Biology subjects

Chen, K.

Publications and source records attributed to Chen, K..

At least 217 records · Page 12Linked to original sources

bioRxiv2023

Neuronal functional connectivity is impaired in a layer dependent manner near the chronically implanted microelectrodes

ObjectiveThis study aims to reveal longitudinal changes in functional network connectivity within and across different brain structures near the chronically implanted microelectrode. While it is well established that the foreign-body response (FBR) contributes to the gradual decline of the signals recorded from brain implants over time, how does the FBR impact affect the functional stability of neural circuits near implanted Brain-Computer Interfaces (BCIs) remains unknown. This research aims to illuminate how the chronic FBR can alter local neural circuit function and the implications for BCI decoders. ApproachThis study utilized multisite Michigan-style microelectrodes that span all cortical layers and the hippocampal CA1 region to collect spontaneous and visually-evoked electrophysiological activity. Alterations in neuronal activity near the microelectrode were tested assessing cross-frequency synchronization of LFP and spike entrainment to LFP oscillatory activity throughout 16 weeks after microelectrode implantation. Main ResultsThe study found that cortical layer 4, the input-receiving layer, maintained activity over the implantation time. However, layers 2/3 rapidly experienced severe impairment, leading to a loss of proper intralaminar connectivity in the downstream output layers 5/6. Furthermore, the impairment of interlaminar connectivity near the microelectrode was unidirectional, showing decreased connectivity from Layers 2/3 to Layers 5/6 but not the reverse direction. In the hippocampus, CA1 neurons gradually became unable to properly entrain to the surrounding LFP oscillations. SignificanceThis study provides a detailed characterization of network connectivity dysfunction over long-term microelectrode implantation periods. This new knowledge could contribute to the development of targeted therapeutic strategies aimed at improving the health of the tissue surrounding brain implants and potentially inform engineering of adaptive decoders as the FBR progresses. Our studys understanding of the dynamic changes in the functional network over time opens the door to developing interventions for improving the long-term stability and performance of intracortical microelectrodes.

bioengineering↗

bioRxiv2023

Heterozygous Kmt2d loss diminishes enhancers to render medulloblastoma cells vulnerable to combinatory inhibition of lysine demethylation and oxidative phosphorylation

The histone H3 lysine 4 (H3K4) methyltransferase KMT2D (also called MLL4) is one of the most frequently mutated epigenetic modifiers in medulloblastoma (MB) and many other types of cancer. Notably, heterozygous loss of KMT2D is prevalent in MB and other cancer types. However, what role heterozygous KMT2D loss plays in tumorigenesis has not been well characterized. Here, we show that heterozygous Kmt2d loss highly promotes MB driven by heterozygous loss of the MB suppressor gene Ptch in mice. Heterozygous Kmt2d loss upregulated tumor-promoting programs, including oxidative phosphorylation and G-protein-coupled receptor signaling, in Ptch+/--driven MB genesis. Mechanistically, both downregulation of the transcription-repressive tumor suppressor gene NCOR2 by heterozygous Kmt2d loss and upregulation of the oncogene MycN by heterozygous Ptch loss increased the expression of tumor-promoting genes. Moreover, heterozygous Kmt2d loss extensively diminished enhancer signals (e.g., H3K27ac) and H3K4me3 signature, including those for tumor suppressor genes (e.g., Ncor2). Combinatory pharmacological inhibition of oxidative phosphorylation and the enhancer-decommissioning H3K4 demethylase LSD1 drastically reduced tumorigenicity of MB cells bearing heterozygous Kmt2d loss. These findings reveal the mechanistic basis underlying the MB-promoting effect of heterozygous KMT2D loss, provide a rationale for a therapeutic strategy for treatment of KMT2D-deficient MB, and have mechanistic implications for the molecular pathogenesis of other types of cancer bearing heterozygous KMT2D loss.

cancer biology↗

bioRxiv2023

Combining Blood-Based Biomarkers and Structural MRI Measurements to Distinguish Persons With and Without Significant Amyloid Plaques

