Circulating Cell-Free DNA in Breast Cancer: Searching for Hidden Information towards Precision Medicine

DNA-Binding Proteins and Passenger Proteins in Plasma DNA-Protein Complexes: Imprint of Parental Cells or Key Mediators of Carcinogenesis Processes?

Knowledge of the composition of proteins that interact with plasma DNA will provide a better understanding of the homeostasis of circulating nucleic acids and the various modes of interaction with target cells, which may be useful in the development of gene targeted therapy approaches. The goal of the present study is to shed light on the composition and architecture of histone-containing nucleoprotein complexes (NPCs) from the blood plasma of healthy females (HFs) and breast cancer patients (BCPs) and to explore the relationship of proteins with crucial steps of tumor progression: epithelial-mesenchymal transition (EMT), cell proliferation, invasion, cell migration, stimulation of angiogenesis, and immune response. MALDI-TOF mass spectrometric analysis of NPCs isolated from blood samples using affine chromatography was performed. Bioinformatics analysis showed that the shares of DNA-binding proteins in the compositions of NPCs in normal and cancer patients are comparable and amount to 40% and 33%, respectively; in total, we identified 38 types of DNA-binding motifs. Functional enrichment analysis using FunRich 3.13 showed that, in BCP blood, the share of DNA-binding proteins involved in nucleic acid metabolism increased, while the proportion of proteins involved in intercellular communication and signal transduction decreased. The representation of NPC passenger proteins in breast cancer also changes: the proportion of proteins involved in transport increases and the share of proteins involved in energy biological pathways decreases. Moreover, in the HF blood, proteins involved in the processes of apoptosis were more represented in the composition of NPCs and in the BCP blood-in the processes of active secretion. For the first time, bioinformatics approaches were used to visualize the architecture of circulating NPCs in the blood and to show that breast cancer has an increased representation of passenger proteins involved in EMT, cell proliferation, invasion, cell migration, and immune response. Using breast cancer protein data from the Human Protein Atlas (HPA) and DEPC, we found that 86% of NPC proteins in the blood of BCPs were not previously annotated in these databases. The obtained data may indirectly indicate directed protein sorting in NPCs, which, along with extracellular vesicles, can not only be diagnostically significant molecules for liquid biopsy, but can also carry out the directed transfer of genetic material from donor cells to recipient cells.

Colorimetric and Electrochemical Dual-Mode Detection of Thioredoxin 1 Based on the Efficient Peroxidase-Mimicking and Electrocatalytic Property of Prussian Blue Nanoparticles

As a potent detection method for cancer biomarkers in physiological fluid, a colorimetric and electrochemical dual-mode sensing platform for breast cancer biomarker thioredoxin 1 (TRX1) was developed based on the excellent peroxidase-mimicking and electrocatalytic property of Prussian blue nanoparticles (PBNPs). PBNPs were hydrothermally synthesized using K3[Fe(CN)6] as a precursor and polyvinylpyrrolidone (PVP) as a capping agent. The synthesized spherical PBNPs showed a significant peroxidase-like activity, having approximately 20 and 60% lower Km values for 3,3',5,5'-tetramethylbenzidine (TMB) and H2O2, respectively, compared to those of horseradish peroxidase (HRP). The PBNPs also enhanced the electron transfer on the electrode surface. Based on the beneficial features, PBNPs were used to detect target TRX1 via sandwich-type immunoassay procedures. Using the strategies, TRX1 was selectively and sensitively detected, yielding limit of detection (LOD) values as low as 9.0 and 6.5 ng mL-1 via colorimetric and electrochemical approaches, respectively, with a linear range of 10-50 ng mL-1 in both strategies. The PBNP-based TRX1 immunoassays also exhibited a high degree of precision when applied to real human serum samples, demonstrating significant potentials to replace conventional HRP-based immunoassay systems into rapid, robust, reliable, and convenient dual-mode assay systems which can be widely utilized for the identification of important target molecules including cancer biomarkers.

