Whole-genome bisulfite sequencing of cell-free DNA identifies signature associated with metastatic breast cancer

DNA methylation in breast cancer: early detection and biomarker discovery through current and emerging approaches

Breast cancer remains one of the most common cancers in women worldwide. Early detection is critical for improving patient outcomes, yet current screening methods have limitations. Therefore, there is a pressing need for more sensitive and specific approaches to detect breast cancer in its earliest stages. Liquid biopsy has emerged as a promising non-invasive method for early cancer detection and management. DNA methylation, an epigenetic alteration that often precedes genetic changes, has been observed in precancerous or early cancer stages, making it a valuable biomarker. This review explores the role of DNA methylation in breast cancer and its potential for developing blood-based tests. We discuss advancements in DNA methylation detection methods, recent discoveries of potential DNA methylation biomarkers from both single-omics and multi-omics integration studies, and the role of machine learning in enhancing diagnostic accuracy. Challenges and future directions are also addressed. Although challenges remain, advances in multi-omics integration and machine learning continue to enhance the clinical potential of methylation-based biomarkers. Ongoing research is crucial to further refine these approaches and improve early detection and patient outcomes.

Noninvasive Multicancer Detection Using DNA Hypomethylation of LINE-1 Retrotransposons

PURPOSE

The detection of ctDNA, which allows noninvasive tumor molecular profiling and disease follow-up, promises optimal and individualized management of patients with cancer. However, detecting small fractions of tumor DNA released when the tumor burden is reduced remains a challenge.

EXPERIMENTAL DESIGN

We implemented a new, highly sensitive strategy to detect bp resolution methylation patterns from plasma DNA and assessed the potential of hypomethylation of long interspersed nuclear element-1 retrotransposons as a noninvasive multicancer detection biomarker. The Detection of Long Interspersed Nuclear Element Altered Methylation ON plasma DNA method targets 30 to 40,000 young long interspersed nuclear element-1 retrotransposons scattered throughout the genome, covering about 100,000 CpG sites and is based on a reference-free analysis pipeline.

RESULTS

Resulting machine learning-based classifiers showed powerful correct classification rates discriminating healthy and tumor plasmas from six types of cancers (colorectal, breast, lung, ovarian, and gastric cancers and uveal melanoma, including localized stages) in two independent cohorts (AUC = 88%-100%, N = 747). The Detection of Long Interspersed Nuclear Element Altered Methylation ON plasma DNA method can also be used to perform copy number alteration analysis that improves cancer detection.

CONCLUSIONS

This should lead to the development of more efficient noninvasive diagnostic tests adapted to all patients with cancer, based on the universality of these factors. See related commentary by Szymanski et al., p. 1179.

Transcorneal electrical stimulation restores DNA methylation changes in retinal degeneration

Background

Retinal degeneration is a major cause of irreversible blindness. Stimulation with controlled low-level electrical fields, such as transcorneal electrical stimulation (TES), has recently been postulated as a therapeutic strategy. With promising results, there is a need for detailed molecular characterization of the therapeutic effects of TES.

Methods

Controlled, non-invasive TES was delivered using a custom contact lens electrode to the retinas of Royal College of Surgeons (RCS) rats, a model of retinal degeneration. DNA methylation in the retina, brain and cell-free DNA in plasma was assessed by reduced representation bisulfite sequencing (RRBS) and gene expression by RNA sequencing.

Results

TES induced DNA methylation and gene expression changes implicated in neuroprotection in the retina of RCS rats. We devised an epigenomic-based retinal health score, derived from DNA methylation changes observed with disease progression in RCS rats, and showed that TES improved the epigenomic health of the retina. TES also induced DNA methylation changes in the superior colliculus: the brain which is involved in integrating visual signaling. Lastly, we demonstrated that TES-induced retinal DNA methylation changes were detectable in cell-free DNA derived from plasma.

Conclusion

TES induced DNA methylation changes with therapeutic effects, which can be measured in circulation. Based on these changes, we were able to devise a liquid biopsy biomarker for retinal health. These findings shed light on the therapeutic potential and molecular underpinnings of TES, and provide a foundation for the further development of TES to improve the retinal health of patients with degenerative eye diseases.

Mapping the epigenomic landscape of post-traumatic stress disorder in human cortical neurons

The study conducted a comprehensive genome-wide analysis of differential 5mC and 5hmC modifications at both CpG and non-CpG sites in postmortem orbitofrontal neurons from 25 PTSD cases and 13 healthy controls. It was observed that PTSD patients exhibit a greater number of differential 5hmC sites compared to 5mC sites. Specifically, individuals with PTSD tend to show hyper-5mC/5hmC at CpG sites, particularly within CpG islands and promoter regions, and hypo-5mC/5hmC at non-CpG sites, especially within intragenic regions. Functional enrichment analysis indicated distinct yet interconnected roles for 5mC and 5hmC in PTSD. The 5mC marks primarily regulate cell-cell adhesion processes, whereas 5hmC marks are involved in embryonic morphogenesis and cell fate commitment. By integrating published PTSD findings from central and peripheral tissues through multi-omics approaches, several biological mechanisms were prioritized, including developmental processes, HPA axis regulation, and immune responses. Based on the consistent enrichment in developmental processes, we hypothesize that if epigenetic changes occur during early developmental stages, they may increase the risk of developing PTSD following trauma exposure. Conversely, if these epigenetic changes occur in adulthood, they may influence neuronal apoptosis and survival mechanisms.

A comprehensive analysis of minimally differentially methylated regions common to pediatric and adult solid tumors

Cancer is the second most common cause of death in children aged 1-14 years in the United States, with 11,000 new cases and 1200 deaths annually. Pediatric cancers typically have lower mutational burden compared to adult-onset cancers, however, the epigenomes in pediatric cancer are highly altered, with widespread DNA methylation changes. The rarity of pediatric cancers poses a significant challenge to developing cancer-type specific biomarkers for diagnosis, prognosis, or treatment monitoring. In the current study, we explored the potential of a DNA methylation profile common across various pediatric cancers. To do this, we conducted whole genome bisulfite sequencing (WGBS) on 31 recurrent pediatric tumor tissues, 13 normal tissues, and 20 plasma cell-free (cf)DNA samples, representing 11 different pediatric cancer types. We defined minimal focal regions that were differentially methylated across samples in the multiple cancer types which we termed minimally differentially methylated regions (mDMRs). These methylation changes were also observed in 506 pediatric and 5691 adult cancer samples accessed from publicly available databases, and in 44 pediatric cancer samples we analyzed using a targeted hybridization probe capture assay. Finally, we found that these methylation changes were detectable in cfDNA and could serve as potential cfDNA methylation biomarkers for early detection or minimal residual disease.

