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Enhanced detection of circulating tumor DNA by fragment size analysis
Abstract
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.
... Here, we evaluated the utility of ctDNA quantification using sWGS to predict treatment response in a consecutive retrospective cohort of metastatic breast cancer patients. We assessed the performance of established analysis tools to measure ctDNA levels, including ichorCNA [14], z-score [15] and t-MAD [16] and developed a Bayesian learning model that uses data from serial ctDNA measurements to dynamically predict treatment response. We also compared this approach to the use of a ctDNA targeted sequencing panel [17] and measuring CA15-3 in the same plasma samples to determine how these different methods performed in predicting treatment response. ...
... From these profiles, we derived three measures of the tumour burden (ichorCNA [14], z-score [15] and t-MAD [16]). We ran a modified version of ichorCNA. ...
... Several methods for ctDNA fraction estimation using sWGS CNA data of DNA extracted from plasma have been proposed, including ichorCNA [14], z-scores [15] or t-MAD [16]. We computed those scores for the first 478 samples that were processed and compared them. ...
Monitoring levels of circulating tumour‐derived DNA (ctDNA) provides both a noninvasive snapshot of tumour burden and also potentially clonal evolution. Here, we describe how applying a novel statistical model to serial ctDNA measurements from shallow whole genome sequencing (sWGS) in metastatic breast cancer patients produces a rapid and inexpensive predictive assessment of treatment response and progression‐free survival. A cohort of 149 patients had DNA extracted from serial plasma samples (total 1013, mean samples per patient = 6.80). Plasma DNA was assessed using sWGS and the tumour fraction in total cell‐free DNA estimated using ichorCNA. This approach was compared with ctDNA targeted sequencing and serial CA15‐3 measurements. We identified a transition point of 7% estimated tumour fraction to stratify patients into different categories of progression risk using ichorCNA estimates and a time‐dependent Cox Proportional Hazards model and validated it across different breast cancer subtypes and treatments, outperforming the alternative methods. We used the longitudinal ichorCNA values to develop a Bayesian learning model to predict subsequent treatment response with a sensitivity of 0.75 and a specificity of 0.66. In patients with metastatic breast cancer, a strategy of sWGS of ctDNA with longitudinal tracking of tumour fraction provides real‐time information on treatment response. These results encourage a prospective large‐scale clinical trial to evaluate the clinical benefit of early treatment changes based on ctDNA levels.
... all cfDNA, the subfraction known as ctDNA is distinct because it originates directly from cancer cells and carries cancer-specific alterations such as mutations, copy number alterations, and DNA methylation profiles (Wan et al., 2017). For example, in pancreatic cancers, the analysis of ctDNA have identified actionable mutations such as KRAS mutations and TP53 mutations that might justify an earlier diagnosis and subsequent treatments tailored for them (Mouliere et al., 2018). Techniques such as digital PCR and NGS improved the sensitivity and specificity in the detection of ctDNA. ...
... Tumor cells grow more, are more invasive, and more resistant to apoptosis through activation of the Ras protein with hyperactivation of downstream MAPK and PI3K-AKT pathways (Hidalgo, 2010;Hezel et al., 2006). It has been particularly specific for PDAC and was the only one that many scientists studied pertaining to a diagnostic and prognostic biomarker in analysis in ctDNA of liquid biopsy (Mouliere et al., 2018). • TP53 Mutation Mutations in TP53, a key tumor suppressor gene, are observed in approximately 50-75% of pancreatic cancers . ...
... With molecular barcoding, error-correction strategies, and ultra-deep sequencing, low frequency mutations in ctDNA can now be identified in the early stages of pancreatic cancer. It is now very likely to be detected with relatively good accuracy for identification of mutation in genes that often get mutated in PDAC, such as KRAS, TP53, CDKN2A, and SMAD4, as mentioned in Mouliere et al., 2018;Wan et al., 2017. All these developments permit identification of actionable mutations at a stage when it can be beneficial in the clinical sense and may be used for possibility of treatment options in terms of personalizing medicine. ...
Pancreatic cancer is a rather aggressive form of malignancy. It characteristically presents at an advanced stage and progresses aggressively. The liquid biopsy has revolutionized the diagnosis and monitoring approach. The present review provides details on current progress, clinical utility, and the challenge in applying the method for managing pancreatic cancer. These can shed light on tumor biology, molecular changes, and treatment responses with the examination of tumor-derived fluids like ctDNA, CTCs, and exosomes. Among the technologies which could enhance sensitivity and specificity to make this a more viable test for early detection and real-time monitoring are next-generation sequencing and microfluidics and other highly advanced exosome isolation techniques. Such clinical studies have only revealed recent times that liquid biopsy is indeed useful in the detection of hallmark mutations, such as KRAS and TP53, prognosis assessment, and therapeutic efficacy monitoring. Recent trends in multi-omics integration and artificial intelligence-driven biomarker discovery as well as liquid biopsy-based developing point-of-care diagnostic devices highlight the potential of revolutionizing personalized medicine. Despite its promise, some challenges that include low abundance of biomarkers, lack of standardization, and high costs characterize what limits acceptance of liquid biopsy in clinical practice. This review outlines the role which liquid biopsy can play in conquest of the challenges of diagnosis and therapy of pancreatic cancer. Concomitantly, it discusses future requirements for research, technological breakthroughs, and a collaborative attitude toward overcoming prevalent limitations. Multidisciplinary approaches in the fields of multi-omics, artificial intelligence, and scalable diagnostic tools hold the promise of enhanced early detection of pancreatic cancer and optimization of treatment strategies in the patients themselves.
... Lowcoverage whole genome sequencing (lcWGS) of plasma cell-free DNA (cfDNA) allows the detection of somatic copy number variations (CNVs) without prior tumor information. We and others demonstrated the suitability of lcWGS for therapy monitoring and response evaluation, particularly in advanced cancer patients who are often characterized by gross chromosomal instability [16][17][18][19][20]. More recently, several cfDNA fragmentation features were identified from lcWGS and linked to the abundance of ctDNA in plasma. ...
... More recently, several cfDNA fragmentation features were identified from lcWGS and linked to the abundance of ctDNA in plasma. These include the preponderance of short cfDNA fragments in cancer patients [20,21], diverse fragment end motifs [22,23], as well as aberrant fragment end positions when compared to cfDNA of non-cancer controls [24,25]. The combined evaluation of CNVs and fragmentation features in cfDNA was demonstrated to enhance the sensitivity of tumor-agnostic ctDNA quantification [23] and may improve response evaluation in NSCLC patients receiving PD-(L)1 blockade. ...
... The profiling of cfDNA fragment features (but not CNVs) was focused on the mononucleosomal cfDNA peak (i.e., fragments ≤ 250-bp) and included an additional fragment length-filtering step. Fragment length features were extracted using custom pysam implementations and comprised: i) the enrichment of short cfDNA fragments (i.e., the proportion of fragments between 126 and 135-bp) [20,21,31], ii) the absolute deviation of fragments between 126 and 135bp from the median of our healthy donor cohort, iii) the quantification of fragment end trinucleotide motif diversity scores (MDS) [22,23], iv) the analysis of fragment end position aberrancy (via information-weighted fraction of aberrant fragments (iwFAF) scores) [24], and v) the fragment end motif-based assessment of Alu element hypomethylation [32]. Further details on the determination of the cfDNA fragment features and per sample information on plasma collection, library preparation, sequencing data quality, and CNV as well as fragmentation biomarkers are given in the Supplementary Methods and Tab. ...
Background
Outcomes under anti-PD-(L)1 therapy have been variable in advanced non-small cell lung cancer (NSCLC) without reliable predictive biomarkers so far. Targeted next-generation sequencing (NGS) of circulating tumor DNA (ctDNA) has demonstrated potential clinical utility to support clinical decisions, but requires prior tumor genetic profiling for proper interpretation, and wide adoption remains limited due to high costs.
Methods
Tumor-agnostic low-coverage ctDNA whole genome sequencing (lcWGS) was used to longitudinally track genome-wide copy number variations (CNVs) and fragmentation features in advanced NSCLC patients ( n = 118 samples from 49 patients) and healthy controls ( n = 57). Tumor PD-L1 expression was available for comparison.
Findings
Fragmentation features and CNVs were complementary indicators, whose combination significantly increased ctDNA detection compared to single-marker assessments (+ 20.3% compared to CNV analysis alone). Baseline fragment length alterations, but not CNVs, were significantly associated with subsequent progression-free survival (PFS; hazard ratio [HR] = 4.10, p = 6.58e-05) and could improve PFS predictions based on tumor PD-L1 expression alone (HR = 2.70, p = 0.019). Residual CNVs or aberrant fragmentation of ctDNA under ongoing therapy could stratify patients according to the subsequent response duration (median 5.8 vs. 47.0 months, p = 1.13e-06). The integrative analysis of ctDNA fragment characteristics at baseline, tumor PD-L1 expression, and residual ctDNA under ongoing treatment constituted the strongest independent predictor of PFS ( p = 6.25e-05) and overall survival ( p = 1.3e-03) in multivariable analyses along with other clinicopathologic variables.
Interpretation
This study demonstrates the feasibility and potential clinical utility of lcWGS for the tumor-agnostic stratification and monitoring of advanced NSCLC under PD-(L)1 blockade based on CNV and fragmentomic profiling.
... The size profile of these shorter fragments from patients with cancer also exhibits increased 10-bp oscillation amplitude in the range of 90-145 bp (ref. 16). cfDNA from patients with cancer may also show a higher proportion of fragments longer than 180 bp (refs. ...
... We also noticed a trend that Fragle exhibited improved ctDNA detection over ichorCNA in samples with low levels of copy number variation ( Supplementary Fig. 7). As an additional comparison, we explored other fragment length features previously used for the classification of cancer and healthy samples 16 , and trained a random forest model on the discovery cohort using four features derived from the fragment length distribution (Methods). This four-feature model demonstrated substantially lower classification accuracy (AUC = 0.79) than Fragle in the validation sets. ...
... While previous studies have explored how cfDNA fragment length signatures can be used to classify plasma samples from patients with cancer and healthy individuals [16][17][18][19][20][21] , it remained unknown whether these fragmentomic signatures could also allow for accurate quantification of ctDNA levels in a blood sample. Here we developed Fragle, a multi-stage machine learning model that quantifies ctDNA levels directly from the cfDNA fragment length density distribution, with no requirement for tumour biopsy or matched normal sample. ...
The quantification of circulating tumour DNA (ctDNA) in blood enables non-invasive surveillance of cancer progression. Here we show that a deep-learning model can accurately quantify ctDNA from the density distribution of cell-free DNA-fragment lengths. We validated the model, which we named ‘Fragle’, by using low-pass whole-genome-sequencing data from multiple cancer types and healthy control cohorts. In independent cohorts, Fragle outperformed tumour-naive methods, achieving higher accuracy and lower detection limits. We also show that Fragle is compatible with targeted sequencing data. In plasma samples from patients with colorectal cancer, longitudinal analysis with Fragle revealed strong concordance between ctDNA dynamics and treatment responses. In patients with resected lung cancer, Fragle outperformed a tumour-naive gene panel in the prediction of minimal residual disease for risk stratification. The method’s versatility, speed and accuracy for ctDNA quantification suggest that it may have broad clinical utility.
... However, early-stage breast cancer detection using ctDNA remains challenging due to the low ctDNA abundance, especially when tumors are small and confined to the breast [60]. Additionally, ctDNA is highly fragmented, typically ranging between 50-200 base pairs, necessitating ultra-sensitive sequencing technologies to accurately detect and quantify tumor-specific methylation changes [61]. Unlike tissue-based NGS, which directly analyses tumor DNA, liquid biopsy must contend with background noise from non-tumor-derived cfDNA, complicating tumor signal extraction and data interpretation [62,63]. ...
... Tumor-derived ctDNA fragments exhibit unique fragmentation characteristics, including shorter fragment sizes, altered nucleosome positioning, and distinct fragment end motifs, which can serve as additional biomarkers for cancer detection [41,61]. ...
Breast cancer remains one of the most common cancers in women worldwide. Early detection is critical for improving patient outcomes, yet current screening methods have limitations. Therefore, there is a pressing need for more sensitive and specific approaches to detect breast cancer in its earliest stages. Liquid biopsy has emerged as a promising non-invasive method for early cancer detection and management. DNA methylation, an epigenetic alteration that often precedes genetic changes, has been observed in precancerous or early cancer stages, making it a valuable biomarker. This review explores the role of DNA methylation in breast cancer and its potential for developing blood-based tests. We discuss advancements in DNA methylation detection methods, recent discoveries of potential DNA methylation biomarkers from both single-omics and multi-omics integration studies, and the role of machine learning in enhancing diagnostic accuracy. Challenges and future directions are also addressed. Although challenges remain, advances in multi-omics integration and machine learning continue to enhance the clinical potential of methylation-based biomarkers. Ongoing research is crucial to further refine these approaches and improve early detection and patient outcomes.
... Epigenomic profiling holds promise for early tumor 40 characteriza]on, given the early occurrence and ]ssue specificity of epigenomic changes, such 41 as DNA methyla]on 9,10 . CfDNA fragmenta]on panerns were equally shown to harbor tumor-42 specific informa]on and reflect ctDNA levels [11][12][13] . This study developed a mul]modal LBx 43 approach, analyzing (epi)genomic cfDNA features with low-coverage whole-genome 44 sequencing (lcWGS) and cell-free methylated DNA immunoprecipita]on sequencing 45 (cfMeDIP-seq) in plasma and urine of newly diagnosed PCa pa]ents and individuals without 46 cancer. ...
... In-silico size selec]on (90-150 bp) aimed to enrich for ctDNA, as previously shown 12,21 , 151 increasing the number of ctDNA-posi]ve plasma samples to nine (5x lPCa, 4x aPCa). In urine, 152 ...
Background and Objective
Prostate cancer (PCa) is a heterogeneous disease, impeding early detection and risk stratification. Liquid biopsies (LBx) enable minimally invasive tumor profiling, but circulating tumor-derived DNA (ctDNA) detection remains difficult, especially in early-stage PCa. This study aimed at developing a multimodal LBx approach, analyzing genomic and epigenomic cell-free DNA (cfDNA) features in plasma and urine from newly diagnosed PCa patients for early detection, tumor characterization, and risk stratification of aggressive PCa.
Methods
Plasma and urine samples were included from 55 localized PCa (lPCa) patients, 18 advanced PCa (aPCa) patients, and 36 cancer-free controls. Low-coverage whole-genome sequencing and methylated DNA immunoprecipitation sequencing were performed to assess fragmentation, chromosomal instability, and methylation in cfDNA.
