Circulating cell-free DNA release in vitro: kinetics, size profiling, and cancer-related gene methylation

BRCA1 & BRCA2 methylation as a prognostic and predictive biomarker in cancer: Implementation in liquid biopsy in the era of precision medicine

BACKGROUND

BReast CAncer gene 1 (BRCA1) and BReast CAncer gene 2 (BRCA2) encode for tumor suppressor proteins which are critical regulators of the Homologous Recombination (HR) pathway, the most precise and important DNA damage response mechanism. Dysfunctional HR proteins cannot repair double-stranded DNA breaks in mammalian cells, a situation called HR deficiency. Since their identification, pathogenic variants and other alterations of BRCA1 and BRCA2 genes have been associated with an increased risk of developing mainly breast and ovarian cancer. Interestingly, HR deficiency is also detected in tumors not carrying BRCA1/2 mutations, a condition termed "BRCAness".

MAIN TEXT

One of the main mechanisms causing the BRCAness phenotype is the methylation of the BRCA1/2 promoters, and this epigenetic modification is associated with carcinogenesis and poor prognosis mainly among patients with breast and ovarian cancer. BRCA1 promoter methylation has been suggested as an emerging biomarker of great predictive significance, especially concerning Poly (ADP-ribose) Polymerase inhibitors (PARP inhibitor-PARPi) responsiveness, along with or beyond BRCA1/2 mutations. However, as its clinical exploitation is still insufficient, the impact of BRCA1/2 promoter methylation status needs to be further evaluated. The current review aims to gather the latest findings about the mechanisms that underline BRCA1/2 function as well as the molecular characteristics of tumors associated with BRCA1/2 defects, by focusing on DNA methylation. Furthermore, we critically analyze their translational meaning and the validity of BRCA methylation biomarkers in predicting treatment response.

CONCLUSIONS

We believe that BRCA1/2 methylation alone or combined with other biomarkers in a clinical setting is expected to change the scenery in prognosis and predicting treatment response in multiple cancer types and is worthy of further attention. The quantitative BRCA1 promoter methylation assessment might predict treatment response in PARPi and analysis of BRCA1/2 methylation in liquid biopsy might define patient subgroups at different time points that may benefit from PARPi. Finally, we suggest a pipeline that could be implemented in liquid biopsy to aid precision pharmacotherapy in BRCA-associated tumors.

Early ctDNA kinetics as a dynamic biomarker of cancer treatment response

Circulating tumor DNA assays are promising tools for the prediction of cancer treatment response. Here, we build a framework for the design of ctDNA biomarkers of therapy response that incorporate variations in ctDNA dynamics driven by specific treatment mechanisms. We develop mathematical models of ctDNA kinetics driven by tumor response to several therapy classes, and utilize them to simulate randomized virtual patient cohorts to test candidate biomarkers. Using this approach, we propose specific biomarkers, based on ctDNA longitudinal features, for targeted therapy, chemotherapy and radiation therapy. We evaluate and demonstrate the efficacy of these biomarkers in predicting treatment response within a randomized virtual patient cohort dataset. These biomarkers are based on novel proposals for ctDNA sampling protocols, consisting of frequent sampling within a compact time window surrounding therapy initiation - which we hypothesize to hold valuable prognostic information on longer-term treatment response. This study highlights a need for tailoring ctDNA sampling protocols and interpretation methodology to specific biological mechanisms of therapy response, and it provides a novel modeling and simulation framework for doing so. In addition, it highlights the potential of ctDNA assays for making early, rapid predictions of treatment response within the first days or weeks of treatment, and generates hypotheses for further clinical testing.

