Back

Live-cell imaging shows uneven segregation of extrachromosomal DNA elements and transcriptionally active extrachromosomal DNA clusters in cancer

Yi, E.; Gujar, A. D.; Guthrie, M.; Kim, H.; Johnson, K. C.; Amin, S. B.; Das, S.; Clow, P. A.; Cheng, A. W.; Verhaak, R. G.

2020-10-21 cancer biology Community evaluation
10.1101/2020.10.20.335216 bioRxiv
Show abstract

Oncogenic extrachromosomal DNA elements (ecDNAs) promote intratumoral heterogeneity, creating a barrier for successful cancer treatments. The underlying mechanisms are poorly understood and studies are hampered in part by a lack of adequate tools enabling studies of ecDNA behavior. Here, we show that single-cell ecDNA copy numbers follow a Gaussian distribution across tumor cells in vitro and in patient glioblastoma specimens, suggesting uneven ecDNA segregation during mitosis. We established a CRISPR-based approach which leverages unique ecDNA breakpoint sequences to tag ecDNA with fluorescent markers in living cells. Applying this method during mitosis revealed disjointed ecDNA inheritance patterns, providing an explanation for rapid ecDNA accumulation in cancer. Post-mitosis, ecDNAs tended to cluster and clustered ecDNAs colocalized with RNA polymerase II, promoting transcription of cargo oncogenes. Our observations provide direct evidence for uneven segregation of ecDNA and shed new lights of mechanisms through which ecDNAs contribute to oncogenesis.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

1
Nature Communications
○ 5641 papers in training set
Top 0.6%
40.1%
Similar papers in this journal
2
Molecular Cell
○ 350 papers in training set
Top 1%
5.6%
Similar papers in this journal
3
Cell Reports
○ 1498 papers in training set
Top 7%
5.2%
Similar papers in this journal
50% of probability mass above
4
Genome Biology
○ 637 papers in training set
Top 3%
4.1%
Similar papers in this journal
5
Communications Biology
○ 993 papers in training set
Top 5%
3.3%
Similar papers in this journal
6
Science Advances
● 1243 papers in training set
Top 13%
2.7%
7
Nature Cell Biology
○ 118 papers in training set
Top 1%
2.7%
8
eLife
● 5828 papers in training set
Top 42%
2.4%
9
Nature Methods
○ 385 papers in training set
Top 3%
2.4%
10
Cell
○ 431 papers in training set
Top 5%
2.2%
11
iScience
○ 1154 papers in training set
Top 13%
2.2%
12
Genome Research
● 468 papers in training set
Top 3%
1.8%
13
Nature Genetics
○ 286 papers in training set
Top 3%
1.8%
14
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 28%
1.7%
15
Nature Biotechnology
○ 172 papers in training set
Top 3%
1.5%
16
Cell Reports Methods
○ 165 papers in training set
Top 2%
1.1%
17
Nature
○ 645 papers in training set
Top 8%
1.1%
18
Cell Genomics
○ 172 papers in training set
Top 3%
1.1%
19
Molecular Cancer
○ 16 papers in training set
Top 0.2%
1.1%
20
Science
● 477 papers in training set
Top 8%
0.9%
21
Nature Cancer
○ 39 papers in training set
Top 1%
0.9%
22
Genes & Development
● 90 papers in training set
Top 2%
0.9%
23
Scientific Reports
○ 3612 papers in training set
Top 71%
0.9%
24
Cancer Discovery
● 66 papers in training set
Top 2%
0.9%
25
npj Precision Oncology
○ 53 papers in training set
Top 2%
0.6%
26
Cell Reports Medicine
○ 153 papers in training set
Top 6%
0.6%
27
Developmental Cell
○ 196 papers in training set
Top 4%
0.6%
28
Nucleic Acids Research
◐ 1281 papers in training set
Top 14%
0.6%
29
Cancer Cell
○ 42 papers in training set
Top 1%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.