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OMICS: A Journal of Integrative Biology
Liver Tumors in Wild Flatfish: A Histopathological, Proteomic, and Metabolomic Study

To cite this article:
G.D. Stentiford, M.R. Viant, D.G. Ward, P.J. Johnson, A. Martin, Wei Wenbin, H.J. Cooper, B.P. Lyons, S.W. Feist. OMICS: A Journal of Integrative Biology. Fall 2005, 9(3): 281-299. doi:10.1089/omi.2005.9.281.

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Dr. G.D. Stentiford
CEFAS Weymouth Laboratory, Dorset United Kingdom.
M.R. Viant
School of Biosciences, University of Birmingham, Birmingham United Kingdom.
D.G. Ward
Cancer Research UK, Institute for Cancer Studies, University of Birmingham, Birmingham United Kingdom.
P.J. Johnson
Cancer Research UK, Institute for Cancer Studies, University of Birmingham, Birmingham United Kingdom.
A. Martin
Cancer Research UK, Institute for Cancer Studies, University of Birmingham, Birmingham United Kingdom.
Wei Wenbin
Cancer Research UK, Institute for Cancer Studies, University of Birmingham, Birmingham United Kingdom.
H.J. Cooper
School of Biosciences, University of Birmingham, Birmingham United Kingdom.
B.P. Lyons
CEFAS Weymouth Laboratory, Dorset United Kingdom.
S.W. Feist
CEFAS Weymouth Laboratory, Dorset United Kingdom.

Fish play host to viral, bacterial, and parasitic diseases in addition to non-infectious conditions such as cancer. The National Marine Monitoring Programme (NMMP) provides information to the U.K. Government on the health status of marine fish stocks. An aspect of this work relates to the presence of tumors and other pathologies in the liver of the offshore sentinel flatfish species, dab (Limanda limanda). Using internationally agreed quality assurance criteria, tumors and pre-tumors are diagnosed using histopathology. The current study has expanded upon this work by integrating these traditional diagnostic approaches with ones utilizing modern technologies for analysis of proteomic and metabolomic profiles of selected lesions. We have applied SELDI and FT-ICR technologies (for proteomic and metabolomic analyses, respectively) to tumor and non-tumor samples resected from the liver of dab. This combined approach has demonstrated how these technologies are able to identify protein and metabolite profiles that are specific to liver tumors. Using histopathology to classify "analysis groups" is key to the success of such an approach since it allows for elimination of spurious samples (e.g., those containing parasite infections) that may confuse interpretation of "omic" data. As such, the pathology laboratory plays a central role in collating information relating to particular specimens and in establishing sampling groups relative to specific diagnostic questions. In this study, we present pilot data, which illustrates that proteomics and metabolomics can be used to discriminate fish liver tumors and suggest future directions for work of this type.

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