Evidence map›Paper›PMID 41942359›Full record

ArticleJournal of gastric cancer2026

Molecular and Phenotypic Characterization of Fluid-Derived Patient-Derived Cell and Organoid Models in Advanced Gastric Cancer.

Ye Jin Moon, Woo Sun Kwon, Chan Hee Park, Jinsoo Jang, Juin Park, Byeong Gyu Yoon, Han Byeol Mun, Namju Kim, Choong-Kun Lee, Hei Cheul Jeung and 3 more

Abstract read
In one paragraph

Article in Journal of gastric cancer, 2026. 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. Article
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

13 authors.

Ye Jin MoonSong-Dang Institute for Cancer Research, Yonsei University College of Medicine, Seoul, Korea.ORCID 0009-0003-4293-3722
Woo Sun KwonSong-Dang Institute for Cancer Research, Yonsei University College of Medicine, Seoul, Korea.ORCID 0000-0003-0268-5624
Chan Hee ParkSong-Dang Institute for Cancer Research, Yonsei University College of Medicine, Seoul, Korea.ORCID 0000-0002-3820-686X
Jinsoo JangSong-Dang Institute for Cancer Research, Yonsei University College of Medicine, Seoul, Korea.ORCID 0009-0004-2573-1253
Juin ParkSong-Dang Institute for Cancer Research, Yonsei University College of Medicine, Seoul, Korea.ORCID 0000-0002-5006-1464
Byeong Gyu YoonSong-Dang Institute for Cancer Research, Yonsei University College of Medicine, Seoul, Korea.ORCID 0009-0007-0443-135X
Han Byeol MunSong-Dang Institute for Cancer Research, Yonsei University College of Medicine, Seoul, Korea.ORCID 0009-0000-2667-4562
Namju KimSong-Dang Institute for Cancer Research, Yonsei University College of Medicine, Seoul, Korea.ORCID 0009-0006-5028-3549
Choong-Kun LeeSong-Dang Institute for Cancer Research, Yonsei University College of Medicine, Seoul, Korea.ORCID 0000-0001-5151-5096
Hei Cheul JeungSong-Dang Institute for Cancer Research, Yonsei University College of Medicine, Seoul, Korea.ORCID 0000-0003-0952-3679
Su-Jin ShinDepartment of Pathology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.ORCID 0000-0001-9114-8438
Tae Soo KimSong-Dang Institute for Cancer Research, Yonsei University College of Medicine, Seoul, Korea.ORCID 0009-0006-7996-3409
Sun Young RhaSong-Dang Institute for Cancer Research, Yonsei University College of Medicine, Seoul, Korea.ORCID 0000-0002-2512-4531

Funding

NRF 2020R1A2B5B02001452
6 · The paper itself

Abstract

purposePatient-derived cells (PDCs) and patient-derived organoids (PDOs) are complementary preclinical models widely used in translational cancer research. However, their molecular and functional differences have not been systematically characterized. This study established and analyzed paired PDC and PDO models derived from the same gastric cancer ascites to delineate platform-dependent molecular and functional profiles. MATERIALS AND

methodsMalignant ascites or pleural fluid obtained from 6 patients with advanced gastric cancer were used to establish paired PDC and PDO models. All pairs underwent comprehensive multi-omics profiling, integrating genomic, transcriptomic, and proteomic data. Phenotypic characterization included morphological, histological, proliferative, and cell cycle analyses. Drug sensitivity assays were performed using 4 chemotherapeutic agents commonly used to treat gastric cancer.

resultsThe 6 paired PDC and PDO models exhibited distinct morphological characteristics. Whole-genome analyses demonstrated high concordance among primary tumors, PDCs, and PDOs, confirming tumor representation across platforms. Multi-omics profiling identified platform-dependent molecular signatures; PDOs were enriched for extracellular matrix remodeling and stemness, whereas PDCs displayed proliferation- and immune-related signatures. Clinically relevant biomarkers, including HER2 and MET alterations, were concordant with primary tumors. Notably, drug responses differed between platforms and patients, indicating platform-dependent and patient-specific chemosensitivity.

conclusionsPaired PDC and PDO models derived from the same patients preserved core patient-specific tumor characteristics while exhibiting distinct molecular and functional profiles. These findings underscore the culture platform as a critical determinant of experimental outcomes and therapeutic responses. Therefore, careful selection of an appropriate preclinical model is essential to accurately address biological questions and optimize precision oncology strategies.

Indexed as

OrganoidsPleural Effusion, MalignantStomach NeoplasmsAgedAscitesBiomarkers, TumorCell ProliferationFemaleHumansMaleMiddle AgedMultiomicsPhenotypeProteomicsBiomarkers, TumorAscitesCell line, tumorGastric cancerMulti-omicsOrganoids

Identifiers

PMID41942359
PMCPMC13053824

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LicenceCC BY-NC
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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.