Biology subjects

Curtis, E. J.

Publications and source records attributed to Curtis, E. J..

7 recordsLinked to original sources

bioRxiv2026

Dynamic optimization of extrachromosomal DNA copy number drives tumour evolution

Extrachromosomal DNA (ecDNA) is common in human cancers and is associated with poor clinical outcomes, yet how ecDNA-driven genetic heterogeneity is translated into functional heterogeneity remains unclear. Using single-cell multiomics sequencing and multiplexed IF-FISH, we show that asymmetric inheritance of ecDNA generates copy number heterogeneity that propagates to gene expression programs, including oncogenic signaling and cellular stress responses. Transgenerational live-cell lineage tracking directly shows that ecDNA heterogeneity arises within only a few cell divisions and modulates daughter cell division timing in a copy number-dependent manner, a property not observed for evenly inherited chromosomal amplicons. We identify an optimal middle ecDNA copy number range that maximizes proliferative fitness at baseline, while drug selection pressure induced by low-dose CHK1 inhibition selects for cells with a new optimal range at low ecDNA copy numbers. These low ecDNA copy number cells pre-exist in the population and can be generated de novo, driving copy number shifts promoting drug resistance. In vivo experiments further demonstrate that shifts toward ecDNA copy numbers that are optimal under the tumour microenvironment enhance tumourigenicity. Together, these findings establish ecDNA copy number plasticity as a central driver of tumour evolution.

cancer biology↗

bioRxiv2026

scAmp analyzes focal gene amplifications at single-cell resolution

Oncogene amplification on extrachromosomal DNA (ecDNA) is a common driver of tumor progression and is associated with acquired drug resistance and poor patient survival. While whole genome sequencing (WGS) studies have revealed the landscape of genes amplified on ecDNA in tumors, it remains challenging to study the subclonal heterogeneity and functional (e.g., transcriptomic) consequences of ecDNA on tumors. To address this, we introduce scAmp: a probabilistic algorithm for detecting and analyzing ecDNA from single-cell datasets. We demonstrate scAmps improved accuracy over WGS approaches on well-characterized cell-lines and its applicability to clinical histopathology. We further showcase scAmp by analyzing 73 patient tumors profiled with single-cell ATAC-seq, where we analyze the subclonal evolution of ecDNA+ subclones and identify the effect of ecDNA amplifications on the chromatin accessibility landscape of cancer cells. Together, we anticipate that scAmp will broadly enable further studies - both retrospective and prospective - that dissect critical questions of how ecDNA affect cancer cells and the tumors in which they reside.

cancer biology↗

bioRxiv2025

Accurate Prediction of ecDNA in Interphase Cancer Cells using Deep Neural Networks

Oncogene amplification is a key driver of cancer pathogenesis and is often mediated by extrachromosomal DNA (ecDNA). EcDNA amplifications are associated with increased pathogenicity of cancer and poorer outcomes for patients. EcDNA can be detected accurately using fluorescence in situ hybridization (FISH) when cells are arrested in metaphase. However, the majority of cancer cells are non-mitotic and must be analyzed in interphase, where it is difficult to discern extrachromosomal amplifications from chromosomal amplifications. Thus, there is a need for methods that accurately predict oncogene amplification status from interphase cells. Here, we present interSeg, a deep learning-based tool to cytogenetically determine the amplification status as EC-amp, HSR-amp, or not amplified from interphase FISH images. We trained and validated interSeg on 652 images (40,446 nuclei). Tests on 215 cultured cell and tissue model images (9,733 nuclei) showed 89% and 97% accuracy at the nuclear and sample levels, respectively. The neuroblastoma patient tissue hold-out set (67 samples and 1,937 nuclei) also revealed 97% accuracy at the sample level in detecting the presence of focal amplification. In experimentally and computationally mixed images, interSeg accurately predicted the level of heterogeneity. The results showcase interSeg as an important method for analyzing oncogene amplifications.

cancer biology↗

bioRxiv2025

EcDNA-borne PVT1 fusion stabilizes oncogenic mRNAs

Extrachromosomal DNA (ecDNA) amplifications are prevalent drivers of human cancers. We show that ecDNAs exhibit elevated structural variants leading to gene fusions that produce oncogene fusion transcripts. The long noncoding RNA (lncRNA) gene PVT1 is the most recurrent structural variant across cancer genomes, with PVT1-MYC fusions arising most frequently on ecDNA. PVT1 exon 1 is the predominant 5 partner fused to MYC or other oncogenes on the 3 end. Mechanistic studies demonstrate that PVT1 exon 1 confers enhanced RNA stability for fusion transcripts, which requires PVT1 exon 1 interaction with SRSF1 protein. Genetic rescue of MYC-addicted cancer models and isoform-specific single-cell RNA sequencing of tumors reveal that PVT1-MYC better supports MYC dependency and better activates MYC target genes in vivo. Thus, the mutagenic landscape of ecDNA contributes to genome instability and generates chimeric fusions of lncRNA and mRNA genes, selecting PVT1 5 region as a stabilizer of oncogene mRNAs.

