Download Integration of DNA Methylation and RNA Expression Data for

Integration of DNA Methylation and RNA Expression Data for Identification of Novel
Epigenetically Deregulated Biomarker Candidates for Prostate Cancer
Jacobsen MN1, Haldrup C1, Høyer S2, Borre M3, Ørntoft TF1, Sørensen KD1
1
Molekylær Medicinsk Afdeling, Aarhus Universitetshospital, Palle Juul-Jensens Boulevard 99, 8200 Aarhus N
2
Patologisk Institut, Aarhus Universitetshospital, Nørrebrogade 44, 8000 Aarhus C
3
Urinvejskirurgisk afdeling K, Aarhus Universitetshospital, Palle Juul-Jensens Boulevard 99, 8200 Aarhus N
Prostate cancer (PC) is the most common cancer amongst men in Western countries. Some PCs remain
latent and never cause any clinical symptoms or risk of morbidity within the lifetime of the patients,
whereas other PCs are aggressive and associated with high mortality. Due to limitations of the currently
available diagnostic and prognostic tools, overdiagnosis and overtreatment of PC has become a major
issue. Therefore, novel diagnostic and/or prognostic biomarkers for PC are urgently needed.
During cancer development and progression, the gene expression of several genes is altered, allowing
the cancer cells to acquire oncogenic capabilities. DNA methylation of promoter regions can affect
gene expression and in PC, DNA methylation has been extensively studied as a novel biomarker.
In this project, we used matching DNA methylation (Illumina 450K DNA methylation array) and gene
expression (RNAseq) data from a set of microdissected nonmalignant (n=15) and tumor (n=29) tissue
specimens from PC patients treated by radical prostatectomy, to identify novel diagnostic biomarkers
for PC, with a significant change in both DNA methylation and gene expression. Five diagnostic top
candidate genes were initially selected. The cancer-specific change in gene expression of each
candidate was validated in two public RNA expression datasets containing both tumor (n=61 and
n=126, respectively) and nonmalignant prostate samples (n=34 and n=29, respectively) (AUCs: 0.740.81 and 0.66-0.93, respectively). Finally, our two top candidates genes were selected for functional
studies in prostate cell lines. A Sleeping Beauty transposon system was used to generate prostate cell
lines with a stable integration of short hairpin RNAs targeting each of these candidate genes. These
newly generated stable cell lines will be used to investigate the function of our two candidate genes in
PC development and/or progression.