|Year : 2019 | Volume
| Issue : 1 | Page : 1-7
Current status of cell-free DNA in head and neck cancer management
Ashish Singhal, Akhlak Hussain, Akash Agarwal, Bimlesh Thakur
Department of Surgical Oncology, RMLIMS, Lucknow, Uttar Pradesh, India
|Date of Web Publication||22-Aug-2019|
Dr. Akhlak Hussain
Department of Surgical Oncology, RMLIMS, Lucknow, Uttar Pradesh
Source of Support: None, Conflict of Interest: None
Tissue biopsies are temporally and spatially limited and often provide a brief snapshot of a single region of a heterogeneous tumor. Carcinogenesis is a complex process in which heterogeneity plays an important role in the development and progression. Research efforts are going on focusing on the discovery of new, noninvasive methods for the diagnosis, and comprehension of the tumor genomic architecture to monitor tumor evolution and therapeutic response in real time. Liquid biopsy is a noninvasive diagnostic tool that can provide a personalized snapshot of primary and metastatic tumor at successive time points, providing knowledge of the tumor burden so as to detect early evidence of recurrence or resistance to the disease and helping clinicians in their therapeutic decision-making. Therefore, using liquid biopsies, we can obtain a molecular profile for each patient. We intended to review cell-free DNA (cfDNA) in oral cancer. We described cfDNA considering their levels, diagnostic value, prognostic value, predictive value.
Keywords: Cell-free DNA, management, oral cancer
|How to cite this article:|
Singhal A, Hussain A, Agarwal A, Thakur B. Current status of cell-free DNA in head and neck cancer management. Ann Indian Acad Otorhinolaryngol Head Neck Surg 2019;3:1-7
|How to cite this URL:|
Singhal A, Hussain A, Agarwal A, Thakur B. Current status of cell-free DNA in head and neck cancer management. Ann Indian Acad Otorhinolaryngol Head Neck Surg [serial online] 2019 [cited 2022 Sep 28];3:1-7. Available from: https://www.aiaohns.in/text.asp?2019/3/1/1/265137
| Introduction|| |
Oral cancer is one of the most prevalent forms of cancers worldwide, showing an incidence and mortality twice as high in men (2.3% and 1.7%, respectively) compared to women (1.2% and 0.8%, respectively). It is responsible for 145,000 deaths worldwide, and an annual incidence of 300,000 diagnosed cases, being a serious and growing problem in less developed regions especially. Oral cancer is a subset of head and neck cancer that includes cancers of the mucosal surfaces of the lips, floor of the mouth, front two-thirds of the tongue, buccal mucosa, lower and upper gingival surfaces, hard palate, soft palate, and retromolar trigone. This cancer is characterized by a multifactorial etiology and its development has been associated with several risk factors such as tobacco smoking, alcohol consumption, human papillomavirus (HPV), and pesticides, the presence of premalignant oral lesions, weakened immune system, diet with nutritional deficiencies, hereditary predisposition, or radiation. Oral carcinogenesis, characterized by several genetic disorders, is a complex multistep process that disturbs cell signaling, growth, survival, motility, angiogenesis, and cell cycle control. Oncogenes and tumor suppressor genes such as CCND1, epidermal growth factor receptor (EGFR), RAS, vascular endothelial growth factor, p53, CDKN2A, STAT3, and retinoblastoma (Rb) have been implicated in oral cancer.,, Tissue biopsy is the gold standard in the diagnosis of oral cancer, but it is invasive, costly, and time-consuming, and it is potentially harmful. Moreover, conventional biopsies are temporally and spatially limited and often provide a brief snapshot of a single region of a heterogeneous tumor. Carcinogenesis is a complex process in which heterogeneity plays an important role in the development and progression. Genetic, transcriptomic, epigenetic, and/or phenotypic changes could explain inter-and intra-tumoral heterogeneity. Thus, cellular mosaicism is closely related to carcinogenesis, resistance to therapy, and the metastasis capacity of distinct subpopulations of cancer cells, knowledge of which is essential for an effective therapy.