Mitochondrial Fraction of Circulating Cell-Free DNA as an Indicator of Human Pathology

Circulating cell-free DNA (ccfDNA) of mitochondrial origin (ccf-mtDNA) consists of a minor fraction of total ccfDNA in blood or in other biological fluids. Aberrant levels of ccf-mtDNA have been observed in many pathologies. Here, we introduce a simple and effective standardized Taqman probe-based dual-qPCR assay for the simultaneous detection and relative quantification of nuclear and mitochondrial fragments of ccfDNA. Three pathologies of major burden, one malignancy (Breast Cancer, BrCa), one inflammatory (Osteoarthritis, OA) and one metabolic (Type 2 Diabetes, T2D), were studied. Higher levels of ccf-mtDNA were detected both in BrCa and T2D in relation to health, but not in OA. In BrCa, hormonal receptor status was associated with ccf-mtDNA levels. Machine learning analysis of ccf-mtDNA datasets was used to build biosignatures of clinical relevance. (A) a three-feature biosignature discriminating between health and BrCa (AUC: 0.887) and a five-feature biosignature for predicting the overall survival of BrCa patients (Concordance Index: 0.756). (B) a five-feature biosignature stratifying among T2D, prediabetes and health (AUC: 0.772); a five-feature biosignature discriminating between T2D and health (AUC: 0.797); and a four-feature biosignature identifying prediabetes from health (AUC: 0.795). (C) a biosignature including total plasma ccfDNA with very high performance in discriminating OA from health (AUC: 0.934). Aberrant ccf-mtDNA levels could have diagnostic/prognostic potential in BrCa and Diabetes, while the developed multiparameter biosignatures can add value to their clinical management.

Multidimensional fragmentomic profiling of cell-free DNA released from patient-derived organoids

BACKGROUND

Fragmentomics, the investigation of fragmentation patterns of cell-free DNA (cfDNA), has emerged as a promising strategy for the early detection of multiple cancers in the field of liquid biopsy. However, the clinical application of this approach has been hindered by a limited understanding of cfDNA biology. Furthermore, the prevalence of hematopoietic cell-derived cfDNA in plasma complicates the in vivo investigation of tissue-specific cfDNA other than that of hematopoietic origin. While conventional two-dimensional cell lines have contributed to research on cfDNA biology, their limited representation of in vivo tissue contexts underscores the need for more robust models. In this study, we propose three-dimensional organoids as a novel in vitro model for studying cfDNA biology, focusing on multifaceted fragmentomic analyses.

RESULTS

We established nine patient-derived organoid lines from normal lung airway, normal gastric, and gastric cancer tissues. We then extracted cfDNA from the culture medium of these organoids in both proliferative and apoptotic states. Using whole-genome sequencing data from cfDNA, we analyzed various fragmentomic features, including fragment size, footprints, end motifs, and repeat types at the end. The distribution of cfDNA fragment sizes in organoids, especially in apoptosis samples, was similar to that found in plasma, implying occupancy by mononucleosomes. The footprints determined by sequencing depth exhibited distinct patterns depending on fragment sizes, reflecting occupancy by a variety of DNA-binding proteins. Notably, we discovered that short fragments (< 118 bp) were exclusively enriched in the proliferative state and exhibited distinct fragmentomic profiles, characterized by 3 bp palindromic end motifs and specific repeats.

CONCLUSIONS

In conclusion, our results highlight the utility of in vitro organoid models as a valuable tool for studying cfDNA biology and its associated fragmentation patterns. This, in turn, will pave the way for further enhancements in noninvasive cancer detection methodologies based on fragmentomics.

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.

Adipose cell-free DNA in diabetes

Cancer-associated necrosis is a well-known source of cell-free DNA (cfDNA). However, the origins of cfDNA are not strictly limited to cancer. Additionally, dietary exposure induces apoptosis-induced proliferation in adipocytes, leading to the release of cfDNA. The genetic information derived from cfDNA as a result of apoptosis-induced proliferation contains specific methylation patterns in adipose tissue that can be used as a marker to detect the risk of developing Type 2 diabetes Mellitus (T2DM) in the future. cfDNA is superior to peripheral blood leukocytes (PBL) and whole blood samples for reflecting tissue pathology due to the frequent use of PBL and whole blood samples that do not match tissue pathology. The difficulty of demonstrating that cfDNA is derived from adipose tissue. We propose several promising techniques by analyzing cfDNA derived from adipose tissue to detect T2DM risk. First, adipose-specific genes such as ADIPOQ and Leptin were utilized. Second, MCTA-Seq, EpiSCORE, deconvolution, multiplexing, and automated machine learning (AutoML) were used to determine the proportion of total methylation in related genes.

