1932

Abstract

Because cancer is caused by an accumulation of genetic mutations, mutant DNA released by tumors can be used as a highly specific biomarker for cancer. Although this principle was described decades ago, the advent and falling costs of next-generation sequencing have made the use of tumor DNA as a biomarker increasingly practical. This review surveys the use of cellular and cell-free DNA for the detection of cancer, with a focus on recent technological developments and applications to solid tumors. It covers () key principles and technology enabling the highly sensitive detection of tumor DNA; () assessment of tumor DNA in plasma, including for genotyping, minimal residual disease detection, and early detection of localized cancer; () detection of tumor DNA in body cavity fluids, such as urine or cerebrospinal fluid; and () challenges posed to the use of tumor DNA as a biomarker by the phenomenon of benign clonal expansions.

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2021-01-24
2024-03-29
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Literature Cited

  1. 1. 
    Wan JCM, Massie C, Garcia-Corbacho J, Mouliere F, Brenton JD et al. 2017. Liquid biopsies come of age: towards implementation of circulating tumour DNA. Nat. Rev. Cancer 17:223–38
    [Google Scholar]
  2. 2. 
    Sidransky D, Von Eschenbach A, Tsai YC, Jones P, Summerhayes I et al. 1991. Identification of p53 gene mutations in bladder cancers and urine samples. Science 252:706–9
    [Google Scholar]
  3. 3. 
    Sidransky D, Tokino T, Hamilton SR, Kinzler KW, Levin B et al. 1992. Identification of ras oncogene mutations in the stool of patients with curable colorectal tumors. Science 256:102–5
    [Google Scholar]
  4. 4. 
    Mao L, Hruban RH, Boyle JO, Tockman M, Sidransky D 1994. Detection of oncogene mutations in sputum precedes diagnosis of lung cancer. Cancer Res 54:1634–37
    [Google Scholar]
  5. 5. 
    Lo YMD, Corbetta N, Chamberlain PF, Rai V, Sargent IL et al. 1997. Presence of fetal DNA in maternal plasma and serum. Lancet 350:485–87
    [Google Scholar]
  6. 6. 
    Bianchi DW, Chiu RWK. 2018. Sequencing of circulating cell-free DNA during pregnancy. N. Engl. J. Med. 379:464–73
    [Google Scholar]
  7. 7. 
    Fan HC, Gu W, Wang J, Blumenfeld YJ, El-Sayed YY, Quake SR 2012. Non-invasive prenatal measurement of the fetal genome. Nature 487:320–24
    [Google Scholar]
  8. 8. 
    Chan KCA, Jiang P, Sun K, Cheng YKY, Tong YK et al. 2016. Second generation noninvasive fetal genome analysis reveals de novo mutations, single-base parental inheritance, and preferred DNA ends. PNAS 113:E8159–68
    [Google Scholar]
  9. 9. 
    Lo YMD, Chan KCA, Sun H, Chen EZ, Jiang P et al. 2010. Maternal plasma DNA sequencing reveals the genome-wide genetic and mutational profile of the fetus. Sci. Transl. Med. 2:61ra91
    [Google Scholar]
  10. 10. 
    Kitzman JO, Snyder MW, Ventura M, Lewis AP, Qiu R et al. 2012. Noninvasive whole-genome sequencing of a human fetus. Sci. Transl. Med. 4:137ra76
    [Google Scholar]
  11. 11. 
    Camunas-Soler J, Lee H, Hudgins L, Hintz SR, Blumenfeld YJ et al. 2018. Noninvasive prenatal diagnosis of single-gene disorders by use of droplet digital PCR. Clin. Chem. 64:336–45
    [Google Scholar]
  12. 12. 
    De Vlaminck I, Valantine HA, Snyder TM, Strehl C, Cohen G et al. 2014. Circulating cell-free DNA enables noninvasive diagnosis of heart transplant rejection. Sci. Transl. Med. 6:241ra77
    [Google Scholar]
  13. 13. 
    Sun K, Jiang P, Chan KCA, Wong J, Cheng YKY et al. 2015. Plasma DNA tissue mapping by genome-wide methylation sequencing for noninvasive prenatal, cancer, and transplantation assessments. PNAS 112:E5503–12
    [Google Scholar]
  14. 14. 
    Merker JD, Oxnard GR, Compton C, Diehn M, Hurley P et al. 2018. Circulating tumor DNA analysis in patients with cancer: American Society of Clinical Oncology and College of American Pathologists joint review. Arch. Pathol. Lab. Med. 142:1242–53
    [Google Scholar]
  15. 15. 
    Heitzer E, Haque IS, Roberts CES, Speicher MR 2019. Current and future perspectives of liquid biopsies in genomics-driven oncology. Nat. Rev. Genet. 20:71–88
    [Google Scholar]
  16. 16. 
    Diaz LA Jr., Bardelli A. 2014. Liquid biopsies: genotyping circulating tumor DNA. J. Clin. Oncol. 32:579–86
    [Google Scholar]
  17. 17. 
    Kopreski MS, Benko FA, Kwee C, Leitzel KE, Eskander E et al. 1997. Detection of mutant K-ras DNA in plasma or serum of patients with colorectal cancer. Br. J. Cancer 76:1293–99
    [Google Scholar]
  18. 18. 