Nowadays, research efforts are focused on the discovery of new, noninvasive methods for the diagnosis and comprehension of the tumor genomic architecture to monitor tumor evolution and therapeutic response in real time. Liquid biopsy is a noninvasive diagnostic tool, based on the detection of circulating tumor cells, circulating tumor DNA (ctDNA), and circulating tumor RNA, proteins, and exosomes. Importantly, in addition to blood, there are other bodily fluids such as urine, saliva, seminal plasma, pleural effusions, cerebrospinal fluid, sputum, and stool samples that can be used for a liquid biopsy. One of the key advantages of studying liquid biopsies is that they provide a personalized snapshot of primary and metastatic tumor at successive time points, providing knowledge of the tumor burden so as to detect early evidence of recurrence or resistance to the disease and helping clinicians in their therapeutic decision-making. Therefore, using liquid biopsies, we can obtain a molecular profile for each patient.
| Methods|| |
We systemically review all the researches available online (PubMed, and Springer) regarding the measurement and role of cell-free DNA (cfDNA). We sequentially describe cfDNA levels, diagnostic value, prognostic value, and in the evaluation of treatment response; methods used for cfDNA assessment, comparison of methods, and clinicopathological correlations.
| Review and Discussion|| |
Pathophysiology of cell-free DNA
Necrosis and apoptosis of both tumor cell and the normal host cell leads to release of free DNA into the bloodstream and other bio fluids. Release of cfDNA actively has also been suggested. Normal, apoptotic and necrotic cells are cleared by infiltrating phagocytes, and cfDNA levels are relatively low. However, phagocytic clearance is not effective for cancer cells. Most of the cfDNA fragments are 70–200 bp long double-stranded DNA. Long (upto 21 kb) fragments also exist. Possible mechanisms leading to cfDNA release are necrosis, autophagy, and other physiologic events induced by microenvironmental stress and treatment pressure.,,,,, Necrosis generates larger DNA fragments due to an incomplete and random digestion of genomic DNA. Apoptosis generates relatively shorter ones. ctDNA lengthening in cancer patients has not been completely understood. In healthy controls, the main source of cell-free circulating DNA is apoptotic cells. During apoptosis, genomic DNA would undergo enzymatic cleavage to produce DNA fragments of ∼180 bp. The increased integrity of circulating DNA in cancer patients has been postulated to be a consequence of pathologic processes other than apoptosis, including necrosis, autophagy, and mitotic catastrophe of tumor cells.,, Interestingly, in contrast to the increased integrity of circulating DNA, the integrity of circulating RNA is reduced in cancer patients.
The fraction of cfDNA derived from the tumor is termed as ctDNA. The spleen, liver, and kidneys are involved in the clearance of cfDNA. Reason for the stability of cfDNA is poorly understood. The fetal cfDNA is studied to follow the initial rapid phase of clearance with the mean half-life of approximately 1 h and then a slow phase with the mean half-life of approximately 13 h. Circulating DNA was first identified by Mandel and Metais in 19,487, but no association with the disease was hypothesized.
Levels of circulating tumor DNA in blood
The median cfDNA concentration in patients with solid tumors is 17 ng/mL (Range: 0.5–1600, which is 3-fold higher than in healthy volunteers. Higher cfDNA concentrations were associated with worse overall survival. Leon et al. found that the cfDNA in plasma of the lung cancer patients were much higher in cancer patients than in healthy controls. However, subsequent studies demonstrated highly variable levels ranging from 0.01% to ≥90%.,,,,,, This variability may correlate with tumor burden, stage, vascularity, cellular turnover, and response to therapy., cfDNA levels may also be raised in benign lesions, inflammatory diseases, tissue trauma, impaired renal clearance, and production of white blood cells. There is no correlation found between the ages of the patients and the concentrations of free or cell-surface-bound circulating DNA. However, studies have identified that the total mean concentration of circulating cell-surface-bound DNA in blood was higher in healthy men (1030 ng/mL of blood) than in healthy women (430 ng/mL).,
Characteristics of cell-free DNA
ctDNA can be differentiated from higher cfDNA concentrations were associated with worse overall survival on the basis of tumor-specific somatic genetic mutations. ctDNA carries genomic and epigenomic alterations specific to the tumor such as point mutations, degree of integrity, rearranged genomic sequences, copy-number variation (CNV), microsatellite instability (MSI), loss of heterozygosity (LOH), and DNA methylation. These characteristics help discriminate ctDNA from normal cfDNA and assure ctDNA as a tumor-specific biomarker.
Cell-free DNA analysis
The serum is the best material for cfDNA preparations since it is having a lower concentration of background wild-type DNA and 2–4 times higher cfDNA amount. Contamination of lysed cellular DNA may affect the relative levels of ctDNA, and the cfDNA has limited stability. Thus, cfDNA preparation should be completed promptly after blood draw. Background levels of wild-type cfDNA may mask the small fraction of tumor-specific DNA making the analysis challenging. cfDNA isolation can be enhanced by various techniques. For example, in the cell-surface-bound DNA, the interactions are so weak that the extracellular cell-surface-bound DNA can be easily eluted with ethylenediaminetetraacetic acid solution. Additional strategies including eluting the more tightly bound DNA with mild trypsin treatment of the cells together with the polypeptide binding nucleic acids. The following methods have been used for analyzing cfDNA.
