The DNA methylome of human vascular endothelium and its use in liquid biopsies.

BACKGROUND: Vascular endothelial cells (VECs) are an essential component of each tissue, contribute to multiple pathologies, and are targeted by important drugs. Yet, there is a shortage of biomarkers to assess VEC turnover. METHODS: To develop DNA methylation-based liquid biopsies for VECs, we determined the methylome of VECs isolated from freshly dissociated human tissues. FINDINGS: A comparison with a human cell-type methylome atlas yielded thousands of loci that are uniquely unmethylated in VECs. These sites are typically gene enhancers, often residing adjacent to VEC-specific genes. We also identified hundreds of genomic loci that are differentially methylated in organotypic VECs, indicating that VECs feeding specific organs are distinct cell types with a stable epigenetic identity. We established universal and lung-specific VEC markers and evaluated their presence in circulating cell-free DNA (cfDNA). Nearly 2.5% of cfDNA in the plasma of healthy individuals originates from VECs. Sepsis, graft versus host disease, and cardiac catheterization are associated with elevated levels of VEC-derived cfDNA, indicative of vascular damage. Lung-specific VEC cfDNA is selectively elevated in patients with chronic obstructive pulmonary disease (COPD) or lung cancer, revealing tissue-specific vascular turnover. CONCLUSIONS: VEC cfDNA biomarkers inform vascular dynamics in health and disease, potentially contributing to early diagnosis and monitoring of pathologies, and assessment of drug activity. FUNDING: This work was supported by the Beutler Research Program, Helmsley Charitable Trust, JDRF, Grail and the DON Foundation (to Y.D.). Y.D holds the Walter & Greta Stiel Chair in heart studies. B.G., R.S., J.M., D.N., T.K., and Y.D. filed patents on cfDNA analysis.

Modeled residual current cancer risk after clinical investigation of a positive multicancer early detection test result.

BACKGROUND: Positive results of a multi-cancer early detection (MCED) test require confirmatory diagnostic workup. Here, residual current cancer risk (RR) during the process of diagnostic resolution, including situations where the initial confirmatory test does not provide resolution, was modeled. METHODS: A decision-tree framework was used to model conditional risk in a patient's journey through confirmatory diagnostic options and outcomes. The diagnostic journey assumed that cancer signal detection (a positive MCED test result) had already led to a transition from screening to diagnosis and began with an initial positive predictive value (PPV) from the positive result. Evaluation of a most probable (top) predicted cancer signal origin (CSO) and then a second-most probable predicted CSO followed. Under the assumption that the top- and second-predicted CSOs were each followed by a targeted confirmatory test, the RR was estimated for each subsequent scenario. RESULTS: For an initial MCED test result with typical performance characteristics modeled (PPV, 40%; top-predicted CSO accuracy, 90%), after a negative initial confirmatory test (sensitivity, 70%, 90%, or 100%) the RR ranged from 6% to 20%. A second-predicted CSO (accuracy, 50%), after a negative second confirmatory test, still provided a significant RR (3%-18%) in comparison with the National Institute for Health and Care Excellence-recommended cancer risk threshold warranting investigation in symptomatic individuals (3%). With a 40% PPV for an MCED test and 90% specificity for a confirmatory test, the risk of incidental findings after one or two confirmatory tests was 6% and 12%, respectively. CONCLUSIONS: These results may illustrate the impact of a positive MCED test on follow-up decision-making.

A DNA methylation atlas of normal human cell types.

DNA methylation is a fundamental epigenetic mark that governs gene expression and chromatin organization, thus providing a window into cellular identity and developmental processes1. Current datasets typically include only a fraction of methylation sites and are often based either on cell lines that underwent massive changes in culture or on tissues containing unspecified mixtures of cells2-5. Here we describe a human methylome atlas, based on deep whole-genome bisulfite sequencing, allowing fragment-level analysis across thousands of unique markers for 39 cell types sorted from 205 healthy tissue samples. Replicates of the same cell type are more than 99.5% identical, demonstrating the robustness of cell identity programmes to environmental perturbation. Unsupervised clustering of the atlas recapitulates key elements of tissue ontogeny and identifies methylation patterns retained since embryonic development. Loci uniquely unmethylated in an individual cell type often reside in transcriptional enhancers and contain DNA binding sites for tissue-specific transcriptional regulators. Uniquely hypermethylated loci are rare and are enriched for CpG islands, Polycomb targets and CTCF binding sites, suggesting a new role in shaping cell-type-specific chromatin looping. The atlas provides an essential resource for study of gene regulation and disease-associated genetic variants, and a wealth of potential tissue-specific biomarkers for use in liquid biopsies.

