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

Exhaustive identification of genome-wide binding events of transcriptional regulators

Genome-wide binding assays aspire to map the complete binding pattern of gene regulators. Common practice relies on replication-duplicates or triplicates-and high stringency statistics to favor false negatives over false positives. Here we show that duplicates and triplicates of CUT&RUN are not sufficient to discover the entire activity of transcriptional regulators. We introduce ICEBERG (Increased Capture of Enrichment By Exhaustive Replicate aGgregation), a pipeline that harnesses large numbers of CUT&RUN replicates to discover the full set of binding events and chart the line between false positives and false negatives. We employed ICEBERG to map the full set of H3K4me3-marked regions, the targets of the co-factor β-catenin, and those of the transcription factor TBX3, in human colorectal cancer cells. The ICEBERG datasets allow benchmarking of individual replicates, comparing the performance of peak calling and replication approaches, and expose the arbitrary nature of strategies to identify reproducible peaks. Instead of a static view of genomic targets, ICEBERG establishes a spectrum of detection probabilities across the genome for a given factor, underlying the intrinsic dynamicity of its mechanism of action, and permitting to distinguish frequent from rare regulation events. Finally, ICEBERG discovered instances, undetectable with other approaches, that underlie novel mechanisms of colorectal cancer progression.

Tissue informative cell-free DNA methylation sites in amyotrophic lateral sclerosis

Cell-free DNA (cfDNA) is increasingly recognized as a promising biomarker candidate for disease monitoring. However, its utility in neurodegenerative diseases, like amyotrophic lateral sclerosis (ALS), remains underexplored. Existing biomarker discovery approaches are tailored to a specific disease context or are too expensive to be clinically practical. Here, we address these challenges through a new approach combining advances in molecular and computational technologies. First, we develop statistical tools to select tissue-informative DNA methylation sites relevant to a disease process of interest. We then employ a capture protocol to select these sites and perform targeted methylation sequencing. Multi-modal information about the DNA methylation patterns are then utilized in machine learning algorithms trained to predict disease status and disease progression. We applied our method to two independent cohorts of ALS patients and controls (n=192). Overall, we found that the targeted sites accurately predicted ALS status and replicated between cohorts. Additionally, we identified epigenetic features associated with ALS phenotypes, including disease severity. These findings highlight the potential of cfDNA as a non-invasive biomarker for ALS.

Chromatin- and nucleosome-associated features in liquid biopsy: implications for cancer biomarker discovery

Cell-free DNA (cfDNA) from the bloodstream has been studied for cancer biomarker discovery, and chromatin-derived epigenetic features have come into the spotlight for their potential to expand clinical applications. Methylation, fragmentation, and nucleosome positioning patterns of cfDNA have previously been shown to reveal epigenomic and inferred transcriptomic information. More recently, histone modifications have emerged as a tool to further identify tumor-specific chromatin variants in plasma. A number of sequencing methods have been developed to analyze these epigenetic markers, offering new insights into tumor biology. Features within cfDNA allow for cancer detection, subtype and tissue of origin classification, and inference of gene expression. These methods provide a window into the complexity of cancer and the dynamic nature of its progression. In this review, we highlight the array of epigenetic features in cfDNA that can be extracted from chromatin- and nucleosome-associated organization and outline potential use cases in cancer management.

Circulating nucleosomes as potential biomarkers for cancer diagnosis and treatment monitoring

Nucleosomes play a crucial role in regulating gene expression through their composition and post-translational modifications. When cells die, intracellular endonucleases are activated and cleave chromatin into oligo- and mono-nucleosomes, which are then released into the body fluids. Studies have shown that the levels of nucleosomes are increased in serum and plasma in various cancer types, suggesting that analysis of circulating nucleosomes can provide an initial assessment of carcinogenesis. However, it should be noted that elevated serum nucleosome levels may not accurately diagnose certain tumor types, as increased cell death may occur in different pathological conditions. Nevertheless, detection of circulating nucleosomes and their histone modifications, along with specific tumor markers, can help diagnose certain types of cancer. Furthermore, monitoring changes in circulating nucleosome levels during chemotherapy or radiotherapy in patients with malignancies can provide valuable insights into clinical outcomes and therapeutic efficacy. The utilization of circulating nucleosomes as biomarkers is an exciting and emerging area of research, with the potential for early detection of various diseases and monitoring of treatment response. Integrating nucleosome-based biomarkers with existing ones may improve the specificity and sensitivity of current assays, offering the possibility of personalized precision medical treatment for patients.

Priming agents transiently reduce the clearance of cell-free DNA to improve liquid biopsies

Liquid biopsies enable early detection and monitoring of diseases such as cancer, but their sensitivity remains limited by the scarcity of analytes such as cell-free DNA (cfDNA) in blood. Improvements to sensitivity have primarily relied on enhancing sequencing technology ex vivo. We sought to transiently augment the level of circulating tumor DNA (ctDNA) in a blood draw by attenuating its clearance in vivo. We report two intravenous priming agents given 1 to 2 hours before a blood draw to recover more ctDNA. Our priming agents consist of nanoparticles that act on the cells responsible for cfDNA clearance and DNA-binding antibodies that protect cfDNA. In tumor-bearing mice, they greatly increase the recovery of ctDNA and improve the sensitivity for detecting small tumors.

