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Ambivalent role of pFAK-Y397 in serous ovarian cancer--a study of the OVCAD consortium.


ABSTRACT:

Background

Focal adhesion kinase (FAK) autophosphorylation seems to be a potential therapeutic target but little is known about the role and prognostic value of FAK and pFAK in epithelial ovarian cancer (EOC). Recently, we validated a gene signature classifying EOC patients into two subclasses and revealing genes of the focal adhesion pathway as significantly deregulated.

Methods

FAK expression and pFAK-Y397 abundance were elucidated by immunohistochemistry and microarray analysis in 179 serous EOC patients. In particular the prognostic value of phosphorylated FAK (pFAK-Y397) and FAK in advanced stage EOC was investigated.

Results

Multiple Cox-regression analysis showed that high pFAK abundance was associated with improved overall survival (HR 0.54; p = 0.034). FAK was positive in a total of 92.2% (n = 165) and high pFAK abundance was found in 36.9% (n = 66). High pFAK abundance (36.9%?; n = 66) was associated with either nodal positivity and/or distant metastasis (p = 0.030). Whole genome gene expression data revealed a connection of the FAK-pFAK-Y397 axis and the mTOR-S6K1 pathway, shown to play a major role in carcinogenesis.

Conclusion

The role of pFAK-Y397 remains controversial: although high pFAK-Y397 abundance is associated with distant and lymph node metastases, it is independently associated with improved overall survival.

SUBMITTER: Aust S 

PROVIDER: S-EPMC3998046 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

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<h4>Background</h4>Focal adhesion kinase (FAK) autophosphorylation seems to be a potential therapeutic target but little is known about the role and prognostic value of FAK and pFAK in epithelial ovarian cancer (EOC). Recently, we validated a gene signature classifying EOC patients into two subclasses and revealing genes of the focal adhesion pathway as significantly deregulated.<h4>Methods</h4>FAK expression and pFAK-Y397 abundance were elucidated by immunohistochemistry and microarray analysis  ...[more]

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