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New, fast and cheap prediction tests for BRCA1 gene mutations identification in clinical samples.

Abstract

Despite significant progress in cancer therapy, cancer is still the second cause of mortality in the world. The necessity to make quick therapeutic decisions forces the development of procedures allowing to obtain a reliable result in a quick and unambiguous manner. Currently, detecting predictive mutations, including BRCA1, is the basis for effectively treating advanced breast cancer. Here, we present new insight on gene mutation detection. We propose a cheap BRCA1 mutation detection tests based on the surface plasmon resonance (SPR) or quartz crystal microbalance with energy dissipation (QCM-D) response changes recorded during a hybridization process of an oligonucleotide molecular probe with DNA fragments, with and without the BRCA1 mutation. The changes in the morphology of the formed DNA layer caused by the presence of the mutation were confirmed by atomic force microscopy. The unique property of the developed SPR and QCM tests is really short time of analysis: ca. 6 min for SPR and ca. 25 min for QCM. The proposed tests have been verified on 22 different DNA extracted from blood leukocytes collected from cancer patients: 17 samples from patients with various BRCA1 gene mutation variants including deletion, insertion and missense single-nucleotide and 5 samples from patients without any BRCA1 mutation. Our test is a response to the need of medical diagnostics for a quick, unambiguous test to identify mutations of the BRCA1 gene, including missense singlenucleotide (SNPs).

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Authors (8)

Keywords

Details

Category:
Articles
Type:
artykuły w czasopismach
Published in:
Scientific Reports no. 13,
ISSN: 2045-2322
Language:
English
Publication year:
2023
Bibliographic description:
Gajda-Walczak A., Potęga A., Kowalczyk A., Sęk S., Zięba S., Kowalik A., Kudelski A., Nowicka A. M.: New, fast and cheap prediction tests for BRCA1 gene mutations identification in clinical samples.// Scientific Reports -Vol. 13, (2023), s.7316-
DOI:
Digital Object Identifier (open in new tab) 10.1038/s41598-023-34588-9
Sources of funding:
  • Grant Nr 2019/35/B/ST4/02752, Narodowe Centrum Nauki (Polska) (projekt spoza PG)
Verified by:
Gdańsk University of Technology

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