Droplet digitálna PCR ako nový diagnostický nástroj

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Autori: B. Váňová ^1,2; B. Malicherova ²; T. Burjanivová ³; A. Liskova ⁴; K. Janikova ^2,5; K. Jasek ²; Z. Lasabová ³; M. Tatár ⁵; L. Plank ⁶
Pôsobisko autorov: Martin´s Center of Immunology, Ltd., Martin, Slovakia ¹; Biomedical Center Martin JFM CU, Martin, Slovakia ²; Department of Molecular Biology JFM CU, Martin, Slovakia ³; Clinic of Obstetrics and Gynecology JFM CU and University Hospital in Martin, Slovakia ⁴; Department of Pathological Physiology JFM CU, Martin, Slovakia ⁵; Department of Pathological Anatomy, JFM CU and University Hospital in Martin, Slovakia ⁶
Vyšlo v časopise: Klin Onkol 2021; 34(1): 33-39
Kategória: Review
doi: https://doi.org/10.48095/ccko202133

Súhrn

Východiská: Podstatou moderných postupov liečby onkologických pacientov je v dnešnej dobe zacielenie konkrétnych molekúl zapojených do bunkovej signalizácie asociovanej s nádorovou iniciáciou a progresiou. Úspech uvedeného prístupu závisí od správne zvoleného diagnostického testu s vysokou citlivosťou, ktorý identifikuje výskyt a hladinu vybraných biomarkerov u pacientov pre selekciu tých, ktorí budú na liečivo reagovať a budú z neho benefitovať. Vývoj nových technológií a modernizácia tých známych, prispievajú k inováciám molekulárnej charakterizácie karcinómov, ktorá umožňuje detekciu mutačného stavu pacienta s vysokou citlivosťou a špecifickosťou. Cieľ: V práci diskutujeme o využití polymerázovej reťazovej reakcie (PCR) tretej generácie, tzv. droplet digitálnej PCR (ddPCR), v molekulárnej diagnostike karcinómov. Podľa štúdií uvedených v našom prehľade predstavuje ddPCR sľubný nástroj pri vytváraní genetického profilu pacientov s onkologickým ochorením. Optimalizácia a presná validácia môžu preto umožniť postupnú implementáciu ddPCR do klinickej praxe v oblasti onkológie.

Klíčová slova:

rakovina – nádorové biomarkery – molekulárna diagnostika – ddPCR

Zdroje

1. World Health Organization. Cancer. [online]. Available from: https: //www.who.int/health-topics/cancer#tab=tab_1.

2. Hanahan D, Weinberg RA. The hallmarks of cancer. Cell 2000; 100 (1): 57–70. doi: 10.1016/s0092-8674 (00) 81 683-9.

3. American Cancer Society. Cancer facts & figures 2018. [online]. Available from: https: //www.cancer.org/cancer/colon-rectal-cancer/about/what-is-colorectal-cancer.html.

4. Marks EI, Yee NS. Molecular genetics and targeted therapeutics in biliary tract carcinoma. World J Gastroenterol 2016; 22 (4): 1335–1347. doi: 10.3748/wjg.v22.i4.1335.

5. Verma M. Personalized medicine and cancer. J Pers Med 2012; 2 (1): 1–14. doi: 10.3390/jpm2010001.

6. Gil J, Laczmanska I, Pesz KA et al. Personalized medicine in oncology. New perspectives in management of gliomas. Contemp Oncol 2018; 22 (1A): 1–2. doi: 10.5114/wo.2018.73872.

7. National Comprehensive Cancer Network. Targeted therapy. [online]. Available from: https: //www.nccn.org/patients/resources/life_with_cancer/treatment/targeted_therapy.aspx.

8. Taube SE. Biomarkers in oncology: trials and tribulations. Ann N Y Acad Sci 2009; 1180: 111–118. doi: 10.1111/j.1749-6632.2009.05019.x.

