Inferring expressed genes by whole-genome sequencing of plasma DNA

Unsupervised detection of fragment length signatures of circulating tumor DNA using non-negative matrix factorization

Sequencing of cell-free DNA (cfDNA) is currently being used to detect cancer by searching both for mutational and non-mutational alterations. Recent work has shown that the length distribution of cfDNA fragments from a cancer patient can inform tumor load and type. Here, we propose non-negative matrix factorization (NMF) of fragment length distributions as a novel and completely unsupervised method for studying fragment length patterns in cfDNA. Using shallow whole-genome sequencing (sWGS) of cfDNA from a cohort of patients with metastatic castration-resistant prostate cancer (mCRPC), we demonstrate how NMF accurately infers the true tumor fragment length distribution as an NMF component - and that the sample weights of this component correlate with ctDNA levels (r=0.75). We further demonstrate how using several NMF components enables accurate cancer detection on data from various early stage cancers (AUC=0.96). Finally, we show that NMF, when applied across genomic regions, can be used to discover fragment length signatures associated with open chromatin.

Circulating tumor DNA for breast cancer: Review of active clinical trials

BACKGROUND

The new diagnostic concept of liquid biopsy is based on the analysis of circulating tumor cells (CTCs) and cell-free DNA (ctDNA). In addition to providing a more comprehensive view of the tumor characteristics including molecular variations, ctDNA analysis through liquid biopsies may also allow for a non-invasive, rapid, and cost-effective identification of biomarkers for tumor detection and monitoring of tumor progression.

OBJECTIVE

In this review, we summarize key active clinical trial studies involving utilization of ctDNA derived from liquid biopsy in the early and metastatic breast cancer setting. With this, we also provide a brief overview of the potential future implementations of the LB technology and outlining how ctDNA analysis needs to be standardized through the performance of similar clinical studies.

METHODS

A review was conducted on Clinicaltrials.gov to identify active trials related to use of circulating tumor DNA (ctDNA) for breast cancer. Search terms included "breast cancer," "liquid biopsy," and "ctDNA."

CONCLUSION

While LB is gaining traction in many cancer settings, its use in BC is still early and warrants more investigation in breast cancer diagnostic and treatment settings, including early detection of disease recurrence.

Fragmentomics of urinary cell-free DNA in nuclease knockout mouse models

Urinary cell-free DNA (ucfDNA) is a potential biomarker for bladder cancer detection. However, the biological characteristics of ucfDNA are not well understood. We explored the roles of deoxyribonuclease 1 (DNASE1) and deoxyribonuclease 1-like 3 (DNASE1L3) in the fragmentation of ucfDNA using mouse models. The deletion of Dnase1 in mice (Dnase1^-/-) caused aberrations in ucfDNA fragmentation, including a 24-fold increase in DNA concentration, and a 3-fold enrichment of long DNA molecules, with a relative decrease of fragments with thymine ends and reduction of jaggedness (i.e., the presence of single-stranded protruding ends). In contrast, such changes were not observed in mice with Dnase1l3 deletion (Dnase1l3^-/-). These results suggested that DNASE1 was an important nuclease contributing to the ucfDNA fragmentation. Western blot analysis revealed that the concentration of DNASE1 protein was higher in urine than DNASE1L3. The native-polyacrylamide gel electrophoresis zymogram showed that DNASE1 activity in urine was higher than that in plasma. Furthermore, the proportion of ucfDNA fragment ends within DNase I hypersensitive sites (DHSs) was significantly increased in Dnase1-deficient mice. In humans, patients with bladder cancer had lower proportions of ucfDNA fragment ends within the DHSs when compared with participants without bladder cancer. The area under the curve (AUC) for differentiating patients with and without bladder cancer was 0.83, suggesting the analysis of ucfDNA fragmentation in the DHSs may have potential for bladder cancer detection. This work revealed the intrinsic links between the nucleases in urine and ucfDNA fragmentomics.

Cell-free DNA (cfDNA) in various bodily fluids, for example blood plasma and urine, is of great importance for noninvasive cancer detection and noninvasive prenatal testing. Many emerging studies on the fragmentation of plasma DNA (i.e., fragmentomics) have received much recent interest. However, the fragmentomics in urinary cfDNA (ucfDNA) remained much less explored. In this study, we explored the biological links between ucfDNA fragmentation and DNA nucleases, using mice for which either the Dnase1 or Dnase1l3 gene was genetically inactivated. Interestingly, we found that the deletion of Dnase1, but not Dnase1l3, caused dramatic alterations of ucfDNA fragmentation patterns, including the elevation of DNA concentration, lengthening of fragment size, disruptions of ucfDNA end motifs (i.e., nucleotide sequences at fragment end) and the jagged ends (i.e., the single-stranded protruding ends). The proportion of fragment ends within DNase I hypersensitive sites (DHSs) was greatly increased in mice with the Dnase1 deletion. Such ucfDNA fragmentation pattern surrounding DHSs holds potential for classifying the human subjects with and without bladder cancer. The analysis combining various fragmentomic features could further improve the performance for bladder cancer detection, with an AUC of 0.91. This study has shed mechanistic insights into fragmentomics of ucfDNA in urine and has opened up new possibilities for applying ucfDNA fragmentomics in a clinical context.

Cell-Free DNA as Biomarker for Sepsis by Integration of Microbial and Host Information

BACKGROUND

Cell-free DNA (cfDNA) is emerging as a biomarker for sepsis. Previous studies have been focused mainly on identifying blood infections or simply quantifying cfDNA. We propose that by characterizing multifaceted unexplored components, cfDNA could be more informative for assessing this complex syndrome.

METHODS

We explored multiple aspects of cfDNA in septic and nonseptic intensive care unit (ICU) patients by metagenomic sequencing, with longitudinal measurement and integrative assessment of plasma cfDNA quantity, human cfDNA fragmentation patterns, infecting pathogens, and overall microbial composition.

RESULTS

Septic patients had significantly increased cfDNA quantity and altered human cfDNA fragmentation pattern. Moreover, human cfDNA fragments appeared to comprise information about cellular oxidative stress and could indicate disease severity. Metagenomic sequencing was more sensitive than blood culture in detecting bacterial infections and allowed for simultaneous detection of viral pathogens. We found differences in microbial composition between septic and nonseptic patients and between survivors and nonsurvivors by 28-day mortality, both on the first day of ICU admission and across the study period. By integrating all the information into a machine learning model, we achieved improved performance in identifying sepsis and prediction of clinical outcome for ICU patients with areas under the curve of 0.992 (95% CI 0.969-1.000) and 0.802 (95% CI 0.605-0.999), respectively.

CONCLUSIONS

We were able to diagnose sepsis and predict mortality as soon as the first day of ICU admission by integrating multifaceted cfDNA information obtained in a single metagenomic assay; this approach could provide important advantages for clinical management and for improving outcomes in ICU patients.

The Influence of Proteins on Fate and Biological Role of Circulating DNA

Circulating DNA has already proven itself as a valuable tool in translational medicine. However, one of the overlooked areas of circulating DNA research is its association with different proteins, despite considerable evidence that this association might impact DNA's fate in circulation and its biological role. In this review, we attempt to shed light on current ideas about circulating DNA origins and forms of circulation, known biological effects, and the clinical potential of circulating tumor deoxyribonucleoprotein complexes.

