Circulating tumour DNA in EGFR-mutant non-small-cell lung cancer

Review Article

Circulating tumour DNA in EGFR-mutant non-small-cell lung cancer


M. Cabanero, MD*, M.S. Tsao, MD*



doi: http://dx.doi.org/10.3747/co.25.3761


ABSTRACT

The advent of targeted therapy in non-small-cell lung cancer (nsclc) has made the routine molecular diagnosis of EGFR mutations crucial for optimal patient management. Obtaining tumour tissue for biomarker testing, especially in the setting of re-biopsy, can present many challenges. A potential alternative source of tumour dna is circulating cell-free tumour-derived dna (ctdna). Although ctdna is present in low quantities in plasma, the convenience of sample acquisition and the increasing reliability of detection methods make this approach a promising one. The various performance characteristics of both digital and nondigital platforms are still variable, and a standardized approach is needed that will make those platforms reliable clinical tools for the detection of EGFR sensitizing mutations and resistance mutations, including the T790M resistance mutation. Information derived from ctdna can be used to assess tumour burden, to identify genomic-based resistance mechanisms, and to track dynamic changes during therapy.

KEYWORDS: Lung adenocarcinoma, EGFR, circulating dna, ctdna, liquid biopsy

INTRODUCTION

Clinical practice has changed since the discovery of mutations in the kinase domain of the EGFR gene in non-small-cell lung cancer (nsclc). Patients with a tumour that harbours such mutations, especially exon 21 L858R and exon 19 deletions (which account for approximately 90% of all sensitizing mutations1), experience prolonged progression-free survival when treated with epidermal growth factor receptor (egfr) tyrosine kinase inhibitors (tkis)24. However, most of those patients will ultimately progress and succumb to their cancer. The action of second-generation tkis (afatinib and dacomitinib), which irreversibly inhibit members of the ErbB family receptor tyrosine kinases, has been less impressive, partly tempered by greater side effects; however, those agents will remain an important therapeutic option. Importantly, acquired resistance in approximately 60% of patients treated with the first-generation egfr tkis erlotinib and gefitinib is conferred by the point mutation T790M5,6. That mutation restores the kinase domain’s binding affinity for adenosine triphosphate, rendering the tkis ineffective. The high frequency of acquired resistance attributable to the T790M mutation has prompted the development of third-generation tkis that can overcome that specific resistance mechanism. Furthermore, the presence of T790M in a tumour before treatment with a first-generation tki is a marker for worse prognosis79. Routine detection of T790M at diagnosis and continual monitoring throughout tki treatment and progression is even more important now that the third-generation egfr tki osimertinib, which specifically inhibits tumours harbouring the T790M mutation, has become clinically available.

In a hallmark example of precision oncology, the initial diagnostic biopsy material from pulmonary adenocarcinomas is now being routinely tested for EGFR sensitizing mutations (and ALK rearrangements), usually on formalin-fixed paraffin-embedded tissue sections. Given the increasing number of approved egfr tkis with differing specificities and resistance mechanism profiles, many institutions are now incorporating pretreatment molecular testing for the T790M point mutation. In many cases, the biopsy material limits that testing, and because most patients with nsclc are diagnosed at an advanced stage, surgical acquisition of more tumour tissue for molecular testing is not a viable alternative. Moreover, monitoring resistance and sensitizing EGFR mutations during progression is determined by accessibility to tumour that can be biopsied. Intratumoural heterogeneity also complicates the matter, in that only a subset of somatic mutations (that is, truncal mutations) are shared by all tumour cells, and subclonal populations might not be thoroughly detected and characterized by the limited sampling.

Alternatively, circulating cell-free tumour-derived dna (ctdna) has been used to detect and monitor tumour progression in various cancers, including detecting sensitizing EGFR mutations in nsclc. In oncology, including in nsclc, ctdna is rapidly gaining clinical utility; many studies have shown promise in monitoring treatment response in patients with sensitizing EGFR mutations undergoing egfr tki therapy, and in detecting the presence of the T790M resistance mutation in treatment-naïve patients and in those with progressive disease while taking the first-generation egfr tkis erlotinib and gefitinib.

PRINCIPLES OF CIRCULATING DNA

Discovered by Mandel and Metais, the presence of circulating cell-free dna has been known since the late 1940s10. Every living cell actively secretes small fragments of dna into the circulation, and the concentration of those secretions increases in certain conditions such as trauma, inflammation, apoptosis, or necrosis11. Circulating dna consists of small double-stranded fragments that are approximately 150 bp in length12, matching the length of dna in a nucleosome. The fragments are rapidly cleared—a 99% clearance rate within 2 hours having been observed in multiple studies13,14. Plasma concentrations of circulating dna vary widely, and a significant difference in quantity is seen between individuals with malignant disease and those who have nonmalignant disease or who are healthy15.

