Dataset Information

Methylation profiling of ductal carcinoma in situ and its relationship to histopathological features.

ABSTRACT: INTRODUCTION: DNA methylation is a well-studied biomarker in invasive breast cancer, but its role in ductal carcinoma in situ (DCIS) is less well characterized. The aims of this study are to assess the methylation profile in DCIS for a panel of well-characterized genes that are frequently methylated in breast cancer, to investigate the relationship of methylation with pathological features, and to perform a proof-of-principle study to evaluate the practicality of methylation as a biomarker in diagnostic DCIS material. METHODS: Promoter CpG island methylation for a panel of 11 breast cancer-related genes was performed by methylation-sensitive high resolution melting (MS-HRM). Formalin-fixed, paraffin-embedded (FFPE) biopsies from 72 samples of pure DCIS (DCIS occurring in the absence of synchronous invasive carcinoma), 10 samples of mixed DCIS (DCIS adjacent to invasive carcinoma), and 18 samples of normal breast epithelium adjacent to a DCIS lesion were micro-dissected prior to DNA extraction. RESULTS: Methylation was seen for all the tested genes except BRCA1. RASSF1A was the most frequently methylated gene (90% of DCIS samples) and its methylation was associated with comedo necrosis (p = 0.018). Cluster analysis based on the methylation profile revealed four groups, the highly methylated cluster being significantly associated with high nuclear grade, HER2 amplification, negative estrogen receptor (ER) ? status, and negative progesterone receptor (PgR) status, (p = 0.038, p = 0.018, p <0.001, p = 0.001, respectively). Methylation of APC (p = 0.017), CDH13 (p = 0.017), and RAR? (p <0.001) was associated with negative ER? status. Methylation of CDH13 (p <0.001), and RAR? (p = 0.001) was associated with negative PgR status. Methylation of APC (p = 0.013) and CDH13 (p = 0.026) was associated with high nuclear grade. Methylation of CDH13 (p = 0.009), and RAR? (p = 0.042) was associated with HER2-amplification. CONCLUSIONS: DNA methylation can be assessed in FFPE-derived samples using suitable methodologies. Methylation of a panel of genes that are known to be methylated in invasive breast cancer was able to classify DCIS into distinct groups and was differentially associated with phenotypic features in DCIS.

SUBMITTER: Pang JM

PROVIDER: S-EPMC4303108 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Methylation profiling of ductal carcinoma in situ and its relationship to histopathological features.

Pang Jia-Min B JM Deb Siddhartha S Takano Elena A EA Byrne David J DJ Jene Nicholas N Boulghourjian Alice A Holliday Anne A Millar Ewan E Lee C Soon CS O'Toole Sandra A SA Dobrovic Alexander A Fox Stephen B SB

Breast cancer research : BCR 20141021 5

<h4>Introduction</h4>DNA methylation is a well-studied biomarker in invasive breast cancer, but its role in ductal carcinoma in situ (DCIS) is less well characterized. The aims of this study are to assess the methylation profile in DCIS for a panel of well-characterized genes that are frequently methylated in breast cancer, to investigate the relationship of methylation with pathological features, and to perform a proof-of-principle study to evaluate the practicality of methylation as a biomarke ...[more]

PMID: 25331261

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Project description:Histopathological assessment of ductal carcinoma in situ, a nonobligate precursor of invasive breast cancer, is characterized by considerable interobserver variability. Previously, post hoc dichotomization of multicategorical variables was used to determine the "ideal" cutoffs for dichotomous assessment. The present international multicenter study evaluated interobserver variability among 39 pathologists who performed upfront dichotomous evaluation of 149 consecutive ductal carcinomas in situ. All pathologists independently assessed nuclear atypia, necrosis, solid ductal carcinoma in situ architecture, calcifications, stromal architecture, and lobular cancerization in one digital slide per lesion. Stromal inflammation was assessed semiquantitatively. Tumor-infiltrating lymphocytes were quantified as percentages and dichotomously assessed with a cutoff at 50%. Krippendorff's alpha (KA), Cohen's kappa and intraclass correlation coefficient were calculated for the appropriate variables. Lobular cancerization (KA = 0.396), nuclear atypia (KA = 0.422), and stromal architecture (KA = 0.450) showed the highest interobserver variability. Stromal inflammation (KA = 0.564), dichotomously assessed tumor-infiltrating lymphocytes (KA = 0.520), and comedonecrosis (KA = 0.539) showed slightly lower interobserver disagreement. Solid ductal carcinoma in situ architecture (KA = 0.602) and calcifications (KA = 0.676) presented with the lowest interobserver variability. Semiquantitative assessment of stromal inflammation resulted in a slightly higher interobserver concordance than upfront dichotomous tumor-infiltrating lymphocytes assessment (KA = 0.564 versus KA = 0.520). High stromal inflammation corresponded best with dichotomously assessed tumor-infiltrating lymphocytes when the cutoff was set at 10% (kappa = 0.881). Nevertheless, a post hoc tumor-infiltrating lymphocytes cutoff set at 20% resulted in the highest interobserver agreement (KA = 0.669). Despite upfront dichotomous evaluation, the interobserver variability remains considerable and is at most acceptable, although it varies among the different histopathological features. Future studies should investigate its impact on ductal carcinoma in situ prognostication. Forthcoming machine learning algorithms may be useful to tackle this substantial diagnostic challenge.

Dataset Information

Methylation profiling of ductal carcinoma in situ and its relationship to histopathological features.

Publications

Methylation profiling of ductal carcinoma in situ and its relationship to histopathological features.

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