cancer biology↗

bioRxiv2024

Rampant transcription replication conflict creates therapeutic vulnerability in extrachromosomal DNA containing cancers

Extrachromosomal DNA (ecDNA) presents a major challenge for precision medicine, contributing to poor survival for patients with oncogene-amplified tumours. EcDNA renders tumours resistant to targeted treatments by facilitating massive transcription of oncogenes and rapid genome evolution. At present, there are no ecDNA- specific treatments. Here we show that enhancing transcription replication conflict enables targeted elimination of ecDNA-containing cancers, exposing an actionable vulnerability. Stepwise analyses of ecDNA transcription reveal landscapes of pervasive RNA transcription and associated single-stranded DNA, leading to excessive transcription replication conflicts and replication stress (RS) compared to chromosomal loci. Nucleotide incorporation onto growing DNA strands is markedly slower on ecDNA, and RS is significantly higher in ecDNA-containing tumours regardless of cancer type or oncogene cargo. Replication Protein A2 phosphorylated on serine 33, a mediator of DNA damage repair that binds single-stranded DNA, shows elevated localization on ecDNA in a transcription dependent manner, along with increased DNA double strand breaks, and activation of the S-phase checkpoint kinase, CHK1. Genetic or pharmacological CHK1 inhibition abrogates the DNA replication check point, causing extensive and preferential tumour cell death in ecDNA-containing tumours as they enter S-phase. To exploit this vulnerability, we develop a highly selective, potent, and bioavailable oral CHK1 inhibitor, BBI-2779, and demonstrate that it preferentially kills ecDNA-containing tumour cells. In a gastric cancer model containing FGFR2 on ecDNA, BBI-2779, suppresses tumour growth and prevents ecDNA-mediated acquired resistance to the pan-FGFR inhibitor infigratinib, resulting in potent and sustained tumour regression in mice. These results reveal transcription-replication conflict as an ecDNA-generated vulnerability that can be targeted as an ecDNA-directed therapy and suggest that synthetic lethality of excess can be exploited as a strategy for treating cancer.

cancer biology↗

bioRxiv2023

Disparate pathways for extrachromosomal DNA biogenesis and genomic DNA repair

Oncogene amplification on extrachromosomal DNA (ecDNA) is a pervasive driver event in cancer, yet our understanding of how ecDNA forms is limited. Here, we couple a CRISPR-based method for induction of ecDNA with extensive characterization of newly formed ecDNA to examine ecDNA biogenesis. We find that DNA circularization is efficient, irrespective of 3D genome context, with formation of a 1 Mb and 1.8 Mb ecDNA both reaching 15%. We show non-homologous end joining and microhomology mediated end joining both contribute to ecDNA formation, while inhibition of DNA-PKcs and ATM have opposing impacts on ecDNA formation. EcDNA and the corresponding chromosomal excision scar form at significantly different rates and respond differently to DNA-PKcs and ATM inhibition. Taken together, our results support a model of ecDNA formation in which double strand break ends dissociate from their legitimate ligation partners prior to joining of illegitimate ends to form the ecDNA and excision scar. SIGNIFICANCEOur study harnesses a CRISPR-based method to examine ecDNA biogenesis, uncovering efficient circularization between DSBs. ecDNAs and their corresponding chromosomal scars can form via NHEJ or MMEJ, but the ecDNA and scar formation processes are distinct. Based on our findings, we establish a mechanistic model of excisional ecDNA formation.

cancer biology↗

bioRxiv2021

Targeting Glioblastoma Signaling and Metabolism with A Re-Purposed Brain-Penetrant Drug

The highly lethal brain cancer glioblastoma (GBM) poses a daunting challenge because the blood-brain barrier renders potentially druggable amplified or mutated oncoproteins relatively inaccessible. Here, we identify SMPD1, an enzyme that regulates the conversion of sphingomyelin to ceramide and a critical regulator of plasma membrane structure and organization, as an actionable drug target in glioblastoma. We show that the safe and highly brain-penetrant antidepressant fluoxetine, potently inhibits SMPD1 activity, killing GBMs, in vitro and in patient-derived xenografts, through inhibition of EGFR signaling and via activation of lysosomal stress. Combining fluoxetine with the chemotherapeutic agent temozolomide, a standard of care for GBM patients, causes massive increases in GBM cell death, and complete and long-lived tumor regression in mice. Incorporation of real-world evidence from electronic medical records from insurance databases, reveals significantly increased survival in glioblastoma patients treated with fluoxetine, which was not seen in patients treated with other SSRI anti-depressants. These results nominate the repurposing of fluoxetine as a potentially safe and promising therapy for GBM patients and suggest prospective randomized clinical trials.

cancer biology↗