Digital PCR for the Analysis of MYC Copy Number Variation in Lung Cancer
Joint Authors
Weber, Daniel G.
Casjens, Swaantje
Johnen, Georg
Brik, Alexander
Rozynek, Peter
Meier, Swetlana
Behrens, Thomas
Stamatis, Georgios
Darwiche, Kaid
Theegarten, Dirk
Brüning, Thomas
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-09-21
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Background.
MYC (v-myc avian myelocytomatosis viral oncogene homolog) is one of the most frequently amplified genes in lung tumors.
For the analysis of gene copy number variations, dPCR (digital PCR) is an appropriate tool.
The aim of our study was the assessment of dPCR for the detection of MYC copy number variations (CNV) in lung tissue considering clinicopathological parameters.
Material and Methods.
MYC status was analyzed with dPCR as well as qPCR (quantitative PCR) using gDNA (genomic DNA) from tumor and adjacent nontumor tissue samples of lung cancer patients.
The performance of MYC was estimated based on the AUC (area under curve).
Results.
The results of the MYC amplification correlated significantly between dPCR and qPCR (rS=0.81, P<0.0001).
The MYC copy number revealed by dPCR showed statistically significant differences between tumor and adjacent nontumor tissues.
For discrimination, a sensitivity of 43% and a specificity of 99% were calculated, representing 55 true-positive and one false-positive tests.
No statistically significant differences could be observed for age, sex, and smoking status or the clinicopathological parameters (histological subtype, grade, and stage).
Conclusion.
The results of the study show that dPCR is an accurate and reliable method for the determination of MYC copy numbers.
The application is characterized by high specificity and moderate sensitivity.
MYC amplification is a common event in lung cancer patients, and it is indicated that the determination of the MYC status might be useful in clinical diagnostics.
American Psychological Association (APA)
Brik, Alexander& Weber, Daniel G.& Casjens, Swaantje& Rozynek, Peter& Meier, Swetlana& Behrens, Thomas…[et al.]. 2020. Digital PCR for the Analysis of MYC Copy Number Variation in Lung Cancer. Disease Markers،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1153837
Modern Language Association (MLA)
Brik, Alexander…[et al.]. Digital PCR for the Analysis of MYC Copy Number Variation in Lung Cancer. Disease Markers No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1153837
American Medical Association (AMA)
Brik, Alexander& Weber, Daniel G.& Casjens, Swaantje& Rozynek, Peter& Meier, Swetlana& Behrens, Thomas…[et al.]. Digital PCR for the Analysis of MYC Copy Number Variation in Lung Cancer. Disease Markers. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1153837
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1153837