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.

The landscape of cell-free mitochondrial DNA in liquid biopsy for cancer detection.

BACKGROUND: Existing methods to detect tumor signal in liquid biopsy have focused on the analysis of nuclear cell-free DNA (cfDNA). However, non-nuclear cfDNA and in particular mitochondrial DNA (mtDNA) has been understudied. We hypothesize that an increase in mtDNA in plasma could reflect the presence of cancer, and that leveraging cell-free mtDNA could enhance cancer detection. RESULTS: We survey 203 healthy and 664 cancer plasma samples from three collection centers covering 12 cancer types with whole genome sequencing to catalogue the plasma mtDNA fraction. The mtDNA fraction is increased in individuals with cholangiocarcinoma, colorectal, liver, pancreatic, or prostate cancer, in comparison to that in healthy individuals. We detect almost no increase of mtDNA fraction in individuals with other cancer types. The mtDNA fraction in plasma correlates with the cfDNA tumor fraction as determined by somatic mutations and/or copy number aberrations. However, the mtDNA fraction is also elevated in a fraction of patients without an apparent increase in tumor-derived cfDNA. A predictive model integrating mtDNA and copy number analysis increases the area under the curve (AUC) from 0.73 when using copy number alterations alone to an AUC of 0.81. CONCLUSIONS: The mtDNA signal retrieved by whole genome sequencing has the potential to boost the detection of cancer when combined with other tumor-derived signals in liquid biopsies.

Integrated radiogenomics models predict response to neoadjuvant chemotherapy in high grade serous ovarian cancer.

High grade serous ovarian carcinoma (HGSOC) is a highly heterogeneous disease that typically presents at an advanced, metastatic state. The multi-scale complexity of HGSOC is a major obstacle to predicting response to neoadjuvant chemotherapy (NACT) and understanding critical determinants of response. Here we present a framework to predict the response of HGSOC patients to NACT integrating baseline clinical, blood-based, and radiomic biomarkers extracted from all primary and metastatic lesions. We use an ensemble machine learning model trained to predict the change in total disease volume using data obtained at diagnosis (n = 72). The model is validated in an internal hold-out cohort (n = 20) and an independent external patient cohort (n = 42). In the external cohort the integrated radiomics model reduces the prediction error by 8% with respect to the clinical model, achieving an AUC of 0.78 for RECIST 1.1 classification compared to 0.47 for the clinical model. Our results emphasize the value of including radiomics data in integrative models of treatment response and provide methods for developing new biomarker-based clinical trials of NACT in HGSOC.

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.

Fragmentation patterns and personalized sequencing of cell-free DNA in urine and plasma of glioma patients.

Glioma-derived cell-free DNA (cfDNA) is challenging to detect using liquid biopsy because quantities in body fluids are low. We determined the glioma-derived DNA fraction in cerebrospinal fluid (CSF), plasma, and urine samples from patients using sequencing of personalized capture panels guided by analysis of matched tumor biopsies. By sequencing cfDNA across thousands of mutations, identified individually in each patient's tumor, we detected tumor-derived DNA in the majority of CSF (7/8), plasma (10/12), and urine samples (10/16), with a median tumor fraction of 6.4 × 10-3 , 3.1 × 10-5 , and 4.7 × 10-5 , respectively. We identified a shift in the size distribution of tumor-derived cfDNA fragments in these body fluids. We further analyzed cfDNA fragment sizes using whole-genome sequencing, in urine samples from 35 glioma patients, 27 individuals with non-malignant brain disorders, and 26 healthy individuals. cfDNA in urine of glioma patients was significantly more fragmented compared to urine from patients with non-malignant brain disorders (P = 1.7 × 10-2 ) and healthy individuals (P = 5.2 × 10-9 ). Machine learning models integrating fragment length could differentiate urine samples from glioma patients (AUC = 0.80-0.91) suggesting possibilities for truly non-invasive cancer detection.

Circulating cell free DNA during definitive chemo-radiotherapy in non-small cell lung cancer patients - initial observations.