Key findings and Limitations
The complementary (epi)genomic analysis of plasma and urinary cfDNA achieved a 45% ctDNA detection rate in newly diagnosed PCa. Major differences were observed between aPCa and controls, reflecting increasing signals with tumor progression. Epigenomic cfDNA features differentiated lPCa from aPCa, and ctDNA was detected in 46% of PCa patients with prostate-specific antigen <10 ng/ml, suggesting potential for risk stratification. However, sensitivity in early PCa remains a major limitation.
Conclusions and Clinical Implications
This study highlights the potential of multimodal LBx approaches, integrating genomic and epigenomic cfDNA features, for minimally invasive characterization of primary PCa and potential metastasis at initial diagnosis. While promising for risk stratification, sensitivity requires optimization for early detection. Incorporating LBx into clinical workflows could complement diagnostics and support clinical decision-making for personalized treatments tailored to patients' PCa risk profiles.
... The somatic copy number aberrations (CNAs) carried by the genome of cancerous cells are detectable by low-coverage whole-genome sequencing and downstream analysis of coverage profiles from cancer patients [10,11]. Fragmentomic analysis of cfDNA offers the possibility to detect new sensitive biomarkers for cancer detection [12,13], as cfDNA fragments mirror the chromatin accessibility, nucleosome positioning, and degradation pattern of their tissue of origin [14][15][16][17]. For this reason, CNA calling can be complemented with fragmentation profile analysis based on fragment length, as well as is therefore of utmost importance in strengthening biological signals and guaranteeing detection performance in independent cohorts. ...
... Surprisingly, observed long (>166 bp) fragment ratios were observed as increased in breast cancer (Fig. 4E). While short (<151 bp) and longer (>220 bp) fragments are both reported as being more prominent in cancer [13,29], a significant portion of these short fragments have been filtered out due to their low mapping quality. In Fig. 4F, we show that these differences in fragmentomic patterns lead to the two control groups being perfectly segregated in t-SNE plots ("Baseline" panel). ...
Cell-free DNA (cfDNA) is a rich source of biomarkers for various pathophysiological conditions. Preanalytical variables, such as the library preparation protocol or sequencing platform, are major confounders of cfDNA analysis. We present DAGIP, a novel data correction method that builds on optimal transport theory and deep learning, which explicitly corrects for the effect of such preanalytical variables and can infer technical biases. Our method improves cancer detection and copy number alteration analysis by alleviating the sources of variation that are not of biological origin. It also enhances fragmentomic analysis of cfDNA. DAGIP allows the integration of cohorts from different studies.
... cfDNA can also help detect new tumor sites and serve as a surrogate for tissue biopsies when the primary site is unidentified, by detecting driver mutations specific to the tumor origin. [10][11][12] Eventually, ctDNA allows access to both intratumor and intertumor genetic heterogeneity, otherwise difficult to access. 13 Fragment Sizes (bp) Concentration (pg/µL) Some of these fragments are originated from tumoral cells, which can be primary, metastatic, or circulating tumor cells. ...
... Subsequently, focusing on these fragments could enhance ctDNA detection. 10 Finally, patients with cancer present distinct and more variable end motifs, 36 different proportions of jagged ends (uneven DNA extremities; Fig 1C), 37,38 and various breakpoint motifs. 39 FIG 1. (Continued). ...
PURPOSE
Liquid biopsy, specifically circulating cell-free DNA (cfDNA), has emerged as a powerful tool for cancer early diagnosis, prognosis, and treatment monitoring over a wide range of cancer types. Computational modeling (CM) of cfDNA data is essential to harness its full potential for real-time, noninvasive insights into tumor biology, enhancing clinical decision making.
DESIGN
This work reviews CM-cfDNA methods applied to clinical oncology, emphasizing both machine learning (ML) techniques and mechanistic approaches. The latter integrate biological principles, enabling a deeper understanding of cfDNA dynamics and its relationship with tumor evolution.
RESULTS
Key findings highlight the effectiveness of CM-cfDNA approaches in improving diagnostic accuracy, identifying prognostic markers, and predicting therapeutic outcomes. ML models integrating cfDNA concentration, fragmentation patterns, and mutation detection achieve high sensitivity and specificity for early cancer detection. Mechanistic models describe cfDNA kinetics, linking them to tumor growth and response to treatment, for example, immune checkpoint inhibitors. Longitudinal data and advanced statistical constructs further refine these models for quantification of interindividual and intraindividual variability.
CONCLUSION
CM-cfDNA represents a pivotal advancement in precision oncology. It bridges the gap between extensive cfDNA data and actionable clinical insights, supporting its integration into routine cancer care. Future efforts should focus on standardizing protocols, validating models across populations, and exploring hybrid approaches combining ML with mechanistic modeling to improve biological understanding.
... Previous studies interrogating the diagnostic potential of liquid biopsies for CNS tumors were primarily focused on genomic alterations and methylation aberrations in ctDNA. Mouliere et al. utilized a RF classifier to integrate copy number alterations with specific fragmentomics signatures, achieving highly accurate cancer classification with an AUC of 0.91 in Article npj Precision Oncology | (2025) 9:123 glioma cases 46 . Lavon et al. reported the use of methylation at the MGMT promoter as a serum marker for brain tumors and demonstrated excellent specificity (100%) but modest sensitivity (59%) 47 , highlighting the limitations of a single-gene strategy. ...
... Additionally, 107 non-cancer controls (NCCs) were analysed with T7-MBDseq and split into a training set (n = 78) and an unseen test set (n = 29, Figure 1). Of the NCCs, 98 were previously published 25,26 The proportion of short cfDNA fragments (p100-150 bp) was determined from the same WGS data 15,28 . Methylation array data from Koelsche et al. ...
Liquid biopsies and cell-free DNA (cfDNA) offer minimally invasive methods for the diagnosis and monitoring of Ewing Sarcoma (EwS). EwS have a low tumour mutational burden and their detection with plasma cfDNA is challenging.
We hypothesised that analysing the cfDNA methylome and fragmentome could enhance sensitivity for detecting EwS and identifying early disease recurrence. We conducted whole-genome and methylome sequencing of cfDNA from 68 serial samples of 15 patients with EwS and 3 patients with CIC-rearranged sarcoma (CIC). With EwingSign, a new machine learning model, we identified EwS or CIC in a test set for 10 out of 12 patients at diagnosis and 15 out of 18 clinically confirmed relapse events. 0 out of 29 non-cancer controls were detected positive with EwingSign.
These findings indicate that cfDNA methylome and fragmentome analysis, if validated in a larger cohort, could improve disease detection, monitoring and relapse identification in patients with EwS.
... For instance, in breast cancer, people with metastasis are likely to have shorter fragments of ctDNA than early-stage patients. While apoptotic tumours generate 180-1000 bp fragments, those from necrotic malignancies can reach 10,000 bp 16,17 . The size of ctDNA is roughly 20-40 bp smaller than DNA length in one nucleosome, with enrichment occurring in segments 90-150 bp and 250-320 bp in size, which also revealed that mutated ctDNA has shorter fragments than non-mutant cfDNA 15,17,18 . ...
Breast cancer contributes a large fraction to mortality among women diagnosed with cancer. It is important to monitor residual disease and extend the lead time to detect relapse in high-risk patients. Minimally invasive techniques that utilise circulating biomarkers are being explored for their potential in diagnosis, prognosis, and disease monitoring of breast cancer. Circulating biomarkers have been investigated as tools for breast cancer diagnosis, prognosis, prediction, and monitoring of therapeutic response and resistance. Among these, circulating tumour cells and cell-free plasma DNA (cfDNA) derived from tumour cells (circulating tumour DNA i.e . ctDNA) have been integrated into clinical trial designs. Among all circulating biomarkers, ctDNA stands out as a promising biomaterial with great potential as it is thought to mirror the tumour’s evolution. However, its clinical utilisation is hampered mainly by gaps in knowledge of its biological properties and specific characteristics. The development of robust and standardised methods for assessing circulating biomarkers is essential for realising the potential of personalised medicine. This review aims to summarise the characteristics of ctDNA and its role in breast cancer, drawing from both basic and translational research to provide insights into its clinical application. This review suggests that ctDNA has the potential to be a non-invasive, real-time surrogate for tumour tissue-based biomarkers. In conclusion, circulating biomarkers have the potential to revolutionise breast cancer diagnosis, prognosis, and treatment monitoring, but the development of standardised methods for their assessment is essential. ctDNA, in particular, shows great promise as a liquid biopsy tool, but further research is needed to understand its biology and ensure its clinical utility fully.
... ctDNA constitutes a small fraction of cfDNA released by malignant tumors into the bloodstream or other bodily fluids [93]. ctDNA typically exhibits greater fragmentation compared to non-mutant cfDNA, with peak enrichment between 90 and 150 base pairs, contrasting with 250-320 base pairs for non-mutant cfDNA [94][95][96]. Levels of ctDNA correlate with clinical and pathological characteristics of cancer, including stage, tumor burden, localization, vascularization, and response to therapy [97][98][99]. Moreover, ctDNA levels vary based on tumor type, shedding rate, and other biological factors [98,100]. ...
Next-generation sequencing (NGS) has emerged as a pivotal technology in the field of oncology, transforming the approach to cancer diagnosis and treatment. This paper provides a comprehensive overview of the integration of NGS into clinical settings, emphasizing its significant contributions to precision medicine. NGS enables detailed genomic profiling of tumors, identifying genetic alterations that drive cancer progression and facilitating personalized treatment plans targeting specific mutations, thereby improving patient outcomes. This capability facilitates the development of personalized treatment plans targeting specific mutations, leading to improved patient outcomes and the potential for better prognosis. The application of NGS extends beyond identifying actionable mutations; it is instrumental in detecting hereditary cancer syndromes, thus aiding in early diagnosis and preventive strategies. Furthermore, NGS plays a crucial role in monitoring minimal residual disease, offering a sensitive method to detect cancer recurrence at an early stage. Its use in guiding immunotherapy by identifying biomarkers that predict response to treatment is also highlighted. Ethical issues related to genetic testing, such as concerns around patient consent and data privacy, are also important considerations that need to be addressed for the broader implementation of NGS. These include the complexities of data interpretation, the need for robust bioinformatics support, cost considerations, and ethical issues related to genetic testing. Addressing these challenges is essential for the widespread adoption of NGS. Looking forward, advancements such as single-cell sequencing and liquid biopsies promise to further enhance the precision of cancer diagnostics and treatment. This review emphasizes the transformative impact of NGS in oncology and advocates for its incorporation into routine clinical practice to promote molecularly driven cancer care.
... In pathological conditions, notably cancer, it has been observed that the average length of nucleosomal lengths of cfDNA fragments are shorter, typically by 10-20 bps, when compared to those of a healthy patient [19][20][21]. Therefore, the relative abundance of the short and long fragments is being used as an effective cfDNA biomarker [19]. ...
Cell-free DNA (cfDNA) is changing the face of liquid biopsy as a minimally invasive tool for disease detection and monitoring, with its main applications in oncology and prenatal testing, and rising roles in transplant patient monitoring. However, the processes of cfDNA biogenesis, fragmentation, and clearance are complex and require further investigation. Evidence suggests that cfDNA production relates to mechanisms of cell death and DNA repair, both of which further influence fragment size and its applicability as a biomarker. An emerging domain, cfDNA fragmentomics is being explored for advancing the field of diagnostics using non-mutational signatures such as fragment size ratios and methylation patterns. Thus, this review examines structural diversity in cfDNA with various fragment sizes. In examining these cfDNA subsets, we discuss their distinct biological origins and potential clinical utility. Development of sequencing methodologies has broadened the application of cfDNA in diagnosing cancers and organ-specific pathologies, as well as directing personalized therapies. This has been achieved by identifying and uncovering different subsets of cfDNA in biofluids using different methodologies and biofluids. Different cfDNA subsets provide important insights regarding genomic and epigenetic features, enhancing the understanding of gene regulation, tissue-specific functions, and disease progression. Advancement of these key areas further asserts increasing clinical relevance for the use of cfDNA as a biomarker. Continued exploration of cfDNA subsets is expected to drive further innovation in liquid biopsy and its integration into routine clinical practice.
... Ultimately, researchers will have to come up with more complex models integrating various descriptors known to be of value in liquid biopsies. In addition to protein analytes and mutations, as already used by CancerSEEK 3 , researchers will have to consider epigenetic marks 44 , nucleosome occupancy 45 , fragment sizes 26,46 , combinations of coding genes, noncoding RNAs like lncRNAs (this study), miRNAs 47 , repeat regions or regulatory elements 48 through a variety of experimental techniques 49 . Rather than relying on broad summary statistics, researchers could use informative fragmentomic features identified through training neural nets. ...
Several studies have made it possible to envision a translational application of plasma DNA sequencing in cancer diagnosis and monitoring. However, the extremely low concentration of circulating tumour DNA (ctDNA) fragments among the total cell-free DNA (cfDNA) remains a formidable challenge to overcome and statistical models have yet to be improved enough to become of practical use. In this study, we set about appraising the predictive value of a variety of binary classification models based on cfDNA sequencing using fragmentation features extracted around transcription start sites (TSSs). We investigated (1) features summarising mapped fragment density around each TSS, (2) long non-coding RNA (lncRNA) genes versus coding genes and (3) selection criteria to generate gene classes to be assigned by the model. Given that, in healthy samples, most of the cfDNA comes from lymphomyeloid lineages, we could identify the model parametrisation with the best accuracy in those lineages using publicly available datasets of healthy patients’ cfDNA. Our results show that (1) the way tissue-specific gene classes are defined matters more than what fragmentation features are included, and (2) in particular, lncRNAs are more tissue specific than coding genes and stand out in terms of both sensitivity and specificity in our results.
... MRD is defined as the complete response (CR) to the disease achieved through surgery, radical radiotherapy, targeted therapy, or combination therapies, with a reduction in the tumor burden by >99%, and still residual tumor cells or other tumor cell derivatives, it can cause tumor recurrence (16)(17)(18). ctDNA is fragmented DNA derived from tumor cells, with a length of 130-150 base pairs and a half-life of 16 min to 2.5 h (19). It accounts for less than 1% of the nucleic acid fragments (20,21). ...
Background and objective:
In recent years, significant advancements have been achieved in the treatment of non-small cell lung cancer (NSCLC), leading to prolonged patient survival; however, a subset of NSCLC patients may experience recurrence or distant metastasis following initial successful treatment. This phenomenon may be attributed to the presence of minimal residual disease (MRD) that remains undetectable by conventional imaging or laboratory techniques post-treatment. The potential sources of tumor recurrence (MRD), are significantly associated with adverse patient prognosis; therefore, the monitoring of these lesions is critically important in the management of NSCLC. This review seeks to examine the current evidence regarding the application of MRD in NSCLC clinical practice, as well as the challenges encountered in its role as a biomarker.
