Evidence map›Paper›PMID 41413532›Full record

ArticleJournal of nanobiotechnology2025

Three-dimensional bioprinting of patient-derived Gastrointestinal stromal tumor: a novel platform for precision oncology and drug response profiling.

Liwei Du, Zicheng Zheng, Yanan Wang, Kai Zhang, Yuce Lu, Minghao Sun, Mingchang Pang, Shangze Jiang, Yixuan He, Shunda Du and 4 more

Abstract read
In one paragraph

Article in Journal of nanobiotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

14 authors.

Liwei Du *Department of Liver Surgery, Peking Union Medical College (PUMC) Hospital, Peking Union Medical College (PUMC), Chinese Academy of Medical Sciences (CAMS), 1# Shuai-Fu-Yuan, Wang-Fu-Jing, Beijing, 100730, China.
Zicheng Zheng *Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1# Shuai-Fu-Yuan, Wang-Fu-Jing, Beijing, Beijing, 100730, China.
Yanan Wang *State Key Laboratory of Common Mechanism Research for Major Diseases, Haihe Laboratory of Cell Ecosystem, Department of Physiology, Institute of Basic Medical Sciences, School of Basic Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Kai ZhangDepartment of Liver Surgery, Peking Union Medical College (PUMC) Hospital, Peking Union Medical College (PUMC), Chinese Academy of Medical Sciences (CAMS), 1# Shuai-Fu-Yuan, Wang-Fu-Jing, Beijing, 100730, China.
Yuce LuDepartment of Liver Surgery, Peking Union Medical College (PUMC) Hospital, Peking Union Medical College (PUMC), Chinese Academy of Medical Sciences (CAMS), 1# Shuai-Fu-Yuan, Wang-Fu-Jing, Beijing, 100730, China.
Minghao SunDepartment of Liver Surgery, Peking Union Medical College (PUMC) Hospital, Peking Union Medical College (PUMC), Chinese Academy of Medical Sciences (CAMS), 1# Shuai-Fu-Yuan, Wang-Fu-Jing, Beijing, 100730, China.
Mingchang PangDepartment of Liver Surgery, Peking Union Medical College (PUMC) Hospital, Peking Union Medical College (PUMC), Chinese Academy of Medical Sciences (CAMS), 1# Shuai-Fu-Yuan, Wang-Fu-Jing, Beijing, 100730, China.
Shangze JiangDepartment of Liver Surgery, Peking Union Medical College (PUMC) Hospital, Peking Union Medical College (PUMC), Chinese Academy of Medical Sciences (CAMS), 1# Shuai-Fu-Yuan, Wang-Fu-Jing, Beijing, 100730, China.
Yixuan HeDepartment of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1# Shuai-Fu-Yuan, Wang-Fu-Jing, Beijing, Beijing, 100730, China.
Shunda DuDepartment of Liver Surgery, Peking Union Medical College (PUMC) Hospital, Peking Union Medical College (PUMC), Chinese Academy of Medical Sciences (CAMS), 1# Shuai-Fu-Yuan, Wang-Fu-Jing, Beijing, 100730, China.
Haitao ZhaoDepartment of Liver Surgery, Peking Union Medical College (PUMC) Hospital, Peking Union Medical College (PUMC), Chinese Academy of Medical Sciences (CAMS), 1# Shuai-Fu-Yuan, Wang-Fu-Jing, Beijing, 100730, China.
Yilei MaoDepartment of Liver Surgery, Peking Union Medical College (PUMC) Hospital, Peking Union Medical College (PUMC), Chinese Academy of Medical Sciences (CAMS), 1# Shuai-Fu-Yuan, Wang-Fu-Jing, Beijing, 100730, China. pumch-liver@hotmail.com.
Huayu YangDepartment of Liver Surgery, Peking Union Medical College (PUMC) Hospital, Peking Union Medical College (PUMC), Chinese Academy of Medical Sciences (CAMS), 1# Shuai-Fu-Yuan, Wang-Fu-Jing, Beijing, 100730, China. dolphinyahy@hotmail.com.
Weiming KangDepartment of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1# Shuai-Fu-Yuan, Wang-Fu-Jing, Beijing, Beijing, 100730, China. Kangwm@pumch.cn.

Funding

CAMS Innovation Fund for Medical Sciences 2023-I2M-C&T-B-016National Natural Science Foundation of China 32271470National Natural Science Foundation of China 82472174Natural Science Foundation of Beijing Municipality 7232117Noncommunicable Chronic Diseases-National Science and Technology Major Project 2024ZD0520602
6 · The paper itself

Abstract

backgroundGastrointestinal stromal tumors (GISTs) exhibit significant heterogeneity, posing substantial challenges for personalized treatment strategies. Patients often display varied responses to different therapeutic agents and dosages. Currently, the absence of robust and physiologically relevant in vitro models for GISTs impedes accurate prediction of therapeutic efficacy, thereby constraining the advancement of effective treatment strategies. Traditional 2D cell cultures fail to replicate the tumor microenvironment (TME) and lack patient-specific characteristics, limiting their predictive value. In contrast, three-dimensional bioprinting (3DP) technology faithfully recapitulates key histological architecture and molecular features of their parental tumors, enhancing the physiological relevance of in vitro models.

methodsWe employed patient-derived 3DP-GIST models via 3D bioprinting technology, followed by comprehensive histopathological, genomic, and transcriptomic analyses. Subsequently, we applied clinically approved targeted therapeutic agents to perform drug screening and response prediction on the 3DP-GIST models. The drug sensitivity profiles obtained from these models were then correlated with retrospective clinical data and patient follow-up records to assess the models' potential in guiding the selection and prediction of effective GIST therapies.

resultsIn our study, we successfully constructed 12 patient-derived 3DP-GIST models. Histopathological assessments, whole-exome sequencing (WES), and transcriptomic analyses confirmed that these models accurately recapitulate the histological architecture, biomarker expression, and molecular features of their corresponding parental tumors. Transcriptomic profiling further revealed gene expression signatures associated with GIST recurrence risk and imatinib resistance. Importantly, the 3DP-GIST models demonstrated the capacity to provide precise, individualized treatment recommendations within 10 days post-surgery, potentially reducing treatment delays and improving patient outcomes.

conclusionsOverall, the 3DP-GIST model represents a robust and efficient platform for evaluating patient-specific drug sensitivities in vitro, thereby guiding personalized therapeutic strategies for GIST patients.

Indexed as

Antineoplastic AgentsBioprintingGastrointestinal NeoplasmsGastrointestinal Stromal TumorsPrecision MedicinePrinting, Three-DimensionalFemaleHumansMaleMiddle AgedTumor MicroenvironmentAntineoplastic AgentsDrug screeningGastrointestinal stromal tumorPersonalized medicinePrecision oncologyThree-dimensional bioprinting

Identifiers

PMID41413532
PMCPMC12831436

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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.