Lambda3: homology search for protein, nucleotide, and bisulfite-converted sequences

MOTIVATION

Local alignments of query sequences in large databases represent a core part of metagenomic studies and facilitate homology search. Following the development of NCBI Blast, many applications aimed to provide faster and equally sensitive local alignment frameworks. Most applications focus on protein alignments, while only few also facilitate DNA-based searches. None of the established programs allow searching DNA sequences from bisulfite sequencing experiments commonly used for DNA methylation profiling, for which specific alignment strategies need to be implemented.

RESULTS

Here, we introduce Lambda3, a new version of the local alignment application Lambda. Lambda3 is the first solution that enables the search of protein, nucleotide as well as bisulfite-converted nucleotide query sequences. Its protein mode achieves comparable performance to that of the highly optimized protein alignment application Diamond, while the nucleotide mode consistently outperforms established local nucleotide aligners. Combined, Lambda3 presents a universal local alignment framework that enables fast and sensitive homology searches for a wide range of use-cases.

AVAILABILITY AND IMPLEMENTATION

Lambda3 is free and open-source software publicly available at https://github.com/seqan/lambda/.

Dissemination of Circulating Tumor Cells in Breast and Prostate Cancer: Implications for Early Detection

Burgeoning evidence suggests that circulating tumor cells (CTCs) may disseminate into blood vessels at an early stage, seeding metastases in various cancers such as breast and prostate cancer. Simultaneously, the early-stage CTCs that settle in metastatic sites [termed disseminated tumor cells (DTCs)] can enter dormancy, marking a potential source of late recurrence and therapy resistance. Thus, the presence of these early CTCs poses risks to patients but also holds potential benefits for early detection and treatment and opportunities for possibly curative interventions. This review delves into the role of early DTCs in driving latent metastasis within breast and prostate cancer, emphasizing the importance of early CTC detection in these diseases. We further explore the correlation between early CTC detection and poor prognoses, which contribute significantly to increased cancer mortality. Consequently, the detection of CTCs at an early stage emerges as a critical imperative for enhancing clinical diagnostics and allowing for early interventions.

OvaPrint-A Cell-free DNA Methylation Liquid Biopsy for the Risk Assessment of High-grade Serous Ovarian Cancer

PURPOSE

High-grade serous ovarian carcinoma (HGSOC) is the most lethal epithelial ovarian cancer (EOC) and is often diagnosed at late stage. In women with a known pelvic mass, surgery followed by pathologic assessment is the most reliable way to diagnose EOC and there are still no effective screening tools in asymptomatic women. In the current study, we developed a cell-free DNA (cfDNA) methylation liquid biopsy for the risk assessment of early-stage HGSOC.

EXPERIMENTAL DESIGN

We performed reduced representation bisulfite sequencing to identify differentially methylated regions (DMR) between HGSOC and normal ovarian and fallopian tube tissue. Next, we performed hybridization probe capture for 1,677 DMRs and constructed a classifier (OvaPrint) on an independent set of cfDNA samples to discriminate HGSOC from benign masses. We also analyzed a series of non-HGSOC EOC, including low-grade and borderline samples to assess the generalizability of OvaPrint. A total of 372 samples (tissue n = 59, plasma n = 313) were analyzed in this study.

RESULTS

OvaPrint achieved a positive predictive value of 95% and a negative predictive value of 88% for discriminating HGSOC from benign masses, surpassing other commercial tests. OvaPrint was less sensitive for non-HGSOC EOC, albeit it may have potential utility for identifying low-grade and borderline tumors with higher malignant potential.

CONCLUSIONS

OvaPrint is a highly sensitive and specific test that can be used for the risk assessment of HGSOC in symptomatic women. Prospective studies are warranted to validate OvaPrint for HGSOC and further develop it for non-HGSOC EOC histotypes in both symptomatic and asymptomatic women with adnexal masses.

Advances in the study of biomarkers related to bone metastasis in breast cancer

Breast cancer is by far the most common malignancy in females. And bone is the most common site of distant metastasis in breast cancer, accounting for about 65 to 75% of all metastatic breast cancer patients.1,2Bone metastasis is an important factor affecting the prognosis of breast cancer. When patients have early-stage breast cancer without metastasis, their 5-year survival rate is as high as 90%, and once metastasis occurs, their 5-year survival rate will drop to 10%.3 Bone radionuclide imaging (ECT), X-ray, CT scan, MRI and other imaging tests to diagnose breast cancer bone metastasis are commonly used in clinical, It is currently believed that breast cancer bone metastasis is a multistep process: first, breast cancer cells need to acquire invasive and metastatic properties; breast cancer cells enter the blood circulation and migrate from blood breast cancer cells enter the blood circulation and migrate from blood vessels to bone tissue in a targeted manner; breast cancer cells adhere and remain in bone tissue and colonise it; and finally, it leads to bone destruction.4 Several key molecules are involved in breast cancer bone metastasis, and serum biomarkers are generally able to detect pathological changes earlier Several key molecules are involved in breast cancer bone metastasis, and serum biomarkers are generally able to detect pathological changes earlier than imaging.5 This review describes the progress of serum biomarkers for breast cancer bone metastasis.

Minimal residual disease in solid tumors: an overview

Minimal residual disease (MRD) is termed as the small numbers of remnant tumor cells in a subset of patients with tumors. Liquid biopsy is increasingly used for the detection of MRD, illustrating the potential of MRD detection to provide more accurate management for cancer patients. As new techniques and algorithms have enhanced the performance of MRD detection, the approach is becoming more widely and routinely used to predict the prognosis and monitor the relapse of cancer patients. In fact, MRD detection has been shown to achieve better performance than imaging methods. On this basis, rigorous investigation of MRD detection as an integral method for guiding clinical treatment has made important advances. This review summarizes the development of MRD biomarkers, techniques, and strategies for the detection of cancer, and emphasizes the application of MRD detection in solid tumors, particularly for the guidance of clinical treatment.

Graft-Derived Cell-Free DNA Quantification following Liver Transplantation Using Tissue-Specific DNA Methylation and Donor-Specific Genotyping Techniques: An Orthogonal Comparison Study