Methods:
We performed a narrative review by systematically searching the PubMed and Web of Science databases for pertinent literature published from 2005 to 2024, with the objective of identifying significant literature related to clinical research and detection techniques for MRD in NSCLC.
Key content and findings:
The detection of circulating tumor DNA (ctDNA) for MRD has emerged as a significant focus in high-sensitivity genetic testing for monitoring NSCLC. This method may facilitate the assessment of recurrence risk in NSCLC and inform clinical decision-making to identify high-risk patients who are likely to benefit from treatment, thereby providing a rationale for treatment escalation or de-escalation. Nevertheless, the clinical application of ctDNA MRD continues to encounter several challenges, among which improving detection sensitivity and selecting the best detection timing are urgent issues that need to be addressed.
Conclusions:
ctDNA MRD testing offers robust evidence to assist clinicians in the early identification of NSCLC recurrence and in guiding clinical treatment. We recommend integrating ctDNA MRD with traditional biomarkers and imaging modalities for a comprehensive evaluation aiming at optimizing treatment strategies.
... Multiple screening approaches have been developed to detect tumour-specific genomic and epigenetic alterations. In addition to PCR, next-generation sequencing (including whole-exome or wholegenome sequencing), cancer personalized profiling by deep sequencing (CAPP-Seq;Newman et al., 2014), tagged-amplicon deep sequencing (TAm-Seq; Forshew et al., 2012) and targeted or whole-genome methylation sequencing (Liu et al., 2020) were developed to detect mutations, copy number aberrations, cfDNA fragmentation profiles (Mouliere et al., 2018) or cancer-specific epigenetic signatures (Liu et al., 2020). Detection of Kirsten rat sarcoma viral oncogene homolog (KRAS) point mutations is specifically important because anti-EGFR therapy is ineffective in the presence of KRAS mutations (Lièvre et al., 2006). ...
Circulating cell‐free DNA (cfDNA), circulating tumour DNA (ctDNA) and inflammatory cytokines have prognostic and predictive value in oncology. However, the effects of acute exercise on cfDNA levels are unknown. Here, we explore the kinetics of cfDNA, ctDNA and cytokines upon an incremental exercise test in a pilot cohort of cancer patients compared with healthy control subjects. Patients with solid tumours (n = 12) and age‐matched control subjects (n = 6) were recruited to perform an all‐out cardiopulmonary bicycle test. Blood samples were collected before (Pre), directly after (Post) and 90 min after the test (+90 min), and the cfDNA, ctDNA (Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations), DNase I activity and cytokine levels were measured. Cardiopulmonary exercise testing was easily feasible in cancer patients, and data from eight patients and five control subjects were available for exploratory statistical evaluation. The cfDNA levels increased from Pre to Post and decreased to baseline at +90 min in all subjects. The cfDNA concentrations and DNase I activity were clearly correlated in the control but not in the cancer group. Neutrophil‐associated myeloperoxidase (MPO), calprotectin (MRP 8/14), and lipocalin A (NGAL) showed strong responses to exercise. The percentage of ctDNA, detected in only one cancer patient, decreased after acute exercise. In our study, we could safely perform cardiopulmonary exercise testing with patients with different cancer entities and subsequently run biomarker analyses. Our results hint at an exercise‐triggered release of cfDNA and neutrophil‐derived cytokines in cancer patients.
... cfDNA fragmentomics is an emerging field in liquid biopsy, referring to the study of cfDNA fragmentation patterns, fragment sizes, and end characteristics [99][100][101] . Studies have demonstrated that cancer patients often exhibit more diverse fragmentation patterns, leading to an overall smaller average fragment size 102 , which can be used to distinguish cancer from noncancer derived cfDNA. In fact, qPCR was used by Diehl et al. to first suggest that cfDNA fragments containing mutant sequences are generally shorter than non-mutant cfDNA fragments 103 . ...
Circulating tumor DNA (ctDNA) has emerged as a dynamic biomarker in cancer, as evidenced by its increasing integration into clinical practice. Carrying tumor specific characteristics, ctDNA can be used to inform treatment selection, monitor response, and identify drug resistance. In this review, we provide a comprehensive, up-to-date summary of ctDNA in monitoring treatment response with a focus on lung, colorectal, and breast cancers, and discuss current challenges and future directions.
... (2) fragment size analysis of tumor-derived ctDNA. The challenges addressed to fully integrating this technology into clinical practice include i.e. standardization of assays, sensitivity limitations, and biological variability due to tumor heterogeneity [53][54][55][56][57]. ...
Melanocytic lesions encompass a broad spectrum of skin neoplasms, ranging from benign nevi to malignant melanoma. Given melanoma’s aggressive nature, early detection and accurate diagnosis are critical for optimal patient outcomes. This review explores the role of complementary diagnostic tools in evaluating melanocytic lesions, focusing on histopathological, immunohistochemical, and molecular-genetic techniques. Histopathology remains the gold standard for diagnosing melanocytic lesions, relying on key features such as asymmetry, architectural disorder, cellular atypia, mitotic activity, and pagetoid spread. Prognostic factors, including Breslow thickness, ulceration, and sentinel lymph node metastasis, guide risk stratification and treatment decisions. Immunohistochemistry enhances diagnostic precision by identifying particularly valuable markers in diagnostically challenging cases and supports pathological assessment. Additionally, molecular and genetic tools refine classification and risk assessment, including fluorescence in situ hybridization, comparative genomic hybridization, next-generation sequencing, and gene expression profiling. BRAF, NRAS, and KIT mutation analyses guide targeted therapies, while TERT promoter and CDKN2A deletions could support prognostication. Emerging technologies such as artificial intelligence (AI)-assisted histopathology will enhance diagnostic reproducibility in the future. Liquid biopsies that detect circulating tumor DNA offer promising support for early melanoma detection and monitoring and provide a noninvasive method for tracking tumor progression. Integrating histopathology with immunohistochemical and molecular tools minimizes diagnostic uncertainty and enables personalized treatment strategies. Future advancements, including AI, multi-omics approaches, and minimally invasive molecular diagnostics, are expected to refine melanoma detection, prognostication, and therapeutic decision-making, further advancing precision medicine in dermatologic oncology.
... However, this does not prove that short sequences of cfDNA are useless in the field of machine learning. Research has confirmed that short sequences can significantly increase the diagnostic capabilities of machine learning models [179]. This may be because short sequences carry various mechanistic information; for example, Esfahani used short-sequence ctDNA to assess the response of NSCLC patients to immunotherapy [180]. ...
Cancer ranks among the most lethal diseases worldwide. Tissue biopsy is currently the primary method for the diagnosis and biological analysis of various solid tumors. However, this method has some disadvantages related to insufficient tissue specimen collection and intratumoral heterogeneity. Liquid biopsy is a noninvasive approach for identifying cancer-related biomarkers in peripheral blood, which allows for repetitive sampling across multiple time points. In the field of liquid biopsy, representative biomarkers include circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and exosomes. Many studies have evaluated the prognostic and predictive roles of CTCs and ctDNA in various solid tumors. Although these studies have limitations, the results of most studies appear to consistently demonstrate the correlations of high CTC counts and ctDNA mutations with lower survival rates in cancer patients. Similarly, a reduction in CTC counts throughout therapy may be a potential prognostic indicator related to treatment response in advanced cancer patients. Moreover, the biochemical characteristics of CTCs and ctDNA can provide information about tumor biology as well as resistance mechanisms against targeted therapy. This review discusses the current clinical applications of liquid biopsy in cancer patients, emphasizing its possible utility in outcome prediction and treatment decision-making.
... The development of standardized reference materials and quality control methods will improve result reproducibility across laboratories [131]. Novel sample preparation techniques are enhancing the recovery of rare molecular species [132]. Advanced multiplexing approaches enable simultaneous analysis of multiple biomarker types from limited sample volumes [133]. ...
Objectives: Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer globally, with HPV-positive cases emerging as a distinct subtype with unique clinical and molecular characteristics. Current diagnostic methods, including tissue biopsy and imaging, face limitations in terms of invasiveness, static disease assessment, and difficulty in distinguishing recurrence from treatment-related changes. This review aimed to assess the potential of liquid biopsy as a minimally invasive tool for the diagnosis, treatment monitoring, and surveillance of HPV-associated HNSCC. Methods: This systematic review analyzed literature from PubMed/MEDLINE, Embase, and Web of Science, focusing on original research and reviews related to liquid biopsy applications in HPV-positive HNSCC. Included studies were evaluated based on the robustness of the study design, clinical relevance, and analytical performance of liquid biopsy technologies. Biomarker types, detection methods, and implementation strategies were assessed to identify advancements and challenges in this field. Results: Liquid biopsy technologies, including circulating HPV DNA, ctDNA, and extracellular vesicles, demonstrated high sensitivity (90–95%) and specificity (>98%) in detecting HPV-positive HNSCC. These methods enabled real-time monitoring of tumor dynamics, early detection of recurrence, and insights into treatment resistance. Longitudinal analysis revealed that biomarker clearance during treatment correlates strongly with patient outcomes. Conclusions: Liquid biopsy is a transformative diagnostic and monitoring tool for HPV-associated HNSCC, offering minimally invasive, real-time insights into tumor biology. While challenges remain in standardization and clinical implementation, ongoing research and technological innovations hold promise for integrating liquid biopsy into personalized cancer care, ultimately improving patient outcomes.
... Additionally, the fragmentation pattern of cfDNA may allow for the distinction of cfDNA from different origins (Ding and Lo 2022). Studies have reported that circulating tumor-derived cfDNA molecules have a shorter size distribution compared to the background cfDNA, which is primarily of hematopoietic origin, suggesting that a fragment size-based approach could enhance the accuracy of data interpretation (Mouliere et al. 2018). ...
Neurodegenerative disorders, including Alzheimer’s disease (AD), Parkinson’s disease (PD), multiple sclerosis (MS), and amyotrophic lateral sclerosis (ALS), are characterized by the progressive and gradual degeneration of neurons. The prevalence and rates of these disorders rise significantly with age. As life spans continue to increase in many countries, the number of cases is expected to grow in the foreseeable future. Early and precise diagnosis, along with appropriate surveillance, continues to pose a challenge. The high heterogeneity of neurodegenerative diseases calls for more accurate and definitive biomarkers to improve clinical therapy. Cell-free DNA (cfDNA), including fragmented DNA released into bodily fluids via apoptosis, necrosis, or active secretion, has emerged as a promising non-invasive diagnostic tool for various disorders including neurodegenerative diseases. cfDNA can serve as an indicator of ongoing cellular damage and mortality, including neuronal loss, and may provide valuable insights into disease processes, progression, and therapeutic responses. This review will first cover the key aspects of cfDNA and then examine recent advances in its potential use as a biomarker for neurodegenerative disorders.
... ctDNA carries genetic information from tumors, including alterations such as point mutations, copy number variations, deletions, and methylation patterns. 57 Consequently, the detection of ctDNA has emerged as a crucial tool in precision oncology, demonstrating substantial potential particularly in driving gene mutation detection, monitoring resistance mutations, and assessing tumor burden. ...
Lung cancer is one of the most lethal malignancies worldwide, making early diagnosis and targeted treatment crucial for improving patient outcomes. Liquid biopsy, a rapidly advancing non-invasive diagnostic tool, has shown significant potential in lung cancer management through dynamic monitoring. This review explores the integration of liquid biopsy with traditional diagnostic techniques in lung cancer management. We first discuss the essential roles of traditional approaches, such as imaging and tissue biopsy, and then examine the concepts of liquid biopsy, emphasizing its unique advantages in early detection, treatment monitoring, and prognosis. Finally, we propose strategies for integrating liquid biopsy with traditional diagnostics, offering multimodal framework to enhance precision medicine in lung cancer.
... Low-pass whole-genome sequencing (LP-WGS) offers another cost-effective and broadly applicable approach for estimation of TF. Early studies used read count based genome-wide z-scores as an estimation of TF by comparing global copy number alterations in a given plasma sample to a panel of normal healthy donors (plasma-Seq) [60] or scores like the trimmed median absolute deviation (tMAD) from the copy number neutral state [61] as TF surrogates. More recently, computational models such as ichorCNA [16] and ACE [62] considering tumour purity, ploidy, and SCNA were developed to estimate ctDNA TF. ...
Circulating tumour DNA (ctDNA) represents an increasingly important biomarker for the screening, diagnosis and management of patients in clinical practice in advanced/metastatic disease across multiple cancer types. In this context, ctDNA-based comprehensive genomic profiling is now available for patient management decisions, and several ctDNA-based companion diagnostic assays have been approved by regulatory agencies. However, although the assessment of ctDNA levels in Phase II-III drug development is now gathering momentum, it remains somewhat surprisingly limited in the early Phase I phases in light of the potential opportunities provided by such analysis. In this perspective review, we investigate the potential and hurdles of applying ctDNA testing for the inclusion and monitoring of patients in phase 1 clinical trials. This will enable more informed decisions regarding patient inclusion, dose optimization, and proof-of-mechanism of drug biological activity and molecular response, thereby supporting the evolving oncology drug development paradigm. Furthermore, we will highlight the use of cost-efficient, agnostic genome-wide techniques (such as low-pass whole genome sequencing and fragmentomics) and methylation-based methods to facilitate a more systematic integration of ctDNA in early clinical trial settings.
... The size distribution of cfDNA is an important biological characteristic for its clinical application, and fragment size can be obtained through single-base resolution sequencing. Existing studies have confirmed that tumor-derived cfDNA molecules in the plasma of cancer patients are usually small [18,19], and short genes typically prioritize tumor-related copy number aberrations. The size characteristics of tumor-derived cfDNA in the plasma of cancer patients can be used to identify tumor DNA fragments and improve cancer detection [20]. ...
Background
Currently, due to the invasive nature of colonoscopy and the associated pain, people avoid undergoing the procedure, making it difficult to detect the majority of potential early stage colorectal carcinoma/precancerous lesions or advanced adenoma. Advanced colorectal adenoma is the main precursor to the development of colorectal carcinoma. Therefore, improving advanced colorectal adenoma detection rate can significantly decrease the development and morbidity of colorectal carcinoma. Accordingly, a non-invasive method to screen high-risk people for colonoscopy in clinical practice is urgently needed.
Main text
With the development of medical technology, screening methods for colorectal carcinoma are emerging rapidly, and diverse non-invasive methods are being developed. Cell-free DNA (cfDNA), commonly referred to as liquid biopsy, has promising application prospects as a minimally invasive strategy for early screening of colorectal cancer. CfDNA has already been applied in the field of prenatal diagnosis, advanced carcinoma, and organ transplantation, and the application cfDNA in advanced colorectal adenoma is at the cutting-edge of current research. Thus, this review summarizes the progress in research on different biological characteristics of cfDNA and its utility in the screening of advanced colorectal adenoma, including sizes of cfDNA molecules, end signature of cfDNA (preferred ends, end motifs, jagged ends), nucleosomal footprints, cfDNA topology, cfDNA methylation, and cfDNA integrity.