Blood Plasma Circulating DNA-Protein Complexes: Involvement in Carcinogenesis and Prospects for Liquid Biopsy of Breast Cancer

Circulating DNA (cirDNA) is a promising tool in translational medicine. However, studies of cirDNA have neglected its association with proteins, despite ample evidence that this interaction may affect the fate of DNA in the bloodstream and its molecular functions. The goal of the current study is to shed light on the differences between the proteomic cargos of histone-containing nucleoprotein complexes (NPCs) from healthy female (HFs) and breast cancer patients (BCPs), and to reveal the proteins involved in carcinogenesis. NPCs were isolated from the blood samples of HFs and BCPs using affinity chromatography. A total of 177 and 169 proteins were identified in NPCs from HFs and BCPs using MALDI-TOF mass spectrometry. A bioinformatics analysis revealed that catalytically active proteins, as well as proteins that bind nucleic acids and regulate the activity of receptors, are the most represented among the unique proteins of blood NPCs from HFs and BCPs. In addition, the proportion of proteins participating in ion channels and proteins binding proteins increases in the NPCs from BCP blood. However, the involvement in transport and signal transduction was greater in BCP NPCs compared to those from HFs. Gene ontology term (GO) analysis revealed that the NPC protein cargo from HF blood was enriched with proteins involved in the negative regulation of cell proliferation, and in BCP blood, proteins involved in EMT, invasion, and cell migration were observed. The combination of SPG7, ADRB1, SMCO4, PHF1, and PSMG1 NPC proteins differentiates BCPs from HFs with a sensitivity of 100% and a specificity of 80%. The obtained results indirectly indicate that, in tandem with proteins, blood cirDNA is an important part of intercellular communication, playing a regulatory and integrating role in the physiology of the body.

Basic ctDNA Panel Promises Affordable Clinical Validity in Colon Cancer Patients but Not in Pancreas Cancer Patients

The potential of circulating tumor DNA (ctDNA) as a biomarker to assess the progression of various solid tumors has been explored extensively. In this study, we investigated the feasibility of utilizing a ctDNA sequencing panel specifically designed to target the most frequently mutated genomic regions in colon and pancreas cancers. Through somatic analysis of colon and pancreas tumors, we targeted 27 regions within eight genes. By employing PCR amplification and Illumina NGS, we ensured that each region was adequately covered with a minimum of 5000 reads (with an average of 12,000 reads). Our method exhibited reproducibility with repetition and dilutions. The positive detection threshold for ctDNA was set at a cutoff value of 0.5% ctDNA of the total reads using IGV. Among the samples analyzed, 71% of colon cancer cases displayed somatic mutations covered by the targeted regions. Within this group, detectable ctDNA was observed in 34% of the cases. Conversely, in pancreatic cancer, 55% of mutations were covered by the panel's regions, but only 13% of these cases exhibited detectable ctDNA. In follow-ups with the patients, changes in ctDNA percentages demonstrated complete concordance with changes in the clinical condition in 88% of the cases. Our findings suggest that employing a basic ctDNA-targeted panel can serve as a cost-effective and reliable approach for repeated monitoring of the efficacy of colon cancer therapy. However, in the case of pancreatic cancer, ctDNA showed limited utility, and alternative biomarkers may offer superior diagnostic value. Additionally, we found that a negative ctDNA test is not a guarantee for a relapse-free recovery; thus, we recommend a continuous follow-up with the patient on a long-term basis.

Liquid Biopsies: Emerging role and clinical applications in solid tumours

Late detection and lack of precision diagnostics are the major challenges in cancer prevention and management. Biomarker discovery in specific cancers, especially at the pre-invasive stage, is vital for early diagnosis, positive treatment response, and good disease prognosis. Traditional diagnostic measures require invasive procedures such as tissue excision using a needle, an endoscope, and/or surgical resection which can be unsafe, expensive, and painful. Additionally, the presence of comorbid conditions in individuals might render them ineligible for undertaking a tissue biopsy, and in some cases, it is difficult to access tumours depending on the site of occurrence. In this context, liquid biopsies are being explored for their clinical significance in solid malignancies management. These non-invasive or minimally invasive methods are being developed primarily for identification of biomarkers for early diagnosis and targeted therapeutics. In this review, we have summarised the use and importance of liquid biopsy as significant tool in diagnosis, prognosis prediction, and therapeutic development. We have also discussed the challenges that are encountered and future perspective.