Background: Graft-derived cell-free DNA (gdcfDNA) analysis has shown promise as a non-invasive tool for monitoring organ health following solid organ transplantation. A number of gdcfDNA analysis techniques have been described; however, the majority rely on sequencing or prior genotyping to detect donor-recipient mis-matched genetic polymorphisms. Differentially methylated regions of DNA can be used to identify the tissue-of-origin of cell-free DNA (cfDNA) fragments. In this study, we aimed to directly compare the performance of gdcfDNA monitoring using graft-specific DNA methylation analysis and donor-recipient genotyping techniques in a pilot cohort of clinical samples from patients post-liver transplantation. Results: 7 patients were recruited prior to LT, 3 developed early, biopsy-proven TCMR in the first 6 weeks post-LT. gdcfDNA was successfully quantified in all samples using both approaches. There was a high level of technical correlation between results using the two techniques (Spearman testing, r_s = 0.87, p < 0.0001). gdcfDNA levels quantified using the genotyping approach were significantly greater across all timepoints in comparison to the tissue-specific DNA methylation-based approach: e.g., day 1 post-LT median 31,350 copies/mL (IQR 6731-64,058) vs. 4133 copies/mL (IQR 1100-8422), respectively. Qualitative trends in gdcfDNA levels for each patient were concordant between the two assays. Acute TCMR was preceded by significant elevations in gdcfDNA as quantified by both techniques. Elevations in gdcfDNA, using both techniques, were suggestive of TCMR in this pilot study with a 6- and 3-day lead-time prior to histological diagnosis in patients 1 and 2. Conclusions: Both the graft-specific methylation and genotyping techniques successfully quantified gdcfDNA in patients post-LT with statistically significant concordance. A direct comparison of these two techniques is not only important from a technical perspective for orthogonal validation, but significantly adds weight to the evidence that gdcfDNA monitoring reflects the underlying biology. Both techniques identified LT recipients who developed acute TCMR, with several days lead-time in comparison to conventional diagnostic workflows. Whilst the two assays performed comparably, gdcfDNA monitoring based on graft-specific DNA methylation patterns in cfDNA offers major practical advantages over the donor-recipient genotyping, and hence enhances the potential to translate this emerging technology into clinical practice.

Circulating cell-free DNA methylation mirrors alterations in cerebral patterns in epilepsy

BACKGROUND

DNA methylation profiling of circulating cell-free DNA (cfDNA) has rapidly become a promising strategy for biomarker identification and development. The cell-type-specific nature of DNA methylation patterns and the direct relationship between cfDNA and apoptosis can potentially be used non-invasively to predict local alterations. In addition, direct detection of altered DNA methylation patterns performs well as a biomarker. In a previous study, we demonstrated marked DNA methylation alterations in brain tissue from patients with mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS).

RESULTS

We performed DNA methylation profiling in cfDNA isolated from the serum of MTLE patients and healthy controls using BeadChip arrays followed by systematic bioinformatic analysis including deconvolution analysis and integration with DNase accessibility data sets. Differential cfDNA methylation analysis showed an overrepresentation of gene ontology terms and transcription factors related to central nervous system function and regulation. Deconvolution analysis of the DNA methylation data sets ruled out the possibility that the observed differences were due to changes in the proportional contribution of cortical neurons in cfDNA. Moreover, we found no overrepresentation of neuron- or glia-specific patterns in the described cfDNA methylation patterns. However, the MTLE-HS cfDNA methylation patterns featured a significant overrepresentation of the epileptic DNA methylation alterations previously observed in the hippocampus.

CONCLUSIONS

Our results support the use of cfDNA methylation profiling as a rational approach to seeking non-invasive and reproducible epilepsy biomarkers.

Targeted DNA methylation from cell-free DNA using hybridization probe capture

Cell-free (cf)DNA signatures are quickly becoming the target of choice for non-invasive screening, diagnosis, treatment and monitoring of human tumors. DNA methylation changes occur early in tumorigenesis and are widespread, making cfDNA methylation an attractive cancer biomarker. Already a proven technology for targeted genome sequencing, hybridization probe capture is emerging as a method for high-throughput targeted methylation profiling suitable to liquid biopsy samples. However, to date there are no reports describing the performance of this approach in terms of reproducibility, scalability, and accuracy. In the current study we performed hybridization probe capture using the myBaits® Custom Methyl-seq kit on 172 plasma samples and standards to evaluate its performance on cfDNA methylation analysis. The myBaits® assay showed high target recovery (>90%), demonstrated excellent reproducibility between captures (R 2 = 0.92 on average), and was unaffected by increasing the number of targets in a capture. Finally, myBaits® accurately replicated 'gold standard' beta values from WGBS (average R 2 = 0.79). The results of this study show that custom targeted methylation sequencing with myBaits® offers a cost-effective, reliable platform to profile DNA methylation at a set of discrete custom regions, with potential applicability to liquid biopsies for cancer monitoring.

Cell-Free DNA Fragmentomics: A Promising Biomarker for Diagnosis, Prognosis and Prediction of Response in Breast Cancer

Identifying novel circulating biomarkers predictive of response and informative about the mechanisms of resistance, is the new challenge for breast cancer (BC) management. The integration of omics information will gradually revolutionize the clinical approach. Liquid biopsy is being incorporated into the diagnostic and decision-making process for the treatment of BC, in particular with the analysis of circulating tumor DNA, although with some relevant limitations, including costs. Circulating cell-free DNA (cfDNA) fragmentomics and its integrity index may become a cheaper, noninvasive biomarker that could provide significant additional information for monitoring response to systemic treatments in BC. The purpose of our review is to focus on the available research on cfDNA integrity and its features as a biomarker of diagnosis, prognosis and response to treatments in BC, highlighting new perspectives and critical issues for future applications.

Whole-genome circulating tumor DNA methylation landscape reveals sensitive biomarkers of breast cancer

The changes in circulating tumor DNA (ctDNA) methylation are believed to be early events in breast cancer initiation, which makes them suitable as promising biomarkers for early diagnosis. However, applying ctDNA in breast cancer early diagnosis remains highly challenging due to the contamination of background DNA from blood and low DNA methylation signals. Here, we report an improved way to extract ctDNA, reduce background contamination, and build a whole-genome bisulfite sequencing (WGBS) library from different stages of breast cancer. We first compared the DNA methylation data of 74 breast cancer patients with those of seven normal controls to screen candidate methylation CpG site biomarkers for breast cancer diagnosis. The obtained 26 candidate ctDNA methylation biomarkers produced high accuracy in breast cancer patients (area under the curve [AUC] = 0.889; sensitivity: 100%; specificity: 75%). Furthermore, we revealed potential ctDNA methylated CpG sites for detecting early-stage breast cancer (AUC = 0.783; sensitivity: 93.44%; specificity: 50%). In addition, different subtypes of breast cancer could be well distinguished by the ctDNA methylome, which was obtained through our improved ctDNA-WGBS method. Overall, we identified high specificity and sensitivity breast cancer-specific methylation CpG site biomarkers, and they will be expected to have the potential to be translated to clinical practice.

Methylated ccfDNA from plasma biomarkers of Alzheimer's disease using targeted bisulfite sequencing

Aim: Noninvasive biomarkers such as methylated ccfDNA from plasma could help to support the diagnosis of Alzheimer's disease (AD). Methods: A targeted sequencing protocol was developed to identify candidate biomarkers of AD in methylated ccfDNA extracted from plasma. Results: The authors identified differentially methylated CpGs, regions of which were the same as those identified in previous AD studies. Specifically, a differentially methylated CpG of the LHX2 gene previously identified in a plasma study of AD was replicated in the study. The MBP and DUSP22 regions have been identified in other brain studies of AD and in the authors' study. Conclusion: Although these biomarkers must be validated in other cohorts, methylated ccfDNA could be a relevant noninvasive biomarker in AD.