Conclusions
We hope that this review will advance this promising research field.
... Autoencoder (AE) [10,22] 6. Stacked Sparse Auto Encoder(SSAE) [5] 7. Stacked Denoising Auto Encoder(SDAE) [6,11,28] 8. Long Short Term Memory (LSTM) [13] 9. Feedforward Neural Network [15,23] 10. ...
... Nesmie sa zabudnúť, že je nutné získať dostatočné množstvo tkaniva k sekvenovaniu a tvorbe sond. dorové DNA fragmenty sú kratšie ako u zdravých buniek [23]. Na vyšetrovanie sa používajú vzorky plazmy pretože sérum obsahuje vysoké množstvo DNA kvôli lýze leukocytov ku ktorej dochádza počas zrážania, táto DNA narúša výsledky vyšetrenia [24]. ...
... It is relatively easy to extract and can be quantified accurately using the appropriate techniques, even during the early stages of cancer [97,98]. Typically, ctDNA is more fragmented than extracellular DNA (with fragments around 90-150 bp in length) [99], and its half-life in peripheral blood ranges from 15 min to several hours, making it an ideal biomarker for real-time monitoring of tumor dynamics [97]. ctDNA levels had been investigated as a biomarker to predict radiological response in patients with SDCs from the CABO-ASAP trial. ...
Background: Salivary gland cancers (SGCs) are a rare and heterogeneous group of malignancies, accounting for approximately 5% of head and neck cancers. Despite their rarity, advances in molecular profiling have revealed a variety of genetic and molecular pathways, many of which are potentially actionable with targeted therapies. Methods: We reviewed the current literature involving the molecular landscape of SGCs, encompassing the diagnostic and prognostic value of tissue and liquid biomarkers and the potential therapeutic targets across various histological subtypes. Results: Our review highlights key molecular diagnostic findings such as the CRTC1-MAML2 fusion in mucoepidermoid carcinoma and MYB-NFIB rearrangements in adenoid cystic carcinoma, but also targetable alterations such as HER2 and AR positivity in salivary duct carcinoma and ETV6-NTRK3 fusion in secretory carcinoma. Liquid biopsy (both blood- or salivary-based), including circulating tumor DNA, circulating tumor cells, and miRNAs, offers novel, noninvasive approaches for disease monitoring and personalized treatment. Emerging therapies such as HER2 inhibitors, androgen deprivation therapy, and TRK inhibitors underscore the shift towards precision oncology in managing these malignancies. Conclusions: Despite promising advances, challenges remain due to the rarity and phenotypic heterogeneity of SGCs, emphasizing the need for molecularly stratified clinical trials. This review presents an overview of tissue and liquid biomarkers, focusing on molecular targets and therapeutic innovations that lay the foundation for improved diagnostic and treatment strategies for SGCs.
... This was conducted as part of the CIRCULATE-Japan GALAXY observational study, providing evidence for the necessity of monitoring ctDNA to assess recurrence risk [196]. Despite the cfDNA fragment length peaking at 167 bp, longer fragments were also detected depending on the harboring nucleosome [197,198]. In addition to the next-generation sequencing, long read sequencing has revealed over 1 kb cfDNA in plasma, which contained a high number of CpG sites to analyze methylation patterns as well as a large portion of informative SNP sites [199]. ...
Delving into cancer dormancy has been an inherent task that may drive the lethal recurrence of cancer after primary tumor relief. Cells in quiescence can survive for a short or long term in silence, may undergo genetic or epigenetic changes, and can initiate relapse through certain contextual cues. The state of dormancy can be induced by multiple conditions including cancer drug treatment, in turn, undergoes a life cycle that generally occurs through dissemination, invasion, intravasation, circulation, immune evasion, extravasation, and colonization. Throughout this cascade, a cellular machinery governs the fate of individual cells, largely affected by gene regulation. Despite its significance, a precise view of cancer dormancy is yet hampered. Revolutionizing advanced single cell and long read sequencing through analysis methodologies and artificial intelligence, the most recent stage in the research tool progress, is expected to provide a holistic view of the diverse aspects of cancer dormancy.
... Exosomes, CEC (circulating endothelial cells) and proteins are biomarkers present in the blood that also serve as common targets for LB Page 3 of 18 Sheriff et al. J Exp Clin Cancer Res (2025) 44:50 fragments released by tumour cells, that may be undergoing apoptosis or necrosis or may be actively secreted [21,22]. Tumour-derived extracellular vesicles are small vesicles produced by tumour cells to transport nucleic acids and proteins that reflect tumour cellular processes and the tumour microenvironment [23,24]. ...
Background
Liquid biopsy (LB) offers a promising, minimally invasive alternative to traditional tissue biopsies in cancer care, enabling real-time monitoring and personalized treatment. Despite its potential, the routine implementation of LB in clinical practice faces significant challenges. This scoping review examines the barriers and facilitators influencing the implementation of liquid biopsies into standard cancer care.
Methods
Four academic databases (PubMed, Scopus, Embase, and Web of Science) were systematically searched without language restrictions. We included peer-reviewed articles that were published between January 2019 and March 2024 that focused on the implementation of LB in cancer care or described barriers and facilitators to its implementation. Data relevant to the review objective, including key article characteristics; barriers and facilitators of implementation; and recommendations for advancement or optimisation; were extracted and analysed using thematic and visual network analyses.
Results
The majority of the included articles were narrative review articles (84%), with most from China (24.2%) and the United States (20%). Thematic analysis identified four main categories and their associated barriers and facilitators to the implementation of LB in cancer care: (1) Laboratory and personnel requirements; (2) Disease specificity; (3) Biomarker-based liquid biopsy; and (4) Policy and regulation. The majority of barriers identified were concentrated in the pre-analytical phase, highlighting the lack of standardization in LB technologies and outcomes.
Conclusions
Through a thematic analysis of the barriers and facilitators to LB implementation, we present an integrated tool designed to encourage the standardization of testing methods for clinical practice guidelines in the field.
... On the other hand, ctDNA, beyond its low level overall, is often more fragmented than cfDNA, complicating its analysis and it has got a short half-life [26]. After sampling, environmental factors may accelerate its degradation, demanding controlled delivery conditions and quick isolation from the matrix. ...
The aim of the Ph.D. project has been focused on uncovering through a blood-based liquid biopsy approach novel extracellular vesicle biomarkers to translate into clinical routine as quicker, innovative and sensitive tools. The proposed signatures have been proved to be reliable enough for usage by themselves or in combination with parameters already integrated in clinical practice. Such an approach has been tested in two different experimental settings, displaying feasibility and robustness. Firstly, it has shown to discriminate prostate tumour patients from those ones affected by hyperplasia in order to do early diagnosis and, thereby, address patients towards different medical care strategies. Secondly, regarding patient management in the follow-up phase, not only it has pinpointed those individuals who will suffer for colorectal cancer recurrence, but it has also discriminated patients for their mismatch repair system status, selecting best candidates for the immunotherapy application. The novelty of this approach consists in usage extracellular vesicles, particularly proteins they deliver, as novel information sources. In addition, an emerging imaging technology, direct stochastic optical reconstruction microscopy (dSTORM), used only for research so far, has been employed, suggesting and encouraging its translatability in clinic as well. Lastly the low volume of starting required samples makes such an approach attractive, mainly in order to avoid repeated sampling which would cause patients’ discomfort.
... influenced by the stage of cancer and demonstrating a tradeoff between sensitivity and specificity. In a related study, Mouliere et al. [92] reported on a random forest classifier that utilizes features based on cfDNA fragment sizes to predict ctDNA presence with significant accuracy across multiple cancer types (AUC = 0.91-0.99). Cohen et al. [93] developed CancerSEEK, an end-to-end blood test that detects early-stage cancer and identifies one of eight specific cancer types from circulating tumor DNA (ctDNA). ...
Radioimmunotherapy (RIT) is a novel cancer treatment that combines radiotherapy and immunotherapy to precisely target tumor antigens using monoclonal antibodies conjugated with radioactive isotopes. This approach offers personalized, systemic, and durable treatment, making it effective in cancers resistant to conventional therapies. Advances in artificial intelligence (AI) present opportunities to enhance RIT by improving precision, efficiency, and personalization. AI plays a critical role in patient selection, treatment planning, dosimetry, and response assessment, while also contributing to drug design and tumor classification. This review explores the integration of AI into RIT, emphasizing its potential to optimize the entire treatment process and advance personalized cancer care.
... To date, population screening in ovarian cancer has not been effective or validated. Efforts are made to monitoring ovarian cancer for diagnostic and prognostic purposes using ctDNA [22][23][24] . In many ovarian cancer studies, the performance of ctDNA platforms is being evaluated in comparison to the levels of the standard serum marker, CA-125, which has played a chief role in screening, detecting, and managing ovarian cancer over the past four decades 25 . ...
The distinctive characteristics of an individual’s T cell receptor repertoire are crucial in recognizing and responding to a diverse array of antigens, contributing to immune specificity and adaptability. The repertoire, famously vast due to a series of cellular mechanisms, can be quantified using repertoire sequencing. In this study, we sampled the repertoire of 85 women: ovarian cancer patients (OC) and healthy donors (HD), generating a dataset of T cell clones and their abundance. For the alpha chain we obtained 6.4·10⁶ reads, with an average of 75936 clones per sample, and an average of 30607 clonotypes per sample. For the beta chain we obtained 13.6·10⁶ reads, with an average of 160400 clones per sample, and an average of 70071 clonotypes per sample. The changes in dynamics of the repertoire can be observed in response to disease, with specific clones undergoing clonal expansion and contraction. The data provided here offers a unique view of immune system behavior in health and disease and can be used to stratify OC and HD.
Background/Aims: Circulating tumor DNA (ctDNA) is becoming a valuable cancer biomarker for clinical decision-making. Nevertheless, the lack of quality control materials to assess the reliability of test results remains a challenge. This study aimed to establish digital PCR (dPCR) assays for detecting TP53 variants (R175H and R248W) and develop a preparation method for ctDNA reference materials to improve detection reliability. Methods: Two dPCR assays targeting TP53-R175H and TP53-R248W variants were developed and validated for repeatability, sensitivity, and linearity. Additionally, a ctDNA reference material preparation protocol was developed by digesting nucleosomes from cultured cancer cell lines with micrococcal nuclease, followed by magnetic beads purification. The size distribution and quality of the generated ctDNA fragments was analyzed, and the developed dPCR assays were applied to detect the variants in the ctDNA samples. Results: The dPCR assays demonstrated high repeatability (RSD of 0.16% to 7.65%) and excellent linearity (R2 values of 1.0000 and 0.9981) across variant allele frequencies of 50%–0.1%. The limits of detection (LOD) and quantification (LOQ) were 0.143% (R175H) and 0.092% (R248W). The ctDNA reference materials exhibited single dominant peaks at 128 bp (R175H) and 143 bp (R248W). The dPCR assays successfully detected variants in these reference materials, confirming their applicability for ctDNA samples. onclusion: Firstly, accurate measurement procedures for TP53-R175H and TP53-R248W variants based on dPCR were established in this study. Furthermore, a protocol for preparing ctDNA reference material was established here. By digesting nucleosomal DNA derived from cancer cell lines with micrococcal nuclease, this method can closely mimic the properties of clinical ctDNA. The dPCR method and ctDNA reference material preparation approach established here could be used in ctDNA detection and for improving its reliability.
Early detection of lung cancer significantly improves survival, yet current screening methods have limitations. This study aimed to identify a robust panel of plasma metabolites for early-stage non-small cell lung cancer (NSCLC) diagnosis using a large, clinically diverse patient cohort. A total of 680 archived plasma samples from biopsy-confirmed NSCLC patients and controls (including healthy individuals and patients with non-cancerous lung diseases) were analyzed using targeted, quantitative mass spectrometry-based metabolomics and used as the discovery cohort. An independent set of 216 plasma samples served as the validation cohort. Logistic regression (LR) models developed from the discovery set using ten metabolites achieved area under the receiver-operating characteristic curve (AUROC) values of 93.63%, 93.74%, and 93.91% for distinguishing all-stage, stage I–II, and stage I NSCLC patients from controls, respectively. Incorporating smoking history further improved model performance. The validation cohort confirmed the model’s robustness, demonstrating high sensitivity and specificity for early-stage detection. These results support the potential of metabolomic biomarkers as a minimally invasive, accurate tool for early NSCLC diagnosis. This approach may complement current screening methods, enabling earlier intervention and improved patient outcomes. Further studies are warranted to validate these findings in more diverse populations and real-world clinical settings.
Purpose of Review
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, with rising incidence and mortality. Early-stage HCC is often asymptomatic, and the lack of reliable early diagnostic markers leads to late-stage diagnosis with limited treatment options. Current treatment relies on tumour staging and patient status, but accurate staging requires invasive procedures that fail to capture tumour heterogeneity and progression. There is an urgent need for less invasive diagnostic strategies, such as liquid biopsy technologies, which allow for repeated sampling and real-time analysis of tumour dynamics. Liquid biopsies, including circulating tumour cells (CTCs) and circulating tumour DNA (ctDNA), offer the potential to monitor recurrence, metastasis, and treatment responses, potentially transforming HCC clinical management by enabling earlier intervention and personalised treatment strategies.
Recent Findings
Recent studies emphasise the potential of ctDNA as a non-invasive biomarker by targeting DNA methylation for early HCC detection, enabling timely intervention and personalised treatment to improve patient outcomes. Comparative analyses have shown that ctDNA mutation testing outperforms alpha-fetoprotein (AFP), with a sensitivity of 85% and a specificity of 92%, compared to 60% sensitivity and 80% specificity for AFP. Additionally, profiling the ctDNA mutation landscape of 100 HCC patients has identified recurrent mutations in genes such as TP53, CTNNB1, and AXIN1.
Summary
ctDNA appears to be a promising non-invasive biomarker in the clinical management of HCC patients, with the sensitivity and specificity improving by 41.67% and 15% respectively. The ctDNA mutations, particularly those targeting DNA methylation, highlight great potential for precision medicine, critical for early diagnosis and prognosis of HCC.
Liquid biopsies, indicating the sampling of body fluids rather than solid-tissue biopsies, have the potential to revolutionize cancer care through personalized, noninvasive disease detection and monitoring. Circulating tumour DNA (ctDNA) and circulating tumour cells (CTCs) are promising blood-based biomarkers in bladder cancer. Results from several studies have shown the clinical potential of ctDNA and CTCs in bladder cancer for prognostication, treatment-response monitoring, and early detection of minimal residual disease and disease recurrence. Following successful clinical trial evaluation, assessment of ctDNA and CTCs holds the potential to transform the therapeutic pathway for patients with bladder cancer - potentially in combination with the analysis of urinary tumour DNA - through tailored treatment guidance and optimized disease surveillance.
