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As IFN type I is a suggested key pathogenic factor, we discuss how the currently used mouse models fit with subdividing patients into IFN-positive and IFN-negative subgroups.
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Taken together with our findings of S100A4 overexpression in advanced thyroid tumours, the transgenic mouse model may fit well with human PTC, implicating that S100A4 may enhance thyroid cancer invasion and metastasis in cooperation with c-erbB-2/ neu.
Slim models fit in tight storage.
All models fit the data well.
Thus, both models fit adequately.
Taken together, these results support the notion that better- or best-fit mouse models for human studies can be identified by applying genome-scale comparison of gene expression patterns.
To test this hypothesis, we investigated whether comparison of global expression patterns of orthologous genes in human and mouse HCCs would identify similar and dissimilar tumor phenotypes, and thus allow the identification of the best-fit mouse models for human HCC.
Lee et al. [286] used unsupervised hierarchical clustering of expression data from human and mouse hepatocellular carcinomas to identify the mouse models that provided the best fit for human cancers.
The term mouse models.
S.F. and D.E.B. provided mouse models.
P.J.M. and Z.-Q.W. provided mouse models.
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