Quantitative assessment of DNA hypermethylation in the inflammatory and non-inflammatory breast cancer phenotypes.
In this study, a comparative quantitative methylation profiling of inflammatory breast cancer (IBC) and non-IBC was set up for the identification of tumor-specific methylation patterns. Methylation ratios of six genes (DAPK, TWIST, HIN-1, RASSF1A, RARbeta2 and APC) were measured in benign breast tissues (n = 9) and in tumor samples from non-IBC (n = 81) and IBC (n = 19) patients using quantitative methylation-specific PCR. Median methylation ratios observed in breast cancer (n = 100) were significantly higher than those observed in benign breast tissues for five of six genes (TWIST, HIN-1, RASSF1A, RARbeta2 and APC). Only one of the individual genes studied, RARbeta2, showed differential methylation ratios in IBC and non-IBC (p = 0.016). Using the maximal methylation ratio observed in benign breast tissue as a threshold, the methylation frequency of two genes, RARbeta2 and APC, was significantly increased in IBC (n = 19) when compared to non-IBC (n = 81): 53 vs. 23% for RARbeta2 (p = 0.012) and 84 vs. 54% for APC (p = 0.017). Using hierarchical clustering, methylation patterns could not classify breast cancers according to their phenotype. The finding of differential frequencies of methylation in IBC and non-IBC for two out of six genes suggests that gene-specific patterns of methylation could provide a basis for molecular classification of IBC. Testing for additional genes could help to define the IBC phenotype based on patterns of aberrant gene promoter methylation.
Van der Auwera
Ilse
I
Translational Cancer Research Group, Laboratory of Pathology, University of Antwerp/University Hospital Antwerp, Oncology Centre, General Hospital St-Augustinus, Antwerp, Belgium. ilse.van.der.auwera@telenet.be
Bovie
Catherine
C
Svensson
Cecilia
C
Limame
Ridha
R
Trinh
Xuan B
XB
van Dam
Peter
P
Van Laere
Steven J
SJ
Van Marck
Eric
E
Vermeulen
Peter B
PB
Dirix
Luc Y
LY
D025601:Adenomatous Polyposis Coli Protein / Q000235:genetics; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D051017:Apoptosis Regulatory Proteins / Q000235:genetics; D014408:Biomarkers, Tumor / Q000235:genetics* / Q000378:metabolism; D001940:Breast / Q000378:metabolism / Q000473:pathology*; D001943:Breast Neoplasms / Q000235:genetics* / Q000473:pathology; D017871:Calcium-Calmodulin-Dependent Protein Kinases / Q000235:genetics; D018899:CpG Islands; D016207:Cytokines / Q000235:genetics; D019175:DNA Methylation; D064550:Death-Associated Protein Kinases; D005260:Female; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D007249:Inflammation / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D008875:Middle Aged; D009361:Neoplasm Invasiveness; D009687:Nuclear Proteins / Q000235:genetics; D010641:Phenotype; D016133:Polymerase Chain Reaction; D011379:Prognosis; D011401:Promoter Regions, Genetic / Q000235:genetics; D018168:Receptors, Retinoic Acid / Q000235:genetics; D025521:Tumor Suppressor Proteins / Q000235:genetics; D051879:Twist-Related Protein 1 / Q000235:genetics
D025601:Adenomatous Polyposis Coli Protein; D051017:Apoptosis Regulatory Proteins; D014408:Biomarkers, Tumor; D016207:Cytokines; D009687:Nuclear Proteins; C533416:RARB2 protein, human; C411762:RASSF1 protein, human; D018168:Receptors, Retinoic Acid; C434732:SCGB3A1 protein, human; C103173:TWIST1 protein, human; D025521:Tumor Suppressor Proteins; D051879:Twist-Related Protein 1; D064550:Death-Associated Protein Kinases; D017871:Calcium-Calmodulin-Dependent Protein Kinases