    Sorenson GD, Pribish DM, Valone FH, Memoli VA, Bzik DJ, Yao SL 1994. Soluble normal and mutated DNA sequences from single-copy genes in human blood. Cancer Epidemiol. Biomark. Prev. 3:67–71
    [Google Scholar]
  19. 19. 
    Kwapisz D. 2017. The first liquid biopsy test approved. Is it a new era of mutation testing for non-small cell lung cancer. Ann. Transl. Med. 5:46
    [Google Scholar]
  20. 20. 
    Vogelstein B, Kinzler KW. 1999. Digital PCR. PNAS 96:9236–41
    [Google Scholar]
  21. 21. 
    Dressman D, Yan H, Traverso G, Kinzler KW, Vogelstein B 2003. Transforming single DNA molecules into fluorescent magnetic particles for detection and enumeration of genetic variations. PNAS 100:8817–22
    [Google Scholar]
  22. 22. 
    Taly V, Pekin D, Benhaim L, Kotsopoulos SK, Le Corre D et al. 2013. Multiplex picodroplet digital PCR to detect KRAS mutations in circulating DNA from the plasma of colorectal cancer patients. Clin. Chem. 59:1722–31
    [Google Scholar]
  23. 23. 
    Oxnard GR, Paweletz CP, Kuang Y, Mach SL, O'Connell A et al. 2014. Noninvasive detection of response and resistance in EGFR-mutant lung cancer using quantitative next-generation genotyping of cell-free plasma DNA. Clin. Cancer Res. 20:1698–705
    [Google Scholar]
  24. 24. 
    Groot VP, Mosier S, Javed AA, Teinor JA, Gemenetzis G et al. 2019. Circulating tumor DNA as a clinical test in resected pancreatic cancer. Clin. Cancer Res. 25:4973–84
    [Google Scholar]
  25. 25. 
    Watanabe M, Kawaguchi T, Isa S, Ando M, Tamiya A et al. 2015. Ultra-sensitive detection of the pretreatment EGFR T790M mutation in non–small cell lung cancer patients with an EGFR-activating mutation using droplet digital PCR. Clin. Cancer Res. 21:3552–60
    [Google Scholar]
  26. 26. 
    Kinde I, Wu J, Papadopoulos N, Kinzler KW, Vogelstein B 2011. Detection and quantification of rare mutations with massively parallel sequencing. PNAS 108:9530–35
    [Google Scholar]
  27. 27. 
    Schmitt MW, Kennedy SR, Salk JJ, Fox EJ, Hiatt JB, Loeb LA 2012. Detection of ultra-rare mutations by next-generation sequencing. PNAS 109:14508–13
    [Google Scholar]
  28. 28. 
    Schmitt MW, Fox EJ, Prindle MJ, Reid-Bayliss KS, True LD et al. 2015. Sequencing small genomic targets with high efficiency and extreme accuracy. Nat. Methods 12:423–25
    [Google Scholar]
  29. 29. 
    Newman AM, Lovejoy AF, Klass DM, Kurtz DM, Chabon JJ et al. 2016. Integrated digital error suppression for improved detection of circulating tumor DNA. Nat. Biotechnol. 34:547–55
    [Google Scholar]
  30. 30. 
    Krimmel JD, Schmitt MW, Harrell MI, Agnew KJ, Kennedy SR et al. 2016. Ultra-deep sequencing detects ovarian cancer cells in peritoneal fluid and reveals somatic TP53 mutations in noncancerous tissues. PNAS 113:6005–10
    [Google Scholar]
  31. 31. 
    Tewhey R, Warner JB, Nakano M, Libby B, Medkova M et al. 2009. Microdroplet-based PCR enrichment for large-scale targeted sequencing. Nat. Biotechnol. 27:1025–31
    [Google Scholar]
  32. 32. 
    Forshew T, Murtaza M, Parkinson C, Gale D, Tsui DW et al. 2012. Noninvasive identification and monitoring of cancer mutations by targeted deep sequencing of plasma DNA. Sci. Transl. Med. 4:136ra68
    [Google Scholar]
  33. 33. 
    Newman AM, Bratman SV, To J, Wynne JF, Eclov NC et al. 2014. An ultrasensitive method for quantitating circulating tumor DNA with broad patient coverage. Nat. Med. 20:548–54
    [Google Scholar]
  34. 34. 
    Phallen J, Sausen M, Adleff V, Leal A, Hruban C et al. 2017. Direct detection of early-stage cancers using circulating tumor DNA. Sci. Transl. Med. 9:eaan2415
    [Google Scholar]
  35. 35. 
    Lanman RB, Mortimer SA, Zill OA, Sebisanovic D, Lopez R et al. 2015. Analytical and clinical validation of a digital sequencing panel for quantitative, highly accurate evaluation of cell-free circulating tumor DNA. PLOS ONE 10:e0140712
    [Google Scholar]
  36. 36. 