The Potential of Circulating Cell-Free DNA Methylation as an Epilepsy Biomarker

Circulating cell-free DNA (cfDNA) are highly degraded DNA fragments shed into the bloodstream. Apoptosis is likely to be the main source of cfDNA due to the matching sizes of cfDNA and apoptotic DNA cleavage fragments. The study of cfDNA in liquid biopsies has served clinical research greatly. Genetic analysis of these circulating fragments has been used in non-invasive prenatal testing, detection of graft rejection in organ transplants, and cancer detection and monitoring. cfDNA sequencing is, however, of limited value in settings in which genetic association is not well-established, such as most neurodegenerative diseases.Recent studies have taken advantage of the cell-type specificity of DNA methylation to determine the tissue of origin, thus detecting ongoing cell death taking place in specific body compartments. Such an approach is yet to be developed in the context of epilepsy research. In this article, we review the different approaches that have been used to monitor cell-type specific death through DNA methylation analysis, and recent data detecting neuronal death in neuropathological settings. We focus on the potential relevance of these tools in focal epilepsies, like Mesial Temporal Lobe Epilepsy with Hippocampal Sclerosis (MTLE-HS), characterized by severe neuronal loss. We speculate on the potential relevance of cfDNA methylation screening for the detection of neuronal cell death in individuals with high risk of epileptogenesis that would benefit from early diagnosis and consequent early treatment.

Epigenetic Therapies and Biomarkers in Breast Cancer

Epigenetic therapies remain a promising, but still not widely used, approach in the management of patients with cancer. To date, the efficacy and use of epigenetic therapies has been demonstrated primarily in the management of haematological malignancies, with limited supportive data in solid malignancies. The most studied epigenetic therapies in breast cancer are those that target DNA methylation and histone modification; however, none have been approved for routine clinical use. The majority of pre-clinical and clinical studies have focused on triple negative breast cancer (TNBC) and hormone-receptor positive breast cancer. Even though the use of epigenetic therapies alone in the treatment of breast cancer has not shown significant clinical benefit, these therapies show most promise in use in combinations with other treatments. With improving technologies available to study the epigenetic landscape in cancer, novel epigenetic alterations are increasingly being identified as potential biomarkers of response to conventional and epigenetic therapies. In this review, we describe epigenetic targets and potential epigenetic biomarkers in breast cancer, with a focus on clinical trials of epigenetic therapies. We describe alterations to the epigenetic landscape in breast cancer and in treatment resistance, highlighting mechanisms and potential targets for epigenetic therapies. We provide an updated review on epigenetic therapies in the pre-clinical and clinical setting in breast cancer, with a focus on potential real-world applications. Finally, we report on the potential value of epigenetic biomarkers in diagnosis, prognosis and prediction of response to therapy, to guide and inform the clinical management of breast cancer patients.

Highly expressed centromere protein L indicates adverse survival and associates with immune infiltration in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is characterized by rapid progression, high recurrence rate and poor prognosis. Early prediction for the prognosis and immunotherapy efficacy is of great significance to improve the survival of HCC patients. However, there is still no reliable predictor at present. This study is aimed to explore the role of centromere protein L (CENPL) in predicting prognosis and its association with immune infiltration in HCC.

METHODS

The expression of CENPL was identified through analyzing the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data. The association between CENPL expression and clinicopathological features was investigated by the Wilcoxon signed-rank test or Kruskal Wallis test and logistic regression. The role of CENPL in prognosis was examined via Kaplan-Meier method and Log-rank test as well as univariate and multivariate Cox regression analysis. Besides, in TIMER and GEPIA database, we investigated the correlation between CENPL level and immunocyte and immunocyte markers, and the prognostic-related methylation sites in CENPL were identified by MethSurv.

RESULTS

CENPL had a high expression in HCC samples. Increased CENPL was prominently associated with unfavorable survival, and maybe an independent prognostic factor of worse overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), progression-free interval (PFI). Additionally, CENPL expression was significantly correlated with immune cell infiltration and some markers. CENPL also contained a methylation site that was notably related to poor prognosis.

CONCLUSIONS

Elevated CENPL may be a promising prognostic marker and associate with immune infiltration in HCC.

Circulating Cell-Free DNA Methylation Profiles in the Early Detection of Ovarian Cancer: A Scoping Review of the Literature

Epithelial ovarian cancer is the most lethal gynecologic malignancy and has few reliable non-invasive tests for early detection or diagnosis. Recent advances in genomic techniques have bolstered the utility of cell-free DNA (cfDNA) evaluation from peripheral blood as a viable cancer biomarker. For multiple reasons, comparing alterations in DNA methylation is particularly advantageous over other molecular assays. We performed a literature review for studies exploring cfDNA methylation in serum and plasma for the early diagnosis of ovarian cancer. The data suggest that serum/plasma cfDNA methylation tests have strong diagnostic accuracies for ovarian cancer (median 85%, range 40-91%). Moreover, there is improved diagnostic performance if multiple genes are used and if the assays are designed to compare detection of ovarian cancer with benign pelvic masses. We further highlight the vast array of possible gene targets and techniques, and a need to include more earlier-stage ovarian cancer samples in test development. Overall, we show the promise of cfDNA methylation analysis in the development of a viable diagnostic biomarker for ovarian cancer.

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

Simple Summary

Our research focuses in the elucidation of the nature of circulating cell-free DNA (ccfDNA) as a biological entity and its exploitation as a liquid biopsy biomaterial. Working on breast cancer, it became clear that although a promising biosource, its clinical exploitation is burdened mainly by gaps in knowledge about its biology and specific characteristics. The current review covers multiple aspects of ccfDNA in breast cancer. We cover key issues such as quantity, integrity, releasing structures, methylation specific changes, release mechanisms, biological role. Machine learning approaches for analyzing ccfDNA-generated data to produce classifiers for clinical use are also discussed.

Abstract

Breast cancer (BC) is a leading cause of death between women. Mortality is significantly raised due to drug resistance and metastasis, while personalized treatment options are obstructed by the limitations of conventional biopsy follow-up. Lately, research is focusing on circulating biomarkers as minimally invasive choices for diagnosis, prognosis and treatment monitoring. Circulating cell-free DNA (ccfDNA) is a promising liquid biopsy biomaterial of great potential as it is thought to mirror the tumor’s lifespan; however, its clinical exploitation is burdened mainly by gaps in knowledge of its biology and specific characteristics. The current review aims to gather latest findings about the nature of ccfDNA and its multiple molecular and biological characteristics in breast cancer, covering basic and translational research and giving insights about its validity in a clinical setting.