Liquid biopsies to predict CDK4/6 inhibitor efficacy and resistance in breast cancer

Cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors combined with endocrine therapy have transformed the treatment of estrogen receptor-positive (ER+) and human epidermal growth factor receptor 2 negative (HER2-) metastatic breast cancer. However, some patients do not respond to this treatment, and patients inevitably develop resistance, such that novel biomarkers are needed to predict primary resistance, monitor treatment response for acquired resistance, and personalize treatment strategies. Circumventing the spatial and temporal limitations of tissue biopsy, newly developed liquid biopsy approaches have the potential to uncover biomarkers that can predict CDK4/6 inhibitor efficacy and resistance in breast cancer patients through a simple blood test. Studies on circulating tumor DNA (ctDNA)-based liquid biopsy biomarkers of CDK4/6 inhibitor resistance have focused primarily on genomic alterations and have failed thus far to identify clear and clinically validated predictive biomarkers, but emerging epigenetic ctDNA methodologies hold promise for further discovery. The present review outlines recent advances and future directions in ctDNA-based biomarkers of CDK4/6 inhibitor treatment response.

Integrating chromatin accessibility states in the design of targeted sequencing panels for liquid biopsy

Dying tumor cells shed DNA fragments into the circulation that are known as circulating tumor DNA (ctDNA). Liquid biopsy tests aim to detect cancer using known markers, including genetic alterations and epigenetic profiles of ctDNA. Despite various advantages, the major limitation remains the low fraction of tumor-originating DNA fragments in a high background of normal blood-cell originating fragments in the cell-free DNA (cfDNA) pool in plasma. Deep targeted sequencing of cfDNA allows for enrichment of fragments in known cancer marker-associated regions of the genome, thus increasing the chances of detecting the low fraction variant harboring fragments. Most targeted sequencing panels are designed to include known recurrent mutations or methylation markers of cancer. Here, we propose the integration of cancer-specific chromatin accessibility states into panel designs for liquid biopsy. Using machine learning approaches, we first identify accessible and inaccessible chromatin regions specific to each major human cancer type. We then introduce a score that quantifies local chromatin accessibility in tumor relative to blood cells and show that this metric can be useful for prioritizing marker regions with higher chances of being detected in cfDNA for inclusion in future panel designs.

Molecular and cytogenetic characterization of myelodysplastic syndromes in cell-free DNA

Molecular and cytogenetic studies are essential for diagnosis and prognosis in patients with myelodysplastic syndromes (MDSs). Cell-free DNA (cfDNA) analysis has been reported to be a reliable noninvasive approach for detecting molecular abnormalities in MDS; however, there is limited information about cytogenetic alterations and monitoring in cfDNA. We assessed the molecular and cytogenetic profile of a cohort of 70 patients with MDS by next-generation sequencing (NGS) of cfDNA and compared the results to sequencing of paired bone marrow (BM) DNA. Sequencing of BM DNA and cfDNA showed a comparable mutational profile (92.1% concordance), and variant allele frequencies (VAFs) strongly correlated between both sample types. Of note, SF3B1 mutations were detected with significantly higher VAFs in cfDNA than in BM DNA. NGS and microarrays were highly concordant in detecting chromosomal alterations although with lower sensitivity than karyotype and fluorescence in situ hybridization. Nevertheless, all cytogenetic aberrations detected by NGS in BM DNA were also detected in cfDNA. In addition, we monitored molecular and cytogenetic alterations and observed an excellent correlation between the VAFs of mutations in BM DNA and cfDNA across multiple matched time points. A decrease in the cfDNA VAFs was detected in patients responding to therapy, but not in nonresponding patients. Of note, cfDNA analysis also showed cytogenetic evolution in 2 nonresponsive cases. In summary, although further studies with larger cohorts are needed, our results support the analysis of cfDNA as a promising strategy for performing molecular characterization, detection of chromosomal aberrations and monitoring of patients with MDS.

Nucleosome footprinting in plasma cell-free DNA for the pre-surgical diagnosis of ovarian cancer

Fragmentation patterns of plasma cell-free DNA (cfDNA) are known to reflect nucleosome positions of cell types contributing to cfDNA. Based on cfDNA fragmentation patterns, the deviation in nucleosome footprints was quantified between diagnosed ovarian cancer patients and healthy individuals. Multinomial modeling was subsequently applied to capture these deviations in a per sample nucleosome footprint score. Validation was performed in 271 cfDNAs pre-surgically collected from women with an adnexal mass. We confirmed that nucleosome scores were elevated in invasive carcinoma patients, but not in patients with benign or borderline disease. Combining nucleosome scores with chromosomal instability scores assessed in the same cfDNA improved prediction of malignancy. Nucleosome scores were, however, more reliable to predict non-high-grade serous ovarian tumors, which are characterized by low chromosomal instability. These data highlight that compared to chromosomal instability, nucleosome footprinting provides a complementary and more generic read-out for pre-surgical diagnosis of invasive disease in women with adnexal masses.

Cell-Free DNA Fragmentomics in Liquid Biopsy

Cell-free DNA (cfDNA) in bodily fluids has rapidly transformed the development of noninvasive prenatal testing, cancer liquid biopsy, and transplantation monitoring. Plasma cfDNA consists of a mixture of molecules originating from various bodily tissues. The study of the fragmentation patterns of cfDNA, also referred to as ‘fragmentomics’, is now an actively pursued area of biomarker research. Clues that cfDNA fragmentation patterns might carry information concerning the tissue of origin of cfDNA molecules have come from works demonstrating that circulating fetal, tumor-derived, and transplanted liver-derived cfDNA molecules have a shorter size distribution than the background mainly of hematopoietic origin. More recently, an improved understanding of cfDNA fragmentation has provided many emerging fragmentomic markers, including fragment sizes, preferred ends, end motifs, single-stranded jagged ends, and nucleosomal footprints. The intrinsic biological link between activities of various DNA nucleases and characteristic fragmentations has been demonstrated. In this review, we focus on the biological properties of cell-free DNA unveiled recently and their potential clinical applications.

Inferring gene expression from cell-free DNA fragmentation profiles

Profiling of circulating tumor DNA (ctDNA) in the bloodstream shows promise for noninvasive cancer detection. Chromatin fragmentation features have previously been explored to infer gene expression profiles from cell-free DNA (cfDNA), but current fragmentomic methods require high concentrations of tumor-derived DNA and provide limited resolution. Here we describe promoter fragmentation entropy as an epigenomic cfDNA feature that predicts RNA expression levels at individual genes. We developed 'epigenetic expression inference from cell-free DNA-sequencing' (EPIC-seq), a method that uses targeted sequencing of promoters of genes of interest. Profiling 329 blood samples from 201 patients with cancer and 87 healthy adults, we demonstrate classification of subtypes of lung carcinoma and diffuse large B cell lymphoma. Applying EPIC-seq to serial blood samples from patients treated with PD-(L)1 immune-checkpoint inhibitors, we show that gene expression profiles inferred by EPIC-seq are correlated with clinical response. Our results indicate that EPIC-seq could enable noninvasive, high-throughput tissue-of-origin characterization with diagnostic, prognostic and therapeutic potential.

