Evidence map›Paper›PMID 41800306›Full record

ArticleFrontiers in veterinary science2026

Beyond bacteria: large agents with analogies to Mimiviruses detected in canine cancers: reexamining Gram staining in cancer diagnostics.

Elena Angela Lusi, Federico Caicci, Viola Zappone, Marco Quartuccio, Ilaria Dragà, Antonio Ieni, Cornelia Mannarino, Giuseppe Mazzullo, Claudia Rifici

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

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0citing papers in PubMed
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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

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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

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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

9 authors.

Elena Angela LusiSt Vincent Health Care Group-UCD, Dublin, Ireland.
Federico CaicciDepartment of Biology, Electron Microscopy Unit, University of Padua, Padua, Italy.
Viola ZapponeDepartment of Veterinary Sciences, University of Messina, Messina, Italy.
Marco QuartuccioDepartment of Veterinary Sciences, University of Messina, Messina, Italy.
Ilaria DragàDepartment of Veterinary Sciences, University of Messina, Messina, Italy.
Antonio IeniDepartment of Human Pathology in Adult and Developmental Age "Gaetano Barresi", Section of Pathology, University of Messina, Messina, Italy.
Cornelia MannarinoDepartment of Veterinary Sciences, University of Messina, Messina, Italy.
Giuseppe MazzulloDepartment of Veterinary Sciences, University of Messina, Messina, Italy.
Claudia RificiDepartment of Veterinary Sciences, University of Messina, Messina, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While Gram staining is traditionally used for classifying bacteria based on their cell wall properties, Mimiviruses and large mammalian agents can also retain the Gram stain, despite not being typical bacteria. In fact, Mimivirus-like agents that exhibit Gram-positive staining were first found in human tissues, particularly in malignant samples, suggesting that these agents may be involved in a unique carcinogenic process. In order to translate the findings published in human medicine to animal models, we evaluated for the first time the presence of analogous Gram-positive agents in canine malignancies and differentiate them from traditional bacteria. Using Gram staining, we analyzed 35 canine tumors across various malignancy types, including 7 sarcomas, 15 carcinomas, and 13 round cell tumors such as mast cell tumors, transmissible venereal tumors and melanomas. Normal tissues and bacteria were used as controls. We were able to identify Gram-positive granulations, exhibiting intracytoplasmic, intra-nuclear and perinuclear patterns, measuring 1-2 μm that were distinct from traditional bacteria. This study, the first of its kind in the veterinary literature, supports comparable published findings in human research and advances our knowledge of the pathophysiology of cancer across species.

Indexed as

canine cancerGram staininghuman cancerMimivirus-like agentoncogenic agent

Identifiers

PMID41800306
PMCPMC12964367

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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.