Utilizing circulating tumour DNA in radiation oncology

Radiotherapy and Oncology xxx (2017) xxx–xxx

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Utilizing circulating tumour DNA in radiation oncology Ariana Rostami a,b, Scott V. Bratman a,b,c,⇑ a Princess Margaret Cancer Center, University Health Network; Toronto, Toronto, Canada

a r t i c l e

i n f o

Article history: Received 15 May 2017 Received in revised form 1 July 2017 Accepted 5 July 2017 Available online xxxx Keywords: Circulating tumour DNA Cell-free DNA Liquid biopsy Personalized medicine Precision radiation medicine

b

Department of Medical Biophysics, University of Toronto; and c Department of Radiation Oncology, University of

a b s t r a c t Emerging technologies for detection of circulating tumour DNA (ctDNA) are expanding the possibilities for clinical impact to patients with localized, potentially curable cancer. For such patients, ctDNA analysis could aid in prognostication, prediction of treatment response, longitudinal monitoring for adaptive treatment, and evaluation of minimal residual disease. Radiation oncologists currently have few tools at their disposal for predicting or rapidly assessing treatment efficacy. By reflecting the genetic and epigenetic makeup of tumours as well as dynamic changes with treatment, ctDNA as a biomarker for radiation response could enable new personalized treatment approaches. In this review, we will discuss recent advances in ctDNA technologies and potential clinical applications of ctDNA analysis throughout the therapeutic course. Furthermore, we will consider how ctDNA analysis could someday guide radiotherapy prescriptions by revealing differences in tumour radiophenotype. Ó 2017 Elsevier B.V. All rights reserved. Radiotherapy and Oncology xxx (2017) xxx–xxx

Biomarkers in radiation oncology Recent technological advances have led to dramatic improvements in precision treatment of cancer patients with ionizing radiation. Intensity modulation, on-board imaging, and motion management techniques have enabled improved dose distribution from external beam radiotherapy (RT), minimizing dose delivered to surrounding normal tissue and better targeting of the tumour [1]. Unlike these improvements in the physical delivery of RT, our understanding of the biological basis of RT efficacy has been under-utilized for the purpose of augmenting the therapeutic index. Headway is now being made in the discovery of biomarkers for personalized RT. Both prognostic and predictive biomarkers could help guide treatment and stratify patients who might benefit from treatment intensification or de-escalation [2]. Such biomarkers may include intrinsic radiosensitivity, HPV status, hypoxia, cancer stem cell surrogates, and repopulation [3]. These parameters reflect the biological characteristics that have been shown to confer differences in tumour response to radiation. However, there remains a need for practical approaches to directly assess these parameters in clinical settings. This may take the form of tissuebased analytes, functional imaging parameters, or blood-borne molecules. As imaging- and blood-based biomarkers are amenable

⇑ Corresponding author at: 101 College Street, MaRS/PMCRT 14-313, Toronto, ON M5G 1L7, Canada. E-mail address: [email protected] (S.V. Bratman).

to serial noninvasive assessment before, during, and after the RT course, these have generated much excitement and attention from the research community.

Characteristics of circulating cell-free DNA The presence of fragmented cell-free DNA (cfDNA) within peripheral blood has been recognized for decades [4]. The majority of cfDNA is derived from non-malignant cells, typically haematopoietic in origin [5–8]. Tumour cells can also release DNA into the circulation that is termed circulating tumour DNA (ctDNA). The levels of both total peripheral blood cfDNA and tumour-specific ctDNA in the plasma of individuals can vary considerably [9], even between patients with the same tumour type [9,10]. For example, ctDNA as a fraction of total cfDNA was found to range from 0.01 to 1.7% in colorectal cancer, 0.02–3.2% in NSCLC, and up to 47% in multiple myeloma [11–13]. The concentration of ctDNA is thought to correlate to some extent with tumour size and the rate of tumour cell death and is also influenced by factors that affect access to the systemic circulation (e.g., the blood brain barrier). The main mechanisms of cfDNA release into the circulation are through apoptosis and necrosis [6,14–16]. Active secretion of cfDNA has also been proposed as an alternative mechanism but its physiological relevance remains uncertain. Once in the circulation, cfDNA that is shed by tumours may be taken up by resident and circulating phagocytes, degraded by circulating nucleases, and excreted in urine, stool, saliva, and other bodily fluids.

http://dx.doi.org/10.1016/j.radonc.2017.07.004 0167-8140/Ó 2017 Elsevier B.V. All rights reserved.

