CpG methylation signature predicts prognosis in breast cancer

DNA methylation patterns associated with breast cancer prognosis that are specific to tumor subtype and menopausal status

Tumor subtype and menopausal status are strong predictors of breast cancer (BC) prognosis. We aimed to find and validate subtype- or menopausal-status-specific changes in tumor DNA methylation (DNAm) associated with all-cause mortality or BC progression. Associations between site-specific tumor DNAm and BC prognosis were estimated among The Cancer Genome Atlas participants (n = 692) with Illumina Infinium HumanMethylation450 BeadChip array data. All-cause mortality and BC progression were modeled using Cox proportional hazards models stratified by tumor subtypes, adjusting for age, race, stage, menopausal status, tumor purity, and cell type proportion. Effect measure modification by subtype and menopausal status were evaluated by incorporating a product term with DNAm. Site-specific inference was used to identify subtype- or menopausal-status-specific differentially methylated regions (DMRs) and functional pathways. The validation of the results was carried out on an independent dataset (GSE72308; n = 180). We identified a total of fifteen unique CpG probes that were significantly associated ( P ≤ 1 × 10 - 7 with survival outcomes in subtype- or menopausal-status-specific manner. Seven probes were associated with overall survival (OS) or progression-free interval (PFI) for women with luminal A subtype, and four probes were associated with PFI for women with luminal B subtype. Five probes were associated with PFI for post-menopausal women. A majority of significant probes showed a lower risk of OS or BC progression with higher DNAm. We identified subtype- or menopausal-status-specific DMRs and functional pathways of which top associated pathways differed across subtypes or menopausal status. None of significant probes from site-specific analyses met genome-wide significant level in validation analyses while directions and magnitudes of coefficients showed consistent pattern. We have identified subtype- or menopausal-status-specific DNAm biomarkers, DMRs and functional pathways associated with all-cause mortality or BC progression, albeit with limited validation. Future studies with larger independent cohort of non-post-menopausal women with non-luminal A subtypes are warranted for identifying subtype- and menopausal-status-specific DNAm biomarkers for BC prognosis.

PCDHB15 as a potential tumor suppressor and epigenetic biomarker for breast cancer

Breast cancer is among the most frequently diagnosed cancer types and the leading cause of cancer-related death in women. The mortality rate of patients with breast cancer is currently increasing, perhaps due to a lack of early screening tools. In the present study, using The Cancer Genome Atlas (TCGA) breast cancer dataset (n=883), it was determined that methylation of the protocadherin β15 (PCDHB15) promoter was higher in breast cancer samples than that in normal tissues. A negative association between promoter methylation and expression of PCDHB15 was observed in the TCGA dataset and breast cancer cell lines. In TCGA cohort, lower PCDHB15 expression was associated with shorter relapse-free survival times. Treatment with the DNA methyltransferase inhibitor restored PCDHB15 expression in a breast cancer cell line; however, overexpression of PCDHB15 was shown to suppress colony formation. PCDHB15 methylation detected in circulating cell-free DNA (cfDNA) isolated from serum samples was higher in patients with breast cancer (40.8%) compared with that in patients with benign tumors (22.4%). PCDHB15 methylation was not correlated with any clinical parameters. Taken together, PCDHB15 is a potential tumor suppressor in cases of breast cancer, which can be epigenetically silenced via promoter methylation. PCDHB15 methylation using cfDNA is a novel minimally invasive epigenetic biomarker for the diagnosis and prognosis of breast cancer.

Role of Immune Cell-Specific Hypermethylation Signatures in Classification and Risk Stratification of Breast Cancer

Background: Epigenetic regulation, including DNA methylation, plays a major role in shaping the identity and function of immune cells. Innate and adaptive immune cells recruited into tumor tissues contribute to the formation of the tumor immune microenvironment (TIME), which is closely involved in tumor progression in breast cancer (BC). However, the specific methylation signatures of immune cells have not been thoroughly investigated yet. Additionally, it remains unknown whether immune cells-specific methylation signatures can identify subgroups and stratify the prognosis of BC patients. Methods: DNA methylation profiles of six immune cell types from eight datasets downloaded from the Gene Expression Omnibus were collected to identify immune cell-specific hypermethylation signatures (IC-SHMSs). Univariate and multivariate cox regression analyses were performed using BC data obtained from The Cancer Genome Atlas to identify the prognostic value of these IC-SHMSs. An unsupervised clustering analysis of the IC-SHMSs with prognostic value was performed to categorize BC patients into subgroups. Multiple Cox proportional hazard models were constructed to explore the role of IC-SHMSs and their relationship to clinical characteristics in the risk stratification of BC patients. Integrated discrimination improvement (IDI) was performed to determine whether the improvement of IC-SHMSs on clinical characteristics in risk stratification was statistically significant. Results: A total of 655 IC-SHMSs of six immune cell types were identified. Thirty of them had prognostic value, and 10 showed independent prognostic value. Four subgroups of BC patients, which showed significant heterogeneity in terms of survival prognosis and immune landscape, were identified. The model incorporating nine IC-SHMSs showed similar survival prediction accuracy as the clinical model incorporating age and TNM stage [3-year area under the curve (AUC): 0.793 vs. 0.785; 5-year AUC: 0.735 vs. 0.761]. Adding the IC-SHMSs to the clinical model significantly improved its prediction accuracy in risk stratification (3-year AUC: 0.897; 5-year AUC: 0.856). The results of IDI validated the statistical significance of the improvement (p < 0.05). Conclusions: Our study suggests that IC-SHMSs may serve as signatures of classification and risk stratification in BC. Our findings provide new insights into epigenetic signatures, which may help improve subgroup identification, risk stratification, and treatment management.