9. Simon R. Clinical trial designs for evaluating the medical utility of prognostic and predictive biomarkers in oncology. Pers Med 2010; 7 (1): 33–47. doi: 10.2217/pme. 09.49.

10. Deschoolmeester V, Baay M, Specenier P et al. A review of the most promising biomarkers in colorectal cancer: one step closer to targeted therapy. The Oncologist 2010; 15 (7): 699–731. doi: 10.1634/theoncologist.2010-0025.

11. Mullis K, Faloona F, Scharf S et al. Specific enzymatic amplification of DNA in vitro: the polymerase chain reaction. Cold Spring Harb Symp Quant Biol 1986; 51 (Pt 1): 263–273. doi: 10.1101/sqb.1986.051.01.032.

12. Schaad NW, Frederick RD. Real-time PCR and its application for rapid plant disease diagnostics. Can J Plant Pathol 2002; 24 (3): 250–258.

13. Baker M. Digital PCR hits its stride. Nat Methods 2012; 9 (6): 541–544.

14. Hrstka R, Kolářová T, Michalová E et al. Vývoj metod založených na PCR a jejich aplikace v onkologickém výzkumu a praxi. Klin Onkol 2014; 27 (Suppl 1): S69–S74. doi: 10.14735/amko20141s69.

15. Liao P, Huang Y. Digital PCR: endless frontier of ‘divide and conquer.’ Micromachines (Basel) 2017; 8 (8): 231. doi: 10.3390/mi8080231.

16. Digital PCR – SK. [online]. Available from: //www.thermofisher.com/uk/en/home/life-science/pcr/digital-pcr.html.

17. Zhang C, Xing D. Miniaturized PCR chips for nucleic acid amplification and analysis: latest advances and future trends. Nucleic Acids Res 2007; 35 (13): 4223–4237. doi: 10.1093/nar/gkm389.

18. 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 (22): 8604–8610. doi: 10.1021/ac202028g.

19. Pinheiro LB, Coleman VA, Hindson CM et al. Evaluation of a droplet digital polymerase chain reaction format for DNA copy number quantification. Anal Chem 2012; 84 (2): 1003–1011. doi: 10.1021/ac202578x.

20. RainDance Digital PCR Reagents and Consumables. Life Science Research | Bio-Rad. [online]. Available from: https: //www.bio-rad.com/en-dk/product/raindance-digital-pcr-reagents-consumables?ID=Q8L21TE08O1Y.

21. Droplet DigitalTM PCR (ddPCRTM) Technology | LSR | Bio-Rad. [online]. Available from: https: //www.bio-rad.com/en-dk/applications-technologies/droplet-digital-pcr-ddpcr-technology?ID=MDV31M4VY.

22. Diehl F, Li M, He Y et al. BEAMing: single-molecule PCR on microparticles in water-in-oil emulsions. Nat Methods 2006; 3 (7): 551–559. doi: 10.1038/nmeth898.

23. BEAMing Technology Overview | OncoBEAMTM. [online]. Available from: https: //www.oncobeam.com/oncobeam-technology/technology-overview.

24. Sensitivity, specificity and limit of detection in dPCR BIO-RAD2016. [online]. Available from: https: //www.bio-rad.com/en-dk/category/genomics?ID=2d11dcf8-2dbe-47a5-a1de-8315abd3c17e.

25. Slutsky B. Handbook of chemometrics and qualimetrics: part A. In: Massart DL, Vandeginste BG, Buydens LM et al. Data handling in science and technology, vol. 20A. Amsterdam: Elsevier 1997: Xvii + 867.

26. Strain MC, Lada SM, Luong T et al. Highly precise measurement of HIV DNA by droplet digital PCR. PloS One 2013; 8 (4): e55943. doi: 10.1371/journal.pone.0055943.

27. Maheshwari Y, Selvaraj V, Hajeri S et al. Application of droplet digital PCR for quantitative detection of Spiroplasma citri in comparison with real time PCR. PLOS One 2017; 12 (9): e0184751. doi: 10.1371/journal.pone.0184751.

