Fig. 2: Evaluation of extrachromosomal DNA amplification identification on cancer cell line genomes. | Nature Communications

Fig. 2: Evaluation of extrachromosomal DNA amplification identification on cancer cell line genomes.

From: Machine learning-based extrachromosomal DNA identification in large-scale cohorts reveals its clinical implications in cancer

Fig. 2

GCAP validation in two known ecDNA+ cancer cell lines a SNU16 and b PC3. The top panels show probe settings and result images of DNA metaphase FISH experiments targeting genes MYC and FGFR2. FISH result of FGFR2 in PC3 represents a naturally negative control. The scale bar used in the figure is 10 micrometers. The middle panels show structural variant view of AmpliconArchitect (AA) reconstructions from WGS data of SNU16 and PC3. The bottom panels show Circle-Seq read density (measured as the number of reads overlapping every one-megabase window) in corresponding chromosomes. c MYC and FGFR2 gene copy number in SNU16 and PC3 by qRT-PCR. d Concordance of copy number estimation by qRT-PCR and WES with six selected genes in SNU16 and PC3. Linear regression lines, point estimates of two-sided Pearson correlation coefficient test and their 95% confidence level intervals are presented. e Copy number profiles and extrachromosomal DNA segment links of a gastric cancer. For better visualization, only chr6 and chr17, which show ecDNA amplifications, are plotted in the Circos plot. The first and second tracks represent the total copy number of tumor tissue and patient-derived xenograft model samples. The inner track represents the extrachromosomal DNA segment links. f, g Comparison between AmpliconArchitect (AA) and GCAP for extrachromosomal DNA amplification on WGS data of two cancer cell line batches. Source data are provided as a Source Data file.

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