BackgroundAmyloid-{beta} (A{beta}) plaques play a pivotal role in Alzheimers disease. The current positron emission tomography (PET) is expensive and limited in availability. In contrast, blood-based biomarkers (BBBMs) show potential for characterizing A{beta} plaques more affordably. We have previously proposed an MRI-based hippocampal morphometry measure to be an indicator of A{beta}-plaques. ObjectiveTo develop and validate an integrated model to predict brain amyloid PET positivity combining MRI feature and plasma A{beta}42/40 ratio. MethodsWe extracted hippocampal multivariate morphometry statistics (MMS) from MR images and together with plasma A{beta}42/40 trained a random forest classifier to perform a binary classification of participant brain amyloid PET positivity. We evaluated the model performance using two distinct cohorts, one from the Alzheimers Disease Neuroimaging Initiative (ADNI) and the other from the Banner Alzheimers Institute (BAI), including prediction accuracy, precision, recall rate, F1 score and AUC score. ResultsResults from ADNI (mean age 72.6, A{beta}+ rate 49.5%) and BAI (mean age 66.2, A{beta}+ rate 36.9%) datasets revealed the integrated multimodal (IMM) models superior performance over unimodal models. The IMM model achieved prediction accuracies of 0.86 in ADNI and 0.92 in BAI, surpassing unimodal models based solely on structural MRI (0.81 and 0.87) or plasma A{beta}42/40 (0.73 and 0.81) predictors. ConclusionOur IMM model, combining MRI and BBBM data, offers a highly accurate approach to predict brain amyloid PET positivity. This innovative multiplex biomarker strategy presents an accessible and cost-effective avenue for advancing Alzheimers disease diagnostics, leveraging diverse pathologic features related to A{beta} plaques and structural MRI.

neuroscience↗

bioRxiv2023

An in vitro platform for quantifying cell cycle phase lengths in primary human intestinal stem cells

Background and AimsThe intestinal epithelium exhibits dynamic control of cell cycle phase lengths, yet no experimental platform exists for directly analyzing cell cycle phases in living human intestinal stem cells (ISCs). Here, we develop primary human ISC lines with two different reporter constructs to provide fluorescent readouts to analyze cell cycle phases in cycling ISCs. Methods3D printing was used to construct a collagen press for making chamber slides that support primary human ISC growth and maintenance within the working distance of a confocal microscope objective. The PIP-FUCCI fluorescent cell cycle reporter and a variant with H2A-mScarlet that allows for automated tracking of cell cycle phases (PIP-H2A) were used in human ISCs along with live imaging and EdU pulsing. An analysis pipeline combining free-to-use programs and publicly available code was compiled to analyze live imaging results. ResultsChamber slides with soft collagen pressed to a thickness of 0.3 mm concurrently support ISC cycling and confocal imaging. PIP-FUCCI ISCs were found to be optimal for snapshot analysis wherein all nuclei are assigned to a cell cycle phase from a single image. PIP-H2A ISCs were better suited for live imaging since constant nuclear signal allowed for more automated analysis. CellPose2 and TrackMate were used together to track cycling cells. ConclusionsWe present two complete platforms for analyzing cell cycle phases in living primary human ISCs. The PIP-FUCCI construct allows for cell cycle phase assignment from one image of living cells, the PIP-H2A construct allows for semi-automated direct quantification of cell cycle phase lengths in human ISCs using our computational pipeline. These platforms hold great promise for future studies on how pharmaceutical agents affect the intestinal epithelium, how cell cycle is regulated in human ISCs, and more.

cell biology↗

bioRxiv2023

Deep learning models of RNA base-pairing structures generalize to unseen folds and make accurate zero-shot predictions of base-base interactions of RNA complexes

The intricate network of RNA-RNA interactions, crucial for orchestrating essential cellular processes like transcriptional and translational regulation, has been unveiling through high-throughput techniques and computational predictions. With the emergence of deep learning methodologies, the question arises: how do these cutting-edge techniques for base-pairing prediction compare to traditional free-energy-based approaches, particularly when applied to the challenging domain of interaction prediction via chain concatenation? In this study, we employ base pairs derived from three-dimensional RNA complex structures as the gold standard benchmark to assess the performance of 23 different methods, including recently developed deep learning models. Our results demonstrate that the deep-learning-based methods, SPOT-RNA can be generalized to make accurate zero-shot predictions of RNA-RNA interactions not only between previously unseen RNA structures but also between RNAs without monomeric structures. The finding underscores the potential of deep learning as a robust tool for advancing our understanding of these complex molecular interactions.

bioinformatics↗

bioRxiv2023

Comparative single-cell regulome reveals evolutionary innovations in neural progenitor cells during primate corticogenesis