28. Suo T, Liu X, Feng J et al. ddPCR: a more accurate tool for SARS-CoV-2 detection in low viral load specimens. Emerg Microbes Infect 2020; 9 (1): 1259–1268. doi: 10.1080/22221751.2020.1772678.

29. Hudecova I, Jiang P, Davies J et al. Noninvasive detection of F8 int22h-related inversions and sequence variants in maternal plasma of hemophilia carriers. Blood 2017; 130 (3): 340–347. doi: 10.1182/blood-2016-12-755017.

30. Camunas-Soler J, Lee H, Hudgins L et al. Noninvasive prenatal diagnosis of single-gene disorders by use of droplet digital PCR. Clin Chem 2018; 64 (2): 336–345. doi: 10.1373/clinchem.2017.278101.

31. Kinugasa H, Nouso K, Tanaka T et al. Droplet digital PCR measurement of HER2 in patients with gastric cancer. Br J Cancer 2015; 112 (10): 1652–1625. doi: 10.1038/bjc.2015.129.

32. Malicherova B, Burjanivova T, Grendar M et al. Droplet digital PCR for detection of BRAF V600E mutation in formalin-fixed, paraffin-embedded melanoma tissues: a comparison with Cobas® 4800, Sanger sequencing, and allele-specific PCR. Am J Transl Res 2018; 10 (11): 3773–3781.

33. Vanova B, Kalman M, Jasek K et al. Droplet digital PCR revealed high concordance between primary tumors and lymph node metastases in multiplex screening of KRAS mutations in colorectal cancer. Clin Exp Med 2019; 19 (2): 219–224. doi: 10.1007/s10238-019-00545-y.

34. Li H, Bai R, Zhao Z et al. Application of droplet digital PCR to detect the pathogens of infectious diseases. Biosci Rep 2018; 38 (6): BSR20181170. doi: 10.1042/BSR20181170.

35. Mu D, Yan L, Tang H et al. A sensitive and accurate quantification method for the detection of hepatitis B virus covalently closed circular DNA by the application of a droplet digital polymerase chain reaction amplification system. Biotechnol Lett 2015; 37 (10): 2063–2073. doi: 10.1007/s10529-015-1890-5.

36. Yang J, Han X, Liu A et al. Use of digital droplet PCR to detect mycobacterium tuberculosis DNA in whole blood-derived DNA samples from patients with pulmonary and extrapulmonary tuberculosis. Front Cell Infect Microbiol 2017; 7: 369. doi: 10.3389/fcimb.2017.00369.

37. Koepfli C, Nguitragool W, Hofmann NE et al. Sensitive and accurate quantification of human malaria parasites using droplet digital PCR (ddPCR). Sci Rep 2016; 16 (6): 39183.

38. Mujezinovic F, Alfirevic Z. Procedure-related complications of amniocentesis and chorionic villous sampling: a systematic review. Obstet Gynecol 2007; 110 (3): 687–694. doi: 10.1097/01.AOG.0000278820.54029.e3.

39. Lun FMF, Tsui NBY, Chan KCA et al. Noninvasive prenatal diagnosis of monogenic diseases by digital size selection and relative mutation dosage on DNA in maternal plasma. Proc Natl Acad Sci USA 2008; 105 (50): 19920–19925. doi: 10.1073/pnas.0810373105.

40. Tsui NBY, Kadir RA, Chan KCA et al. Noninvasive prenatal diagnosis of hemophilia by microfluidics digital PCR analysis of maternal plasma DNA. Blood 2011; 117 (13): 3684–3691. doi: 10.1182/blood-2010-10-310789.

41. Barrett AN, McDonnell TCR, Chan KCA et al. Digital PCR analysis of maternal plasma for noninvasive detection of sickle cell anemia. Clin Chem 2012; 58 (6): 1026–1032.

