Enhancer activation from transposable elements in extrachromosomal DNA

Abstract

Extrachromosomal DNA (ecDNA) drives oncogene amplification and intratumoral heterogeneity in aggressive cancers. While transposable element (TE) reactivation is common in cancer, its role on ecDNA remains unexplored. Here, we map the 3D architecture of MYC-amplified ecDNA in colorectal cancer cells and identify 68 ecDNA-interacting elements (EIEs)-genomic loci enriched for TEs that are frequently integrated onto ecDNA. We focus on an L1M4a1#LINE/L1 fragment co-amplified with MYC, which functions only in the ecDNA amplified context. Using CRISPR-CATCH, CRISPR interference, and reporter assays, we confirm its presence on ecDNA, enhancer activity, and essentiality for cancer cell fitness. These findings reveal that repetitive elements can be reactivated and co-opted as functional rather than inactive sequences on ecDNA, potentially driving oncogene expression and tumor evolution. Our study uncovers a mechanism by which ecDNA harnesses repetitive elements to shape cancer phenotypes, with implications for diagnosis and therapy.

Figure 1:. Identification of ecDNA interacting elements (EIEs)

a. Method schematic of Hi-C performed in the ecDNA containing COLO320DM cell line. b. Identification of ecDNA-interacting elements (EIEs). 68 Individual EIEs were manually annotated across all chromosomes based on the interaction across the entirety of the MYC-amplified region of chromosome 8. The visualization represents the ecDNA from chromosome 8 with 3 examples of ecDNA-interacting elements (EIEs) localized on other chromosomes. c. An example of a specific interaction, EIE 14 on chromosome 3, is enlarged and associated genes are shown for both loci. Arrow and purple hexagon indicate EIE. d. Overlap fraction of EIE sequence and annotated LINE, SINE, and LTR elements reported in RepBase. EIEs are clustered according to similarity in overlap fraction across these three classes of repetitive elements. e. Pipeline for using Oxford Nanopore ultra-long read sequencing to identify the overlap of ecDNA genomic intervals and EIE-containing reads. f. The number of reads that contain a particular EIE and overlap with an ecDNA interval in the COLO320DM cell line. Counts are reported as log₁₀(1+x). Average genome coverage (12.1) is represented as a red dashed line. g. Reconstruction of the ecDNA breakpoint graph for COLO320DM from Oxford Nanopore ultra-long read data using the CoRAL algorithm. The EIE14 region is highlighted in red and the breakpoint indicating its translocation to the amplified chr8 locus is annotated. Source numerical data are available in source data.

Figure 2:. CRISPR-CATCH Elucidates ecDNA Composition and EIE Insertions

a. Schematic diagram illustrating the CRISPR-CATCH experiment designed to isolate and characterize ecDNA components. The process involves the use of guide RNA targeting the EIE 14 from chromosome 3. DNA is embedded in agarose, followed by pulse-field gel electrophoresis (PFGE), allowing for the band extraction and subsequent next-generation sequencing (NGS) of ecDNA fragments. b. The PFGE gel image displays the separation of DNA fragments, lines from left ladder, ladder, empty lane, Negative control, sgRNA #1, sgRNA #2 and band numbers for NGS seen in C-D. EIE 14 targeted by the guide RNAs leads to cutting of the ecDNA’s chromosome 8 sequences to form multiple discrete bands, confirming EIE 14 insertion onto ecDNA. sgRNA #1 ATATAGGACAGTATCAAGTA; sgRNA #2 TATATTATTAGTCTGCTGAA; Full EIE 14 sequences from long-read sequencing is in Supplementary Table T6. c. Whole genome sequencing results confirm the presence of EIE 14, originally annotated on chromosome 3, within the ecDNA, between the CASC8 and CASC11 genes, approximately 200 kilobases upstream from MYC. The dotted line indicates the position of this insertion. Each band is an ecDNA molecule of a different size that contains the EIE 14 insertion. d. Additional EIEs identified in the initial Hi-C screen, captured, and sequenced in the CRISPR-CATCH gel bands from (B), each EIE is one one vertical shaded box with coordinates and denote insertion events within the ecDNA. e. ORCA (Optical Reconstruction of Chromatin Architecture) visualization of the COLO320DM cell nucleus. The max-projected images show the spatial arrangement of the MYC oncogene, EIE 14 and the PVT1 locus, labeled in different colors for two different cells. Left most panel is an overlay of all images registered to nm precision (see Methods).The scale bar represents 5 micrometers. Chr3 probe maps to the breakpoints of the EIE 14 origin inside CD96 intron. Source numerical data and unprocessed blot are available in source data.