Endogenous cell-free DNA in fetal bovine serum introduces artifacts to in vitro cell-free DNA models

Cell-free DNA (cfDNA) is of growing clinical and research significance. In vitro cfDNA models are a useful tool in cfDNA research; however, artifacts in these models may have implications for the interpretation of new and published data. This report aimed to establish how endogenous cfDNA in fetal bovine serum (FBS) may influence in vitro cfDNA measurements. Three commercial cell culture media, supplemented with 10% FBS, were analyzed for the presence of cfDNA, with and without culture with ovarian cancer cell lines. cfDNA from FBS was identified with all three commercial media and contributed a major portion of 167-bp cfDNA. Future studies should account for bovine cfDNA in FBS-supplemented media when conducting in vitro cfDNA research.

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.

New Perspectives on the Importance of Cell-Free DNA Biology

Body fluids are constantly replenished with a population of genetically diverse cell-free DNA (cfDNA) fragments, representing a vast reservoir of information reflecting real-time changes in the host and metagenome. As many body fluids can be collected non-invasively in a one-off and serial fashion, this reservoir can be tapped to develop assays for the diagnosis, prognosis, and monitoring of wide-ranging pathologies, such as solid tumors, fetal genetic abnormalities, rejected organ transplants, infections, and potentially many others. The translation of cfDNA research into useful clinical tests is gaining momentum, with recent progress being driven by rapidly evolving preanalytical and analytical procedures, integrated bioinformatics, and machine learning algorithms. Yet, despite these spectacular advances, cfDNA remains a very challenging analyte due to its immense heterogeneity and fluctuation in vivo. It is increasingly recognized that high-fidelity reconstruction of the information stored in cfDNA, and in turn the development of tests that are fit for clinical roll-out, requires a much deeper understanding of both the physico-chemical features of cfDNA and the biological, physiological, lifestyle, and environmental factors that modulate it. This is a daunting task, but with significant upsides. In this review we showed how expanded knowledge on cfDNA biology and faithful reverse-engineering of cfDNA samples promises to (i) augment the sensitivity and specificity of existing cfDNA assays; (ii) expand the repertoire of disease-specific cfDNA markers, thereby leading to the development of increasingly powerful assays; (iii) reshape personal molecular medicine; and (iv) have an unprecedented impact on genetics research.

Cell-Free DNA Fragmentation Patterns in a Cancer Cell Line

Unique bits of genetic, biological and pathological information occur in differently sized cell-free DNA (cfDNA) populations. This is a significant discovery, but much of the phenomenon remains to be explored. We investigated cfDNA fragmentation patterns in cultured human bone cancer (143B) cells using increasingly sensitive electrophoresis assays, including four automated microfluidic capillary electrophoresis assays from Agilent, i.e., DNA 1000, High Sensitivity DNA, dsDNA 915 and dsDNA 930, and an optimized manual agarose gel electrophoresis protocol. This comparison showed that (i) as the sensitivity and resolution of the sizing methods increase incrementally, additional nucleosomal multiples are revealed (hepta-nucleosomes were detectable with manual agarose gel electrophoresis), while the estimated size range of high molecular weight (HMW) cfDNA fragments narrow correspondingly; (ii) the cfDNA laddering pattern extends well beyond the 1–3 nucleosomal multiples detected by commonly used methods; and (iii) the modal size of HMW cfDNA populations is exaggerated due to the limited resolving power of electrophoresis, and instead consists of several poly-nucleosomal subpopulations that continue the series of DNA laddering. Furthermore, the most sensitive automated assay used in this study (Agilent dsDNA 930) revealed an exponential decay in the relative contribution of increasingly longer cfDNA populations. This power-law distribution suggests the involvement of a stochastic inter-nucleosomal DNA cleavage process, wherein shorter populations accumulate rapidly as they are fed by the degradation of all larger populations. This may explain why similar size profiles have historically been reported for cfDNA populations originating from different processes, such as apoptosis, necrosis, accidental cell lysis and purported active release. These results not only demonstrate the diversity of size profiles generated by different methods, but also highlight the importance of caution when drawing conclusions on the mechanisms that generate different cfDNA size populations, especially when only a single method is used for sizing.