A High Epigenetic Risk Score Shapes the Non-Inflamed Tumor Microenvironment in Breast Cancer

Background: Epigenetic dysregulation via aberrant DNA methylation has gradually become recognized as an efficacious signature for predicting tumor prognosis and response to therapeutic targets. However, reliable DNA methylation biomarkers describing tumorigenesis remain to be comprehensively explored regarding their prognostic and therapeutic potential in breast cancer (BC).

Methods: Whole-genome methylation datasets integrated from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database were profiled (n = 1,268). A three-stage selection procedure (discovery, training, and external validation) was utilized to screen out the prominent biomarkers and establish a robust risk score from more than 300,000 CpG sites after quality control, rigorous filtering, and reducing dimension. Moreover, gene set enrichment analyses guided us to systematically correlate this epigenetic risk score with immunological characteristics, including immunomodulators, anti-cancer immunity cycle, immune checkpoints, tumor-infiltrating immune cells and a series of signatures upon modulating components within BC tumor microenvironment (TME). Multi-omics data analyses were performed to decipher specific genomic alterations in low- and high-risk patients. Additionally, we also analyzed the role of risk score in predicting response to several treatment options.

Results: A 10-CpG-based prognostic signature which could significantly and independently categorize BC patients into distinct prognoses was established and sufficiently validated. And we hypothesize that this signature designs a non-inflamed TME in BC based on the evidence that the derived risk score is negatively correlated with tumor-associated infiltrating immune cells, anti-cancer immunity cycle, immune checkpoints, immune cytolytic activity, T cell inflamed score, immunophenoscore, and the vast majority of immunomodulators. The identified high-risk patients were characterized by upregulation of immune inhibited oncogenic pathways, higher TP53 mutation and copy number burden, but lower response to cancer immunotherapy and chemotherapy.

Conclusion: Our work highlights the complementary roles of 10-CpG-based signature in estimating overall survival in BC patients, shedding new light on investigating failed events concerning immunotherapy at present.

The epigenetics of breast cancer - Opportunities for diagnostics, risk stratification and therapy

The stage and molecular pathology-dependent prognosis of breast cancer, the limited treatment options for triple-negative carcinomas, as well as the development of resistance to therapies illustrate the need for improved early diagnosis and the development of new therapeutic approaches. Increasing data suggests that some answers to these challenges could be found in the area of epigenetics. In this study, we focus on the current research of the epigenetics of breast cancer, especially on the potential of epigenetics for clinical application in diagnostics, risk stratification and therapy. The differential DNA methylation status of specific gene regions has been used in the past to differentiate breast cancer cells from normal tissue. New technologies as detection of circulating nucleic acids including microRNAs to early detect breast cancer are emerging. Pattern of DNA methylation and expression of histone-modifying enzymes have been successfully used for risk stratification. However, all these epigenetic biomarkers should be validated in larger clinical studies. Recent preclinical and clinical studies show a therapeutic benefit of epigenetically active drugs for breast cancer entities that are still difficult to treat (triple negative, UICC stage IV). Remarkably, epigenetic therapies combined with chemotherapies or hormone-based therapies represent the most promising strategy. At the current stage, the integration of epigenetic substances into established breast cancer therapy protocols seems to hold the greatest potential for a clinical application of epigenetic research.

Genome-Wide Analysis of Methylation-Driven Genes and Identification of an Eight-Gene Panel for Prognosis Prediction in Breast Cancer

BACKGROUND

Aberrant DNA methylation is a crucial epigenetic regulator that is closely related to the occurrence and development of various cancers, including breast cancer (BC). The present study aimed to identify a novel methylation-based prognosis biomarker panel by integrally analyzing gene expression and methylation patterns in BC patients.

METHODS

DNA methylation and gene expression data of breast cancer (BRCA) were downloaded from The Cancer Genome Atlas (TCGA). R packages, including ChAMP, SVA, and MethylMix, were applied to identify the unique methylation-driven genes. Subsequently, these genes were subjected to Metascape for GO analysis. Univariant Cox regression was used to identify survival-related genes among the methylation-driven genes. Robust likelihood-based survival modeling was applied to define the prognosis markers. An independent data set (GSE72308) was used for further validation of our risk score system.

RESULTS

A total of 879 DNA methylation-driven genes were identified from 765 BC patients. In the discovery cohort, we identified 50 survival-related methylation-driven genes. Finally, we built an eight-methylation-driven gene panel that serves as prognostic predictors.

CONCLUSIONS

Our analysis of transcriptome and methylome variations associated with the survival status of BC patients provides a further understanding of basic biological processes and a basis for the genetic etiology in BC.