Basic methods for analysis include quantitative real-time polymerase chain reaction (PCR)-based, fluorescence-based, and spectrophotometric approaches.,,
- PCR-based methods are nested real-time PCR, amplified refractory mutation system/Scorpion PCR, PCR-single-strand conformational polymorphism, mutant allele-specific PCR, mass spectrometry, and Bidirectional PAP allele-specific amplification. These are easy to use with the lowest cost. However, they are lesser sensitive and detect only limited genetic loci. However, most manufacturers of real-time quantitative PCR (qPCR) instruments and qPCR reagents recommend amplicon lengths of 80–150 bp, as longer products have lowered amplification efficiencies, which may increase variation and thus decrease the reliability of the results., cfDNA quantities based on the measurement of some target genes (e.g., human telomerase reverse transcriptase [TERT]) can be much higher than those of other assays
- Digital PCR: It involves droplet-based systems, microfluidic platforms for parallel PCR, and an approach called BEAMing (beads, emulsions, amplification, and magnetic) to detect point mutations (KRAS, EGFR, and PIK3CA) and genetic alterations in ctDNA. It is highly sensitive but detects only limited genetic loci,
- Next-generation sequencing: These are highly sensitive and relatively inexpensive, identifying widespread alterations in cfDNA.
Targeted deep sequencing analyses specified genomic regions (selected single nucleotide variants [SNVs], CNVs, and rearrangements across targeted regions). It is highly sensitive, relatively inexpensive but is less comprehensive than whole-exome sequencing methods. It includes PCR-based targeted deep sequencing such as TamSeq, SafeSeq, and Ion AmpliSeq™ and capture-based targeted deep sequencing such as CAPP-Seq.
Whole genome sequencing provides comprehensive characterization of the alteration profiles, not just limited to predefined or existing mutations. Genome-wide detection of chromosomal rearrangements and CNVs in ctDNA has excellent sensitivity and specificity., Two genome-wide methods, personalized analysis of rearranged ends (PARE), and digital karyotyping have been used for ctDNA detection. PARE helps in identifying specific somatic rearrangements which can be detected by PCR-based assays to detect these tumor biomarkers in the circulation., Digital karyotyping is used to quantify the DNA copy number and novel sequences on a genomic scale. It can detect previously uncharacterized chromosomal changes and exogenous sequences in human tumors.,,
Clinical application of cell-free DNA
Diagnostic and prognostic tool
- DNA methylation: aberrations of DNA methylation in the gene promoter region or in the noncoding genomic sequences, causing silencing of tumor suppressor genes, are associated with tumor initiation, dissemination, and metastasis establishment, and progression. Aberrant CpG island hypermethylation almost always occurs in neoplastic cells. The status of DNA methylation is very stable, even in the circulation. Therefore, the examination of abnormal methylation patterns in ctDNA, released from these cells, may help in the early detection of cancers with high sensitivity. This can be used to monitor tumor-related processes and as screening and prognostic tool also. However, it is yet to be validated. It is difficult to implement on populations at risk.,
The frequently hypermethylations that can be targeted for detection in ctDNA are as follows:
- MLH1: colon, endometrial, and gastric cancers
- ER-beta (Estrogen receptor-beta) and RAR-beta2: breast cancer
- P16: esophageal, lung, colon, liver, and pancreas cancer
- GSTP1 (Glutathione-S-transferase P1): hepatocellular carcinoma
- 14-3-3 sigma/stratifin: breast cancers
- BRCA1: breast and ovarian cancers
- VHL: kidney tumors
- TMEFF2: lung and various tumor types
- DNA methyltransferase and O6-methylguanine-DNA methyltransferase (MGMT): various tumor types.