Please cite this article in press as: Rostami A, Bratman SV. Utilizing circulating tumour DNA in radiation oncology. Radiother Oncol (2017), http://dx.doi. org/10.1016/j.radonc.2017.07.004

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Increased tumour burden and cellular shedding results in inefficient clearance of ctDNA, eventually leading to its accumulation in the circulation [6,11,14].cfDNA displays a characteristic fragment size distribution centred at approximately 166 base pairs. Fragments of this length correspond to the DNA wrapped around a nucleosome plus its linker. This feature reflects the protective effect of histones against the activity of endonucleases cleaving DNA at exposed sites within the chromatin of cells undergoing apoptosis [6,14,17]. Thus, apoptotic cells have been proposed to be the predominant source of cfDNA [5,11,14,17–21]. Although DNA fragments generated through necrosis are initially much larger in length (>10,000 base pairs) [14,22], circulating nucleases cleave the large DNA fragments into fragments that are of similar size or even smaller than those derived from apoptotic cells. For example, Jiang et al. found that in a cohort of 90 hepatocellular carcinoma patients, higher tumour burden and elevated levels of tumour-derived ctDNA were both correlated with DNA fragments shorter than 166 base pairs [23]. Once released into the circulation, cfDNA is short lived. The halflife of elimination for cfDNA has been reported to range from 16 min to 2 h [18,24–26]. This property allows ctDNA to depict a ‘real-time’ snapshot of tumour changes and disease burden. Thus, ctDNA may enable more rapid evaluation of tumour dynamics compared to conventional protein or imaging biomarkers [15,18,27].

tomography, and magnetic resonance imaging [40–42]. Despite the ubiquity of these approaches, sensitivity and specificity is often insufficient for accurate determination of treatment response. For example, lung radiotherapy often causes inflammatory pulmonary infiltrates and fibrosis that is difficult to distinguish from residual/ recurrent cancer. In certain contexts, blood-based biomarkers are able to offer greater sensitivity than medical imaging to assess treatment response. A prime example is prostate-specific antigen (PSA) in prostate cancer, which has become the standard response biomarker in this disease [43]. However, even PSA is imperfect owing to its lack of cancer specificity and to its uncoupling from cancer burden during androgen deprivation therapy, which is commonly administered during and following radiotherapy. Other than prostate cancer, most cancer types do not have any reliable blood-based response biomarker. Because ctDNA is by nature cancer-specific, it has the potential to provide similar or even greater utility for multiple cancer types as PSA has for prostate cancer. In fact, ctDNA detection has already shown initial promise in comparisons with conventional protein biomarkers and imaging modalities for monitoring disease progression and treatment response [12,18,27,44,45]. In this section, we will review potential clinical applications of ctDNA detection and quantification throughout the therapeutic course (Fig. 1).

Methods for measuring ctDNA

Pre-treatment ctDNA detection for prognostication and risk stratification

The use of ctDNA as a liquid biopsy for cancer has accelerated over the past two decades due to advances in methodologies for detecting DNA somatic variants at very low allelic fractions (<0.1–1%) [15,28]. Prior to this, the implementation of ctDNA as a clinical biomarker was critically limited due to substantial challenges in detecting the ‘signal’ (i.e., cancer-specific DNA variants) from the ‘noise’ (i.e., the vast background of cfDNA released from non-malignant cells). The advent of highly sensitive genomic tech nologies—specifically, PCR-based quantitative approaches and next-generation sequencing (NGS)-based detection methods—has opened the door to a broader array of clinical applications for ctDNA analysis [11,15,18]. Initial approaches to ctDNA analysis relied on allele-specific PCR methods for detection of hotspot mutations in plasma or serum, with limited sensitivity and inconsistent detection [29– 31]. Digital PCR technologies, including droplet digital PCR and BEAMing, offer improved sensitivity and precision for detection of mutations with low allele fraction [11,32–36]. These methods enable investigation of a small number of mutations in parallel but are not capable of simultaneous interrogation of large segments of genes or intergenic regions. In contrast, NGS techniques allow detection of multiple genomic regions of interest through targeted sequencing using PCR amplicons or hybrid capture methods [12,35,37]. By detecting multiple cancer-specific somatic variants simultaneously, the ctDNA signals can be more accurately distinguished from non-cancer noise [12]. Methods aimed to suppress errors introduced by PCR and/or sequencing through molecular barcoding and other approaches can further improve the detection threshold of mutations with allelic fractions below 0.1% [38,39]. These techniques have enabled highly sensitive detection of ctDNA in patients and are now being advanced within clinical settings.