42. El Khattabi LA, Rouillac-Le Sciellour C, Le Tessier D et al. Could digital PCR be an alternative as a non-invasive prenatal test for trisomy 21: a proof of concept study. PLoS One 2016; 11 (5): e0155009. doi: 10.1371/journal.pone.0155009.

43. D’Aversa E, Breveglieri G, Pellegatti P et al. Non-invasive fetal sex diagnosis in plasma of early weeks pregnants using droplet digital PCR. Mol Med 2018; 24 (1): 14.

44. O’Brien H, Hyland C, Schoeman E et al. Non-invasive prenatal testing (NIPT) for fetal Kell, Duffy and Rh blood group antigen prediction in alloimmunised pregnant women: power of droplet digital PCR. Br J Haematol 2020; 189 (3): e90–e94. doi: 10.1111/bjh.16500.

45. Mazaika E, Homsy J. Digital droplet PCR: CNV analysis and other applications. Curr Protoc Hum Genet 2014; 82: 7.24.1–13. doi: 10.1002/0471142905.hg0724s82.

46. Van Wesenbeeck L, Janssens L, Meeuws H et al. Droplet digital PCR is an accurate method to assess methylation status on FFPE samples. Epigenetics 2018; 13 (3): 207–213. doi: 10.1080/15592294.2018.1448679.

47. Kinugasa H, Nouso K, Miyahara K et al. Detection of K-ras gene mutation by liquid biopsy in patients with pancreatic cancer. Cancer. 2015; 121 (13): 2271–2280. doi: 10.1002/cncr.29364.

48. Hughesman CB, Lu XJD, Liu KYP et al. Detection of clinically relevant copy number alterations in oral cancer progression using multiplexed droplet digital PCR. Sci Rep 2017; 7 (1): 11855. doi: 10.1038/s41598-017-11201-4.

49. Shlien A, Malkin D. Copy number variations and cancer. Genome Med 2009; 1 (6): 62.

50. Liu YJ, Shen D, Yin X et al. HER2, MET and FGFR2 oncogenic driver alterations define distinct molecular segments for targeted therapies in gastric carcinoma. Br J Cancer 2014; 110 (5): 1169–1178. doi: 10.1038/bjc.2014.61.

51. Zhang Y, Tang E-T, Du Z. Detection of MET gene copy number in cancer samples using the droplet digital PCR method. PloS One 2016; 11 (1): e0146784. doi: 10.1371/journal.pone.0146784.

52. Lewandowska J, Bartoszek A. DNA methylation in cancer development, diagnosis and therapy--multiple opportunities for genotoxic agents to act as methylome disruptors or remediators. Mutagenesis 2011; 26 (4): 475–487. doi: 10.1093/mutage/ger019.

53. Koch A, Joosten SC, Feng Z et al. Analysis of DNA methylation in cancer: location revisited. Nat Rev Clin Oncol 2018; 15 (7): 459–466. doi: 10.1038/s41571-018-0004-4.

54. Hayashi M, Guerrero-Preston R, Sidransky D et al. PAX5 methylation detection by droplet digital PCR for ultra-sensitive deep surgical margins analysis of head and neck squamous cell carcinoma. Cancer Prev Res (Phila) 2015; 8 (11): 1017–1026. doi: 10.1158/1940-6207.CAPR-15-0180.

55. Menschikowski M, Jandeck C, Friedemann M et al. Identification of rare levels of methylated tumor DNA fragments using an optimized bias based pre-amplification-digital droplet PCR (OBBPA-ddPCR). Oncotarget 2018; 9 (90): 36137–36150. doi: 10.18632/oncotarget.26315.

56. Chibon F. Cancer gene expression signatures – the rise and fall? Eur J Cancer Oxf Engl (1990) 2013; 49 (8): 2000–2009. doi: 10.1016/j.ejca.2013.02.021.

57. Rapin N, Bagger FO, Jendholm J et al. Comparing cancer vs normal gene expression profiles identifies new disease entities and common transcriptional programs in AML patients. Blood 2014; 123 (6): 894–904. doi: 10.1182/blood-2013-02-485771.