Evaluation of cell-free DNA approaches for multi-cancer early detection.

In the Circulating Cell-free Genome Atlas (NCT02889978) substudy 1, we evaluate several approaches for a circulating cell-free DNA (cfDNA)-based multi-cancer early detection (MCED) test by defining clinical limit of detection (LOD) based on circulating tumor allele fraction (cTAF), enabling performance comparisons. Among 10 machine-learning classifiers trained on the same samples and independently validated, when evaluated at 98% specificity, those using whole-genome (WG) methylation, single nucleotide variants with paired white blood cell background removal, and combined scores from classifiers evaluated in this study show the highest cancer signal detection sensitivities. Compared with clinical stage and tumor type, cTAF is a more significant predictor of classifier performance and may more closely reflect tumor biology. Clinical LODs mirror relative sensitivities for all approaches. The WG methylation feature best predicts cancer signal origin. WG methylation is the most promising technology for MCED and informs development of a targeted methylation MCED test.

Circulating Tumor DNA Allele Fraction: A Candidate Biological Signal for Multicancer Early Detection Tests to Assess the Clinical Significance of Cancers.

Current imaging-based cancer screening approaches provide useful but limited prognostic information. Complementary to existing screening tests, cell-free DNA-based multicancer early detection (MCED) tests account for cancer biology [manifested through circulating tumor allele fraction (cTAF)], which could inform prognosis and help assess the cancer's clinical significance. This review discusses the factors affecting circulating tumor DNA (ctDNA) levels and cTAF, and their correlation with the cancer's clinical significance. Furthermore, it discusses the influence of cTAF on MCED test performance, which could help inform prognosis. Clinically significant cancers show higher ctDNA levels quantified by cTAF than indolent phenotype cancers within each stage. This is because more frequent mitosis and cell death combined with increased trafficking of cell-free DNA into circulation leads to greater vascularization and depth of tumor invasion. cTAF has been correlated with biomarkers for cancer aggressiveness and overall survival; cancers with lower cTAF had better survival when compared with cancers as determined by the higher cTAF and Surveillance, Epidemiology, and End Results-based survival for that cancer type at each stage. MCED-detected cancers in case-control studies had comparable survival to Surveillance, Epidemiology, and End Results-based survival at each stage. Because many MCED tests use ctDNA as an analyte, cTAF could provide a common metric to compare performance. The prognostic value of cTAF may allow MCED tests to preferentially detect clinically significant cancers at early stages when outcomes are favorable and this may avoid overdiagnosis.

Clinical correlates of circulating cell-free DNA tumor fraction.

BACKGROUND: Oncology applications of cell-free DNA analysis are often limited by the amount of circulating tumor DNA and the fraction of cell-free DNA derived from tumor cells in a blood sample. This circulating tumor fraction varies widely between individuals and cancer types. Clinical factors that influence tumor fraction have not been completely elucidated. METHODS AND FINDINGS: Circulating tumor fraction was determined for breast, lung, and colorectal cancer participant samples in the first substudy of the Circulating Cell-free Genome Atlas study (CCGA; NCT02889978; multi-cancer early detection test development) and was related to tumor and patient characteristics. Linear models were created to determine the influence of tumor size combined with mitotic or metabolic activity (as tumor mitotic volume or excessive lesion glycolysis, respectively), histologic type, histologic grade, and lymph node status on tumor fraction. For breast and lung cancer, tumor mitotic volume and excessive lesion glycolysis (primary lesion volume scaled by percentage positive for Ki-67 or PET standardized uptake value minus 1.0, respectively) were the only statistically significant covariates. For colorectal cancer, the surface area of tumors invading beyond the subserosa was the only significant covariate. The models were validated with cases from the second CCGA substudy and show that these clinical correlates of circulating tumor fraction can predict and explain the performance of a multi-cancer early detection test. CONCLUSIONS: Prognostic clinical variables, including mitotic or metabolic activity and depth of invasion, were identified as correlates of circulating tumor DNA by linear models that relate clinical covariates to tumor fraction. The identified correlates indicate that faster growing tumors have higher tumor fractions. Early cancer detection from assays that analyze cell-free DNA is determined by circulating tumor fraction. Results support that early detection is particularly sensitive for faster growing, aggressive tumors with high mortality, many of which have no available screening today.