Combinatorial Power of cfDNA, CTCs and EVs in Oncology

Liquid biopsy is a promising technique for clinical management of oncological patients. The diversity of analytes circulating in the blood useable for liquid biopsy testing is enormous. Circulating tumor cells (CTCs), cell-free DNA (cfDNA) and extracellular vesicles (EVs), as well as blood cells and other soluble components in the plasma, were shown as liquid biopsy analytes. A few studies directly comparing two liquid biopsy analytes showed a benefit of one analyte over the other, while most authors concluded the benefit of the additional analyte. Only three years ago, the first studies to examine the value of a characterization of more than two liquid biopsy analytes from the same sample were conducted. We attempt to reflect on the recent development of multimodal liquid biopsy testing in this review. Although the analytes and clinical purposes of the published multimodal studies differed significantly, the additive value of the analytes was concluded in almost all projects. Thus, the blood components, as liquid biopsy reservoirs, are complementary rather than competitive, and orthogonal data sets were even shown to harbor synergistic effects. The unmistakable potential of multimodal liquid biopsy testing, however, is dampened by its clinical utility, which is yet to be proven, the lack of methodical standardization and insufficiently mature reimbursement, logistics and data handling.

LIQUORICE: detection of epigenetic signatures in liquid biopsies based on whole-genome sequencing data

Summary

Fragmentation patterns of cell-free DNA reflect the chromatin structure of the cells from which these fragments are derived. Nucleosomes protect the DNA from fragmentation, resulting in decreased sequencing coverage in regions of open chromatin. LIQUORICE is a user-friendly software tool that takes aligned whole-genome sequencing data as input and calculates bias-corrected coverage signatures for predefined, application-specific sets of genomic regions. The tool thereby enables a blood-based analysis of cell death in the body, and it provides a minimally invasive assessment of tumor chromatin states and cell-of-origin. With user-defined sets of regions that exhibit tissue-specific or disease-specific open chromatin, LIQUORICE can be applied to a wide range of detection, classification and quantification tasks in the analysis of liquid biopsies.

Availability and implementation

LIQUORICE is freely and openly available as a Python package and command-line tool for UNIX-based systems from bioconda. Documentation, examples and usage instructions are provided at http://liquorice.computational-epigenetics.org.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

A clinician’s handbook for using ctDNA throughout the patient journey

Background

The promise of precision cancer medicine presently centers around the genomic sequence of a patient’s tumor being translated into timely, actionable information to inform clinical care. The analysis of cell-free DNA from liquid biopsy, which contains circulating tumor DNA (ctDNA) in patients with cancer, has proven to be amenable to various settings in oncology. However, open questions surrounding the clinical validity and utility of plasma-based analyses have hindered widespread clinical adoption.

Main body

Owing to the rapid evolution of the field, studies supporting the use of ctDNA as a biomarker throughout a patient’s journey with cancer have accumulated in the last few years, warranting a review of the latest status for clinicians who may employ ctDNA in their precision oncology programs. In this work, we take a step back from the intricate coverage of detection approaches described extensively elsewhere and cover basic concepts around the practical implementation of next generation sequencing (NGS)-guided liquid biopsy. We compare relevant targeted and untargeted approaches to plasma DNA analysis, describe the latest evidence for clinical validity and utility, and highlight the value of genome-wide ctDNA analysis, particularly as it relates to early detection strategies and discovery applications harnessing the non-coding genome.

Conclusions

The maturation of liquid biopsy for clinical application will require interdisciplinary efforts to address current challenges. However, patients and clinicians alike may greatly benefit in the future from its incorporation into routine oncology care.

Liquid biopsy: a step closer to transform diagnosis, prognosis and future of cancer treatments

Over the past decade, invasive techniques for diagnosing and monitoring cancers are slowly being replaced by non-invasive methods such as liquid biopsy. Liquid biopsies have drastically revolutionized the field of clinical oncology, offering ease in tumor sampling, continuous monitoring by repeated sampling, devising personalized therapeutic regimens, and screening for therapeutic resistance. Liquid biopsies consist of isolating tumor-derived entities like circulating tumor cells, circulating tumor DNA, tumor extracellular vesicles, etc., present in the body fluids of patients with cancer, followed by an analysis of genomic and proteomic data contained within them. Methods for isolation and analysis of liquid biopsies have rapidly evolved over the past few years as described in the review, thus providing greater details about tumor characteristics such as tumor progression, tumor staging, heterogeneity, gene mutations, and clonal evolution, etc. Liquid biopsies from cancer patients have opened up newer avenues in detection and continuous monitoring, treatment based on precision medicine, and screening of markers for therapeutic resistance. Though the technology of liquid biopsies is still evolving, its non-invasive nature promises to open new eras in clinical oncology. The purpose of this review is to provide an overview of the current methodologies involved in liquid biopsies and their application in isolating tumor markers for detection, prognosis, and monitoring cancer treatment outcomes.

Circulating Tumour DNA in Melanoma-Clinic Ready?

PURPOSE OF REVIEW

Liquid biopsies, including circulating tumour DNA (ctDNA), can inform a variety of clinical questions. This review examines the potential role of ctDNA as a clinical tool to inform clinical decision-making from early to late stage cutaneous melanoma.

RECENT FINDINGS

In pre-clinical studies, ctDNA has been shown to detect minimal residual disease and molecular relapse; predict and monitor response to therapy; and identify key resistance mechanisms. Here, we examine the potential utility of ctDNA and discuss its limitations for use in patients with melanoma. We present novel clinical trials, which are testing its value as a tool to augment clinical decision-making. Finally, we discuss the steps that are needed to ensure that ctDNA is used optimally in order to improve outcomes for patients with melanoma. Preclinical studies have shown that ctDNA has huge potential to provide real-time information about disease status in patients with melanoma. It is now time to test it rigorously within clinical trials to assess how it can be optimally used to benefit patients in the clinic.

Circulating tumor DNA in cancer diagnosis, monitoring, and prognosis

BACKGROUND

Circulating tumor DNA (ctDNA) has become one of the crucial components for cancer detection with the increase of precision medicine practice. ctDNA has great potential as a blood-based biomarker for the detection and treatment of cancer in its early stages. The purpose of this article was to discuss ctDNA and how it can be utilized to detect cancer. The benefits and drawbacks of this cancer detection technology, as well as the field's future possibilities in various cancer management scenarios, are discussed. MAIN TEXT: ctDNA has clinical applications in disease diagnosis and monitoring. It can be used to identify mutations of interest and genetic heterogeneity. Another use of ctDNA is to monitor the effects of therapy by detecting mutation-driven resistance. Different technologies are being used for the detection of ctDNA. Next-generation sequencing, digital PCR, real-time PCR, and mass spectrometry are used. Using dPCR makes it possible to partition and analyze individual target sequences from a complex mixture. Mass-spectrometry technology enables accurate detection and quantification of ctDNA mutations at low frequency. Surface-enhanced Raman spectroscopy (SERS) and UltraSEEK are two systems based on this technology. There is no unified standard for detecting ctDNA as it exists in a low concentration in blood. As there is no defined approach, false positives occur in several methods due to inadequate sensitivities. Techniques used in ctDNA are costly and there is a limitation in clinical settings.

SHORT CONCLUSION

A detailed investigation is urgently needed to increase the test's accuracy and sensitivity. To find a standard marker for all forms of cancer DNA, more study is needed. Low concentrations of ctDNA in a sample require improved technology to provide the precision that low concentrations of ctDNA in a sample afford.

