From Sampling to Sequencing: A Liquid Biopsy Pre-Analytic Workflow to Maximize Multi-Layer Genomic Information from a Single Tube.
CSF
blood preservation tubes
cancer
cell-free DNA
cell-free RNA
droplet digital PCR
liquid biopsy
low-coverage whole-genome sequencing
pre-analytics
size selection
Journal
Cancers
ISSN: 2072-6694
Titre abrégé: Cancers (Basel)
Pays: Switzerland
ID NLM: 101526829
Informations de publication
Date de publication:
15 Jun 2021
15 Jun 2021
Historique:
received:
29
03
2021
revised:
03
05
2021
accepted:
09
06
2021
entrez:
2
7
2021
pubmed:
3
7
2021
medline:
3
7
2021
Statut:
epublish
Résumé
Liquid biopsies hold great promise for the management of cancer. Reliable liquid biopsy data depend on stable and reproducible pre-analytical protocols that comply with quality measures, irrespective of the sampling and processing site. We established a workflow for plasma preservation, followed by processing, cell-free nucleic acid isolation, quantification, and enrichment of potentially tumor-derived cell-free DNA and RNA. Employing the same input material for a direct comparison of different kits and protocols allowed us to formulate unbiased recommendations for sample collection, storage, and processing. The presented workflow integrates the stabilization in Norgen, PAX, or Streck tubes and subsequent parallel isolation of cell-free DNA and RNA with NucleoSnap and NucleoSpin. Qubit, Bioanalyzer, and TapeStation quantification and quality control steps were optimized for minimal sample use and high sensitivity and reproducibility. We show the efficiency of the proposed workflow by successful droplet digital PCR amplification of both cell-free DNA and RNA and by detection of tumor-specific alterations in low-coverage whole-genome sequencing and DNA methylation profiling of plasma-derived cell-free DNA. For the first time, we demonstrated successful parallel extraction of cell-free DNA and RNA from plasma samples. This workflow paves the road towards multi-layer genomic analysis from one single liquid biopsy sample.
Identifiants
pubmed: 34203921
pii: cancers13123002
doi: 10.3390/cancers13123002
pmc: PMC8232701
pii:
doi:
Types de publication
Journal Article
Langues
eng
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