The biologic role of circulating dna is still far from completely understood. Studies have shown that circulating dna in healthy individuals plays an important antimicrobial role as a principal component of neutrophil extracellular traps16. It is thought that release of those traps by neutrophils serves as an innate form of immune response that is capable of degrading virulence factors and killing bacteria. The circulating dna component of the neutrophil extracellular traps also plays a crucial role in activating the coagulation system and is thought to be regulated by dnase in the bloodstream.

The Human Genome Project provided the impetus for the technological progress in molecular analyses in the 1990s. The surge of newer molecular techniques allowed for the clinical application of circulating cell-free dna. Indeed, the cell-free dna present in the circulation, together with its accessibility by the minimally invasive technique of venipuncture, has led to its use in various clinical scenarios, including prenatal diagnosis of fetal trisomies17; prediction of outcomes in traumatic and burn injuries, myocardial infarctions, and stroke11; and monitoring of allograft rejection in organ transplantation18.

Experimental evidence that tumour cells also release their dna into the circulation has been available since 198919, and cancer-specific point mutations (NRAS point mutations in myelodysplastic syndrome and acute myeloid leukemia, and KRAS mutations in pancreatic cancer) were first detected in 199420,21. Detection of other cancer-specific molecular alterations in the circulation, including microsatellite instability22, gene amplifications23,24, and the hypermethylation status of promoter regions in tumour suppressor genes25,26, were discovered soon after. It was also noted that the total circulating dna concentration was higher overall in patients with lung cancer (among other cancers) than in healthy subjects27,28.

Recently, Underhill et al.28 demonstrated that, in patients with lung cancer (and other tumours), the fragment lengths of ctdna are shorter than those of normal circulating dna (for lung cancer: 277 bp vs. 283 bp; p = 0.002). Additionally, by selecting the fraction of circulating dna with base pairs shorter than the peak fragment length of that individual’s library (approximately 20–50 bp shorter), they were able to increase the allele frequency of T790M mutation signals, suggesting an improvement in mutant call sensitivity by fractional selection of shorter fragment lengths. The realization that ctdna has the potential to be used as a reliable biomarker for the presence and overall burden of a tumour has prompted many investigators to discover better, more sensitive methods of detection29.

The challenge in the detection of ctdna is that it is markedly dilute compared with the background circulating germline dna (0.01%–10%)30, requiring highly sensitive methods to increase its weak signal. Standard approaches, including Sanger sequencing and pyrosequencing, often fail to detect ctdna fragments except in individuals with a very high tumour burden or level of ctdna. Current approaches for detecting ctdna can be broadly categorized in two ways: targeting specific molecular alterations and targeting all possible molecular alterations in dna (including targeted and whole-genome or whole-exome sequencing).

MUTATION DETECTION METHODS

A variety of polymerase chain reaction (pcr)–based methods have been used to assess ctdna for specific molecular alterations. These techniques generally require less dna input material, have a good signal-to-noise ratio, and are efficient for use in cancers with few, but important, molecular alterations, including nsclc with EGFR sensitizing mutations and the T790M resistance mutation. However, with the exception of digital pcr, these methods are more reliable for qualitative than for precise quantitative assessments. The amplification refractory mutation system uses sequence-specific pcr primers that allow amplification only if the target allele is present; it is broadly used in detecting EGFR sensitizing mutations31,32. Peptide nucleic acid clamping pcr relies on preferential amplification of mismatched sequences to enrich non-target sequences of a mixed template33.

A growing number of studies are investigating the utility of ctdna in cancer management, and the field is moving toward digital methods of detection. Digital methods of pcr technology incorporate a number of techniques to improve the specificity and sensitivity of mutation detection. Digital droplet pcr sample preparation includes separation of template molecules into individual reaction vessels, which can then be individually assessed for the presence of mutation. That approach converts the analog nature of pcr into a linear digital signal and permits absolute quantification of variant alleles34,35. A specific subtype of the latter approach, beaming (beads, emulsion, amplification, magnetics), places single dna molecules onto magnetic beads, upon which thousands of copies are made, creating a one-to-one representation of the starting dna molecule per bead36. The technology has been commercialized, and although being actively used37, it has not gained traction because the protocol is laborious and requires specific bead-bound oligonucleotides for each mutation tested. Oxnard et al.38 used beaming digital pcr to retrospectively detect the presence of the T790M mutation in patients with acquired egfr tki resistance receiving osimertinib.