Epigenetic Landscape of Liquid Biopsy in Colorectal Cancer

Colorectal cancer (CRC) is one of the most common malignancies and is a major cause of cancer-related deaths worldwide. Thus, there is a clinical need to improve early detection of CRC and personalize therapy for patients with this disease. In the era of precision oncology, liquid biopsy has emerged as a major approach to characterize the circulating tumor elements present in body fluids, including cell-free DNA and RNA, circulating tumor cells, and extracellular vesicles. This non-invasive tool has allowed the identification of relevant molecular alterations in CRC patients, including some indicating the disruption of epigenetic mechanisms. Epigenetic alterations found in solid and liquid biopsies have shown great utility as biomarkers for early detection, prognosis, monitoring, and evaluation of therapeutic response in CRC patients. Here, we summarize current knowledge of the most relevant epigenetic mechanisms associated with cancer development and progression, and the implications of their deregulation in cancer cells and liquid biopsy of CRC patients. In particular, we describe the methodologies used to analyze these epigenetic alterations in circulating tumor material, and we focus on the clinical utility of epigenetic marks in liquid biopsy as tumor biomarkers for CRC patients. We also discuss the great challenges and emerging opportunities of this field for the diagnosis and personalized management of CRC patients.

Cell-Free DNA-Methylation-Based Methods and Applications in Oncology

Liquid biopsy based on cell-free DNA (cfDNA) enables non-invasive dynamic assessment of disease status in patients with cancer, both in the early and advanced settings. The analysis of DNA-methylation (DNAm) from cfDNA samples holds great promise due to the intrinsic characteristics of DNAm being more prevalent, pervasive, and cell- and tumor-type specific than genomics, for which established cfDNA assays already exist. Herein, we report on recent advances on experimental strategies for the analysis of DNAm in cfDNA samples. We describe the main steps of DNAm-based analysis workflows, including pre-analytics of cfDNA samples, DNA treatment, assays for DNAm evaluation, and methods for data analysis. We report on protocols, biomolecular techniques, and computational strategies enabling DNAm evaluation in the context of cfDNA analysis, along with practical considerations on input sample requirements and costs. We provide an overview on existing studies exploiting cell-free DNAm biomarkers for the detection and monitoring of cancer in early and advanced settings, for the evaluation of drug resistance, and for the identification of the cell-of-origin of tumors. Finally, we report on DNAm-based tests approved for clinical use and summarize their performance in the context of liquid biopsy.

Age-related DNA methylation in paired normal and tumour breast tissue in Chinese breast cancer patients

Age-related DNA methylation is a potential mechanism contributing to breast cancer development. Studies of primarily Caucasian women have identified many CpG sites of age-related methylation in non-diseased breast tissue possibly driving cancer development over time. There is a paucity of studies involving Asian women whose ages at breast cancer onset are usually younger than Caucasians. We identified the 181 most consistent age-related methylation events in non-diseased breast tissue across published studies. Age-related methylation events were measured in adjacent normal and breast tumour tissue in an exclusively Asian population at the previously identified age-related methylation sites. Age-related methylation was found in 118 probes in adjacent normal breast tissue. Methylation of 99% of these sites was increased with age and predominantly located on CpG islands in promoter regions. To ascertain biological relevance to breast cancer, we focused on the 37 sites with overall higher methylation in tumour compared to adjacent normal samples. Some sites positively related to age, including AQP5 and CORO6, inversely correlated with gene expression. Several others have known involvement in suppression of carcinogenesis including GPC5 and SST, suggesting that perturbation of epigenetic regulation at these sites due to ageing may contribute to the progression of carcinogenesis. This study highlights an age-related methylation landscape in non-tumour tissue, consistent not just across studies, but also across different populations. We present candidate age-related methylation sites warranting further investigation as potential epigenetic drivers of breast cancer. They may serve as potential targets of site-specific demethylation intervention strategies for the prevention of age-related breast cancer.

Blood DNA Methylation and Breast Cancer: A Prospective Case-Cohort Analysis in the Sister Study

BACKGROUND

Peripheral blood DNA methylation may be associated with breast cancer, but studies of candidate genes and global and genome-wide DNA methylation have been inconsistent.

METHODS

We performed an epigenome-wide study using Infinium HumanMethylation450 BeadChips with prospectively collected blood DNA samples from the Sister Study (1552 cases, 1224 subcohort). Differentially methylated cytosine-phosphate-guanine sites (dmCpGs) were identified using case-cohort proportional hazard models and replicated using deposited data from European Prospective Investigation into Cancer and Nutrition in Italy (EPIC-Italy) (n = 329). The correlation between methylation and time to diagnosis was examined using robust linear regression. Causal or consequential relationships of methylation to breast cancer were examined by Mendelian randomization using OncoArray 500 K single-nucleotide polymorphism data. All statistical tests were two-sided.

RESULTS

We identified 9601 CpG markers associated with invasive breast cancer (false discovery rate = q < 0.01), with 510 meeting a strict Bonferroni correction threshold (10-7). A total of 2095 of these CpGs replicated in the independent EPIC-Italy dataset, including 144 meeting the Bonferroni threshold. Sister Study women who developed ductal carcinoma in situ had methylation similar to noncases. Most (1501, 71.6%) dmCpGs showed lower methylation in invasive cases. In case-only analysis, methylation was statistically significantly associated (false discovery rate = q < 0.05) with time to diagnosis for 892 (42.6%) of the dmCpGs. Analyses based on genetic association suggest that methylation differences are likely a consequence rather than a cause of breast cancer. Pathway analysis shows enrichment of breast cancer-related gene pathways, and dmCpGs are overrepresented in known breast cancer susceptibility genes.

CONCLUSIONS

Our findings suggest that the DNA methylation profile of blood starts to change in response to invasive breast cancer years before the tumor is clinically detected.

A FACS-based approach to obtain viable eosinophils from human adipose tissue

Eosinophils have been widely investigated in asthma and allergic diseases. More recently, new insights into the biology of these cells has illustrated eosinophils contribute to homeostatic functions in health such as regulation of adipose tissue glucose metabolism. Human translational studies are limited by the difficulty of obtaining cells taken directly from their tissue environment, relying instead on eosinophils isolated from peripheral blood. Isolation techniques for tissue-derived eosinophils can result in unwanted cell or ribonuclease activation, leading to poor cell viability or RNA quality, which may impair analysis of effector activities of these cells. Here we demonstrate a technique to obtain eosinophils from human adipose tissue samples for the purpose of downstream molecular analysis. From as little as 2 g of intact human adipose tissue, greater than 10⁴ eosinophils were purified by fluorescence-activated cell sorting (FACS) protocol resulting in ≥ 99% purity and ≥ 95% viable eosinophils. We demonstrated that the isolated eosinophils could undergo epigenetic analysis to determine differences in DNA methylation in various settings. Here we focused on comparing eosinophils isolated from human peripheral blood vs human adipose tissue. Our results open the door to future mechanistic investigations to better understand the role of tissue resident eosinophils in different context.