Integration of Cell-Free DNA End Motifs and Fragment Lengths Can Identify Active Genes in Liquid Biopsies

Multiple studies have shown that cell-free DNA (cfDNA) from cancer patients differ in both fragment length and fragment end motif (FEM) from healthy individuals, yet there is a lack of understanding of how the two factors combined are associated with cancer and gene transcription. In this study, we conducted cfDNA fragmentomics evaluations using plasma from lung cancer patients (n = 12) and healthy individuals (n = 7). A personal gene expression profile was established from plasma using H3K36me3 cell-free chromatin immunoprecipitation sequencing (cfChIP-seq). The genes with the highest expression displayed an enrichment of short cfDNA fragments (median = 19.99%, IQR: 16.94-27.13%, p < 0.0001) compared to the genes with low expression. Furthermore, distinct GC-rich FEMs were enriched after cfChIP. Combining the frequency of short cfDNA fragments with the presence of distinct FEMs resulted in an even further enrichment of the most expressed genes (median = 37.85%, IQR: 30.10-39.49%, p < 0.0001). An in vitro size selection of <150 bp cfDNA could isolate cfDNA representing active genes and the size-selection enrichment correlated with the cfChIP-seq enrichment (Spearman r range: 0.499-0.882, p < 0.0001). This study expands the knowledge regarding cfDNA fragmentomics and sheds new light on how gene activity is associated with both cfDNA fragment lengths and distinct FEMs.

Plasma Cell-Free Tumor Methylome as a Biomarker in Solid Tumors: Biology and Applications

DNA methylation is a fundamental mechanism of epigenetic control in cells and its dysregulation is strongly implicated in cancer development. Cancers possess an extensively hypomethylated genome with focal regions of hypermethylation at CPG islands. Due to the highly conserved nature of cancer-specific methylation, its detection in cell-free DNA in plasma using liquid biopsies constitutes an area of interest in biomarker research. The advent of next-generation sequencing and newer computational technologies have allowed for the development of diagnostic and prognostic biomarkers that utilize methylation profiling to diagnose disease and stratify risk. Methylome-based predictive biomarkers can determine the response to anti-cancer therapy. An additional emerging application of these biomarkers is in minimal residual disease monitoring. Several key challenges need to be addressed before cfDNA-based methylation biomarkers become fully integrated into practice. The first relates to the biology and stability of cfDNA. The second concerns the clinical validity and generalizability of methylation-based assays, many of which are cancer type-specific. The third involves their practicability, which is a stumbling block for translating technologies from bench to clinic. Future work on developing pan-cancer assays with their respective validities confirmed using well-designed, prospective clinical trials is crucial in pushing for the greater use of these tools in oncology.

Artificial intelligence in biology and medicine, and radioprotection research: perspectives from Jerusalem

While AI is widely used in biomedical research and medical practice, its use is constrained to few specific practical areas, e.g., radiomics. Participants of the workshop on "Artificial Intelligence in Biology and Medicine" (Jerusalem, Feb 14-15, 2023), both researchers and practitioners, aimed to build a holistic picture by exploring AI advancements, challenges and perspectives, as well as to suggest new fields for AI applications. Presentations showcased the potential of large language models (LLMs) in generating molecular structures, predicting protein-ligand interactions, and promoting democratization of AI development. Ethical concerns in medical decision making were also addressed. In biological applications, AI integration of multi-omics and clinical data elucidated the health relevant effects of low doses of ionizing radiation. Bayesian latent modeling identified statistical associations between unobserved variables. Medical applications highlighted liquid biopsy methods for non-invasive diagnostics, routine laboratory tests to identify overlooked illnesses, and AI's role in oral and maxillofacial imaging. Explainable AI and diverse image processing tools improved diagnostics, while text classification detected anorexic behavior in blog posts. The workshop fostered knowledge sharing, discussions, and emphasized the need for further AI development in radioprotection research in support of emerging public health issues. The organizers plan to continue the initiative as an annual event, promoting collaboration and addressing issues and perspectives in AI applications with a focus on low-dose radioprotection research. Researchers involved in radioprotection research and experts in relevant public policy domains are invited to explore the utility of AI in low-dose radiation research at the next workshop.

Cell-free chromatin immunoprecipitation to detect molecular pathways in heart transplantation

Existing monitoring approaches in heart transplantation lack the sensitivity to provide deep molecular assessments to guide management, or require endomyocardial biopsy, an invasive and blind procedure that lacks the precision to reliably obtain biopsy samples from diseased sites. This study examined plasma cell-free DNA chromatin immunoprecipitation sequencing (cfChIP-seq) as a noninvasive proxy to define molecular gene sets and sources of tissue injury in heart transplant patients. In healthy controls and in heart transplant patients, cfChIP-seq reliably detected housekeeping genes. cfChIP-seq identified differential gene signals of relevant immune and nonimmune molecular pathways that were predominantly down-regulated in immunosuppressed heart transplant patients compared with healthy controls. cfChIP-seq also identified cell-free DNA tissue sources. Compared with healthy controls, heart transplant patients demonstrated greater cell-free DNA from tissue types associated with heart transplant complications, including the heart, hematopoietic cells, lungs, liver, and vascular endothelium. cfChIP-seq may therefore be a reliable approach to profile dynamic assessments of molecular pathways and sources of tissue injury in heart transplant patients.

Single-molecule systems for detection and monitoring of plasma circulating nucleosomes and oncoproteins in Diffuse Midline Glioma

The analysis of cell-free tumor DNA (ctDNA) and proteins in the blood of cancer patients potentiates a new generation of non-invasive diagnostics and treatment monitoring approaches. However, confident detection of these tumor-originating markers is challenging, especially in the context of brain tumors, in which extremely low amounts of these analytes circulate in the patient's plasma. Here, we applied a sensitive single-molecule technology to profile multiple histone modifications on millions of individual nucleosomes from the plasma of Diffuse Midline Glioma (DMG) patients. The system reveals epigenetic patterns that are unique to DMG, significantly differentiating this group of patients from healthy subjects or individuals diagnosed with other cancer types. We further develop a method to directly capture and quantify the tumor-originating oncoproteins, H3-K27M and mutant p53, from the plasma of children diagnosed with DMG. This single-molecule system allows for accurate molecular classification of patients, utilizing less than 1ml of liquid-biopsy material. Furthermore, we show that our simple and rapid detection strategy correlates with MRI measurements and droplet-digital PCR (ddPCR) measurements of ctDNA, highlighting the utility of this approach for non-invasive treatment monitoring of DMG patients. This work underscores the clinical potential of single-molecule-based, multi-parametric assays for DMG diagnosis and treatment monitoring.

