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Identification of Novel Epigenetic Markers of Prostate Cancer by NotI-Microarray Analysis

Dmitriev, AA (author)
Rosenberg, EE (author)
Krasnov, GS (author)
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Gerashchenko, GV (author)
Gordiyuk, VV (author)
Pavlova, TV (author)
Karolinska Institutet
Kudryavtseva, AV (author)
Beniaminov, AD (author)
Belova, AA (author)
Bondarenko, YN (author)
Danilets, RO (author)
Glukhov, AI (author)
Kondratov, AG (author)
Alexeyenko, A (author)
Karolinska Institutet
Alekseev, BY (author)
Klein, G (author)
Karolinska Institutet
Senchenko, VN (author)
Kashuba, VI (author)
Karolinska Institutet
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 (creator_code:org_t)
Hindawi Limited, 2015
2015
English.
In: Disease markers. - : Hindawi Limited. - 1875-8630 .- 0278-0240. ; 2015, s. 241301-
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • A significant need for reliable and accurate cancer diagnostics and prognosis compels the search for novel biomarkers that would be able to discriminate between indolent and aggressive tumors at the early stages of disease. The aim of this work was identification of potential diagnostic biomarkers for characterization of different types of prostate tumors. NotI-microarrays with 180 clones associated with chromosome 3 genes/loci were applied to determine genetic and epigenetic alterations in 33 prostate tumors. For 88 clones, aberrations were detected in more than 10% of tumors. The major types of alterations were DNA methylation and/or deletions. Frequent methylation of the discovered loci was confirmed by bisulfite sequencing on selective sampling of genes:FGF12,GATA2, andLMCD1. Three genes (BHLHE40,BCL6, andITGA9) were tested for expression level alterations using qPCR, and downregulation associated with hypermethylation was shown in the majority of tumors. Based on these data, we proposed the set of potential biomarkers for detection of prostate cancer and discrimination between prostate tumors with different malignancy and aggressiveness:BHLHE40,FOXP1,LOC285205,ITGA9,CTDSPL,FGF12,LOC440944/SETD5,VHL,CLCN2,OSBPL10/ZNF860,LMCD1,FAM19A4,CAND2,MAP4,KY, andLRRC58. Moreover, we probabilistically estimated putative functional relations between the genes within each set using the network enrichment analysis.

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