacology : the official journal of the Society on NeuroImmune Pharmacology · 2026
    Review
  10. Review
  11. Review
  12. Review
  13. Review
  14. Review
  15. Review
  16. Organoids for disease modeling and treatment: state-of-the-art.Experimental hematology & oncology · 2026
    Review
  17. Review
  18. Review
  19. Review
  20. Role of circulating tumor cell clusters in breast cancer.Translational breast cancer research : a journal focusing on translational research in breast cancer · 2026
    Review
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

2 authors.

Minqi LiuKey Laboratory of Chemical Biology & Traditional Chinese Medicine Research of Ministry of Education, Key Laboratory of Study and Discovery of Small Targeted Molecules of Hunan Province, Engineering Research Center of Reproduction and Translational Medicine of Hunan Province, Key Laboratory of Protein Chemistry and Developmental Biology of Fish of Ministry of Education, Department of Pharmacy, School of Medicine, Hunan Normal University, Changsha, Hunan 410013, China.
Xiaoping YangKey Laboratory of Chemical Biology & Traditional Chinese Medicine Research of Ministry of Education, Key Laboratory of Study and Discovery of Small Targeted Molecules of Hunan Province, Engineering Research Center of Reproduction and Translational Medicine of Hunan Province, Key Laboratory of Protein Chemistry and Developmental Biology of Fish of Ministry of Education, Department of Pharmacy, School of Medicine, Hunan Normal University, Changsha, Hunan 410013, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite advancing therapeutic treatments, cancer remains the leading cause of death worldwide, with most of its patients developing drug resistance and recurrence after initial treatment. Therefore, incorporating preclinical models that mimic human cancer biology and drug responses is essential for improving treatment efficacy and prognosis. Patient-derived xenograft (PDX) models, as a promising and reliable preclinical trial platform, retain key features of the original tumor such as gene expression profiles, histopathological features, drug responses, and molecular signatures more faithfully compared with traditional tumor cell line models and cell line-derived xenograft models. Their significant advantages have been the preferred choice in cancer research, especially demonstrating remarkable potential in drug development, clinical combination therapy, and precision medicine. However, the successful construction and effective application of PDX models still face several challenges. In this review, we summarize the details of constructing PDX models and the drivers affecting their success rates, which will provide some theoretical basis for subsequent model optimization. In the meantime, we delineate the strengths and weaknesses of various mature PDX models and other developing preclinical models, including PDX-derived models, organoids, and genetically engineered models. Moreover, we highlight the challenges of newly developed technologies on the PDX models. Finally, we emphasize the innovative usage of PDX models in a variety of cancer studies and offer insights into their prospects.

Indexed as

Cancer modelsCo-clinical trialsDrug screeningPDX modelsPrecision medicine

Identifiers

PMID40548062
PMCPMC12179623

What OpenQuestion 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 OpenQuestion graph.