Cell-free multi-omics analysis reveals potential biomarkers in gastrointestinal cancer patients' blood

During cancer progression, tumorigenic and immune signals are spread through circulating molecules, such as cell-free DNA (cfDNA) and cell-free RNA (cfRNA) in the blood. So far, they have not been comprehensively investigated in gastrointestinal cancers. Here, we profile 4 categories of cell-free omics data from patients with colorectal cancer and patients with stomach adenocarcinoma and then assay 15 types of genomic, epigenomic, and transcriptomic variations. We find that multi-omics data are more appropriate for detection of cancer genes compared with single-omics data. In particular, cfRNAs are more sensitive and informative than cfDNAs in terms of detection rate, enriched functional pathways, etc. Moreover, we identify several peripheral immune signatures that are suppressed in patients with cancer. Specifically, we establish a γδ-T cell score and a cancer-associated-fibroblast (CAF) score, providing insights into clinical statuses like cancer stage and survival. Overall, we reveal a cell-free multi-molecular landscape that is useful for blood monitoring in personalized cancer treatment.

Megakaryocyte- and erythroblast-specific cell-free DNA patterns in plasma and platelets reflect thrombopoiesis and erythropoiesis levels

Circulating cell-free DNA (cfDNA) fragments are a biological analyte with extensive utility in diagnostic medicine. Understanding the source of cfDNA and mechanisms of release is crucial for designing and interpreting cfDNA-based liquid biopsy assays. Using cell type-specific methylation markers as well as genome-wide methylation analysis, we determine that megakaryocytes, the precursors of anuclear platelets, are major contributors to cfDNA (~26%), while erythroblasts contribute 1-4% of cfDNA in healthy individuals. Surprisingly, we discover that platelets contain genomic DNA fragments originating in megakaryocytes, contrary to the general understanding that platelets lack genomic DNA. Megakaryocyte-derived cfDNA is increased in pathologies involving increased platelet production (Essential Thrombocythemia, Idiopathic Thrombocytopenic Purpura) and decreased upon reduced platelet production due to chemotherapy-induced bone marrow suppression. Similarly, erythroblast cfDNA is reflective of erythrocyte production and is elevated in patients with thalassemia. Megakaryocyte- and erythroblast-specific DNA methylation patterns can thus serve as biomarkers for pathologies involving increased or decreased thrombopoiesis and erythropoiesis, which can aid in determining the etiology of aberrant levels of erythrocytes and platelets.

Drug-tolerant persister cells in cancer: the cutting edges and future directions

Drug-tolerant persister (DTP) cell populations were originally discovered in antibiotic-resistant bacterial biofilms. Similar populations with comparable features have since been identified among cancer cells and have been linked with treatment resistance that lacks an underlying genomic alteration. Research over the past decade has improved our understanding of the biological roles of DTP cells in cancer, although clinical knowledge of the role of these cells in treatment resistance remains limited. Nonetheless, targeting this population is anticipated to provide new treatment opportunities. In this Perspective, we aim to provide a clear definition of the DTP phenotype, discuss the underlying characteristics of these cells, their biomarkers and vulnerabilities, and encourage further research on DTP cells that might improve our understanding and enable the development of more effective anticancer therapies.

Liquid biopsy epigenomic profiling for cancer subtyping

Although circulating tumor DNA (ctDNA) assays are increasingly used to inform clinical decisions in cancer care, they have limited ability to identify the transcriptional programs that govern cancer phenotypes and their dynamic changes during the course of disease. To address these limitations, we developed a method for comprehensive epigenomic profiling of cancer from 1 ml of patient plasma. Using an immunoprecipitation-based approach targeting histone modifications and DNA methylation, we measured 1,268 epigenomic profiles in plasma from 433 individuals with one of 15 cancers. Our assay provided a robust proxy for transcriptional activity, allowing us to infer the expression levels of diagnostic markers and drug targets, measure the activity of therapeutically targetable transcription factors and detect epigenetic mechanisms of resistance. This proof-of-concept study in advanced cancers shows how plasma epigenomic profiling has the potential to unlock clinically actionable information that is currently accessible only via direct tissue sampling.

Cell-free DNA reveals distinct pathology of multisystem inflammatory syndrome in children

Multisystem inflammatory syndrome in children (MIS-C) is a rare but life-threatening hyperinflammatory condition induced by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes pediatric COVID-19 (pCOVID-19). The relationship of the systemic tissue injury to the pathophysiology of MIS-C is poorly defined. We leveraged the high sensitivity of epigenomics analyses of plasma cell-free DNA (cfDNA) and plasma cytokine measurements to identify the spectrum of tissue injury and glean mechanistic insights. Compared with pediatric healthy controls (pHCs) and patients with pCOVID-19, patients with MIS-C had higher levels of cfDNA primarily derived from innate immune cells, megakaryocyte-erythroid precursor cells, and nonhematopoietic tissues such as hepatocytes, cardiac myocytes, and kidney cells. Nonhematopoietic tissue cfDNA levels demonstrated significant interindividual variability, consistent with the heterogenous clinical presentation of MIS-C. In contrast, adaptive immune cell-derived cfDNA levels were comparable in MIS-C and pCOVID-19 patients. Indeed, the cfDNA of innate immune cells in patients with MIS-C correlated with the levels of innate immune inflammatory cytokines and nonhematopoietic tissue-derived cfDNA, suggesting a primarily innate immunity-mediated response to account for the multisystem pathology. These data provide insight into the pathogenesis of MIS-C and support the value of cfDNA as a sensitive biomarker to map tissue injury in MIS-C and likely other multiorgan inflammatory conditions.