    Moding EJL, Liu Y, Nabet BY, Chabon JJ, Chaudhuri AA et al. 2020. Circulating tumor DNA dynamics predict benefit from consolidation immunotherapy in locally advanced non-small-cell lung cancer. Nat. Cancer 1:176–83
    [Google Scholar]
  37. 37. 
    Azad TD, Chaudhuri AA, Fang P, Qiao Y, Esfahani MS et al. 2019. Circulating tumor DNA analysis for detection of minimal residual disease after chemoradiotherapy for localized esophageal cancer. Gastroenterology 158:494–505.e6
    [Google Scholar]
  38. 38. 
    Chaudhuri AA, Chabon JJ, Lovejoy AF, Newman AM, Stehr H et al. 2017. Early detection of molecular residual disease in localized lung cancer by circulating tumor DNA profiling. Cancer Discov 7:1394–403
    [Google Scholar]
  39. 39. 
    Chen G, Mosier S, Gocke CD, Lin MT, Eshleman JR 2014. Cytosine deamination is a major cause of baseline noise in next-generation sequencing. Mol. Diagn. Ther. 18:587–93
    [Google Scholar]
  40. 40. 
    Gerstung M, Beisel C, Rechsteiner M, Wild P, Schraml P et al. 2012. Reliable detection of subclonal single-nucleotide variants in tumour cell populations. Nat. Commun. 3:811
    [Google Scholar]
  41. 41. 
    Cohen JD, Li L, Wang Y, Thoburn C, Afsari B et al. 2018. Detection and localization of surgically resectable cancers with a multi-analyte blood test. Science 359:926–30
    [Google Scholar]
  42. 42. 
    Knouse KAD, Davoli T, Elledge SJ, Amon A 2017. Aneuploidy in cancer: seq-ing answers to old questions. Annu. Rev. Cancer Biol. 1:335–54
    [Google Scholar]
  43. 43. 
    Douville C, Springer S, Kinde I, Cohen JD, Hruban RH et al. 2018. Detection of aneuploidy in patients with cancer through amplification of long interspersed nucleotide elements (LINEs). PNAS 115:1871–76
    [Google Scholar]
  44. 44. 
    Douville CC, Cohen JD, Ptak J, Popoli M, Schaefer J et al. 2020. Assessing aneuploidy with repetitive element sequencing. PNAS 117:4858–63
    [Google Scholar]
  45. 45. 
    Mouliere F, Chandrananda D, Piskorz AM, Moore EK, Morris J et al. 2018. Enhanced detection of circulating tumor DNA by fragment size analysis. Sci. Transl. Med. 10:eaat4921
    [Google Scholar]
  46. 46. 
    Underhill HR, Kitzman JO, Hellwig S, Welker NC, Daza R et al. 2016. Fragment length of circulating tumor DNA. PLOS Genet 12:e1006162
    [Google Scholar]
  47. 47. 
    Jiang P, Chan CW, Chan KCA, Cheng SH, Wong J et al. 2015. Lengthening and shortening of plasma DNA in hepatocellular carcinoma patients. PNAS 112:E1317–25
    [Google Scholar]
  48. 48. 
    Jiang P, Sun K, Tong YK, Cheng SH, Cheng THT et al. 2018. Preferred end coordinates and somatic variants as signatures of circulating tumor DNA associated with hepatocellular carcinoma. PNAS 115:E10925–33
    [Google Scholar]
  49. 49. 
    Cristiano S, Leal A, Phallen J, Fiksel J, Adleff V et al. 2019. Genome-wide cell-free DNA fragmentation in patients with cancer. Nature 570:385–89
    [Google Scholar]
  50. 50. 
    Snyder MW, Kircher M, Hill AJ, Daza RM, Shendure J 2016. Cell-free DNA comprises an in vivo nucleosome footprint that informs its tissues-of-origin. Cell 164:57–68
    [Google Scholar]
  51. 51. 
    Shen SY, Singhania R, Fehringer G, Chakravarthy A, Roehrl MHA et al. 2018. Sensitive tumour detection and classification using plasma cell-free DNA methylomes. Nature 563:579–83
    [Google Scholar]
  52. 52. 
    Lehmann-Werman R, Neiman D, Zemmour H, Moss J, Magenheim J et al. 2016. Identification of tissue-specific cell death using methylation patterns of circulating DNA. PNAS 113:E1826–34
    [Google Scholar]
  53. 53. 
    Li J, Wang L, Mamon H, Kulke MH, Berbeco R, Makrigiorgos GM 2008. Replacing PCR with COLD-PCR enriches variant DNA sequences and redefines the sensitivity of genetic testing. Nat. Med. 14:579–84
    [Google Scholar]
  54. 54. 
    Guha M, Castellanos-Rizaldos E, Liu P, Mamon H, Makrigiorgos GM 2013. Differential strand separation at critical temperature: a minimally disruptive enrichment method for low-abundance unknown DNA mutations. Nucleic Acids Res 41:e50
    [Google Scholar]
  55. 55. 
    Song C, Liu Y, Fontana R, Makrigiorgos A, Mamon H et al. 2016. Elimination of unaltered DNA in mixed clinical samples via nuclease-assisted minor-allele enrichment. Nucleic Acids Res 44:e146
    [Google Scholar]
  56. 56. 