LOH and MSI: tumor-specific LOH in ctDNA has diagnostic and prognostic value. LOH can also indicate recurrence and tumor burden. In serum, ctDNA is present in high- and low-molecular-weight fractions. LOH at different loci is found in the low-molecular-weight fraction. Thus, fractionation of circulating DNA is essential for analysis., DNA mismatch repair (MMR) corrects errors that occur during DNA replication. MSI results from malfunctioning of the MMR system. Accumulate errors are an important event in carcinogenesis. Detection of MSI in ctDNA helps in diagnosis and assessing progression, MSI and LOH in ctDNA was initially detected by Nawroz et al. Subsequently, there are studied in breast, brain, colorectal, ovarian, and prostate cancers. A study involving breast cancer patients (n = 388) revealed that high-LOH frequencies, especially CCND2 loss was associated with the aggressiveness and an unfavorable prognosisCancer-associated genomic rearrangements/genetic alterations: the identification of tumor-specific genetic variations (single nucleotide polymorphism, CNV), and epigenetic alterations has implications in diagnosis and assessing recurrences and therapeutic resistances. These variations are currently being investigated in ctDNA. Dawson et al. used targeted or whole-genome sequencing in metastatic breast cancer patients and designed personalized assays to quantify ctDNA genetic alterations. They found that ctDNA levels are associated with changes in tumor burden. Duncan et al. published the first whole-genome sequencing analysis of ctDNA. SNVs and CNV were detected in all advanced stage cancer patients, but not in healthy controls. Chan et al. did the genome-wide profiling of CNVs and point mutations. Concordant genome-wide SNVs have been identified between tumor tissues and presurgical cfDNA. These structural alterations disappeared completely after surgery. Furthermore, ctDNA sequencing helps to study tumor heterogeneity.
Tumor burden and predictive markers
ctDNA has comprehensive, inherently specific, and highly sensitive information. ctDNA levels have been found to increased rapidly with disease progression and declined correspondingly after successful treatment.,, Mutations associated with treatment resistance can be effectively assessed in ctDNA., KRAS alterations are associated with the onset of acquired resistance to anti-EGFR treatment of colorectal cancers. The detection of KRAS variants in ctDNA of patients receiving anti-EGFR therapies can identify relapse 10 months before radiographic documentation of disease progression. Serial ctDNA analysis by whole-exome sequencing can provide a complete assessment of genomic alterations during the acquisition of treatment resistance. Since cfDNA analysis can provide a global picture of genetic alterations, combination treatments can be designed accordingly to minimize therapeutic resistance.
Minimal residual disease
There is no effective tool to diagnose minimal residual disease after curative treatment (especially surgery) that can result in recurrence. As a result, potentially cured patients are still receiving adjuvant chemotherapy unnecessarily. The assessment of tumor-specific mutations in plasma DNA postsurgery can identify individuals with residual disease, i.e., at risk of relapse and detect disease recurrence this early prediction of relapse may allow effective treatment to be introduced early with minimal disease burden.
Cell-free DNA and head and neck cancers
- Coulet et al., 2000, used fluorescence emission after adding a dye intercalating with plasma DNA to test for circulating DNA in head and neck squamous cell carcinoma (HNSCC). They used MSI at UT5085 and p53 mutation screening. Of the 117 tumors typed at UT5085, 65 cases demonstrated bandshifts (55%). Plasma and tumor DNA showed similar alteration in only one case among these samples, and the prevalence of tumor DNA in plasma was estimated to be <2% using microsatellite analysis. Tumor DNA was detected in plasma at a higher prevalence (2 of 11 cases) when using p53 mutant allele-specific amplification. These results showed that in plasma, tumor DNA is largely diluted by normal DNA. Plasma DNA concentrations, however, did not significantly correlate between gender and tumor stage or tumor localization. They concluded that plasma DNA should be analyzed with very sensitive and specific methods such as mutant allele-specific amplification, which excludes artifacts
- Jiang et al., 2006, employed a real-time PCR-based assay to assess the DNA strand integrity of cfDNA in a total of 58 HNSCC patients with paired pre- and post-surgical plasma and plasma from 47 controls without HNSCC. The mean DNA integrity index was significantly greater in HNSCC patients, 0.24 (95% confidence interval [CI]: 0.11, 0.38), when compared to the controls, −2.24 (95% CI: −2.92, −1.56), P < 0.0001 using multivariate analysis. However, there was no significant difference noted between pre- and post-operative DNA integrity index in HNSCC patients. The lack of normalization of plasma DNA integrity index after surgical resection implies the persistence of a population of cells with an altered pattern of DNA degradation despite the removal of malignancy
