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Deutsche Zeitschrift für Onkologie 2019; 51(02): 60-64
DOI: 10.1055/a-0827-9604
Forschung
© Georg Thieme Verlag KG Stuttgart · New York

Die Untersuchung zellfreier DNA durch Liquid Biopsy in der Medizin

The Investigation of Cell-Free DNA by Liquid Biopsy in Medicine
Bernd Eiben
1   amedes genetics, Institut für Labormedizin und Klinische Genetik Rhein/Ruhr, Essen
,
Ralf Glaubitz
2   amedes genetics, Hannover
,
Ekkehard Schütz
3   Chronix Biomedical GmbH, Göttingen
,
Julia Beck
3   Chronix Biomedical GmbH, Göttingen
,
Christian Eiben
4   Paracelsus Medical University Salzburg (A)
,
Anna Teubert
2   amedes genetics, Hannover
,
Helmut Wagner
5   Liquid Biopsy Center, Göttingen
,
Thomas Winkler
5   Liquid Biopsy Center, Göttingen
,
Wolf Kupatt
5   Liquid Biopsy Center, Göttingen
,
Michael Oellerich
6   Universitätsmedizin Göttingen, Georg-August-Universität, Institut für Klinische Pharmakologie, Göttingen
› Author Affiliations
Further Information

Publication History

Publication Date:
15 March 2019 (online)

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Zusammenfassung

Bei Diagnostik und Monitoring von Tumoren stellten bisher bild- oder biopsiebasierte Verfahren den Goldstandard dar. Neuere Verfahren könnten dieses Vorgehen verändern. So ist es gelungen, zirkulierende Tumorzellen direkt aus dem peripheren Blut zu isolieren und zu charakterisieren. Intratumorale Zellheterogenitäten stellen sich hierbei jedoch als problematisch dar, da diese zu fehlerhaften Betrachtungen führen können. Durch die Analyse von zellfreier Tumor-DNA aus Tumorabbauprodukten im peripheren Blut (sog. Liquid Biopsy) mittels neuester Sequenziertechniken (NGS) können nun auch sehr komplexe Zusammenhänge analysiert werden. Dadurch werden sowohl Einzelgenveränderungen als auch gesamtgenomische Kopienzahlveränderungen (sog. copy number variations, CNV) erkennbar. Bei über 90% der malignen Tumoren lassen sich größere CNV-Abweichungen nachweisen. Der Grad der CNV-Abweichung vom Normalzustand lässt sich in copy number instability (CNI)-Scores standardisieren. Dadurch ist der CNI-Score ein vielversprechender klinischer Biomarker für die Risikostratifizierung und das individualisierte Therapiemonitoring mit dem Potenzial, die Gesundheitskosten und die Krankheitsbelastung für Krebspatienten zu senken.

Abstract

In diagnosis and monitoring of tumors, image- or biopsy-based methods have so far been the gold standard. However, newer methods could change this approach. It is now possible to isolate and characterize circulating tumor cells from peripheral blood directly. Intratumoral cell heterogeneities, however, are problematic because they can lead to incorrect observations. By analyzing cell-free tumor DNA from tumor degradation products in peripheral blood (Liquid Biopsy), even very complex relationships can now be analyzed by using the latest sequencing techniques (NGS). This allows both single gene changes and total genomic copy number changes, so-called copy number variations (CNV), to be identified. In more than 90% of malignant tumors, larger CNV deviations can be detected. The degree of CNV deviation from the normal state can be standardized by a copy number instability (CNI) score. This makes the CNI score a promising clinical biomarker for risk stratification and individualized therapy monitoring with the potential to reduce health costs and disease burden for cancer patients.

Schlüsselwörter

freie DNA - Liquid Biopsy - CNI-Score - Tumormarker - zirkulierende Tumorzellen - prediktiver Wert

Key words

freeDNA - liquid biopy - CNI score - biochemical tumor marker - circulating tumor cells - predictive value
 