Label-Free Human Disease Characterization through Circulating Cell-Free DNA Analysis Using Raman Spectroscopy

Circulating cell-free DNA (ccfDNA) is a liquid biopsy biomaterial attracting significant attention for the implementation of precision medicine diagnostics. Deeper knowledge related to its structure and biology would enable the development of such applications. In this study, we employed Raman spectroscopy to unravel the biomolecular profile of human ccfDNA in health and disease. We established reference Raman spectra of ccfDNA samples from healthy males and females with different conditions, including cancer and diabetes, extracting information about their chemical composition. Comparative observations showed a distinct spectral pattern in ccfDNA from breast cancer patients taking neoadjuvant therapy. Raman analysis of ccfDNA from healthy, prediabetic, and diabetic males uncovered some differences in their biomolecular fingerprints. We also studied ccfDNA released from human benign and cancer cell lines and compared it to their respective gDNA, confirming it mirrors its cellular origin. Overall, we explored for the first time Raman spectroscopy in the study of ccfDNA and provided spectra of samples from different sources. Our findings introduce Raman spectroscopy as a new approach to implementing liquid biopsy diagnostics worthy of further elaboration.

Comparative Analysis of Molecular Functions and Biological Role of Proteins from Cell-Free DNA-Protein Complexes Circulating in Plasma of Healthy Females and Breast Cancer Patients

Cell-free DNA (cfDNA) circulates in the bloodstream packed in membrane-coated structures (such as apoptotic bodies) or bound to proteins. To identify proteins involved in the formation of deoxyribonucleoprotein complexes circulating in the blood, native complexes were isolated using affinity chromatography with immobilized polyclonal anti-histone antibodies from plasma of healthy females (HFs) and breast cancer patients (BCPs). It was found that the nucleoprotein complexes (NPCs) from HF plasma samples contained shorter DNA fragments (~180 bp) than BCP NPCs. However, the share of DNA in the NPCs from cfDNA in blood plasma in HFs and BCPs did not differ significantly, as well as the share of NPC protein from blood plasma total protein. Proteins were separated by SDS-PAGE and identified by MALDI-TOF mass spectrometry. Bioinformatic analysis showed that in the presence of a malignant tumor, the proportion of proteins involved in ion channels, protein binding, transport, and signal transduction increased in the composition of blood-circulating NPCs. Moreover, 58 (35%) proteins are differentially expressed in a number of malignant neoplasms in the NPCs of BCPs. Identified NPC proteins from BCP blood can be recommended for further testing as breast cancer diagnostic/prognostic biomarkers or as being useful in developing gene-targeted therapy approaches.

Bridging biological cfDNA features and machine learning approaches

Liquid biopsies (LBs), particularly using circulating tumor DNA (ctDNA), are expected to revolutionize precision oncology and blood-based cancer screening. Recent technological improvements, in combination with the ever-growing understanding of cell-free DNA (cfDNA) biology, are enabling the detection of tumor-specific changes with extremely high resolution and new analysis concepts beyond genetic alterations, including methylomics, fragmentomics, and nucleosomics. The interrogation of a large number of markers and the high complexity of data render traditional correlation methods insufficient. In this regard, machine learning (ML) algorithms are increasingly being used to decipher disease- and tissue-specific signals from cfDNA. Here, we review recent insights into biological ctDNA features and how these are incorporated into sophisticated ML applications.

Autotaxin in Breast Cancer: Role, Epigenetic Regulation and Clinical Implications

Autotaxin (ATX), the protein product of Ectonucleotide Pyrophosphatase Phosphodiesterase 2 (ENPP2), is a secreted lysophospholipase D (lysoPLD) responsible for the extracellular production of lysophosphatidic acid (LPA). ATX-LPA pathway signaling participates in several normal biological functions, but it has also been connected to cancer progression, metastasis and inflammatory processes. Significant research has established a role in breast cancer and it has been suggested as a therapeutic target and/or a clinically relevant biomarker. Recently, ENPP2 methylation was described, revealing a potential for clinical exploitation in liquid biopsy. The current review aims to gather the latest findings about aberrant signaling through ATX-LPA in breast cancer and discusses the role of ENPP2 expression and epigenetic modification, giving insights with translational value.

