|Year : 2017 | Volume
| Issue : 2 | Page : 39-45
Mutation detection with a liquid biopsy 96 mutation assay in cancer patients and healthy donors
Aaron Yun Chen, Glenn D Braunstein, Megan S Anselmo, Jair A Jaboni, Fernando Troy Viloria, Julie A Neidich, Xiang Li, Anja Kammesheidt
Research and Development, Pathway Genomics, San Diego, CA, USA
|Date of Submission||08-Nov-2016|
|Date of Acceptance||25-Dec-2016|
|Date of Web Publication||27-Apr-2017|
Pathway Genomics, 4755 Nexus Center Drive, San Diego, CA 92121
Source of Support: None, Conflict of Interest: None
Aim: Detection of circulating tumor DNA (ctDNA) holds promise as an adjunct to traditional cancer screening methods. To determine the sensitivity and specificity of ctDNA measurements, levels were measured in plasma from patients with a cancer diagnosis and a low-risk, healthy population.
Methods: We validated a plasma assay for detection of 96 ctDNA mutations in nine cancer genes (BRAF, CTNNB1, EGFR, FOXL2, GNAS, KRAS, NRAS, PIK3CA, and TP53). The assay reliably detects low levels of ctDNA, >2 copies. A total of 183 plasma samples from cancer patients were obtained along with plasma from 102 healthy individuals.
Results: ctDNA was detected in 24.0% of cancer patients (14.7% stage I, 18.8% II, 33.3% III, and 50.0% IV). ctDNA was not detected in 96% of low-risk subjects. Three subjects tested positive for one mutation and one subject tested positive for two mutations. ctDNA levels in positive subjects were followed for a year, and levels remained steady with small fluctuation. Multiple lung nodules found in the subject with two mutations have remained stable for 1 year. None of the healthy individuals was diagnosed with cancer in the year following study entry.
Conclusion: The sensitivity of the ctDNA assay was 24.0% in the mixture of cancers. The specificity was 96.1%. In the low cancer risk population, the apparent false positive detection rate for ctDNA at 1 year is 3.9%.
Keywords: Cancer, cell-free DNA, circulating tumor DNA, laboratory-developed test, liquid biopsy, mutation
|How to cite this article:|
Chen AY, Braunstein GD, Anselmo MS, Jaboni JA, Viloria FT, Neidich JA, Li X, Kammesheidt A. Mutation detection with a liquid biopsy 96 mutation assay in cancer patients and healthy donors. Cancer Transl Med 2017;3:39-45
|How to cite this URL:|
Chen AY, Braunstein GD, Anselmo MS, Jaboni JA, Viloria FT, Neidich JA, Li X, Kammesheidt A. Mutation detection with a liquid biopsy 96 mutation assay in cancer patients and healthy donors. Cancer Transl Med [serial online] 2017 [cited 2018 Apr 24];3:39-45. Available from: http://www.cancertm.com/text.asp?2017/3/2/39/202228
| Introduction|| |
Somatic mutations are linked to the activation, progression, or metastasis of a malignant tumor. The evaluation of somatic mutations has become relevant in assisting cancer diagnosis, treatment planning, monitoring drug response or resistance, and planning of alternative therapies.,,,,,, To date, the majority of these somatic mutations have been detected in tumor tissue obtained by biopsy or surgery. Circulating cell-free DNA (cfDNA) represents extracellular small DNA fragments (150–200 base pairs) released into the blood stream. The level of cfDNA in healthy individuals and those with nonmalignant conditions varies. Increased levels of cfDNA have been reported in patients with cancer and progression of disease in multiple cancer types. Thus, a portion of the cfDNA represents circulating tumor DNA (ctDNA), which contains the tumor-specific somatic mutations.,,,, Detection of this ctDNA offers a complementary method or possibly an alternative to mutation detection in tumor tissue since there is a high degree of concordance between variants found in tissue and blood ctDNA.
