In:
Journal of Clinical Pathology, BMJ, Vol. 73, No. 10 ( 2020-10), p. 648-655
Abstract:
The identification of actionable DNA mutations associated with a patient’s tumour is critical for devising a targeted, personalised cancer treatment strategy. However, these molecular analyses are typically performed using tissue obtained via biopsy, which involves substantial risk and is often not feasible. In addition, biopsied tissue does not always reflect tumour heterogeneity, and sequential biopsies to track disease progression (eg, emergence of drug resistance mutations) are not well tolerated. To overcome these and other biopsy-associated limitations, we have developed non-invasive ‘liquid biopsy’ technologies to enable the molecular characterisation of a patient’s cancer using peripheral blood samples. Methods The Target Selector ctDNA platform uses a real-time PCR-based approach, coupled with DNA sequencing, to identify cancer-associated genetic mutations within circulating tumour DNA. This is accomplished via a patented blocking approach suppressing wild-type DNA amplification, while allowing specific amplification of mutant alleles. Results To promote the clinical uptake of liquid biopsy technologies, it is first critical to demonstrate concordance between results obtained via liquid and traditional biopsy procedures. Here, we focused on three genes frequently mutated in cancer: EGFR (Del19, L858, and T790), BRAF (V600) and KRAS (G12/G13). For each Target Selector assay, we demonstrated extremely high accuracy, sensitivity and specificity compared with results obtained from tissue biopsies. Overall, we found between 93% and 96% concordance to blinded tissue samples across 127 clinical assays. Conclusions The switch-blocker technology reported here offers a highly effective method for non-invasively determining the molecular signatures of patients with cancer.
Type of Medium:
Online Resource
ISSN:
0021-9746
,
1472-4146
DOI:
10.1136/jclinpath-2019-206381
Language:
English
Publisher:
BMJ
Publication Date:
2020
detail.hit.zdb_id:
2028928-5