Diagnostic and Therapeutic Potential of Circulating-Free DNA and Cell-Free RNA in Cancer Management

Over time, molecular biology and genomics techniques have been developed to speed up the early diagnosis and clinical management of cancer. These therapies are often most effective when administered to the subset of malignancies harboring the target identified by molecular testing. Important advances in applying molecular testing involve circulating-free DNA (cfDNA)- and cell-free RNA (cfRNA)-based liquid biopsies for the diagnosis, prognosis, prediction, and treatment of cancer. Both cfDNA and cfRNA are sensitive and specific biomarkers for cancer detection, which have been clinically proven through multiple randomized and prospective trials. These help in cancer management based on the noninvasive evaluation of size, quantity, and point mutations, as well as copy number alterations at the tumor site. Moreover, personalized detection of ctDNA helps in adjuvant therapeutics and predicts the chances of recurrence of cancer and resistance to cancer therapy. Despite the controversial diagnostic values of cfDNA and cfRNA, many clinical trials have been completed, and the Food and Drug Administration has approved many multigene assays to detect genetic alterations in the cfDNA of cancer patients. In this review, we underpin the recent advances in the physiological roles of cfDNA and cfRNA, as well as their roles in cancer detection by highlighting recent clinical trials and their roles as prognostic and predictive markers in cancer management.

Size and Methylation Index of Cell-Free and Cell-Surface-Bound DNA in Blood of Breast Cancer Patients in the Contest of Liquid Biopsy

Aberrantly methylated circulating DNA (cirDNA) has proven to be a good cancer marker, but its detection is limited by low concentrations, fragmentation, and insufficiency. Since the methylated cirDNA was shown to be more stable in circulation than the unmethylated one and was shown to bind with the blood cell surface, we studied the concentration, representation, and fragmentation of tumor-derived methylated DNA in cell-free and cell-surface-associated DNA. We found that long DNA fragments (more than 10 kb) are mainly associated with the surface of blood cells. However, in plasma short DNA fragments (100–1000 bp) were also found along with long DNA fragments. Isolation of short fragments after separation of cirDNA in 6% PAGE followed by quantitative PCR (L1 element) has shown that short DNA fragments in healthy females represent 22% versus 0.5–4.4% in breast cancer patients. The methylated form of the RARβ2 gene was detected only in long DNA fragments by Real-time TaqMan PCR of bisulfite-converted DNA. The methylation index of cirDNA from healthy women was estimated at 0%, 9%, and 7% in plasma, PBS-EDTA, and trypsin eluates from the surface of blood cells, respectively. The methylation index of breast cancer patients’ DNA was found to be 33%, 15%, and 61% in the same fractions confirming the overrepresentation of methylated DNA in csbDNA.

Just Add Data: automated predictive modeling for knowledge discovery and feature selection

Fully automated machine learning (AutoML) for predictive modeling is becoming a reality, giving rise to a whole new field. We present the basic ideas and principles of Just Add Data Bio (JADBio), an AutoML platform applicable to the low-sample, high-dimensional omics data that arise in translational medicine and bioinformatics applications. In addition to predictive and diagnostic models ready for clinical use, JADBio focuses on knowledge discovery by performing feature selection and identifying the corresponding biosignatures, i.e., minimal-size subsets of biomarkers that are jointly predictive of the outcome or phenotype of interest. It also returns a palette of useful information for interpretation, clinical use of the models, and decision making. JADBio is qualitatively and quantitatively compared against Hyper-Parameter Optimization Machine Learning libraries. Results show that in typical omics dataset analysis, JADBio manages to identify signatures comprising of just a handful of features while maintaining competitive predictive performance and accurate out-of-sample performance estimation.

The level of free-circulating mtDNA in patients with radon-induced lung cancer

OBJECTIVE

According to the World Health Organization, radon is the second leading cause of lung cancer after smoking. Cell free circulating mitochondrial DNA (cf mtDNA) have been used not only as a biomarker of carcinogenesis but also as a biomarker of exposure to radiation, but nothing is known about changes in the level of cf mtDNA following radon exposure. Therefore, the purpose of this study was to estimate the cf mtDNA copy number as a biomarker of the response to radon exposure in lung cancer pathogenesis.

METHODS

207 subjects were examined including 41 radon-exposed lung cancer patients, 40 lung cancer patients without radon exposure and 126 healthy controls exposed/not exposed to high level of radon. Total cell free circulating DNA from blood samples was extracted and used to detect cell free circulating mitochondrial DNA copy number by quantitative real-time polymerase chain reaction (qRT-PCR).