The cellular and genetic mechanism underlying the human-specific features of cortex development remains unclear. We generated a cell-type resolved atlas of transcriptome and regulome of the developing macaque and mouse prefrontal cortex, and conducted evolutionary analyses with the published complementary human data. We discovered a primate-specific expansion of two neural progenitor subclasses, glia-committed radial glia (RG) and truncated RG. Specifically, the human neural progenitors show extensive transcriptional rewiring in the growth factor and extracellular matrix pathways. Expression of the human-specific progenitor marker ITGA2 in the cortex of fetal mouse promotes progenitor proliferation and an increased upper-layer neuron proportion. We demonstrate that these transcriptional divergences are primarily driven by the activity changes of the distal regulatory elements in the genome. Markedly, the chromatin regions with human-gained accessibility enrich the human-fixed sequence changes, as well as sequence polymorphisms associated with intelligence and neuropsychiatric disorders. Our results uncover evolutionary innovations in neural progenitors and gene regulatory mechanism during primate cortex evolution.

evolutionary biology↗

bioRxiv2023

Sound elicits stereotyped facial movements that provide a sensitive index of hearing abilities

Sound elicits rapid movements of muscles in the face, ears, and eyes that protect the body from injury and trigger brain-wide internal state changes. Here, we performed quantitative facial videography from mice resting atop a piezoelectric force plate and observed that broadband sounds elicit rapid, small, and highly stereotyped movements of a facial region near the vibrissae array. Facial motion energy (FME) analysis revealed sensitivity to far lower sound levels than the acoustic startle reflex and greater reliability across trials and mice than sound-evoked pupil dilations or movement of other facial and body regions. FME tracked the low-frequency envelope of sounds and could even decode speech phonemes in varying levels of background noise with high accuracy. FME growth slopes were disproportionately steep in mice with autism risk gene mutations and noise-induced sensorineural hearing loss, providing an objective behavioral measure of sensory hyper-responsivity. Increased FME after noise-induced cochlear injury was closely associated with the emergence of excess gain in later waves of the auditory brainstem response, suggesting a midbrain contribution. Deep layer auditory cortex units were entrained to spontaneous facial movements but optogenetic suppression of cortical activity facilitated - not suppressed - sound-evoked FME, suggesting the auditory cortex is a modulator rather than a mediator of sound-evoked facial movements. These findings highlight a simple involuntary behavior that is more sensitive and integrative than other auditory reflex pathways and captures higher-order changes in sound processing from mice with inherited and acquired hearing disorders.

neuroscience↗

bioRxiv2023

Super-silencer perturbation by EZH2 and REST inhibition leads to large loss of chromatin interactions and reduction in cancer growth

Human silencers have been shown to exist and regulate developmental gene expression. However, the functional importance of human silencers needs to be elucidated, such as whether they can form "super-silencers" and whether they are linked to cancer progression. Here, through interrogating two putative silencer components of FGF18 gene, we found that two nearby silencers can cooperate via compensatory chromatin interactions to form a "super-silencer". Furthermore, double knockout of two silencers exhibited synergistic upregulation of FGF18 expression and changes of cell identity. To perturb the "super-silencers", we applied combinational treatment of an EZH2 inhibitor GSK343, and a REST inhibitor, X5050 ("GR"). We found that GR led to severe loss of TADs and loops, while the use of one inhibitor by itself only showed mild changes. Such changes in TADs and loops were associated with reduced CTCF and TOP2A mRNA levels. Moreover, GSK343 and X5050 synergistically upregulated super-silencer-controlled genes related to cell cycle, apoptosis and DNA damage, leading to anticancer effects both in vitro and in vivo. Overall, our data demonstrated the first example of a "super-silencer" and showed that combinational usage of GSK343 and X5050 to disrupt "super-silencers" could potentially lead to cancer ablation.

molecular biology↗

bioRxiv2023

Brain-Derived CCN3 Is An Osteoanabolic Hormone That Sustains Bone in Lactating Females

