INTRODUCTION: Epigenetic changes are known to play a pivotal role in hepatocellular carcinogenesis, but the effects of these changes on cancer cell protein expression remain poorly characterized. We correlated DNA copy number changes with miRNA expression profiles in patients with hepatocellular carcinoma (HCC) to determine high value candidate miRNAs predictive of recurrence after liver transplant. We discovered that decreased miR-1226 expression inversely correlates with MUC1 surface staining in patients with recurrent HCC.

METHODS: Global miRNA expression profiling was performed using oligonucleotide microarrays on 88 tumor nodules from 64 patients, 48% of whom had recurrent HCC after transplant within 3 years. A subset of 11 recurrent and 10 nonrecurrent patients were analyzed for genomic copy number changes using molecular inversion probe technology and high density snp arrays. Results were analyzed using Nexus Copy Number v6.1. MUC1 immunohistochemistry staining was performed on tissue sections cut from the same tumor blocks used to purify the nucleic acids for copy number and miRNA expression analyses.

RESULTS: Thirteen HCC genomic instability regions contained miRNA loci and 11 of these miRNAs belong to a previously described biomarker shown to be predictive of HCC recurrence after transplant. In one such region, loss of allele 3p21.2 was detected in 40% of recurrent patients (p=0.035) and this allele contains the miR-1226 locus that correlates with recurrence. MUC1 is a known target of miR-1226, so we performed immunohistochemistry staining for MUC1 on all tumors used in the genomic analysis. 77% of recurrent patients were MUC1+ and 62% of nonrecurrent patients were MUC1-. For miR-1226 expression relative to recurrence, 92% of patients with downregulated miR-1226 were MUC1+ and 78% with upregulated miR-1226 were MUC1-, in keeping with the known inverse relationship between miR-1226 expression and MUC1 translation.

CONCLUSION: This small pilot study demonstrates proof of principle in applying bioinformatic analysis of epigenetic observations to reveal clinically meaningful biomarkers. Further efforts to discover additional protein biomarkers in this heterogeneous disease using this approach are warranted.

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