Evidence map›Paper›PMID 39412757›Full record

ArticleClinical cancer research : an official journal of the American Association for Cancer Research2024

Large-Scale Comparative Analysis of Canine and Human Osteosarcomas Uncovers Conserved Clinically Relevant Tumor Microenvironment Subtypes.

Sushant Patkar, Joshua Mannheimer, Stephanie A Harmon, Christina J Ramirez, Christina N Mazcko, Peter L Choyke, Gregory Thomas Brown, Baris Turkbey, Amy K LeBlanc, Jessica A Beck

Abstract readComparative Study
In one paragraph

Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Trial
  2. Review
  3. Integrated Multiomic Profiling Enhances Risk Stratification and Prognostication in Canine Osteosarcoma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026
    Article
  4. Review
  5. Article
  6. Review
  7. Combined radiation andMolecular therapy. Oncology · 2026
    Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. NFATC3 enhances osteosarcoma progression by increasing PD-L1 and CXCL2 levels.Medical oncology (Northwood, London, England) · 2025
    Article
  16. Spatial Transcriptomics Advances the Use of Canine Patients in Cancer Research: Analysis of Osteosarcoma-Bearing Pet Dogs Enrolled in a Clinical Trial.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025
    Article
  17. Review
  18. Article
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  20. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Sushant PatkarArtificial Intelligence Resource, Molecular Imaging Branch, National Cancer Institute, NIH, Bethesda, Maryland.ORCID 0000-0002-5877-0599
Joshua MannheimerPfizer Inc., Andover, Massachusetts.ORCID 0009-0006-0527-1805
Stephanie A HarmonArtificial Intelligence Resource, Molecular Imaging Branch, National Cancer Institute, NIH, Bethesda, Maryland.ORCID 0000-0002-2507-2399
Christina J RamirezMolecular Histopathology Laboratory, Laboratory of Animal Sciences Program, Frederick National Laboratory for Cancer Research, Frederick, Maryland.ORCID 0009-0008-7280-2316
Christina N MazckoComparative Oncology Program, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, Maryland.ORCID 0000-0002-2543-7781
Peter L ChoykeArtificial Intelligence Resource, Molecular Imaging Branch, National Cancer Institute, NIH, Bethesda, Maryland.ORCID 0000-0003-1086-8826
Gregory Thomas BrownArtificial Intelligence Resource, Molecular Imaging Branch, National Cancer Institute, NIH, Bethesda, Maryland.ORCID 0000-0001-7383-3116
Baris TurkbeyArtificial Intelligence Resource, Molecular Imaging Branch, National Cancer Institute, NIH, Bethesda, Maryland.ORCID 0000-0003-0853-6494
Amy K LeBlancComparative Oncology Program, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, Maryland.ORCID 0000-0001-7656-9859
Jessica A BeckComparative Oncology Program, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, Maryland.ORCID 0000-0002-0145-7606

Funding

DNA TOPOISOMERASES AS TARGET OF ACTION OF ANTICANCER DRUGSZ01BC006161 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI POMMIER, YVES · 1996 to 2008
$1.5M
Intramural NIH HHS Z01 BC006161National Institutes of Health (NIH) Z01-BC006161
6 · The paper itself

Abstract

purposeOsteosarcoma is an aggressive bone cancer lacking robust biomarkers for personalized treatment. Despite its scarcity in humans, it is relatively common in adult pet dogs. This study aimed to analyze clinically annotated bulk tumor transcriptomic datasets of canine and patients with human osteosarcoma to identify potentially conserved patterns of disease progression. EXPERIMENTAL

designBulk transcriptomic data from 245 pet dogs with treatment-naïve appendicular osteosarcoma were analyzed using deconvolution to characterize the tumor microenvironment (TME). The TME of both primary and metastatic tumors derived from the same dog was compared, and its impact on canine survival was assessed. A machine learning model was developed to classify the TME based on its inferred composition using canine tumor data. This model was applied to eight independent human osteosarcoma datasets to assess its generalizability and prognostic value.

resultsThis study found three distinct TME subtypes of canine osteosarcoma based on cell type composition of bulk tumor samples: immune enriched, immune enriched dense extracellular matrix-like, and immune desert. These three TME-based subtypes of canine osteosarcomas were conserved in humans and could predict progression-free survival outcomes of human patients, independent of conventional prognostic factors such as percent tumor necrosis post standard of care chemotherapy treatment and disease stage at diagnosis.

conclusionsThese findings demonstrate the potential of leveraging data from naturally occurring cancers in canines to model the complexity of the human osteosarcoma TME, offering a promising avenue for the discovery of novel biomarkers and developing more effective precision oncology treatments.

Indexed as

Bone NeoplasmsOsteosarcomaTumor MicroenvironmentAnimalsBiomarkers, TumorDog DiseasesDogsFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMachine LearningMalePrognosisTranscriptomeBiomarkers, Tumor

Identifiers

PMID39412757
PMCPMC11647208

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.