58. Yan M, Schwaederle M, Arguello D et al. HER2 expression status in diverse cancers: review of results from 37,992 patients. Cancer Metastasis Rev 2015; 34 (1): 157–164. doi: 10.1007/s10555-015-9552-6.

59. Wang Q, Jia P, Li F et al. Detecting somatic point mutations in cancer genome sequencing data: a comparison of mutation callers. Genome Med 2013; 5 (10): 91. doi: 10.1186/gm495.

60. Milbury CA, Zhong Q, Lin J et al. Determining lower limits of detection of digital PCR assays for cancer-related gene mutations. Biomol Detect Quantif 2014; 1 (1): 8–22. doi: 10.1016/j.bdq.2014.08.001.

61. Decraene C, Silveira AB, Bidard F-C et al. Multiple hotspot mutations scanning by single droplet digital PCR. Clin Chem 2018; 64 (2): 317–328. doi: 10.1373/clinchem.2017.272518.

62. Denis JA, Patroni A, Guillerm E et al. Droplet digital PCR of circulating tumor cells from colorectal cancer patients can predict KRAS mutations before surgery. Mol Oncol 2016; 10 (8): 1221–1231. doi: 10.1016/j.molonc.2016.05.009.

63. Burjanivova T, Malicherova B, Grendar M et al. Detection of BRAFV600E mutation in melanoma patients by digital PCR of circulating DNA. Genet Test Mol Biomark 2019; 23 (4): 241–245. doi: 10.1089/gtmb.2018. 0193.

64. Murray NP. Biomarkers detecting minimal residual disease in solid tumors: what do they mean in the clinical management of patients? Biomark Med 2019; 13 (18): 1535–1538. doi: 10.2217/bmm-2019-0401.

65. Drandi D, Kubiczkova-Besse L, Ferrero S et al. Minimal residual disease detection by droplet digital PCR in multiple myeloma, mantle cell lymphoma, and follicular lymphoma: a comparison with real-time PCR. J Mol Diagn JMD 2015; 17 (6): 652–660. doi: 10.1016/j.jmoldx.2015.05.007.

66. Dudová S, Hájek R. Využití metody real-time PCR (kvantitativní PCR, PCR v reálném čase) v hematologii a studiu mnohočetného myelomu. Klin Onkol 2018; 21 (Suppl 1): 220–222.

67. Chin R-I, Chen K, Usmani A et al. Detection of solid tumor molecular residual disease (MRD) using circulating tumor DNA (ctDNA). Mol Diagn Ther 2019; 23 (3): 311–331. doi: 10.1007/s40291-019-00390-5.

68. Taniguchi K, Uchida J, Nishino K et al. Quantitative detection of EGFR mutations in circulating tumor DNA derived from lung adenocarcinomas. Clin Cancer Res Off J Am Assoc Cancer Res 2011; 17 (24): 7808–7815. doi: 10.1158/1078-0432.CCR-11-1712.

69. Taly V, Pekin D, Benhaim L et al. Multiplex picodroplet digital PCR to detect KRAS mutations in circulating DNA from the plasma of colorectal cancer patients. Clin Chem 2013; 59 (12): 1722–1731. doi: 10.1373/clinchem.2013.206359.

70. Garcia-Murillas I, Schiavon G, Weigelt B et al. Mutation tracking in circulating tumor DNA predicts relapse in early breast cancer. Sci Transl Med 2015; 7 (302): 302ra133. doi: 10.1126/scitranslmed.aab0021.

71. Sausen M, Phallen J, Adleff V et al. Clinical implications of genomic alterations in the tumour and circulation of pancreatic cancer patients. Nat Commun 2015; 6: 7686. doi: 10.1038/ncomms8686.

72. Birkenkamp-Demtröder K, Nordentoft I, Christensen E et al. Genomic alterations in liquid biopsies from patients with bladder cancer. Eur Urol 2016; 70 (1): 75–82. doi: 10.1016/j.eururo.2016.01.007.