Multiple myeloma (MM) remains an incurable disease primarily due to the emergence of drug resistance, and the underlying mechanisms remain unclear. Extrachromosomal circular DNAs (eccDNAs) are prevalent in cancer genomes of both coding and non‐coding regions. However, the role of non‐coding eccDNA regions that serve as enhancers has been largely overlooked. Here, genome‐wide profiling of serum eccDNAs from donors and MM patients who responded well or poorly to bortezomib‐lenalidomide‐dexamethasone (VRd) therapy is characterized. A high copy number of eccDNA ANKRD28 (eccANKRD28) predicts poor therapy response and prognosis but enhanced transcriptional activity. Established VRd‐resistant MM cell lines exhibit a higher abundance of eccANKRD28, and CRISPR/Cas9‐mediated elevation of eccANKRD28 desensitizes bortezomib and lenalidomide treatment both in vitro and in vivo. Integrated multi‐omics analysis (H3K27ac ChIP‐seq, scRNA‐seq, scATAC‐seq, CUT&Tag, et al.) identifies eccANKRD28 as an active enhancer involved in drug resistance driven by the key transcription factor, POU class 2 homeobox 2 (POU2F2). POU2F2 interacts with sequence‐specific eccANKRD28 as well as RUNX1 and RUNX2 motifs to form the protein complex, which activates the promoter of oncogenes, including IRF4, JUNB, IKZF3, RUNX3, and BCL2. This study elucidates the potential transcriptional network of enhancer eccANKRD28 in MM drug resistance from a previously unrecognized epigenetic perspective.
Early detection of lung cancer is important for improving patient survival rates. Liquid biopsy using whole-genome sequencing of cell-free DNA (cfDNA) offers a promising avenue for lung cancer screening, providing a potential alternative or complementary approach to current screening modalities. Here, we aimed to develop and validate an approach by integrating fragment and genomic features of cfDNA to enhance lung cancer detection accuracy across diverse populations. Deep learning–based classifiers were trained using comprehensive cfDNA fragmentomic features from participants in multi-institutional studies, including a Korean discovery dataset (218 patients with lung cancer and 2,559 controls), a Korean validation dataset (111 patients with lung cancer and 1,136 controls), and an independent Caucasian validation cohort (50 patients with lung cancer and 50 controls). In the discovery dataset, classifiers using fragment end motif by size, a feature that captures both fragment end motif and size profiles, outperformed standalone fragment end motif and fragment size classifiers, achieving an area under the curve (AUC) of 0.917. The ensemble classifier integrating fragment end motif by size and genomic coverage achieved an improved performance, with an AUC of 0.937. This performance extended to the Korean validation dataset and demonstrated ethnic generalizability in the Caucasian validation cohort. Overall, the development of a deep learning–based classifier integrating cfDNA fragmentomic and genomic features in this study highlights the potential for accurate lung cancer detection across diverse populations.
Significance: Evaluating fragment-based features and genomic coverage in cell-free DNA offers an accurate lung cancer screening method, promising improvements in early cancer detection and addressing challenges associated with current screening methods.
Background
Early-onset gastric cancer (EOGC) is a lethal malignancy. It differs from late-onset gastric cancer (LOGC) in clinical and molecular characteristics. The current strategies for EOGC detection have certain limitations in diagnostic performance due to the rising trend in EOGC.
Objective
We developed a liquid biopsy signature for EOGC detection.
Design
We use a systematic discovery approach by analysing genome-wide transcriptomic profiling data from EOGC (n=43), LOGC (n=31) and age-matched non-disease controls (n=37) tissue samples. An extracellular vesicle-derived long non-coding RNA (EV-lncRNA) signature was identified in blood samples from a training cohort (n=299), and subsequently confirmed by qPCR in two external validation cohorts (n=462 and n=438), a preoperative/postoperative cohort (n=66) and a gastrointestinal tumour cohort (n=225).
Results
A three EV-lncRNA (NALT1, PTENP1 and HOTTIP) liquid biopsy signature was developed for EOGC detection with an area under the receiver operating characteristic curve (AUROC) of 0.924 (95% CI 0.889 to 0.953). This EV-lncRNA signature provided robust diagnostic performance in two external validation cohorts (Xi’an cohort: AUROC, 0.911; Beijing cohort: AUROC, 0.9323). Furthermore, the EV-lncRNA signature reliably identified resectable stage EOGC patients (stage I/II) and demonstrated better diagnostic performance than traditional GC-related biomarkers in distinguishing early-stage EOGC (stage I) from precancerous lesions. The low levels of this biomarker in postsurgery and other gastrointestinal tumour plasma samples indicated its GC specificity.
Conclusions
The newly developed EV-lncRNA signature effectively identified EOGC patients at a resectable stage with enhanced precision, thereby improving the prognosis of patients who would have otherwise missed the curative treatment window.
Shallow whole-genome sequencing (sWGS) offers a cost-effective approach to detect copy number alterations (CNAs). However, there remains a gap for a standardized workflow specifically designed for sWGS analysis. To address this need, in this work we present SAMURAI, a bioinformatics pipeline specifically designed for analyzing CNAs from sWGS data in a standardized and reproducible manner. SAMURAI is built using established community standards, ensuring portability, scalability, and reproducibility. The pipeline features a modular design with independent blocks for data preprocessing, copy number analysis, and customized reporting. Users can select workflows tailored for either solid or liquid biopsy analysis (e.g. circulating tumor DNA), with specific tools integrated for each sample type. The final report generated by SAMURAI provides detailed results to facilitate data interpretation and potential downstream analyses. To demonstrate its robustness, SAMURAI was validated using simulated and real-world data sets. The pipeline achieved high concordance with ground truth data and maintained consistent performance across various scenarios. By promoting standardization and offering a versatile workflow, SAMURAI empowers researchers in diverse environments to reliably analyze CNAs from sWGS data. This, in turn, holds promise for advancements in precision medicine.
Early detection of cancer is a significant unmet clinical need. Improved technical ability to detect circulating tumor-derived DNA (ctDNA) in the cell-free DNA (cfDNA) component of blood plasma via next-generation sequencing and established correlations between ctDNA load and tumor burden in cancer patients have spurred excitement about the possibilities of detecting cancer early by performing ctDNA mutation detection.
We reanalyze published data on the expected ctDNA allele fraction in early-stage cancer and the population statistics of cfDNA concentration to show that under conservative technical assumptions, high-sensitivity cancer detection by ctDNA mutation detection will require either more blood volume (150-300mL) than practical for a routine screen or variant filtering that may be impossible given our knowledge of cancer evolution, and will likely remain out of economic reach for routine population screening without multiple-order-of-magnitude decreases in sequencing cost. Instead, new approaches that integrate ctDNA mutations with multiple other blood-based analytes (such as exosomes, circulating tumor cells, ctDNA epigenetics, metabolites) as well as integration of these signals over time for each individual may be needed.
The genomic complexity of profound copy number aberrations has prevented effective molecular stratification of ovarian cancers. Here, to decode this complexity, we derived copy number signatures from shallow whole-genome sequencing of 117 high-grade serous ovarian cancer (HGSOC) cases, which were validated on 527 independent cases. We show that HGSOC comprises a continuum of genomes shaped by multiple mutational processes that result in known patterns of genomic aberration. Copy number signature exposures at diagnosis predict both overall survival and the probability of platinum-resistant relapse. Measurement of signature exposures provides a rational framework to choose combination treatments that target multiple mutational processes.
Whole-exome sequencing of cell-free DNA (cfDNA) could enable comprehensive profiling of tumors from blood but the genome-wide concordance between cfDNA and tumor biopsies is uncertain. Here we report ichorCNA, software that quantifies tumor content in cfDNA from 0.1× coverage whole-genome sequencing data without prior knowledge of tumor mutations. We apply ichorCNA to 1439 blood samples from 520 patients with metastatic prostate or breast cancers. In the earliest tested sample for each patient, 34% of patients have ≥10% tumor-derived cfDNA, sufficient for standard coverage whole-exome sequencing. Using whole-exome sequencing, we validate the concordance of clonal somatic mutations (88%), copy number alterations (80%), mutational signatures, and neoantigens between cfDNA and matched tumor biopsies from 41 patients with ≥10% cfDNA tumor content. In summary, we provide methods to identify patients eligible for comprehensive cfDNA profiling, revealing its applicability to many patients, and demonstrate high concordance of cfDNA and metastatic tumor whole-exome sequencing.
Genomic complexity from profound copy-number aberration has prevented effective molecular stratification of ovarian and other cancers. Here we present a method for copy-number signature identification that decodes this complexity. We derived eight signatures using 117 shallow whole-genome sequenced high-grade serous ovarian cancer cases, which were validated on a further 497 cases. Mutational processes underlying the copy-number signatures were identified, including breakage-fusion-bridge cycles, homologous recombination deficiency and whole-genome duplication. We show that most tumours are heterogeneous and harbour multiple signature exposures. We also demonstrate that copy number signatures predict overall survival and changes in signature exposure observed in response to chemotherapy suggest potential treatment strategies.
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.
The early detection of relapse following primary surgery for non-small cell lung cancer and the characterization of emerging subclones seeding metastatic sites might offer new therapeutic approaches to limit tumor recurrence. The potential to non-invasively track tumor evolutionary dynamics in ctDNA of early-stage lung cancer is not established. Here we conduct a tumour-specific phylogenetic approach to ctDNA profiling in the first 100 TRACERx (TRAcking non-small cell lung Cancer Evolution through therapy (Rx)) study participants, including one patient co-recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release and perform tumor volume limit of detection analyses. Through blinded profiling of post-operative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients destined to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastases, providing a new approach for ctDNA driven therapeutic studies.
Background
Circulating tumour DNA (ctDNA) carrying tumour-specific sequence alterations may provide a minimally invasive means to dynamically assess tumour burden and response to treatment in cancer patients. Somatic TP53 mutations are a defining feature of high-grade serous ovarian carcinoma (HGSOC). We tested whether these mutations could be used as personalised markers to monitor tumour burden and early changes as a predictor of response and time to progression (TTP).
Methods and Findings
We performed a retrospective analysis of serial plasma samples collected during routine clinical visits from 40 patients with HGSOC undergoing heterogeneous standard of care treatment. Patient-specific TP53 assays were developed for 31 unique mutations identified in formalin-fixed paraffin-embedded tumour DNA from these patients. These assays were used to quantify ctDNA in 318 plasma samples using microfluidic digital PCR. The TP53 mutant allele fraction (TP53MAF) was compared to serum CA-125, the current gold-standard response marker for HGSOC in blood, as well as to disease volume on computed tomography scans by volumetric analysis. Changes after one cycle of treatment were compared with TTP.
The median TP53MAF prior to treatment in 51 relapsed treatment courses was 8% (interquartile range [IQR] 1.2%–22%) compared to 0.7% (IQR 0.3%–2.0%) for seven untreated newly diagnosed stage IIIC/IV patients. TP53MAF correlated with volumetric measurements (Pearson r = 0.59, p < 0.001), and this correlation improved when patients with ascites were excluded (r = 0.82). The ratio of TP53MAF to volume of disease was higher in relapsed patients (0.04% per cm³) than in untreated patients (0.0008% per cm³, p = 0.004). In nearly all relapsed patients with disease volume > 32 cm³, ctDNA was detected at ≥20 amplifiable copies per millilitre of plasma. In 49 treatment courses for relapsed disease, pre-treatment TP53MAF concentration, but not CA-125, was associated with TTP. Response to chemotherapy was seen earlier with ctDNA, with a median time to nadir of 37 d (IQR 28–54) compared with a median time to nadir of 84 d (IQR 42–116) for CA-125. In 32 relapsed treatment courses evaluable for response after one cycle of chemotherapy, a decrease in TP53MAF of >60% was an independent predictor of TTP in multivariable analysis (hazard ratio 0.22, 95% CI 0.07–0.67, p = 0.008). Conversely, a decrease in TP53MAF of ≤60% was associated with poor response and identified cases with TTP < 6 mo with 71% sensitivity (95% CI 42%–92%) and 88% specificity (95% CI 64%–99%). Specificity was improved when patients with recent drainage of ascites were excluded. Ascites drainage led to a reduction of TP53MAF concentration. The limitations of this study include retrospective design, small sample size, and heterogeneity of treatment within the cohort.
Conclusions
In this retrospective study, we demonstrated that ctDNA is correlated with volume of disease at the start of treatment in women with HGSOC and that a decrease of ≤60% in TP53MAF after one cycle of chemotherapy was associated with shorter TTP. These results provide evidence that ctDNA has the potential to be a highly specific early molecular response marker in HGSOC and warrants further investigation in larger cohorts receiving uniform treatment.
Long-lasting success in lung cancer therapy using tyrosine kinase inhibitors (TKIs) is rare since the tumors develop resistance due to the occurrence of molecularly altered subclones. The aim of this study was to monitor tumors over time based on the quantity of mutant plasma DNA and to identify early indications for therapy response and tumor progression. Serial plasma samples from lung adenocarcinoma patients treated with TKIs were used to quantify EGFR and KRAS mutations in circulating DNA by digital PCR. Mutant DNA levels were compared with the courses of responses to treatment with TKIs, conventional chemotherapy, radiotherapy, or combinations thereof. Variations in plasma DNA mutation levels over time were found in 15 patients. We categorize three major courses: First, signs of therapy response are associated with a fast clearing of plasma DNA mutations within a few days. Second, periods of stable disease are accompanied by either absence of mutations or fluctuation at low levels. Finally, dramatic increase of mutational load is followed by rapid tumor progression and poor patient survival. In summary, the serial assessment of EGFR mutations in the plasma of NSCLC patients allows conclusions about controlled disease and tumor progression earlier than currently available methods.
Malignant tumors shed DNA into the circulation. The transient half-life of circulating tumor DNA (ctDNA) may afford the opportunity to diagnose, monitor recurrence, and evaluate response to therapy solely through a non-invasive blood draw. However, detecting ctDNA against the normally occurring background of cell-free DNA derived from healthy cells has proven challenging, particularly in non-metastatic solid tumors. In this study, distinct differences in fragment length size between ctDNAs and normal cell-free DNA are defined. Human ctDNA in rat plasma derived from human glioblastoma multiforme stem-like cells in the rat brain and human hepatocellular carcinoma in the rat flank were found to have a shorter principal fragment length than the background rat cell-free DNA (134-144 bp vs. 167 bp, respectively). Subsequently, a similar shift in the fragment length of ctDNA in humans with melanoma and lung cancer was identified compared to healthy controls. Comparison of fragment lengths from cell-free DNA between a melanoma patient and healthy controls found that the BRAF V600E mutant allele occurred more commonly at a shorter fragment length than the fragment length of the wild-type allele (132-145 bp vs. 165 bp, respectively). Moreover, size-selecting for shorter cell-free DNA fragment lengths substantially increased the EGFR T790M mutant allele frequency in human lung cancer. These findings provide compelling evidence that experimental or bioinformatic isolation of a specific subset of fragment lengths from cell-free DNA may improve detection of ctDNA.
