Evidence map›Paper›PMID 42029803›Full record

ReviewMolecular biotechnology2026

Research Advances in Multi-tissue Organoid Models Based on PBMCs.

Dongyang He, Yicheng Feng, Xiao An

Abstract readReview
PubMed Publisher
In one paragraph

Review in Molecular biotechnology, 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. 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

3 authors.

Dongyang HeShanghai General Hospital, Shanghai Jiao Tong University School of Medicine, No. 100 Haining Road, Shanghai, 200080, China.ORCID http://orcid.org/0009-0008-7900-8043
Yicheng FengShanghai General Hospital, Shanghai Jiao Tong University School of Medicine, No. 100 Haining Road, Shanghai, 200080, China.
Xiao AnShanghai General Hospital, Shanghai Jiao Tong University School of Medicine, No. 100 Haining Road, Shanghai, 200080, China. drxiaoan@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Organoids, as three-dimensional in vitro culture models, closely recapitulate the architectural, cellular, and functional characteristics of their in vivo counterparts. Consequently, they play a pivotal role in diverse biomedical fields, including disease modeling, drug screening, and regenerative medicine. However, conventional organoid models often lack a complex native microenvironment, specifically the tumor microenvironment (TME), which limits their utility in studying immune-related pathologies and evaluating immunotherapeutic strategies. Peripheral blood mononuclear cells (PBMCs) offer distinct advantages, including accessibility, a heterogeneous composition of immune cells, and the capacity to mirror a patient's specific immune status. As a result, PBMCs have emerged as a predominant source of immune cells for engineering immune-integrated organoid models. This article reviews recent advancements in integrating PBMCs into various tissue organoid systems. It summarizes the key biological properties of PBMCs and their applications across multiple models, including cerebral, renal, pulmonary, and hepatic organoids. Furthermore, this study compares the advantages and limitations of current modeling methodologies and discusses future research directions and persistent challenges in leveraging PBMC-integrated organoids for personalized medicine and the elucidation of disease mechanisms.

Indexed as

Leukocytes, MononuclearModels, BiologicalOrganoidsAnimalsCell Culture TechniquesHumansPrecision MedicineTissue EngineeringTumor MicroenvironmentIntegrated immune modelOrganoidsPBMCsTumor microenvironment

Identifiers

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.