Genomics & Informatics

Korea Genome Organization (한국유전체학회)
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Detection of KRAS mutations in plasma cell-free DNA of colorectal cancer patients and comparison with cancer panel data for tissue samples of the same cancers

  • Min, Suji (Department of Microbiology, College of Medicine, The Catholic University of Korea) ;
  • Shin, Sun (Department of Microbiology, College of Medicine, The Catholic University of Korea) ;
  • Chung, Yeun-Jun (Department of Microbiology, College of Medicine, The Catholic University of Korea)
  • Received : 2019.10.24
  • Accepted : 2019.11.04
  • Published : 2019.12.31
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Abstract

Robust identification of genetic alterations is important for the diagnosis and subsequent treatment of tumors. Screening for genetic alterations using tumor tissue samples may lead to biased interpretations because of the heterogeneous nature of the tumor mass. Liquid biopsy has been suggested as an attractive tool for the non-invasive follow-up of cancer treatment outcomes. In this study, we aimed to verify whether the mutations identified in primary tumor tissue samples could be consistently detected in plasma cell-free DNA (cfDNA) by digital polymerase chain reaction (dPCR). We first examined the genetic alteration profiles of three colorectal cancer (CRC) tissue samples by targeted next-generation sequencing (NGS) and identified 11 non-silent amino acid changes across six cancer-related genes (APC, KRAS, TP53, TERT, ARIDIA, and BRCA1). All three samples had KRAS mutations (G12V, G12C, and G13D), which were well-known driver events. Therefore, we examined the KRAS mutations by dPCR. When we examined the three KRAS mutations by dPCR using tumor tissue samples, all of them were consistently detected and the variant allele frequencies (VAFs) of the mutations were almost identical between targeted NGS and dPCR. When we examined the KRAS mutations using the plasma cfDNA of the three CRC patients by dPCR, all three mutations were consistently identified. However, the VAFs were lower (range, 0.166% to 2.638%) than those obtained using the CRC tissue samples. In conclusion, we confirmed that the KRAS mutations identified from CRC tumor tissue samples were consistently detected in the plasma cfDNA of the three CRC patients by dPCR.

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References

  1. Swanton C. Intratumor heterogeneity: evolution through space and time. Cancer Res 2012;72:4875-4882. https://doi.org/10.1158/0008-5472.CAN-12-2217
  2. Siravegna G, Marsoni S, Siena S, Bardelli A. Integrating liquid biopsies into the management of cancer. Nat Rev Clin Oncol 2017;14:531-548. https://doi.org/10.1038/nrclinonc.2017.14
  3. Crowley E, Di Nicolantonio F, Loupakis F, Bardelli A. Liquid biopsy: monitoring cancer-genetics in the blood. Nat Rev Clin Oncol 2013;10:472-484. https://doi.org/10.1038/nrclinonc.2013.110
  4. Diaz LA Jr, Bardelli A. Liquid biopsies: genotyping circulating tumor DNA. J Clin Oncol 2014;32:579-586. https://doi.org/10.1200/JCO.2012.45.2011
  5. Beck J, Bierau S, Balzer S, Andag R, Kanzow P, Schmitz J, et al. Digital droplet PCR for rapid quantification of donor DNA in the circulation of transplant recipients as a potential universal biomarker of graft injury. Clin Chem 2013;59:1732-1741. https://doi.org/10.1373/clinchem.2013.210328
  6. Devonshire AS, O'Sullivan DM, Honeyborne I, Jones G, Karczmarczyk M, Pavsic J, et al. The use of digital PCR to improve the application of quantitative molecular diagnostic methods for tuberculosis. BMC Infect Dis 2016;16:366. https://doi.org/10.1186/s12879-016-1696-7
  7. Thress KS, Brant R, Carr TH, Dearden S, Jenkins S, Brown H, 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;90:509-515. https://doi.org/10.1016/j.lungcan.2015.10.004
  8. Burjanivova T, Malicherova B, Grendar M, Minarikova E, Dusenka R, Vanova B, et al. Detection of BRAFV600E mutation in melanoma patients by digital PCR of circulating DNA. Genet Test Mol Biomarkers 2019;23:241-245. https://doi.org/10.1089/gtmb.2018.0193
  9. Garcia-Murillas I, Lambros M, Turner NC. Determination of HER2 amplification status on tumour DNA by digital PCR. PLoS One 2013;8:e83409. https://doi.org/10.1371/journal.pone.0083409
  10. Yu SM, Jung SH, Chung YJ. Comparison of the genetic alterations between primary colorectal cancers and their corresponding patient-derived xenograft tissues. Genomics Inform 2018;16:30-35. https://doi.org/10.5808/GI.2018.16.2.30
  11. Choi SH, Jung SH, Chung YJ. Validation of customized cancer panel for detecting somatic mutations and copy number alterations. Genomics Inform 2017;15:136-141. https://doi.org/10.5808/GI.2017.15.4.136
  12. Day E, Dear PH, McCaughan F. Digital PCR strategies in the development and analysis of molecular biomarkers for personalized medicine. Methods 2013;59:101-107. https://doi.org/10.1016/j.ymeth.2012.08.001
  13. Perincheri S, Hui P. KRAS mutation testing in clinical practice. Expert Rev Mol Diagn 2015;15:375-384. https://doi.org/10.1586/14737159.2015.986102
  14. Zhuang R, Li S, Li Q, Guo X, Shen F, Sun H, et al. The prognostic value of KRAS mutation by cell-free DNA in cancer patients: a systematic review and meta-analysis. PLoS One 2017;12:e0182562. https://doi.org/10.1371/journal.pone.0182562
  15. Christensen E, Nordentoft I, Vang S, Birkenkamp-Demtroder K, Jensen JB, Agerbaek M, et al. Optimized targeted sequencing of cell-free plasma DNA from bladder cancer patients. Sci Rep 2018;8:1917. https://doi.org/10.1038/s41598-018-20282-8