Prognostic Significance of Blood-Based Multi-cancer Detection in Plasma Cell-Free DNA.

PURPOSE: We recently reported the development of a cell-free DNA (cfDNA) targeted methylation (TM)-based sequencing approach for a multi-cancer early detection (MCED) test that includes cancer signal origin prediction. Here, we evaluated the prognostic significance of cancer detection by the MCED test using longitudinal follow-up data. EXPERIMENTAL DESIGN: As part of a Circulating Cell-free Genome Atlas (CCGA) substudy, plasma cfDNA samples were sequenced using a TM approach, and machine learning classifiers predicted cancer status and cancer signal origin. Overall survival (OS) of cancer participants in the first 3 years of follow-up was evaluated in relation to cancer detection by the MCED test and clinical characteristics. RESULTS: Cancers not detected by the MCED test had significantly better OS (P < 0.0001) than cancers detected, even after accounting for other covariates, including clinical stage and method of clinical diagnosis (i.e., standard-of-care screening or clinical presentation with signs/symptoms). Additionally, cancers not detected by the MCED test had better OS than was expected when data were adjusted for age, stage, and cancer type from the Surveillance, Epidemiology, and End Results (SEER) program. In cancers with current screening options, the MCED test also differentiated more aggressive cancers from less aggressive cancers (P < 0.0001). CONCLUSIONS: Cancer detection by the MCED test was prognostic beyond clinical stage and method of diagnosis. Cancers not detected by the MCED test had better prognosis than cancers detected and SEER-based expected survival. Cancer detection and prognosis may be linked by the underlying biological factor of tumor fraction in cfDNA.

High-intensity sequencing reveals the sources of plasma circulating cell-free DNA variants.

Accurate identification of tumor-derived somatic variants in plasma circulating cell-free DNA (cfDNA) requires understanding of the various biological compartments contributing to the cfDNA pool. We sought to define the technical feasibility of a high-intensity sequencing assay of cfDNA and matched white blood cell DNA covering a large genomic region (508 genes; 2 megabases; >60,000× raw depth) in a prospective study of 124 patients with metastatic cancer, with contemporaneous matched tumor tissue biopsies, and 47 controls without cancer. The assay displayed high sensitivity and specificity, allowing for de novo detection of tumor-derived mutations and inference of tumor mutational burden, microsatellite instability, mutational signatures and sources of somatic mutations identified in cfDNA. The vast majority of cfDNA mutations (81.6% in controls and 53.2% in patients with cancer) had features consistent with clonal hematopoiesis. This cfDNA sequencing approach revealed that clonal hematopoiesis constitutes a pervasive biological phenomenon, emphasizing the importance of matched cfDNA-white blood cell sequencing for accurate variant interpretation.

Characterisation of the changing genomic landscape of metastatic melanoma using cell free DNA.

Cancer is characterised by complex somatically acquired genetic aberrations that manifest as intra-tumour and inter-tumour genetic heterogeneity and can lead to treatment resistance. In this case study, we characterise the genome-wide somatic mutation dynamics in a metastatic melanoma patient during therapy using low-input (50 ng) PCR-free whole genome sequencing of cell-free DNA from pre-treatment and post-relapse blood samples. We identify de novo tumour-specific somatic mutations from cell-free DNA, while the sequence context of single nucleotide variants showed the characteristic UV-damage mutation signature of melanoma. To investigate the behaviour of individual somatic mutations during proto-oncogene B-Raf -targeted and immune checkpoint inhibition, amplicon-based deep sequencing was used to verify and track frequencies of 212 single nucleotide variants at 10 distinct time points over 13 months of treatment. Under checkpoint inhibition therapy, we observed an increase in mutant allele frequencies indicating progression on therapy 88 days before clinical determination of non-response positron emission tomogrophy-computed tomography. We also revealed mutations from whole genome sequencing of cell-free DNA that were not present in the tissue biopsy, but that later contributed to relapse. Our findings have potential clinical applications where high quality tumour-tissue derived DNA is not available.

Stable recombination hotspots in birds.