ABCC9, NKAPL, and TMEM132C are potential diagnostic and prognostic markers in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a highly heterogeneous disease. The aim of this study is to identify the diagnostic and poor prognostic signatures in TNBC by exploring the aberrant DNA methylation and gene expression. Differential expression and methylation analysis of the TNBC and paracancer samples from The Cancer Genome Atlas were performed. Gene set enrichment and protein-protein interaction (PPI) network analysis was used to explore the mechanisms of TNBC. Methylation-gene expression correlation analysis was performed, and multivariate Cox analysis and receiver operating characteristics analysis were used to further screen the hub genes for TNBC. We identified 1,525 differentially expressed genes and 150 differentially methylated genes between TNBC and paracancer samples. About 96.64% of the methylation sites were located on the CpG island. A total of 17 Gene Ontology biological process terms and 18 signal pathways were significantly enriched. GNG4, GNG11, PENK, MAOA, and AOX1 were identified as the core genes of the PPI network. Methylation-expression correlations revealed that ABCC9 (cg06951626), NKAPL (cg18675097, cg01031101, and cg17384889), and TMEM132C (cg03530754) showed promise as diagnostic and prognostic markers in TNBC. ABCC9 (cg06951626), NKAPL (cg18675097, cg01031101, and cg17384889), and TMEM132C (cg03530754) were potential diagnostic and prognostic markers in TNBC.

Induction of DNMT3B by PGE2 and IL6 at Distant Metastatic Sites Promotes Epigenetic Modification and Breast Cancer Colonization

Current cancer treatments are largely based on the genetic characterization of primary tumors and are ineffective for metastatic disease. Here we report that DNA methyltransferase 3B (DNMT3B) is induced at distant metastatic sites and mediates epigenetic reprogramming of metastatic tumor cells. Multiomics analysis and spontaneous metastatic mouse models revealed that DNMT3B alters multiple pathways including STAT3, NFκB, PI3K/Akt, β-catenin, and Notch signaling, which are critical for cancer cell survival, apoptosis, proliferation, invasion, and colonization. PGE2 and IL6 were identified as critical inflammatory mediators in DNMT3B induction. DNMT3B expression levels positively correlated with human metastatic progression. Targeting IL6 or COX-2 reduced DNMT3B induction and improved chemo or PD1 therapy. We propose a novel mechanism linking the metastatic microenvironment with epigenetic alterations that occur at distant sites. These results caution against the "Achilles heel" in cancer therapies based on primary tumor characterization and suggests targeting DNMT3B induction as new option for treating metastatic disease. SIGNIFICANCE: These findings reveal that DNMT3B epigenetically regulates multiple pro-oncogenic signaling pathways via the inflammatory microenvironment at distant sites, cautioning the clinical approach basing current therapies on genetic characterization of primary tumors.

Disease prediction by cell-free DNA methylation

Disease diagnosis using cell-free DNA (cfDNA) has been an active research field recently. Most existing approaches perform diagnosis based on the detection of sequence variants on cfDNA; thus, their applications are limited to diseases associated with high mutation rate such as cancer. Recent developments start to exploit the epigenetic information on cfDNA, which could have substantially wider applications. In this work, we provide thorough reviews and discussions on the statistical method developments and data analysis strategies for using cfDNA epigenetic profiles, in particular DNA methylation, to construct disease diagnostic models. We focus on two important aspects: marker selection and prediction model construction, under different scenarios. We perform simulations and real data analysis to compare different approaches, and provide recommendations for data analysis.

'Omics Approaches to Explore the Breast Cancer Landscape

Breast cancer incidence is increasing worldwide with more than 600,000 deaths reported in 2018 alone. In current practice treatment options for breast cancer patients consists of surgery, chemotherapy, radiotherapy or targeting of classical markers of breast cancer subtype: estrogen receptor (ER) and HER2. However, these treatments fail to prevent recurrence and metastasis. Improved understanding of breast cancer and metastasis biology will help uncover novel biomarkers and therapeutic opportunities to improve patient stratification and treatment. We will first provide an overview of current methods and models used to study breast cancer biology, focusing on 2D and 3D cell culture, including organoids, and on in vivo models such as the MMTV mouse model and patient-derived xenografts (PDX). Next, genomic, transcriptomic, and proteomic approaches and their integration will be considered in the context of breast cancer susceptibility, breast cancer drivers, and therapeutic response and resistance to treatment. Finally, we will discuss how 'Omics datasets in combination with traditional breast cancer models are useful for generating insights into breast cancer biology, for suggesting individual treatments in precision oncology, and for creating data repositories to undergo further meta-analysis. System biology has the potential to catalyze the next great leap forward in treatment options for breast cancer patients.

Identification of key genes by integrating DNA methylation and next-generation transcriptome sequencing for esophageal squamous cell carcinoma

Aberrant DNA methylation leads to abnormal gene expression, making it a significant regulator in the progression of cancer and leading to the requirement for integration of gene expression with DNA methylation. Here, we identified 120 genes demonstrating an inverse correlation between DNA methylation and mRNA expression in esophageal squamous cell carcinoma (ESCC). Sixteen key genes, such as SIX4, CRABP2, and EHD3, were obtained by filtering 10 datasets and verified in paired ESCC samples by qRT-PCR. 5-Aza-dC as a DNA methyltransferase (DNMT) inhibitor could recover their expression and inhibit clonal growth of cancer cells in seven ESCC cell lines. Furthermore, 11 of the 16 genes were correlated with OS (overall survival) and DFS (disease-free survival) in 125 ESCC patients. ChIP-Seq data and WGBS data showed that DNA methylation and H3K27ac histone modification of these key genes displayed inverse trends, suggesting that there was collaboration between DNA methylation and histone modification in ESCC. Our findings illustrate that the integrated multi-omics data (transcriptome and epigenomics) can accurately obtain potential prognostic biomarkers, which may provide important insight for the effective treatment of cancers.

Detection and analysis of stable and flexible genes towards a genome signature framework in cancer

Comparison and detection of stable cancer genes across cancer types is of interest. The gene expression data of 6 different cancer types (colon, breast, lung, ovarian, brain and renal) and a control group from The Cancer Genome Atlas (TCGA) database were used in this study. The comparison of gene expression data together with the calculation standard deviations of such data was completed using a statistical model for the detection of stable genes. Genes having similar expression (referred as flexible genes) pattern to the control group in four out of six cancer types are PATE, NEUROD4 and TRAFD1. Moreover, 13 genes showed low difference compared to the control group with low standard deviation across cancer types (referred as stable genes). Among them, genes GDF2, KCNT1 and RNF151 showed consistent low expression while ODF4, OR5I1, MYOG and OR2B11 showed consistent high expression. Thus, the detection and analysis of stable and flexible cancer genes help towards the design and development of a framework (outline) for specific genome signature (biomarker) in cancer.

Cell-Free DNA Methylation Profiling Analysis-Technologies and Bioinformatics

Analysis of circulating nucleic acids in bodily fluids, referred to as “liquid biopsies”, is rapidly gaining prominence. Studies have shown that cell-free DNA (cfDNA) has great potential in characterizing tumor status and heterogeneity, as well as the response to therapy and tumor recurrence. DNA methylation is an epigenetic modification that plays an important role in a broad range of biological processes and diseases. It is well known that aberrant DNA methylation is generalizable across various samples and occurs early during the pathogenesis of cancer. Methylation patterns of cfDNA are also consistent with their originated cells or tissues. Systemic analysis of cfDNA methylation profiles has emerged as a promising approach for cancer detection and origin determination. In this review, we will summarize the technologies for DNA methylation analysis and discuss their feasibility for liquid biopsy applications. We will also provide a brief overview of the bioinformatic approaches for analysis of DNA methylation sequencing data. Overall, this review provides informative guidance for the selection of experimental and computational methods in cfDNA methylation-based studies.