While the correlation between ctDNA and tumor stage has been more extensively studied, the role of ctDNA in screening for occult or early stage I tumors is yet to be established. In this study, we sought to evaluate the levels of ctDNA in patients with an established diagnosis of cancer to determine the true positive rate of ctDNA detection as well as in an unselected low-risk population to establish the false positive rate in presumably "healthy" individuals who provided 1 year of follow-up information.
| Methods|| |
Patients with cancer
Plasma samples (1–2 mL) from 183 patients (105 females, 77 males, 1 NA) with cancer were purchased from several commercial biobanks (Geneticist, Glendale, CA, USA; Proteogenex, Culver City, CA, USA; Conversant, Huntsville, AL, USA). The tumor types included breast (n = 20), colorectal (n = 18), lung (n = 31), ovarian (n = 16), pancreatic (n = 41), thyroid (n = 11), gastric (n = 25), endometrial (n = 1), prostate (n = 2), and miscellaneous head and neck cancers (n = 5) as well as skin/melanoma (n = 13). Clinical information on these samples included grade, tumor-node-metastasis stage, tumor size, and lymph node status [Supplementary Table 1 [Additional file 1]].
A total of 102 healthy donors (55 females and 47 males) were recruited under a Chesapeake Institutional Review Board approved standard protocol in August 2015. The donors were asymptomatic, had no personal history of cancer, and filled out a health questionnaire. The cohort was not selected for high-risk individuals, such as individuals with strong family history of cancer, advanced age, or those carrying a germline mutation in BRCA1/ 2 or other known hereditary cancer genes.
Circulating tumor DNA measurement
For the healthy participants, approximately 20 mL of whole blood was collected in cfDNA BCT blood collection tubes (Streck, Omaha, NE, USA). Plasma was separated and frozen in 5 mL aliquots. The cfDNA was subsequently isolated from 1 to 2 mL of plasma from the cancer patients and 5 mL of plasma from the healthy volunteers using the QIAmp Circulating Nucleic Acid Kit (Qiagen, Hilden, Germany). cfDNA yields were quantified using Qubit dsDNA HS Assay Kit (Thermo Fisher Scientific, Waltham, MA, USA). The cfDNA was processed with 96 mutation assay (CancerIntercept™, Pathway Genomics, San Diego, CA, USA), which uses a proprietary polymerase chain reaction-based amplification method and mutation enrichment, validated as a laboratory-developed test in-house. Next-generation sequencing and data acquisition were carried out using Illumina MiSeq (Illumina, San Diego, CA, USA). For data analysis, the FASTQ files generated on MiSeq were analyzed using an in-house analysis pipeline for mapping, variant calling, and quantification of ctDNA relative to input cfDNA.
The assay detects the presence of 96 "hotspot" ctDNA mutations in nine genes, BRAF, CTNNB1, EGFR, FOXL2, GNAS, KRAS, NRAS, PIK3CA, and TP53, even at very low copy levels. The mutations are listed in [Supplementary Table 2 [Additional file 2]] and were selected for their prevalence in various cancers. The assay has been validated with an overall > 78% analytical sensitivity at the level of 2–5 copies input, > 98% at 5–9 copies input, and 100% for > 9 copies input. Both the analytic specificity and precision (reproducibility) of the panel are over 99% for plasma samples (internal validation data not shown). Based on the performance characteristics of this panel, reporting is possible on as few as two copies of mutant ctDNA. Mutant ctDNA not specifically targeted by this assay is not detected.
| Results|| |
Patients with cancer
The ages of the cancer patients ranged from 28 to 88 (mean 61) years for 182 patients; one patient's age and gender are unknown. Forty-four of the 183 (24%) patients with cancer had ≥ 2 copies of ctDNA detected in their plasma, and several had more than one mutation detected [Supplementary Table 1]. Overall, a total of 77 total mutations, 41 of which unique, were detected in eight of the nine genes (except FOXL2) in the 44 patients positive for ctDNA. [Table 1]a provides the breakdown by tumor tissue, indicating that patients with colon, pancreatic, gastric, lung, thyroid, breast, endometrial, and ovarian cancers had detectable ctDNA with this 96 mutation assay. [Table 1]b provides the breakdown of ctDNA-positive patients by stage of disease. A lower proportion of patients with stage I disease had detectable ctDNA than those with more advanced disease, and the percentage of patients with detectable ctDNA increased with advancing disease: stage I = 14.7% (17/116), stage II = 18.8% (3/16), stage III = 33.3% (3/9), and stage IV = 50% (21/42). [Table 1]c provides the breakdown count of all ctDNA mutations (n = 77) grouped by gene and cancer type. In this study, the sensitivity of the assay is based on 1–2 mL of plasma available from the cancer patients, a lower plasma volume than the 5 mL used in our other clinical studies, including those with healthy volunteers (vide infra).