In lactating mothers, the high calcium (Ca2+) demand for milk production triggers significant bone resorption. While estrogen would normally counteract excessive bone loss and maintain sufficient bone formation during this postpartum period, this sex steroid drops precipitously after giving birth. Here, we report that brain-derived CCN3 (Cellular Communication Network factor 3) secreted from KISS1 neurons of the arcuate nucleus (ARCKISS1) fills this void and functions as a potent osteoanabolic factor to promote bone mass in lactating females. Using parabiosis and bone transplant methods, we first established that a humoral factor accounts for the female-specific, high bone mass previously observed by our group after deleting estrogen receptor alpha (ER) from ARCKISS1 neurons1. This exceptional bone phenotype in mutant females can be traced back to skeletal stem cells (SSCs), as reflected by their increased frequency and osteochondrogenic potential. Based on multiple assays, CCN3 emerged as the most promising secreted pro-osteogenic factor from ARCKISS1 neurons, acting on mouse and human SSCs at low subnanomolar concentrations independent of age or sex. That brain-derived CCN3 promotes bone formation was further confirmed by in vivo gain- and loss-of-function studies. Notably, a transient rise in CCN3 appears in ARCKISS1 neurons in estrogen-depleted lactating females coincident with increased bone remodeling and high calcium demand. Our findings establish CCN3 as a potentially new therapeutic osteoanabolic hormone that defines a novel female-specific brain-bone axis for ensuring mammalian species survival.

neuroscience↗

bioRxiv2023

The ubiquitin ligase STUB1 suppresses tumorigenesis of renal cell carcinomas through regulating YTHDF1 stability

STIP1 homology and U-box protein 1 (STUB1), a key RING family E3 ubiquitin ligase, plays both oncogenic and tumor-suppressive roles in a variety of human cancers. However, the role and mechanism of STUB1 in clear cell renal cell carcinoma (ccRCC) remains poorly defined. Here, we identified YTHDF1 as a novel STUB1 interactor by affinity purification mass spectrometry (AP-MS). STUB1 polyubiquitylates YTHDF1 and promotes YTHDF1 degradation. STUB1 depletion stabilizes YTHDF1 in renal cancer cells. STUB1-knockdown renal cancer cells exhibit increased migration and invasion in YTHDF1 dependent manner. Further study demonstrates that STUB1 knockdown promoted the tumorigenicity of ccRCC in a xenograft model. Clinically, STUB1 expression is down-regulated in ccRCC tissues, and the low expression level of STUB1 was associated with higher tumor stage and poor overall survival in patients with ccRCC. These findings reveal that STUB1 acts as an E3 ubiquitin ligase and promotes degradation of YTHDF1, and STUB1 inhibits the tumorigenicity of ccRCC through ubiquitinating YTHDF1. Novelty & Impact StatementsSTUB1 plays both oncogenic and tumor-suppressive roles in a variety of human cancers. Here, the authors demonstrated that STUB1 acts as a tumor suppressor in ccRCC, and the low expression level of STUB1 was associated with higher tumor stage and poor overall survival in patients with ccRCC. In addition, STUB1-knockdown renal cancer cells exhibit increased migration and invasion in YTHDF1 dependent manner. Mechanistically, STUB1 polyubiquitylates YTHDF1 and promotes YTHDF1 degradation.

cancer biology↗

bioRxiv2023

Benchmarking of Small Molecule Feature Representations for hERG, Nav1.5, and Cav1.2 Cardiotoxicity Prediction

In the field of drug discovery, there is a substantial challenge in seeking out chemical structures that possess desirable pharmacological, toxicological, and pharmacokinetic properties. Complications arise when drugs interfere with the functioning of cardiac ion channels, leading to serious cardiovascular consequences. The discontinuation and removal of numerous approved drugs from the market or at late development stages in the pipeline due to such inhibitory effects further highlight the urgency of addressing this issue. Consequently, the early prediction of potential blockers targeting cardiac ion channels during the drug discovery process is of paramount importance. This study introduces a deep learning framework that computationally determines the cardiotoxicity associated with the voltagegated potassium channel (hERG), the voltage-gated calcium channel (Cav1.2), and the voltage-gated sodium channel (Nav1.5) for drug candidates. The predictive capabilities of three feature representations--molecular fingerprints, descriptors, and graph-based numerical representations-- are rigorously benchmarked. Additionally, a novel training and evaluation dataset framework is presented, enabling predictive model training of drug off-target cardiotoxicity using a comprehensive and large curated dataset covering these three cardiac ion channels. To facilitate these predictions, a robust and comprehensive small molecule cardiotoxicity prediction tool named CToxPred has been developed. It is made available as open source under the permissive MIT license at https://github.com/issararab/CToxPred.

pharmacology and toxicology↗

bioRxiv2023

Eukaryotic RNA-guided endonucleases evolved from a unique clade of bacterial enzymes

