Evidence map›Paper›PMID 39748450›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

Prediction of Patient Drug Response via 3D Bioprinted Gastric Cancer Model Utilized Patient-Derived Tissue Laden Tissue-Specific Bioink.

Yoo-Mi Choi, Deukchae Na, Goeun Yoon, Jisoo Kim, Seoyeon Min, Hee-Gyeong Yi, Soo-Jeong Cho, Jae Hee Cho, Charles Lee, Jinah Jang

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

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

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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

10 authors.

Yoo-Mi ChoiCenter for 3D Organ Printing and Stem cells (COPS), Pohang University of Science and Technology (POSTECH), Pohang, 37666, Republic of Korea.
Deukchae NaEwha Institute of Convergence Medicine, Ewha Womans University Mokdong Hospital, Seoul, 07985, Republic of Korea.
Goeun YoonDepartment of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37666, Republic of Korea.ORCID https://orcid.org/0009-0005-2780-963X
Jisoo KimSchool of Interdisciplinary Bioscience and Bioengineering, Pohang University of Science and Technology (POSTECH), Pohang, 37666, Republic of Korea.
Seoyeon MinEwha Institute of Convergence Medicine, Ewha Womans University Mokdong Hospital, Seoul, 07985, Republic of Korea.
Hee-Gyeong YiDepartment of Rural and Biosystems Engineering, Chonnam National University, Gwangju, 61186, Republic of Korea.
Soo-Jeong ChoDepartment of Internal Medicine, Liver Research Institute, Seoul National University Hospital, Seoul, 03080, Republic of Korea.
Jae Hee ChoDepartment of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, 06273, Republic of Korea.
Charles LeeEwha Institute of Convergence Medicine, Ewha Womans University Mokdong Hospital, Seoul, 07985, Republic of Korea.
Jinah JangCenter for 3D Organ Printing and Stem cells (COPS), Pohang University of Science and Technology (POSTECH), Pohang, 37666, Republic of Korea.ORCID https://orcid.org/0000-0001-9046-3495

Funding

Korea government (MSIT), National Research Foundation of Korea(NRF) grant. 2021R1A2C2004981Korea government (MSIT), National Research Foundation of Korea(NRF) grant. 2022M3C1A3081359Ministry of Education, Basic Science Research Program through the National Research Foundation of Korea(NRF) 2020R1A6A1A03047902
6 · The paper itself

Abstract

Despite significant research progress, tumor heterogeneity remains elusive, and its complexity poses a barrier to anticancer drug discovery and cancer treatment. Response to the same drug varies across patients, and the timing of treatment is an important factor in determining prognosis. Therefore, development of patient-specific preclinical models that can predict a patient's drug response within a short period is imperative. In this study, a printed gastric cancer (pGC) model is developed for preclinical chemotherapy using extrusion-based 3D bioprinting technology and tissue-specific bioinks containing patient-derived tumor chunks. The pGC model retained the original tumor characteristics and enabled rapid drug evaluation within 2 weeks of its isolation from the patient. In fact, it is confirmed that the drug response-related gene profile of pGC tissues co-cultured with human gastric fibroblasts (hGaFibro) is similar to that of patient tissues. This suggested that the application of the pGC model can potentially overcome the challenges associated with accurate drug evaluation in preclinical models (e.g., patient-derived xenografts) owing to the deficiency of stromal cells derived from the patient. Consequently, the pGC model manifested a remarkable similarity with patients in terms of response to chemotherapy and prognostic predictability. Hence, it is considered a promising preclinical tool for personalized and precise treatments.

Indexed as

Antineoplastic AgentsBioprintingPrinting, Three-DimensionalStomach NeoplasmsAnimalsCoculture TechniquesHumansAntineoplastic Agentsdrug efficacy testinggastric cancer patient‐derived xenograftgastric tissue‐derived decellularized extracellular matrixtumor tissue printing

Identifiers

PMID39748450
PMCPMC11905052

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Registered trials

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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.