While various clinical applications especially in oncology are now in progress such as diagnosis, prognosis, therapy monitoring, or patient follow-up, the determination of structural characteristics of cell-free circulating DNA (cirDNA) are still being researched. Nevertheless, some specific structures have been identified and cirDNA has been shown to be composed of many "kinds." This structural description goes hand-in-hand with the mechanisms of its origins such as apoptosis, necrosis, active release, phagocytosis, and exocytose. There are multiple structural forms of cirDNA depending upon the mechanism of release: particulate structures (exosomes, microparticles, apoptotic bodies) or macromolecular structures (nucleosomes, virtosomes/proteolipidonucleic acid complexes, DNA traps, links with serum proteins or to the cell-free membrane parts). In addition, cirDNA concerns both nuclear and/or mitochondrial DNA with both species exhibiting different structural characteristics that potentially reveal different forms of biological stability or diagnostic significance. This review focuses on the origins, structures and functional aspects that are paradoxically less well described in the literature while numerous reviews are directed to the clinical application of cirDNA. Differentiation of the various structures and better knowledge of the fate of cirDNA would considerably expand the diagnostic power of cirDNA analysis especially with regard to the patient follow-up enlarging the scope of personalized medicine. A better understanding of the subsequent fate of cirDNA would also help in deciphering its functional aspects such as their capacity for either genometastasis or their pro-inflammatory and immunological effects.
Circulating cell-free DNA (cfDNA) is emerging as a powerful monitoring tool in cancer, pregnancy and organ transplantation. Nucleosomal DNA, the predominant form of plasma cfDNA, can be adapted for sequencing via ligation of double-stranded DNA (dsDNA) adapters. dsDNA library preparations, however, are insensitive to ultrashort, degraded cfDNA. Drawing inspiration from advances in paleogenomics, we have applied a single-stranded DNA (ssDNA) library preparation method to sequencing of cfDNA in the plasma of lung transplant recipients (40 samples, six patients). We found that ssDNA library preparation yields a greater portion of sub-100 bp nuclear genomic cfDNA (p 10−5, Mann-Whitney U Test), and an increased relative abundance of mitochondrial (10.7x, p 10−5) and microbial cfDNA (71.3x, p 10−5). The higher yield of microbial sequences from this method increases the sensitivity of cfDNA-based monitoring for infections following transplantation. We detail the fragmentation pattern of mitochondrial, nuclear genomic and microbial cfDNA over a broad fragment length range. We report the observation of donor-specific mitochondrial cfDNA in the circulation of lung transplant recipients. A ssDNA library preparation method provides a more informative window into understudied forms of cfDNA, including mitochondrial and microbial derived cfDNA and short nuclear genomic cfDNA, while retaining information provided by standard dsDNA library preparation methods.
Objectives:
The aims of this study were to test the utility of benchtop NGS platforms for NIPT for trisomy 21 using previously published z score calculation methods and to optimize the sample preparation and data analysis with use of in silico and physical size selection methods.
Methods:
Samples from 130 pregnant women were analyzed by whole genome sequencing on benchtop NGS systems Ion Torrent PGM and MiSeq. The targeted yield of 3 million raw reads on each platform was used for z score calculation. The impact of in silico and physical size selection on analytical performance of the test was studied.
Results:
Using a z score value of 3 as the cut-off, 98.11% - 100% (104-106/106) specificity and 100% (24/24) sensitivity and 99.06% - 100% (105-106/106) specificity and 100% (24/24) sensitivity were observed for Ion Torrent PGM and MiSeq, respectively. After in silico based size selection both platforms reached 100% specificity and sensitivity. Following the physical size selection z scores of tested trisomic samples increased significantly-p = 0.0141 and p = 0.025 for Ion Torrent PGM and MiSeq, respectively.
Conclusions:
Noninvasive prenatal testing for chromosome 21 trisomy with the utilization of benchtop NGS systems led to results equivalent to previously published studies performed on high-to-ultrahigh throughput NGS systems. The in silico size selection led to higher specificity of the test. Physical size selection performed on isolated DNA led to significant increase in z scores. The observed results could represent a basis for increasing of cost effectiveness of the test and thus help with its penetration worldwide.
Tumor-educated blood platelets (TEPs) are implicated as central players in the systemic and local responses to tumor growth, thereby altering their RNA profile. We determined the diagnostic potential of TEPs by mRNA sequencing of 283 platelet samples. We distinguished 228 patients with localized and metastasized tumors from 55 healthy individuals with 96% accuracy. Across six different tumor types, the location of the primary tumor was correctly identified with 71% accuracy. Also, MET or HER2-positive, and mutant KRAS, EGFR, or PIK3CA tumors were accurately distinguished using surrogate TEP mRNA profiles. Our results indicate that blood platelets provide a valuable platform for pan-cancer, multiclass cancer, and companion diagnostics, possibly enabling clinical advances in blood-based "liquid biopsies".
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.
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.
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.
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.
Recent progress in the analysis of cell-free DNA fragments [cell-free circulating tumor DNA (ctDNA)] now allows monitoring of tumor genomes by noninvasive means. However, previous studies with plasma DNA from patients with cancer demonstrated highly variable allele frequencies of ctDNA. The comprehensive analysis of tumor genomes is greatly facilitated when plasma DNA has increased amounts of ctDNA. Therefore, a fast and cost-effective prescreening method to identify such plasma samples without previous knowledge about alterations in the respective tumor genome could assist in the selection of samples suitable for further extensive qualitative analysis.
We adapted the recently described Fast Aneuploidy Screening Test-Sequencing System (FAST-SeqS) method, which was originally established as a simple, effective, noninvasive screening method for fetal aneuploidy from maternal blood.
We show that our modified FAST-SeqS method (mFAST-SeqS) can be used as a prescreening tool for an estimation of ctDNA percentage. With a combined evaluation of genome-wide and chromosome arm-specific z-scores from dilution series with cell line DNA and by comparisons of plasma-Seq profiles with data from mFAST-SeqS, we established a detection limit of ≥10% mutant alleles. Plasma samples with an mFAST-SeqS z-score >5 showed results that were highly concordant with those of copy number profiles obtained from our previously described plasma-Seq approach.
Advantages of this approach include the speed and cost-effectiveness of the assay and that no prior knowledge about the genetic composition of tumor samples is necessary to identify plasma DNA samples with >10% ctDNA content.
© 2015 American Association for Clinical Chemistry.
Significance
We used massively parallel sequencing to study the size profiles of plasma DNA samples at single-base resolution and in a genome-wide manner. We used chromosome arm-level z -score analysis (CAZA) to identify tumor-derived plasma DNA for studying their specific size profiles. We showed that populations of aberrantly short and long DNA molecules existed in the plasma of patients with hepatocellular carcinoma. The short ones preferentially carried the tumor-associated copy number aberrations. We further showed that there were elevated amounts of mitochondrial DNA in the plasma of hepatocellular carcinoma patients. Such molecules were much shorter than the nuclear DNA in plasma. These findings have shed light on fundamental biological characteristics of plasma DNA and related diagnostic applications for cancer.
Background
Cancers arise from multiple acquired mutations, which presumably occur over many years. Early stages in cancer development might be present years before cancers become clinically apparent.
Methods
We analyzed data from whole-exome sequencing of DNA in peripheral-blood cells from 12,380 persons, unselected for cancer or hematologic phenotypes. We identified somatic mutations on the basis of unusual allelic fractions. We used data from Swedish national patient registers to follow health outcomes for 2 to 7 years after DNA sampling.
Results
Clonal hematopoiesis with somatic mutations was observed in 10% of persons older than 65 years of age but in only 1% of those younger than 50 years of age. Detectable clonal expansions most frequently involved somatic mutations in three genes (DNMT3A, ASXL1, and TET2) that have previously been implicated in hematologic cancers. Clonal hematopoiesis was a strong risk factor for subsequent hematologic cancer (hazard ratio, 12.9; 95% confidence interval, 5.8 to 28.7). Approximately 42% of hematologic cancers in this cohort arose in persons who had clonality at the time of DNA sampling, more than 6 months before a first diagnosis of cancer. Analysis of bone marrow–biopsy specimens obtained from two patients at the time of diagnosis of acute myeloid leukemia revealed that their cancers arose from the earlier clones.
Conclusions
Clonal hematopoiesis with somatic mutations is readily detected by means of DNA sequencing, is increasingly common as people age, and is associated with increased risks of hematologic cancer and death. A subset of the genes that are mutated in patients with myeloid cancers is frequently mutated in apparently healthy persons; these mutations may represent characteristic early events in the development of hematologic cancers. (Funded by the National Human Genome Research Institute and others.)
Detection of DNA copy number aberrations by shallow whole-genome sequencing (WGS) faces many challenges including lack of completion and errors in the human reference genome, repetitive sequences, polymorphisms, variable sample quality, and biases in the sequencing procedures. Formalin-fixed paraffin-embedded (FFPE) archival material, the analysis of which is important for studies of cancer, presents particular analytical difficulties due to degradation of the DNA and frequent lack of matched reference samples. We present a robust, cost-effective WGS method for DNA copy number analysis that addresses these challenges more successfully than currently available procedures. In practice, very useful profiles can be obtained with ~0.1x genome coverage. We improve on previous methods by; first, implementing a combined correction for sequence mappability and GC content, and second, applying this procedure to sequence data from the 1000 Genomes Project in order to develop a blacklist of problematic genome regions. A small subset of these blacklisted regions were previously identified by ENCODE, but the vast majority are novel unappreciated problematic regions. Our procedures are implemented in a pipeline called QDNAseq. We have analyzed over 1,000 samples, most of which were obtained from the fixed tissue archives of over 25 institutions. We demonstrate that for most samples our sequencing and analysis procedures yield genome profiles with noise levels near the statistical limit imposed by read counting. The described procedures also provide better correction of artifacts introduced by low DNA quality than prior approaches, and better copy number data than high-resolution microarrays at substantially lower cost.
Significance
Noninvasive prenatal testing (NIPT) using fetal DNA in maternal plasma has been rapidly adopted worldwide. Current NIPT for fetal chromosomal disorders are based on the counting of DNA molecules in maternal plasma. Here, we show that plasma DNA-based molecular diagnostics can also be built around DNA fragment size, instead of count. First, we demonstrate that the fetal DNA fraction in maternal plasma can be rapidly measured by size analysis, even simply using microchip-based capillary electrophoresis. Second, we show that plasma DNA size analysis can be used for the detection of multiple types of fetal chromosomal aneuploidies with high accuracy. This strategy has many potential diagnostic applications, e.g., in oncology and transplantation monitoring.
The development of noninvasive methods to detect and monitor tumors continues to be a major challenge in oncology. We used digital polymerase chain reaction-based technologies to evaluate the ability of circulating tumor DNA (ctDNA) to detect tumors in 640 patients with various cancer types. We found that ctDNA was detectable in >75% of patients with advanced pancreatic, ovarian, colorectal, bladder, gastroesophageal, breast, melanoma, hepatocellular, and head and neck cancers, but in less than 50% of primary brain, renal, prostate, or thyroid cancers. In patients with localized tumors, ctDNA was detected in 73, 57, 48, and 50% of patients with colorectal cancer, gastroesophageal cancer, pancreatic cancer, and breast adenocarcinoma, respectively. ctDNA was often present in patients without detectable circulating tumor cells, suggesting that these two biomarkers are distinct entities. In a separate panel of 206 patients with metastatic colorectal cancers, we showed that the sensitivity of ctDNA for detection of clinically relevant KRAS gene mutations was 87.2% and its specificity was 99.2%. Finally, we assessed whether ctDNA could provide clues into the mechanisms underlying resistance to epidermal growth factor receptor blockade in 24 patients who objectively responded to therapy but subsequently relapsed. Twenty-three (96%) of these patients developed one or more mutations in genes involved in the mitogen-activated protein kinase pathway. Together, these data suggest that ctDNA is a broadly applicable, sensitive, and specific biomarker that can be used for a variety of clinical and research purposes in patients with multiple different types of cancer.
Background
Patients with prostate cancer may present with metastatic or recurrent disease despite initial curative treatment. The propensity of metastatic prostate cancer to spread to the bone has limited repeated sampling of tumor deposits. Hence, considerably less is understood about this lethal metastatic disease, as it is not commonly studied. Here we explored whole-genome sequencing of plasma DNA to scan the tumor genomes of these patients non-invasively.
Methods
We wanted to make whole-genome analysis from plasma DNA amenable to clinical routine applications and developed an approach based on a benchtop high-throughput platform, that is, Illuminas MiSeq instrument. We performed whole-genome sequencing from plasma at a shallow sequencing depth to establish a genome-wide copy number profile of the tumor at low costs within 2 days. In parallel, we sequenced a panel of 55 high-interest genes and 38 introns with frequent fusion breakpoints such as the TMPRSS2-ERG fusion with high coverage. After intensive testing of our approach with samples from 25 individuals without cancer we analyzed 13 plasma samples derived from five patients with castration resistant (CRPC) and four patients with castration sensitive prostate cancer (CSPC).
Results
The genome-wide profiling in the plasma of our patients revealed multiple copy number aberrations including those previously reported in prostate tumors, such as losses in 8p and gains in 8q. High-level copy number gains in the AR locus were observed in patients with CRPC but not with CSPC disease. We identified the TMPRSS2-ERG rearrangement associated 3-Mbp deletion on chromosome 21 and found corresponding fusion plasma fragments in these cases. In an index case multiregional sequencing of the primary tumor identified different copy number changes in each sector, suggesting multifocal disease. Our plasma analyses of this index case, performed 13 years after resection of the primary tumor, revealed novel chromosomal rearrangements, which were stable in serial plasma analyses over a 9-month period, which is consistent with the presence of one metastatic clone.
Conclusions
The genomic landscape of prostate cancer can be established by non-invasive means from plasma DNA. Our approach provides specific genomic signatures within 2 days which may therefore serve as 'liquid biopsy'.
Circulating DNA (ctDNA) is acknowledged as a potential diagnostic tool for various cancers including colorectal cancer, especially when considering the detection of mutations. Certainly due to lack of normalization of the experimental conditions, previous reports present many discrepancies and contradictory data on the analysis of the concentration of total ctDNA and on the proportion of tumour-derived ctDNA fragments.
