Evidence map›Paper›PMID 42840631›Full record

ReviewFrontiers in oncology2026

Tumor organoids for testing metabolic flexibility in precision oncology.

Di Hao, Yijie Ren, Hui Zhang

Abstract readReview
In one paragraph

Review in Frontiers in oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Di HaoGraduate School of China Academy of Chinese Medical Sciences, Suzhou, China.
Yijie RenCrown Bioscience Inc., San Diego, CA, United States.
Hui ZhangAffiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tumors adapt their metabolism to fluctuating nutrients, hypoxia, stromal interactions, immune pressure, and treatment. Tumor organoids are attractive systems in which to test this flexibility, but existing reviews have largely emphasized organoid applications, physiologic culture conditions or metabolomics workflows rather than the strength of evidence behind individual metabolic claims. Here, we address a narrower problem: which metabolic properties of a patient tumor are directly retained or recreated in organoid culture? We evaluate organoid evidence using three levels of support: direct metabolic measurements and perturbation in organoids, biological mechanisms established in other models that require organoid validation, and translational associations that require prospective clinical testing. Recent studies provide direct advances in pancreatic cancer organoids, including subtype-specific oxidative and glycolytic states, KRAS-associated cholesterol dependence and hypoxia-driven invasion, and in gastric and colorectal models where engineered co-cultures expose niche-dependent lipid or immune responses. These findings also expose a central gap: matched benchmarking of organoid metabolic flux and spatial heterogeneity against native tumors remains uncommon. We propose a validation framework based on physiologically specified environments, spatial and isotope-resolved measurements, multi-compartment co-culture and prospective linkage of functional readouts to patient outcomes. Tumor organoids can therefore advance cancer metabolism most credibly as tested, context-specific models rather than assumed replicas of metabolic flexibility

Indexed as

cancer metabolismmetabolic flexibilitymetabolic heterogeneitypatient-derived modelsprecision oncologytumor microenvironmenttumor organoids

Identifiers

PMID42840631
PMCPMC13640303

What OpenQuestion holds

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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.