  • Literatur

  • 1 Siegel R. et al. Cancer treatment and survivorship statistics. Cancer J Clin 2012; 62: 220-241
    CrossrefPubMedGoogle Scholar
  • 2 Gourd E. Mammography deficiencies: the result of poor positioning. Lancet Oncol 2018; 19: e385 doi: 10.1016/S1470-2045(18)30489-3
    CrossrefPubMedGoogle Scholar
  • 3 Mikolajczyk SD. et al. Detection of EpCAM-negative and cytokeratin-negative circulating tumor cells in peripheral blood. J Oncol 2011; 2011: 252361 doi: 10.1155/2011/252361
    PubMedGoogle Scholar
  • 4 Serrano MJ. et al. EMT and EGFR in CTCs cytokeratin negative non-metastatic breast cancer. Oncotarget 2014; 5: 7486-7497
    CrossrefPubMedGoogle Scholar
  • 5 Bidard FC. et al. Clinical validity of circulating tumour cells in patients with metastatic breast cancer: a pooled analysis of individual patient data. Lancet Oncol 2014; 15: 406-414
    CrossrefPubMedGoogle Scholar
  • 6 Hiley C, de Bruin EC, McGranahan N, Swanton C. Deciphering intratumor heterogeneity and temporal acquisition of driver events to refine precision medicine. Genome Biol 2014; 15: 453
    CrossrefPubMedGoogle Scholar
  • 7 Lindström LS. et al. Clinically used breast cancer markers such as estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 are unstable throughout tumor progression. J Clin Oncol 2012; 30: 2601-2608
    CrossrefPubMedGoogle Scholar
  • 8 Ignatiadis M, Lee M, Jeffrey SS. Circulating tumor cells and circulating tumor DNA: challenges and opportunities on the path to clinical utility. Clin Cancer Res 2015; 21: 4786-4800
    CrossrefPubMedGoogle Scholar
  • 9 Lo YM. et al. Presence of fetal DNA in maternal plasma and serum. Lancet 1997; 350: 485-487
    CrossrefPubMedGoogle Scholar
  • 10 Leung TN, Zhang J, Lau TK, Hjelm NM, Lo YM. Maternal plasma fetal DNA as a marker for preterm labour. Lancet 1998; 352: 1904-1905
    PubMedGoogle Scholar
  • 11 Lo YM. et al. Presence of donor-specific DNA in plasma of kidney and liver-transplant recipients. Lancet 1998; 351: 1329-1330
    CrossrefPubMedGoogle Scholar
  • 12 Sun K. et al. Size-tagged preferred ends in maternal plasma DNA shed light on the production mechanism and show utility in noninvasive prenatal testing. Proc Natl Acad Sci U S A 2018; 115: E5106-E5114
    CrossrefPubMedGoogle Scholar
  • 13 El Messaoudi S, Rolet F, Mouliere F, Thierry AR. Circulating cell free DNA: preanalytical considerations. Clin Chim Acta 2013; 424: 222-230
    CrossrefPubMedGoogle Scholar
  • 14 International Cancer Genome Consortium. Available at: http://icgc. org/ (accessed: 29th June 2018)
    PubMed
  • 15 Bettegowda C. et al. Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci Transl Med 2014; 6: 224ra24
    CrossrefPubMedGoogle Scholar
  • 16 Dawson SJ. et al. Analysis of circulating tumor DNA to monitor metastatic breast cancer. N Engl J Med 2013; 368: 1199-1209
    CrossrefPubMedGoogle Scholar
  • 17 Riediger AL. et al. Mutation analysis of circulating plasma DNA to determine response to EGFR tyrosine kinase inhibitor therapy of lung adenocarcinoma patients. Sci Rep 2016; 6: 33505
    CrossrefPubMedGoogle Scholar
  • 18 Eiben B. et al. Single nucleotide polymorphism-based analysis of cell-free fetal DNA in 3000 cases from Germany and Austria. Ultrasound Int Open 2015; 1: E8-E11
    Article in Thieme ConnectPubMedGoogle Scholar
  • 19 Kagan K, Eiben B, Kozlowski P. Combined first trimester screening and cell-free fetal DNA – “Next Generation Screening”. Ultraschall der Medizin. Eur J Ultrasound 2014; 35: 229-236
    PubMedGoogle Scholar
  • 20 Schmid M. et al. Cell-free DNA testing for fetal chromosomal anomalies in clinical practice: Austrian-German-Swiss recommendations for non-invasive prenatal tests (NIPT). Ultraschall der Medizin – Eur J Ultrasound 2015; 36: 507-510
    PubMedGoogle Scholar
  • 21 Bianchi DW. et al. Noninvasive prenatal testing and incidental detection of occult maternal malignancies. JAMA 2015; 314: 162-169
    CrossrefPubMedGoogle Scholar
  • 22 Amant F. et al. Presymptomatic identification of cancers in pregnant women during noninvasive prenatal testing. JAMA Oncol 2015; 1: 814-819
    CrossrefPubMedGoogle Scholar
  • 23 Cohen PA. et al. Abnormal plasma DNA profiles in early ovarian cancer using a non-invasive prenatal testing platform: implications for cancer screening. BMC Med 2016; 14: 126
    CrossrefPubMedGoogle Scholar
  • 24 Berg M. et al. Molecular subtypes in stage II-III colon cancer defined by genomic instability: early recurrence-risk associated with a high copy-number variation and loss of RUNX3 and CDKN2A. PLoS One 2015; 10: e0122391
    CrossrefPubMedGoogle Scholar
  • 25 Endesfelder D. et al. Chromosomal instability selects gene copy-number variants encoding core regulators of proliferation in ER+breast cancer. Cancer Res 2014; 74: 4853-4863
    CrossrefPubMedGoogle Scholar
  • 26 Weiss GJ. et al. Tumor cell–free DNA copy number instability predicts therapeutic response to immunotherapy. Clin Cancer Res 2017; 23: 5074-5081
    CrossrefPubMedGoogle Scholar
  • 27 Schirmer MA. et al. Cell-free plasma DNA for disease stratification and prognosis in head and neck cancer. Clin Chem 2018; 64: 959-970
    CrossrefPubMedGoogle Scholar
  • 28 Oellerich M. et al. Using circulating cell-free DNA to monitor personalized cancer therapy. Crit Rev Clin Lab Sci 2017; 54: 205-218
    CrossrefPubMedGoogle Scholar
  • 29 Watts G. Liquid biopsy: still early days for early detection. Lancet 2018; 391: 2593-2594
    CrossrefPubMedGoogle Scholar