Biology subjects

Chavez, L.

Publications and source records attributed to Chavez, L..

14 recordsLinked to original sources

bioRxiv2026

Inferring ecDNA Evolution from Allele Frequency Spectra

Extrachromosomal DNA (ecDNA) can arise early in the development of aggressive tumors or later upon progression, but the impact of chronology on patient outcome is not known. Currently, it is not possible to determine when an ecDNA arose in the course of tumor development and progression, based on genome sequencing data. Here, we develop an analytic method, ecEvol, to infer ecDNA emergence time, selection strength, mutation rate, and clonal dominance from allele frequency spectra in bulk whole-genome sequencing. EcEvol outperforms other methods and predicts parameters with high accuracy across a wide range of parameter values. Applying ecEvol to primary, treatment-naive tumors, we find that ecDNA typically emerges early and undergoes strong positive selection, albeit with substantial variation across cancer types. EcDNAs carrying known oncogenes emerge earlier and reach greater clonal dominance than ecDNAs lacking known oncogenes. In advanced and predominantly treated tumors, ecDNA emerges substantially later than in matched primary tumors, consistent with the generation and selection of new ecDNA during tumor progression and therapy. Longitudinal samples further support continued expansion of ecDNA-bearing lineages. Finally, earlier ecDNA emergence is associated with poorer overall survival. These results provide insight into the chronology of ecDNA formation from a single tumor biopsy taken at any point during the course of the disease, revealing that allele-frequency spectra encode the evolutionary history of ecDNA and provide a quantitative framework for reconstructing its emergence and expansion.

bioinformatics↗

bioRxiv2026

Paternal Metabolic Reversal Remodels Sperm RNA Profiles and Ameliorates Intergenerational Metabolic Disorder in Mice

Paternal obesity increases metabolic risk in offspring, but whether this risk can be reduced by restoring paternal health before conception remains unresolved. We developed a within-sire induction-and-reversal model in outbred CD1 mice in which high-fat diet (HFD)-exposed males generated offspring before and after transition to an ingredient-matched control diet with voluntary exercise. HFD caused obesity, glucose intolerance, insulin resistance, and extensive remodeling of sperm mRNA, lncRNA, and sncRNA profiles, together with transcriptomic changes in metabolic tissues. Diet and exercise reversal normalized paternal metabolic indices and broadly restored tissue RNA profiles, although sperm retained a limited transcriptional memory of prior HFD exposure. Offspring sired before reversal developed sex-dependent metabolic dysfunction despite control-diet rearing, whereas offspring sired after reversal showed substantial improvement. These findings show that paternal metabolic risk is modifiable before conception and that this reversibility is linked to remodeling of sperm RNA. (140 words) HighlightsO_LIPaternal HFD-Ex induces obesity, glucose intolerance and insulin resistance in CD1 males C_LIO_LISperm shows much stronger RNA response than four metabolic organs profiled C_LIO_LIDiet and exercise reversal restores metabolism and RNA profiles in sperm and four metabolic organs analyzed C_LIO_LIOffspring metabolic risk is reduced when sires conceive after reversal through diet and exercise intervention C_LI eTOC BlurbChen, Magalhaes, et al. show that paternal metabolic recovery before conception remodels sperm RNA and reduces transmission of HFD-associated metabolic risk to offspring in a within-sire mouse model.

genetics↗

bioRxiv2026

Detecting Extrachromosomal DNA from Routine Histopathology

Extrachromosomal DNA (ecDNA) is a major driver of oncogene amplification, tumour heterogeneity and poor clinical outcomes [1-3], yet its detection relies on specialised genomic assays that are not integrated into routine diagnostics. Here, we show that ecDNA status can be inferred directly from standard haematoxylin and eosin-stained whole-slide pathology images. We develop an end-to-end, weakly supervised deep learning framework that aggregates thousands of high-magnification patches per slide with slide-level augmentation and interpretable attention. Across twelve cancer types from The Cancer Genome Atlas, the approach identifies tumours with genomic amplifications and, critically, distinguishes ecDNA-amplified from chromosomally amplified or non-amplified tumours, with the strongest signal in glioblastoma. Attention maps localise regions enriched for nuclei with altered chromatin intensity and texture, and predicted ecDNA status recapitulates its adverse association with survival. These results indicate that ecDNA amplifications leave reproducible histomorphologic foot-prints detectable by routine pathology, enabling scalable screening to prioritise tumours for confirmatory molecular testing.