Effective Identification of Maternal Malignancies in Pregnancies Undergoing Noninvasive Prenatal Testing

Background: The existence of maternal malignancy may cause false-positive results or failed tests of NIPT. Though recent studies have shown multiple chromosomal aneuploidies (MCA) are associated with malignancy, there is still no effective solution to identify maternal cancer patients from pregnant women with MCA results using NIPT. We aimed to develop a new method to effectively detect maternal cancer in pregnant women with MCA results using NIPT and a random forest classifier to identify the tissue origin of common maternal cancer types.

Methods: For examination, 496 participants with MCA results via NIPT were enrolled from January 2016 to June 2019 at BGI. Cancer and non-cancer participants were confirmed through the clinical follow-up. The cohort comprising 42 maternal cancer cases and 294 non-cancer cases enrolled from January 2016 to December 2017 was utilized to develop a method named mean of the top five chromosome z scores (MTOP5Zscores). The remaining 160 participants enrolled from January 2018 to June 2019 were used to validate the performance of MTOP5Zscores. We established a random forest model to classify three common cancer types using normalized Pearson correlation coefficient (NPCC) values, z scores of 22 chromosomes, and seven plasma tumor markers (PTMs) as predictor variables.

Results: 62 maternal cancer cases were confirmed with breast cancer, liver cancer, and lymphoma, the most common cancer types. MTOP5Zscores showed a sensitivity of 85% (95% confidence interval (CI), 62.11–96.79%) and specificity of 80% (95% CI, 72.41–88.28%) in the detection of maternal cancer among pregnant women with MCA results. The sensitivity of the classifier was 93.33, 66.67, and 50%, while specificity was 66.67, 90, and 97.06%, and positive predictive value (PPV) was 60.87, 72.73, and 80% for the prediction of breast cancer, liver cancer, and lymphoma, respectively.

Conclusion: This study presents a solution to identify maternal cancer patients from pregnant women with MCA results using NIPT, indicating it as a value-added application of NIPT in the detection of maternal malignancies in addition to screening for fetal aneuploidies with no extra cost.

Refined characterization of circulating tumor DNA through biological feature integration

Circulating tumor DNA (ctDNA) in blood plasma is present at very low concentrations compared to cell-free DNA (cfDNA) of non-tumor origin. To enhance ctDNA detection, recent studies have been focused on understanding the non-random fragmentation pattern of cfDNA. These studies have investigated fragment sizes, genomic position of fragment end points, and fragment end motifs. Although these features have been described and shown to be aberrant in cancer patients, there is a lack of understanding of how the individual and integrated analysis of these features enrich ctDNA fraction and enhance ctDNA detection. Using whole genome sequencing and copy number analysis of plasma samples from 5 high grade serious ovarian cancer patients, we observed that (1) ctDNA is enriched not only in fragments shorter than mono-nucleosomes (~ 167 bp), but also in those shorter than di-nucleosomes (~ 240-330 bp) (28-159% enrichment). (2) fragments that start and end at the border or within the nucleosome core are enriched in ctDNA (5-46% enrichment). (3) certain DNA motifs conserved in regions 10 bp up- and down- stream of fragment ends (i.e. cleavage sites) could be used to detect tumor-derived fragments (10-44% enrichment). We further show that the integrated analysis of these three features resulted in a higher enrichment of ctDNA when compared to using fragment size alone (additional 7-25% enrichment after fragment size selection). We believe these genome wide features, which are independent of genetic mutational changes, could allow new ways to analyze and interpret cfDNA data, as significant aberrations of these features from a healthy state could improve its utility as a diagnostic biomarker.

Characteristics, origin, and potential for cancer diagnostics of ultrashort plasma cell-free DNA

Current evidence suggests that plasma cell-free DNA (cfDNA) is fragmented around a mode of 166 bp. Data supporting this view has been mainly acquired through the analysis of double-stranded cfDNA. The characteristics and diagnostic potential of single-stranded and damaged double-stranded cfDNA in healthy individuals and cancer patients remain unclear. Here, through a combination of high-affinity magnetic bead-based DNA extraction and single-stranded DNA sequencing library preparation (MB-ssDNA), we report the discovery of a large proportion of cfDNA fragments centered at ∼50 bp. We show that these "ultrashort" cfDNA fragments have a greater relative abundance in plasma of healthy individuals (median = 19.1% of all sequenced cfDNA fragments, n = 28) than in plasma of patients with cancer (median = 14.2%, n = 21, P < 0.0001). The ultrashort cfDNA fragments map to accessible chromatin regions of blood cells, particularly in promoter regions with the potential to adopt G-quadruplex (G4) DNA secondary structures. G4-positive promoter chromatin accessibility is significantly enriched in ultrashort plasma cfDNA fragments from healthy individuals relative to patients with cancers (P < 0.0001), in whom G4-cfDNA enrichment is inversely associated with copy number aberration-inferred tumor fractions. Our findings redraw the landscape of cfDNA fragmentation by identifying and characterizing a novel population of ultrashort plasma cfDNA fragments. Sequencing of MB-ssDNA libraries could facilitate the characterization of gene regulatory regions and DNA secondary structures via liquid biopsy. Our data underline the diagnostic potential of ultrashort cfDNA through classification for cancer patients.

Cell-free DNA technologies for the analysis of brain cancer

Survival for glioma patients has shown minimal improvement over the past 20 years. The ability to detect and monitor gliomas relies primarily upon imaging technologies that lack sensitivity and specificity, especially during the post-surgical treatment phase. Treatment-response monitoring with an effective liquid-biopsy paradigm may also provide the most facile clinical scenario for liquid-biopsy integration into brain-tumour care. Conceptually, liquid biopsy is advantageous when compared with both tissue sampling (less invasive) and imaging (more sensitive and specific), but is hampered by technical and biological problems. These problems predominantly relate to low concentrations of tumour-derived DNA in the bloodstream of glioma patients. In this review, we highlight methods by which the neuro-oncological scientific and clinical communities have attempted to circumvent this limitation. The use of novel biological, technological and computational approaches will be explored. The utility of alternate bio-fluids, tumour-guided sequencing, epigenomic and fragmentomic methods may eventually be leveraged to provide the biological and technological means to unlock a wide range of clinical applications for liquid biopsy in glioma.

Liquid biopsy: the value of different bodily fluids

Liquid biopsies have gained an increasing interest in the last years among medical and scientific communities. Indeed, the value of liquid effusions, while less invasive and more accurate techniques, has been markedly highlighted. Peripheral blood comprises the most often analyzed sample, but recent evidences have pointed out the huge importance of other bodily fluids, including pleural and peritoneal fluids, urine, saliva and cerebrospinal fluid in the detection and monitoring of different tumor types. In face to these advances, this review aims to provide an overview of the value of tumor-associated mutations, detectable in different effusions, and how they can be used in clinical practice, namely in prognosis assessment and early disease and minimal disease recurrence detection, and in predicting the treatment response or acquired-resistance development.

