Biology subjects

Gryder, B. E.

Publications and source records attributed to Gryder, B. E..

9 recordsLinked to original sources

bioRxiv2026

Rare RNA Polymerase II failure modes mark the cancer-driving genes most affected by epigenetic perturbation

RNA Polymerase II (Pol2) transcribes genes through a complex life cycle (initiation, pausing, elongation, co-transcriptional splicing, termination, and recycling). Chromatin immunoprecipitation of Pol2 before and after chemical perturbation has identified promoter-proximal accumulation (pausing) as a critical step in the transcription genome-wide. However, the full landscape of Pol2 responses has not been well characterized. Here, we introduce a tool for comparing Pol2 Activity State Shifts (compPASS), a computational pipeline which uses data from paired ChIP-based approaches to assign genes to one of eight distinct modes by Pol2 response under different forms of perturbation. In multiple cancer types and drug contexts, we show that compPASS identifies previously undescribed Pol2 failure modes with important implications for gene regulation. By looking past pausing, compPASS exposes Pol2 failure modes (clogging, entry, gain, loss) that are rare but pinpoint the genes most relevant to cancer cell state changes in response to therapy, turning a single paired Pol2 ChIP-seq into a mechanistic map of shifting transcriptional states.

bioinformatics↗

bioRxiv2026

CpG island density predicts CBP/p300 dependency across 3D chromatin clusters

RNA Polymerase II (Pol2) organizes transcription through higher-ordered chromatin clusters that integrate promoter and enhancer interactions to coordinate gene expression. Nevertheless, the features that distinguish unique classes of Pol2-mediated clusters remain to be defined. Here, we identify two distinct classes of Pol2-mediated clusters: one enriched for CpG islands, promoter-promoter interactions, and housekeeping gene expression, and another characterized by high CBP/p300 occupancy, enhancer-promoter looping, and lineage-defining (LD) transcriptional programs. Acute inhibition of CBP/p300 catalytic activity leads to rapid loss of acetylation at enhancers and preferential downregulation of LD genes, resulting in impaired cellular proliferation and activation of apoptotic programs. Integrative machine learning modeling reveals that cluster strength, RNA half-life, and CpG island content as strong predictors of genes sensitive to CBP/p300 inhibition. Together, these findings clarify enhancer-addiction and vulnerability to CBP/p300 inhibition.

cancer biology↗

bioRxiv2026

Integrative Single-cell and Spatial Transcriptomic Analysis of Osteosarcoma Reveals Conserved and Distinct Ecosystems Across Sites and Species

Osteosarcoma is a heterogeneous malignancy, exhibiting significant variability among patients, individual cancer cells within a tumor, and the stromal cells that compose primary and metastatic lesions. To facilitate the study of this complex disease, we compiled a unique cross-species single-cell transcriptomic dataset totaling over a million cells/nuclei from human specimens, canine specimens, patient-derived xenografts/PDX, and syngeneic mouse models at both primary (bone) and metastatic (lung) sites. Using a rigorous process for multi-species alignment and annotation, we identified six conserved tumor cell transcriptional states organized along hierarchical differentiation trajectories from progenitor to differentiated phenotypes. Parallel analysis of tumor-associated cells identified conserved macrophage, fibroblast, and endothelial populations that exhibit species- and site-specific reprogramming. Validation by mapping cell types using spatial transcriptomics revealed structured neighborhood architectures that were reproduced across multiple samples. Cell-cell interaction analysis revealed similarities and differences in tumor-host networks across primary and metastatic sites and across species. This analysis enabled pathway-specific assessment of tumor-host communication fidelity across osteosarcoma model systems relative to humans, revealing canine osteosarcoma as a more faithful model. Metastatic lung lesions, counterintuitively, exhibited more intense and complex extracellular matrix (ECM) signaling than primary bone tumors. A key example was tumor-derived fibronectin (FN1), which engages integrin and syndecan receptors on lung epithelial cells, driving a pathological mesenchymal and profibrotic state that promotes fibrotic niche formation and metastatic lung colonization. Together, this cross-species resource delineates both conserved and divergent tumor microenvironment programs, demonstrates how model-aware analyses uncover previously unrecognized tumor-host interactions, and underscores the need for therapies that co-target tumor heterogeneity and its supportive metastatic niche. Statement of SignificanceWe show that the tumor microenvironment in human osteosarcoma patients has biological phenotypes that are conserved across both patients and species. This points towards underlying molecular mechanisms that could be therapeutically targeted.