Seminal studies demonstrating the potential clinical applications of ctDNA were conducted in patients with nasopharyngeal carcinoma (NPC). NPC is strongly associated with Epstein-Barr virus (EBV) infection, endemic to Southeast Asia where almost all cases harbour the virus [46]. An early study investigated the prognostic utility of pre-treatment plasma/serum EBV DNA load by quantitative PCR in patients with NPC [47]. Patients with higher median plasma EBV DNA concentration within the first year after treatment had increased risk of recurrence and metastasis, independent of clinical disease stage [47]. In a subsequent study, Lin et al. [48], showed that advanced NPC patients with pre-treatment levels of EBV DNA greater than 1500 copies per millilitre had unfavorable survival and relapse rates. These studies, and many others since, have helped make plasma EBV DNA one of the most well established blood-based DNA tumour biomarkers, and studies on NPC continue to guide the entire liquid biopsy field. More recently, ctDNA has been investigated in the context of other virally related cancer types. The establishment of a causal relationship between human papillomavirus (HPV) infection and a subset of oropharyngeal carcinomas (OPC) marked the potential for HPV DNA to act as blood-based biomarker to assess response and detect recurrence in these patients [49]. Capone et al. compared the use of conventional PCR to quantitative PCR (qPCR) to detect HPV DNA in the sera of OPC patients [50]. Quantitative PCR detection using primers targeting the E7 open reading frame resulted in measurable levels of HPV DNA in two additional sera samples (6/65 samples) not previously detected by conventional PCR (4/65 samples) [50]. More recent studies have shown varying levels of detection sensitivity. Cao et al. detected HPV DNA in 65% of pre-treatment plasma samples from HPV-positive OPC patients [51]. Ahn et al. showed that combining detection of HPV DNA in saliva and plasma increased sensitivity of pre-treatment HPV detection to 76% from 52.8% and 67.3% respectively [52]. However, Dahlstrom et al. found that pre-treatment serum HPV did not have clinical significance as a biomarker for disease recurrence [53]. The inconsistencies between these studies suggest that HPV ctDNA detection in OPC may be less sensitive than EBV ctDNA in NPC.

Detecting and quantifying ctDNA – Clinical applications in RT patients Assessment of RT efficacy typically relies on medical imaging modalities including computed tomography, positron emission

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Fig. 1. Potential applications of ctDNA analysis for personalized treatment of RT patients. (A) Pre-treatment plasma ctDNA could inform patient prognosis and help to stratify patients for aggressive radical RT vs. alternative treatments such as palliation. Furthermore, detection of tumour-specific DNA features that are known to confer sensitivity or resistance to radiotherapy (i.e., HPV or Nrf2 pathway aberrations) could be used to adjust RT prescriptions (i.e., dose escalation or de-escalation). (B) Serial assessment of ctDNA during the course of fractionated RT could provide an early indication of treatment response. Early monitoring to identify responders from non-responders could allow earlier treatment-related decisions and modifications. (C) Post-treatment ctDNA analysis for minimal residual disease (MRD) detection could help to distinguish patients who require adjuvant or salvage therapy from those who can be observed or treated with less aggressive de-escalated adjuvant systemic therapy (if otherwise indicated).

