Detection of cell-free dna in blood plasma samples of cancer patients

Vikrant Palande, Dorith Raviv Shay, M. I.L.A.N.A. Frenkel-Morgenstern

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Identifying mutations in tumors of cancer patients is a very important step in disease management. These mutations serve as biomarkers for tumor diagnosis as well as for the treatment selection and its response in cancer patients. The current gold standard method for detecting tumor mutations involves a genetic test of tumor DNA by means of tumor biopsies. However, this invasive method is difficult to be performed repeatedly as a follow-up test of the tumor mutational repertoire. Liquid biopsy is a new and emerging technique for detecting tumor mutations as an easy-to-use and non-invasive biopsy approach. Cancer cells multiply rapidly. In parallel, numerous cancer cells undergo apoptosis. Debris from these cells are released into a patient’s circulatory system, together with finely fragmented DNA pieces, called cell-free DNA (cfDNA) fragments, which carry tumor DNA mutations. Therefore, for identifying cfDNA based biomarkers using liquid biopsy technique, blood samples are collected from the cancer patients, followed by the separation of plasma and buffy coat. Next, plasma is processed for the isolation of cfDNA, and the respective buffy coat is processed for the isolation of a patient's genomic DNA. Both nucleic acid samples are then checked for their quantity and quality; and analyzed for mutations using next-generation sequencing (NGS) techniques. In this manuscript, we present a detailed protocol for liquid biopsy, including blood collection, plasma, and buffy coat separation, cfDNA and germline DNA extraction, quantification of cfDNA or germline DNA, and cfDNA fragment enrichment analysis.

Original languageEnglish
Article numbere61449
Pages (from-to)1-21
Number of pages21
JournalJournal of Visualized Experiments
Volume2020
Issue number163
DOIs
StatePublished - 9 Sep 2020

Bibliographical note

Publisher Copyright:
© 2020 JoVE Journal of Visualized Experiments.

Funding

The authors would like to thank the members of the Laboratory of Cancer Genomics and Biocomputing of Complex Diseases for their keen observational inputs and their participation in multiple discussions at different stages of this project. The funding support includes Israel Cancer Association (ICA grant for M.F-M 2017-2019) and Kamin grant of Israel Innovation Authority (for M.F-M.).

FundersFunder number
Israel Innovation Authority
International Communication Association
Israel Cancer Association

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