More affordable approaches to targeted sequencing based on oligonucleotide dna capture has been used to sequence target gene panels and even the entire human exome39. That approach relies on sequencing library construction, followed by hybridization to dna or rna oligonucleotides complementary to selected regions. The hybrid molecules are sequestered and amplified with universal primer pairs complementary to the adaptors. Because ctdna exists as smaller nucleic acid fragments, ligation-based chemistry can be used to directly prepare libraries40, by-passing the standard next-generation sequencing methods for library preparation that require either shearing of larger fragments before adaptor ligation or transposon-based library construction, which simultaneously fragments and tags dna in a single reaction. Pioneering work by Newman et al.41 incorporated that technology to quantify ctdna in patients with nsclc. To select their regions-of-interest panel, those authors used data from the Catalogue of Somatic Mutations in Cancer and The Cancer Genome Atlas to include regions of the genome that contain the most recurrent mutations in nsclc. Their capp-seq (cancer personalized profiling by deep sequencing) panel targets 521 exons and 13 introns from 139 recurrently mutated genes, covering approximately 125 kb, and identifies insertions, deletions, point mutations, and structural alterations, including ALK rearrangements. They demonstrated that, compared with radiographic imaging, ctdna analysis better assesses early response to treatment and could be used to distinguish between residual disease and treatment-related changes. They have also now integrated molecular barcoding, which incorporates sequencing adapters that act as “barcodes” to allow for reconstruction of the parental dna duplexes after amplification, as well as in silico filtering of common recurrent background errors that reflect oxidative damage arising in vivo or ex vivo (that is, G>T transversions and C>T or G>A transitions). The latter work has resulted in an error rate lower by a factor of 15 than that achieved with the original capp-seq approach42.

Whole-exome sequencing does not require a priori knowledge of a tumour’s molecular profile. As proof of principle, Murtaza et al.43 used whole-exome sequencing to monitor treatment response in 6 patients with advanced breast, ovarian, and lung cancers. They demonstrated an overall strong concordance between mutations detected in the primary tumour tissue and in ctdna. They observed that the variant allele frequency largely reflected the levels of ctdna in each sample. However, the relatively high cost, large target size for coverage, and high dna input requirement (>100 ng/mL) currently limits the practicality of this approach in assessing ctdna.

CORRELATION OF TISSUE AND PLASMA SAMPLES

The performance characteristics of the many technology platforms used to detect EGFR sensitizing mutations in plasma vary considerably. Table i summarizes the various methods and the ranges of their diagnostic accuracy. Non-digital methods have high specificity, but suffer from lower sensitivities. Digital methods, including digital droplet pcr and beaming, have high sensitivities and specificities, but require more technical expertise and laborious protocols.

TABLE I Assay performance in detecting EGFR-sensitizing mutations in circulating tumour DNA

 

A growing body of evidence about the diagnostic utility and performance of various methods for the noninvasive measurement of the T790M resistance mutation in ctdna is accumulating (Table ii). As in the case of EGFR sensitizing mutations, nondigital methods maintain relatively high specificity, but lower sensitivity. The concordance rates between the studies vary widely, possibly for several reasons. First, small-volume tumours might not shed enough dna into the circulation. Second, intratumoural heterogeneity could explain a positive call on the plasma even though the primary tumour tests negative. Third, detection discordance between tumour tissue and plasma could reflect the differing sensitivities of the platforms used.

TABLE II Assay performance in the detection of T790M in circulating tumour DNA

 

CIRCULATING DNA TO ASSESS TUMOUR BURDEN

There are many advantages to using ctdna as a way to assess overall tumour burden. Several studies have investigated the use of total circulating dna quantification as a surrogate for tumour burden in cancer patients, especially in metastatic disease—analogous to assessing hiv viral load47,49. Investigators have shown that, in lung cancer patients, increasing concentrations of total circulating dna are correlated with tumour stage and overall survival6062. Using quantitative real-time pcr, Szpechcinski et al.63 compared total circulating dna concentrations in patients with chronic respiratory inflammation (chronic obstructive pulmonary disease, sarcoidosis, or asthma) and in patients with nsclc. They determined that increased total circulating dna is 90% sensitive and 80.5% specific for plasma from lung cancer patients compared with non-cancer patients, even in the presence of confounding pulmonary pathology.

The recent tracerx study64 also provides valuable insight into predictors of ctdna detection in early-stage nsclc. The study authors discovered that plasma-based detection is increased in tumours with non-adenocarcinoma histology, necrosis, lymphovascular invasion, and a higher Ki-67 proliferation index. Tumour volume was also seen to correlate with plasma ctdna variant allele frequencies, and a primary tumour volume of 10 cm3 predicted a ctdna plasma variant allele frequency of 0.1%.

Chen et al.65 investigated the clinical value of urinary samples as source of ctdna in patients with nsclc. The study enrolled 150 patients with sensitizing EGFR mutations who were receiving a first-generation egfr tki (erlotinib or gefitinib) and compared dna from primary tumour tissue with ctdna from blood and urine. Serial urinary and plasma ctdna measurements were also performed every month for 9 months. The authors reported a concordance rate of 88% between primary tumour tissue and urinary ctdna for EGFR mutation, and a concordance rate of 98% between plasma and urinary ctdna. As expected, ctdna concentrations dropped in both urine and plasma after tki initiation. By the final time point, 53% of patients in the study cohort had developed the T790M mutation, which had been absent at baseline; the median period of mutation emergence for the group overall was 6 months after tki initiation. Additionally, the quantity of urinary ctdna was higher in patients who developed the T790M mutation, spiking upward a few months after detection of the resistant mutation. Urinary T790M was also prognostic, with the group testing positive for the mutation experiencing significantly worse overall survival.