RESULTS

Our data indicate that the level of cf mtDNA in the radon-induced lung cancer patients was significantly higher than that of the other study participants. There was a significant difference in the level of cf mtDNA in the blood plasma of healthy volunteers exposed and not exposed to high doses of radon. Moreover, in healthy volunteers living in areas with high radon levels, the mtDNA copy number was higher than that in patients with lung cancer who were not exposed to high doses of radon.

CONCLUSION

Our study provides evidence for a possible role of cf mtDNA as a promising biomarker of lung cancer induced by exposure to high dose of radon.

Current and Developing Liquid Biopsy Techniques for Breast Cancer

Breast cancer is the most commonly diagnosed cancer and leading cause of cancer mortality among woman worldwide. The techniques of diagnosis, prognosis, and therapy monitoring of breast cancer are critical. Current diagnostic techniques are mammography and tissue biopsy; however, they have limitations. With the development of novel techniques, such as personalized medicine and genetic profiling, liquid biopsy is emerging as the less invasive tool for diagnosing and monitoring breast cancer. Liquid biopsy is performed by sampling biofluids and extracting tumor components, such as circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), cell-free mRNA (cfRNA) and microRNA (miRNA), proteins, and extracellular vehicles (EVs). In this review, we summarize and focus on the recent discoveries of tumor components and biomarkers applied in liquid biopsy and novel development of detection techniques, such as surface-enhanced Raman spectroscopy (SERS) and microfluidic devices.

ENPP2 Promoter Methylation Correlates with Decreased Gene Expression in Breast Cancer: Implementation as a Liquid Biopsy Biomarker

Autotaxin (ATX), encoded by the ctonucleotide pyrophosphatase/phosphodiesterase 2 (ENPP2) gene, is a key enzyme in lysophosphatidic acid (LPA) synthesis. We have recently described ENPP2 methylation profiles in health and multiple malignancies and demonstrated correlation to its aberrant expression. Here we focus on breast cancer (BrCa), analyzing in silico publicly available BrCa methylome datasets, to identify differentially methylated CpGs (DMCs) and correlate them with expression. Numerous DMCs were identified between BrCa and healthy breast tissues in the gene body and promoter-associated regions (PA). PA DMCs were upregulated in BrCa tissues in relation to normal, in metastatic BrCa in relation to primary, and in stage I BrCa in relation to normal, and this was correlated to decreased mRNA expression. The first exon DMC was also investigated in circulating cell free DNA (ccfDNA) isolated by BrCa patients; methylation was increased in BrCa in relation to ccfDNA from healthy individuals, confirming in silico results. It also differed between patient groups and was correlated to the presence of multiple metastatic sites. Our data indicate that promoter methylation of ENPP2 arrests its transcription in BrCa and introduce first exon methylation as a putative biomarker for diagnosis and monitoring which can be assessed in liquid biopsy.

Computational challenges in detection of cancer using cell-free DNA methylation

Cell-free DNA(cfDNA) methylation profiling is considered promising and potentially reliable for liquid biopsy to study progress of diseases and develop reliable and consistent diagnostic and prognostic biomarkers. There are several different mechanisms responsible for the release of cfDNA in blood plasma, and henceforth it can provide information regarding dynamic changes in the human body. Due to the fragmented nature, low concentration of cfDNA, and high background noise, there are several challenges in its analysis for regular use in diagnosis of cancer. Such challenges in the analysis of the methylation profile of cfDNA are further aggravated due to heterogeneity, biomarker sensitivity, platform biases, and batch effects. This review delineates the origin of cfDNA methylation, its profiling, and associated computational problems in analysis for diagnosis. Here we also contemplate upon the multi-marker approach to handle the scenario of cancer heterogeneity and explore the utility of markers for 5hmC based cfDNA methylation pattern. Further, we provide a critical overview of deconvolution and machine learning methods for cfDNA methylation analysis. Our review of current methods reveals the potential for further improvement in analysis strategies for detecting early cancer using cfDNA methylation.