RNA-guided endonucleases form the crux of diverse biological processes and technologies, including adaptive immunity, transposition, and genome editing. Some of these enzymes are components of insertion sequences (IS) in the IS200/IS605 and IS607 transposon families. Both IS families encode a TnpA transposase and TnpB nuclease, an RNA-guided enzyme ancestral to CRISPR-Cas12. In eukaryotes and their viruses, TnpB homologs occur as two distinct types, Fanzor1 and Fanzor2. We analyzed the evolutionary relationships between prokaryotic TnpBs and eukaryotic Fanzors, revealing that a clade of IS607 TnpBs with unusual active site arrangement found primarily in Cyanobacteriota likely gave rise to both types of Fanzors. The wide-spread nature of Fanzors imply that the properties of this particular group of IS607 TnpBs were particularly suited to adaptation and evolution in eukaryotes and their viruses. Experimental characterization of a prokaryotic IS607 TnpB and virally encoded Fanzor1s uncovered features that may have fostered coevolution between TnpBs/Fanzors and their cognate transposases. Our results provide insight into the evolutionary origins of a ubiquitous family of RNA-guided proteins that shows remarkable conservation across domains of life.

molecular biology↗

bioRxiv2023

Multi-region spatial transcriptome analysis reveals cellular networks and pathways associated with hepatocellular carcinoma recurrence

Hepatocellular carcinomas (HCC) are driven by various etiologies and molecular diversity at presentation. Patient prognosis post-surgery is generally dismal, and the majority respond poorly to adjuvant targeted and/or immuno-therapies. Tumours are an ecosystem comprised of organization and interaction between different cell types that may contribute to clinically significant outcomes, such as disease recurrence. To better understand this phenomenon, we leveraged on a local cohort of patients with or without recurrence to generate spatial transcriptome profiles from multiple sectors from each tumour. We identified widespread gene expression intra- and inter tumour heterogeneity observed across the tumour sectors. Our analysis also revealed the cell type enrichment and localization, and ligand-receptor interactions identify a specific subset of endothelial cell enriched in primary tumours of patients with recurrence. Altogether, this study describes the spatial gene expression landscape in HCC patients associated with disease recurrence.

cancer biology↗

bioRxiv2023

Using graph-based model to identify cell specific synthetic lethal effects

Synthetic lethal (SL) pairs are pairs of genes whose simultaneous loss-of-function results in cell death, while a damaging mutation of either gene alone does not affect the cells survival. This makes SL pairs attractive targets for precision cancer therapies, as targeting the unimpaired gene of the SL pair can selectively kill cancer cells that already harbor the impaired gene. Limited by the difficulty of finding true SL pairs, especially on specific cell types, the identification of SL targets still relies on expensive, time-consuming experimental approaches. In this work, we utilized various cell-line specific omics data to design a deep learning model for predicting SL pairs on particular cell-lines. By incorporating multiple types of cell-specific omics data with a self-attention module, we represent gene relationships as graphs. Our approach demonstrates the potential to facilitate the discovery of cell-specific SL targets for cancer therapeutics, providing a tool to unearth mechanisms underlying the origin of SL in cancer biology. Our approach allows for prediction of SL pairs in a cell-specific manner and enhances cancer precision medicine. The code and data of our approach can be found at https://github.com/promethiume/SLwise HighlightsO_LIFew computational methods can systematically predict SL pairs at a cell-specific level, and their performance may not generalize well to clinical scenarios due to the heterogeneity of cancer types. C_LIO_LIThe SLWise utilizes various cell-line specific omics data to design a deep learning model with a graph-based representation and self-attention mechanism. C_LIO_LIThis approach allows for the prediction of SL pairs in a cell-specific manner, providing valuable insights on effectively identifying the cell-type specific SL targets for personalized treatment strategies. C_LI

bioinformatics↗

bioRxiv2023

EMDiffuse: a diffusion-based deep learning method augmenting ultrastructural imaging and volume electron microscopy

Electron microscopy (EM) revolutionized the way to visualize cellular ultrastructure. Volume EM (vEM) has further broadened its three-dimensional nanoscale imaging capacity. However, intrinsic trade-offs between imaging speed and quality of EM restrict the attainable imaging area and volume. Isotropic imaging with vEM for large biological volumes remains unachievable. Here we developed EMDiffuse, a suite of algorithms designed to enhance EM and vEM capabilities, leveraging the cutting-edge image generation diffusion model. EMDiffuse demonstrates outstanding denoising and super-resolution performance, generates realistic predictions without unwarranted smoothness, improves predictions resolution by [~]30%, and exhibits excellent transferability by taking only one pair of images to fine-tune. EMDiffuse also pioneers the isotropic vEM reconstruction task, generating isotropic volume similar to that obtained using advanced FIB-SEM even in the absence of isotropic training data. We demonstrated the robustness of EMDiffuse by generating isotropic volumes from six public datasets obtained from different vEM techniques and instruments. The generated isotropic volume enables accurate organelle reconstruction, making 3D nanoscale ultrastructure analysis faster and more accessible and extending such capability to larger volumes. More importantly, EMDiffuse features self-assessment functionalities and guarantees reliable predictions for all tasks. We envision EMDiffuse to pave the way for more in-depth investigations into the intricate subcellular nanoscale structures within large areas and volumes of biological systems.