The DNA-binding protein PRDM9 has a critical role in specifying meiotic recombination hotspots in mice and apes, but it appears to be absent from other vertebrate species, including birds. To study the evolution and determinants of recombination in species lacking the gene that encodes PRDM9, we inferred fine-scale genetic maps from population resequencing data for two bird species: the zebra finch, Taeniopygia guttata, and the long-tailed finch, Poephila acuticauda. We found that both species have recombination hotspots, which are enriched near functional genomic elements. Unlike in mice and apes, most hotspots are shared between the two species, and their conservation seems to extend over tens of millions of years. These observations suggest that in the absence of PRDM9, recombination targets functional features that both enable access to the genome and constrain its evolution.

Nonhuman genetics. Strong male bias drives germline mutation in chimpanzees.

Germline mutation determines rates of molecular evolution, genetic diversity, and fitness load. In humans, the average point mutation rate is 1.2 × 10(-8) per base pair per generation, with every additional year of father's age contributing two mutations across the genome and males contributing three to four times as many mutations as females. To assess whether such patterns are shared with our closest living relatives, we sequenced the genomes of a nine-member pedigree of Western chimpanzees, Pan troglodytes verus. Our results indicate a mutation rate of 1.2 × 10(-8) per base pair per generation, but a male contribution seven to eight times that of females and a paternal age effect of three mutations per year of father's age. Thus, mutation rates and patterns differ between closely related species.

Arabidopsis meiotic crossover hot spots overlap with H2A.Z nucleosomes at gene promoters.

PRDM9 directs human meiotic crossover hot spots to intergenic sequence motifs, whereas budding yeast hot spots overlap regions of low nucleosome density (LND) in gene promoters. To investigate hot spots in plants, which lack PRDM9, we used coalescent analysis of genetic variation in Arabidopsis thaliana. Crossovers increased toward gene promoters and terminators, and hot spots were associated with active chromatin modifications, including H2A.Z, histone H3 Lys4 trimethylation (H3K4me3), LND and low DNA methylation. Hot spot-enriched A-rich and CTT-repeat DNA motifs occurred upstream and downstream, respectively, of transcriptional start sites. Crossovers were asymmetric around promoters and were most frequent over CTT-repeat motifs and H2A.Z nucleosomes. Pollen typing, segregation and cytogenetic analysis showed decreased numbers of crossovers in the arp6 H2A.Z deposition mutant at multiple scales. During meiosis, H2A.Z forms overlapping chromosomal foci with the DMC1 and RAD51 recombinases. As arp6 reduced the number of DMC1 or RAD51 foci, H2A.Z may promote the formation or processing of meiotic DNA double-strand breaks. We propose that gene chromatin ancestrally designates hot spots within eukaryotes and PRDM9 is a derived state within vertebrates.

Multiple instances of ancient balancing selection shared between humans and chimpanzees.

Instances in which natural selection maintains genetic variation in a population over millions of years are thought to be extremely rare. We conducted a genome-wide scan for long-lived balancing selection by looking for combinations of SNPs shared between humans and chimpanzees. In addition to the major histocompatibility complex, we identified 125 regions in which the same haplotypes are segregating in the two species, all but two of which are noncoding. In six cases, there is evidence for an ancestral polymorphism that persisted to the present in humans and chimpanzees. Regions with shared haplotypes are significantly enriched for membrane glycoproteins, and a similar trend is seen among shared coding polymorphisms. These findings indicate that ancient balancing selection has shaped human variation and point to genes involved in host-pathogen interactions as common targets.

A fine-scale chimpanzee genetic map from population sequencing.

To study the evolution of recombination rates in apes, we developed methodology to construct a fine-scale genetic map from high-throughput sequence data from 10 Western chimpanzees, Pan troglodytes verus. Compared to the human genetic map, broad-scale recombination rates tend to be conserved, but with exceptions, particularly in regions of chromosomal rearrangements and around the site of ancestral fusion in human chromosome 2. At fine scales, chimpanzee recombination is dominated by hotspots, which show no overlap with those of humans even though rates are similarly elevated around CpG islands and decreased within genes. The hotspot-specifying protein PRDM9 shows extensive variation among Western chimpanzees, and there is little evidence that any sequence motifs are enriched in hotspots. The contrasting locations of hotspots provide a natural experiment, which demonstrates the impact of recombination on base composition.