    Gu W, Crawford ED, O'Donovan BD, Wilson MR, Chow ED et al. 2016. Depletion of Abundant Sequences by Hybridization (DASH): using Cas9 to remove unwanted high-abundance species in sequencing libraries and molecular counting applications. Genome Biol 17:41
    [Google Scholar]
  57. 57. 
    Aalipour A, Dudley JC, Park SM, Murty S, Chabon JJ et al. 2018. Deactivated CRISPR associated protein 9 for minor-allele enrichment in cell-free DNA. Clin. Chem. 64:307–16
    [Google Scholar]
  58. 58. 
    Adalsteinsson VA, Ha G, Freeman SS, Choudhury AD, Stover DG et al. 2017. Scalable whole-exome sequencing of cell-free DNA reveals high concordance with metastatic tumors. Nat. Commun. 8:1324
    [Google Scholar]
  59. 59. 
    Razavi P, Li BT, Brown DN, Jung B, Hubbell E et al. 2019. High-intensity sequencing reveals the sources of plasma circulating cell-free DNA variants. Nat. Med. 25:1928–37
    [Google Scholar]
  60. 60. 
    Dudley JC, Schroers-Martin J, Lazzareschi DV, Shi WY, Chen SB et al. 2019. Detection and surveillance of bladder cancer using urine tumor DNA. Cancer Discov 9:500–9
    [Google Scholar]
  61. 61. 
    Stetson DA, Ahmed A, Xu X, Nuttall BRB, Lubinski TJ et al. 2019. Orthogonal comparison of four plasma NGS tests with tumor suggests technical factors are a major source of assay discordance. JCO Precis. Oncol. 3: https://doi.org/10.1200/PO.18.00191
    [Crossref] [Google Scholar]
  62. 62. 
    Jamal-Hanjani M, Wilson GA, McGranahan N, Birkbak NJ, Watkins TBK et al. 2017. Tracking the evolution of non-small-cell lung cancer. N. Engl. J. Med. 376:2109–21
    [Google Scholar]
  63. 63. 
    Reiter JG, Makohon-Moore AP, Gerold JM, Heyde A, Attiyeh MA et al. 2018. Minimal functional driver gene heterogeneity among untreated metastases. Science 361:1033–37
    [Google Scholar]
  64. 64. 
    Bettegowda C, Sausen M, Leary RJ, Kinde I, Wang Y et al. 2014. Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci. Transl. Med. 6:224ra24
    [Google Scholar]
  65. 65. 
    Diaz LA Jr., Williams RT, Wu J, Kinde I, Hecht JR et al. 2012. The molecular evolution of acquired resistance to targeted EGFR blockade in colorectal cancers. Nature 486:537–40
    [Google Scholar]
  66. 66. 
    Mattox AK, Bettegowda C, Zhou S, Papadopoulos N, Kinzler KW, Vogelstein B 2019. Applications of liquid biopsies for cancer. Sci. Transl. Med. 11:eaay1984
    [Google Scholar]
  67. 67. 
    Murtaza M, Dawson SJ, Tsui DW, Gale D, Forshew T et al. 2013. Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA. Nature 497:108–12
    [Google Scholar]
  68. 68. 
    Chabon JJ, Simmons AD, Lovejoy AF, Esfahani MS, Newman AM et al. 2016. Circulating tumour DNA profiling reveals heterogeneity of EGFR inhibitor resistance mechanisms in lung cancer patients. Nat. Commun. 7:11815
    [Google Scholar]
  69. 69. 
    Thress KS, Paweletz CP, Felip E, Cho BC, Stetson D et al. 2015. Acquired EGFR C797S mutation mediates resistance to AZD9291 in non–small cell lung cancer harboring iEGFR T790M. Nat. Med. 21:560–62
    [Google Scholar]
  70. 70. 
    Yao W, Mei C, Nan X, Hui L 2016. Evaluation and comparison of in vitro degradation kinetics of DNA in serum, urine and saliva: a qualitative study. Gene 590:142–48
    [Google Scholar]
  71. 71. 
    To EW, Chan KCA, Leung SF, Chan LY, To KF et al. 2003. Rapid clearance of plasma Epstein-Barr virus DNA after surgical treatment of nasopharyngeal carcinoma. Clin. Cancer Res. 9:3254–59
    [Google Scholar]
  72. 72. 
    Chen K, Zhao H, Shi Y, Yang F, Wang LT et al. 2019. Perioperative dynamic changes in circulating tumor DNA in patients with lung cancer (DYNAMIC). Clin. Cancer Res. 25:7058–67
    [Google Scholar]
  73. 73. 
    Diehl F, Schmidt K, Choti MA, Romans K, Goodman S et al. 2008. Circulating mutant DNA to assess tumor dynamics. Nat. Med. 14:985–90
    [Google Scholar]
  74. 74. 
    Dawson SJ, Tsui DW, Murtaza M, Biggs H, Rueda OM et al. 2013. Analysis of circulating tumor DNA to monitor metastatic breast cancer. N. Engl. J. Med. 368:1199–209
    [Google Scholar]
  75. 75. 