Liquid biopsies for cancer: From bench to clinic

Over the past two decades, liquid biopsy has been increasingly used as a supplement, or even, a replacement to the traditional biopsy in clinical oncological practice, due to its noninvasive and early detectable properties. The detections can be based on a variety of features extracted from tumor‑derived entities, such as quantitative alterations, genetic changes, and epigenetic aberrations, and so on. So far, the clinical applications of cancer liquid biopsy mainly aimed at two aspects, prediction (early diagnosis, prognosis and recurrent evaluation, therapeutic response monitoring, etc.) and intervention. In spite of the rapid development and great contributions achieved, cancer liquid biopsy is still a field under investigation and deserves more clinical practice. To better open up future work, here we systematically reviewed and compared the latest progress of the most widely recognized circulating components, including circulating tumor cells, cell-free circulating DNA, noncoding RNA, and nucleosomes, from their discovery histories to clinical values. According to the features applied, we particularly divided the contents into two parts, beyond epigenetics and epigenetic-based. The latter was considered as the highlight along with a brief overview of the advances in both experimental and bioinformatic approaches, due to its unique advantages and relatively lack of documentation.

Advancements in Focal Amplification Detection in Tumor/Liquid Biopsies and Emerging Clinical Applications

Focal amplifications (FAs) are crucial in cancer research due to their significant diagnostic, prognostic, and therapeutic implications. FAs manifest in various forms, such as episomes, double minute chromosomes, and homogeneously staining regions, arising through different mechanisms and mainly contributing to cancer cell heterogeneity, the leading cause of drug resistance in therapy. Numerous wet-lab, mainly FISH, PCR-based assays, next-generation sequencing, and bioinformatics approaches have been set up to detect FAs, unravel the internal structure of amplicons, assess their chromatin compaction status, and investigate the transcriptional landscape associated with their occurrence in cancer cells. Most of them are tailored for tumor samples, even at the single-cell level. Conversely, very limited approaches have been set up to detect FAs in liquid biopsies. This evidence suggests the need to improve these non-invasive investigations for early tumor detection, monitoring disease progression, and evaluating treatment response. Despite the potential therapeutic implications of FAs, such as, for example, the use of HER2-specific compounds for patients with ERBB2 amplification, challenges remain, including developing selective and effective FA-targeting agents and understanding the molecular mechanisms underlying FA maintenance and replication. This review details a state-of-the-art of FA investigation, with a particular focus on liquid biopsies and single-cell approaches in tumor samples, emphasizing their potential to revolutionize the future diagnosis, prognosis, and treatment of cancer patients.

Epigenetic markers and therapeutic targets for metastasis

The last few years have seen an increasing number of discoveries which collectively demonstrate that histone and DNA modifying enzyme modulate different stages of metastasis. Moreover, epigenomic alterations can now be measured at multiple scales of analysis and are detectable in human tumors or liquid biopsies. Malignant cell clones with a proclivity for relapse in certain organs may arise in the primary tumor as a consequence of epigenomic alterations which cause a loss in lineage integrity. These alterations may occur due to genetic aberrations acquired during tumor progression or concomitant to therapeutic response. Moreover, evolution of the stroma can also alter the epigenome of cancer cells. In this review, we highlight current knowledge with a particular emphasis on leveraging chromatin and DNA modifying mechanisms as biomarkers of disseminated disease and as therapeutic targets to treat metastatic cancers.

Elevated cfDNA after exercise is derived primarily from mature polymorphonuclear neutrophils, with a minor contribution of cardiomyocytes

Strenuous physical exercise causes a massive elevation in the concentration of circulating cell-free DNA (cfDNA), which correlates with effort intensity and duration. The cellular sources and physiological drivers of this phenomenon are unknown. Using methylation patterns of cfDNA and associated histones, we show that cfDNA in exercise originates mostly in extramedullary polymorphonuclear neutrophils. Strikingly, cardiomyocyte cfDNA concentration increases after a marathon, consistent with elevated troponin levels and indicating low-level, delayed cardiac cell death. Physical impact, low oxygen levels, and elevated core body temperature contribute to neutrophil cfDNA release, while muscle contraction, increased heart rate, β-adrenergic signaling, or steroid treatment fail to cause elevation of cfDNA. Physical training reduces neutrophil cfDNA release after a standard exercise, revealing an inverse relationship between exercise-induced cfDNA release and training level. We speculate that the release of cfDNA from neutrophils in exercise relates to the activation of neutrophils in the context of exercise-induced muscle damage.

Liquid biopsy for brain metastases and leptomeningeal disease in patients with breast cancer

A significant subset of patients with metastatic breast cancer develops brain metastasis. As efficacy of systemic therapies has improved and patients live longer with metastatic breast cancer, the incidence of breast cancer brain metastases has increased. Brain metastases pose a clinical challenge in diagnosis, treatment, and monitoring across all breast cancer subtypes, and better tools are needed. Liquid biopsy, which enables minimally invasive sampling of a patient's cancer, has the potential to shed light on intra-cranial tumor biology and to improve patient care by enabling therapy tailoring. Here we review current evidence for the clinical validity of liquid biopsy in patients with breast cancer brain metastases, with a focus on circulating tumor cells and circulating tumor DNA.

Genetic and Genomic Testing for Prostate Cancer: Beyond DNA Repair

Significant progress has been made in genetic and genomic testing for prostate cancer across the disease spectrum. Molecular profiling is increasingly relevant for routine clinical management, fueled in part by advancements in testing technology and integration of biomarkers into clinical trials. In metastatic prostate cancer, defects in DNA damage response genes are now established predictors of benefit to US Food and Drug Administration-approved poly (ADP-ribose) polymerase inhibitors and immune checkpoint inhibitors, and trials are actively investigating these and other targeted treatment strategies in earlier disease states. Excitingly, opportunities for molecularly informed management beyond DNA damage response genes are also maturing. Germline genetic variants (eg, BRCA2 or MSH2/6) and polygenic germline risk scores are being investigated to inform cancer screening and active surveillance in at-risk carriers. RNA expression tests have recently gained traction in localized prostate cancer, enabling patient risk stratification and tailored treatment intensification via radiotherapy and/or androgen deprivation therapy for localized or salvage treatment. Finally, emerging minimally invasive circulating tumor DNA technology promises to enhance biomarker testing in advanced disease pending additional methodological and clinical validation. Collectively, genetic and genomic tests are rapidly becoming indispensable tools for informing the optimal clinical management of prostate cancer.