Using ctDNA to More Comprehensively Characterize Resistance Mechanisms

The clinical impact of intratumoural geographic heterogeneity cannot be underscored further than by the characterization of resistance mechanisms. Tissue biopsies sample a particular geographic region of a tumour and will not always fully characterize the subclones present. Notably, earlier studies using ctdna to characterize egfr tki resistance mechanisms were limited to methods specific for EGFR sensitizing mutations37,57,6670. Newer studies using next-generation sequencing aim to more broadly capture and categorize drug-specific resistance mechanisms.

Chabon et al.71 used capp-seq to analyze the ctdna of 43 patients with T790M-mutant nsclc who progressed on first-or second-generation egfr tkis and who entered a clinical trial for the third-generation tki rociletinib. Analysis of ctdna during progression but before rociletinib initiation showed additional molecular alterations constituting resistance mechanisms not previously detected in almost half the patients, including increased MET or ERBB2 copy numbers, and additional single nucleotide variants in EGFR, PIK3CA, or RB1. Those patients experienced inferior responses and shorter progression-free survival when treated with rociletinib. Moreover, the authors described resistance mechanisms treatment-specific to third-generation tkis, including a novel EGFR mutation (L798I) and an activating KRAS mutation as mechanisms of resistance to rociletinib. In contrast, EGFR C797S, a common resistance mutation found in patients treated with osimertinib70, is not really found as a resistance mechanism in those treated with rociletinib. The authors also noted that, as opposed to preclinical models72,73 in which resistance mutations to third-generation tkis have primarily involved additional mutations in the EGFR gene (for example, C797S), their patient cohort showed mostly bypass pathway activation, with MET copy number gain observed in 25% of patients as a common mechanism of acquired resistance74. In overcoming the limitations inherent in classic tissue biopsies, “liquid biopsies” are showing promise in more comprehensively characterizing egfr tki resistance mechanisms and will lead to more tailored combination or single-agent therapies.

Using ctDNA to Monitor Response to Therapy

He et al.56 used digital droplet pcr to prospectively detect EGFR mutations in a cohort of 200 patients with nsclc being treated with afatinib after developing resistance to a first-generation tki. All patients underwent baseline blood sampling before any tki treatment, and patients with de novo T790M were excluded. Eventually, 168 patients developed resistance to either erlotinib or gefitinib, and 128 patients were monitored to detect ctdna variations. The authors reported 93.5% concordance between tissue and ctdna for the EGFR sensitizing mutations L858R and ex19del, and 100% concordance for the T790M resistance mutation. Of the tested patients, 47% were positive for T790M ctdna, and the average mutant ctdna concentration in those patients was 660 ± 311 copies per millilitre. Interestingly, a correlative increase in ctdna concentration was evident in patients who developed T790M, consistent with the reduced effectiveness of the first-generation tkis. Serial monitoring of plasma samples after the start of afatinib treatment was able to capture the dynamic changes during treatment, with 46% of the patients receiving afatinib expeirencing a drop in ctdna concentration, with a correspondingly favourable overall survival.

Clearly, the clinical utility of ctdna as a means of genotyping and monitoring treatment response with EGFR-mutant nsclc is rapidly becoming reality. To address the objective evaluation of ctdna for monitoring the dynamic changes in nsclc during tki therapy, Kato et al.75 proposed using a “mart” (mutation allele ratio in therapy) score as an index of therapeutic response. A diagnostic score called the plasma mutation score was defined as the number of reads with deletions (exon 19 deletions) or substitutions (exon 20: T790M; exon 21: L858R, L861Q) in 100,000 reads. The mart score is the ratio of the plasma mutation score for the activating mutation after therapy (taken at 2 or 4 weeks after initiation) compared with before therapy initiation. In a 52-patient cohort, all 3 patients who developed progressive disease had a mart score that exceeded 0.1.

Kato et al. also proposed a numeric index that defines the onset of disease progression. By defining the point at which ctdna started to exceed the limit-of-quantification threshold and comparing it with the time point of objective disease progression by the Response Evaluation Criteria in Solid Tumors, they observed three types of responders (based on an arbitrary cut-off point of 100 days). In approximately 40% of patients, the interval between rising ctdna and objective disease progression was within approximately 100 days and most likely indicated a parallel change in disease. However, in a small subset of patients (approximately 15%), ctdna elevations preceded radiographic growth by more than 100 days and was characterized by more varied ctdna dynamics. In 1 patient, ctdna levels of the activating mutation rose and maintained at a certain level until disease progression, after which an accompanying increase in T790M ctdna occurred. What is unclear is whether the early ctdna elevations in these patients represent true disease progression or confounding secondary pathology. Lastly, for approximately 45% of the patients, ctdna did not elevate with disease progression. Additional studies and further confirmation will be necessary to develop a consensus objective method for using ctdna to monitor response to treatment.