bioinformatics↗

bioRxiv2025

PlantCV v4: Image analysis software for high-throughput plant phenotyping

PlantCV is an open-source Python project aimed at developing tools to address a range of image-based, plant phenotyping questions. PlantCV has been used for more than 10 years to automate trait collection from image data and the newest release, PlantCV version 4, continues to lower the barrier to entry for users without substantial coding experience through extensive example use-case tutorials and simplified installation. In addition to usability, we document added functionality since the release of PlantCV v2, including support for more image types such as fluorescence, thermal, and hyperspectral data. Finally, we describe the development of a new subpackage focused on morphological trait measurements like leaf angle, and demonstrate its utility as compared to more manual methods of data collection. CORE IDEASO_LIPlantCV is an open-source, open-development, Python-based software package that has a new release for improved functionality and usability to make image analysis flexible and easier for researchers without a coding background. C_LIO_LIPlantCV is now capable of handling new data types that are relevant to researchers, such as thermal and hyperspectral, and has built in functionality for extracting information from these image types. C_LIO_LIThe software project aims to lower the barrier to entry into image analysis for researchers by providing numerous, versioned, interactive tutorials that cover most common use cases, particularly in plant science. C_LI

plant biology↗

bioRxiv2025

Interferon Restores Antigen Presentation and Sensitizes Medulloblastoma to T Cell Killing

Medulloblastomas are commonly considered immunologically cold and refractory to immunotherapy. One contributing factor to their low immunogenicity is impaired antigen presentation, which allows tumor cells to escape from cytotoxic T cells. Here we use a syngeneic mouse model of medulloblastoma to study the role of CD8+ T cells in medulloblastoma growth. We demonstrate that despite low expression of MHC Class I on tumor cells, depletion of CD8+ T cells accelerates tumor growth, whereas adoptive transfer of tumor-reactive CD8+ T cells prolongs survival. These anti-tumor effects rely on T cells secreting interferon gamma (IFN{gamma}), which induces MHC class I on tumor cells and facilitates tumor cell killing by T cells. Notably, this response is essential for CD8+ T cell-mediated tumor attack, as blocking IFN{gamma} signaling in vivo abrogates MHC class I induction and eliminates the beneficial effect of T cells. Importantly, delivering IFN{gamma} directly into tumors via convection-enhanced delivery (CED) enhances CD8+ T cell-mediated killing of tumor cells and significantly prolongs survival in tumor-bearing mice. These studies highlight the importance of T cells in controlling brain tumor growth and the value of IFN{gamma} as an adjuvant for T cell-based immunotherapy.

cancer biology↗

bioRxiv2025

Preservation and Clonal Behavior of Extrachromosomal DNA in Patient-Derived Xenograft Models of Childhood Cancers

Extrachromosomal DNA (ecDNA) is a powerful oncogenic driver linked to poor prognosis in pediatric cancers. Whole-genome sequencing of 338 patient-derived xenograft (PDX) samples and 127 matched primary tumors across multiple childhood cancer types was used to compare ecDNA prevalence, sequence conservation, and clonal dynamics. ecDNA in PDX models frequently mirrored oncogene amplifications observed in patient tumors (e.g., MYCN, MYC, MDM2) and showed high sequence conservation. Medulloblastoma and neuroblastoma PDXs exhibited significantly higher ecDNA prevalence, consistent with strong selection or de novo formation during tumor propagation. Although ecDNA copy numbers were generally preserved, some neuroblastoma PDXs displayed marked MYCN copy gains. Single-cell multiome profiling revealed that ecDNA-positive clones either persisted or expanded dramatically in PDXs, in one case growing from a minor subpopulation to nearly all tumor cells. These findings establish PDX models as valuable systems for ecDNA research and underscore the selective growth advantage conferred by ecDNA during tumor evolution.

genomics↗

bioRxiv2025

Ras-Responsive Element Binding Protein 1 regulates survival of Group 3 medulloblastoma

Medulloblastoma (MB) is the most common malignant pediatric brain tumor, and Group 3 (G3, MYC-driven) MB has the worst prognosis. Despite advances in molecular classification, oncogenic drivers of G3 MB remain poorly defined. To identify such drivers, we profiled transcription factor expression across MB subgroups. Our analysis revealed Ras-responsive element binding protein 1 (RREB1) as one of the most highly expressed transcription factors in G3 MB. RREB1 knockdown impaired cell proliferation in vitro and prolonged survival in orthotopic xenograft models, suggesting it plays a key role in regulating tumor growth. Mechanistically, RREB1 acts by enhancing transcription of TGF-{beta} pathway genes. Upstream, RREB1 expression is controlled by c-MET signaling, and the MET inhibitor SU11274 decreased RREB1 levels and MB cell viability. Local delivery of SU11274 in tumor-bearing mice suppressed RREB1 expression and extended survival. These results establish the c-MET/RREB1 axis as a critical oncogenic regulator and a promising therapeutic target in in high-risk MB.