Integrative modeling of tumor genomes and epigenomes for enhanced cancer diagnosis by cell-free DNA

Multi-cancer early detection remains a key challenge in cell-free DNA (cfDNA)-based liquid biopsy. Here, we perform cfDNA whole-genome sequencing to generate two test datasets covering 2125 patient samples of 9 cancer types and 1241 normal control samples, and also a reference dataset for background variant filtering based on 20,529 low-depth healthy samples. An external cfDNA dataset consisting of 208 cancer and 214 normal control samples is used for additional evaluation. Accuracy for cancer detection and tissue-of-origin localization is achieved using our algorithm, which incorporates cancer type-specific profiles of mutation distribution and chromatin organization in tumor tissues as model references. Our integrative model detects early-stage cancers, including those of pancreatic origin, with high sensitivity that is comparable to that of late-stage detection. Model interpretation reveals the contribution of cancer type-specific genomic and epigenomic features. Our methodologies may lay the groundwork for accurate cfDNA-based cancer diagnosis, especially at early stages.

Enhancing clinical potential of liquid biopsy through a multi-omic approach: A systematic review

In the last years, liquid biopsy gained increasing clinical relevance for detecting and monitoring several cancer types, being minimally invasive, highly informative and replicable over time. This revolutionary approach can be complementary and may, in the future, replace tissue biopsy, which is still considered the gold standard for cancer diagnosis. “Classical” tissue biopsy is invasive, often cannot provide sufficient bioptic material for advanced screening, and can provide isolated information about disease evolution and heterogeneity. Recent literature highlighted how liquid biopsy is informative of proteomic, genomic, epigenetic, and metabolic alterations. These biomarkers can be detected and investigated using single-omic and, recently, in combination through multi-omic approaches. This review will provide an overview of the most suitable techniques to thoroughly characterize tumor biomarkers and their potential clinical applications, highlighting the importance of an integrated multi-omic, multi-analyte approach. Personalized medical investigations will soon allow patients to receive predictable prognostic evaluations, early disease diagnosis, and subsequent ad hoc treatments.

Bridging biological cfDNA features and machine learning approaches

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

Epigenetic liquid biopsies: a novel putative biomarker in immunology and inflammation

Immune and inflammatory processes occurring within tissues are often undetectable by blood cell counts, standard circulating biomarkers, or imaging, representing an unmet biomedical need. Here, we outline recent advances indicating that liquid biopsies can broadly inform human immune system dynamics. Nucleosome-size fragments of cell-free DNA (cfDNA) released from dying cells into blood contain rich epigenetic information such as methylation, fragmentation, and histone mark patterns. This information allows to infer the cfDNA cell of origin, as well as pre-cell death gene expression patterns. We propose that the analysis of epigenetic features of immune cell-derived cfDNA can shed light on immune cell turnover dynamics in healthy people, and inform the study and diagnosis of cancer, local inflammation, infectious or autoimmune diseases, as well as responses to vaccination.

Multiplexed, single-molecule, epigenetic analysis of plasma-isolated nucleosomes for cancer diagnostics

The analysis of cell-free DNA (cfDNA) in plasma provides information on pathological processes in the body. Blood cfDNA is in the form of nucleosomes, which maintain their tissue- and cancer-specific epigenetic state. We developed a single-molecule multiparametric assay to comprehensively profile the epigenetics of plasma-isolated nucleosomes (EPINUC), DNA methylation and cancer-specific protein biomarkers. Our system allows for high-resolution detection of six active and repressive histone modifications and their ratios and combinatorial patterns on millions of individual nucleosomes by single-molecule imaging. In addition, our system provides sensitive and quantitative data on plasma proteins, including detection of non-secreted tumor-specific proteins, such as mutant p53. EPINUC analysis of a cohort of 63 colorectal cancer, 10 pancreatic cancer and 33 healthy plasma samples detected cancer with high accuracy and sensitivity, even at early stages. Finally, combining EPINUC with direct single-molecule DNA sequencing revealed the tissue of origin of colorectal, pancreatic, lung and breast tumors. EPINUC provides multilayered information of potential clinical relevance from limited (<1 ml) liquid biopsy material.

Genome-wide epigenetic and mRNA-expression profiling followed by CRISPR/Cas9-mediated gene-disruptions corroborate the MIR141/MIR200C-ZEB1/ZEB2-FGFR1 axis in acquired EMT-associated EGFR TKI-resistance in NSCLC cells

Background

Epithelial-mesenchymal-transition (EMT) is an epigenetic-based mechanism contributing to the acquired treatment resistance against receptor tyrosine kinase inhibitors (TKIs) in non-small cell lung cancer (NSCLC) cells harboring epidermal growth factor receptor (EGFR)-mutations. Delineating the exact epigenetic and gene-expression alterations in EMT-associated EGFR TKI-resistance (EMT-E-TKI-R) is vital for improved diagnosis and treatment of NSCLC patients.

Methods

We characterized genome-wide changes in mRNA-expression, DNA-methylation and the histone-modification H3K36me3 in EGFR-mutated NSCLC HCC827 cells in result of acquired EMT-E-TKI-R. CRISPR/Cas9 was used to functional examine key findings from the omics analyses.

Results

Acquired EMT-E-TKI-R was analyzed with three omics approaches. RNA-sequencing identified 2,233 and 1,972 up- and down-regulated genes, respectively, and among these were established EMT-markers. DNA-methylation EPIC array analyses identified 14,163 and 7,999 hyper- and hypo-methylated, respectively, differential methylated positions of which several were present in EMT-markers. Finally, H3K36me3 chromatin immunoprecipitation (ChIP)-sequencing detected 2,873 and 3,836 genes with enrichment and depletion, respectively, and among these were established EMT-markers. Correlation analyses showed that EMT-E-TKI-R mRNA-expression changes correlated better with H3K36me3 changes than with DNA-methylation changes. Moreover, the omics data supported the involvement of the MIR141/MIR200C-ZEB1/ZEB2-FGFR1 signaling axis for acquired EMT-E-TKI-R. CRISPR/Cas9-mediated analyses corroborated the importance of ZEB1 in acquired EMT-E-TKI-R, MIR200C and MIR141 to be in an EMT-E-TKI-R-associated auto-regulatory loop with ZEB1, and FGFR1 to mediate cell survival in EMT-E-TKI-R.