    Tie J, Wang Y, Tomasetti C, Li L, Springer S et al. 2016. Circulating tumor DNA analysis detects minimal residual disease and predicts recurrence in patients with stage II colon cancer. Sci. Transl. Med. 8:346ra92
    [Google Scholar]
  76. 76. 
    Garcia-Murillas I, Schiavon G, Weigelt B, Ng C, Hrebien S et al. 2015. Mutation tracking in circulating tumor DNA predicts relapse in early breast cancer. Sci. Transl. Med. 7:302ra133
    [Google Scholar]
  77. 77. 
    Abbosh C, Birkbak NJ, Wilson GA, Jamal-Hanjani M, Constantin T et al. 2017. Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution. Nature 545:446–51
    [Google Scholar]
  78. 78. 
    Phallen J, Leal A, Woodward BD, Forde PM, Naidoo J et al. 2019. Early noninvasive detection of response to targeted therapy in non–small cell lung cancer. Cancer Res 79:1204–13
    [Google Scholar]
  79. 79. 
    Kurtz DM, Esfahani MS, Scherer F, Soo J, Jin MC et al. 2019. Dynamic risk profiling using serial tumor biomarkers for personalized outcome prediction. Cell 178:699–713.e19
    [Google Scholar]
  80. 80. 
    Kalinich M, Haber DA. 2018. Cancer detection: seeking signals in blood. Science 359:866–67
    [Google Scholar]
  81. 81. 
    Aravanis AM, Lee M, Klausner RD 2017. Next-generation sequencing of circulating tumor DNA for early cancer detection. Cell 168:571–74
    [Google Scholar]
  82. 82. 
    Inst. Health Metr. Eval. (IHME) 2018. Global Burden of Disease Study 2017 Seattle, WA: IHME
  83. 83. 
    Chan KCA, Woo JKS, King A, Zee BCY, Lam WKJ et al. 2017. Analysis of plasma Epstein-Barr virus DNA to screen for nasopharyngeal cancer. N. Engl. J. Med. 377:513–22
    [Google Scholar]
  84. 84. 
    Lam WKJ, Jiang P, Chan KCA, Cheng SH, Zhang H et al. 2018. Sequencing-based counting and size profiling of plasma Epstein-Barr virus DNA enhance population screening of nasopharyngeal carcinoma. PNAS 115:E5115–24
    [Google Scholar]
  85. 85. 
    Lam WKJ, Jiang P, Chan KCA, Peng W, Shang H et al. 2019. Methylation analysis of plasma DNA informs etiologies of Epstein-Barr virus-associated diseases. Nat. Commun. 10:3256
    [Google Scholar]
  86. 86. 
    Ulz P, Thallinger GG, Auer M, Graf R, Kashofer K et al. 2016. Inferring expressed genes by whole-genome sequencing of plasma DNA. Nat. Genet. 48:1273–78
    [Google Scholar]
  87. 87. 
    Ulz P, Perakis S, Zhou Q, Moser T, Belic J et al. 2019. Inference of transcription factor binding from cell-free DNA enables tumor subtype prediction and early detection. Nat. Commun. 10:4666
    [Google Scholar]
  88. 88. 
    Kinde I, Munari E, Faraj SF, Hruban RH, Schoenberg M et al. 2013. TERT promoter mutations occur early in urothelial neoplasia and are biomarkers of early disease and disease recurrence in urine. Cancer Res 73:7162–67
    [Google Scholar]
  89. 89. 
    Springer SU, Chen CH, Rodriguez Pena MDC, Li L, Douville C et al. 2018. Non-invasive detection of urothelial cancer through the analysis of driver gene mutations and aneuploidy. eLife 7:e32143
    [Google Scholar]
  90. 90. 
    Cheng THT, Jiang P, Teoh JYC, Heung MMS, Tam JCW et al. 2019. Noninvasive detection of bladder cancer by shallow-depth genome-wide bisulfite sequencing of urinary cell-free DNA for methylation and copy number profiling. Clin. Chem. 65:927–36
    [Google Scholar]
  91. 91. 
    Patel KM, van der Vos KE, Smith CG, Mouliere F, Tsui D et al. 2017. Association of plasma and urinary mutant DNA with clinical outcomes in muscle invasive bladder cancer. Sci. Rep. 7:5554
    [Google Scholar]
  92. 92. 
    Ge G, Peng D, Guan B, Zhou Y, Gong Y et al. 2019. Urothelial carcinoma detection based on copy number profiles of urinary cell-free DNA by shallow whole-genome sequencing. Clin. Chem. 6:188–98
    [Google Scholar]
  93. 93. 
    Togneri FS, Ward DG, Foster JM, Devall AJ, Wojtowicz P et al. 2016. Genomic complexity of urothelial bladder cancer revealed in urinary cfDNA. Eur. J. Hum. Genet. 24:1167–74
    [Google Scholar]
  94. 94. 
    Xia Y, Huang CC, Dittmar R, Du M, Wang Y et al. 2016. Copy number variations in urine cell free DNA as biomarkers in advanced prostate cancer. Oncotarget 7:35818–31
    [Google Scholar]
  95. 95. 
    Tsui NB, Jiang P, Chow KC, Su X, Leung TY et al. 2012. High resolution size analysis of fetal DNA in the urine of pregnant women by paired-end massively parallel sequencing. PLOS ONE 7:e48319
    [Google Scholar]
  96. 96. 
