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Lange, J. T.

Publications and source records attributed to Lange, J. T..

6 recordsLinked to original sources

Synergistic RAS-MAPK and AKT Activation in MYC-Driven Tumors via Adjacent PVT1 Rearrangements

MYC-driven (MYC+) cancers are aggressive and often fatal. MYC dysregulation is a key event in these cancers, but overexpression of MYC alone is not always enough to cause cancer. Plasmocytoma Variant Translocation 1 (PVT1), a long non-coding RNA (lncRNA) adjacent to MYC on chromosome 8 is a rearrangement hotspot in many MYC+ cancers. In addition to being co-amplified with MYC, the genomic rearrangement at PVT1 involves translocation, which has had obscure functional consequences. We report that translocation at the PVT1 locus cause asymmetric enrichment of 5-PVT1 and loss of 3-PVT1. Despite being classified as a non-coding RNA, the retained 5 region of PVT1 generates a circular RNA (CircPVT1) that codes for the novel peptide we call Firefox (FFX). FFX augments AKT signaling and synergistically activates MYC and mTORC1 in these cells. Further, the 3 end of PVT1, which is lost during the translocation, codes for a tumor-suppressing micropeptide we named as Honeybadger (HNB). We demonstrate that HNB interacts with KRAS and disrupts the activation of KRAS effectors. Loss of HNB leads to activation of RAS/MAPK signaling pathway, and enhances MYC stability by promoting phosphorylation of MYC at Ser62. These findings identify PVT1 as a critical node that synchronizes MYC, AKT, and RAS-MAPK activities in cancer. Our study thus identifies a key mechanism by which rearrangements at the PVT1 locus activate additional oncogenic pathways that synergize with MYC to exacerbate the aggressiveness of MYC+ cancers. This newfound understanding explains the poor prognosis associated with MYC+ cancers and offers potential therapeutic targets that could be leveraged in treatment strategies for these cancers.

cancer biology↗

Coordinated inheritance of extrachromosomal DNA species in human cancer cells

The chromosomal theory of inheritance has dominated human genetics, including cancer genetics. Genes on the same chromosome segregate together while genes on different chromosomes assort independently, providing a fundamental tenet of Mendelian inheritance. Extrachromosomal DNA (ecDNA) is a frequent event in cancer that drives oncogene amplification, dysregulated gene expression and intratumoral heterogeneity, including through random segregation during cell division. Distinct ecDNA sequences, herein termed ecDNA species, can co-exist to facilitate intermolecular cooperation in cancer cells. However, how multiple ecDNA species within a tumor cell are assorted and maintained across somatic cell generations to drive cancer cell evolution is not known. Here we show that cooperative ecDNA species can be coordinately inherited through mitotic co-segregation. Imaging and single-cell analyses show that multiple ecDNAs encoding distinct oncogenes co-occur and are correlated in copy number in human cancer cells. EcDNA species are coordinately segregated asymmetrically during mitosis, resulting in daughter cells with simultaneous copy number gains in multiple ecDNA species prior to any selection. Computational modeling reveals the quantitative principles of ecDNA co-segregation and co-selection, predicting their observed distributions in cancer cells. Finally, we show that coordinated inheritance of ecDNAs enables co-amplification of specialized ecDNAs containing only enhancer elements and guides therapeutic strategies to jointly deplete cooperating ecDNA oncogenes. Coordinated inheritance of ecDNAs confers stability to oncogene cooperation and novel gene regulatory circuits, allowing winning combinations of epigenetic states to be transmitted across cell generations.

cancer biology↗

The landscape of extrachromosomal circular DNA in medulloblastoma

Extrachromosomal circular DNA (ecDNA) is an important driver of aggressive tumor growth, promoting high oncogene copy number, intratumoral heterogeneity, accelerated evolution of drug resistance, enhancer rewiring, and poor outcome. ecDNA has been reported in medulloblastoma (MB), the most common malignant pediatric brain tumor, but the ecDNA landscape and its association with specific MB subgroups, its impact on enhancer rewiring, and its potential clinical implications, are not known. We assembled a retrospective cohort of 468 MB patient samples with available whole genome sequencing (WGS) data covering the four major MB subgroups WNT, SHH, Group 3 and Group 4. Using computational methods for the detection and reconstruction of ecDNA1, we find ecDNA in 82 patients (18%) and observe that ecDNA+ MB patients are more than twice as likely to relapse and three times as likely to die of disease. In addition, we find that individual medulloblastoma tumors often harbor multiple ecDNAs, each containing different amplified oncogenes along with co-amplified non-coding regulatory enhancers. ecDNA was substantially more prevalent among 31 analyzed patient-derived xenograft (PDX) models and cell lines than in our patient cohort. By mapping the accessible chromatin and 3D conformation landscapes of MB tumors that harbor ecDNA, we observe frequent candidate "enhancer rewiring" events that spatially link oncogenes with co-amplified enhancers. Our study reveals the frequency and diversity of ecDNA in a subset of highly aggressive tumors and suggests enhancer rewiring as a frequent oncogenic mechanism of ecDNAs in MB. Further, these results demonstrate that ecDNA is a frequent and potent driver of poor outcome in MB patients.