SUMMARY

Precision oncology in nsclc relies on the ability to detect “actionable” mutations in a precise and timely manner. That reliance is now truer than ever, given the availability of multiple generations of egfr tkis with action-specific targets and drug-specific resistance mechanisms. Analysis of ctdna provides many benefits for real-time monitoring of tumour response to egfr tkis and for the detection of acquired resistance such as T790M. Obtaining plasma samples is easy, low-cost, and minimally invasive, with low morbidity. By sampling the full clonal spectrum, ctdna also addresses the limitations of solid biopsies in capturing tumour heterogeneity. However, because ctdna constitutes only a very minor percentage of total circulating dna, ultra-sensitive methods are necessary for ctdna pipelines. Many studies now underway are looking at using ctdna to assess the burden of EGFR-mutant nsclc and its response to egfr tkis, and to demonstrate the prognostic value of acquired resistance mutations. Although the field is moving toward digital methods of ctdna detection, the various assays have different sensitivity, specificity, and concordance profiles. The clinical utility of ctdna will require more standardization and technical training in the newer digital platforms to ensure reliability as an adjunct tool in the management of EGFR-mutant nsclc.

CONFLICT OF INTEREST DISCLOSURES

We have read and understood Current Oncology’s policy on disclosing conflicts of interest, and we declare the following interests: MST received grants and personal fees from AstraZeneca during the conduct of this study, and grants and personal fees from Merck, personal fees from Bristol–Myers Squibb, personal fees from Ventana/Roche, and grants and personal fees from Pfizer Canada outside the submitted work. MC has no conflicts to declare.

AUTHOR AFFILIATIONS

*Princess Margaret Cancer Centre, University Health Network, and,
Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON..

REFERENCES

1. Shi Y, Au JS, Thongprasert S, et al. A prospective, molecular epidemiology study of EGFR mutations in Asian patients with advanced non-small-cell lung cancer of adenocarcinoma histology (pioneer). J Thorac Oncol 2014;9:154–62.
cross-ref  pmc  

2. Mok TS, Wu YL, Thongprasert S, et al. Gefitinib or carboplatin–paclitaxel in pulmonary adenocarcinoma. N Engl J Med 2009;361:947–57.
cross-ref  

3. Mitsudomi T, Morita S, Yatabe Y, et al. Gefitinib versus cisplatin plus docetaxel in patients with non-small-cell lung cancer harbouring mutations of the epidermal growth factor receptor (wjtog3405): an open label, randomised phase 3 trial. Lancet Oncol 2010;11:121–8.
cross-ref  

4. Zhou C, Wu YL, Chen G, et al. Erlotinib versus chemotherapy as first-line treatment for patients with advanced EGFR mutation-positive non-small-cell lung cancer (optimal, ctong-0802): a multicentre, open-label, randomised, phase 3 study. Lancet Oncol 2011;12:735–42.
cross-ref  

5. Kobayashi S, Boggon TJ, Dayaram T, et al. EGFR mutation and resistance of non-small-cell lung cancer to gefitinib. N Engl J Med 2005;352:786–92.
cross-ref  pubmed  

6. Pao W, Miller VA, Politi KA, et al. Acquired resistance of lung adenocarcinomas to gefitinib or erlotinib is associated with a second mutation in the egfr kinase domain. PLoS Med 2005;2:e73.
cross-ref  

7. Maheswaran S, Sequist LV, Nagrath S, et al. Detection of mutations in EGFR in circulating lung-cancer cells. N Engl J Med 2008;359:366–77.
cross-ref  pubmed  pmc  

8. Su KY, Chen HY, Li KC, et al. Pretreatment epidermal growth factor receptor (EGFR) T790M mutation predicts shorter egfr tyrosine kinase inhibitor response duration in patients with non-small-cell lung cancer. J Clin Oncol 2012;30:433–40.
cross-ref  pubmed  

9. He J, Tan W, Tang X, Ma J. Variations in EGFR ctdna correlates to the clinical efficacy of afatinib in non small cell lung cancer with acquired resistance. Pathol Oncol Res 2017;23:307–15.
cross-ref  

10. Mandel P, Metais P. Nucleic acids of blood plasma in humans [French]. C R Seances Soc Biol Fil 1948;142:241–3.

11. Butt AN, Swaminathan R. Overview of circulating nucleic acids in plasma/serum. Ann N Y Acad Sci 2008;1137:236–42.
cross-ref  pubmed  

12. 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.
cross-ref  pubmed  pmc  

13. Tsumita T, Iwanaga M. Fate of injected deoxyribonucleic acid in mice. Nature 1963;198:1088–9.
cross-ref  pubmed  

14. Lo YM, Zhang J, Leung TN, Lau TK, Chang AM, Hjelm NM. Rapid clearance of fetal dna from maternal plasma. Am J Hum Genet 1999;64:218–24.
cross-ref  