Conclusions

The current study describes the synchronous genome-wide changes in mRNA-expression, DNA-methylation, and H3K36me3 in NSCLC EMT-E-TKI-R. The omics approaches revealed potential novel diagnostic markers and treatment targets. Besides, the study consolidates the functional impact of the MIR141/MIR200C-ZEB1/ZEB2-FGFR1-signaling axis in NSCLC EMT-E-TKI-R.

Cell-free Chromatin Immunoprecipitation to detect molecular pathways in Physiological and Disease States

Patient monitoring is a cornerstone in clinical practice to define disease phenotypes and guide clinical management. Unfortunately, this is often reliant on invasive and/or less sensitive methods that do not provide deep phenotype assessments of disease state to guide treatment. This paper examined plasma cell-free DNA chromatin immunoprecipitation sequencing (cfChIP-seq) to define molecular gene sets in physiological and heart transplant patients taking immunosuppression medications. We show cfChIP-seq reliably detect gene signals that correlate with gene expression. In healthy controls and in heart transplant patients, cfChIP-seq reliably detected housekeeping genes. cfChIP-seq identified differential gene signals of the relevant immune and non-immune molecular pathways that were predominantly downregulated in immunosuppressed heart transplant patients compared to healthy controls. cfChIP-seq also identified tissue sources of cfDNA, detecting greater cell-free DNA from cardiac, hematopoietic, and other non-hematopoietic tissues such as the pulmonary, digestive, and neurological tissues in transplant patients than healthy controls. cfChIP-seq gene signals were reproducible between patient populations and blood collection methods. cfChIP-seq may therefore be a reliable approach to provide dynamic assessments of molecular pathways and tissue injury associated to disease.

Cell-Free DNA Fragmentomics: The Novel Promising Biomarker

Cell-free DNA molecules are released into the plasma via apoptotic or necrotic events and active release mechanisms, which carry the genetic and epigenetic information of its origin tissues. However, cfDNA is the mixture of various cell fragments, and the efficient enrichment of cfDNA fragments with diagnostic value remains a great challenge for application in the clinical setting. Evidence from recent years shows that cfDNA fragmentomics' characteristics differ in normal and diseased individuals without the need to distinguish the source of the cfDNA fragments, which makes it a promising novel biomarker. Moreover, cfDNA fragmentomics can identify tissue origins by inferring epigenetic information. Thus, further insights into the fragmentomics of plasma cfDNA shed light on the origin and fragmentation mechanisms of cfDNA during physiological and pathological processes in diseases and enhance our ability to take the advantage of plasma cfDNA as a molecular diagnostic tool. In this review, we focus on the cfDNA fragment characteristics and its potential application, such as fragment length, end motifs, jagged ends, preferred end coordinates, as well as nucleosome footprints, open chromatin region, and gene expression inferred by the cfDNA fragmentation pattern across the genome. Furthermore, we summarize the methods for deducing the tissue of origin by cfDNA fragmentomics.

Treating inflammation to combat non-alcoholic fatty liver disease

Non-alcoholic fatty liver disease (NAFLD) with its more progressive form non-alcoholic steatohepatitis (NASH) has become the most common chronic liver disease, thereby representing a great burden for patients and healthcare systems. Specific pharmacological therapies for NAFLD are still missing. Inflammation is an important driver in the pathogenesis of NASH, and the mechanisms underlying inflammation in NAFLD represent possible therapeutic targets. In NASH, various intra- and extrahepatic triggers involved in the metabolic injury typically lead to the activation of different immune cells. This includes hepatic Kupffer cells, i.e. liver-resident macrophages, which can adopt an inflammatory phenotype and activate other immune cells by releasing inflammatory cytokines. As inflammation progresses, Kupffer cells are increasingly replaced by monocyte-derived macrophages with a distinct lipid-associated and scar-associated phenotype. Many other immune cells, including neutrophils, T lymphocytes - such as auto-aggressive cytotoxic as well as regulatory T cells - and innate lymphoid cells balance the progression and regression of inflammation and subsequent fibrosis. The detailed understanding of inflammatory cell subsets and their activation pathways prompted preclinical and clinical exploration of potential targets in NAFLD/NASH. These approaches to target inflammation in NASH include inhibition of immune cell recruitment via chemokine receptors (e.g. cenicriviroc), neutralization of CD44 or galectin-3 as well as agonism to nuclear factors like peroxisome proliferator-activated receptors and farnesoid X receptor that interfere with the activation of immune cells. As some of these approaches did not demonstrate convincing efficacy as monotherapies, a rational and personalized combination of therapeutic interventions may be needed for the near future.