Review of applications of high-throughput sequencing in personalized medicine: barriers and facilitators of future progress in research and clinical application

There has been an exponential growth in the performance and output of sequencing technologies (omics data) with full genome sequencing now producing gigabases of reads on a daily basis. These data may hold the promise of personalized medicine, leading to routinely available sequencing tests that can guide patient treatment decisions. In the era of high-throughput sequencing (HTS), computational considerations, data governance and clinical translation are the greatest rate-limiting steps. To ensure that the analysis, management and interpretation of such extensive omics data is exploited to its full potential, key factors, including sample sourcing, technology selection and computational expertise and resources, need to be considered, leading to an integrated set of high-performance tools and systems. This article provides an up-to-date overview of the evolution of HTS and the accompanying tools, infrastructure and data management approaches that are emerging in this space, which, if used within in a multidisciplinary context, may ultimately facilitate the development of personalized medicine.

Genome-Wide Plasma Cell-Free DNA Methylation Profiling Identifies Potential Biomarkers for Lung Cancer

As a noninvasive blood testing, the detection of cell-free DNA (cfDNA) methylation in plasma has raised an increasing interest due to diagnostic applications. Although extensively used in cfDNA methylation analysis, bisulfite sequencing is less cost-effective. In this study, we investigated the cfDNA methylation patterns in lung cancer patients by MeDIP-seq. Compared with the healthy individuals, 330 differentially methylated regions (DMRs) at gene promoters were identified in lung cancer patients with 33 hypermethylated and 297 hypomethylated regions, respectively. Moreover, these hypermethylated genes were validated with the publicly available DNA methylation data, yielding a set of ten significant differentially methylated genes in lung cancer, including B3GAT2, BCAR1, HLF, HOPX, HOXD11, MIR1203, MYL9, SLC9A3R2, SYT5, and VTRNA1-3. Our study demonstrated MeDIP-seq could be effectively used for cfDNA methylation profiling and identified a set of potential biomarker genes with clinical application for lung cancer.

Detection of epigenetic field defects using a weighted epigenetic distance-based method

Identifying epigenetic field defects, notably early DNA methylation alterations, is important for early cancer detection. Research has suggested these early methylation alterations are infrequent across samples and identifiable as outlier samples. Here we developed a weighted epigenetic distance-based method characterizing (dis)similarity in methylation measures at multiple CpGs in a gene or a genetic region between pairwise samples, with weights to up-weight signal CpGs and down-weight noise CpGs. Using distance-based approaches, weak signals that might be filtered out in a CpG site-level analysis could be accumulated and therefore boost the overall study power. In constructing epigenetic distances, we considered both differential methylation (DM) and differential variability (DV) signals. We demonstrated the superior performance of the proposed weighted epigenetic distance-based method over non-weighted versions and site-level EWAS (epigenome-wide association studies) methods in simulation studies. Application to breast cancer methylation data from Gene Expression Omnibus (GEO) comparing normal-adjacent tissue to tumor of breast cancer patients and normal tissue of independent age-matched cancer-free women identified novel epigenetic field defects that were missed by EWAS methods, when majority were previously reported to be associated with breast cancer and were confirmed the progression to breast cancer. We further replicated some of the identified epigenetic field defects.

Analysis of genome-wide in cell free DNA methylation: progress and prospect

In this work, we focus on the detection methods of cfDNA methylation based on NGS and the latest progress.

From Single Level Analysis to Multi-Omics Integrative Approaches: A Powerful Strategy towards the Precision Oncology

Integration of multi-omics data from different molecular levels with clinical data, as well as epidemiologic risk factors, represents an accurate and promising methodology to understand the complexity of biological systems of human diseases, including cancer. By the extensive use of novel technologic platforms, a large number of multidimensional data can be derived from analysis of health and disease systems. Comprehensive analysis of multi-omics data in an integrated framework, which includes cumulative effects in the context of biological pathways, is therefore eagerly awaited. This strategy could allow the identification of pathway-addiction of cancer cells that may be amenable to therapeutic intervention. However, translation into clinical settings requires an optimized integration of omics data with clinical vision to fully exploit precision cancer medicine. We will discuss the available technical approach and more recent developments in the specific field.

Discovery and development of differentially methylated regions in human papillomavirus-related oropharyngeal squamous cell carcinoma

Human papillomavirus (HPV)-related oropharyngeal squamous cell carcinoma (OPSCC) exhibits a different composition of epigenetic alterations. In this study, we identified differentially methylated regions (DMRs) with potential utility in screening for HPV-positive OPSCC. Genome wide DNA methylation was measured using methyl-CpG binding domain protein-enriched genome sequencing (MBD-seq) in 50 HPV-positive OPSCC tissues and 25 normal tissues. Fifty-one DMRs were defined with maximal methylation specificity to cancer samples. The Cancer Genome Atlas (TCGA) methylation array data was used to evaluate the performance of the proposed candidates. Supervised hierarchical clustering of 51 DMRs found that HPV-positive OPSCC had significantly higher DNA methylation levels compared to normal samples, and non-HPV-related head and neck squamous cell carcinoma (HNSCC). The methylation levels of all top 20 DNA methylation biomarkers in HPV-positive OPSCC were significantly higher than those in normal samples. Further confirmation using quantitative methylation specific PCR (QMSP) in an independent set of 24 HPV-related OPSCCs and 22 controls showed that 16 of the 20 candidates had significant higher methylation levels in HPV-positive OPSCC samples compared with controls. One candidate, OR6S1, had a sensitivity of 100%, while 17 candidates (KCNA3, EMBP1, CCDC181, DPP4, ITGA4, BEND4, ELMO1, SFMBT2, C1QL3, MIR129-2, NID2, HOXB4, ZNF439, ZNF93, VSTM2B, ZNF137P and ZNF773) had specificities of 100%. The prediction accuracy of the 20 candidates rang from 56.2% to 99.8% by receiver operating characteristic analysis. We have defined 20 highly specific DMRs in HPV-related OPSCC, which can potentially be applied to molecular-based detection tests and improve disease management.

Targeted methylation sequencing of plasma cell-free DNA for cancer detection and classification

Background

Targeted methylation sequencing of plasma cell-free DNA (cfDNA) has a potential to expand liquid biopsies to patients with tumors without detectable oncogenic alterations, which can be potentially useful in early diagnosis.