ENPP2 Methylation in Health and Cancer

Autotaxin (ATX) encoded by Ectonucleotide Pyrophosphatase/Phosphodiesterase 2 (ENPP2) is a key enzyme in Lysophosphatidic Acid (LPA) synthesis implicated in cancer. Although its aberrant expression has been reported, ENPP2 methylation profiles in health and malignancy are not described. We examined in silico the methylation of ENPP2 analyzing publicly available methylome datasets, to identify Differentially Methylated CpGs (DMCs) which were then correlated with expression at gene and isoform levels. Significance indication was set to be FDR corrected p-value < 0.05. Healthy tissues presented methylation in all gene body CGs and lower levels in Promoter Associated (PA) regions, whereas in the majority of the tumors examined (HCC, melanoma, CRC, LC and PC) the methylation pattern was reversed. DMCs identified in the promoter were located in sites recognized by multiple transcription factors, suggesting involvement in gene expression. Alterations in methylation were correlated to an aggressive phenotype in cancer cell lines. In prostate and lung adenocarcinomas, increased methylation of PA CGs was correlated to decreased ENPP2 mRNA expression and to poor prognosis parameters. Collectively, our results corroborate that methylation is an active level of ATX expression regulation in cancer. Our study provides an extended description of the methylation status of ENPP2 in health and cancer and points out specific DMCs of value as prognostic biomarkers.

Methylation Status of Corticotropin-Releasing Factor (CRF) Receptor Genes in Colorectal Cancer

The corticotropin-releasing factor (CRF) system has been strongly associated with gastrointestinal pathophysiology, including colorectal cancer (CRC). We previously showed that altered expression of CRF receptors (CRFRs) in the colon critically affects CRC progression and aggressiveness through regulation of colonic inflammation. Here, we aimed to assess the potential of CRFR methylation levels as putative biomarkers in CRC. In silico methylation analysis of CRF receptor 1 (CRFR1) and CRF receptor 2 (CRFR2) was performed using methylome data derived by CRC and Crohn's disease (CD) tissues and CRC-derived circulating cell-free DNAs (ccfDNAs). In total, 32 and 33 differentially methylated sites of CpGs (DMCs) emerged in CRFR1 and CRFR2, respectively, between healthy and diseased tissues. The methylation patterns were verified in patient-derived ccfDNA samples by qMSP and associated with clinicopathological characteristics. An automated machine learning (AutoML) technology was applied to ccfDNA samples for classification analysis. In silico analysis revealed increased methylation of both CRFRs in CRC tissue and ccfDNA-derived datasets. CRFR1 hypermethylation was also noticed in gene body DMCs of CD patients. CRFR1 hypermethylation was further validated in CRC adjuvant-derived ccfDNA samples, whereas CRFR1 hypomethylation, observed in metastasis-derived ccfDNAs, was correlated to disease aggressiveness and adverse prognostic characteristics. AutoML analysis based on CRFRs methylation status revealed a three-feature high-performing biosignature for CRC diagnosis with an estimated AUC of 0.929. Monitoring of CRFRs methylation-based signature in CRC tissues and ccfDNAs may be of high diagnostic and prognostic significance in CRC.

Deciphering the Methylation Landscape in Breast Cancer: Diagnostic and Prognostic Biosignatures through Automated Machine Learning

DNA methylation plays an important role in breast cancer (BrCa) pathogenesis and could contribute to driving its personalized management. We performed a complete bioinformatic analysis in BrCa whole methylome datasets, analyzed using the Illumina methylation 450 bead-chip array. Differential methylation analysis vs. clinical end-points resulted in 11,176 to 27,786 differentially methylated genes (DMGs). Innovative automated machine learning (AutoML) was employed to construct signatures with translational value. Three highly performing and low-feature-number signatures were built: (1) A 5-gene signature discriminating BrCa patients from healthy individuals (area under the curve (AUC): 0.994 (0.982-1.000)). (2) A 3-gene signature identifying BrCa metastatic disease (AUC: 0.986 (0.921-1.000)). (3) Six equivalent 5-gene signatures diagnosing early disease (AUC: 0.973 (0.920-1.000)). Validation in independent patient groups verified performance. Bioinformatic tools for functional analysis and protein interaction prediction were also employed. All protein encoding features included in the signatures were associated with BrCa-related pathways. Functional analysis of DMGs highlighted the regulation of transcription as the main biological process, the nucleus as the main cellular component and transcription factor activity and sequence-specific DNA binding as the main molecular functions. Overall, three high-performance diagnostic/prognostic signatures were built and are readily available for improving BrCa precision management upon prospective clinical validation. Revisiting archived methylomes through novel bioinformatic approaches revealed significant clarifying knowledge for the contribution of gene methylation events in breast carcinogenesis.