The ages of the healthy donors ranged from 20 to 71 (mean 40) years; 55 females and 47 males participated. Due to data confirmation, replication, and follow-up studies, a total of 134 individual plasma samples were processed. The average cfDNA yield from 5 mL plasma was 28.4 ± 13.5 ng (standard deviation). Yields were grouped by gender (male vs. female) and age (< 50 years vs. ≥ 50 years) and are listed in [Table 2]. There was no statistically significant difference between the gender and age groups. Overall, 98/102 (96%) individuals were negative for the 96 mutation panel. A single mutation was detected in three individuals at just above the detection threshold, and two mutations were detected in one individual [Table 3]. All four positive patients were over 50 years of age. Mutation levels were monitored every 2–3 months over a year's time in three of the four individuals, and the levels have remained relatively steady with small copy number variations [Table 4].
|Table 4: Follow-up circulating tumor DNA levels (% abundance mutant DNA relative to circulating tumor DNA input) in patients with circulating tumor DNA detected|
Click here to view
Case 1 is a 62-year-old female health-care worker who had a multinodular thyroid and low-level NRAS_G12S mutation in her cfDNA. Several nodules had been biopsied and were colloid nodules. Physical examinations and a recent mammogram had been normal.
Case 2 is a 53-year-old male artist with a history of heavy sun and solvent exposure. He had a TP53_R273H mutation in his cfDNA. He elected to withdraw from the study for further blood work after 6 months but did self-report as healthy on the 1-year follow-up questionnaire.
Case 3 is a 58-year-old female laboratory worker without known cancer risk who had a confirmed low copy GNAS_R201H mutation in her cfDNA. Her physician elected not to perform any imaging study, and during the ensuing 10 months, no health issues developed.
Case 4, a 66-year-old male steel worker, was found to have both KRAS and TP53 mutations. He underwent serial chest computed tomography scans, an abdominal magnetic resonance imaging and a colonoscopy. Two small-lung nodules were detected and had remained stable over the year. A benign-appearing renal cyst and an enlarged prostate without focal lesions were found. Three benign polyps (tubular adenomas) were removed at colonoscopy, but his mutant DNA levels did not fall following their removal.
One year after the initial enrollment, all participants were given the option to fill out a survey to gather information on a potential change of health status. Of the 102 initial individuals, 82 responded and none self-reported the development of a malignant neoplasm other than basal cell carcinomas of the skin.
| Discussion|| |
Numerous studies have shown that almost all malignancies harbor somatic mutations, and that these mutations may be detected in blood, which in some cases obviates the necessity of performing mutation analysis on tissue samples., The types of mutations that can be detected include single-nucleotide base substitutions, insertions, deletions, gene fusions, gene amplification, losses of heterozygosity, and methylation changes. ctDNA measurements have been shown to be useful for guiding initial targeted therapy, monitoring tumor growth or regression, and detecting emerging resistance to therapy in some tumors., Our study demonstrates that there is an increasing fraction of patients with cancer who have ctDNA detected in their plasma as the stage of the cancer increases, a finding that has been reported by other investigators previously., The frequency of detection is dependent on characteristics of the tumor including type, volume of neoplasm, vascularity, the types of somatic mutations present and degree of apoptosis or active DNA secretion, as well as assay characteristics, particularly the specific mutations measured, the sensitivity of the methods, and the volume of the blood sample.