15. Zaher ER, Anwar MM, Kohail HM, El-Zoghby SM, Abo-El-Eneen MS. Cell-free dna concentration and integrity as a screening tool for cancer. Indian J Cancer 2013;50:175–83.
cross-ref  

16. Brinkmann V, Reichard U, Goosmann C, et al. Neutrophil extracellular traps kill bacteria. Science 2004;303:1532–5.
cross-ref  

17. Greene MF, Phimister EG. Screening for trisomies in circulating dna. N Engl J Med 2014;370:874–5.
cross-ref  pubmed  

18. Beck J, Oellerich M, Schulz U, et al. Donor-derived cell-free dna is a novel universal biomarker for allograft rejection in solid organ transplantation. Transplant Proc 2015;47:2400–3.
cross-ref  

19. 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.
cross-ref  

20. Sorenson GD, Pribish DM, Valone FH, Memoli VA, Bzik DJ, Yao SL. Soluble normal and mutated dna sequences from single-copy genes in human blood. Cancer Epidemiol Biomarkers Prev 1994;3:67–71.
pubmed  

21. Vasioukhin V, Anker P, Maurice P, Lyautey J, Lederrey C, Stroun M. Point mutations of the N-ras gene in the blood plasma dna of patients with myelodysplastic syndrome or acute myelogenous leukaemia. Br J Haematol 1994;86:774–9.
cross-ref  pubmed  

22. Chen XQ, Stroun M, Magnenat JL, et al. Microsatellite alterations in plasma dna of small cell lung cancer patients. Nat Med 1996;2:1033–5.
cross-ref  pubmed  

23. Chiang PW, Beer DG, Wei WL, Orringer MB, Kurnit DM. Detection of erbB-2 amplifications in tumors and sera from esophageal carcinoma patients. Clin Cancer Res 1999;5:1381–6.
pubmed  

24. Combaret V, Audoynaud C, Iacono I, et al. Circulating MYCN dna as a tumor-specific marker in neuroblastoma patients. Cancer Res 2002;62:3646–8.
pubmed  

25. Esteller M, Sanchez-Cespedes M, Rosell R, Sidransky D, Baylin SB, Herman JG. Detection of aberrant promoter hypermethylation of tumor suppressor genes in serum dna from non-small cell lung cancer patients. Cancer Res 1999;59:67–70.
pubmed  

26. Wong IH, Lo YM, Zhang J, et al. Detection of aberrant p16 methylation in the plasma and serum of liver cancer patients. Cancer Res 1999;59:71–3.
pubmed  

27. Chorostowska-Wynimko J, Szpechcinski A. The impact of genetic markers on the diagnosis of lung cancer: a current perspective. J Thorac Oncol 2007;2:1044–51.
cross-ref  pubmed  

28. Underhill HR, Kitzman JO, Hellwig S, et al. Fragment length of circulating tumor dna. PLoS Genet 2016;12:e1006162.
cross-ref  

29. Diehl F, Schmidt K, Choti MA, et al. Circulating mutant dna to assess tumor dynamics. Nat Med 2008;14:985–90.
cross-ref  pubmed  pmc  

30. Diaz LA Jr, Bardelli A. Liquid biopsies: genotyping circulating tumor dna. J Clin Oncol 2014;32:579–86.
cross-ref  pubmed  pmc  

31. Whitcombe D, Theaker J, Guy SP, Brown T, Little S. Detection of pcr products using self-probing amplicons and fluorescence. Nat Biotechnol 1999;17:804–7.
cross-ref  pubmed  

32. Kimura H, Kasahara K, Kawaishi M, et al. Detection of epidermal growth factor receptor mutations in serum as a predictor of the response to gefitinib in patients with non-small-cell lung cancer. Clin Cancer Res 2006;12:3915–21.
cross-ref  pubmed  

33. Won JK, Keam B, Koh J, et al. Concomitant ALK translocation and EGFR mutation in lung cancer: a comparison of direct sequencing and sensitive assays and the impact on responsiveness to tyrosine kinase inhibitor. Ann Oncol 2015;26:348–54.
cross-ref  

34. Vogelstein B, Kinzler KW. Digital pcr. Proc Natl Acad Sci U S A 1999;96:9236–41.
cross-ref  pubmed  pmc  

35. Hindson BJ, Ness KD, Masquelier DA, et al. High-throughput droplet digital pcr system for absolute quantitation of dna copy number. Anal Chem 2011;83:8604–10.
cross-ref  pubmed  pmc  

36. 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.
cross-ref  pubmed  pmc  

37. Taniguchi K, Uchida J, Nishino K, et al. Quantitative detection of EGFR mutations in circulating tumor dna derived from lung adenocarcinomas. Clin Cancer Res 2011;17:7808–15.
cross-ref  pubmed  

