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[Preprint]. 2023 Nov 28:2023.04.24.537925.

doi: 10.1101/2023.04.24.537925.

Transcriptional immune suppression and upregulation of double stranded DNA damage and repair repertoires in ecDNA-containing tumors

Miin S Lin¹, Se-Young Jo², Jens Luebeck³, Howard Y Chang^{4

5

6}, Sihan Wu⁷, Paul S Mischel^{8

9}, Vineet Bafna^{3

10}

Affiliations

¹ Bioinformatics and Systems Biology Graduate Program, University of California at San Diego, La Jolla, CA, USA.
² Department of Biomedical Systems Informatics and Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, Seoul, South Korea.
³ Department of Computer Science and Engineering, University of California at San Diego, La Jolla, CA, USA.
⁴ Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA.
⁵ Department of Genetics, Stanford University, Stanford, CA, USA.
⁶ Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
⁷ Children's Medical Center Research Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA.
⁸ Sarafan Chemistry, Engineering, and Medicine for Human Health (Sarafan ChEM-H), Stanford University, Stanford, CA, USA.
⁹ Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
¹⁰ Halıcıoğlu Data Science Institute, University of California at San Diego, La Jolla, CA, USA.

PMID: 37162993
PMCID: PMC10168239
DOI: 10.1101/2023.04.24.537925

Transcriptional immune suppression and upregulation of double stranded DNA damage and repair repertoires in ecDNA-containing tumors

Miin S Lin et al. bioRxiv. 2023.

[Preprint]. 2023 Nov 28:2023.04.24.537925.

doi: 10.1101/2023.04.24.537925.

Authors

Miin S Lin¹, Se-Young Jo², Jens Luebeck³, Howard Y Chang^{4

5

6}, Sihan Wu⁷, Paul S Mischel^{8

9}, Vineet Bafna^{3

10}

Affiliations

¹ Bioinformatics and Systems Biology Graduate Program, University of California at San Diego, La Jolla, CA, USA.
² Department of Biomedical Systems Informatics and Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, Seoul, South Korea.
³ Department of Computer Science and Engineering, University of California at San Diego, La Jolla, CA, USA.
⁴ Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA.
⁵ Department of Genetics, Stanford University, Stanford, CA, USA.
⁶ Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
⁷ Children's Medical Center Research Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA.
⁸ Sarafan Chemistry, Engineering, and Medicine for Human Health (Sarafan ChEM-H), Stanford University, Stanford, CA, USA.
⁹ Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
¹⁰ Halıcıoğlu Data Science Institute, University of California at San Diego, La Jolla, CA, USA.

PMID: 37162993
PMCID: PMC10168239
DOI: 10.1101/2023.04.24.537925

Update in

Transcriptional immune suppression and up-regulation of double-stranded DNA damage and repair repertoires in ecDNA-containing tumors.
Lin MS, Jo SY, Luebeck J, Chang HY, Wu S, Mischel PS, Bafna V. Lin MS, et al. Elife. 2024 Jun 19;12:RP88895. doi: 10.7554/eLife.88895. Elife. 2024. PMID: 38896472 Free PMC article.

Abstract

Extrachromosomal DNA is a common cause of oncogene amplification in cancer. The non-chromosomal inheritance of ecDNA enables tumors to rapidly evolve, contributing to treatment resistance and poor outcome for patients. The transcriptional context in which ecDNAs arise and progress, including chromosomally-driven transcription, is incompletely understood. We examined gene expression patterns of 870 tumors of varied histological types, to identify transcriptional correlates of ecDNA. Here we show that ecDNA containing tumors impact four major biological processes. Specifically, ecDNA containing tumors upregulate DNA damage and repair, cell cycle control, and mitotic processes, but downregulate global immune regulation pathways. Taken together, these results suggest profound alterations in gene regulation in ecDNA containing tumors, shedding light on molecular processes that give rise to their development and progression.

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Conflict of interest statement

Competing Interests V.B. is a co-founder, paid consultant, SAB member and has equity interest in Boundless Bio, inc. and Abterra Biosciences, Inc. H.Y.C. is a co-founder of Accent Therapeutics, Boundless Bio, Cartography Biosciences, Orbital Therapeutics, and an advisor of 10x Genomics, Arsenal Biosciences, Chroma Medicine, and Spring Discovery. P.S.M. is a co-founder and advisor of Boundless Bio. J.L. receives compensation as a consultant for Boundless Bio. The remaining authors declare no competing interests.