cancer biology↗

Principles of ecDNA random inheritance drive rapid genome change and therapy resistance in human cancers

The foundational principles of Darwinian evolution are variation, selection, and identity by descent. Oncogene amplification on extrachromosomal DNA (ecDNA) is a common event, driving aggressive tumour growth, drug resistance, and shorter survival in patients1-4. Currently, the impact of non-chromosomal oncogene inheritance--random identity by descent--is not well understood. Neither is the impact of ecDNA on variation and selection. Here, integrating mathematical modeling, unbiased image analysis, CRISPR-based ecDNA tagging, and live-cell imaging, we identify a set of basic "rules" for how random ecDNA inheritance drives oncogene copy number and distribution, resulting in extensive intratumoural ecDNA copy number heterogeneity and rapid adaptation to metabolic stress and targeted cancer treatment. Observed ecDNAs obligatorily benefit host cell survival or growth and can change within a single cell cycle. In studies ranging from well-curated, patient-derived cancer cell cultures to clinical tumour samples from patients with glioblastoma and neuroblastoma treated with oncogene-targeted drugs, we show how these ecDNA inheritance "rules" can predict, a priori, some of the aggressive features of ecDNA-containing cancers. These properties are entailed by their ability to rapidly change their genomes in a way that is not possible for cancers driven by chromosomal oncogene amplification. These results shed new light on how the non-chromosomal random inheritance pattern of ecDNA underlies poor outcomes for cancer patients.

cancer biology↗

EcDNA hubs drive cooperative intermolecular oncogene expression

Extrachromosomal DNAs (ecDNAs) are prevalent in human cancers and mediate high oncogene expression through elevated copy number and altered gene regulation1. Gene expression typically involves distal enhancer DNA elements that contact and activate genes on the same chromosome2,3. Here we show that ecDNA hubs, comprised of ~10-100 ecDNAs clustered in the nucleus of interphase cells, drive intermolecular enhancer input for amplified oncogene expression. Single-molecule sequencing, single-cell multiome, and 3D enhancer connectome reveal subspecies of MYC-PVT1 ecDNAs lacking enhancers that access intermolecular and ectopic enhancer-promoter interactions in ecDNA hubs. ecDNA hubs persist without transcription and are tethered by BET protein BRD4. BET inhibitor JQ1 disperses ecDNA hubs, preferentially inhibits ecDNA oncogene transcription, and kills ecDNA+ cancer cells. Two amplified oncogenes MYC and FGFR2 intermix in ecDNA hubs, engage in intermolecular enhancer-promoter interactions, and transcription is uniformly sensitive to JQ1. Thus, ecDNA hubs are nuclear bodies of many ecDNAs tethered by proteins and platforms for cooperative transcription, leveraging the power of oncogene diversification and combinatorial DNA interactions. We suggest ecDNA hubs, rather than individual ecDNAs, as units of oncogene function, cooperative evolution, and new targets for cancer therapy.

cancer biology↗

AmpliconReconstructor: Integrated analysis of NGS and optical mapping resolves the complex structures of focal amplifications in cancer

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 mechanism driving focal copy number amplification (fCNA) - enabling gene amplification, rapid tumor evolution, and the rewiring of regulatory circuitry. Resolving an fCNAs structure is a first step in deciphering the mechanisms of its genesis and the subsequent biological consequences. Here, we introduce a powerful new computational method, AmpliconReconstructor (AR), for integrating optical mapping (OM) of long DNA fragments (>150kb) 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 performance by extensive simulations, we used AR to reconstruct fCNAs in seven cancer cell lines to reveal the complex architecture of ecDNA, breakage-fusion-bridge cycles, and other complex rearrangements. By distinguishing between chromosomal and extrachromosomal origins, and by reconstructing the rearrangement signatures associated with a given fCNAs generative mechanism, AR enables a more thorough understanding of the origins of fCNAs, and their functional consequences.

bioinformatics↗