cell biology↗

bioRxiv2023

Aster-dependent non-vesicular transport facilitates dietary cholesterol uptake

Intestinal cholesterol absorption is an important contributor to systemic cholesterol homeostasis. Niemann-Pick C1 Like 1 (NPC1L1), the target of the drug ezetimibe (EZ), assists in the initial step of dietary cholesterol uptake. However, how cholesterol moves downstream of NPC1L1 is unknown. Here we show that Aster-B and Aster-C are critical for non-vesicular cholesterol movement in enterocytes, bridging NPC1L1 at the plasma membrane (PM) and ACAT2 in the endoplasmic reticulum (ER). Loss of NPC1L1 diminishes accessible PM cholesterol in enterocytes and abolishes Aster recruitment to the intestinal brush border. Enterocytes lacking Asters accumulate cholesterol at the PM and display evidence of ER cholesterol depletion, including decreased cholesterol ester stores and activation of the SREBP-2 transcriptional pathway. Aster-deficient mice have impaired cholesterol absorption and are protected against diet-induced hypercholesterolemia. Finally, we show that the Aster pathway can be targeted with a small molecule inhibitor to manipulate dietary cholesterol uptake. These findings identify the Aster pathway as a physiologically important and pharmacologically tractable node in dietary lipid absorption. One-Sentence SummaryIdentification of a targetable pathway for regulation of dietary cholesterol absorption

physiology↗

bioRxiv2023

Spatiotemporal Mapping of brain cilia length and orientation reveals region-specific Oscillation

In this study, we conducted high-throughput spatiotemporal analysis of primary cilia length and orientation across 22 mouse brain regions. We developed automated image analysis algorithms, which enabled us to examine over 10 million individual cilia, generating the largest spatiotemporal atlas of cilia. We found that cilia length and orientation display substantial variations across different brain regions and exhibit fluctuations over a 24-hour period, with region-specific peaks during light-dark phases. Our analysis revealed unique orientation patterns of cilia at 45{degrees} intervals, suggesting that cilia orientation within the brain is not random but follows specific patterns. Using BioCycle, we identified circadian rhythms of cilia length in five brain regions: nucleus accumbens core, somatosensory cortex, and three hypothalamic nuclei. Our findings present novel insights into the complex relationship between cilia dynamics, circadian rhythms, and brain function, highlighting cilia crucial role in the brains response to environmental changes and regulation of time-dependent physiological processes. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/546950v3_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@153135corg.highwire.dtl.DTLVardef@11c1d7eorg.highwire.dtl.DTLVardef@d47014org.highwire.dtl.DTLVardef@10a65ca_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2023

Immortalization and transformation of primary cells mediated by engineered ecDNAs

Focal gene amplifications are among the most common cancer-associated mutations, but their evolution and contribution to tumorigenesis have proven challenging to recapitulate in primary cells and model organisms. Here we describe a general approach to engineer large (>1 Mbp) focal amplifications mediated by extrachromosomal circular DNAs (ecDNAs, also known as "double minutes") in a spatiotemporally controlled manner in cancer cell lines and in primary cells derived from genetically engineered mice. With this strategy, ecDNA formation can be coupled with expression of fluorescent reporters or other selectable markers to enable the identification and tracking of ecDNA-containing cells. We demonstrate the feasibility of this approach by engineering MDM2-containing ecDNAs in near-diploid human cells, showing that GFP expression can be used to track ecDNA dynamics under physiological conditions or in the presence of specific selective pressures. We also apply this approach to generate mice harboring inducible Myc- and Mdm2-containing ecDNAs analogous to those spontaneously occurring in human cancers. We show that the engineered ecDNAs rapidly accumulate in primary cells derived from these animals, promoting proliferation, immortalization, and transformation.

cancer biology↗