Genome-scale methylation assessment did not identify prognostic biomarkers in oral tongue carcinomas. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Lim, Annette; Wong, Nicholas; Pidsley, Ruth; Zotenko, Elena; Corry, June; Dobrovic, Alexander; Clark, Susan; Rischin, Danny; Solomon, Benjamin
• Is Part Of: Clinical epigenetics. Volume 8:Issue 1(2016)
• Page Start: 1
• Page End: 12
• Publication Date: 2016-12
• Subjects: DNA methylation -- Tongue -- Oral carcinoma -- HM450K -- Profiling -- Survival -- Epigenetics; Epigenesis -- Periodicals; Genetic regulation -- Periodicals; Human cytogenetics -- Periodicals; Human molecular genetics -- Periodicals; Cancer -- Genetic aspects -- Periodicals; 611.01816
• DOI: 10.1186/s13148-016-0235-0
• Languages: English
• ISSNs: 1868-7075

Abstract

Abstract Background DNA methylation profiling of heterogeneous head and neck squamous cell carcinoma (HNSCC) cohorts has been reported to predict patient outcome. We investigated if a prognostic DNA methylation profile could be found in tumour tissue from a single uniform subsite, the oral tongue. The methylation status of 109 comprehensively annotated oral tongue squamous cell carcinoma (OTSCC) formalin-fixed paraffin-embedded (FFPE) samples from a single institution were examined with the Illumina HumanMethylation450K (HM450K) array. Data pre-processing, quality control and analysis were performed using R packages. Probes mapping to SNPs, sex chromosomes and unreliable probes were accounted for prior to downstream analyses. The relationship between methylation and patient survival was examined using both agnostic approaches and feature selection. The cohort was enlarged by incorporation of 331 The Cancer Genome Atlas (TCGA) HNSCC samples, which included 91 TCGA OTSCC samples with HM450K and survival data available. Results Given the use of FFPE-derived DNA, we defined different cohorts for separate analyses. Overall, similar results were found between cohorts. With an unsupervised approach, no distinct hypermethylated group of samples was identified and nor was a prognostic methylation profile identified. The use of multiple downstream feature selection approaches, including a linear models for microarray data (LIMMA), centroid feature selection (CFS), and recursive feature elimination (RFE) support vector machines, similarly failed to identify a significant methylation signature informative for patient prognosis or any clinicopathological data available. Furthermore, we were unable to confirm the prognostic methylation profiles or specific prognostic loci reported within the literature for HNSCC. Conclusions With genome-scale assessment of DNA methylation using HM450K in one of the largest OTSCC cohorts to date, we were unable to identify a hypermethylated group of tumours or a prognostic methylation signature. This suggests that either DNA methylation in isolation is not likely to be of prognostic value or larger cohorts are required to identify such a biomarker for OTSCC.