Profiling of cell-free DNA methylation and histone signatures in pediatric NAFLD: A pilot study

Nonalcoholic fatty liver disease (NAFLD) has become the most common chronic liver disease in children and adolescents, increasing the risk of its progression toward nonalcoholic steatohepatitis (NASH), cirrhosis, and cancer. There is an urgent need for noninvasive early diagnostic and prognostic tools such as epigenetic marks (epimarks), which would replace liver biopsy in the future. We used plasma samples from 67 children with biopsy-proven NAFLD, and as controls we used samples from 20 children negative for steatosis by ultrasound. All patients were genotyped for patatin-like phospholipase domain containing 3 (PNPLA3), transmembrane 6 superfamily member 2 (TM6SF2), membrane bound O-acyltransferase domain containing 7 (MBOAT7), and klotho-β (KLB) gene variants, and data on anthropometric and biochemical parameters were collected. Furthermore, plasma cell-free DNA (cfDNA) methylation was quantified using a commercially available kit, and ImageStream(X) was used for the detection of free circulating histone complexes and variants. We found a significant enrichment of the levels of histone macroH2A1.2 in the plasma of children with NAFLD compared to controls, and a strong correlation between cfDNA methylation levels and NASH. Receiver operating characteristic curve analysis demonstrated that combination of cfDNA methylation, PNPLA3 rs738409 variant, coupled with either high-density lipoprotein cholesterol or alanine aminotransferase levels can strongly predict the progression of pediatric NAFLD to NASH with area under the curve >0.87. Conclusion: Our pilot study combined epimarks and genetic and metabolic markers for a robust risk assessment of NAFLD development and progression in children, offering a promising noninvasive tool for the consistent diagnosis and prognosis of pediatric NAFLD. Further studies are necessary to identify their pathogenic origin and function.

Plasma Cell-Free DNA Predicts Survival and Maps Specific Sources of Injury in Pulmonary Arterial Hypertension

BACKGROUND

Cell-free DNA (cfDNA) is a noninvasive marker of cellular injury. Its significance in pulmonary arterial hypertension (PAH) is unknown.

METHODS

Plasma cfDNA was measured in 2 PAH cohorts (A, n=48; B, n=161) and controls (n=48). Data were collected for REVEAL 2.0 (Registry to Evaluate Early and Long-Term PAH Disease Management) scores and outcome determinations. Patients were divided into the following REVEAL risk groups: low (≤6), medium (7-8), and high (≥9). Total cfDNA concentrations were compared among controls and PAH risk groups by 1-way analysis of variance. Log-rank tests compared survival between cfDNA tertiles and REVEAL risk groups. Areas under the receiver operating characteristic curve were estimated from logistic regression models. A sample subset from cohort B (n=96) and controls (n=16) underwent bisulfite sequencing followed by a deconvolution algorithm to map cell-specific cfDNA methylation patterns, with concentrations compared using t tests.

RESULTS

In cohort A, median (interquartile range) age was 62 years (47-71), with 75% female, and median (interquartile range) REVEAL 2.0 was 6 (4-9). In cohort B, median (interquartile range) age was 59 years (49-71), with 69% female, and median (interquartile range) REVEAL 2.0 was 7 (6-9). In both cohorts, cfDNA concentrations differed among patients with PAH of varying REVEAL risk and controls (analysis of variance P≤0.002) and were greater in the high-risk compared with the low-risk category (P≤0.002). In cohort B, death or lung transplant occurred in 14 of 54, 23 of 53, and 35 of 54 patients in the lowest, middle, and highest cfDNA tertiles, respectively. cfDNA levels stratified as tertiles (log-rank: P=0.0001) and REVEAL risk groups (log-rank: P<0.0001) each predicted transplant-free survival. The addition of cfDNA to REVEAL improved discrimination (area under the receiver operating characteristic curve, 0.72-0.78; P=0.02). Compared with controls, methylation analysis in patients with PAH revealed increased cfDNA originating from erythrocyte progenitors, neutrophils, monocytes, adipocytes, natural killer cells, vascular endothelium, and cardiac myocytes (Bonferroni adjusted P<0.05). cfDNA concentrations derived from erythrocyte progenitor cells, cardiac myocytes, and vascular endothelium were greater in patients with PAH with high-risk versus low-risk REVEAL scores (P≤0.02).

CONCLUSIONS

Circulating cfDNA is elevated in patients with PAH, correlates with disease severity, and predicts worse survival. Results from cfDNA methylation analyses in patients with PAH are consistent with prevailing paradigms of disease pathogenesis.

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.

Androgen receptor genomic alterations and treatment resistance in metastatic prostate cancer

BACKGROUND

Genomic alterations to the androgen receptor (AR) are common in metastatic castration-resistant prostate cancer (mCRPC). AR copy number amplifications, ligand-binding domain missense mutations, and intronic structural rearrangements can all drive resistance to approved AR pathway inhibitors and their detection via tissue or liquid biopsy is linked to clinical outcomes. With an increasingly crowded treatment landscape, there is hope that AR genomic alterations can act as prognostic and/or predictive biomarkers to guide patient management.

METHODS

In this review, we evaluate the current evidence for AR genomic alterations as clinical biomarkers in mCRPC, focusing on correlative studies that have used plasma circulating tumor DNA to characterize AR genotype.

RESULTS

We highlight data that demonstrates the complexity of AR genotype within individual patients, and suggest that future studies should account for cancer clonal heterogeneity and variable tumor content in liquid biopsy samples. Given the potential for cooccurrence of multiple AR genomic alterations in the same or competing subclones of a patient, it is distinctly challenging to attribute blanket clinical significance to any individual alteration. This challenge is further complicated by the varied treatment exposures in contemporary patients, and the fact that AR genotype continues to evolve in the mCRPC setting across sequential lines of systemic therapy.

CONCLUSIONS

As treatment access and liquid biopsy technology continues to improve, we posit that real-time measures of AR biology are likely to play a key role in emerging precision oncology strategies for metastatic prostate cancer.

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.

Modeling Susceptibility to Cardiotoxicity in Cancer Therapy Using Human iPSC-Derived Cardiac Cells and Systems Biology

The development of human-induced pluripotent stem cell-derived cardiac cell types has created a new paradigm in assessing drug-induced cardiotoxicity. Advances in genomics and epigenomics have also implicated several genomic loci and biological pathways that may contribute to susceptibility to cancer therapies. In this review, we first provide a brief overview of the cardiotoxicity associated with chemotherapy. We then provide a detailed summary of systems biology approaches being applied to elucidate potential molecular mechanisms involved in cardiotoxicity. Finally, we discuss combining systems biology approaches with iPSC technology to help discover molecular mechanisms associated with cardiotoxicity.