Tracing the Origin of Cell-Free DNA Molecules through Tissue-Specific Epigenetic Signatures

All cell and tissue types constantly release DNA fragments into human body fluids by various mechanisms including programmed cell death, accidental cell degradation and active extrusion. Particularly, cell-free DNA (cfDNA) in plasma or serum has been utilized for minimally invasive molecular diagnostics. Disease onset or pathological conditions that lead to increased cell death alter the contribution of different tissues to the total pool of cfDNA. Because cfDNA molecules retain cell-type specific epigenetic features, it is possible to infer tissue-of-origin from epigenetic characteristics. Recent research efforts demonstrated that analysis of, e.g., methylation patterns, nucleosome occupancy, and fragmentomics determined the cell- or tissue-of-origin of individual cfDNA molecules. This novel tissue-of origin-analysis enables to estimate the contributions of different tissues to the total cfDNA pool in body fluids and find tissues with increased cell death (pathologic condition), expanding the portfolio of liquid biopsies towards a wide range of pathologies and early diagnosis. In this review, we summarize the currently available tissue-of-origin approaches and point out the next steps towards clinical implementation.

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.

Tissue-Specific Methylation Biosignatures for Monitoring Diseases: An In Silico Approach

Tissue-specific gene methylation events are key to the pathogenesis of several diseases and can be utilized for diagnosis and monitoring. Here, we established an in silico pipeline to analyze high-throughput methylome datasets to identify specific methylation fingerprints in three pathological entities of major burden, i.e., breast cancer (BrCa), osteoarthritis (OA) and diabetes mellitus (DM). Differential methylation analysis was conducted to compare tissues/cells related to the pathology and different types of healthy tissues, revealing Differentially Methylated Genes (DMGs). Highly performing and low feature number biosignatures were built with automated machine learning, including: (1) a five-gene biosignature discriminating BrCa tissue from healthy tissues (AUC 0.987 and precision 0.987), (2) three equivalent OA cartilage-specific biosignatures containing four genes each (AUC 0.978 and precision 0.986) and (3) a four-gene pancreatic β-cell-specific biosignature (AUC 0.984 and precision 0.995). Next, the BrCa biosignature was validated using an independent ccfDNA dataset showing an AUC and precision of 1.000, verifying the biosignature's applicability in liquid biopsy. Functional and protein interaction prediction analysis revealed that most DMGs identified are involved in pathways known to be related to the studied diseases or pointed to new ones. Overall, our data-driven approach contributes to the maximum exploitation of high-throughput methylome readings, helping to establish specific disease profiles to be applied in clinical practice and to understand human pathology.

Liquid Biopsy in Type 2 Diabetes Mellitus Management: Building Specific Biosignatures via Machine Learning

BACKGROUND

The need for minimally invasive biomarkers for the early diagnosis of type 2 diabetes (T2DM) prior to the clinical onset and monitoring of β-pancreatic cell loss is emerging. Here, we focused on studying circulating cell-free DNA (ccfDNA) as a liquid biopsy biomaterial for accurate diagnosis/monitoring of T2DM.