There is vast interest in using ctDNA measurements to screen for cancer, the rationale being that early detection may lead to a higher cure rate than when tumors are discovered after clinical symptoms develop. However, for a screening test to be useful, it should be positive in many patients with the disease (clinically sensitive), and not be falsely positive in patients without the disease (clinically specific). Since few tests are 100% specific, the clinical utility of a screening test will depend on the prevalence of the disease of interest (i.e., cancer) in the population. Thus, in August 2015, we undertook an initial clinical study with 102 healthy volunteers to establish the false positive rate of our ctDNA test and found that 3.9% (4/102) had detectable ctDNA in their plasma. All the positive mutations were detected in donors over 50 years old. In the follow-up tests over 1 year, the level of mutations detected in cfDNA in those donors has remained stable. The source of the ctDNA in each of these patients is unknown, but since no cancer has been found over the year of follow-up, we conclude that these are false positive results. Indeed, other investigators have reported false positive ctDNA findings in healthy or benign disease control patients in studies that have screened patients for cancer or have examined the sensitivity of ctDNA measurements in patients with established cancer [Table 5].,,,,,,,,,,,,,,,,,,,,,,,,,,, Whether this represents the presence of occult, indolent cancers, benign neoplasms, or other nonmalignant disorders, or the results of the normal process of immune surveillance, which destroys cells that have undergone mutations, is unknown. Over the last year, the experience in our other ongoing clinical trials is in line with the initial observations in the 102 healthy donor series.
|Table 5: False positive rates for circulating tumor DNA measurements in published studies|
Click here to view
There is a reciprocal relationship between sensitivity and specificity. In our study, on healthy volunteers, three of the four individuals with detectable ctDNA had levels above 2 copies/5 mL but < 5 copies/5 mL of plasma. If we raise the level of a "positive" result to ≥ 5 copies, the false positive rate will decrease to just below 1%. However, our sensitivity would decrease from 14.7% (17/116) for stage I cancers to 6.0% (7/116), resulting in a 94% false negative rate. It should be noted that we were only able to obtain and use 1–2 mL of plasma from the patients with documented cancer rather than 5 mL from the healthy individuals. The lower volume would be expected to reduce our sensitivity for detecting cancer.
For screening patients in a low-risk population for cancer, it is best to keep the false positive rate low in order to avoid excessive testing and the potential emotional trauma that a healthy patient may experience after receiving a "positive" result. This strategy keeps the false positive rate low at the expense of an increase in the false negative rate of patients with cancer who are not picked up by the test. In contrast, it is often best to maximize the sensitivity of the test, accepting a higher false positive rate, in a high-risk population such as heavy smokers or patients with germline mutations that predispose to cancer (e.g., BRCA1 or BRCA2 carriers; TP53 mutations). In that setting, the number of true positive results should exceed the number of false positive results. This concept is well illustrated by the study by Gormally et al. who prospectively measured blood levels of KRAS2 and TP53 mutations in patients at high risk of cancers of the lung, bladder, and upper aerodigestive tract and leukemia matched with a low-risk control population with a median follow-up of 6.3 years. They found that 3% of the control population had TP53 mutations and 1% had KRAS2 mutations, and none developed cancer; however, 5.5% of the high-risk patients with TP53 mutations and 3.8% with KRAS2 mutations developed bladder cancer.
The approach that we have taken to balance the issues around sensitivity and specificity is to establish an "indeterminate" range between two and five copies of ctDNA, in which we obtain an additional blood sample within 3 months after the first blood draw. In our experience, patients with probable false positive results do not show a significant change in the ctDNA levels while those with proven cancer often have an increase (unpublished data). The clinical utility of this approach with this test is being studied in multiple trials, including a 1000-patient prospective study that started in December 2015 of individuals at increased risk for developing cancer (ClinicalTrials.gov identifier NCT02612350).
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Vogelstein B, Papadopoulos N, Velculescu VE, Zhou S, Diaz LA Jr., Kinzler KW. Cancer genome landscapes. Science
2013; 339 (6127): 1546–58.
Ascierto PA, Minor D, Ribas A, Lebbe C, O'Hagan A, Arya N, Guckert M, Schadendorf D, Kefford RF, Grob JJ, Hamid O, Amaravadi R, Simeone E, Wilhelm T, Kim KB, Long GV, Martin AM, Mazumdar J, Goodman VL, Trefzer U. Phase II trial (BREAK-2) of the BRAF inhibitor dabrafenib (GSK2118436) in patients with metastatic melanoma. J Clin Oncol
2013; 31 (26): 3205–11.
da Cunha Santos G, Shepherd FA, Tsao MS. EGFR mutations and lung cancer. Annu Rev Pathol
2011; 6: 49–69.
De Stefano A, Carlomagno C. Beyond KRAS: predictive factors of the efficacy of anti-EGFR monoclonal antibodies in the treatment of metastatic colorectal cancer. World J Gastroenterol
2014; 20 (29): 9732–43.