Figures

**Figure 1.. Genes predictive of ecDNA status.**
**(a)** The feature selection algorithm, Boruta, was applied to 200 datasets of randomly selected subsets consisting of 80% of all samples. Genes selected by Boruta in at least 10 of the 200 trials were identified as the Core set of genes (408) that were predictive of ecDNA presence. **(b)** Identification of highly co-expressed and stable gene clusters using pvclust expanded the Core set by an additional 235 genes to the final list of 643 CorEx genes. **(c)** Out of 354 clusters, the majority (344) of clusters contained 1 or 2 Core genes. **(d)** Most clusters were small, with only 7 clusters containing more than 10 genes.

**Figure 2.. Validation of CorEx genes.**
**(a)** Cross-validation experiments validating the predictive value of CorEx genes. Precision denotes the fraction of predicted samples that were truly ecDNA(+). Recall refers to the fraction of ecDNA(+) samples that were predicted correctly. **(b)** For precision windows of width 0.1 and a value of at least 0.5, recall values were plotted as boxplots. The interquartile ranges for CorEx and Core genes overlap, suggesting similar predictive power. CorEx genes have higher predictive rates compared to the top 643 differentially expressed genes based on logarithmic fold changes from a DESeq2 analysis (Top-|LFC| genes), 3,012 significant genes selected from a generalized linear model (GLM), and 643 randomly selected genes. **(c)** CorEx genes were consistently up- or down-regulated in ecDNA(+) samples across tumor types, with the exception of SARC. AU p-values from multiscale bootstrap resampling are shown at the dendrogram branches. **(d)** Of the 643 Top-|LFC| genes, 240 were up-regulated while 403 were down-regulated in ecDNA(+) samples. Of the CorEx genes, 325 were up-regulated while 318 were down-regulated. The absolute LFC values of the Top-|LFC| gene set was significantly greater than that of the CorEx genes (p-value 1.83e-158). **(e)** The normalized gene expression values of the CorEx genes were significantly higher than that of the Top-|LFC| gene set (p-value < 2e-308). ***p-value < 0.001.

**Figure 3.. Up-regulated CorEx genes.**
**(a)** GO biological processes enriched in up-regulated genes were clustered into 11 broad categories. The horizontal barplot represents the number of GO biological processes belonging to each of the 11 broad categories, while the vertical barplot represents the number of broad categories that a specific GO biological process belongs to. **(b)** Genes up- or down-regulated in processes involved in major double-strand break (DSB) damage repair pathways. Many critical genes in the c-NHEJ pathway were down-regulated in ecDNA(+) samples relative to ecDNA(−) samples.

**Figure 4.. Down-regulated CorEx genes.**
**(a)** GO biological processes enriched in down-regulated genes were clustered into 7 broad categories. The horizontal barplot represents the number of GO biological processes belonging to each of the 7 broad categories, while the vertical barplot represents the number of broad categories that a specific GO biological process belongs to. **(b)** Four of these categories map to steps in the cancer-immunity cycle. CorEx genes in three of the four categories were significantly down-regulated compared to all genes (Fisher’s exact test).

**Figure 5.. Mutational characteristics of ecDNA-containing tumors.**
**(a)** Total mutation burden of ecDNA(+) and ecDNA(−) samples. ecDNA(+) samples have significantly higher mutation burden than the ecDNA(−) samples (p-value < 0.0001, Mann Whitney test). **(b)** Odds ratios of differentially mutated genes in ecDNA(+) and ecDNA(−) (p-value < 0.005). The size of the dot indicates whether the corresponding gene belongs to the Cancer Gene Census (CGC) or not (Non-CGC). Only *TP53* and *BRAF* showed significance at the level of FDR < 0.1 (Benjamini-Hochberg).

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References

1. Turner K. M. et al. Extrachromosomal oncogene amplification drives tumour evolution and genetic heterogeneity. Nature 543, 122–125 (2017). - PMC - PubMed
1. Kim H. et al. Extrachromosomal DNA is associated with oncogene amplification and poor outcome across multiple cancers. Nat. Genet. 52, 891–897 (2020). - PMC - PubMed
1. Nathanson D. A. et al. Targeted therapy resistance mediated by dynamic regulation of extrachromosomal mutant EGFR DNA. Science 343, 72–76 (2014). - PMC - PubMed
1. Lange J. T. et al. The evolutionary dynamics of extrachromosomal DNA in human cancers. Nat. Genet. 54, 1527–1533 (2022). - PMC - PubMed
1. Luebeck J. et al. Extrachromosomal DNA in the cancerous transformation of Barrett’s oesophagus. Nature (2023) doi: 10.1038/s41586-023-05937-5. - DOI - PMC - PubMed

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This is a preprint.

Transcriptional immune suppression and upregulation of double stranded DNA damage and repair repertoires in ecDNA-containing tumors

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Transcriptional immune suppression and upregulation of double stranded DNA damage and repair repertoires in ecDNA-containing tumors

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Conflict of interest statement

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