METHODS

ccfDNA levels were directly quantified in sera from 96 T2DM patients and 71 healthy individuals via fluorometry, and then fragment DNA size profiling was performed by capillary electrophoresis. Following this, ccfDNA methylation levels of five β-cell-related genes were measured via qPCR. Data were analyzed by automated machine learning to build classifying predictive models.

RESULTS

ccfDNA levels were found to be similar between groups but indicative of apoptosis in T2DM. INS (Insulin), IAPP (Islet Amyloid Polypeptide-Amylin), GCK (Glucokinase), and KCNJ11 (Potassium Inwardly Rectifying Channel Subfamily J member 11) levels differed significantly between groups. AutoML analysis delivered biosignatures including GCK, IAPP and KCNJ11 methylation, with the highest ever reported discriminating performance of T2DM from healthy individuals (AUC 0.927).

CONCLUSIONS

Our data unravel the value of ccfDNA as a minimally invasive biomaterial carrying important clinical information for T2DM. Upon prospective clinical evaluation, the built biosignature can be disruptive for T2DM clinical management.

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.

Serial profiling of cell-free DNA and nucleosome histone modifications in cell cultures

Recent advances in basic research have unveiled several strategies for improving the sensitivity and specificity of cell-free DNA (cfDNA) based assays, which is a prerequisite for broadening its clinical use. Included among these strategies is leveraging knowledge of both the biogenesis and physico-chemical properties of cfDNA towards the identification of better disease-defining features and optimization of methods. While good progress has been made on this front, much of cfDNA biology remains uncharted. Here, we correlated serial measurements of cfDNA size, concentration and nucleosome histone modifications with various cellular parameters, including cell growth rate, viability, apoptosis, necrosis, and cell cycle phase in three different cell lines. Collectively, the picture emerged that temporal changes in cfDNA levels are rather irregular and not the result of constitutive release from live cells. Instead, changes in cfDNA levels correlated with intermittent cell death events, wherein apoptosis contributed more to cfDNA release in non-cancer cells and necrosis more in cancer cells. Interestingly, the presence of a ~ 3 kbp cfDNA population, which is often deemed to originate from accidental cell lysis or active release, was found to originate from necrosis. High-resolution analysis of this cfDNA population revealed an underlying DNA laddering pattern consisting of several oligo-nucleosomes, identical to those generated by apoptosis. This suggests that necrosis may contribute significantly to the pool of mono-nucleosomal cfDNA fragments that are generally interrogated for cancer mutational profiling. Furthermore, since active steps are often taken to exclude longer oligo-nucleosomes from clinical biospecimens and subsequent assays this raises the question of whether important pathological information is lost.

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.

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.

Putative Origins of Cell-Free DNA in Humans: A Review of Active and Passive Nucleic Acid Release Mechanisms

Through various pathways of cell death, degradation, and regulated extrusion, partial or complete genomes of various origins (e.g., host cells, fetal cells, and infiltrating viruses and microbes) are continuously shed into human body fluids in the form of segmented cell-free DNA (cfDNA) molecules. While the genetic complexity of total cfDNA is vast, the development of progressively efficient extraction, high-throughput sequencing, characterization via bioinformatics procedures, and detection have resulted in increasingly accurate partitioning and profiling of cfDNA subtypes. Not surprisingly, cfDNA analysis is emerging as a powerful clinical tool in many branches of medicine. In addition, the low invasiveness of longitudinal cfDNA sampling provides unprecedented access to study temporal genomic changes in a variety of contexts. However, the genetic diversity of cfDNA is also a great source of ambiguity and poses significant experimental and analytical challenges. For example, the cfDNA population in the bloodstream is heterogeneous and also fluctuates dynamically, differs between individuals, and exhibits numerous overlapping features despite often originating from different sources and processes. Therefore, a deeper understanding of the determining variables that impact the properties of cfDNA is crucial, however, thus far, is largely lacking. In this work we review recent and historical research on active vs. passive release mechanisms and estimate the significance and extent of their contribution to the composition of cfDNA.

