Open AccessHypermethylation of Tumor Suppressor Genes Involved in Critical Regulatory Pathways for Developing a Blood-Based Test in Breast Cancer
Author(s) -
Ramin Radpour,
Zeinab Barekati,
Corina Kohler,
Qing Lv,
Nicole Bürki,
Claude Diesch,
Johannes Bitzer,
Hong Zheng,
Seraina Schmid,
Xiao Yan Zhong
Publication year - 2011
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0016080
Subject(s) - breast cancer , dna methylation , biomarker , epigenetics , cancer , methylation , cpg site , oncology , cancer research , medicine , cohort , biology , pathology , gene , gene expression , genetics
Background Aberrant DNA methylation patterns might be used as a biomarker for diagnosis and management of cancer patients. Methods and Findings To achieve a gene panel for developing a breast cancer blood-based test we quantitatively assessed the DNA methylation proportion of 248 CpG sites per sample (total of 31,248 sites in all analyzed samples) on 10 candidate genes ( APC , BIN1 , BMP6 , BRCA1 , CST6 , ESR-b , GSTP1 , P16 , P21 and TIMP3 ). The number of 126 samples consisting of two different cohorts was used (first cohort: plasma samples from breast cancer patients and normal controls; second cohort: triple matched samples including cancerous tissue, matched normal tissue and serum samples). In the first cohort, circulating cell free methylated DNA of the 8 tumor suppressor genes (TSGs) was significantly higher in patients with breast cancer compared to normal controls ( P <0.01). In the second cohort containing triple matched samples, seven genes showed concordant hypermethylated profile in tumor tissue and serum samples compared to normal tissue ( P <0.05). Using eight genes as a panel to develop a blood-based test for breast cancer, a sensitivity and specificity of more than 90% could be achieved in distinguishing between tumor and normal samples. Conclusions Our study suggests that the selected TSG panel combined with the high-throughput technology might be a useful tool to develop epigenetic based predictive and prognostic biomarker for breast cancer relying on pathologic methylation changes in tumor tissue, as well as in circulation.