BACKGROUND: The overall aim was to investigate the change over time in circulating cell free DNA (cfDNA) in patients with locally advanced non-small cell lung cancer (NSCLC) undergoing concurrent chemo-radiotherapy. Furthermore, to assess the possibility of detecting circulating cell free tumor DNA (ctDNA) using shallow whole genome sequencing (sWGS) and size selection. METHODS: Ten patients were included in a two-phase study. The first four patients had blood samples taken prior to a radiation therapy (RT) dose fraction and at 30 minutes, 1 hour and 2 hours after RT to estimate the short-term dynamics of cfDNA concentration after irradiation. The remaining six patients had one blood sample taken on six treatment days 30 minutes post treatment to measure cfDNA levels. Presence of ctDNA as indicated by chromosomal aberrations was investigated using sWGS. The sensitivity of this method was further enhanced using in silico size selection. RESULTS: cfDNA concentration from baseline to 120 min after therapy was stable within 95% tolerance limits of +/- 2 ng/ml cfDNA. Changes in cfDNA were observed during therapy with an apparent qualitative difference between adenocarcinoma (average increase of 0.69 ng/ml) and squamous cell carcinoma (average increase of 4.0 ng/ml). Tumor shrinkage on daily cone beam computer tomography scans during radiotherapy did not correlate with changes in concentration of cfDNA. CONCLUSION: Concentrations of cfDNA remain stable during the first 2 hours after an RT fraction. However, based on the sWGS profiles, ctDNA represented only a minor fraction of cfDNA in this group of patients. The detection sensitivity of genomic alterations in ctDNA strongly increases by applying size selection.

Comprehensive characterization of cell-free tumor DNA in plasma and urine of patients with renal tumors.

BACKGROUND: Cell-free tumor-derived DNA (ctDNA) allows non-invasive monitoring of cancers, but its utility in renal cell cancer (RCC) has not been established. METHODS: Here, a combination of untargeted and targeted sequencing methods, applied to two independent cohorts of patients (n = 91) with various renal tumor subtypes, were used to determine ctDNA content in plasma and urine. RESULTS: Our data revealed lower plasma ctDNA levels in RCC relative to other cancers of similar size and stage, with untargeted detection in 27.5% of patients from both cohorts. A sensitive personalized approach, applied to plasma and urine from select patients (n = 22) improved detection to ~ 50%, including in patients with early-stage disease and even benign lesions. Detection in plasma, but not urine, was more frequent amongst patients with larger tumors and in those patients with venous tumor thrombus. With data from one extensively characterized patient, we observed that plasma and, for the first time, urine ctDNA may better represent tumor heterogeneity than a single tissue biopsy. Furthermore, in a subset of patients (n = 16), longitudinal sampling revealed that ctDNA can track disease course and may pre-empt radiological identification of minimal residual disease or disease progression on systemic therapy. Additional datasets will be required to validate these findings. CONCLUSIONS: These data highlight RCC as a ctDNA-low malignancy. The biological reasons for this are yet to be determined. Nonetheless, our findings indicate potential clinical utility in the management of patients with renal tumors, provided improvement in isolation and detection approaches.

ctDNA monitoring using patient-specific sequencing and integration of variant reads.

Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Detection of ctDNA can be challenging in patients with low-volume or residual disease, where plasma contains very few tumor-derived DNA fragments. We show that sensitivity for ctDNA detection in plasma can be improved by analyzing hundreds to thousands of mutations that are first identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) pipeline, which combines custom error-suppression methods and signal-enrichment approaches based on biological features of ctDNA. With this approach, the detection limit in each sample can be estimated independently based on the number of informative reads sequenced across multiple patient-specific loci. We applied INVAR to custom hybrid-capture sequencing data from 176 plasma samples from 105 patients with melanoma, lung, renal, glioma, and breast cancer across both early and advanced disease. By integrating signal across a median of >105 informative reads, ctDNA was routinely quantified to 1 mutant molecule per 100,000, and in some cases with high tumor mutation burden and/or plasma input material, to parts per million. This resulted in median area under the curve (AUC) values of 0.98 in advanced cancers and 0.80 in early-stage and challenging settings for ctDNA detection. We generalized this method to whole-exome and whole-genome sequencing, showing that INVAR may be applied without requiring personalized sequencing panels so long as a tumor mutation list is available. As tumor sequencing becomes increasingly performed, such methods for personalized cancer monitoring may enhance the sensitivity of cancer liquid biopsies.

Measurement of Plasma Cell-Free Mitochondrial Tumor DNA Improves Detection of Glioblastoma in Patient-Derived Orthotopic Xenograft Models.