Corticotropin Releasing Factor Receptors in breast cancer: Expression and activity in hormone-dependent growth in vitro

Corticotropin Releasing Factor (CRF) neuropeptides coordinate the stress response via two distinct membrane receptors (CRF-Rs). We have previously shown expression of both CRF-Rs in human breast cancer tissues. In the present study, we examined in vitro using the MCF-7 cell line model, the regulation of CRF-Rs expression and their signaling in hormone-dependent breast cancer growth. Our findings show that similarly to breast cancer biopsies, the predominant receptor type expressed in the cell line is CRF-R2α. The transcription of CRF-R1 and CRF-R2 is up and down-regulated respectively by exposure to estradiol (E2); however this effect seems not to be exerted at the level of promoter gene methylation, although in human breast cancer specimens, CRF-R1 methylation was found to be positively associated with the presence of steroid hormone receptors. Finally, we showed that specific activation of CRF-R2 increased the migration of MCF-7 cells and potentiated an estrogen-inducing effect. Our data support an involvement of CRF-R signaling in breast cancer pathophysiology via a regulatory steroid-hormone interplay.

Comparison of methods for the isolation of cell-free DNA from cell culture supernatant

In vitro characterization of cell-free DNA using two-dimensional cell culture models is emerging as an important step toward an improved understanding of the physical and biological characteristics of cell-free DNA in human biology. However, precise measurement of the cell-free DNA in cell culture medium is highly dependent on the efficacy of the method used for DNA purification, and is often a juncture of experimental confusion. Therefore, in this study, we compared six commercially available cell-free DNA isolation kits for the recovery of cell-free DNA from the cell culture supernatant of a human bone cancer cell line (143B), including two magnetic bead-based manual kits, one automated magnetic bead-based extraction method, and three manual spin-column kits. Based on cell-free DNA quantitation and sizing, using the Qubit dsDNA HS assay and Bioanalyzer HS DNA assay, respectively, the different methods showed significant variability concerning recovery, reproducibility, and size discrimination. These findings highlight the importance of selecting a cell-free DNA extraction method that is appropriate for the aims of a study. For example, mutational analysis of cell-free DNA may be enhanced by a method that favors a high yield or is biased toward the isolation of short cell-free DNA fragments. In contrast, quantitative analysis of cell-free DNA in a comparative setting (e.g. measuring the fluctuation of cell-free DNA levels over time) may require the selection of a cell-free DNA isolation method that forgoes a high recovery for high reproducibility and minimal size bias.

Early detection of cancer using circulating tumor DNA: biological, physiological and analytical considerations

Early diagnosis of cancer improves the efficacy of curative therapies. However, due to the difficulties involved in distinguishing between small early-stage tumors and normal biological variation, early detection of cancer is an extremely challenging task and there are currently no clinically validated biomarkers for a pan-cancer screening test. It is thus of particular significance that increasing evidence indicates the potential of circulating tumor DNA (ctDNA) molecules, which are fragmented segments of DNA shed from tumor cells into adjacent body fluids and the circulatory system, to serve as molecular markers for early cancer detection and thereby allow early intervention and improvement of therapeutic and survival outcomes. This is possible because ctDNA molecules bear cancer-specific fragmentation patterns, nucleosome depletion motifs, and genetic and epigenetic alterations, as distinct from plasma DNA originating from non-cancerous tissues/cells. Compared to traditional biomarkers, ctDNA analysis therefore presents the distinctive advantage of detecting tumor-specific alterations. However, based on a thorough survey of the literature, theoretical and empirical evidence suggests that current ctDNA analysis strategies, which are mainly based on DNA mutation detection, do not demonstrate the necessary diagnostic sensitivity and specificity that is required for broad clinical implementation in a screening context. Therefore, in this review we explain the biological, physiological, and analytical challenges toward the development of clinically meaningful ctDNA tests. In addition, we explore some approaches that can be implemented in order to increase the sensitivity and specificity of ctDNA assays.