38. Oxnard GR, Thress KS, Alden RS, et al. Association between plasma genotyping and outcomes of treatment with osimertinib (AZD9291) in advanced non-small-cell lung cancer. J Clin Oncol 2016;34:3375–82.
cross-ref  pubmed  pmc  

39. Ng SB, Turner EH, Robertson PD, et al. Targeted capture and massively parallel sequencing of 12 human exomes. Nature 2009;461:272–6.
cross-ref  

40. Jiang P, Chan CW, Chan KC, et al. Lengthening and shortening of plasma dna in hepatocellular carcinoma patients. Proc Natl Acad Sci U S A 2015;112:E1317–25.
cross-ref  pubmed  pmc  

41. Newman AM, Bratman SV, To J, et al. An ultrasensitive method for quantitating circulating tumor dna with broad patient coverage. Nat Med 2014;20:548–54.
cross-ref  pmc  

42. Newman AM, Lovejoy AF, Klass DM, et al. Integrated digital error suppression for improved detection of circulating tumor dna. Nat Biotechnol 2016;34:547–55.
cross-ref  pmc  

43. Murtaza M, Dawson SJ, Tsui DW, et al. Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma dna. Nature 2013;497:108–12.
cross-ref  pubmed  

44. Kuang Y, Rogers A, Yeap BY, et al. Noninvasive detection of EGFR T790M in gefitinib or erlotinib resistant non–small cell lung cancer. Clin Cancer Res 2009;15:2630–6.
cross-ref  pmc  

45. Xu F, Wu J, Xue C, et al. Comparison of different methods for detecting epidermal growth factor receptor mutations in peripheral blood and tumor tissue of non–small cell lung cancer as a predictor of response to gefitinib. Onco Targets Ther 2012;5:439–47.
pmc  

46. Liu X, Lu Y, Zhu G, et al. The diagnostic accuracy of pleural effusion and plasma samples versus tumour tissue for detection of EGFR mutation in patients with advanced non–small cell lung cancer: comparison of methodologies. J Clin Pathol 2013;66:1065–9.
cross-ref  pmc  

47. Douillard JY, Ostoros G, Cobo M, et al. Gefitinib treatment in EGFR mutated Caucasian nsclc: circulating-free tumor dna as a surrogate for determination of EGFR status. J Thorac Oncol 2014;9:1345–53.
cross-ref  pmc  

48. Weber B, Meldgaard P, Hager H, et al. Detection of EGFR mutations in plasma and biopsies from non–small cell lung cancer patients by allele-specific pcr assays. BMC Cancer 2014;14:294.
cross-ref  

49. Kim HR, Lee SY, Hyun DS, et al. Detection of EGFR mutations in circulating free dna by pna-mediated pcr clamping. J Exp Clin Cancer Res 2013;32:50.
cross-ref  

50. Yung TK, Chan KC, Mok TS, Tong J, To KF, Lo YM. Single-molecule detection of epidermal growth factor receptor mutations in plasma by microfluidics digital pcr in non–small cell lung cancer patients. Clin Cancer Res 2009;15:2076–84.
cross-ref  pubmed  

51. Ishii H, Azuma K, Sakai K, et al. Digital pcr analysis of plasma cell-free dna for non-invasive detection of drug resistance mechanisms in EGFR mutant nsclc: correlation with paired tumor samples. Oncotarget 2015;6:30850–8.
cross-ref  

52. Lee JY, Qing X, Xiumin W, et al. Longitudinal monitoring of EGFR mutations in plasma predicts outcomes of nsclc patients treated with egfrtkis: Korean Lung Cancer Consortium (klcc-12-02). Oncotarget 2016;7:6984–93.
pubmed  pmc  

53. Seki Y, Fujiwara Y, Kohno T, et al. Picoliter-droplet digital polymerase chain reaction–based analysis of cell-free plasma dna to assess EGFR mutations in lung adenocarcinoma that confer resistance to tyrosine-kinase inhibitors. Oncologist 2016;21:156–64.
cross-ref  pmc  

54. Takahama T, Sakai K, Takeda M, et al. Detection of the T790M mutation of EGFR in plasma of advanced non–small cell lung cancer patients with acquired resistance to tyrosine kinase inhibitors (West Japan Oncology Group 8014LTR study). Oncotarget 2016;7:58492–9.
cross-ref  pubmed  pmc  

55. Del Re M, Tiseo M, Bordi P, et al. Contribution of KRAS mutations and c.2369C>T (p.T790M) EGFR to acquired resistance to egfr-tkis in EGFR mutant nsclc: a study on circulating tumor dna. Oncotarget 2017;8:13611–19.