In order to rigorously analyse ctDNA, we thoroughly investigated ctDNA size distribution. We used a highly specific Q-PCR assay and athymic nude mice xenografted with SW620 or HT29 human colon cancer cells, and we correlated our results by examining plasma from metastatic CRC patients.
Fragmentation and concentration of tumour-derived ctDNA is positively correlated with tumour weight. CtDNA quantification by Q-PCR depends on the amplified target length and is optimal for 60-100 bp fragments. Q-PCR analysis of plasma samples from xenografted mice and cancer patients showed that tumour-derived ctDNA exhibits a specific amount profile based on ctDNA size and significant higher ctDNA fragmentation. Metastatic colorectal patients (n = 12) showed nearly 5-fold higher mean ctDNA fragmentation than healthy individuals (n = 16).
Cell-free fetal DNA is present in the plasma of pregnant women. It consists of short DNA fragments among primarily maternally derived DNA fragments. We sequenced a maternal plasma DNA sample at up to 65-fold genomic coverage. We showed that the entire fetal and maternal genomes were represented in maternal plasma at a constant relative proportion. Plasma DNA molecules showed a predictable fragmentation pattern reminiscent of nuclease-cleaved nucleosomes, with the fetal DNA showing a reduction in a 166-base pair (bp) peak relative to a 143-bp peak, when compared with maternal DNA. We constructed a genome-wide genetic map and determined the mutational status of the fetus from the maternal plasma DNA sequences and from information about the paternal genotype and maternal haplotype. Our study suggests the feasibility of using genome-wide scanning to diagnose fetal genetic disorders prenatally in a noninvasive way.
The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals.
We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows-Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is approximately 10-20x faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package.
http://maq.sourceforge.net.
The measurement of circulating nucleic acids has transformed the management of chronic viral infections such as HIV. The development of analogous markers for individuals with cancer could similarly enhance the management of their disease. DNA containing somatic mutations is highly tumor specific and thus, in theory, can provide optimum markers. However, the number of circulating mutant gene fragments is small compared to the number of normal circulating DNA fragments, making it difficult to detect and quantify them with the sensitivity required for meaningful clinical use. In this study, we applied a highly sensitive approach to quantify circulating tumor DNA (ctDNA) in 162 plasma samples from 18 subjects undergoing multimodality therapy for colorectal cancer. We found that ctDNA measurements could be used to reliably monitor tumor dynamics in subjects with cancer who were undergoing surgery or chemotherapy. We suggest that this personalized genetic approach could be generally applied to individuals with other types of cancer.
Increased levels of DNA fragments have frequently been found in the blood plasma of cancer patients. Published data suggest that only a fraction of the DNA in blood plasma is derived from cancer cells. However, it is not known how much of the circulating DNA is from cancer or from noncancer cells. By quantitative methylation-specific PCR of the promoter region of the CDKN2A tumor suppressor gene, we were able to quantify the fraction of plasma DNA derived from tumor cells. In the plasma samples of 30 unselected cancer patients, we detected quantities of tumor DNA from only 3% to as much as 93% of total circulating DNA. We investigated possible origins of nontumor DNA in the plasma and demonstrate here a contribution of T-cell DNA in a few cases only. To investigate the possibility that plasma DNA originates from apoptotic or necrotic cells, we performed studies with apoptotic (staurosporine) and necrotic (staurosporine plus oligomycin) cells in vitro and with mice after induction of apoptotic (anti-CD95) or necrotic (acetaminophen) liver injury. Increasing amounts of DNA were found to be released in the supernatants of cells and in the blood plasma samples of treated animals. A clear discrimination of apoptotic and necrotic plasma DNA was possible by gel electrophoresis. The same characteristic patterns of DNA fragments could be identified in plasma derived from different cancer patients. The data are consistent with the possibility that apoptotic and necrotic cells are a major source for plasma DNA in cancer patients.
Purpose:
Cell-free DNA (cfDNA) sequencing provides a non-invasive method for obtaining actionable genomic information to guide personalized cancer treatment, but the presence of multiple alterations in circulation related to treatment and tumor heterogeneity complicate the interpretation of the observed variants. Experimental Design: We describe the somatic mutation landscape of 70 cancer genes from cfDNA deep-sequencing analysis of 21,807 patients with treated, late-stage cancers across >50 cancer types. To facilitate interpretation of the genomic complexity of circulating tumor DNA in advanced, treated cancer patients, we developed methods to identify cfDNA copy-number driver alterations and cfDNA clonality.
Results:
Patterns and prevalence of cfDNA alterations in major driver genes for non-small cell lung, breast, and colorectal cancer largely recapitulated those from tumor tissue sequencing compendia (TCGA and COSMIC; r=0.90-0.99), with the principle differences in alteration prevalence being due to patient treatment. This highly sensitive cfDNA sequencing assay revealed numerous subclonal tumor-derived alterations, expected as a result of clonal evolution, but leading to an apparent departure from mutual exclusivity in treatment-naïve tumors. Upon applying novel cfDNA clonality and copy-number driver identification methods, robust mutual exclusivity was observed among predicted truncal driver cfDNA alterations (FDR=5x10-7 for EGFR and ERBB2), in effect distinguishing tumor-initiating alterations from secondary alterations. Treatment-associated resistance, including both novel alterations and parallel evolution, was common in the cfDNA cohort and was enriched in patients with targetable driver alterations (>18.6% patients).
Conclusions:
Together these retrospective analyses of a large cfDNA sequencing data set reveal subclonal structures and emerging resistance in advanced solid tumors.
Purpose:
Plasma cell-free DNA (cfDNA) genotyping is increasingly used in cancer care, but assay accuracy is debated. Because most cfDNA is derived from peripheral blood cells (PBC), we hypothesized that nonmalignant mutations harbored by hematopoietic cells (clonal hematopoiesis, CH) could be a cause of false positive plasma genotyping. Experimental Design: We identified patients with advanced NSCLC withKRAS,JAK2, orTP53mutations identified in cfDNA. With consent, PBC DNA was tested using droplet digital PCR (ddPCR) or next-generation sequencing (NGS) to test for CH-derived mutations. Results: We first studied plasma ddPCR results from 58EGFR-mutant NSCLC patients. Two hadKRASG12X detected in cfDNA and both were present in PBC, including one where theKRASmutation was detected serially for 20 months. We then studied 143 plasma NGS results from 122 NSCLC patients, and identified 5JAK2V617F mutations derived from PBC. Additionally, 108TP53mutations were detected in cfDNA; for 33 of theTP53mutations, PBC and tumor NGS were available for comparison, and 5 were present in PBC but absent in tumor, consistent with CH.
Conclusions:
We find that mostJAK2mutations, someTP53mutations, and rareKRASmutations detected in cfDNA are derived from CH not tumor. Clinicians ordering plasma genotyping must be prepared for the possibility that mutations detected in plasma, particularly in genes mutated in CH, may not represent true tumor genotype. Efforts to use plasma genotyping for cancer detection may need paired PBC genotyping so that CH-derived mutations are not misdiagnosed as occult malignancy.
SEEK and you may find cancer earlier
Many cancers can be cured by surgery and/or systemic therapies when detected before they have metastasized. This clinical reality, coupled with the growing appreciation that cancer's rapid genetic evolution limits its response to drugs, have fueled interest in methodologies for earlier detection of the disease. Cohen et al. developed a noninvasive blood test, called CancerSEEK that can detect eight common human cancer types (see the Perspective by Kalinich and Haber). The test assesses eight circulating protein biomarkers and tumor-specific mutations in circulating DNA. In a study of 1000 patients previously diagnosed with cancer and 850 healthy control individuals, CancerSEEK detected cancer with a sensitivity of 69 to 98% (depending on cancer type) and 99% specificity.
Science , this issue p. 926 ; see also p. 866
Purpose
Cell-free DNA (cfDNA) offers the potential for minimally invasive genome-wide profiling of tumor alterations without tumor biopsy and may be associated with patient prognosis. Triple-negative breast cancer (TNBC) is characterized by few mutations but extensive somatic copy number alterations (SCNAs), yet little is known regarding SCNAs in metastatic TNBC. We sought to evaluate SCNAs in metastatic TNBC exclusively via cfDNA and determine if cfDNA tumor fraction is associated with overall survival in metastatic TNBC.
Patients and Methods
In this retrospective cohort study, we identified 164 patients with biopsy-proven metastatic TNBC at a single tertiary care institution who received prior chemotherapy in the (neo)adjuvant or metastatic setting. We performed low-coverage genome-wide sequencing of cfDNA from plasma.
Results
Without prior knowledge of tumor mutations, we determined tumor fraction of cfDNA for 96.3% of patients and SCNAs for 63.9% of patients. Copy number profiles and percent genome altered were remarkably similar between metastatic and primary TNBCs. Certain SCNAs were more frequent in metastatic TNBCs relative to paired primary tumors and primary TNBCs in publicly available data sets The Cancer Genome Atlas and METABRIC, including chromosomal gains in drivers NOTCH2, AKT2, and AKT3. Prespecified cfDNA tumor fraction threshold of ≥ 10% was associated with significantly worse metastatic survival (median, 6.4 v 15.9 months) and remained significant independent of clinicopathologic factors (hazard ratio, 2.14; 95% CI, 1.4 to 3.8; P < .001).
Conclusion
We present the largest genomic characterization of metastatic TNBC to our knowledge, exclusively from cfDNA. Evaluation of cfDNA tumor fraction was feasible for nearly all patients, and tumor fraction ≥ 10% is associated with significantly worse survival in this large metastatic TNBC cohort. Specific SCNAs are enriched and prognostic in metastatic TNBC, with implications for metastasis, resistance, and novel therapeutic approaches.
Good bacteria help fight cancer
Resident gut bacteria can affect patient responses to cancer immunotherapy (see the Perspective by Jobin). Routy et al. show that antibiotic consumption is associated with poor response to immunotherapeutic PD-1 blockade. They profiled samples from patients with lung and kidney cancers and found that nonresponding patients had low levels of the bacterium Akkermansia muciniphila . Oral supplementation of the bacteria to antibiotic-treated mice restored the response to immunotherapy. Matson et al. and Gopalakrishnan et al. studied melanoma patients receiving PD-1 blockade and found a greater abundance of “good” bacteria in the guts of responding patients. Nonresponders had an imbalance in gut flora composition, which correlated with impaired immune cell activity. Thus, maintaining healthy gut flora could help patients combat cancer.
Science , this issue p. 91 , p. 104 , p. 97 ; see also p. 32
Identifying molecular residual disease (MRD) after treatment of localized lung cancer could facilitate early intervention and personalization of adjuvant therapies. Here, we apply cancer personalized profiling by deep sequencing (CAPP-seq) circulating tumor DNA (ctDNA) analysis to 255 samples from 40 patients treated with curative intent for stage I–III lung cancer and 54 healthy adults. In 94% of evaluable patients experiencing recurrence, ctDNA was detectable in the first posttreatment blood sample, indicating reliable identification of MRD. Posttreatment ctDNA detection preceded radiographic progression in 72% of patients by a median of 5.2 months, and 53% of patients harbored ctDNA mutation profiles associated with favorable responses to tyrosine kinase inhibitors or immune checkpoint blockade. Collectively, these results indicate that ctDNA MRD in patients with lung cancer can be accurately detected using CAPP-seq and may allow personalized adjuvant treatment while disease burden is lowest.
Significance: This study shows that ctDNA analysis can robustly identify posttreatment MRD in patients with localized lung cancer, identifying residual/recurrent disease earlier than standard-of-care radiologic imaging, and thus could facilitate personalized adjuvant treatment at early time points when disease burden is lowest. Cancer Discov; 7(12); 1394–403. ©2017 AACR.
See related commentary by Comino-Mendez and Turner, p. 1368.
This article is highlighted in the In This Issue feature, p. 1355
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.
Blood-based liquid biopsies, including tumor-educated blood platelets (TEPs), have emerged as promising biomarker sources for non-invasive detection of cancer. Here we demonstrate that particle-swarm optimization (PSO)-enhanced algorithms enable efficient selection of RNA biomarker panels from platelet RNA-sequencing libraries (n = 779). This resulted in accurate TEP-based detection of early- and late-stage non-small-cell lung cancer (n = 518 late-stage validation cohort, accuracy, 88%; AUC, 0.94; 95% CI, 0.92–0.96; p < 0.001; n = 106 early-stage validation cohort, accuracy, 81%; AUC, 0.89; 95% CI, 0.83–0.95; p < 0.001), independent of age of the individuals, smoking habits, whole-blood storage time, and various inflammatory conditions. PSO enabled selection of gene panels to diagnose cancer from TEPs, suggesting that swarm intelligence may also benefit the optimization of diagnostics readout of other liquid biopsy biosources.
During cancer progression and treatment, multiple subclonal populations of tumour cells compete with one another, with selective pressures leading to the emergence of predominant subclones that replicate and spread most proficiently, and are least susceptible to treatment. At present, the molecular landscapes of solid tumours are established using surgical or biopsy tissue samples. Tissue-based tumour profiles are, however, subject to sampling bias, provide only a snapshot of tumour heterogeneity, and cannot be obtained repeatedly. Genomic profiles of circulating cell-free tumour DNA (ctDNA) have been shown to closely match those of the corresponding tumours, with important implications for both molecular pathology and clinical oncology. Analyses of circulating nucleic acids, commonly referred to as 'liquid biopsies', can be used to monitor response to treatment, assess the emergence of drug resistance, and quantify minimal residual disease. In addition to blood, several other body fluids, such as urine, saliva, pleural effusions, and cerebrospinal fluid, can contain tumour-derived genetic information. The molecular profiles gathered from ctDNA can be further complemented with those obtained through analysis of circulating tumour cells (CTCs), as well as RNA, proteins, and lipids contained within vesicles, such as exosomes. In this Review, we examine how different forms of liquid biopsies can be exploited to guide patient care and should ultimately be integrated into clinical practice, focusing on liquid biopsy of ctDNA — arguably the most clinically advanced approach.
Improvements in genomic and molecular methods are expanding the range of potential applications for circulating tumour DNA (ctDNA), both in a research setting and as a 'liquid biopsy' for cancer management. Proof-of-principle studies have demonstrated the translational potential of ctDNA for prognostication, molecular profiling and monitoring. The field is now in an exciting transitional period in which ctDNA analysis is beginning to be applied clinically, although there is still much to learn about the biology of cell-free DNA. This is an opportune time to appraise potential approaches to ctDNA analysis, and to consider their applications in personalized oncology and in cancer research.
http://www.readcube.com/articles/10.1038/nrc.2017.7
The analysis of cell-free DNA (cfDNA) in plasma represents a rapidly advancing field in medicine. cfDNA consists predominantly of nucleosome-protected DNA shed into the bloodstream by cells undergoing apoptosis. We performed whole-genome sequencing of plasma DNA and identified two discrete regions at transcription start sites (TSSs) where nucleosome occupancy results in different read depth coverage patterns for expressed and silent genes. By employing machine learning for gene classification, we found that the plasma DNA read depth patterns from healthy donors reflected the expression signature of hematopoietic cells. In patients with cancer having metastatic disease, we were able to classify expressed cancer driver genes in regions with somatic copy number gains with high accuracy. We were able to determine the expressed isoform of genes with several TSSs, as confirmed by RNA-seq analysis of the matching primary tumor. Our analyses provide functional information about cells releasing their DNA into the circulation.