Figure 3:. EIE 14 spatially clusters with MYC

a. X, Y, Z projections of MYC exon (purple), PVT1 (blue), and EIE 14 (pink) b. Endogenous coordinates of all three measured genomic regions. c. Single cell projection of the 3D fitted points from (A). d. Pairwise distances between MYC (purple), PVT1 (blue), and EIE 14 (pink) of a single cell. Number of fitted points per genomic region n=60, n=43, and n=25 respectively. e. Histogram of distribution of distances of the observed shortest pairwise EIE 14 to EIE 14 distances and the expected shortest pairwise distances of points randomly simulated in a sphere (two-tailed Wilcoxon ranksum p<1e-10) of n=1329 analyzed cells across 2 biological replicates. f. As in (E) but for MYC to MYC shortest pairwise distances (Two-tailed Wilcoxon ranksum p<1e-10). g. Schematic of Ripley’s K function to describe clustering behaviors over different nucleus volumes. Top shows the nucleus divided into different shell intervals and how the K value is plotted for increasing radius (r). Bottom shows an example of what clustered K(r)>1 vs. random K(r)~1 points could look like. K-values greater than one indicate clustering behavior relative to a random distribution over that given distance interval (r), K values ~ one denote random distribution, while K values less than one indicate dispersion behavior h. The average K(r) value across distance intervals of 0.01 to 0.5 um in 0.02 um step sizes to describe the clustering relationship of PVT1 and EIE 14 relative to MYC across different distance intervals (um). Error bars denote SEM. (Two-tailed Wilcoxon ranksum p=0.01442). Source numerical data are available in source data.

Figure 4:. EIE 14 is important for cell proliferation and has enhancer signatures

a. Schematic of the CRISPRi screening strategy used to evaluate the regulatory potential of the 68 EIEs by designing 4–6 gRNAs per element for a total of 257 genomic regions tested and 125 non-targeting control sgRNAs. The screen involved the transduction of cells with a lentivirus expressing dCas9-KRAB and the sgRNAs such that each cell received 1 sgRNA, followed by calculation of cell growth phenotype over a series of time points (Baseline(4 days), Baseline + 3 days, Baseline + 14 days, and Baseline + 1 month). The screen was further filtered on guide specificity (methods) and 36/68 targeted EIEs met the qualifying threshold. b. The growth phenotype of COLO320DM cells 2 weeks post-transduction, relative to non-targeting control (NTC). Each point represents the average guide effect (Z-score) for sgRNAs targeting the 36 qualifying EIEs, ranked by their impact on cell growth. EIE 14 is indicated by dashed rectangle with negative Z-score < −1 (significant negative impact on cell viability). See Extended Data for additional timepoints. Positive hits are labeled in pink with their corresponding EIE. c. UCSC Genome Browser multi-region view showing the locations of the EIEs within the genome. Each EIE is indicated by a vertical bar. The browser displays the annotations for genes and repetitive elements such as Alu, LINE, and LTR elements (RepeatMasker), ATAC-seq dataset is normalized for copy number (see Methods). d. Zoom-in of EIE 14’s histone marks: enrichment of H3K27 acetylation, BRD4 binding, and ATAC-seq peaks. ChIP data was normalized to input to control for copy number. ATAC-seq data was normalized to library size (methods). e. H3K9me3 histone modification of EIE 14 across ENCODE cell lines.^,

Figure 5:. ecDNA context is critical for EIE 14 enhancer activity

a. (Top) Schematic outlining COLO320DM cell line as high copy number and high ecDNA vs HSR- as high copy number but low ecDNA. b. RNA-FISH labeling for EIE 14 and MYC exon 2 transcription in COLO320 DM and HSR. Median transcripts for EIE 14 are 4 and 0 for the DM and HSR cells ( two-tailed wilcoxon ranksum p=8.22 10–94), respectively. DM cells have a median of 14 MYC transcripts and HSR cells have a median of 8 transcripts per cell (two-tailed wilcoxon ranksum p=2.18 10–66). n=712 cells (DM) n=681 (HSR) across 2 biological replicates. c. Luciferase enhancer assay schematics and fold change in luciferase signal driven by either MYC or TK promoter normalized to promoter-only construct. n=4 biological replicates. EIE 14 compared to positive control (PVT1 positive control from). P-values obtained from two-tailed unpaired t-test. Error bars are standard deviations from the mean. d. Schematic outlining EIE 14 as a translocation event in healthy patients where EIE 14 is normally inactive across annotated cell lines (Fig. 5A). EIE 14 gains regulatory potential when it is amplified within ecDNA as a consequence of translocation near MYC. EIE 14 can then act as a regulator of MYC in both cis- and trans-contacts within and between ecDNAs. Source numerical data and images are available in source data.