cancer biology↗

bioRxiv2025

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↗

bioRxiv2025

Reconstructing the three-dimensional architecture of extrachromosomal DNA with ec3D

Extrachromosomal DNAs (ecDNAs) are large, acentric, circular DNA molecules that occur pervasively across many human cancers. EcDNA can drive tumor formation and evolution, contribute to drug resistance, and associate with poor patient survival outcomes. Beyond mediating high copy numbers, the circular topology and dynamic conformational changes of ecDNA disrupt topological domains and rewire regulatory networks, thereby conferring an important role in the transcriptional regulation of oncogenes. Here, we develop ec3D, a computational method for reconstructing the three-dimensional structures of ecDNA and analyzing significant interactions from high-throughput chromatin capture (Hi-C) data. Given a candidate ecDNA sequence and the corresponding whole-genome Hi-C as input, ec3D reconstructs the spatial structure of ecDNA by maximizing the Poisson likelihood of observed interactions. Ec3Ds performance was validated using both simulated ecDNA structures with varying conformations and Hi-C data from previously-characterized cancer cell lines. Our reconstructions reveal that ecDNAs occupy spherical configurations and mediate unique long-range interactions involved in gene regulation. Through algorithmic innovations, ec3D can resolve complex ecDNA structures with duplicated genomic segments, identify multi-way interactions, and distinguish between interactions arising from direct spatial proximity and secondary interactions resulting from alternative folding patterns or intermolecular (trans) contacts of ecDNA molecules. Our findings provide insights into how the spatial organization of ecDNA may influence gene regulation and contribute to increased oncogene expression. Code availabilityhttps://github.com/AmpliconSuite/ec3D

cancer biology↗

bioRxiv2024

ecPath detects ecDNA in tumors from histopathology images

Circular extrachromosomal DNA (ecDNA) can drive tumor initiation, progression and resistance in some of the most aggressive cancers and is emerging as a promising anti-cancer target. However, detection currently requires costly whole-genome sequencing (WGS) or labor-intensive cytogenetic or FISH imaging, limiting its application in routine clinical diagnosis. To overcome this, we developed ecPath (ecDNA from histopathology), a computational method for predicting ecDNA status from routinely available hematoxylin and eosin (H&E) images. ecPath implements a deep-learning method we call transcriptomics-guided learning, which utilizes both transcriptomics and H&E images during the training phase to enable successful ecDNA prediction from H&E images alone, a task not achievable with models trained on H&E images only. It is trained on more than 6,000 tumor whole-slide images from the TCGA cohort with the best performance in predicting ecDNA status in brain and stomach tumors (average AUC=0.78). ecPath revealed that ecDNA-positive tumors are enriched with pleomorphic, larger and high-density nuclei. Testing in an independent cohort, ecPath predicted ecDNA status of 985 pediatric brain tumor patients with an AUC of 0.72. Finally, we applied ecPath to identify ecDNA-positive tumors in the TCGA cohort for which no WGS data were available. Like WGS-based ecDNA-positive labels, the predicted ecDNA-positive status also identify poor prognoses for low grade glioma patients. These results demonstrate that ecPath enables the detection of ecDNA from routinely available H&E imaging alone and help nominate aggressive tumors with ecDNA to study and target it.

pathology↗

bioRxiv2024

Ligase-mediated programmable genomic integration (L-PGI): an efficient site-specific gene editing system that overcomes the limitations of reverse transcriptase-based editing systems

Since their discovery, CRISPR/Cas9 systems have been repurposed for programmable targeted genomic editing. This has led to unprecedented advancement of gene editing for therapeutic benefit. Initial uses of CRISPR/Cas9 were focused on gene disruption via DNA cleavage, but significant engineering led to systems for single base editing as well as insertion, deletion and manipulation of short stretches of genomic sequences using nicking Cas9 and RT-based methods. These technologies allowed safer and more precise editing but were limited to small corrections and showed significantly reduced efficiencies in nondividing cells, presenting difficulty for translation to in vivo therapies. To find an alternate editing strategy that could address these shortcomings, we revisited the mechanism of DNA nicking by nCas9. nCas9 nicking creates a free 5 phosphate group and a 3 hydroxyl group on the complementary strand of the target sequence. Under ordinary conditions in the cell these ends are re-joined by endogenously expressed ligases to repair DNA back to wild-type. If, however, a DNA fragment containing the desired edit were present, ligation of the nicked genomic DNA with the delivered fragment could result in gene editing. We demonstrate that optimization of each component and introduction of a chemically modified high affinity splinting DNA allows a variety of ligase-based edits, including longer edits not efficient with RT-based systems, at high efficiencies and fidelities that minimize genomic byproducts in both dividing and nondividing cells as well as in vivo in adult mice. Here we present the first therapeutically relevant ligation-based programmable gene editing technology, L-PGI.

