Evidence map›Paper›PMID 40001264›Full record

ArticleJournal of experimental & clinical cancer research : CR2025

Combining molecular characteristics and therapeutic analysis of PDOs predict clinical responses and guide PDAC personalized treatment.

Peng Li, Minli Huang, Mengyao Li, Gen Li, Yifan Ma, Yong Zhao, Xiaowu Wang, Yongbin Zhang, Changhong Shi

Abstract read
In one paragraph

Article in Journal of experimental & clinical cancer research : CR, 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.

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  5. Organoids glimpse: the nexus for diverse tumor heterogeneity.Frontiers in cell and developmental biology · 2026
    Review
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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

9 authors.

Peng Li *Division of Cancer Biology, Laboratory Animal Center, The Fourth Military Medical University, Xi'an, Shaanxi, 710032, PR China.
Minli Huang *Division of Cancer Biology, Laboratory Animal Center, The Fourth Military Medical University, Xi'an, Shaanxi, 710032, PR China.
Mengyao Li *Division of Cancer Biology, Laboratory Animal Center, The Fourth Military Medical University, Xi'an, Shaanxi, 710032, PR China.
Gen LiDepartment of Urology, Tangdu Hospital, Fourth Military Medical University, Xi'an, Shaanxi, 710032, PR China.
Yifan MaGansu University of Chinese Medicine, Lanzhou, 730030, China.
Yong ZhaoDivision of Cancer Biology, Laboratory Animal Center, The Fourth Military Medical University, Xi'an, Shaanxi, 710032, PR China.
Xiaowu WangDepartment of Cardiovascular Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, PR China. 1774754900@qq.com.
Yongbin ZhangAnimal Laboratory Center, Guangzhou University of Chinese Medicine, Guangzhou, 510405, PR China. yongbinzhang@gzucm.edu.cn.
Changhong ShiDivision of Cancer Biology, Laboratory Animal Center, The Fourth Military Medical University, Xi'an, Shaanxi, 710032, PR China. changhong@fmmu.edu.cn.

Funding

Laboratory Animal Foundation Program SYDW_KY 2021-14National Natural Science Foundation of China 32070532 and 32270566Shaanxi Province Innovation Capability Support Plan 2022PT-38
6 · The paper itself

Abstract

backgroundThe emergence of targeted therapies and immunotherapy has broadened treatment options for patients with pancreatic ductal adenocarcinoma (PDAC). Despite this, traditional drug selection, predominantly relies on tumor markers and clinical staging, has underutilized these drugs due to ignoring patient genomic diversity. Patient-derived organoids (PDOs) and corresponding patient-derived organoid xenograft (PDOX) models offer a way to better understand and address this.

methodsIn this study, we established PDOs and PDOX models from PDAC clinical samples. These models were analyzed using immunohistochemistry, H&E staining, and genomic profiling. Drug screening with 111 FDA-approved drugs was performed on PDOs, and drug responses in PDOs and PDOX models were compared to assess consistency with clinical treatment outcomes. Gene analysis was conducted to explore the molecular mechanisms underlying variations in drug responses. Additionally, by analyzing the sequencing results from various drug-sensitive groups, the identified differential gene-drug metabolism gene UGT1A10 were modulated in PDOs to evaluate its impact on drug efficacy. A co-culture system of PDOs with immune cells was developed to study the efficacy of immunotherapies.

resultsPDOs and matched PDOX models retain the morphological, biological, and genomic characteristics of the primary tumor. Exome sequencing and RNA sequencing confirmed both the consistency and heterogeneity among the PDOs. High-throughput drug screening revealed significant variability in drug sensitivity across different organoids, yet PDOs and PDOX derived from the same patient exhibited a high degree of concordance in response to clinical chemotherapy agents. The gene expression analysis of PDOs with significant differences in drug sensitivity revealed UGT1A10 as a crucial regulator. The knockdown of UGT1A10 notably increased drug sensitivity. Furthermore, immune cells demonstrated specific cytotoxicity towards the organoids, underscoring the potential of the co-culture system for application in tumor immunotherapy.

conclusionOur results highlight the necessity for personalized treatment strategies that consider genomic diversity beyond tumor markers, thus validating the utility of PDOs and PDOX models in advancing PDAC research and personalized medicine.

Indexed as

Carcinoma, Pancreatic DuctalOrganoidsPancreatic NeoplasmsPrecision MedicineAnimalsFemaleHumansImmunotherapyMiceXenograft Model Antitumor AssaysGenomic diversityImmunotherapyPancreatic ductal adenocarcinoma (PDAC)Patient-derived organoids (PDOs)Personalized treatment

Identifiers

PMID40001264
PMCPMC11863571

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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.