PAI-1 −675 4G/5G polymorphism as a prognostic biomarker in breast cancer View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2007-07-07

AUTHORS

Haixin Lei, Kari Hemminki, Robert Johansson, Andrea Altieri, Kerstin Enquist, Roger Henriksson, Per Lenner, Asta Försti

ABSTRACT

Extracellular matrix degradation, mediated by the urokinase plasminogen activation (uPA) system, is a critical step in tumor invasion and metastasis. High tumor levels of uPA and its inhibitor PAI-1 have been correlated with poor prognosis in breast cancer. We examined whether genetic variation in the genes of the uPA system affect breast cancer susceptibility and prognosis. We genotyped eight potentially functional single nucleotide polymorphisms (SNPs) in six genes of the uPA system in 959 Swedish breast cancer patients with detailed clinical data and up to 15 years of follow-up together with 952 matched controls. We used the unconditional logistic regression models to evaluate the associations between genotypes and breast cancer risk and tumor characteristics. The Kaplan-Meier method was used to estimate the survival probabilities; the log-rank test was used to test differences between subgroups. None of the SNPs conferred an increased breast cancer risk, but correlation with some traditional prognostic factors was observed for several SNPs. Most importantly, we identified the -675 4G/5G SNP in the PAI-1 gene as a promising prognostic biomarker for breast cancer. Compared to the 4G/4G and 4G/5G genotypes 5G/5G homozygosity correlated significantly with worse survival (RR 2.04, 95% CI 1.45–2.86, P < 0.001), especially in patients with more aggressive tumors. 5G/5G homozygotes were also the group with worse survival among lymph node negative cases. Our finding suggests that genotyping PAI-1 -675 4G/5G may help in clinical prognosis of breast cancer. More... »

PAGES

165-175

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10549-007-9635-3

DOI

http://dx.doi.org/10.1007/s10549-007-9635-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1028293650

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/17616807


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