cancer biology↗

bioRxiv2024

Metastasis-initiating osteosarcoma subpopulations establish paracrine interactions with both lung and tumor cells to create a metastatic niche

Osteosarcoma is an aggressive and deadly bone tumor, primarily afflicting children, adolescents, and young adults. Poor outcomes for osteosarcoma patients are intricately linked with the development of lung metastasis. While lung metastasis is responsible for nearly all deaths caused by osteosarcoma, identification of biologically defined, metastasis-targeting therapies remains elusive because the underlying cellular and molecular mechanisms that govern metastatic colonization of circulating tumor cells to the lung remains poorly understood. While thousands of tumor cells are released into circulation each day, very few can colonize the lung. Herein, using a combination of a novel organotypic metastasis in vitro model, single-cell RNA sequencing, human xenograft, and murine immunocompetent osteosarcoma models, we find that metastasis is initiated by a subpopulation of hypo-proliferative cells with the unique capacity to sustain production of metastasis promoting cytokines such as IL6 and CXCL8 in response to lung-epithelial derived IL1. Critically, genomic and pharmacologic disruption of IL1 signaling in osteosarcoma cells significantly reduces metastatic progression. Collectively, our study supports that tumor-stromal interactions are important for metastasis, and suggests that metastatic competency is driven, in part, by the tumor cells ability to respond to the metastatic niche. Our findings support that disruption of tumor-stromal signaling is a promising therapeutic approach to disrupt metastasis progression.

cancer biology↗

bioRxiv2024

Aberrant activation of wound healing programs within the metastatic niche facilitates lung colonization by osteosarcoma cells

PurposeLung metastasis is responsible for nearly all deaths caused by osteosarcoma, the most common pediatric bone tumor. How malignant bone cells coerce the lung microenvironment to support metastatic growth is unclear. The purpose of this study is to identify metastasis-specific therapeutic vulnerabilities by delineating the cellular and molecular mechanisms underlying osteosarcoma lung metastatic niche formation. Experimental designUsing single-cell transcriptomics (scRNA-seq), we characterized genome- and tissue-wide molecular changes induced within lung tissues by disseminated osteosarcoma cells in both immunocompetent murine models of metastasis and patient samples. We confirmed transcriptomic findings at the protein level and determined spatial relationships with multi-parameter immunofluorescence and spatial transcriptomics. Based on these findings, we evaluated the ability of nintedanib, a kinase inhibitor used to treat patients with pulmonary fibrosis, to impair metastasis progression in both immunocompetent murine osteosarcoma and immunodeficient human xenograft models. Single-nucleus and spatial transcriptomics was used to perform molecular pharmacodynamic studies that define the effects of nintedanib on tumor and non-tumor cells within the metastatic microenvironment. ResultsOsteosarcoma cells induced acute alveolar epithelial injury upon lung dissemination. scRNA-seq demonstrated that the surrounding lung stroma adopts a chronic, non-resolving wound-healing phenotype similar to that seen in other models of lung injury. Accordingly, metastasis-associated lung demonstrated marked fibrosis, likely due to the accumulation of pathogenic, pro-fibrotic, partially differentiated epithelial intermediates and macrophages. Our data demonstrated that nintedanib prevented metastatic progression in multiple murine and human xenograft models by inhibiting osteosarcoma-induced fibrosis. ConclusionsFibrosis represents a targetable vulnerability to block the progression of osteosarcoma lung metastasis. Our data support a model wherein interactions between osteosarcoma cells and epithelial cells create a pro-metastatic niche by inducing tumor deposition of extracellular matrix proteins such as fibronectin that is disrupted by the anti-fibrotic TKI nintedanib. Our data shed light on the non-cell autonomous effects of TKIs on metastasis and provide a roadmap for using single-cell and spatial transcriptomics to define the mechanism of action of TKI on metastases in animal models. Statement of translational relevanceTherapies that block metastasis have the potential to save the majority of lives lost due to solid tumors. Disseminated tumor cells must integrate into the foreign, inhospitable microenvironments they encounter within secondary organs to facilitate metastatic colonization and progression. Our study elucidated that disseminated osteosarcoma cells survive within the lung by co-opting and amplifying the lungs endogenous wound-healing response program. This osteosarcoma-induced wound response results in fibrosis of the surrounding microenvironment. Our data implicates fibrosis and abnormal wound healing as key drivers of osteosarcoma lung metastasis that can be targeted therapeutically to disrupt metastasis progression.

