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                  <mods:namePart>Michailidi, Christina</mods:namePart>
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                  <mods:namePart>Soudry, Ethan</mods:namePart>
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                  <mods:namePart>Perez, Jimena</mods:namePart>
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                  <mods:namePart>Yang, Quiang</mods:namePart>
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                  <mods:namePart>Valle, Blanca</mods:namePart>
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                  <mods:namePart>Meltzer, Stephen J.</mods:namePart>
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                  <mods:namePart>Torbenson, Michael</mods:namePart>
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               <mods:name>
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                  <mods:namePart>Esteller, Manel</mods:namePart>
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                  <mods:namePart>Sidransky, David</mods:namePart>
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               <mods:name>
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                  <mods:namePart>Rafael, Guerrero-Preston</mods:namePart>
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                  <mods:dateIssued encoding="iso8601">2018-07-30T09:18:00Z2018-07-30T09:18:00Z2014-04-152018-07-30T09:18:01Z</mods:dateIssued>
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               <mods:abstract>The majority of the epigenomic reports in hepatocellular carcinoma have focused on identifying novel differentially methylated drivers or passengers of the oncogenic process. Few reports have considered the technologies in place for clinical translation of newly identified biomarkers. The aim of this study was to identify epigenomic technologies that need only a small number of samples to discriminate HCC from non-HCC tissue, a basic requirement for biomarker development trials. To assess that potential, we used quantitative Methylation Specific PCR, oligonucleotide tiling arrays, and Methylation BeadChip assays. Concurrent global DNA hypomethylation, gene-specific hypermethylation, and chromatin alterations were observed as a hallmark of HCC. A global loss of promoter methylation was observed in HCC with the Illumina BeadChip assays and the Nimblegen oligonucleotide arrays. HCC samples had lower median methylation peak scores and a reduced number of significant promoter-wide methylated probes. Promoter hypermethylation of RASSF1A, SSBP2, and B4GALT1 quantified by qMSP had a sensitivity ranging from 38% to 52%, a specificity of 100%, and an AUC from 0.58 to 0.75. A panel combining these genes with HCC risk factors had a sensitivity of 87%, a specificity of 100%, and an AUC of 0.91.</mods:abstract>
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               <mods:accessCondition type="useAndReproduction">cc-by (c) Michailidi, Christina et al., 2014 http://creativecommons.org/licenses/by/3.0/es info:eu-repo/semantics/openAccess</mods:accessCondition>
               <mods:subject>
                  <mods:topic>Epigenètica</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Cèl·lules hepàtiques</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Marcadors bioquímics</mods:topic>
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               <mods:subject>
                  <mods:topic>Càncer de fetge</mods:topic>
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               <mods:subject>
                  <mods:topic>Metilació</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Epigenetics</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Liver cells</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Biochemical markers</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Liver cancer</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Methylation</mods:topic>
               </mods:subject>
               <mods:titleInfo>
                  <mods:title>Genome-wide and gene-specific epigenomic platforms for hepatocellular carcinoma biomarker development trials</mods:title>
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               <mods:genre>info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion</mods:genre>
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