NucPosDB: a database of nucleosome positioning in vivo and nucleosomics of cell-free DNA

Nucleosome positioning is involved in many gene regulatory processes happening in the cell, and it may change as cells differentiate or respond to the changing microenvironment in a healthy or diseased organism. One important implication of nucleosome positioning in clinical epigenetics is its use in the “nucleosomics” analysis of cell-free DNA (cfDNA) for the purpose of patient diagnostics in liquid biopsies. The rationale for this is that the apoptotic nucleases that digest chromatin of the dying cells mostly cut DNA between nucleosomes. Thus, the short pieces of DNA in body fluids reflect the positions of nucleosomes in the cells of origin. Here, we report a systematic nucleosomics database — NucPosDB — curating published nucleosome positioning datasets in vivo as well as datasets of sequenced cell-free DNA (cfDNA) that reflect nucleosome positioning in situ in the cells of origin. Users can select subsets of the database by a number of criteria and then obtain raw or processed data. NucPosDB also reports the originally determined regions with stable nucleosome occupancy across several individuals with a given condition. An additional section provides a catalogue of computational tools for the analysis of nucleosome positioning or cfDNA experiments and theoretical algorithms for the prediction of nucleosome positioning preferences from DNA sequence. We provide an overview of the field, describe the structure of the database in this context, and demonstrate data variability using examples of different medical conditions. NucPosDB is useful both for the analysis of fundamental gene regulation processes and the training of computational models for patient diagnostics based on cfDNA. The database currently curates ~ 400 publications on nucleosome positioning in cell lines and in situ as well as cfDNA from > 10,000 patients and healthy volunteers. For open-access cfDNA datasets as well as key MNase-seq datasets in human cells, NucPosDB allows downloading processed mapped data in addition to the regions with stable nucleosome occupancy. NucPosDB is available at https://generegulation.org/nucposdb/.

Recent Advances in Device Engineering and Computational Analysis for Characterization of Cell-Released Cancer Biomarkers

During cancer progression, tumors shed different biomarkers into the bloodstream, including circulating tumor cells (CTCs), extracellular vesicles (EVs), circulating cell-free DNA (cfDNA), and circulating tumor DNA (ctDNA). The analysis of these biomarkers in the blood, known as 'liquid biopsy' (LB), is a promising approach for early cancer detection and treatment monitoring, and more recently, as a means for cancer therapy. Previous reviews have discussed the role of CTCs and ctDNA in cancer progression; however, ctDNA and EVs are rapidly evolving with technological advancements and computational analysis and are the subject of enormous recent studies in cancer biomarkers. In this review, first, we introduce these cell-released cancer biomarkers and briefly discuss their clinical significance in cancer diagnosis and treatment monitoring. Second, we present conventional and novel approaches for the isolation, profiling, and characterization of these markers. We then investigate the mathematical and in silico models that are developed to investigate the function of ctDNA and EVs in cancer progression. We convey our views on what is needed to pave the way to translate the emerging technologies and models into the clinic and make the case that optimized next-generation techniques and models are needed to precisely evaluate the clinical relevance of these LB markers.

A Deep-Learning Pipeline for TSS Coverage Imputation From Shallow Cell-Free DNA Sequencing

Cell-free DNA (cfDNA) serves as a footprint of the nucleosome occupancy status of transcription start sites (TSSs), and has been subject to wide development for use in noninvasive health monitoring and disease detection. However, the requirement for high sequencing depth limits its clinical use. Here, we introduce a deep-learning pipeline designed for TSS coverage profiles generated from shallow cfDNA sequencing called the Autoencoder of cfDNA TSS (AECT) coverage profile. AECT outperformed existing single-cell sequencing imputation algorithms in terms of improvements to TSS coverage accuracy and the capture of latent biological features that distinguish sex or tumor status. We built classifiers for the detection of breast and rectal cancer using AECT-imputed shallow sequencing data, and their performance was close to that achieved by high-depth sequencing, suggesting that AECT could provide a broadly applicable noninvasive screening approach with high accuracy and at a moderate cost.

At the dawn: cell-free DNA fragmentomics and gene regulation

Epigenetic mechanisms play instrumental roles in gene regulation during embryonic development and disease progression. However, it is challenging to non-invasively monitor the dynamics of epigenomes and related gene regulation at inaccessible human tissues, such as tumours, fetuses and transplanted organs. Circulating cell-free DNA (cfDNA) in peripheral blood provides a promising opportunity to non-invasively monitor the genomes from these inaccessible tissues. The fragmentation patterns of plasma cfDNA are unevenly distributed in the genome and reflect the in vivo gene-regulation status across multiple molecular layers, such as nucleosome positioning and gene expression. In this review, we revisited the computational and experimental approaches that have been recently developed to measure the cfDNA fragmentomics across different resolutions comprehensively. Moreover, cfDNA in peripheral blood is released following cell death, after apoptosis or necrosis, mainly from haematopoietic cells in healthy people and diseased tissues in patients. Several cfDNA-fragmentomics approaches showed the potential to identify the tissues-of-origin in cfDNA from cancer patients and healthy individuals. Overall, these studies paved the road for cfDNA fragmentomics to non-invasively monitor the in vivo gene-regulatory dynamics in both peripheral immune cells and diseased tissues.

Liquid Biopsies beyond Mutation Calling: Genomic and Epigenomic Features of Cell-Free DNA in Cancer

Cell-free DNA (cfDNA) analysis using liquid biopsies is a non-invasive method to gain insights into the biology, therapy response, mechanisms of acquired resistance and therapy escape of various tumors. While it is well established that individual cancer treatment options can be adjusted by panel next-generation sequencing (NGS)-based evaluation of driver mutations in cfDNA, emerging research additionally explores the value of deep characterization of tumor cfDNA genomics and fragmentomics as well as nucleosome modifications (chromatin structure), and methylation patterns (epigenomics) for comprehensive and multi-modal assessment of cfDNA. These tools have the potential to improve disease monitoring, increase the sensitivity of minimal residual disease identification, and detection of cancers at earlier stages. Recent progress in emerging technologies of cfDNA analysis is summarized, the added potential clinical value is highlighted, strengths and limitations are identified and compared with conventional targeted NGS analysis, and current challenges and future directions are discussed.

Multi-region sequencing reveals genetic correlation between esophageal squamous cell carcinoma and matched cell-free DNA

PURPOSE

This study aimed to determine if both ubiquitous and heterogeneous somatic mutations could be detected in circulating cell-free DNA (cfDNA) in patients with esophageal squamous cell carcinoma (ESCC).

METHODS

Paired multi-regional tumor tissues, cfDNA, and white blood cells (WBCs) were collected from five ESCC patients before treatment, as part of an ongoing prospective study (NCT02395705). Samples from Cohort 1 were sequenced by whole-exome sequencing and samples from Cohort 2 were sequenced by targeted capture sequencing. Somatic single-nucleotide variations (SNVs) were detected by comparing solid tumor or cfDNA with matched WBCs, with a minimum variant allele frequency (VAF) of 0.1% and P value <0.05.

RESULTS

Genomic DNA (gDNA) and plasma-derived cfDNA from 26 samples were sequenced successfully. In Cohort 1, a significant linear relationship between the tumor and cfDNA VAFs (R²= 0.78, P < 0.0001) was found. In Cohort 2, cfDNA could recover an average of 60.7% (31/51; range, 35.7-76.2%) of somatic mutations present in matched solid tumors. There was a significant positive correlation in VAFs between cfDNA and matched solid tumor tissues (R²= 0.92, P < 0.0001).

CONCLUSIONS

Both sequencing approaches revealed high intratumoral heterogeneity in ESCC, and enabled the detection of both ubiquitous and heterogeneous mutations in cfDNA.