Similar studies in cervical cancer have investigated the potential utility of HPV DNA detection for clinical applications. Early studies showed increased HPV DNA levels in invasive cervical cancer cases, with higher levels seen in metastatic patients compared to non-metastatic patients [54,55]. However, studies have shown variable detection rates of HPV DNA, ranging from 30 to 87% [56,57]. Furthermore, detection rates appeared to be higher in serum samples stored at 80 °C (81–93%) compared to 20 °C (58–83%) [57]. HPV DNA levels were on average higher in plasma samples than in serum samples. Moreover, the volume of plasma used for analysis can affect the detection rate [51]. Together, these studies on HPV ctDNA detection highlight the importance of preanalytical processes and storage conditions for ensuring adequate detection and reducing the variability of results. Analogous to the analysis of circulating viral-derived tumour DNA, somatic changes to the cancer genome have been used to quantify ctDNA. The ability to discriminate tumour-derived DNA from normal cell-free DNA relies on the unique genetic profile of the tumour. ctDNA reflects specific somatic mutations, such as small nucleotide variants and structural chromosomal aberrations, that are not present in the DNA of the normal tissue [15]. An early study in colorectal cancer showed that the 2 year overall survival (OS) rate was 48% in the group where plasma ctDNA was detected, compared to 100% OS in the group with undetectable plasma ctDNA [58]. Studies in non-small lung cell carcinoma (NSCLC) have demonstrated that patients with higher plasma ctDNA concentrations were shown to have worse response to treatment and OS rates compared to patients with lower levels [59–63]. A study in metastatic breast cancer showed that patients with ctDNA concentrations above 2000 copies per millilitre had significantly worse prognosis and OS compared to patients with lower levels of ctDNA [27]. Taken together, pre-treatment ctDNA levels appear to provide insight into patient prognosis and could be used to stratify patients based on likelihood of survival.

Detecting minimal residual disease through post-treatment ctDNA analysis Minimal residual disease (MRD) is a clinical construct that defines the existence of cancer remaining in a patient after use of a potentially curative therapeutic modality. MRD usually indicates the presence of a low number of malignant cells in a patient otherwise in clinical remission; i.e., with no clinical or radiographic signs of disease [64]. Detection of MRD promises to provide meaningful assessment of treatment efficacy and prognosis. The practice of MRD detection is well established in the management of haematological malignancies. For solid tumours, ultrasensitive detection of PSA following radical prostatectomy is an example of MRD detection influencing clinical decisions, where elevated postoperative PSA is an indication that clinical recurrence is likely and, therefore, that adjuvant/salvage RT may be beneficial [65–67]. Thus, for other solid tumours lacking strong biomarkers for evaluating treatment efficacy and treatment response, ctDNA analysis has great potential to influence clinical practice [28]. Virally related cancer types have led early investigations into the use of ctDNA to detect MRD following definitive RT. Studies in NPC suggested that plasma EBV DNA detection had potential clinical applications for monitoring NPC patients post-treatment. Lo et al. [25] showed that of the 47% of patients with undetectable EBV DNA 1 month post-RT, all had complete regression of the tumour. Several groups confirmed these findings, demonstrating that patients with detectable levels of plasma EBV DNA after therapy had worse overall and relapse-free survival and a higher chance of disease progression [48,68–71]. Similar findings have been reported for plasma HPV DNA detection in HPV-positive OPC with post-treatment sensitivity for predicting recurrence within 3 years of 55.1% [52]. Quantification of cancer-specific mutations within ctDNA has also shown promise for MRD detection. Diehl et al. [18] followed a cohort of patients with colorectal cancer that underwent surgery

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of the primary tumour. ctDNA and CEA levels were monitored to assess tumour dynamics following resection. ctDNA detection was a highly sensitive indicator of relapse and was more reliable than CEA. These findings have recently been extended to a cohort of stage II colon cancer patients following resection [72]. Patients with detectable postoperative ctDNA had a 0% relapse-free survival at 3 years compared to 90% for the undetectable ctDNA group. Furthermore, in a study of early stage breast cancer patients receiving curative treatment, plasma ctDNA collected post-treatment had a high accuracy of predicting metastatic relapse [44]. Mutation tracking from serial plasma samples increased sensitivity for predicting relapse, identifying early breast cancer patients at high risk of relapse with a median lead-time of 7.9 months over clinical relapse. More studies are needed to evaluate the clinical validity of ctDNA-based approaches for MRD detection. The probability of detecting ctDNA is known to diminish as the concentration of ctDNA declines [44,72–74]. However, detection of ctDNA in some instances months before gross recurrent disease is evident using conventional medical imaging highlights the potential use of ctDNA for MRD detection and for predicting subsequent clinical relapse. Furthermore, emerging ctDNA detection technologies that promise to have even greater sensitivity than existing methods might be capable of predicting clinical relapse with even longer lead times. Implementing ctDNA-based MRD detection could revolutionize indications for RT (Fig. 2). For example, following surgery MRDpositive patients without standard indications for adjuvant therapy may derive benefit from RT, and those already slated for RT could receive a higher dose. Some MRD-negative patients may be

