Evidence map›Paper›PMID 41170752›Full record

ReviewCancer reports (Hoboken, N.J.)2025

Mouse Models of Osteosarcoma: Unraveling Disease Mechanisms and Accelerating Drug Discovery and Development.

Staci L Haney, Sarah A Holstein

Abstract readReview
In one paragraph

Review in Cancer reports (Hoboken, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

2 authors.

Staci L HaneyDepartment of Internal Medicine, University of Nebraska Medical Center, Omaha, Nebraska, USA.ORCID 0009-0001-7826-6090
Sarah A HolsteinDepartment of Internal Medicine, University of Nebraska Medical Center, Omaha, Nebraska, USA.ORCID 0000-0002-9342-5635

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOsteosarcoma is the most frequent primary bone malignancy, affecting mainly children, adolescents, and young adults. For the past 40 years, improvements in the survival of patients with osteosarcoma have been minimal, primarily as a consequence of the lack of systemic therapy options beyond traditional cytotoxic agents. In particular, management of metastatic and recurrent disease continues to be a significant clinical challenge. RECENT

findingsMouse models of osteosarcoma serve as a valuable tool to study disease biology, metastasis, and response to novel treatments. In recent years, mouse models have been employed to evaluate the efficacy of several innovative drugs, including nanoparticle formulations that can target drug delivery to osteosarcoma tumor cells and diminish off-target effects. In addition, significant preclinical advancements in immune checkpoint inhibitors and immunotherapies for osteosarcoma have been made with the aid of mouse models.

conclusionThis review provides insight into the advantages and shortcomings of the numerous osteosarcoma mouse models described in the literature, including transgenic, orthotopic, and heterotopic models as well as patient-derived xenografts. We highlight how these models are currently being used to support preclinical studies focused on the development of novel therapies.

Indexed as

Bone NeoplasmsDrug DevelopmentLung NeoplasmsNeoplasms, ExperimentalOsteosarcomaAnimalsAntineoplastic AgentsCell Line, TumorDrug DiscoveryHumansImmune Checkpoint InhibitorsMiceMice, TransgenicOncogene ProteinsTumor Suppressor ProteinsXenograft Model Antitumor AssaysAntineoplastic AgentsImmune Checkpoint InhibitorsOncogene ProteinsTumor Suppressor Proteins

Identifiers

PMID41170752
PMCPMC12576592

What Socratic 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 Socratic graph.