Analysis of cf-mtDNA and cf-nDNA fragment size distribution using different isolation methods in BV-2 cell supernatant of starvation-induced autophagy

Fragment size distribution, the important biological properties of cell-free DNA (cfDNA), provides useful information required for diagnostic assay development. However, besides methodological discrepancies, it varies due to the complicated origins and occurrences of in vivo cfDNA. In addition, limited data are available concerning the cfDNA associated with autophagy and distributional difference between cf-mitochondrial DNA (cf-mtDNA) and cf-nuclear DNA (cf-nDNA) fragments. Here we developed an in vitro model of mouse microglial cell (BV-2) with starvation-induced autophagy, in which cfDNA was isolated from the cell supernatant by ultrafiltration (UF) and column-based commercial kit (CC), respectively. Using Agilent 2100 Bioanalyzer, a DNA ladder pattern as the presence of peaks corresponding to mono-, di- and tri-nucleosomes was clearly visualized both in isolation products of UF and CC. However, we also detected shorter fragments than mono-nucleosome by UF. In comparing the UF and CC, we found that the former produced the higher recovery efficiency for spiked-in DNA of shorter fragments than mono-nucleosome in both water and medium, but the latter was superior for spiked-in DNA fragments which were longer than or equal to mono-nucleosome in medium. Combined with these two isolation methods, we have observed that autophagy-associated cf-mtDNA and cf-nDNA were both highly enriched in <mono-nucleosomes fragments more than 71%, and showed no significant differences in the relative percentages for these four fragment sizes. These results have improved our understanding of the fragment size distribution of autophagy-derived cf-mtDNA and cf-nDNA in vitro, and might further develop application of cfDNA as a diagnostic tool.

Precision Medicine for Colorectal Cancer with Liquid Biopsy and Immunotherapy

Simple Summary

There are some challenges to improve the clinical outcome of colorectal cancers (CRCs) by implementing new technologies, such as early detection of recurrence/relapse and selection of appropriate drugs based on the genomic profiles of tumors. For example, the genomic characteristics of tumors can be analyzed by blood-based tests, namely ‘liquid biopsies’, which are minimally-invasive and can be performed repeatedly during the treatment course. Hence, liquid biopsies are considered to hold great promise to fill these gaps in clinical routines. In this review, we addressed clinical usefulness of liquid biopsies in the clinical management of CRC patients, including cancer screening, detection of minimal residual disease, selection of appropriate molecular-targeted drugs, monitoring of the treatment responsiveness, and very early detection of recurrence/relapse of the disease. Furthermore, we discussed the possibility of adoptive T cell therapies and a future personalized immunotherapy based on tumor genome information.

Abstract

In the field of colorectal cancer (CRC) treatment, diagnostic modalities and chemotherapy regimens have progressed remarkably in the last two decades. However, it is still difficult to identify minimal residual disease (MRD) necessary for early detection of recurrence/relapse of tumors and to select and provide appropriate drugs timely before a tumor becomes multi-drug-resistant and more aggressive. We consider the leveraging of in-depth genomic profiles of tumors as a significant breakthrough to further improve the overall prognosis of CRC patients. With the recent technological advances in methodologies and bioinformatics, the genomic profiles can be analyzed profoundly without delay by blood-based tests—‘liquid biopsies’. From a clinical point of view, a minimally-invasive liquid biopsy is thought to be a promising method and can be implemented in routine clinical settings in order to meet unmet clinical needs. In this review, we highlighted clinical usefulness of liquid biopsies in the clinical management of CRC patients, including cancer screening, detection of MRD, selection of appropriate molecular-targeted drugs, monitoring of the treatment responsiveness, and very early detection of recurrence/relapse of the disease. In addition, we addressed a possibility of adoptive T cell therapies and a future personalized immunotherapy based on tumor genome information.

Recent advances in blood-based and artificial intelligence-enhanced approaches for gastrointestinal cancer diagnosis

Gastrointestinal (GI) cancers are among the most common cancer types and leading causes of cancer-related deaths worldwide. There is a tremendous clinical need for effective early diagnosis for better healthcare of GI cancer patients. In this article, we provide a short overview of the recent advances in GI cancer diagnosis. In the first part, we discuss the applications of blood-based biomarkers, such as plasma circulating cell-free DNA, circulating tumor cells, extracellular vesicles, and circulating cell-free RNA, for cancer liquid biopsies. In the second part, we review the current trends of artificial intelligence (AI) for pathology image and tissue biopsy analysis for GI cancer, as well as deep learning-based approaches for purity assessment of tissue biopsies. We further provide our opinions on the future directions in blood-based and AI-enhanced approaches for GI cancer diagnosis, and we think that these fields will have more intensive integrations with clinical needs in the near future.

Clinical and biological determinants of circulating tumor DNA detection and prognostication using a next-generation sequencing panel assay

Circulating tumor DNA (ctDNA) is utilized for molecular profiling of cancers, and is under investigation for a growing number of applications based on the assumption that ctDNA levels faithfully reflect disease burden. Our objective was to investigate whether patient and tumor characteristics may impact ctDNA detection or levels and the prognostic significance of ctDNA levels or mutations. We performed a retrospective cohort analysis of a comprehensively annotated cohort of 561 patients at a National Cancer Institute-designated comprehensive cancer center with advanced solid cancers who underwent ctDNA testing using a commercial targeted next-generation sequencing assay. ctDNA detection in advanced cancers was associated with older age, non-obese body mass index, and diabetes, but not with tumor diameter, volume, lesion number, or other pathological features. Regression models indicate that no more than 14.3% of the variance in ctDNA levels between patients was explained by known clinical factors and disease burden. Even after adjusting for established prognostic factors and tumor burden, ctDNA levels were associated with worse survival among patients without prior systemic therapy, while ctDNA mutations were associated with survival among patients who previously received systemic treatment. These findings uncover clinical factors that affect ctDNA detection in patients with advanced cancers and challenge the convention that ctDNA is a surrogate for tumor burden. Our study also indicates that the prognostic value of ctDNA levels and mutations are independent of tumor burden and dependent on treatment context.

FinaleDB: a browser and database of cell-free DNA fragmentation patterns

Summary

Circulating cell-free DNA (cfDNA) is a promising biomarker for the diagnosis and prognosis of many diseases, including cancer. The genome-wide non-random fragmentation patterns of cfDNA are associated with the nucleosomal protection, epigenetic environment and gene expression in the cell types that contributed to cfDNA. However, current progress on the development of computational methods and understanding of molecular mechanisms behind cfDNA fragmentation patterns is significantly limited by the controlled-access of cfDNA whole-genome sequencing (WGS) dataset. Here, we present FinaleDB (FragmentatIoN AnaLysis of cEll-free DNA DataBase), a comprehensive database to host thousands of uniformly processed and curated de-identified cfDNA WGS datasets across different pathological conditions. Furthermore, FinaleDB comes with a fragmentation genome browser, from which users can seamlessly integrate thousands of other omics data in different cell types to experience a comprehensive view of both gene-regulatory landscape and cfDNA fragmentation patterns.

Availability and implementation

FinaleDB service: http://finaledb.research.cchmc.org/. FinaleDB source code: https://github.com/epifluidlab/finaledb_portal, https://github.com/epifluidlab/finaledb_workflow.

Supplementary information

Supplementary data are available at Bioinformatics online.