The factors responsible for the low detection rate of cell-free tumor DNA (ctDNA) in the plasma of patients with glioblastoma (GBM) are currently unknown. In this study, we measured circulating nucleic acids in patient-derived orthotopically implanted xenograft (PDOX) models of GBM (n = 64) and show that tumor size and cell proliferation, but not the integrity of the blood-brain barrier or cell death, affect the release of ctDNA in treatment-naïve GBM PDOX. Analysis of fragment length profiles by shallow genome-wide sequencing (<0.2× coverage) of host (rat) and tumor (human) circulating DNA identified a peak at 145 bp in the human DNA fragments, indicating a difference in the origin or processing of the ctDNA. The concentration of ctDNA correlated with cell death only after treatment with temozolomide and radiotherapy. Digital PCR detection of plasma tumor mitochondrial DNA (tmtDNA), an alternative to detection of nuclear ctDNA, improved plasma DNA detection rate (82% vs. 24%) and allowed detection in cerebrospinal fluid and urine. Mitochondrial mutations are prevalent across all cancers and can be detected with high sensitivity, at low cost, and without prior knowledge of tumor mutations via capture-panel sequencing. Coupled with the observation that mitochondrial copy number increases in glioma, these data suggest analyzing tmtDNA as a more sensitive method to detect and monitor tumor burden in cancer, specifically in GBM, where current methods have largely failed. SIGNIFICANCE: These findings show that detection of tumor mitochondrial DNA is more sensitive than circulating tumor DNA analysis to detect and monitor tumor burden in patient-derived orthotopic xenografts of glioblastoma.

Detection of cell-free DNA fragmentation and copy number alterations in cerebrospinal fluid from glioma patients.

Glioma is difficult to detect or characterize using current liquid biopsy approaches. Detection of cell-free tumor DNA (cftDNA) in cerebrospinal fluid (CSF) has been proposed as an alternative to detection in plasma. We used shallow whole-genome sequencing (sWGS, at a coverage of < 0.4×) of cell-free DNA from the CSF of 13 patients with primary glioma to determine somatic copy number alterations and DNA fragmentation patterns. This allowed us to determine the presence of cftDNA in CSF without any prior knowledge of point mutations present in the tumor. We also showed that the fragmentation pattern of cell-free DNA in CSF is different from that in plasma. This low-cost screening method provides information on the tumor genome and can be used to target those patients with high levels of cftDNA for further larger-scale sequencing, such as by whole-exome and whole-genome sequencing.

Effects of Collection and Processing Procedures on Plasma Circulating Cell-Free DNA from Cancer Patients.

Circulating tumor DNA (ctDNA) offers new opportunities for noninvasive cancer management. Detecting ctDNA in plasma is challenging because it constitutes only a minor fraction of the total cell-free DNA (cfDNA). Pre-analytical factors affect cfDNA levels contributed from leukocyte lysis, hence the ability to detect low-frequency mutant alleles. This study investigates the effects of the delay in processing, storage temperatures, different blood collection tubes, centrifugation protocols, and sample shipment on cfDNA levels. Peripheral blood (n = 231) from cancer patients (n = 62) were collected into K3EDTA or Cell-free DNA BCT tubes and analyzed by digital PCR, targeted amplicon, or shallow whole-genome sequencing. To assess pre-analytic effects, plasma was processed under different conditions after 0, 6, 24, 48, 96 hours, and 1 week at room temperature or 4°C, or using different centrifugation protocols. Digital PCR showed that cfDNA levels increased gradually with time in K3EDTA tubes, but were stable in BCT tubes. K3EDTA samples stored at 4°C showed less variation than room temperature storage, but levels were elevated compared with BCT. A second centrifugation at 3000 × g gave similar cfDNA yields compared with higher-speed centrifugation. Next-generation sequencing showed negligible differences in background error or copy number changes between K3EDTA and BCT, or following shipment in BCT. This study provides insights into the effects of sample processing on ctDNA analysis.

Dynamics of multiple resistance mechanisms in plasma DNA during EGFR-targeted therapies in non-small cell lung cancer.

Tumour heterogeneity leads to the development of multiple resistance mechanisms during targeted therapies. Identifying the dominant driver(s) is critical for treatment decision. We studied the relative dynamics of multiple oncogenic drivers in longitudinal plasma of 50 EGFR-mutant non-small-cell lung cancer patients receiving gefitinib and hydroxychloroquine. We performed digital PCR and targeted sequencing on samples from all patients and shallow whole-genome sequencing on samples from three patients who underwent histological transformation to small-cell lung cancer. In 43 patients with known EGFR mutations from tumour, we identified them accurately in plasma of 41 patients (95%, 41/43). We also found additional mutations, including EGFR T790M (31/50, 62%), TP53 (23/50, 46%), PIK3CA (7/50, 14%) and PTEN (4/50, 8%). Patients with both TP53 and EGFR mutations before treatment had worse overall survival than those with only EGFR Patients who progressed without T790M had worse PFS during TKI continuation and developed alternative alterations, including small-cell lung cancer-associated copy number changes and TP53 mutations, that tracked subsequent treatment responses. Longitudinal plasma analysis can help identify dominant resistance mechanisms, including non-druggable genetic information that may guide clinical management.

