Evidence map›Paper›PMID 40219336›Full record

ReviewPolymers2025

Advances and Challenges in 3D Bioprinted Cancer Models: Opportunities for Personalized Medicine and Tissue Engineering.

Sai Liu, Pan Jin

Abstract readReview
In one paragraph

Review in Polymers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Review
  6. Review
  7. Review
  8. Review
  9. The role of stem cells in precision medicine: next-generation cancer treatment.Journal of the Egyptian National Cancer Institute · 2025
    Review
  10. Dynamic Hydrogels in Breast Tumor Models.Gels (Basel, Switzerland) · 2025
    Review
  11. 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.

Sai LiuHealth Science Center, Yangtze University, Jingzhou 434023, China.
Pan JinHealth Science Center, Yangtze University, Jingzhou 434023, China.

Funding

National Natural Science Foundation of China (NSFC) No. 81860386 No. 81860386
6 · The paper itself

Abstract

Cancer is the second leading cause of death worldwide, after cardiovascular disease, claiming not only a staggering number of lives but also causing considerable health and economic devastation, particularly in less-developed countries. Therapeutic interventions are impeded by differences in patient-to-patient responses to anti-cancer drugs. A personalized medicine approach is crucial for treating specific patient groups and includes using molecular and genetic screens to find appropriate stratifications of patients who will respond (and those who will not) to treatment regimens. However, information on which risk stratification method can be used to hone in on cancer types and patients who will be likely responders to a specific anti-cancer agent remains elusive for most cancers. Novel developments in 3D bioprinting technology have been widely applied to recreate relevant bioengineered tumor organotypic structures capable of mimicking the human tissue and microenvironment or adequate drug responses in high-throughput screening settings. Parts are autogenously printed in the form of 3D bioengineered tissues using a computer-aided design concept where multiple layers include different cell types and compatible biomaterials to build specific configurations. Patient-derived cancer and stromal cells, together with genetic material, extracellular matrix proteins, and growth factors, are used to create bioprinted cancer models that provide a possible platform for the screening of new personalized therapies in advance. Both natural and synthetic biopolymers have been used to encourage the growth of cells and biological materials in personalized tumor models/implants. These models may facilitate physiologically relevant cell-cell and cell-matrix interactions with 3D heterogeneity resembling real tumors.

Indexed as

3D bioprintingpersonalized medicinetumor microenvironmenttumor model

Identifiers

PMID40219336
PMCPMC11991528

What OpenQuestion holds

Textmetadata
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.