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Stochastic epigenetic outliers can define field defects in cancer.

ABSTRACT: There is growing evidence that DNA methylation alterations may contribute to carcinogenesis. Recent data also suggest that DNA methylation field defects in normal pre-neoplastic tissue represent infrequent stochastic "outlier" events. This presents a statistical challenge for standard feature selection algorithms, which assume frequent alterations in a disease phenotype. Although differential variability has emerged as a novel feature selection paradigm for the discovery of outliers, a growing concern is that these could result from technical confounders, in principle thus favouring algorithms which are robust to outliers.Here we evaluate five differential variability algorithms in over 700 DNA methylomes, including two of the largest cohorts profiling precursor cancer lesions, and demonstrate that most of the novel proposed algorithms lack the sensitivity to detect epigenetic field defects at genome-wide significance. In contrast, algorithms which recognise heterogeneous outlier DNA methylation patterns are able to identify many sites in pre-neoplastic lesions, which display progression in invasive cancer. Thus, we show that many DNA methylation outliers are not technical artefacts, but define epigenetic field defects which are selected for during cancer progression.Given that cancer studies aiming to find epigenetic field defects are likely to be limited by sample size, adopting the novel feature selection paradigm advocated here will be critical to increase assay sensitivity.

SUBMITTER: Teschendorff AE

PROVIDER: S-EPMC4840974 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

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Stochastic epigenetic outliers can define field defects in cancer.

Teschendorff Andrew E AE Jones Allison A Widschwendter Martin M

BMC bioinformatics 20160422

<h4>Background</h4>There is growing evidence that DNA methylation alterations may contribute to carcinogenesis. Recent data also suggest that DNA methylation field defects in normal pre-neoplastic tissue represent infrequent stochastic "outlier" events. This presents a statistical challenge for standard feature selection algorithms, which assume frequent alterations in a disease phenotype. Although differential variability has emerged as a novel feature selection paradigm for the discovery of ou ...[more]

PMID: 27103033

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Project description:Background: The biological role of microRNAs (miRNAs) in field cancerization is unknown. To investigate the involvement of miRNAs in gastric field cancerization, we evaluated the expression profile of ten miRNAs and their diagnostic value. Methods: We used three groups of FFPE gastric samples: non-cancer (NC), cancer adjacent (ADJ) and gastric cancer (GC). The expression profiles of hsa-miR-10a, -miR-21, -miR-29c, -miR-135b, -miR-148a, -miR-150, -miR-204, -miR-215, -miR-483 and -miR-664a were investigated using qRT-PCR. The results obtained by qRT-PCR were validated in Small RNA-Seq data from the TCGA database. The search for target genes of the studied miRNAs was performed in the miRTarBase public database and miRTargetLink tool, using experimentally validated interactions. In addition, we also performed the functional analysis of these genes using enrichment in KEGG pathways. The potential as biomarker was evaluated using a receiver operating characteristic (ROC) curve and the derived area under the curve (AUC>0.85) analysis. Results: The miRNAs hsa-miR-10a, -miR-21, -miR-135b, hsa-miR-148a, -miR-150, -miR-215, -miR-204, -miR-483 and -miR-664a were up-regulated in ADJ and GC compared to NC (P<0.03); and hsa-miR-21 and -miR-135b were up-regulated in GC compared to ADJ (P<0.01). Hsa-miR-148a, -miR-150, -miR-215, -miR-483 and -miR-664a were not differentially expressed between GC and ADJ, suggesting that both share similar changes (P>0.1). The TS-miR hsa-miR-29c was up-regulated in ADJ compared to NC and GC (P<0.01); we did not observe a significant difference in the expression of this miRNA between NC and GC. This feature may be an antitumor mechanism used by cancer-adjacent tissue because this miRNA regulates the BCL-2, CDC42 and DMNT3A oncogenes. The expression level of hsa-miR-204 was associated with Helicobacter pylori infection status (P<0.05). Functional analysis using the genes regulated by the studied miRNAs showed that they are involved in biological pathways and cellular processes that are critical for the establishment of H. pylori infection and for the onset, development and progression of GC. hsa-miR-10a, -miR-21, -miR-135b, -miR-148a, -miR-150, -miR-215, -miR-483 and -miR-664a were able to discriminate NC from other tissues with great accuracy (AUC>0.85). Conclusion: The studied miRNAs are closely related to field cancerization, regulate genes important for gastric carcinogenesis and can be potentially useful as biomarkers in GC.

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Stochastic epigenetic outliers can define field defects in cancer.

Publications

Stochastic epigenetic outliers can define field defects in cancer.

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