bioengineering↗

bioRxiv2024

High-resolution Inference of Multiplexed Anti-HIV Gene Editing using Single-Cell Targeted DNA Sequencing

Gene therapy-based HIV cure strategies typically aim to excise the HIV provirus directly, or target host dependency factors (HDFs) that support viral persistence. Cure approaches will likely require simultaneous co-targeting of multiple sites within the HIV genome to prevent evolution of resistance, and/or co-targeting of multiple HDFs to fully render host cells refractory to HIV infection. Bulk cell-based methods do not enable inference of co-editing within individual viral or target cell genomes, and do not discriminate between monoallelic and biallelic gene disruption. Here, we describe a targeted single-cell DNA sequencing (scDNA-seq) platform characterizing the near full-length HIV genome and 50 established HDF genes, designed to evaluate anti-HIV gene therapy strategies. We implemented the platform to investigate the capacity of multiplexed CRISPR-Cas9 ribonucleoprotein complexes (Cas9-RNPs) to simultaneously 1) inactivate the HIV provirus, and 2) knockout the CCR5 and CXCR4 HDF (entry co-receptor) genes in microglia and primary monocyte-derived macrophages (MDMs). Our scDNA-seq pipeline revealed that antiviral gene editing is rarely observed at multiple loci (or both alleles of a locus) within an individual cell, and editing probabilities across sites are linked. Our results demonstrate that single-cell sequencing is critical to evaluate the true efficacy and therapeutic potential of HIV gene therapy.

genomics↗

bioRxiv2024

Endocrine disruptor-induced epimutagenesis in vitro: Insight into molecular mechanisms

Endocrine disrupting chemicals (EDCs) such as bisphenol S (BPS) are xenobiotic compounds that can disrupt endocrine signaling following exposure due to steric similarities to endogenous hormones within the body. EDCs have been shown to induce disruptions in normal epigenetic programming (epimutations) that accompany dysregulation of normal gene expression patterns that appear to predispose disease states. Most interestingly, the prevalence of epimutations following exposure to many different EDCs often persists over multiple subsequent generations, even with no further exposure to the causative EDC. Many previous studies have described both the direct and prolonged effects of EDC exposure in animal models, but many questions remain about molecular mechanisms by which EDCs initially induce epimutations or contribute to the propagation of EDC-induced epimutations either within the exposed generation or to subsequent generations. Additional questions remain regarding the extent to which there may be differences in cell-type specific susceptibilities to various EDCs, and whether this susceptibility is correlative with expression of relevant hormone receptors and/or the location of relevant hormone response elements (HREs) in the genome. To address these questions, we exposed cultured mouse pluripotent (induced pluripotent stem [iPS]), somatic (Sertoli and granulosa), and germ (primordial germ cell like [PGCLC]) cells to BPS and measured changes in DNA methylation levels at the epigenomic level and gene expression at the transcriptomic level. We found that there was indeed a difference in cell-type specific susceptibility to EDC-induced epimutagenesis and that this susceptibility correlated with differential expression of relevant hormone receptors and, in many cases, tended to generate epimutations near relevant HREs within the genome. Additionally, however, we also found that BPS can induce epimutations in a cell type that does not express relevant receptors and in genomic regions that do not contain relevant HREs, suggesting that both canonical and non-canonical signaling mechanisms can be disrupted by BPS exposure. Most interestingly, we found that when iPS cells were exposed to BPS and then induced to differentiate into PGCLCs, the prevalence of epimutations and differentially expressed genes (DEGs) initially induced in the iPSCs was largely retained in the resulting PGCLCs, however, >90% of the specific epimutations and DEGs were not conserved but were rather replaced by novel epimutations and DEGs following the iPSC to PGCLC transition. These results are consistent with a unique concept that many EDC-induced epimutations may normally be corrected by germline and/or embryonic epigenetic reprogramming but that due to disruption of the underlying chromatin architecture induced by the EDC exposure, many novel epimutations may emerge during the reprogramming process as well. Thus, it appears that following exposure to a disruptive agent such as an EDC, a prevalence of epimutations may transcend epigenetic reprogramming even though most individual epimutations are not conserved during this process.

molecular biology↗

bioRxiv2021

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↗