Enhanced detection of circulating tumor DNA by fragment size analysis.

Existing methods to improve detection of circulating tumor DNA (ctDNA) have focused on genomic alterations but have rarely considered the biological properties of plasma cell-free DNA (cfDNA). We hypothesized that differences in fragment lengths of circulating DNA could be exploited to enhance sensitivity for detecting the presence of ctDNA and for noninvasive genomic analysis of cancer. We surveyed ctDNA fragment sizes in 344 plasma samples from 200 patients with cancer using low-pass whole-genome sequencing (0.4×). To establish the size distribution of mutant ctDNA, tumor-guided personalized deep sequencing was performed in 19 patients. We detected enrichment of ctDNA in fragment sizes between 90 and 150 bp and developed methods for in vitro and in silico size selection of these fragments. Selecting fragments between 90 and 150 bp improved detection of tumor DNA, with more than twofold median enrichment in >95% of cases and more than fourfold enrichment in >10% of cases. Analysis of size-selected cfDNA identified clinically actionable mutations and copy number alterations that were otherwise not detected. Identification of plasma samples from patients with advanced cancer was improved by predictive models integrating fragment length and copy number analysis of cfDNA, with area under the curve (AUC) >0.99 compared to AUC <0.80 without fragmentation features. Increased identification of cfDNA from patients with glioma, renal, and pancreatic cancer was achieved with AUC > 0.91 compared to AUC < 0.5 without fragmentation features. Fragment size analysis and selective sequencing of specific fragment sizes can boost ctDNA detection and could complement or provide an alternative to deeper sequencing of cfDNA.

High-resolution characterization of sequence signatures due to non-random cleavage of cell-free DNA.

BACKGROUND: High-throughput sequencing of cell-free DNA fragments found in human plasma has been used to non-invasively detect fetal aneuploidy, monitor organ transplants and investigate tumor DNA. However, many biological properties of this extracellular genetic material remain unknown. Research that further characterizes circulating DNA could substantially increase its diagnostic value by allowing the application of more sophisticated bioinformatics tools that lead to an improved signal to noise ratio in the sequencing data. METHODS: In this study, we investigate various features of cell-free DNA in plasma using deep-sequencing data from two pregnant women (>70X, >50X) and compare them with matched cellular DNA. We utilize a descriptive approach to examine how the biological cleavage of cell-free DNA affects different sequence signatures such as fragment lengths, sequence motifs at fragment ends and the distribution of cleavage sites along the genome. RESULTS: We show that the size distributions of these cell-free DNA molecules are dependent on their autosomal and mitochondrial origin as well as the genomic location within chromosomes. DNA mapping to particular microsatellites and alpha repeat elements display unique size signatures. We show how cell-free fragments occur in clusters along the genome, localizing to nucleosomal arrays and are preferentially cleaved at linker regions by correlating the mapping locations of these fragments with ENCODE annotation of chromatin organization. Our work further demonstrates that cell-free autosomal DNA cleavage is sequence dependent. The region spanning up to 10 positions on either side of the DNA cleavage site show a consistent pattern of preference for specific nucleotides. This sequence motif is present in cleavage sites localized to nucleosomal cores and linker regions but is absent in nucleosome-free mitochondrial DNA. CONCLUSIONS: These background signals in cell-free DNA sequencing data stem from the non-random biological cleavage of these fragments. This sequence structure can be harnessed to improve bioinformatics algorithms, in particular for CNV and structural variant detection. Descriptive measures for cell-free DNA features developed here could also be used in biomarker analysis to monitor the changes that occur during different pathological conditions.

Investigating and correcting plasma DNA sequencing coverage bias to enhance aneuploidy discovery.

Pregnant women carry a mixture of cell-free DNA fragments from self and fetus (non-self) in their circulation. In recent years multiple independent studies have demonstrated the ability to detect fetal trisomies such as trisomy 21, the cause of Down syndrome, by Next-Generation Sequencing of maternal plasma. The current clinical tests based on this approach show very high sensitivity and specificity, although as yet they have not become the standard diagnostic test. Here we describe improvements to the analysis of the sequencing data by reducing GC bias and better handling of the genomic repeats. We show substantial improvements in the sensitivity of the standard trisomy 21 statistical tests, which we measure by artificially reducing read coverage. We also explore the bias stemming from the natural cleavage of plasma DNA by examining DNA motifs and position specific base distributions. We propose a model to correct this fragmentation bias and observe that incorporating this bias does not lead to any further improvements in the detection of fetal trisomy. The improved bias corrections that we demonstrate in this work can be readily adopted into existing fetal trisomy detection protocols and should also lead to improvements in sub-chromosomal copy number variation detection.