Boundless Bio, Inc. (BB), and serve as consultants. V.B. is a co-founder, and has equity interest in Boundless Bio, inc. (BB) and Digital Proteomics, LLC (DP), and receives income from DP. The terms of this arrangement have been reviewed and approved by the University of California, San Diego in accordance with its conflict of interest policies. BB and DP were not involved in the research presented here. Data Availability. Whole genome-, RNA-, ATAC-, MNase-, ChIP-, PLAC-Seq data are deposited in the NCBI Sequence Read Archive (BioProject: PRJNA506071). The source data files of the pixel quantification of ATAC-see on metaphase chromosome spread images to create Extended Data Figure 7d are available on Figshare (

Extrachromosomal DNA (ecDNA) amplification promotes intratumoral genetic heterogeneity and accelerated tumor evolution 1 – 3 , but its frequency and clinical impact are unclear. Here we show, using computational analysis of whole-genome sequencing data from 3,212 cancer patients, that ecDNA amplification frequently occurs in most cancer types, but not in blood or normal tissue. Oncogenes were highly enriched on amplified ecDNA and the most common recurrent oncogene amplifications arise on ecDNA. EcDNA amplifications resulted in higher levels of oncogene transcription compared to copy number matched linear DNA, coupled with enhanced chromatin accessibility and more frequently resulted in transcript fusions. Patients whose cancers carry ecDNAs have significantly shorter survival, even when controlled for tissue type, than do patients whose cancers are not driven by ecDNA-based oncogene amplification. The results presented here demonstrate that ecDNA-based oncogene amplification is common in cancer, is different from chromosomal amplification and drives poor outcome for patients across many cancer types.

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Precision oncology hinges on linking tumor genotype with druggable enzymatic dependencies1, however targeting the frequently dysregulated metabolic landscape of cancer has proven to be a major challenge2. Here we show that tissue context is the major determinant of NAD metabolic pathway dependence in cancer. By analyzing over 7000 tumors and 2600 matched normal samples of 19 tissue types, coupled with mathematical modeling and extensive in vitro and in vivo analyses, we identify a simple and actionable set of "rules". If the rate limiting enzyme of de novo NAD synthesis, NAPRT, is highly expressed in a normal tissue type, cancers that arise from that tissue will have a high frequency of NAPRT amplification and will be completely and irreversibly dependent on NAPRT for survival. Tumors arising from normal tissues that do not highly express NAPRT are entirely dependent on the NAD Salvage-pathway for survival. We identify the previously unknown enhancer that underlies this dependence. NAPRT amplification is demonstrated to generate an absolute, pharmacologically actionable tumor cell dependence for survival; dependence on NAMPT generated through enhancer remodeling is subject to resistance through NMRK1-dependent NAD synthesis. These results identify a central role for tissue context §

Oncogene amplification, a major driver of cancer pathogenicity, is often mediated through focal amplification of genomic segments. Recent results implicate extrachromosomal DNA (ecDNA) as the primary driver of focal copy number amplification (fCNA)-enabling gene amplification, rapid tumor evolution, and the rewiring of regulatory circuitry. Resolving an fCNA's structure is a first step in deciphering the mechanisms of its genesis and the fCNA's subsequent biological consequences. We introduce a computational method, AmpliconReconstructor (AR), for integrating optical mapping (OM) of long DNA fragments (>150 kb) with next-generation sequencing (NGS) to resolve fCNAs at single-nucleotide resolution. AR uses an NGS-derived breakpoint graph alongside OM scaffolds to produce high-fidelity reconstructions. After validating its performance through multiple simulation strategies, AR reconstructed fCNAs in seven cancer cell lines to reveal the complex architecture of ecDNA, a breakage-fusion-bridge and other complex rearrangements. By reconstructing the rearrangement signatures associated with an fCNA's generative mechanism, AR enables a more thorough understanding of the origins of fCNAs.