Evidence map›Paper›PMID 41012744›Full record

ReviewVeterinary sciences2025

Advancing In Vitro Tools for Oncologic Research in Cats and Dogs.

Chang He, Sven Rottenberg

Abstract readReview
In one paragraph

Review in Veterinary sciences, 2025. 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

2 authors.

Chang HeInstitute of Animal Pathology, Vetsuisse Faculty, University of Bern, 3012 Bern, Switzerland.ORCID 0009-0003-8464-2392
Sven RottenbergInstitute of Animal Pathology, Vetsuisse Faculty, University of Bern, 3012 Bern, Switzerland.ORCID 0000-0003-2044-9844

Funding

Department of Defense W81XWH-22-1-0557European Union ERC-2019-AdG-883877Everycat Foundation EC24F-229ISREC Foundation NASwiss Cancer Research Foundation KFS-5519-02-2022Swiss National Science Foundation 320030M_219453
6 · The paper itself

Abstract

In vitro culture systems have advanced cancer biology, particularly through 2D and 3D tumor cultures. These have answered numerous scientific inquiries and propelled human oncologic research, with growing recognition of their potential to improve cancer treatment in companion animals, specifically cats and dogs. These species develop cancer spontaneously, closely resembling specific human cancer subtypes. For example, canine and feline mammary tumors are especially valuable for studying tumor biology. In vitro models from these tumors therefore offer a unique opportunity for veterinary cancer research. Recent 3D cell culture advancements provide promising platforms for predicting therapeutic responses in human cancer and may be applied to mammary tumors in animals. However, while limitations in fully recapitulating in vivo conditions and predicting chemotherapy response have been observed in colorectal tumoroids, similar challenges are emerging in mammary and breast tumors. In particular, canine mammary tumors and human breast cancers share critical heterogeneity and microenvironmental factors usually inadequately modeled in vitro. This review critically examines the predictivity of 3D mammary tumoroids from humans and companion animals, highlighting challenges related to stromal and immune cell preservation, reproducibility, and the translational gap between in vitro findings and clinical outcomes. We propose future directions to optimize these models for both comparative oncology and veterinary-specific applications.

Indexed as

3D culture systemscancer biologycatcomparative oncologydogin vitro modelmammary tumortranslational medicine

Identifiers

PMID41012744
PMCPMC12474302

What OpenQuestion holds

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LicenceCC BY
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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.