safely observed without RT. Likewise, ctDNA-based MRD could guide adjuvant or salvage treatments following definitive RT (Fig. 1C). Thus, ctDNA-based MRD detection could allow individualized delivery of sequential treatments, leading to greater cure rates with lower overall toxicity rates [75]. Highly sensitive and specific techniques will be required to achieve this goal, and it is possible that serial testing will improve performance [44]. Additional challenges to ctDNA-based MRD detection include intratumoral genomic heterogeneity and the need for residual cancer cells to be in a state of active proliferation as opposed to dormancy [44,76,77]. An additional limitation of the ctDNA-based MRD approach is the inability with current techniques to determine the anatomical location of the ctDNA source. Thus, clinical applications combining ctDNA detection with medical imaging may offer the greatest promise. Monitoring ctDNA for adaptive treatment Lessons from plasma EBV DNA detection in NPC point to strong prognostic value of post-RT ctDNA analysis. Results from posttreatment tests may inform subsequent adjuvant therapy decisions but cannot easily be implemented into adaptive RT. Leung et al. [78] compared the value of mid-RT and post-RT plasma EBV DNA to predict clinical outcome in patients with NPC and found even stronger prognostic value with the mid-RT assessment. If this result is validated, it could someday open the door to biomarkerdriven adaptive RT dosing based on ctDNA evidence of rapid response (Fig. 1B). Other investigators have asked what clinical utility may be derived from very early measurements of ctDNA during the RT

Fig. 2. Potential applications of ctDNA analysis for personalized treatment of surgery patients. (A) In instances where standard treatment consists of surgery only, postsurgery residual detectable ctDNA could identify patients who might benefit from adjuvant therapy as opposed to observation. (B) In instances where standard treatment consists of surgery plus adjuvant RT, post-surgery residual detectable ctDNA could identify patients who might benefit from the addition of a systemic agent to adjuvant RT. Patients without residual detectable ctDNA may be safely treated with observation (or with de-escalated adjuvant RT).

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course. ctDNA levels display a short half-life in peripheral blood [18,24,25]. Since ctDNA is released into the circulation by cells undergoing cell death, it has been proposed that longitudinal monitoring of ctDNA concentration could reflect rapid death of cancer cells. Much like the phenomenon of tumour lysis syndrome, whereby large amounts of intracellular products are released from cells treated with cytotoxic agents, ctDNA could serve as a biomarker for treatment efficacy [79,80]. However, to date only limited clinical evidence supports this hypothesis. In one clinical study, a subset of NPC patients treated with definitive RT showed an initial spike in EBV DNA within the first week of treatment [80]. Plasma HPV DNA has also been shown to rise one week after starting RT in a subset of OPC patients [51]. In metastatic melanoma patients harbouring the BRAF V600E mutation and undergoing tumourinfiltrating-lymphocytes (TIL) immunotherapy, an early spike and subsequent clearance of ctDNA levels showed a strong correlation with response to treatment [81]. Finally, in a study utilizing preclinical human xenograft tumour models, ctDNA was shown to rise early after initiation of cytotoxic chemotherapy [79]. Together, these studies provide tantalizing early evidence in support of the hypothesis that early spikes in ctDNA concentration could reflect response to cytotoxic therapies such as RT. This line of investigation is reminiscent of earlier studies evaluating ex vivo clonogenic assays to predict radiosensitivity and treatment response for cervical cancer and head and neck cancer [82,83]. Despite some promise of utility in predicting response to RT, these studies were hampered by technical hurdles with implementing the assays and were unable to evaluate in vivo parameters that underlie radiation response. ctDNA analysis has the potential to overcome these limitations and provide a near real-time and individualized readout of RT efficacy. Thus, early ctDNA monitoring could someday identify responders from non-responders and guide treatment decisions as part of biomarker-driven adaptive RT.

