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. 2011 Jan;120(1):113-20.
doi: 10.1016/j.ygyno.2010.09.019. Epub 2010 Nov 6.

Distinctive DNA methylation patterns of cell-free plasma DNA in women with malignant ovarian tumors

Thomas E Liggett  1 , Anatoliy Melnikov, Qilong Yi, Charles Replogle, Wei Hu, Jacob Rotmensch, Aparna Kamat, Anil K Sood, Victor Levenson
Affiliations

Distinctive DNA methylation patterns of cell-free plasma DNA in women with malignant ovarian tumors

Thomas E Liggett et al. Gynecol Oncol. 2011 Jan.

Abstract

Objective: Epithelial ovarian carcinoma (OvCa) is rarely detected early, and it is also difficult to determine whether an adnexal mass is benign or malignant. Previously, we noted differences in methylation patterns of cell-free plasma DNA (cfpDNA) in women without disease compared to patients with OvCa. In this work, we investigated whether methylation patterns of cfpDNA can differentiate between benign and malignant tumors.

Methods: Methylation patterns in cfpDNA were determined in three cohorts (30 samples each) using a microarray-based assay (MethDet 56). Principal component analysis, supervised clustering, linear discrimination analysis, and 25 rounds of 5-fold cross-validation were used to determine informative genes and assess the sensitivity and specificity of differentiating between OvCa vs. healthy control (HC), benign ovarian disease (mostly serous cystadenoma, BOD) vs. HC, and OvCa vs. BOD samples.

Results: Differential methylation of three promoters (RASSF1A, CALCA, and EP300) differentiated between OvCa vs. HC with a sensitivity of 90.0% and a specificity of 86.7%. Three different promoters (BRCA1, CALCA, and CDKN1C) were informative for differentiating between BOD vs. HC, with a sensitivity of 90.0% and a specificity of 76.7%. Finally, two promoters (RASSF1A and PGR-PROX) were informative for differentiating between OvCa vs. BOD, with a sensitivity of 80.0% and a specificity of 73.3%.

Conclusions: This proof-of-principle data show that differential methylation of promoters in cfpDNA may be a useful biomarker to differentiate between certain benign and malignant ovarian tumors.

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Figures

Figure 1
Figure 1. Comparisons between ovarian serous carcinoma and healthy controls
A) Unsupervised principal component analysis; B) hierarchical clustering; C) Supervised linear discrimination analysis coupled with cross validation were used to determine informative genes; D) Sensitivity (Bold upper left) and specificity (Bold lower right).
Figure 2
Figure 2. Comparisons between benign ovarian disease and healthy controls
A) Unsupervised principal component analysis; B) hierarchical clustering; C) Supervised linear discrimination analysis coupled with cross validation were used to determine informative genes; D) Sensitivity (Bold upper left) and specificity (Bold lower right).
Figure 3
Figure 3. Comparisons between benign ovarian disease and ovarian serous carcinoma
A) Unsupervised principal component analysis; B) hierarchical clustering; C) Supervised linear discrimination analysis coupled with cross validation were used to determine informative genes; D) Sensitivity (Bold upper left) and specificity (Bold lower right).
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