- Chan et al., 2008, investigated the plasma DNA integrity levels in nasopharyngeal carcinoma and its association with patients' survival after radiotherapy. The integrity index of circulating DNA in NPC was calculated as the ratio of the two concentrations (201 bp/105 bp). If all cfDNA molecules are of high molecular weight and span the whole leptin gene, the concentrations determined by the two assays would be identical, thus giving an integrity index of 1. However, if the cfDNA molecules are fragmented to <201 bp, the concentration determined using the 105 bp assay would be higher than that determined by the 201 bp assay, thus giving an integrity index of <1. Therefore, the integrity of circulating DNA could be reflected by the integrity index. The more intact the plasma DNA, the higher the integrity index would be. They determine the integrity of circulating DNA fragments using two real-time PCR assays targeting the leptin gene with amplicon sizes of 105 and 201 bp. The plasma DNA integrity index of the NPC patients was significantly higher than that of the healthy controls (median, 0.356 vs. 0.238; P < 0.001). After radiotherapy, a reduction in plasma DNA integrity index was observed in 70% NPC patients. Patients with persistent aberrations of plasma DNA integrity had significantly poorer survival probability than those with reduced DNA integrity after treatment (P < 0.001, Kaplan–Meier analysis)
- Shukla et al., 2013, studied cfDNA in oral epithelial dysplasia and oral squamous cell carcinoma (OSCC), through spectrophotometry. No significant difference was observed in levels of cfDNA in blood between patients and controls. This study also concluded that progression is not correlated with changes in levels of cfDNA
- Mazurek et al., 2016, quantified cfDNA level of 200 HNSCC patients using TaqMan-based TERT amplification. TaqMan technology was also used for HPV 16/18 detection. KRAS and EGFR mutations were also investigated. A higher level (P = 0.011) of the total cfDNA was found in oropharyngeal squamous cell carcinoma (OPSCC) (9.60 ± 6.23 ng/ml) in comparison with other HNSCC (7.67 ± 4.44 ng/ml). The level of cfDNA in cases of clinical N2-N3 disease (9.28 ± 6.34 ng/ml) was higher than in cases with clinical N0–N1 disease (7.50 ± 3.69 ng/ml; P = 0.015). It was also higher in patients with Stage IV (9.16 ± 6.04 ng/ml) compared with Stages I–III of cancer (7.26 ± 3.63 ng/ml) (P = 0.011). cfDNA level was comparable in HPV-positive and HPV-negative HNSCC patients, as well in the OPSCC subgroup. Somatic mutations in EGFR and KRAS were not found. Thus, they highlight the diagnostic potential of plasma-based HPV cfDNA tests for the early detection and monitoring of HPV-positive HNSCC
- Desai et al., 2018, aimed to quantify plasma level of total, short and long fragmented cfDNA along with DNA integrity in patients with oral cancer, oral precancer, and tobacco users without lesions and normal controls. The quantity of short and long fragmented DNA was assessed using PCR with two different primer sets for the beta-actin gene, amplifying short (102 bp), and long (253 bp) products. The DNA integrity index was measured by calculating the ratio of quantity of long fragmented to short fragmented DNA. Total cfDNA level, short and long fragmented cfDNA concentration and DNA integrity were significantly higher in oral cancer group as compared to other (P = 0.0001). They did not find any correlation of total, short and long cfDNA and DNA integrity with tumor size and histologic type or grading. However, positive correlation of total cfDNA was found with nodal metastasis (P = 0.001) and clinical stages (P = 0.006). They concluded that total cfDNA may be applied as a screening marker for early detection of precancer and cancer as well as for prognostication of oral cancer. In addition, plasma levels of short and long fragmented cfDNA and DNA integrity index can be applied for early detection of oral cancer. Only 40 OSCC samples enrolled in this study, clinicopathological parameters cannot analyze through the limited samples size
- Lin et al., 2018, investigated 121 OSCC and 50 controls for cfDNA levels using quantitative spectrometry. The size distribution of cfDNA was similar in OSCC and controls; the average size was 150–200 bp. The mean concentrations of cfDNA were 53.1 ± 6.69 ng/mL in OSCC and 24.0 ± 3.33 ng/mL in the controls. A multivariate logistic regression analysis indicated an adjusted odds ratio of 4.15 (95% CI, 2.16–9.20; P < 0.001). CfDNA was not found to be associated with age, gender, perineural invasion, and cell differentiation. However, it was related to tumor size, TNM staging, and lymphovascular invasion. CfDNA levels were higher in patients with neck lymph node metastasis as compared to those without these features. A multivariate logistic regression analysis indicated an adjusted odds ratio of 2.53 (95% CI, 1.06–6.08; P = 0.038). They found a significant decrease in cfDNA after tumor resection in 75% of the patients. After adjusting for tumor size, perineural invasion, and lymphovascular invasion; neck lymph node metastasis (hazard ratio, 9.529; 95% CI, 2.054–44.195; P = 0.004) and cfDNA level (hazard ratio, 4.432; 95% CI, 1.214–16.178; P = 0.024) were found to be independent factors influencing disease-specific survival. Kaplan–Meier analysis indicated an association of higher cfDNA levels with worse disease-specific survival (P = 0.001) and disease-free survival (P = 0.003).
| Conclusion|| |
CfDNA may be a good tool in diagnosis, management guidance, and follow-up. More investigations are required to specifically define its role.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M, et al.
Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer 2015;136:E359-86.
Sinevici N, O'sullivan J. Oral cancer: Deregulated molecular events and their use as biomarkers. Oral Oncol 2016;61:12-8.
Krishna A, Singh S, Kumar V, Pal US. Molecular concept in human oral cancer. Natl J Maxillofac Surg 2015;6:9-15.
] [Full text]
Ramos-García P, Gil-Montoya JA, Scully C, Ayén A, González-Ruiz L, Navarro-Triviño FJ, et al.
An update on the implications of cyclin D1 in oral carcinogenesis. Oral Dis 2017;23:897-912.
Bellairs JA, Hasina R, Agrawal N. Tumor DNA: An emerging biomarker in head and neck cancer. Cancer Metastasis Rev 2017;36:515-23.
de Sá Junior PL, Câmara DA, Porcacchia AS, Fonseca PM, Jorge SD, Araldi RP, et al.
The roles of ROS in cancer heterogeneity and therapy. Oxid Med Cell Longev 2017;2017:2467940.
Peng M, Chen C, Hulbert A, Brock MV, Yu F. Non-blood circulating tumor DNA detection in cancer. Oncotarget 2017;8:69162-73.
Sumanasuriya S, Lambros MB, de Bono JS. Application of liquid biopsies in cancer targeted therapy. Clin Pharmacol Ther 2017;102:745-7.
Salvi S, Gurioli G, De Giorgi U, Conteduca V, Tedaldi G, Calistri D, et al.
Cell-free DNA as a diagnostic marker for cancer: Current insights. Onco Targets Ther 2016;9:6549-59.
Pantel K, Alix-Panabières C. Circulating tumour cells in cancer patients: Challenges and perspectives. Trends Mol Med 2010;16:398-406.
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.
Jahr S, Hentze H, Englisch S, Hardt D, Fackelmayer FO, Hesch RD, et al.
DNA fragments in the blood plasma of cancer patients: Quantitations and evidence for their origin from apoptotic and necrotic cells. Cancer Res 2001;61:1659-65.
Chan KC, Zhang J, Hui AB, Wong N, Lau TK, Leung TN, et al.
Size distributions of maternal and fetal DNA in maternal plasma. Clin Chem 2004;50:88-92.
Mouliere F, Robert B, Arnau Peyrotte E, Del Rio M, Ychou M, Molina F, et al.
High fragmentation characterizes tumour-derived circulating DNA. PLoS One 2011;6:e23418.
Diehl F, Schmidt K, Choti MA, Romans K, Goodman S, Li M, et al.
Circulating mutant DNA to assess tumor dynamics. Nat Med 2008;14:985-90.
Wang BG, Huang HY, Chen YC, Bristow RE, Kassauei K, Cheng CC, et al.
Increased plasma DNA integrity in cancer patients. Cancer Res 2003;63:3966-8.
Umetani N, GiulianoAE, Hiramatsu SH, et al.
Prediction of breast tumor progression by integrity of free circulating DNA in serum. J Clin Oncol 2006;24:4270-6.
Jin Z, El-Deiry WS. Overview of cell death signaling pathways. Cancer Biol Ther 2005;4:139-63.
Wong BC, Chan KC, Chan AT, Leung SF, Chan LY, Chow KC, et al.
Reduced plasma RNA integrity in nasopharyngeal carcinoma patients. Clin Cancer Res 2006;12:2512-6.
Yu SC, Lee SW, Jiang P, Leung TY, Chan KC, Chiu RW, et al.
High-resolution profiling of fetal DNA clearance from maternal plasma by massively parallel sequencing. Clin Chem 2013;59:1228-37.
Mandel P, Sétais P. Les acides nucléiques du plasma sanguin chez l'homme. C. R. Acad. Sci Paris 1948;142:241-3.
Breitbach S, Tug S, Simon P. Circulating cell-free DNA: An up-coming molecular marker in exercise physiology. Sports Med 2012;42:565-86.
Leon SA, Shapiro B, Sklaroff DM, Yaros MJ. Free DNA in the serum of cancer patients and the effect of therapy. Cancer Res 1977;37:646-50.
Stroun M, Anker P, Maurice P, Lyautey J, Lederrey C, Beljanski M. Neoplastic characteristics of the DNA found in the plasma of cancer patients. Oncology 1989;46:318-22.
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.
Gormally E, Caboux E, Vineis P, Hainaut P. Circulating free DNA in plasma or serum as biomarker of carcinogenesis: Practical aspects and biological significance. Mutat Res 2007;635:105-17.