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pathway in tumour cells, which results in abundant ROS scavenging and limits the deleterious effects of ionizing radiation. Early clinical experience with detecting these mutations within ctDNA in NSCLC patients suggests that this could be a useful strategy for noninvasive prediction of RT efficacy [86]. Tumour heterogeneity and clonal evolution Inter-tumour heterogeneity in radiation response has been well documented [87–89]. Additionally, intra-tumoural heterogeneity has been extensively studied, wherein distinct regions within a tumour demonstrate different radiosensitivities depending on several factors, including tissue oxygenation, distribution of cancer stem cells, and specific genetic and molecular alterations [90– 93]. Intra-tumoural genetic heterogeneity has also been implicated as a strong mechanism underlying treatment resistance, possibly due to a higher likelihood of radioresistant subclones [92–95]. Treatment resistance develops through clonal evolution of tumour cells under selective pressure to evade cell death [76,96]. Recent ctDNA analysis platforms have shown promise for reporting on genetic heterogeneity and clonal evolution in response to selective pressure [10,12,37,38,76,77,97]. Unlike tumour biopsies that are inherently biased by their limited spatial sampling of tumours, ctDNA could allow for noninvasive and near real-time sampling of multifocal tumour clones [97]. All tumour subclones are expected to contribute to ctDNA; thus, a plasma sample should encompass the heterogeneity of the tumour’s genetic profile. The ability of ctDNA to track the emergence of resistant clones could someday enable treatment modification directed towards the resistant cells. Future directions Predicting tissue-of-origin of cfDNA

Predictive markers of radiotherapeutic effect Biology-driven precision radiation medicine, in which radiation dose is modified based on tumour and/or normal tissue molecular features, has yet to be effectively translated into clinical practice [3]. In this section we discuss how ctDNA-based assays, by revealing differences in tumour/tissue radiophenotype, could someday be used to guide RT prescriptions.

Genetic determinants of radiosensitivity Determinants of radiosensitivity include intrinsic radiosensitivity of the tumour cells, tissue oxygenation, reactive oxygen species (ROS) scavenging within tumour cells, cellular proficiency of DNA double-strand break repair, the number of cancer stem cells, tumour cell immunogenicity, and cell cycle phase. Due to these diverse factors (and likely others), generating a single assay that can predict radiosensitivity has been challenging. Notable exceptions that lend themselves to ctDNA analysis include: (1) HPV association in OPC; and (2) genetic aberrations in the Nrf2 ROS scavenging pathway in non-small cell lung cancer (NSCLC). In OPC, HPV-association has been shown to correlate with increased tumour radiosensitivity [84,85]. Serving as a genetic determinant of radiosensitivity, HPV status could act to identify patients who may benefit from de-escalation of RT dose. HPV status is most commonly determined based on tumour tissue, but if insufficient material is available, plasma HPV DNA detection could someday replace the need for repeat biopsy for this purpose. NSCLC and many other cancer types harbour frequent somatic genetic aberrations within genes involved in the Nrf2 pathway (e.g., NFE2L2 and KEAP1). Mutations characteristically cause overactivation of this

A limitation of existing ctDNA technologies that rely on mutation detection is that most mutations lack specificity for any particular cancer type. To address this, there have been recent efforts to derive the tissue-of-origin of cfDNA through epigenetic marks instead. Sun et al. [98] used a genome-wide bisulphite sequencing approach to identify methylation patterns within cfDNA that are representative of specific tissues. This method successfully allowed for identification of relative tissue contributions to the cfDNA pool in pregnant women, cancer patients, and transplant recipients. In another recent study, Lehmann et al. [99] identified tissuespecific DNA methylation markers within cfDNA from individuals with multiple sclerosis, Type 1 diabetes, ischaemic brain damage, pancreatic cancer. Synder et al. [7] inferred nucleosome positioning from whole genome sequencing of cfDNA. Their findings showed that cfDNA from healthy individuals displayed nucleosome positioning characteristic of haematopoietic cells, whereas cfDNA from cancer patients had greater contributions form nonhaematopoietic tissues [7]. Although currently cost prohibitive for routine clinical use, cfDNA tissue-of-origin analysis could someday complement more established mutation-based approaches for ctDNA detection. Features of the tumour microenvironment As previously discussed, RT efficacy is affected by several parameters within the tumour microenvironment. For example, hypoxia within tumours interferes with radiation effect and is a significant contributor to treatment resistance [100]. A number of hypoxia-directed treatment approaches have shown modest clinical benefit; robust and convenient biomarkers of tumour hypoxia are needed to enrich for patients most likely to benefit