Liquid biopsy in lymphoma: Is it primed for clinical translation?

The simultaneous growth in our understanding of lymphoma biology and the burgeoning therapeutic options has come with a renewed drive for precision-based approaches and how best to incorporate them into contemporary and future patient care. In the hunt for accurate and sensitive biomarkers, liquid biopsies, particularly circulating tumour DNA, have come to the forefront as a promising tool in multiple cancer types including lymphomas, with considerable implications for clinical practice. Liquid biopsy analyses could supplement existing tissue biopsies with distinct advantages including the minimally invasive nature and the ease with which it can be repeated during a patient's clinical journey. Circulating tumour DNA (ctDNA) analyses has been and continues to be evaluated across lymphoma subtypes with potential applications as a diagnostic, disease monitoring and treatment selection tool. To make the leap into the clinic, these assays must demonstrate accuracy, reliability and a quick turnaround to be employed in the real-time clinical management of lymphoma patients. Here, we review the available ctDNA assays and discuss key practical and technical issues around improving sensitivity. We then focus on their potential roles in several lymphoma subtypes exemplified by recent studies and provide a glimpse of different features that can be analysed beyond ctDNA.

Detection of Cell Types Contributing to Cancer From Circulating, Cell-Free Methylated DNA

Detection of cellular changes in tissue biopsies has been the basis for cancer diagnostics. However, tissue biopsies are invasive and limited by inaccuracies due to sampling locations, restricted sampling frequency, and poor representation of tissue heterogeneity. Liquid biopsies are emerging as a complementary approach to traditional tissue biopsies to detect dynamic changes in specific cell populations. Cell-free DNA (cfDNA) fragments released into the circulation from dying cells can be traced back to the tissues and cell types they originated from using DNA methylation, an epigenetic regulatory mechanism that is highly cell-type specific. Decoding changes in the cellular origins of cfDNA over time can reveal altered host tissue homeostasis due to local cancer invasion and metastatic spread to distant organs as well as treatment responses. In addition to host-derived cfDNA, changes in cancer cells can be detected from cell-free, circulating tumor DNA (ctDNA) by monitoring DNA mutations carried by cancer cells. Here, we will discuss computational approaches to identify and validate robust biomarkers of changed tissue homeostasis using cell-free, methylated DNA in the circulation. We highlight studies performing genome-wide profiling of cfDNA methylation and those that combine genetic and epigenetic markers to further identify cell-type specific signatures. Finally, we discuss opportunities and current limitations of these approaches for implementation in clinical oncology.

Analysis of recurrently protected genomic regions in cell-free DNA found in urine

Cell-free DNA (cfDNA) in urine is a promising analyte for noninvasive diagnostics. However, urine cfDNA is highly fragmented. Whether characteristics of these fragments reflect underlying genomic architecture is unknown. Here, we characterized fragmentation patterns in urine cfDNA using whole-genome sequencing. Size distribution of urine cfDNA fragments showed multiple strong peaks between 40 and 120 base pairs (bp) with a modal size of 81- and sharp 10-bp periodicity, suggesting transient protection from complete degradation. These properties were robust to preanalytical perturbations, such as at-home collection and delay in processing. Genome-wide sequencing coverage of urine cfDNA fragments revealed recurrently protected regions (RPRs) conserved across individuals, with partial overlap with nucleosome positioning maps inferred from plasma cfDNA. The ends of cfDNA fragments clustered upstream and downstream of RPRs, and nucleotide frequencies of fragment ends indicated enzymatic digestion of urine cfDNA. Compared to plasma, fragmentation patterns in urine cfDNA showed greater correlation with gene expression and chromatin accessibility in epithelial cells of the urinary tract. We determined that tumor-derived urine cfDNA exhibits a higher frequency of aberrant fragments that end within RPRs. By comparing the fraction of aberrant fragments and nucleotide frequencies of fragment ends, we identified urine samples from cancer patients with an area under the curve of 0.89. Our results revealed nonrandom genomic positioning of urine cfDNA fragments and suggested that analysis of fragmentation patterns across recurrently protected genomic loci may serve as a cancer diagnostic.

Evolutionary conservation in noncoding genomic regions

Humans may share more genomic commonalities with other species than previously thought. According to current estimates, ~5% of the human genome is functionally constrained, which is a much larger fraction than the ~1.5% occupied by annotated protein-coding genes. Hence, ~3.5% of the human genome comprises likely functional conserved noncoding elements (CNEs) preserved among organisms, whose common ancestors existed throughout hundreds of millions of years of evolution. As whole-genome sequencing emerges as a standard procedure in genetic analyses, interpretation of variations in CNEs, including the elucidation of mechanistic and functional roles, becomes a necessity. Here, we discuss the phenomenon of noncoding conservation via four dimensions (sequence, regulatory conservation, spatiotemporal expression, and structure) and the potential significance of CNEs in phenotype variation and disease.

Noninvasive discrimination of benign and malignant breast lesions using genome-wide nucleosome profiles of plasma cell-free DNA

BACKGROUND

Breast malignancy is the most frequently diagnosed malignancy in women worldwide, and the diagnosis relies on invasive examinations. However, most clinical breast changes in women are benign, and invasive diagnostic approaches cause unnecessary suffering for the patients. Thus, a novel noninvasive approach for discriminating malignant breast lesions from benign lesions is needed.

METHODS

We performed cell-free DNA (cfDNA) sequencing on plasma samples from 173 malignant breast lesion patients, 158 benign breast lesion patients, and 102 healthy women. We then analyzed the cfDNA-based nucleosome profiles, which reflect the various tissues of origin and transcription factor activities. Moreover, by using machine learning classifiers along with the cfDNA sequencing data, we built classifiers for discriminating benign from malignant breast lesions. Receiver operating characteristic curve analyses were used to evaluate the performance of the classifiers.

RESULTS

cfDNA-based nucleosome profiles reflected the various tissues of origin and transcription factor activities in benign and malignant breast lesions. The cfDNA-based transcription factor activities and breast malignancy-specific transcription factor-binding site accessibility profiles could accurately distinguish benign and malignant breast lesions, with area under the curve values of 0.777 and 0.824, respectively.

CONCLUSIONS

Our proof-of-principle study established a methodology for noninvasively discriminating benign from malignant breast lesions.

Mutated circulating tumor DNA as a liquid biopsy in lung cancer detection and treatment

Over the past decade, substantial developments have been made in the detection of circulating tumor DNA (ctDNA)-cell-free DNA (cfDNA) fragments released into the circulation from tumor cells and displaying the genetic alterations of those cells. As such, ctDNA detected in liquid biopsies serves as a powerful tool for cancer patient stratification, therapy guidance, detection of resistance, and relapse monitoring. In this Review, we describe lung cancer diagnosis and monitoring strategies using ctDNA detection technologies and compile recent evidence regarding lung cancer-related mutation detection in liquid biopsy. We focus not only on epidermal growth factor receptor (EGFR) alterations, but also on significant co-mutations that shed more light on novel ctDNA-based liquid biopsy applications. Finally, we discuss future perspectives of early-cancer detection and clonal hematopoiesis filtering strategies, with possible inclusion of microbiome-driven liquid biopsy.

