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DNA methylation patterns in luminal breast cancers differ from non-luminal subtypes and can identify relapse risk independent of other clinical variables.

ABSTRACT: The diversity of breast cancers reflects variations in underlying biology and affects the clinical implications for patients. Gene expression studies have identified five major subtypes- Luminal A, Luminal B, basal-like, ErbB2+ and Normal-Like. We set out to determine the role of DNA methylation in subtypes by performing genome-wide scans of CpG methylation in breast cancer samples with known expression-based subtypes. Unsupervised hierarchical clustering using a set of most varying loci clustered the tumors into a Luminal A majority (82%) cluster, Basal-like/ErbB2+ majority (86%) cluster and a non-specific cluster with samples that were also inconclusive in their expression-based subtype correlations. Contributing methylation loci were both gene associated loci (30%) and non-gene associated (70%), suggesting subtype dependant genome-wide alterations in the methylation landscape. The methylation patterns of significant differentially methylated genes in luminal A tumors are similar to those identified in CD24 + luminal epithelial cells and the patterns in basal-like tumors similar to CD44 + breast progenitor cells. CpG islands in the HOXA cluster and other homeobox (IRX2, DLX2, NKX2-2) genes were significantly more methylated in Luminal A tumors. A significant number of genes (2853, p < 0.05) exhibited expression-methylation correlation, implying possible functional effects of methylation on gene expression. Furthermore, analysis of these tumors by using follow-up survival data identified differential methylation of islands proximal to genes involved in Cell Cycle and Proliferation (Ki-67, UBE2C, KIF2C, HDAC4), angiogenesis (VEGF, BTG1, KLF5), cell fate commitment (SPRY1, OLIG2, LHX2 and LHX5) as having prognostic value independent of subtypes and other clinical factors.

SUBMITTER: Kamalakaran S

PROVIDER: S-EPMC5528275 | biostudies-literature | 2011 Feb

REPOSITORIES: biostudies-literature

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DNA methylation patterns in luminal breast cancers differ from non-luminal subtypes and can identify relapse risk independent of other clinical variables.

Kamalakaran Sitharthan S Varadan Vinay V Giercksky Russnes Hege E HE Levy Dan D Kendall Jude J Janevski Angel A Riggs Michael M Banerjee Nilanjana N Synnestvedt Marit M Schlichting Ellen E Kåresen Rolf R Shama Prasada K K Rotti Harish H Rao Ramachandra R Rao Laxmi L Eric Tang Man-Hung MH Satyamoorthy K K Lucito Robert R Wigler Michael M Dimitrova Nevenka N Naume Bjorn B Borresen-Dale Anne-Lise AL Hicks James B JB

Molecular oncology 20101202 1

The diversity of breast cancers reflects variations in underlying biology and affects the clinical implications for patients. Gene expression studies have identified five major subtypes- Luminal A, Luminal B, basal-like, ErbB2+ and Normal-Like. We set out to determine the role of DNA methylation in subtypes by performing genome-wide scans of CpG methylation in breast cancer samples with known expression-based subtypes. Unsupervised hierarchical clustering using a set of most varying loci cluster ...[more]

PMID: 21169070

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Project description:BackgroundDNA methylation-associated studies on biliary tract cancer (BTC), including cholangiocarcinoma (CCA) and gallbladder cancer (GBC), may improve the BTC classification scheme. We proposed to identify the shared methylation changes of BTCs and investigate their associations with genomic aberrations, immune characteristics, and survival outcomes.MethodsMulti-dimensional data concerning mutation, DNA methylation, immune-related features, and clinical data of 57 CCAs and 48 GBCs from Eastern Hepatobiliary Surgery Hospital (EHSH) and 36 CCAs in the TCGA-CHOL cohort were analyzed.ResultsIn our cohort including 24 intrahepatic CCAs (iCCAs), 20 perihilar CCAs (pCCAs), 13 distal CCAs (dCCAs), and 48 GBCs, 3369 common differentially methylated regions (DMRs) were identified by comparing tumor and non-tumor samples. A lower level of methylation changes of these common DMRs was associated with fewer copy number variations, fewer mutational burden, and remarkably longer overall survival (OS, hazard ratio [HR] = 0.07, 95% confidence interval [CI] 0.01-0.65, P = 0.017). Additionally, a 12-marker model was developed and validated for prognostication after curative surgery (HR = 0.21, 95% CI 0.10-0.43, P < 0.001), which exhibited undifferentiated prognostic effects in subgroups defined by anatomic location (iCCAs, d/pCCAs, GBCs), TNM stage, and tumor purity. Its prognostic utility remained significant in multivariable analysis (HR = 0.26, 95% CI 0.11-0.59, P = 0.001). Moreover, the BTCs with minimal methylation changes exhibited higher immune-related signatures, infiltration of CD8+ lymphocytes, and programmed death-ligand 1 (PD-L1) expression, indicating an inflamed tumor immune microenvironment (TIME) with PD-L1 expression elicited by immune attack, potentially suggesting better immunotherapy efficacy.ConclusionsIn BTCs, DNA methylation is a powerful tool for molecular classification, serving as a robust indicator of genomic aberrations, survival outcomes, and tumor immune microenvironment. Our integrative analysis provides insights into the prognostication after curative surgery and patient selection for immunotherapy.