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from such treatments [101–103]. Tumour hypoxia has been shown to cause global DNA hypermethylation through reduction of TET enzymatic activity [104]. It is therefore tempting to speculate that tumour hypoxia could be reflected in the cfDNA methylome. Whether other features of the tumour microenvironment can be discerned from cfDNA analysis is also worthy of further study. Conclusions The analysis of ctDNA offers a noninvasive approach to detect and assess tumour dynamics. This review has highlighted recent evidence for potential clinical applications of ctDNA as a prognostic and predictive biomarker, and as a tool for evaluating posttreatment MRD or adapting treatment. Identification of tumourspecific genetic mutations offers the possibility to track acquired resistance and clonal evolution with the potential to stratify patients based on expected treatment response. Following the technological advances driving physical precision in the Radiation Oncology field, the clinical use of ctDNA could further improve personalized treatment approaches. Ultimately, the success of this approach will require adequate detection techniques depending on the clinical applications and context. ctDNA as a biomarker for RT response may, in the future, be used to complement current imaging modalities with the potential to improve sensitivity of detection and enable biology-driven precision radiation medicine. Conflict of interest statement SVB is co-inventor on a patent ‘Identification and use of circulating tumor markers’ 14/209,807 licensed to Roche Molecular Diagnostics. AR has no conflicts of interest to disclose. Acknowledgments We gratefully acknowledge the support from the Princess Margaret Cancer Foundation, the Joe and Cara Finley Centre for Head & Neck Translational Research, and grants held by SVB from Cancer Research Society and Canadian Cancer Society Research Institute. This work was funded by a Conquer Cancer Foundation of ASCO Career Development Award. Any opinions, findings, and conclusions expressed in this material are those of the author(s) and do not necessarily reflect those of the American Society of Clinical Oncology or the Conquer Cancer Foundation. SVB is supported by the Gattuso-Slaight Personalized Cancer Medicine Fund at Princess Margaret Cancer Centre. References [1] Lacombe J, Azria D, Mange A, Solassol J. Proteomic approaches to identify biomarkers predictive of radiotherapy outcomes. Expert Rev Proteomics 2013;10:33–42. [2] Bibault J-E, Fumagalli I, Ferté C, Chargari C, Soria J-C, Deutsch E. Personalized radiation therapy and biomarker-driven treatment strategies: a systematic review. Cancer Metastasis Rev 2013;32:479–92. [3] Baumann M, Krause M, Overgaard J, Debus J, Bentzen SM, Daartz J, et al. Radiation oncology in the era of precision medicine. Nat Rev Cancer 2016;16:234–49. [4] Mandel P, Metais P. Not Available. C R Seances Soc Biol Fil 1948;142:241–3. [5] Anker P, Mulcahy H, Chen XQ, Stroun M. Detection of circulating tumour DNA in the blood (plasma/serum) of cancer patients. Cancer Metastasis Rev 1999;18:65–73. [6] Stroun M, Lyautey J, Lederrey C, Olson-Sand A, Anker P. About the possible origin and mechanism of circulating DNA apoptosis and active DNA release. Clin Chim Acta 2001;313:139–42. [7] Snyder MW, Kircher M, Hill AJ, Daza RM, Shendure J. Cell-free DNA comprises an in vivo nucleosome footprint that informs its tissues-of-origin. Cell 2016;164:57–68. [8] Zheng YWL, Chan KCA, Sun H, Jiang P, Su X, Chen EZ, et al. Nonhematopoietically derived DNA is shorter than hematopoietically derived DNA in plasma: a transplantation model. Clin Chem 2012;58:549–58.

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