Pan-Cancer Detection and Typing by Mining Patterns in Large Genome-Wide Cell-Free DNA Sequencing Datasets

BACKGROUND

Cell-free DNA (cfDNA) analysis holds great promise for non-invasive cancer screening, diagnosis, and monitoring. We hypothesized that mining the patterns of cfDNA shallow whole-genome sequencing datasets from patients with cancer could improve cancer detection.

METHODS

By applying unsupervised clustering and supervised machine learning on large cfDNA shallow whole-genome sequencing datasets from healthy individuals (n = 367) and patients with different hematological (n = 238) and solid malignancies (n = 320), we identified cfDNA signatures that enabled cancer detection and typing.

RESULTS

Unsupervised clustering revealed cancer type-specific sub-grouping. Classification using a supervised machine learning model yielded accuracies of 96% and 65% in discriminating hematological and solid malignancies from healthy controls, respectively. The accuracy of disease type prediction was 85% and 70% for the hematological and solid cancers, respectively. The potential utility of managing a specific cancer was demonstrated by classifying benign from invasive and borderline adnexal masses with an area under the curve of 0.87 and 0.74, respectively.

CONCLUSIONS

This approach provides a generic analytical strategy for non-invasive pan-cancer detection and cancer type prediction.

Liquid Biopsy Derived Circulating Tumor Cells and Circulating Tumor DNA as Novel Biomarkers in Hepatocellular Carcinoma

INTRODUCTION

The diagnosis of hepatocellular carcinoma (HCC) is made at a relatively advanced stage resulting in poor prognosis. Alpha-fetoprotein and liver ultrasound have limited accuracy as biomarkers in HCC. Liver biopsy provides information on tumor biology; however, it is invasive and holds high threat of tumor seeding. Thus, more accurate and less invasive approaches are needed.

AREAS COVERED

Highly sensitive liquid biopsy assays have made possible the detection and analysis of cells or organelles such as circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and tumor-derived exosomes. Here, we focus on CTCs and ctDNA components of liquid biopsy and their clinical application as diagnostic, prognostic and predictive biomarkers in HCC. Unlike tissue biopsy, liquid biopsy involves attaining a sample at several time frames in an easy and a non-invasive manner. They have been efficacious in detecting and classifying cancer, in predicting treatment response, in monitoring disease relapse and in identifying mechanisms of resistance to targeted therapies.

EXPERT OPINION

Although interesting and highly promising, liquid biopsy techniques still have many obstacles to overcome before their wide spread clinical application sees the light. It is expected that these techniques will be incorporated into traditional methodologies for better diagnostic, predictive and prognostic results.

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.

Cell-free DNA in lung transplantation: research tool or clinical workhorse?

PURPOSE OF REVIEW

Recent evidence indicates that plasma donor-derived cell-free DNA (dd-cfDNA) is a sensitive biomarker for the detection of underlying allograft injury, including rejection and infection. In this review, we will cover the latest evidence revolving around dd-cfDNA in lung transplantation and its role in both advancing mechanistic insight into disease states in lung transplant recipients as well as its potential clinical utility.

RECENT FINDINGS

Plasma dd-cfDNA increases in the setting of allograft injury, including in primary graft dysfunction, acute cellular rejection, antibody-mediated rejection and infection. Dd-cfDNA has demonstrated good performance characteristics for the detection of various allograft injury states, most notably with a high negative-predictive value for detection of acute rejection. Elevated levels of dd-cfDNA in the early posttransplant period, reflecting molecular evidence of lung allograft injury, are associated with increased risk of chronic lung allograft dysfunction and death.

SUMMARY

As a quantitative, molecular biomarker of lung allograft injury, dd-cfDNA holds great promise in clinical and research settings for advancing methods of posttransplant surveillance monitoring, diagnosis of allograft injury states, monitoring adequacy of immunosuppression, risk stratification and unlocking pathophysiological mechanisms of various disease.

B-cell-derived cfDNA after primary BNT162b2 mRNA vaccination anticipates memory B-cells and SARS-CoV-2 neutralizing antibodies

Background

Methods

Findings

Conclusions

Funding

To understand the turnover of immune cells following SARS-CoV-2 vaccination, Fox-Fisher et al. analyzed fragments of cell-free DNA (cfDNA) that are released from dying immune cells to blood. The levels of B cell cfDNA after the primary dose correlated with neutralizing antibodies and memory B cells after the booster, revealing that early B cell turnover—potentially reflecting affinity maturation—affects later development of effective antibodies. They also observed co-elevation of lymphocyte and monocyte cfDNA after the booster, underscoring the involvement of innate immune cell turnover in the development of humoral and cellular adaptive immunity. cfDNA biomarkers open a new window into human immune cell dynamics in response to perturbations.

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.

It’s all in the combination: decoding the epigenome for cancer research and diagnostics

Genome regulation is governed by the dynamics of chromatin modifications. The extensive and diverse array of DNA and histone modifications allow multiple elements to act combinatorically and direct tissue-specific and cell-specific outcomes. Yet, our ability to elucidate these complex combinations and link them to normal genome regulation, as well as understand their deregulation in cancer, has been hindered by the lack of suitable technologies. Here, we describe recent findings indicating the importance of the combinatorial epigenome, and novel methodologies to measure and characterize these combinations. These complementary methods span multiple disciplines, providing a means to decode epigenetic combinations and link them to biological outcomes. Finally, we discuss the promise of harnessing the rich combinatorial epigenetic information to improve cancer diagnostics and monitoring.

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.

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.

Cell types of origin of the cell-free transcriptome

Cell-free RNA from liquid biopsies can be analyzed to determine disease tissue of origin. We extend this concept to identify cell types of origin using the Tabula Sapiens transcriptomic cell atlas as well as individual tissue transcriptomic cell atlases in combination with the Human Protein Atlas RNA consensus dataset. We define cell type signature scores, which allow the inference of cell types that contribute to cell-free RNA for a variety of diseases.

Cell types affected by various diseases are inferred from cell-free RNA.