ReviewVeterinary sciences2023
Molecular Profile of Canine Hemangiosarcoma and Potential Novel Therapeutic Targets.
Review in Veterinary sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- NMR Metabolomics in Veterinary Medicine: From Biomarker Discovery to Clinical Implementation.Veterinary sciences · 2026Review
- Primary Hepatic Hemangiosarcoma With Hemoperitoneum in a Dog: Clinical Course and Therapeutic Outcome.Case reports in veterinary medicine · 2026Article
- Editorial: Advancements and challenges in veterinary oncology.Frontiers in veterinary science · 2026Article
- MicroRNA differential expression analysis in canine visceral hemangiosarcoma formalin-fixed, paraffin-embedded tissues.Frontiers in veterinary science · 2026Article
- A Review on Canine and Human Soft Tissue Sarcomas: New Insights on Prognosis Factors and Treatment Measures.Veterinary sciences · 2024Review
- Diagnosis of Canine Tumours and the Value of Combined Detection of VEGF, P53, SF and NLRP3 for the Early Diagnosis of Canine Mammary Carcinoma.Animals : an open access journal from MDPI · 2024Article
- Tumor Immune Microenvironment and Its Clinicopathological and Prognostic Associations in Canine Splenic Hemangiosarcoma.Animals : an open access journal from MDPI · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Canine hemangiosarcoma (HSA) is a relatively common neoplasia, occurring mainly in the skin, spleen, liver and right atrium. Despite the numerous studies investigating the treatment of canine HSA, no significant improvement in survival has been achieved in the last 20 years. Advancements in genetic and molecular profiling presented molecular similarities between canine HSA and human angiosarcoma. It could therefore serve as a valuable model for investigating new and more effective treatments in people and dogs. The most common genetic abnormalities in canine HSA have been found in the phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) and neuroblastoma RAS viral oncogene homolog (NRAS) pathways. Mutations are also found in tumor protein p53 (TP53), phosphatase and tensin homolog (PTEN) and cyclin dependent kinase inhibitor 2A (CDKN2A). Known abnormal protein expression could be exploited to trial new target treatments that could be beneficial for both canine and human patients. Despite the high expression of vascular endothelial growth factor (VEGF) and its receptor (VEGFR), no correlation with overall survival time has ever been found. In this review, we explore the most recent developments in molecular profiling in canine HSA and discuss their possible applications in the prognosis and treatment of this fatal disease.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.