56. He J, Tan W, Ma J. Circulating tumor cells and dna for real-time EGFR detection and monitoring of non-small-cell lung cancer. Future Oncol 2017;13:787–97.
cross-ref  

57. Thress KS, Brant R, Carr TH, et al. EGFR mutation detection in ctdna from nsclc patient plasma: a cross-platform comparison of leading technologies to support the clinical development of AZD9291. Lung Cancer 2015;90:509–15.
cross-ref  pubmed  

58. Chai X, Ren P, Wei B, et al. A comparative study of EGFR oncogenic mutations in matching tissue and plasma samples from patients with advanced non–small cell lung carcinoma. Clin Chim Acta 2016;457:106–11.
cross-ref  

59. Wang Z, Cheng G, Han X, et al. Application of single-molecule amplification and resequencing technology for broad surveillance of plasma mutations in patients with advanced lung adenocarcinoma. J Mol Diagn 2017;19:169–81.
cross-ref  

60. Gautschi O, Bigosch C, Huegli B, et al. Circulating deoxyribonucleic acid as prognostic marker in non-small-cell lung cancer patients undergoing chemotherapy. J Clin Oncol 2004;22:4157–64.
cross-ref  

61. Tissot C, Toffart AC, Villar S, et al. Circulating free dna concentration is an independent prognostic biomarker in lung cancer. Eur Respir J 2015;46:1773–80.
cross-ref  pubmed  

62. Wei Z, Shah N, Deng C, Xiao X, Zhong T, Li X. Circulating dna addresses cancer monitoring in non small cell lung cancer patients for detection and capturing the dynamic changes of the disease. Springerplus 2016;5:531.
cross-ref  

63. Szpechcinski A, Chorostowska-Wynimko J, Struniawski R, et al. Cell-free dna levels in plasma of patients with non-small-cell lung cancer and inflammatory lung disease. Br J Cancer 2015;113:476–83.
cross-ref  pmc  

64. Abbosh C, Birkbak NJ, Wilson GA, et al. Phylogenetic ctdna analysis depicts early stage lung cancer evolution. Nature 2017;545:446–51.
cross-ref  

65. Chen S, Zhao J, Cui L, Liu Y. Urinary circulating dna detection for dynamic tracking of EGFR mutations for nsclc patients treated with egfr-tkis. Clin Transl Oncol 2017;19:332–40.
cross-ref  

66. Oxnard GR, Paweletz CP, Kuang Y, et al. Noninvasive detection of response and resistance in EGFR-mutant lung cancer using quantitative next-generation genotyping of cell-free plasma dna. Clin Cancer Res 2014;20:1698–705.
cross-ref  pubmed  pmc  

67. Sorensen BS, Wu L, Wei W, et al. Monitoring of epidermal growth factor receptor tyrosine kinase inhibitor–sensitizing and resistance mutations in the plasma dna of patients with advanced non–small cell lung cancer during treatment with erlotinib. Cancer 2014;120:3896–901.
cross-ref  pubmed  pmc  

68. Marchetti A, Palma JF, Felicioni L, et al. Early prediction of response to tyrosine kinase inhibitors by quantification of EGFR mutations in plasma of nsclc patients. J Thorac Oncol 2015;10:1437–43.
cross-ref  pubmed  

69. Mok T, Wu YL, Lee JS, et al. Detection and dynamic changes of EGFR mutations from circulating tumor dna as a predictor of survival outcomes in nsclc patients treated with first-line intercalated erlotinib and chemotherapy. Clin Cancer Res 2015;21:3196–203.
cross-ref  

70. Thress KS, Paweletz CP, Felip E, et al. Acquired EGFR C797S mutation mediates resistance to AZD9291 in non–small cell lung cancer harboring EGFR T790M. Nat Med 2015;21:560–2.
cross-ref  

71. Chabon JJ, Simmons AD, Lovejoy AF, et al. Circulating tumour dna profiling reveals heterogeneity of egfr inhibitor resistance mechanisms in lung cancer patients. Nat Commun 2016;7:11815.
cross-ref  

72. Ercan D, Choi HG, Yun CH, et al. EGFR mutations and resistance to irreversible pyrimidine-based egfr inhibitors. Clin Cancer Res 2015;21:3913–23.
cross-ref  

73. Niederst MJ, Hu H, Mulvey HE, et al. The allelic context of the C797S mutation acquired upon treatment with third-generation egfr inhibitors impacts sensitivity to subsequent treatment strategies. Clin Cancer Res 2015;21:3924–33.
cross-ref  pmc  

74. Cabanero M, Sangha R, Sheffield BS, et al. Management of EGFR-mutated non-small-cell lung cancer: practical implications from a clinical and pathology perspective. Curr Oncol 2017;24:111–19.
cross-ref  pmc  

75. Kato K, Uchida J, Kukita Y, et al. Numerical indices based on circulating tumor dna for the evaluation of therapeutic response and disease progression in lung cancer patients. Sci Rep 2016;6:29093.
cross-ref  


Correspondence to: Ming S. Tsao, 14-401 Princess Margaret Cancer Research Tower, 101 College Street, Toronto, Ontario M5G 1L7. E-mail: ming.tsao@uhn.ca

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Current Oncology, VOLUME 25, SUPPLEMENT 1, June 2018








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ISSN: 1198-0052 (Print) ISSN: 1718-7729 (Online)