    Goldman JW, Karlovich C, Sequist LV, Melnikova V, Franovic A et al. 2018. EGFR genotyping of matched urine, plasma, and tumor tissue in patients with non-small-cell lung cancer treated with rociletinib, an EGFR tyrosine kinase inhibitor. JCO Precis. Oncol. 2: https://doi.org/10.1200/PO.17.00116
    [Crossref] [Google Scholar]
  97. 97. 
    Lu T, Li J. 2017. Clinical applications of urinary cell-free DNA in cancer: current insights and promising future. Am. J. Cancer Res. 7:2318–32
    [Google Scholar]
  98. 98. 
    Reckamp KL, Melnikova VO, Karlovich C, Sequist LV, Camidge DR et al. 2016. A highly sensitive and quantitative test platform for detection of NSCLC EGFR mutations in urine and plasma. J. Thorac. Oncol. 11:1690–700
    [Google Scholar]
  99. 99. 
    Umansky SR, Tomei LD. 2006. Transrenal DNA testing: progress and perspectives. Expert Rev. Mol. Diagn. 6:153–63
    [Google Scholar]
  100. 100. 
    Su YH, Wang M, Block TM, Landt O, Botezatu I et al. 2004. Transrenal DNA as a diagnostic tool: important technical notes. Ann. N.Y. Acad. Sci. 1022:81–89
    [Google Scholar]
  101. 101. 
    Botezatu I, Serdyuk O, Potapova G, Shelepov V, Alechina R et al. 2000. Genetic analysis of DNA excreted in urine: a new approach for detecting specific genomic DNA sequences from cells dying in an organism. Clin. Chem. 46:1078–84
    [Google Scholar]
  102. 102. 
    Su YH, Wang M, Brenner DE, Ng A, Melkonyan H et al. 2004. Human urine contains small, 150 to 250 nucleotide-sized, soluble DNA derived from the circulation and may be useful in the detection of colorectal cancer. J. Mol. Diagn. 6:101–7
    [Google Scholar]
  103. 103. 
    Shekhtman EM, Anne K, Melkonyan HS, Robbins DJ, Warsof SL, Umansky SR 2009. Optimization of transrenal DNA analysis: detection of fetal DNA in maternal urine. Clin. Chem. 55:723–29
    [Google Scholar]
  104. 104. 
    Fujii T, Barzi A, Sartore-Bianchi A, Cassingena A, Siravegna G et al. 2017. Mutation-enrichment next-generation sequencing for quantitative detection of KRAS mutations in urine cell-free DNA from patients with advanced cancers. Clin. Cancer Res. 23:3657–66
    [Google Scholar]
  105. 105. 
    Arbyn M, Anttila A, Jordan J, Ronco G, Schenck U et al. 2010. European Guidelines for quality assurance in cervical cancer screening. Second edition—summary document. Ann. Oncol. 21:448–58
    [Google Scholar]
  106. 106. 
    Cibas ES, Ducatman BS. 2014. Cytology: Diagnostic Principles and Clinical Correlates Philadelphia: Elsevier
  107. 107. 
    Kinde I, Bettegowda C, Wang Y, Wu J, Agrawal N et al. 2013. Evaluation of DNA from the Papanicolaou test to detect ovarian and endometrial cancers. Sci. Transl. Med. 5:167ra4
    [Google Scholar]
  108. 108. 
    Wang Y, Li L, Douville C, Cohen JD, Yen TT et al. 2018. Evaluation of liquid from the Papanicolaou test and other liquid biopsies for the detection of endometrial and ovarian cancers. Sci. Transl. Med. 10:eaap8793
    [Google Scholar]
  109. 109. 
    Maritschnegg E, Wang Y, Pecha N, Horvat R, Van Nieuwenhuysen E et al. 2015. Lavage of the uterine cavity for molecular detection of Müllerian duct carcinomas: a proof-of-concept study. J. Clin. Oncol. 33:4293–300
    [Google Scholar]
  110. 110. 
    Wang Y, Sundfeldt K, Mateoiu C, Shih M, Kurman RJ et al. 2016. Diagnostic potential of tumor DNA from ovarian cyst fluid. eLife 5:e15175
    [Google Scholar]
  111. 111. 
    Springer S, Masica DL, Dal Molin M, Douville C, Thoburn CJ et al. 2019. A multimodality test to guide the management of patients with a pancreatic cyst. Sci. Transl. Med. 11:eaav4772
    [Google Scholar]
  112. 112. 
    Springer S, Wang Y, Dal Molin M, Masica DL, Jiao Y et al. 2015. A combination of molecular markers and clinical features improve the classification of pancreatic cysts. Gastroenterology 149:1501–10
    [Google Scholar]
  113. 113. 
    Rosenbaum MW, Jones M, Dudley JC, Le LP, Iafrate AJ, Pitman MB 2017. Next-generation sequencing adds value to the preoperative diagnosis of pancreatic cysts. Cancer Cytopathol 125:41–47
    [Google Scholar]
  114. 114. 
