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Digital PCR for the Analysis of MYC Copy Number Variation in Lung Cancer

Authors :
Dirk Theegarten
Thomas BrĂ¼ning
Swetlana Meier
Daniel G. Weber
Georg Johnen
Alexander Brik
Thomas Behrens
Swaantje Casjens
Kaid Darwiche
P. Rozynek
Georgios Stamatis
Source :
Disease Markers, Vol 2020 (2020)
Publication Year :
2020
Publisher :
Hindawi Limited, 2020.

Abstract

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.

Details

ISSN :
18758630 and 02780240
Volume :
2020
Database :
OpenAIRE
Journal :
Disease Markers
Accession number :
edsair.doi.dedup.....db0e5c115f42efbac745b378a8ba9cd5
Full Text :
https://doi.org/10.1155/2020/4176376