Engelman JA. Targeting PI3K signalling in cancer: opportunities, challenges and limitations. Nat Rev Cancer
2009; 9 (8): 550–62.
Hyman DM, Puzanov I, Subbiah V, Faris JE, Chau I, Blay JY, Wolf J, Raje NS, Diamond EL, Hollebecque A, Gervais R, Elez-Fernandez ME, Italiano A, Hofheinz RD, Hidalgo M, Chan E, Schuler M, Lasserre SF, Makrutzki M, Sirzen F, Veronese ML, Tabernero J, Baselga J. Vemurafenib in Multiple Nonmelanoma Cancers with BRAF V600 Mutations. N Engl J Med
2015; 373 (8): 726–3.
Rothschild SI. Targeted therapies in non-small cell lung cancer-beyond EGFR and ALK. Cancers
) 2015; 7 (2): 930–49.
García-Olmo DC, Domínguez C, García-Arranz M, Anker P, Stroun M, García-Verdugo JM, García-Olmo D. Cell-free nucleic acids circulating in the plasma of colorectal cancer patients induce the oncogenic transformation of susceptible cultured cells. Cancer Res
2010; 70 (2): 560–7.
Fleischhacker M, Schmidt B. Circulating nucleic acids (CNAs) and cancer – A survey. Biochim Biophys Acta
2007; 1775 (1): 181–232.
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 (4): 774–9.
Esposito A, Bardelli A, Criscitiello C, Colombo N, Gelao L, Fumagalli L, Minchella I, Locatelli M, Goldhirsch A, Curigliano G. Monitoring tumor-derived cell-free DNA in patients with solid tumors: clinical perspectives and research opportunities. Cancer Treat Rev
2014; 40 (5): 648–55.
Frattini M, Balestra D, Verderio P, Gallino G, Leo E, Sozzi G, Pierotti MA, Daidone MG. Reproducibility of a semiquantitative measurement of circulating DNA in plasma from neoplastic patients. J Clin Oncol
2005; 23 (13): 3163–4.
Catarino R, Ferreira MM, Rodrigues H, Coelho A, Nogal A, Sousa A, Medeiros R. Quantification of free circulating tumor DNA as a diagnostic marker for breast cancer. DNA Cell Biol
2008; 27 (8): 415–21.
Bettegowda C, Sausen M, Leary RJ, Kinde I, Wang Y, Agrawal N, Bartlett BR, Wang H, Luber B, Alani RM, Antonarakis ES, Azad NS, Bardelli A, Brem H, Cameron JL, Lee CC, Fecher LA, Gallia GL, Gibbs P, Le D, Giuntoli RL, Goggins M, Hogarty MD, Holdhoff M, Hong SM, Jiao Y, Juhl HH, Kim JJ, Siravegna G, Laheru DA, Lauricella C, Lim M, Lipson EJ, Marie SK, Netto GJ, Oliner KS, Olivi A, Olsson L, Riggins GJ, Sartore-Bianchi A, Schmidt K, Shih lM, Oba-Shinjo SM, Siena S, Theodorescu D, Tie J, Harkins TT, Veronese S, Wang TL, Weingart JD, Wolfgang CL, Wood LD, Xing D, Hruban RH, Wu J, Allen PJ, Schmidt CM, Choti MA, Velculescu VE, Kinzler KW, Vogelstein B, Papadopoulos N, Diaz LA Jr. Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci Transl Med
2014; 6 (224): 224ra24.
Castells A, Puig P, Móra J, Boadas J, Boix L, Urgell E, Solé M, CapellÁ G, Lluís F, Fernández-Cruz L, Navarro S, Farré A. K-ras mutations in DNA extracted from the plasma of patients with pancreatic carcinoma: diagnostic utility and prognostic significance. J Clin Oncol
1999; 17 (2): 578–84.
Dai MH, Zhao YP, Cai LX, Zhu Y. Combined detection of K-ras mutation and CA 19-9 level in plasma of patients with pancreatic cancer. Zhonghua Wai Ke Za Zhi
2003; 41 (5): 332–5. (in Chinese)
Dianxu F, Shengdao Z, Tianquan H, Yu J, Ruoqing L, Zurong Y, Xuezhi W. A prospective study of detection of pancreatic carcinoma by combined plasma K-ras mutations and serum CA19-9 analysis. Pancreas
2002; 25 (4): 336–41.