    Jones M, Zheng Z, Wang J, Dudley J, Albanese E et al. 2016. Impact of next-generation sequencing on the clinical diagnosis of pancreatic cysts. Gastrointest. Endosc. 83:140–48
    [Google Scholar]
  115. 115. 
    Dudley JC, Zheng Z, McDonald T, Le LP, Dias-Santagata D et al. 2016. Next-generation sequencing and fluorescence in situ hybridization have comparable performance characteristics in the analysis of pancreaticobiliary brushings for malignancy. J. Mol. Diagn. 18:124–30
    [Google Scholar]
  116. 116. 
    Diehl F, Schmidt K, Durkee KH, Moore KJ, Goodman SN et al. 2008. Analysis of mutations in DNA isolated from plasma and stool of colorectal cancer patients. Gastroenterology 135:489–98
    [Google Scholar]
  117. 117. 
    Ahlquist DA, Zou H, Domanico M, Mahoney DW, Yab TC et al. 2012. Next-generation stool DNA test accurately detects colorectal cancer and large adenomas. Gastroenterology 142:248–56
    [Google Scholar]
  118. 118. 
    Ahlquist DA, Taylor WR, Mahoney DW, Zou H, Domanico M et al. 2012. The stool DNA test is more accurate than the plasma septin 9 test in detecting colorectal neoplasia. Clin. Gastroenterol. Hepatol. 10:272–77.e1
    [Google Scholar]
  119. 119. 
    Nikiforova MN, Wald AI, Roy S, Durso MB, Nikiforov YE 2013. Targeted next-generation sequencing panel (ThyroSeq) for detection of mutations in thyroid cancer. J. Clin. Endocrinol. Metab. 98:E1852–60
    [Google Scholar]
  120. 120. 
    Nikiforov YE, Nikiforova MN. 2011. Molecular genetics and diagnosis of thyroid cancer. Nat. Rev. Endocrinol. 7:569–80
    [Google Scholar]
  121. 121. 
    Steward DL, Carty SE, Sippel RS, Yang SP, Sosa JA et al. 2019. Performance of a multigene genomic classifier in thyroid nodules with indeterminate cytology: a prospective blinded multicenter study. JAMA Oncol 5:204–12
    [Google Scholar]
  122. 122. 
    Boyle JO, Mao L, Brennan JA, Koch WM, Eisele DW et al. 1994. Gene mutations in saliva as molecular markers for head and neck squamous cell carcinomas. Am. J. Surg. 168:429–32
    [Google Scholar]
  123. 123. 
    Wang Y, Springer S, Mulvey CL, Silliman N, Schaefer J et al. 2015. Detection of somatic mutations and HPV in the saliva and plasma of patients with head and neck squamous cell carcinomas. Sci. Transl. Med. 7:293ra104
    [Google Scholar]
  124. 124. 
    Ahn SM, Chan JY, Zhang Z, Wang H, Khan Z et al. 2014. Saliva and plasma quantitative polymerase chain reaction-based detection and surveillance of human papillomavirus-related head and neck cancer. JAMA Otolaryngol. Head Neck Surg. 140:846–54
    [Google Scholar]
  125. 125. 
    Hubers AJ, Prinsen CF, Sozzi G, Witte BI, Thunnissen E 2013. Molecular sputum analysis for the diagnosis of lung cancer. Br. J. Cancer 109:530–37
    [Google Scholar]
  126. 126. 
    De Mattos-Arruda L, Mayor R, Ng CKY, Weigelt B, Martinez-Ricarte F et al. 2015. Cerebrospinal fluid-derived circulating tumour DNA better represents the genomic alterations of brain tumours than plasma. Nat. Commun. 6:8839
    [Google Scholar]
  127. 127. 
    Miller AM, Shah RH, Pentsova EI, Pourmaleki M, Briggs S et al. 2019. Tracking tumour evolution in glioma through liquid biopsies of cerebrospinal fluid. Nature 565:654–58
    [Google Scholar]
  128. 128. 
    Pan C, Diplas BH, Chen X, Wu Y, Xiao X et al. 2019. Molecular profiling of tumors of the brainstem by sequencing of CSF-derived circulating tumor DNA. Acta Neuropathol 137:297–306
    [Google Scholar]
  129. 129. 
    Zheng MM, Li YS, Jiang BY, Tu HY, Tang WF et al. 2019. Clinical utility of cerebrospinal fluid cell-free DNA as liquid biopsy for leptomeningeal metastases in ALK-rearranged NSCLC. J. Thorac. Oncol. 14:924–32
    [Google Scholar]
  130. 130. 
    Juratli TA, Stasik S, Zolal A, Schuster C, Richter S et al. 2018. TERT promoter mutation detection in cell-free tumor-derived DNA in patients with IDH wild-type glioblastomas: a pilot prospective study. Clin. Cancer Res. 24:5282–91
    [Google Scholar]
  131. 131. 
    Panditharatna E, Kilburn LB, Aboian MS, Kambhampati M, Gordish-Dressman H et al. 2018. Clinically relevant and minimally invasive tumor surveillance of pediatric diffuse midline gliomas using patient-derived liquid biopsy. Clin. Cancer Res. 24:5850–59
    [Google Scholar]
  132. 132. 
