Evidence map›Paper›PMID 30514258›Full record

ArticleBMC cancer2018

Isolation and characterization of two canine melanoma cell lines: new models for comparative oncology.

Zacharie Segaoula, Aline Primot, Frederic Lepretre, Benoit Hedan, Emmanuel Bouchaert, Kevin Minier, Laurent Marescaux, François Serres, Sylvie Galiègue-Zouitina, Catherine André and 3 more

Open access · goldAbstract readComparative Study
In one paragraph

Article in BMC cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.5field-weighted citation impact, top 16% of its field
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

14 citing papers in PubMed, 25 citations in OpenAlex.

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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

13 authors at 5 institutions in 2 countries.

Zacharie SegaoulaUniversity of Lille, Inserm, CHU Lille, UMR-S 1172 - JPArc - Jean-Pierre AUBERT Research Centre of Neuroscience and Cancer, F-59000, Lille, France.
Aline PrimotCNRS-University of Rennes 1, UMR 6290, Institute of Genetique and Development of Rennes, Faculty of Medicine, SFR Biosit, Rennes, France.
Frederic LepretreFunctional Genomic Platform, Univ. Lille, F-59000, Lille, France.
Benoit HedanCNRS-University of Rennes 1, UMR 6290, Institute of Genetique and Development of Rennes, Faculty of Medicine, SFR Biosit, Rennes, France.
Emmanuel BouchaertOCR (Oncovet Clinical Research), SIRIC ONCOLille, Parc Eurasante, Rue du Dr Alexandre Yersin, F-59120, Loos, France.
Kevin MinierOncovet Cancer Centre, Avenue Paul Langevin, 59650, Villeneuve d'Ascq, France.
Laurent MarescauxOncovet Cancer Centre, Avenue Paul Langevin, 59650, Villeneuve d'Ascq, France.
François SerresOCR (Oncovet Clinical Research), SIRIC ONCOLille, Parc Eurasante, Rue du Dr Alexandre Yersin, F-59120, Loos, France.
Sylvie Galiègue-ZouitinaUniversity of Lille, Inserm, CHU Lille, UMR-S 1172 - JPArc - Jean-Pierre AUBERT Research Centre of Neuroscience and Cancer, F-59000, Lille, France.
Catherine AndréCNRS-University of Rennes 1, UMR 6290, Institute of Genetique and Development of Rennes, Faculty of Medicine, SFR Biosit, Rennes, France.
Bruno QuesnelUniversity of Lille, Inserm, CHU Lille, UMR-S 1172 - JPArc - Jean-Pierre AUBERT Research Centre of Neuroscience and Cancer, F-59000, Lille, France.
Xavier ThuruUniversity of Lille, Inserm, CHU Lille, UMR-S 1172 - JPArc - Jean-Pierre AUBERT Research Centre of Neuroscience and Cancer, F-59000, Lille, France.
Dominique TiernyOCR (Oncovet Clinical Research), SIRIC ONCOLille, Parc Eurasante, Rue du Dr Alexandre Yersin, F-59120, Loos, France. dtierny@oncovet-clinical-research.com.ORCID http://orcid.org/0000-0001-5192-6813
Centre National de la Recherche Scientifique · FRInserm · FROnco Lille · FRNational Cancer Centre Japan · JPUniversité de Lille · FR

Funding

Association Nationale de la Recherche et de la Technologie (FR) CIFRE N 2013/1203Oncovet Clinical Research CPR2014/08/27
6 · The paper itself

Abstract

backgroundMetastatic melanoma is one of the most aggressive forms of cancer in humans. Among its types, mucosal melanomas represent one of the most highly metastatic and aggressive forms, with a very poor prognosis. Because they are rare in Caucasian individuals, unlike cutaneous melanomas, there has been fewer epidemiological, clinical and genetic evaluation of mucosal melanomas. Moreover, the lack of predictive models fully reproducing the pathogenesis and molecular alterations of mucosal melanoma makes its treatment challenging. Interestingly, dogs are frequently affected by melanomas of the oral cavity that are characterized, as their human counterparts, by focal infiltration, recurrence, and metastasis to regional lymph nodes, lungs and other organs. In dogs, some particular breeds are at high risk, suggesting a specific genetic background and strong genetic drivers. Altogether, the striking homologies in clinical presentation, histopathological features, and overall biology between human and canine mucosal melanomas make dogs invaluable natural models with which to investigate tumor development, including tumor ætiology, and develop tailored treatments.

methodsWe developed and characterized two canine oral melanoma cell lines from tumors isolated from dog patients with distinct clinical profiles; with and without lung metastases. The cells were characterized using immunohistochemistry, pharmacology and genetic studies.

resultsWe have developed and immunohistochemically, genetically, and pharmacologically characterized. Two cell lines (Ocr_OCMM1X & Ocr_OCMM2X) were produced through mouse xenografts originating from two clinically contrasting melanomas of the oral cavity. Their exhaustive characterization showed two distinct biological and genetic profiles that are potentially linked to the stage of malignancy at the time of diagnosis and sample collection of each melanoma case. These cell lines thus constitute relevant tools with which to perform genetic and drug screening analyses for a better understanding of mucosal melanomas in dogs and humans.

conclusionsThe aim of this study was to establish and characterize xenograft-derived canine melanoma cell lines with different morphologies, genetic features and pharmacological sensitivities that constitute good predictive models for comparative oncology. These cell lines are relevant tools to advance the use of canine mucosal melanomas as natural models for the benefit of both veterinary and human medicine.

Indexed as

AnimalsAntineoplastic AgentsCell Line, TumorCutaneous Malignant MelanomaDogsDose-Response Relationship, DrugFemaleHumansMelanomaMiceMice, NudeMouth NeoplasmsSkin NeoplasmsTumor Cells, CulturedXenograft Model Antitumor AssaysAntineoplastic AgentsCancerCell linesComparative oncologyDogMelanomaPreclinical models

Identifiers

PMID30514258
PMCPMC6280433
OpenAlexW2903099422

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.