Feng D, Han T, Jiang Y, Yuan Z, Wang X, Jiang Z, Zhang S. Detection of K-ras gene mutations in DNA extracted from the plasma of patients with pancreatic cancer. Zhonghua Wai Ke Za Zhi
2000; 38 (10): 767–70. (in Chinese)
Maire F, Micard S, Hammel P, Voitot H, Lévy P, Cugnenc PH, Ruszniewski P, Puig PL. Differential diagnosis between chronic pancreatitis and pancreatic cancer: value of the detection of KRAS2 mutations in circulating DNA. Br J Cancer
2002; 87 (5): 551–4.
Mulcahy HE, Lyautey J, Lederrey C, qi Chen X, Anker P, Alstead EM, Ballinger A, Farthing MJ, Stroun M. A prospective study of K-ras mutations in the plasma of pancreatic cancer patients. Clin Cancer Res
1998; 4 (2): 271–5.
Theodor L, Melzer E, Sologov M, Idelman G, Friedman E, Bar-Meir S. Detection of pancreatic carcinoma: diagnostic value of K-ras mutations in circulating DNA from serum. Dig Dis Sci
1999; 44 (10): 2014–9.
Wang Y, Yamaguchi Y, Watanabe H, Ohtsubo K, Motoo Y, Sawabu N. Detection of p53gene mutations in the supernatant of pancreatic juice and plasma from patients with pancreatic carcinomas. Pancreas
2004; 28 (1): 13–9.
Kopreski MS, Benko FA, Kwee C, Leitzel KE, Eskander E, Lipton A, Gocke CD. Detection of mutant K-ras DNA in plasma or serum of patients with colorectal cancer. Br J Cancer
1997; 76 (10): 1293–9.
Mayall F, Jacobson G, Wilkins R, Chang B. Mutations of p53 gene can be detected in the plasma of patients with large bowel carcinoma. J Clin Pathol
1998; 51 (8): 611–3.
Koproski MS, Benko FA, Borys DJ, Khan A, McGarity TJ, Gocke CD. Somatic mutation screening: identification of individuals harboring K-ras mutations with the use of plasma DNA. J Natl Cancer Inst
2000; 92 (11): 918–23.
Wang JY, Hsieh JS, Chang MY, Huang TJ, Chen FM, Cheng TL, Alexandersen K, Huang YS, Tzou WS, Lin SR. Molecular detection of APC, K-ras, and p53 mutations in the serum of colorectal cancer patients as circulating biomarkers. World J Surg
2004; 28 (7): 721–6.
Perrone F, Lampis A, Bertan C, Verderio P, Ciniselli CM, Pizzamiglio S, Frattini M, Nucifora M, Molinari F, Gallino G, Gariboldi M, Meroni E, Leo E, Pierotti MA, Pilotti S. Circulating free DNA in a screening program for early colorectal cancer detection. Tumori
2014; 100 (2): 115–21.
Lu DD, Zhang XR. Plasma 249Ser p53 mutation in patients with hepatocellular carcinoma residing in a high risk area. J Cell Mol Med
2003; 7 (1): 89–92.
Huang XH, Sun LH, Lu DD, Sun Y, Ma LJ, Zhang XR, Huang J, Yu L. Codon 249 mutation in exon 7 of p53 gene in plasma DNA: maybe a new early diagnostic marker of hepatocellular carcinoma in Qidong risk area, China. World J Gastroenterol
2003; 9 (4): 692–5.
Jackson PE, Kuang SY, Wang JB, Strickland PT, Muñoz A, Kensler TW, Qian GS, Groopman JD. Prospective detection of codon 249 mutations in plasma of hepatocellular carcinoma patients. Carcinogenesis
2003; 24 (10): 1657–63.
Kimbi GC, Kew MC, Yu MC, Arakawa K, Hodkinson J. 249ser p53 mutation in the serum of black Southern African patients with hepatocellular carcinoma. J Gastroenterol Hepatol
2005; 20 (8): 1185–90.
Kirk GD, Camus-Randon AM, Mendy M, Goedert JJ, Merle P, Trépo C, Bréchot C, Hainaut P, Montesano R. Ser-249 p53 mutations in plasma DNA of patients with hepatocellular carcinoma from the Gambia. J Natl Cancer Inst
2000; 92 (2): 148–53.