    Mouliere F, Mair R, Chandrananda D, Marass F, Smith CG et al. 2018. Detection of cell-free DNA fragmentation and copy number alterations in cerebrospinal fluid from glioma patients. EMBO Mol. Med. 10:e9323
    [Google Scholar]
  133. 133. 
    Martinez-Ricarte F, Mayor R, Martinez-Sáez E, Rubio-Pérez C, Pineda E et al. 2018. Molecular diagnosis of diffuse gliomas through sequencing of cell-free circulating tumor DNA from cerebrospinal fluid. Clin. Cancer Res. 24:2812–19
    [Google Scholar]
  134. 134. 
    Li YS, Jiang BY, Yang JJ, Zhang XC, Zhang Z et al. 2018. Unique genetic profiles from cerebrospinal fluid cell-free DNA in leptomeningeal metastases of EGFR-mutant non-small-cell lung cancer: a new medium of liquid biopsy. Ann. Oncol. 29:945–52
    [Google Scholar]
  135. 135. 
    Huang TY, Piunti A, Lulla RR, Qi J, Horbinski CM et al. 2017. Detection of Histone H3 mutations in cerebrospinal fluid-derived tumor DNA from children with diffuse midline glioma. Acta Neuropathol. Commun. 5:28
    [Google Scholar]
  136. 136. 
    Pentsova EI, Shah RH, Tang J, Boire A, You D et al. 2016. Evaluating cancer of the central nervous system through next-generation sequencing of cerebrospinal fluid. J. Clin. Oncol. 34:2404–15
    [Google Scholar]
  137. 137. 
    Wang Y, Springer S, Zhang M, McMahon KW, Kinde I et al. 2015. Detection of tumor-derived DNA in cerebrospinal fluid of patients with primary tumors of the brain and spinal cord. PNAS 112:9704–9
    [Google Scholar]
  138. 138. 
    Foote MB, Papadopoulos N, Diaz LA Jr 2015. Genetic classification of gliomas: refining histopathology. Cancer Cell 28:9–11
    [Google Scholar]
  139. 139. 
    Risques RA, Kennedy SR. 2018. Aging and the rise of somatic cancer-associated mutations in normal tissues. PLOS Genet 14:e1007108
    [Google Scholar]
  140. 140. 
    Kato S, Lippman SM, Flaherty KT, Kurzrock R 2016. The conundrum of genetic “drivers” in benign conditions. J. Natl. Cancer Inst. 108:djw036
    [Google Scholar]
  141. 141. 
    Genovese G, Kahler AK, Handsaker RE, Lindberg J, Rose SA et al. 2014. Clonal hematopoiesis and blood-cancer risk inferred from blood DNA sequence. N. Engl. J. Med. 371:2477–87
    [Google Scholar]
  142. 142. 
    Jaiswal S, Fontanillas P, Flannick J, Manning A, Grauman PV et al. 2014. Age-related clonal hematopoiesis associated with adverse outcomes. N. Engl. J. Med. 371:2488–98
    [Google Scholar]
  143. 143. 
    Young AL, Challen GA, Birmann BM, Druley TE 2016. Clonal haematopoiesis harbouring AML-associated mutations is ubiquitous in healthy adults. Nat. Commun. 7:12484
    [Google Scholar]
  144. 144. 
    Nair N, Camacho-Vanegas O, Rykunov D, Dashkoff M, Camacho SC et al. 2016. Genomic analysis of uterine lavage fluid detects early endometrial cancers and reveals a prevalent landscape of driver mutations in women without histopathologic evidence of cancer: a prospective cross-sectional study. PLOS Med 13:e1002206
    [Google Scholar]
  145. 145. 
    Anglesio MS, Papadopoulos N, Ayhan A, Nazeran TM, Noe M et al. 2017. Cancer-associated mutations in endometriosis without cancer. N. Engl. J. Med. 376:1835–48
    [Google Scholar]
  146. 146. 
    Martincorena I, Roshan A, Gerstung M, Ellis P, Van Loo P et al. 2015. Tumor evolution. High burden and pervasive positive selection of somatic mutations in normal human skin. Science 348:880–86
    [Google Scholar]
  147. 147. 
    Martincorena I, Fowler JC, Wabik A, Lawson ARJ, Abascal F et al. 2018. Somatic mutant clones colonize the human esophagus with age. Science 362:911–17
    [Google Scholar]
  148. 148. 
    Yokoyama A, Kakiuchi N, Yoshizato T, Nannya Y, Suzuki H et al. 2019. Age-related remodelling of oesophageal epithelia by mutated cancer drivers. Nature 565:312–17
    [Google Scholar]
  149. 149. 
    Yoshida K, Gowers KHC, Lee-Six H, Chandrasekharan DP, Coorens T et al. 2020. Tobacco smoking and somatic mutations in human bronchial epithelium. Nature 578:266–72
    [Google Scholar]
  150. 150. 
    Yizhak K, Aguet F, Kim J, Hess JM, Kubler K et al. 2019. RNA sequence analysis reveals macroscopic somatic clonal expansion across normal tissues. Science 364:eaaw0726
    [Google Scholar]
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