Fleischhacker M, Schmidt B. Circulating nucleic acids (CNAs) and cancer–A survey. Biochim Biophys Acta 2007;1775 (1):181–232.
Schwarzenbach H, Alix-Panabières C, Müller I, Letang N, Vendrell JP, Rebillard X, et al.
Cell-free tumor DNA in blood plasma as a marker for circulating tumor cells in prostate cancer. Clin Cancer Res 2009;15:1032-8.
Park JL, Kim HJ, Choi BY, Lee HC, Jang HR, Song KS, et al.
Quantitative analysis of cell-free DNA in the plasma of gastric cancer patients. Oncol Lett 2012;3:921-6.
Kohler C, Barekati Z, Radpour R, Zhong XY. Cell-free DNA in the circulation as a potential cancer biomarker. Anticancer Res 2011;31:2623-8.
Giordano A, Giuliano M, De Laurentiis M, Eleuteri A, Iorio F, Tagliaferri R, et al.
Artificial neural network analysis of circulating tumor cells in metastatic breast cancer patients. Breast Cancer Res Treat 2011;129:451-8.
Aparicio S, Caldas C. The implications of clonal genome evolution for cancer medicine. N
Engl J Med 2013;368:842-51.
Jin D, Xie S, Mo Z, Liang Y, Guo B, Yu M. Circulating DNA-important biomarker of cancer. J Mol Biomarkers Diagn 2012. doi: 10.4172/2155-9929.S2-009.
Tsang JC, Lo YM. Circulating nucleic acids in plasma/serum. Pathology 2007;39:197-207.
Marzese DM, Hirose H, Hoon DS. Diagnostic and prognostic value of circulating tumor-related DNA in cancer patients. Expert Rev Mol Diagn 2013;13:827-44.
Björkman L, Reich CF, Pisetsky DS. The use of fluorometric assays to assess the immune response to DNA in murine systemic lupus erythematosus. Scand J Immunol 2003;57:525-33.
Tuaeva NO, Abramova ZI, Sofronov VV. The origin of elevated levels of circulating DNA in blood plasma of premature neonates. Ann N
Y Acad Sci 2008;1137:27-30.
Chen Z, Feng J, Buzin CH, Liu Q, Weiss L, Kernstine K, et al.
Analysis of cancer mutation signatures in blood by a novel ultra-sensitive assay: Monitoring of therapy or recurrence in non-metastatic breast cancer. PLoS One 2009;4:e7220.
Vogelstein B, Kinzler KW. Digital PCR. Proc Natl Acad Sci U S A 1999;96:9236-41.
Thornton B, Basu C. Real-time PCR (qPCR) primer design using free online software. Biochem Mol Biol Educ 2011;39:145-54.
Mazurek AM, Rutkowski T, Fiszer-Kierzkowska A, Małusecka E, Składowski K. Assessment of the total cfDNA and HPV16/18 detection in plasma samples of head and neck squamous cell carcinoma patients. Oral Oncol 2016;54:36-41.
Pekin D, Skhiri Y, Baret JC, Le Corre D, Mazutis L, Salem CB, et al.
Quantitative and sensitive detection of rare mutations using droplet-based microfluidics. Lab Chip 2011;11:2156-66.
Dressman D, Yan H, Traverso G, Kinzler KW, Vogelstein B. Transforming single DNA molecules into fluorescent magnetic particles for detection and enumeration of genetic variations. Proc Natl Acad Sci U S A 2003;100:8817-22.
McBride DJ, Orpana AK, Sotiriou C, Joensuu H, Stephens PJ, Mudie LJ, et al.
Use of cancer-specific genomic rearrangements to quantify disease burden in plasma from patients with solid tumors. Genes Chromosomes Cancer 2010;49:1062-9.
Shaw JA, Page K, Blighe K, Hava N, Guttery D, Ward B, et al.
Genomic analysis of circulating cell-free DNA infers breast cancer dormancy. Genome Res 2012;22:220-31.
Leary RJ, Kinde I, Diehl F, Schmidt K, Clouser C, Duncan C, et al.
Development of personalized tumor biomarkers using massively parallel sequencing. Sci Transl Med 2010;2:20ra14.
Wang TL, Maierhofer C, Speicher MR, Lengauer C, Vogelstein B, Kinzler KW, et al.
Digital karyotyping. Proc Natl Acad Sci U S A 2002;99:16156-61.
Leary RJ, Sausen M, Kinde I, Papadopoulos N, Carpten JD, Craig D, et al.
Detection of chromosomal alterations in the circulation of cancer patients with whole-genome sequencing. Sci Transl Med 2012;4:162ra154.