Detection of circulating tumor DNA (ctDNA) after resection of stage II colon cancer may identify patients at the highest risk of recurrence and help inform adjuvant treatment decisions. We used massively parallel sequencing-based assays to evaluate the ability of ctDNA to detect minimal residual disease in 1046 plasma samples from a prospective cohort of 230 patients with resected stage II colon cancer. In patients not treated with adjuvant chemotherapy, ctDNA was detected postoperatively in 14 of 178 (7.9%) patients, 11 (79%) of whom had recurred at a median follow-up of 27 months; recurrence occurred in only 16 (9.8 %) of 164 patients with negative ctDNA [hazard ratio (HR), 18; 95% confidence interval (CI), 7.9 to 40; P < 0.001]. In patients treated with chemotherapy, the presence of ctDNA after completion of chemotherapy was also associated with an inferior recurrence-free survival (HR, 11; 95% CI, 1.8 to 68; P = 0.001). ctDNA detection after stage II colon cancer resection provides direct evidence of residual disease and identifies patients at very high risk of recurrence.
The discovery of cell-free tumor and fetal DNA molecules in the plasma of cancer patients and pregnant women, respectively, has opened up exciting opportunities in molecular diagnosis. The understanding of the biological properties of circulating cell-free DNA (cfDNA) molecules would be essential for us to make the best use of such molecules in different clinical settings. In this review we start by exploring the technologies that have been used for analyzing the size profiles of cfDNA in plasma. We then review the size profiles of cfDNA in different clinical scenarios, including cancer, pregnancy, transplantation, and autoimmune diseases. Finally, we discuss the potential diagnostic applications of plasma DNA size profiling.
High-throughput sequencing of circulating tumor DNA (ctDNA) promises to facilitate personalized cancer therapy. However, low quantities of cell-free DNA (cfDNA) in the blood and sequencing artifacts currently limit analytical sensitivity. To overcome these limitations, we introduce an approach for integrated digital error suppression (iDES). Our method combines in silico elimination of highly stereotypical background artifacts with a molecular barcoding strategy for the efficient recovery of cfDNA molecules. Individually, these two methods each improve the sensitivity of cancer personalized profiling by deep sequencing (CAPP-Seq) by about threefold, and synergize when combined to yield ∼15-fold improvements. As a result, iDES-enhanced CAPP-Seq facilitates noninvasive variant detection across hundreds of kilobases. Applied to non-small cell lung cancer (NSCLC) patients, our method enabled biopsy-free profiling of EGFR kinase domain mutations with 92% sensitivity and >99.99% specificity at the variant level, and with 90% sensitivity and 96% specificity at the patient level. In addition, our approach allowed monitoring of NSCLC ctDNA down to 4 in 10(5) cfDNA molecules. We anticipate that iDES will aid the noninvasive genotyping and detection of ctDNA in research and clinical settings.
Nucleosome positioning varies between cell types. By deep sequencing cell-free DNA (cfDNA), isolated from circulating blood plasma, we generated maps of genome-wide in vivo nucleosome occupancy and found that short cfDNA fragments harbor footprints of transcription factors. The cfDNA nucleosome occupancies correlate well with the nuclear architecture, gene structure, and expression observed in cells, suggesting that they could inform the cell type of origin. Nucleosome spacing inferred from cfDNA in healthy individuals correlates most strongly with epigenetic features of lymphoid and myeloid cells, consistent with hematopoietic cell death as the normal source of cfDNA. We build on this observation to show how nucleosome footprints can be used to infer cell types contributing to cfDNA in pathological states such as cancer. Since this strategy does not rely on genetic differences to distinguish between contributing tissues, it may enable the noninvasive monitoring of a much broader set of clinical conditions than currently possible.
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The most prominent factor that delays the translation of cell-free DNA (cfDNA) analyses to clinical practice is the lack of knowledge regarding its origin and composition. The elucidation of the former is complicated by the seemingly random fluctuation of quantitative and qualitative characteristics of cfDNA in the blood of healthy and diseased individuals. Besides methodological discrepancies, this could be ascribed to a web of cellular responses to various environmental cues and stressors. Since all cells release cfDNA, it follows that the cfDNA in the blood of cancer patients is not only representative of tumour derived DNA, but also of DNA released by healthy cells under different conditions. Additionally, cfDNA released by malignant cells is not necessarily just aberrant, but likely includes non-mutated chromosomal DNA fragments. This may cause false positive/negative results. Although many have acknowledged that this is a major problem, few have addressed it. We propose that many of the current stumbling blocks encountered in in vivo cfDNA studies can be partially circumvented by in vitro models. Accordingly, the purpose of this work was to evaluate the release of cfDNA from cultured cells and to gauge its potential use for elucidating the nature of cfDNA. Results suggest that the occurrence of cfDNA is not a consequence of apoptosis or necrosis, but primarily a result of actively secreted DNA, perhaps in association with a protein complex. This study demonstrates the potential of in vitro cell culture models to obtain useful information about the phenomenon of cfDNA.
Development of a Q-PCR-based assay for the high-performance analysis of circulating cell-free DNA (ccfDNA) requires good knowledge of its structure and size.
In this work, we present the first visual determination of ccfDNA by Atomic Force Microscopy (AFM) on plasma samples from colorectal cancer (CRC) patients and healthy donors. In addition to the examination of fragment size distribution profile as performed by Q-PCR, this analysis confirms that ccfDNA is highly fragmented and that more than 80% of ccfDNA fragments in CRC plasma are below 145 bp. We adapted an Allele-Specific Blocker (ASB) Q-PCR to small ccfDNA fragments to determine simultaneously the total ccfDNA concentration, the presence of point mutation, the proportion of mutated allele, and a ccfDNA integrity index. The data validated analytically these four parameters in 124 CRC clinical samples and 71 healthy individuals. The multi-marker method, termed Intplex, enables sensitive and specific non-invasive analysis of tumor ccfDNA, which has great potential in terms of cost, quality control, and easy implementation in every clinical center laboratory.
Cancers acquire resistance to systemic treatment as a result of clonal evolution and selection. Repeat biopsies to study genomic evolution as a result of therapy are difficult, invasive and may be confounded by intra-tumour heterogeneity. Recent studies have shown that genomic alterations in solid cancers can be characterized by massively parallel sequencing of circulating cell-free tumour DNA released from cancer cells into plasma, representing a non-invasive liquid biopsy. Here we report sequencing of cancer exomes in serial plasma samples to track genomic evolution of metastatic cancers in response to therapy. Six patients with advanced breast, ovarian and lung cancers were followed over 1-2 years. For each case, exome sequencing was performed on 2-5 plasma samples (19 in total) spanning multiple courses of treatment, at selected time points when the allele fraction of tumour mutations in plasma was high, allowing improved sensitivity. For two cases, synchronous biopsies were also analysed, confirming genome-wide representation of the tumour genome in plasma. Quantification of allele fractions in plasma identified increased representation of mutant alleles in association with emergence of therapy resistance. These included an activating mutation in PIK3CA (phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha) following treatment with paclitaxel; a truncating mutation in RB1 (retinoblastoma 1) following treatment with cisplatin; a truncating mutation in MED1 (mediator complex subunit 1) following treatment with tamoxifen and trastuzumab, and following subsequent treatment with lapatinib, a splicing mutation in GAS6 (growth arrest-specific 6) in the same patient; and a resistance-conferring mutation in EGFR (epidermal growth factor receptor; T790M) following treatment with gefitinib. These results establish proof of principle that exome-wide analysis of circulating tumour DNA could complement current invasive biopsy approaches to identify mutations associated with acquired drug resistance in advanced cancers. Serial analysis of cancer genomes in plasma constitutes a new paradigm for the study of clonal evolution in human cancers.
Background:
The management of metastatic breast cancer requires monitoring of the tumor burden to determine the response to treatment, and improved biomarkers are needed. Biomarkers such as cancer antigen 15-3 (CA 15-3) and circulating tumor cells have been widely studied. However, circulating cell-free DNA carrying tumor-specific alterations (circulating tumor DNA) has not been extensively investigated or compared with other circulating biomarkers in breast cancer.
Methods:
We compared the radiographic imaging of tumors with the assay of circulating tumor DNA, CA 15-3, and circulating tumor cells in 30 women with metastatic breast cancer who were receiving systemic therapy. We used targeted or whole-genome sequencing to identify somatic genomic alterations and designed personalized assays to quantify circulating tumor DNA in serially collected plasma specimens. CA 15-3 levels and numbers of circulating tumor cells were measured at identical time points.
Results:
Circulating tumor DNA was successfully detected in 29 of the 30 women (97%) in whom somatic genomic alterations were identified; CA 15-3 and circulating tumor cells were detected in 21 of 27 women (78%) and 26 of 30 women (87%), respectively. Circulating tumor DNA levels showed a greater dynamic range, and greater correlation with changes in tumor burden, than did CA 15-3 or circulating tumor cells. Among the measures tested, circulating tumor DNA provided the earliest measure of treatment response in 10 of 19 women (53%).
Conclusions:
This proof-of-concept analysis showed that circulating tumor DNA is an informative, inherently specific, and highly sensitive biomarker of metastatic breast cancer. (Funded by Cancer Research UK and others.).
Plasma of cancer patients contains cell-free tumor DNA that carries information on tumor mutations and tumor burden. Individual mutations have been probed using allele-specific assays, but sequencing of entire genes to detect cancer mutations in circulating DNA has not been demonstrated. We developed a method for tagged-amplicon deep sequencing (TAm-Seq) and screened 5995 genomic bases for low-frequency mutations. Using this method, we identified cancer mutations present in circulating DNA at allele frequencies as low as 2%, with sensitivity and specificity of >97%. We identified mutations throughout the tumor suppressor gene TP53 in circulating DNA from 46 plasma samples of advanced ovarian cancer patients. We demonstrated use of TAm-Seq to noninvasively identify the origin of metastatic relapse in a patient with multiple primary tumors. In another case, we identified in plasma an EGFR mutation not found in an initial ovarian biopsy. We further used TAm-Seq to monitor tumor dynamics, and tracked 10 concomitant mutations in plasma of a metastatic breast cancer patient over 16 months. This low-cost, high-throughput method could facilitate analysis of circulating DNA as a noninvasive "liquid biopsy" for personalized cancer genomics.
The hallmarks of cancer comprise six biological capabilities acquired during the multistep development of human tumors. The hallmarks constitute an organizing principle for rationalizing the complexities of neoplastic disease. They include sustaining proliferative signaling, evading growth suppressors, resisting cell death, enabling replicative immortality, inducing angiogenesis, and activating invasion and metastasis. Underlying these hallmarks are genome instability, which generates the genetic diversity that expedites their acquisition, and inflammation, which fosters multiple hallmark functions. Conceptual progress in the last decade has added two emerging hallmarks of potential generality to this list-reprogramming of energy metabolism and evading immune destruction. In addition to cancer cells, tumors exhibit another dimension of complexity: they contain a repertoire of recruited, ostensibly normal cells that contribute to the acquisition of hallmark traits by creating the "tumor microenvironment." Recognition of the widespread applicability of these concepts will increasingly affect the development of new means to treat human cancer.
Prenatal diagnosis of monogenic diseases, such as cystic fibrosis and β-thalassemia, is currently offered as part of public health programs. However, current methods based on chorionic villus sampling and amniocentesis for obtaining fetal genetic material pose a risk to the fetus. Since the discovery of cell-free fetal DNA in maternal plasma, the noninvasive prenatal assessment of paternally inherited traits or mutations has been achieved. Due to the presence of background maternal DNA, which interferes with the analysis of fetal DNA in maternal plasma, noninvasive prenatal diagnosis of maternally inherited mutations has not been possible. Here we describe a digital relative mutation dosage (RMD) approach that determines if the dosages of the mutant and wild-type alleles of a disease-causing gene are balanced or unbalanced in maternal plasma. When applied to the testing of women heterozygous for the CD41/42 (–CTTT) and hemoglobin E mutations on HBB, digital RMD allows the fetal genotype to be deduced. The diagnostic performance of digital RMD is dependent on interplay between the fractional fetal DNA concentration and number of DNA molecules in maternal plasma. To achieve fetal genotype diagnosis at lower volumes of maternal plasma, fetal DNA enrichment is desired. We thus developed a digital nucleic acid size selection (NASS) strategy that effectively enriches the fetal DNA without additional plasma sampling or experimental time. We show that digital NASS can work in concert with digital RMD to increase the proportion of cases with classifiable fetal genotypes and to bring noninvasive prenatal diagnosis of monogenic diseases closer to reality.
• digital PCR
• fetal DNA
• mass spectrometry
• microfluidics
• thalassemia
The amount of non-cell-associated DNA free in blood plasma from pancreatic cancer patients usually exceeds that from healthy donors. We have evaluated the plasma DNA by gel electrophoresis and measured the variation in length of soluble DNA fragments by electron microscopy in plasma from three patients with pancreatic cancer and from three healthy controls. Whereas electrophoresis of nick-translated DNA isolated from plasma obtained from healthy controls showed autoradiographic bands at sizes equivalent to whole-number multiples (1-5x) of nucleosomal DNA (185-200 bp), in the samples obtained from pancreatic cancer patients, stronger ladder patterns appeared. Likewise, strand length distributions of DNA (DNA-SL) in the two groups differ. The DNA-SL distribution data include 2,752 measurements made from cancer patient plasma and 3,291 for control plasma. The shortest DNA-SL measured approximately 30 nm (approximately 88 bp calculated at 0.34 nm/bp) and the largest approximately 28,000 nm (>80,000 bp), with 50% of all lengths measuring between 100 and 900 nm long. The average plasma DNA-SL in controls (311 nm; median, 273 nm) exceeded that in cancer patients (231 nm; median, 185 nm). Small excesses of DNA at approximately 63, approximately 126, approximately 189, approximately 252, and approximately 315 nm, corresponding to small multiples of lengths associated with nucleosomes, were more prominent in the cancer patient plasma than in the healthy control plasma. This study provides evidence indicating differences in non-cell-associated DNA in plasma between cancer patients and healthy controls and indicates that a significant amount of this DNA is probably derived from apoptosis in neoplastic and/or normal cells.