Project description:BackgroundThe luminal subtype accounts for ~70% of newly diagnosed breast cancer patients. Although it has a better prognosis, approximately 30% of them develop a late relapse. Identifying those patients is of interest to improve treatment decisions.MethodsA retrospective observational, single-centre study based on data from medical records of 572 non-metastatic (I-III) invasive ductal breast carcinoma patients, 448 with luminal tumours and 124 with triple-negative tumours. Kaplan-Meier, Cox regression and time-dependent Cox regression were carried out to obtain the prognosis value of risk factors.ResultsDuring a median observation of 5.5 years, 105 distant metastasis events and 105 all-cause deaths were observed. In addition to known clinicopathological factors (i.e., age, tumour size and lymph node metastasis), the high semi-quantitative expression of both hormone receptors was associated with distant metastasis-free survival (DMFS) (adjusted hazard ratio (HaR): 0.524 (0.316-0.867), p = 0.012) and overall survival (OS) (adjusted HaR: 0.486 (0.286-0.827), p = 0.008). The stratified analysis made it possible to identify risk modification factors. Subsequent stratification by histological grade, Ki-67 and semi-quantitative PR expression or, mainly, the composite semi-quantitative expression of hormone receptors (cHR) enabled the identification of luminal breast cancer patients of adjuvant schema at higher risk for metastasis and death. However, initial analyses including patients of neoadjuvant therapy pointed to a path of subsequent stratification by cHR and histological grade, also enabling grouping of luminal breast cancer patients with similar prognosis for DMFS (cHR ≤ 4+ G2 or G3 versus triple-negative, adjusted HaR: 0.703 (0.415-1.189), p = 0.189) and OS (cHR ≤4+ G2 or G3 versus triple-negative, adjusted HaR: 0.662 (0.403-1.088), p = 0.104).ConclusionThe semi-quantitative expression of both cHR, Ki-67 proliferation index and histological grade can identify luminal breast cancer patients at greater risk of developing metastasis and death when combined in a hierarchical fashion, and could be useful for a better prognosis stratification in services from low- and middle-income countries.

Project description:ObjectiveObesity is driven by modifiable lifestyle factors whose effects may be mediated by epigenetics. Therefore, we investigated lifestyle effects on blood DNA methylation in participants of the LIFE-Adult study, a well-characterised population-based cohort from Germany.Research design and methodsLifestyle scores (LS) based on diet, physical activity, smoking and alcohol intake were calculated in 4107 participants of the LIFE-Adult study. Fifty subjects with an extremely healthy lifestyle and 50 with an extremely unhealthy lifestyle (5th and 95th percentiles LS) were selected for genome-wide DNA methylation analysis in blood samples employing Illumina Infinium® Methylation EPIC BeadChip system technology.ResultsDifferences in DNA methylation patterns between body mass index groups (<25 vs. >30 kg/m2 ) were rather marginal compared to inter-lifestyle differences (0 vs. 145 differentially methylated positions [DMPs]), which identified 4682 differentially methylated regions (DMRs; false discovery rate [FDR <5%) annotated to 4426 unique genes. A DMR annotated to the glutamine-fructose-6-phosphate transaminase 2 (GFPT2) locus showed the strongest hypomethylation (∼6.9%), and one annotated to glutamate rich 1 (ERICH1) showed the strongest hypermethylation (∼5.4%) in healthy compared to unhealthy lifestyle individuals. Intersection analysis showed that diet, physical activity, smoking and alcohol intake equally contributed to the observed differences, which affected, among others, pathways related to glutamatergic synapses (adj. p < .01) and axon guidance (adj. p < .05). We showed that methylation age correlates with chronological age and waist-to-hip ratio with lower DNA methylation age (DNAmAge) acceleration distances in participants with healthy lifestyles. Finally, two identified top DMPs for the alanyl aminopeptidase (ANPEP) locus also showed the strongest expression quantitative trait methylation in blood.ConclusionsDNA methylation patterns help discriminate individuals with a healthy versus unhealthy lifestyle, which may mask subtle methylation differences derived from obesity.

Dataset Information

DNA methylation patterns in luminal breast cancers differ from non-luminal subtypes and can identify relapse risk independent of other clinical variables.

Publications

DNA methylation patterns in luminal breast cancers differ from non-luminal subtypes and can identify relapse risk independent of other clinical variables.

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