Patients and methods

We developed a comprehensive methylation sequencing assay targeting 9223 CpG sites consistently hypermethylated according to The Cancer Genome Atlas. Next, we carried out a clinical validation of our method using plasma cfDNA samples from 78 patients with advanced colorectal cancer, non-small-cell lung cancer (NSCLC), breast cancer or melanoma and compared results with patients' outcomes.

Results

Median methylation scores in plasma cfDNA samples from patients on therapy were lower than from patients off therapy (4.74 versus 85.29; P = 0.001). Of 68 plasma samples from patients off therapy, methylation scores detected the presence of cancer in 57 (83.8%), and methylation-based signatures accurately classified the underlying cancer type in 45 (78.9%) of these. Methylation scores were most accurate in detecting colorectal cancer (96.3%), followed by breast cancer (91.7%), melanoma (81.8%) and NSCLC (61.1%), and most accurate in classifying the underlying cancer type in colorectal cancer (88.5%), followed by NSCLC (81.8%), breast cancer (72.7%) and melanoma (55.6%). Low methylation scores versus high were associated with longer survival (10.4 versus 4.4 months, P < 0.001) and longer time-to-treatment failure (2.8 versus 1.6 months, P = 0.016).

Conclusions

Comprehensive targeted methylation sequencing of 9223 CpG sites in plasma cfDNA from patients with common advanced cancers detects the presence of cancer and underlying cancer type with high accuracy. Methylation scores in plasma cfDNA correspond with treatment outcomes.

High Interspecimen Variability in Nucleic Acid Extraction Efficiency Necessitates the Use of Spike-In Control for Accurate qPCR-based Measurement of Plasma Cell-Free DNA Levels

Objective

To assess the interspecimen variability associated with plasma DNA extraction in order to provide insight regarding the necessity to use an exogenous spike-in control when measuring cell-free DNA (cfDNA) levels using quantitative polymerase chain reaction (qPCR).

Methods

Plasma specimens were obtained from 8 healthy individuals, 20 patients with cardiovascular disease risk factors, and 54 patients diagnosed with acute stroke. Specimens were spiked with an exogenous oligonucleotide fragment, and total DNA was extracted via automated solid phase anion exchange. We determined recovery of the exogenous fragment via qPCR and used this information to calculate DNA extraction efficiency.

Results

Plasma DNA extraction efficiencies varied dramatically between specimens, ranging from 22.9% to 88.1%, with a coefficient of variance of 28.9%. No significant differences in DNA extraction efficiencies were observed between patient populations.

Conclusions

We strongly recommend the use of an exogenous spike-in control to account for variance in plasma DNA extraction efficiency when assessing cell free DNA (cfDNA) levels by qPCR in future biomarker investigations.

Liquid biopsies: DNA methylation analyses in circulating cell-free DNA

Analysis of patient's materials like cells or nucleic acids obtained in a minimally invasive or noninvasive manner through the sampling of blood or other body fluids serves as liquid biopsies, which has huge potential for numerous diagnostic applications. Circulating cell-free DNA (cfDNA) is explored as a prognostic or predictive marker of liquid biopsies with the improvements in genomic and molecular methods. DNA methylation is an important epigenetic marker known to affect gene expression. cfDNA methylation detection is a very promising approach as abnormal distribution of DNA methylation is one of the hallmarks of many cancers and methylation changes occur early during carcinogenesis. This review summarizes the various investigational applications of cfDNA methylation and its oxidized derivatives as biomarkers for cancer diagnosis, prenatal diagnosis and organ transplantation monitoring. The review also provides a brief overview of the technologies for cfDNA methylation analysis based on next generation sequencing.

Development of a Method to Implement Whole-Genome Bisulfite Sequencing of cfDNA from Cancer Patients and a Mouse Tumor Model

The goal of this study was to develop a method for whole genome cell-free DNA (cfDNA) methylation analysis in humans and mice with the ultimate goal to facilitate the identification of tumor derived DNA methylation changes in the blood. Plasma or serum from patients with pancreatic neuroendocrine tumors or lung cancer, and plasma from a murine model of pancreatic adenocarcinoma was used to develop a protocol for cfDNA isolation, library preparation and whole-genome bisulfite sequencing of ultra low quantities of cfDNA, including tumor-specific DNA. The protocol developed produced high quality libraries consistently generating a conversion rate >98% that will be applicable for the analysis of human and mouse plasma or serum to detect tumor-derived changes in DNA methylation.

Epigenetic biomarkers: Current strategies and future challenges for their use in the clinical laboratory

Epigenetic modifications and regulators represent potential molecular elements which control relevant physiological and pathological features, thereby contributing to the natural history of human disease. These epigenetic modulators can be employed as disease biomarkers, since they show several advantages and provide information about gene function, thus explaining differences among patient endophenotypes. In addition, epigenetic biomarkers can incorporate information regarding the effects of the environment and lifestyle on health and disease, and monitor the effect of applied therapies. Technologies used to analyze these epigenetic biomarkers are constantly improving, becoming much easier to use. Laboratory professionals can easily acquire experience and techniques are becoming more affordable. A high number of epigenetic biomarker candidates are being continuously proposed, making now the moment to adopt epigenetics in the clinical laboratory and convert epigenetic marks into reliable biomarkers. In this review, we describe some current promising epigenetic biomarkers and technologies being applied in clinical practice. Furthermore, we will discuss some laboratory strategies and kits to accelerate the adoption of epigenetic biomarkers into clinical routine. The likelihood is that over time, better markers will be identified and will likely be incorporated into future multi-target assays that might help to optimize its application in a clinical laboratory. This will improve cost-effectiveness, and consequently encourage the development of theragnosis and the application of precision medicine.

Implementation of a Precision Pathology Program Focused on Oncology-Based Prognostic and Predictive Outcomes

Personalized or precision medicine as a diagnostic and therapeutic paradigm was introduced some 10-15 years ago, with the advent of biomarker discovery as a mechanism for identifying prognostic and predictive attributes associated with treatment indication and outcome. While the concept is not new, the successful development and implementation of novel 'companion diagnostics', especially in oncology, continues to represent a significant challenge and is currently at the forefront of smart trial design and therapeutic choice. The ability to determine patient selection for a specific therapy has broad implications including better chances for a positive outcome, limited exposure to potentially toxic drugs and improved health economics. Importantly, a significant step in this paradigm is the role of predictive pathology or the accurate assessment of morphology at the microscopic level. In breast cancer, this has been most useful where histologic attributes such as the classification of tubular and cribriform carcinoma dictates surgery while neoadjuvant studies suggest that patients with lobular carcinoma are not likely to benefit from chemotherapy. The next level of 'personalized pathology' at the tissue-cellular level is the use of 'protein biomarker panels' to classify the disease process and ultimately drive tumor characterization and treatment. The following review article will focus on the evolution of predictive pathology from a subjective, 'opinion-based' approach to a quantitative science. In addition, we will discuss the individual components of the precise pathology platform including advanced image analysis, biomarker quantitation with mathematical modeling and the integration with fluid-based (i.e. blood, urine) analytics as drivers of next generation precise patient phenotyping.