Hosny G, Farahat N, Tayel H, Hainaut P. Ser-249 TP53 and CTNNB1 mutations in circulating free DNA of Egyptian patients with hepatocellular carcinoma versus chronic liver diseases. Cancer Lett
2008; 264 (2): 201–8.
Schlechte HH, Stelzer C, Weickmann S, Fleischhacker M, Schulze G. TP53 gene in blood plasma DNA of tumor patients. Ann N Y Acad Sci
2004; 1022: 61–9.
Allan JM, Hardie LJ, Briggs JA, Davidson LA, Watson JP, Pearson SB, Muers MF, Wild CP. Genetic alterations in bronchial mucosa and plasma DNA from individuals at high risk of lung cancer. Int J Cancer
2001; 91 (3): 359–65.
Freidin MB, Freydina DV, Leung M, Montero Fernandez A, Nicholson AG, Lim E. Circulating tumor DNA outperforms circulating tumor cells for KRAS mutation detection in thoracic malignancies. Clin Chem
2015; 61 (10): 1299–304.
Fernandez-Cuesta L, Perdomo S, Avogbe PH, Leblay N, Delhomme TM, Gaborieau V, Abedi-Ardekani B, Chanudet E, Olivier M, Zaridze D, Mukeria A, Vilensky M, Holcatova I, Polesel J, Simonato L, Canova C, Lagiou P, Brambilla C, Brambilla E, Byrnes G, Scelo G, Le Calvez-Kelm F, Foll M, McKay JD, Brennan P. Identification of circulating tumor DNA for the early detection of small-cell lung cancer. EBioMedicine
2016; 10: 117–23.
Sozzi G, Conte D, Mariani L, Lo Vullo S, Roz L, Lombardo C, Pierotti MA, Tavecchio L. Analysis of circulating tumor DNA in plasma at diagnosis and during follow-up of lung cancer patients. Cancer Res
2001; 61 (12): 4675–8.
Schwaederle M, Husain H, Fanta PT, Piccioni DE, Kesari S, Schwab RB, Banks KC, Lanman RB, Talasaz A, Parker BA, Kurzrock R. Detection rate of actionable mutations in diverse cancers using a biopsy-free (blood) circulating tumor cell DNA assay. Oncotarget
2016; 7 (9): 9707–17.
Wiggin M, Mai L, Walsh S, Marziali A. Low cost liquid biopsy by selective sequencing of mutant DNA [Abstract]. Presented at the 66th
Annual Meeting of The American Society of Human Genetics; 19 October, 2016, Vancouver, Canada.
Oshiro C, Kagara N, Naoi Y, Shimoda M, Shimomura A, Maruyama N, Shimazu K, Kim SJ, Noguchi S. PIK3CA mutations in serum DNA are predictive of recurrence in primary breast cancer patients. Breast Cancer Res Treat
2015; 150 (2): 299–307.
Sanmamed MF, Fernández-Landázuri S, Rodríguez C, Zárate R, Lozano MD, Zubiri L, Perez-Gracia JL, Martín-Algarra S, González A. Quantitative cell-free circulating BRAFV600E mutation analysis by use of droplet digital PCR in the follow-up of patients with melanoma being treated with BRAF inhibitors. Clin Chem
2015; 61 (1): 297–304.
Gormally E, Vineis P, Matullo G, Veglia F, Caboux E, Le Roux E, Peluso M, Garte S, Guarrera S, Munnia A, Airoldi L, Autrup H, Malaveille C, Dunning A, Overvad K, Tjønneland A, Lund E, Clavel-Chapelon F, Boeing H, Trichopoulou A, Palli D, Krogh V, Tumino R, Panico S, Bueno-de-Mesquita HB, Peeters PH, Pera G, Martinez C, Dorronsoro M, Barricarte A, Navarro C, Quirós JR, Hallmans G, Day NE, Key TJ, Saracci R, Kaaks R, Riboli E, Hainaut P. TP53 and KRAS2 mutations in plasma DNA of healthy subjects and subsequent cancer occurrence: a prospective study. Cancer Res
2006; 66 (13): 6871–6.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]