Comparison of methods for the quantification of cell-free DNA isolated from cell culture supernatant

Gaining a better understanding of the biological properties of cell-free DNA constitutes an important step in the development of clinically meaningful cell-free DNA–based tests. Since the in vivo characterization of cell-free DNA is complicated by the immense heterogeneity of blood samples, an increasing number of in vitro cell culture experiments, which offer a greater level of control, are being conducted. However, cell culture studies are currently faced with three notable caveats. First, the concentration of cell-free DNA in vitro is relatively low. Second, the median amount and size of cell-free DNA in culture medium varies greatly between cell types. Third, the amount and size of cell-free DNA in the culture medium of a single cell line fluctuates over time. Although these are interesting findings, it can also be a great source of experimental confusion and emphasizes the importance of method optimization and standardization. Therefore, in this study, we compared five commonly used cell-free DNA quantification methods, including quantitative polymerase chain reaction, Qubit Double-Stranded DNA High Sensitivity assay, Quant-iT PicoGreen Assay, Bioanalyzer High Sensitivity DNA assay, and NanoDrop Onec. Analysis of the resulting data, along with an interpretation of theoretical values (i.e. the theoretical detection and quantification limits of the respective methods), enables the calculation of optimal conditions for several important preanalytical steps pertaining to each quantification method and different cell types, including the (1) time-point at which culture medium should be collected for cell-free DNA extraction, (2) amount of cell culture supernatant from which to isolate cell-free DNA, (3) volume of elution buffer, and (4) volume of cell-free DNA sample to use for quantification.

Diagnostic significance assessment of the circulating cell-free DNA in ovarian cancer: An updated meta-analysis

BACKGROUND

Recently, disagreements remain in increasing evidence about the potential value of circulating cell-free DNA (cfDNA) as a noninvasive diagnostic biomarker for ovarian cancer (OC). Here, this update meta-analysis was performed to further assess the diagnostic performance of circulating cfDNA in discriminating OC from non-cancerous individuals.

METHODS

We performed a systemic literature search of PubMed, Embase, Web of Science, Cochrane Library, OVID, Chinese National Knowledge Infrastructure (CNKI) and Wanfang databases to obtain 22 eligible articles including a total of 1125 patients and 1244 controls. The pooled sensitivity, specificity, diagnostic odds ratio (DOR) and area under receiver operating characteristics curves (AUROC) of the included studies for cfDNA in diagnosing OC patients were used to estimate the diagnostic value. The clinical utility of cfDNA was evaluated by Fagan nomogram. Heterogeneity was explored utilizing subgroup analysis and meta-regression.

RESULTS

The pooled sensitivity and specificity were 73% and 90%, the DOR and AUROC were 25.29 and 0.90, respectively. Subgroup analyses and meta-regression, according to patients' region, study design, clinical stage, specimen types, detection indicators, simple size, publication year revealed there were no significant sources of heterogeneity. Additionally, subgroup analyses showed qualitative detection (methylation detection); TNM stage I-IV, publication year 2011-2018, serum-based cfDNA assays exhibited better diagnostic performance as compared to quantitative detection, TNM stage III-IV, publication year 2002-2010; plasma-based cfDNA assays, and more participants and prospective studies manifested superior diagnostic accuracy. The result of sensitivity analysis indicated no study exclusively contributed to the heterogeneity and Deeks' funnel plot suggested no evidence of significant publication bias.

CONCLUSIONS

Our meta-analysis found the qualitative detection (methylation); TNM stage I-IV, publication year 2011-2018 were related to more effective diagnostic accuracy for OC. However, serum-based cell-free DNA detection should be cautiously interpreted due to unclear factors. Hence, further large-scale longitudinal studies are required to validate the diagnostic potential of cell-free DNA. The present study provides to accrue knowledge of cell-free DNA levels for future researches.