Transcriptional Start Site Coverage Analysis in Plasma Cell-Free DNA Reveals Disease Severity and Tissue Specificity of COVID-19 Patients

Symptoms of coronavirus disease 2019 (COVID-19) range from asymptomatic to severe pneumonia and death. A deep understanding of the variation of biological characteristics in severe COVID-19 patients is crucial for the detection of individuals at high risk of critical condition for the clinical management of the disease. Herein, by profiling the gene expression spectrum deduced from DNA coverage in regions surrounding transcriptional start site in plasma cell-free DNA (cfDNA) of COVID-19 patients, we deciphered the altered biological processes in the severe cases and demonstrated the feasibility of cfDNA in measuring the COVID-19 progression. The up- and downregulated genes in the plasma of severe patient were found to be closely related to the biological processes and functions affected by COVID-19 progression. More importantly, with the analysis of transcriptome data of blood cells and lung cells from control group and cases with severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection, we revealed that the upregulated genes were predominantly involved in the viral and antiviral activity in blood cells, reflecting the intense viral replication and the active reaction of immune system in the severe patients. Pathway analysis of downregulated genes in plasma DNA and lung cells also demonstrated the diminished adenosine triphosphate synthesis function in lung cells, which was evidenced to correlate with the severe COVID-19 symptoms, such as a cytokine storm and acute respiratory distress. Overall, this study revealed tissue involvement, provided insights into the mechanism of COVID-19 progression, and highlighted the utility of cfDNA as a noninvasive biomarker for disease severity inspections.

Multimodal analysis of cell-free DNA whole-genome sequencing for pediatric cancers with low mutational burden

Sequencing of cell-free DNA in the blood of cancer patients (liquid biopsy) provides attractive opportunities for early diagnosis, assessment of treatment response, and minimally invasive disease monitoring. To unlock liquid biopsy analysis for pediatric tumors with few genetic aberrations, we introduce an integrated genetic/epigenetic analysis method and demonstrate its utility on 241 deep whole-genome sequencing profiles of 95 patients with Ewing sarcoma and 31 patients with other pediatric sarcomas. Our method achieves sensitive detection and classification of circulating tumor DNA in peripheral blood independent of any genetic alterations. Moreover, we benchmark different metrics for cell-free DNA fragmentation analysis, and we introduce the LIQUORICE algorithm for detecting circulating tumor DNA based on cancer-specific chromatin signatures. Finally, we combine several fragmentation-based metrics into an integrated machine learning classifier for liquid biopsy analysis that exploits widespread epigenetic deregulation and is tailored to cancers with low mutation rates. Clinical associations highlight the potential value of cfDNA fragmentation patterns as prognostic biomarkers in Ewing sarcoma. In summary, our study provides a comprehensive analysis of circulating tumor DNA beyond recurrent genetic aberrations, and it renders the benefits of liquid biopsy more readily accessible for childhood cancers.

OCRDetector: Accurately Detecting Open Chromatin Regions via Plasma Cell-Free DNA Sequencing Data

Open chromatin regions (OCRs) are special regions of the human genome that can be accessed by DNA regulatory elements. Several studies have reported that a series of OCRs are associated with mechanisms involved in human diseases, such as cancers. Identifying OCRs using ATAC-seq or DNase-seq is often expensive. It has become popular to detect OCRs from plasma cell-free DNA (cfDNA) sequencing data, because both the fragmentation modes of cfDNA and the sequencing coverage in OCRs are significantly different from those in other regions. However, it is a challenging computational problem to accurately detect OCRs from plasma cfDNA-seq data, as multiple factors—e.g., sequencing and mapping bias, insufficient read depth, etc.—often mislead the computational model. In this paper, we propose a novel bioinformatics pipeline, OCRDetector, for detecting OCRs from whole-genome cfDNA sequencing data. The pipeline calculates the window protection score (WPS) waveform and the cfDNA sequencing coverage. To validate the proposed pipeline, we compared the percentage overlap of our OCRs with those obtained by other methods. The experimental results show that 81% of the TSS regions of housekeeping genes are detected, and our results have obvious tissue specificity. In addition, the overlap percentage between our OCRs and the high-confidence OCRs obtained by ATAC-seq or DNase-seq is greater than 70%.

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.

ChIP-seq of plasma cell-free nucleosomes identifies gene expression programs of the cells of origin

Cell-free DNA (cfDNA) in human plasma provides access to molecular information about the pathological processes in the organs or tumors from which it originates. These DNA fragments are derived from fragmented chromatin in dying cells and retain some of the cell-of-origin histone modifications. In this study, we applied chromatin immunoprecipitation of cell-free nucleosomes carrying active chromatin modifications followed by sequencing (cfChIP-seq) to 268 human samples. In healthy donors, we identified bone marrow megakaryocytes, but not erythroblasts, as major contributors to the cfDNA pool. In patients with a range of liver diseases, we showed that we can identify pathology-related changes in hepatocyte transcriptional programs. In patients with metastatic colorectal carcinoma, we detected clinically relevant and patient-specific information, including transcriptionally active human epidermal growth factor receptor 2 (HER2) amplifications. Altogether, cfChIP-seq, using low sequencing depth, provides systemic and genome-wide information and can inform diagnosis and facilitate interrogation of physiological and pathological processes using blood samples.

The Detection of Cancer Epigenetic Traces in Cell-Free DNA

Nucleic acid fragments found in blood circulation originate mostly from dying cells and carry signs pointing to specific features of the parental cell types. Deciphering these clues may be transformative for numerous research and clinical applications but strongly depends on the development and implementation of robust analytical methods. Remarkable progress has been achieved in the reliable detection of sequence alterations in cell-free DNA while decoding epigenetic information from methylation and fragmentation patterns requires more sophisticated approaches. This review discusses the currently available strategies for detecting and analyzing the epigenetic marks in the liquid biopsies.

Epigenetics, fragmentomics, and topology of cell-free DNA in liquid biopsies

Liquid biopsies that analyze cell-free DNA in blood plasma are used for noninvasive prenatal testing, oncology, and monitoring of organ transplant recipients. DNA molecules are released into the plasma from various bodily tissues. Physical and molecular features of cell-free DNA fragments and their distribution over the genome bear information about their tissues of origin. Moreover, patterns of DNA methylation of these molecules reflect those of their tissue sources. The nucleosomal organization and nuclease content of the tissue of origin affect the fragmentation profile of plasma DNA molecules, such as fragment size and end motifs. Besides double-stranded linear fragments, other topological forms of cell-free DNA also exist-namely circular and single-stranded molecules. Enhanced by these features, liquid biopsies hold promise for the noninvasive detection of tissue-specific pathologies with a range of clinical applications.

Current status of ctDNA in precision oncology for hepatocellular carcinoma

The conventional method used to obtain a tumor biopsy for hepatocellular carcinoma (HCC) is invasive and does not evaluate dynamic cancer progression or assess tumor heterogeneity. It is thus imperative to create a novel non-invasive diagnostic technique for improvement in cancer screening, diagnosis, treatment selection, response assessment, and predicting prognosis for HCC. Circulating tumor DNA (ctDNA) is a non-invasive liquid biopsy method that reveals cancer-specific genetic and epigenetic aberrations. Owing to the development of technology in next-generation sequencing and PCR-based assays, the detection and quantification of ctDNA have greatly improved. In this publication, we provide an overview of current technologies used to detect ctDNA, the ctDNA markers utilized, and recent advances regarding the multiple clinical applications in the field of precision medicine for HCC.