Wang TL, Diaz LA Jr., Romans K, Bardelli A, Saha S, Galizia G, et al.
Digital karyotyping identifies thymidylate synthase amplification as a mechanism of resistance to 5-fluorouracil in metastatic colorectal cancer patients. Proc Natl Acad Sci U S A 2004;101:3089-94.
Duncan CG, Leary RJ, Lin JC, Cummins J, Di C, Schaefer CF, et al.
Identification of microbial DNA in human cancer. BMC Med Genomics 2009;2:22.
Heyn H, Esteller M. DNA methylation profiling in the clinic: Applications and challenges. Nat Rev Genet 2012;13:679-92.
Sunami E, Vu AT, Nguyen SL, Hoon DS. Analysis of methylated circulating DNA in cancer patients' blood. Methods Mol Biol 2009;507:349-56.
Lu Y, Soong TD, Elemento O. A novel approach for characterizing microsatellite instability in cancer cells. PLoS One 2013;8:e63056.
Nawroz H, Koch W, Anker P, Stroun M, Sidransky D. Microsatellite alterations in serum DNA of head and neck cancer patients. Nat Med 1996;2:1035-7.
Schwarzenbach H, Eichelser C, Kropidlowski J, Janni W, Rack B, Pantel K. Loss of heterozygosity at tumor suppressor genes detectable on fractionated circulating cell-free tumor DNA as indicator of breast cancer progression. Clin Cancer Res 2012;18:5719-30.
Dawson SJ, Tsui DW, Murtaza M, Biggs H, Rueda OM, Chin SF, et al.
Analysis of circulating tumor DNA to monitor metastatic breast cancer. N
Engl J Med 2013;368:1199-209.
Chan KC, Jiang P, Zheng YW, Liao GJ, Sun H, Wong J, et al.
Cancer genome scanning in plasma: Detection of tumor-associated copy number aberrations, single-nucleotide variants, and tumoral heterogeneity by massively parallel sequencing. Clin Chem 2013;59:211-24.
Bidard FC, Madic J, Mariani P, Piperno-Neumann S, Rampanou A, Servois V, et al.
Detection rate and prognostic value of circulating tumor cells and circulating tumor DNA in metastatic uveal melanoma. Int J Cancer 2014;134:1207-13.
Misale S, Yaeger R, Hobor S, Scala E, Janakiraman M, Liska D, et al.
Emergence of KRAS mutations and acquired resistance to anti-EGFR therapy in colorectal cancer. Nature 2012;486:532-6.
De Mattos-Arruda L, Cortes J, Santarpia L, Vivancos A, Tabernero J, Reis-Filho JS, et al.
Circulating tumour cells and cell-free DNA as tools for managing breast cancer. Nat Rev Clin Oncol 2013;10:377-89.
Murtaza M, Dawson SJ, Tsui DW, Gale D, Forshew T, Piskorz AM, et al.
Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA. Nature 2013;497:108-12.
Sorenson GD, Pribish DM, Valone FH, Memoli VA, Bzik DJ, Yao SL, et al.
Soluble normal and mutated DNA sequences from single-copy genes in human blood. Cancer Epidemiol Biomarkers Prev 1994;3:67-71.
Coulet F, Blons H, Cabelguenne A, Lecomte T, Lacourreye O, Brasnu D, et al.
Detection of plasma tumor DNA in head and neck squamous cell carcinoma by microsatellite typing and p53 mutation analysis. Cancer Res 2000;60:707-11.
Jiang WW, Zahurak M, Goldenberg D, Milman Y, Park HL, Westra WH, et al.
Increased plasma DNA integrity index in head and neck cancer patients. Int J Cancer 2006;119:2673-6.
Chan KC, Leung SF, Yeung SW, Chan AT, Lo YM. Persistent aberrations in circulating DNA integrity after radiotherapy are associated with poor prognosis in nasopharyngeal carcinoma patients. Clin Cancer Res 2008;14:4141-5.
Shukla D, Kale AD, Hallikerimath S, Yerramalla V, Subbiah V. Can quantifying free-circulating DNA be a diagnostic and prognostic marker in oral epithelial dysplasia and oral squamous cell carcinoma? J Oral Maxillofac Surg 2013;71:414-8.
Desai A, Kallianpur S, Mani A, Tijare MS, Khan S, Jain M, et al.
Quantification of circulating plasma cell free DNA fragments in patients with oral cancer and precancer. Gulf J Oncolog 2018;1:11-7.
Lin LH, Chang KW, Kao SY, Cheng HW, Liu CJ. Increased plasma circulating cell-free DNA could be a potential marker for oral cancer. Int J Mol Sci 2018;19. pii: E3303.