Evidence map›Paper›PMID 41322649›Full record

ReviewACS omega2025

Engineering Osteosarcoma In Vitro: From Traditional Models to Biofabricated Platforms for Precision Medicine.

Jing Liu, Bihan Ren, Tianma He, Dingming Li, Tao Ding, Qian Wang, Haochen Liu

Abstract readReview
In one paragraph

Review in ACS omega, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. 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

7 authors.

Jing LiuSchool of Biology, Food and Environment, Hefei University, Hefei, 230601, P. R. China.ORCID https://orcid.org/0000-0001-6595-2764
Bihan RenSchool of Biology, Food and Environment, Hefei University, Hefei, 230601, P. R. China.
Tianma HeSchool of Biology, Food and Environment, Hefei University, Hefei, 230601, P. R. China.
Dingming LiSchool of Biology, Food and Environment, Hefei University, Hefei, 230601, P. R. China.
Tao DingSchool of Biology, Food and Environment, Hefei University, Hefei, 230601, P. R. China.
Qian WangCAS Key Laboratory of Mechanical Behavior and Design of Materials, Department of Modern Mechanics, University of Science and Technology of China, Hefei 230027, China.
Haochen LiuDepartment of Cardiovascular Surgery, Xi'an Children's Hospital, Xi'an, 710003, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Osteosarcoma is a highly malignant primary bone tumor that predominantly affects adolescents. Despite the widespread application of standard treatment modalities, including surgical resection, chemotherapy, and radiotherapy, the long-term survival rate of patients remains unsatisfactory due to the high metastatic potential and drug resistance of the disease. In recent years, researchers have focused on developing more precise in vitro models that aim to better simulate the tumor microenvironment, thereby enhancing the effectiveness of drug screening and personalized therapy. This review summarizes the latest advances in osteosarcoma in vitro modeling, including the development of conventional two-dimensional culture systems, three-dimensional culture platforms, organoid models, and microfluidic chips designed to mimic the tumor microenvironment. Additionally, this review explores the application value of these models in drug screening, immune coculture systems, and personalized treatment strategies. The integration of multiomics data and artificial intelligence is also discussed as a means to optimize model design and facilitate precision oncology. Biomimetic in vitro models have the potential to more accurately replicate tumor heterogeneity, cell-cell interactions, and the complexity of the tumor microenvironment, thereby increasing the translational value of preclinical drug development. Finally, this review highlights the current challenges in the field, including the lack of standardized protocols, issues with model stability and reproducibility, and the practical integration of these models into preclinical research pipelines.

Identifiers

PMID41322649
PMCPMC12658639

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.