Refined characterization of circulating tumor DNA through biological feature integration

AbstractCirculating 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.</jats:p

Association Of Plasma And Urinary Mutant DNA With Clinical Outcomes In Muscle Invasive Bladder Cancer

Muscle Invasive Bladder Cancer (MIBC) has a poor prognosis. Whilst patients can achieve a 6% improvement in overall survival with Neo-Adjuvant Chemotherapy (NAC), many do not respond. Body fluid mutant DNA (mutDNA) may allow non-invasive identification of treatment failure. We collected 248 liquid biopsy samples including plasma, cell pellet (UCP) and supernatant (USN) from spun urine, from 17 patients undergoing NAC. We assessed single nucleotide variants and copy number alterations in mutDNA using Tagged-Amplicon- and shallow Whole Genome- Sequencing. MutDNA was detected in 35.3%, 47.1% and 52.9% of pre-NAC plasma, UCP and USN samples respectively, and urine samples contained higher levels of mutDNA (p = <0.001). Longitudinal mutDNA demonstrated tumour evolution under the selective pressure of NAC e.g. in one case, urine analysis tracked two distinct clones with contrasting treatment sensitivity. Of note, persistence of mutDNA detection during NAC predicted disease recurrence (p = 0.003), emphasising its potential as an early biomarker for chemotherapy response.We would like to thank the CRUK-CI core facilities in particular; the bio-repository, genomic and bioinformatic cores. We are grateful for support from Cancer Research UK, the University of Cambridge and the Netherlands Cancer Institute. CGS and CEM were supported by European Research Council [337905]. KP was supported by the Cambridge Cancer Centre [A18345], the Royal College of Surgeons of England [KEVAL PATEL] and the Addenbrookes Charitable Trust [28/13A 9935]. MSH was supported by a grant from the Netherlands Organization for Scientific Research (NWO, Veni program)

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 0.91 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.We would like to acknowledge the support of The University of Cambridge, Cancer Research UK and the EPSRC (CRUK grant numbers A11906 (NR), A20240 (NR), A22905 (JDB), A15601 (JDB), A25177 (CRUK Cancer Centre Cambridge), A17242 (KMB), A16465 (CRUK-EPSRC Imaging Centre in Cambridge and Manchester)). The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 337905. The research was supported by the National Institute for Health Research Cambridge, National Cancer Research Network, Cambridge Experimental Cancer Medicine Centre and Hutchison Whampoa Limited. This research is also supported by Target Ovarian Cancer and the Medical Research Council through their Joint Clinical Research Training Fellowship for Dr Moore. The CALIBRATE study was supported by funding from AstraZeneca

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

Circulating tumor DNA (ctDNA) offers new opportunities for non-invasive cancer management. Detecting ctDNA in plasma is challenging since 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 i) delay in processing, ii) storage temperatures, iii) different blood collection tubes, iv) centrifugation protocols, and v) sample shipment on cfDNA levels. Peripheral blood (n=231) from cancer patients (n=62) were collected into K3EDTA or Cell-free DNA BCT® (BCT) tubes and analyzed by digital PCR, targeted amplicon, or shallow whole-genome (sWGS) sequencing. To assess pre-analytic effects, plasma was processed under different conditions after 0h, 6h, 24h, 48h, 96h, 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 to BCT. A second centrifugation at 3000g gave similar cfDNA yields compared to 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

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

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