cancer biology↗

bioRxiv2022

High-throughput Approaches to Uncover Synergistic Drug Combinations in Leukemia

We report a comprehensive drug synergy study in acute myeloid leukemia (AML). In this work, we investigate 11 cell lines spanning both MLL-rearranged and non-rearranged subtypes. The work comprises a resource for the community, with many synergistic drug combinations that could not have been predicted a priori, and open source code for automation and analyses. We base our definitions of drug synergy on the Chou-Talalay method, which is useful for visualizations of synergy experiments in isobolograms, and median-effects plots, among other representations. Our key findings include drug synergies affecting the chromatin state, specifically in the context of regulation of the modification state of histone H3 lysine-27. We report open source high throughput methodology such that multidimensional drug screening can be accomplished with equipment that is accessible to most laboratories. This study will enable preclinical investigation of new drug combinations in a lethal blood cancer, with data analysis and automation workflows freely available to the community. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=90 SRC="FIGDIR/small/518409v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1e85ef9org.highwire.dtl.DTLVardef@b3369eorg.highwire.dtl.DTLVardef@1c6d705org.highwire.dtl.DTLVardef@14ec6b2_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2021

Convergence of case-specific epigenetic alterations identify a confluence of genetic vulnerabilities tied to opioid dependence

Opioid dependence is a highly heterogeneous disease driven by a variety of genetic and environmental risk factors which have yet to be fully elucidated. We interrogated the effects of opioid dependence on the brain using ChIP-seq to quantify patterns of H3K27 acetylation in dorsolateral prefrontal cortical neurons isolated from 51 opioid-overdose cases and 51 accidental death controls. Among opioid cases, we observed global hypoacetylation and identified 388 putative enhancers consistently depleted for H3K27ac. Machine learning on H3K27ac patterns predicts case-control status with high accuracy. We focus on case-specific regulatory alterations, revealing 81,399 hypoacetylation events, uncovering vast inter-patient heterogeneity. We developed a strategy to decode this heterogeneity based on convergence analysis, which leveraged promoter-capture Hi-C to identify five genes over-burdened by alterations in their regulatory network or "plexus": ASTN2, KCNMA1, DUSP4, GABBR2, ENOX1. These convergent loci are enriched for opioid use disorder risk genes and heritability for generalized anxiety, number of sexual partners, and years of education. Overall, our multi-pronged approach uncovers neurobiological aspects of opioid dependence and captures genetic and environmental factors perpetuating the opioid epidemic.

genomics↗

bioRxiv2019

MEIS1 down-regulation by MYC mediates prostate cancer development through elevated HOXB13 expression and AR activity

Localized prostate cancer develops very slowly in most men, with the androgen receptor (AR) and MYC transcription factors amongst the most well-characterized drivers of prostate tumorigenesis. Canonically, MYC up-regulation in luminal prostate cancer cells functions to oppose the terminally differentiating effects of AR. However, the effects of MYC up-regulation are pleiotropic and inconsistent with a poorly proliferative phenotype. Here we show that increased MYC expression and activity are associated with the down-regulation of MEIS1, a HOX-family transcription factor. Using RNA-seq to profile a series of human prostate cancer specimens laser capture microdissected on the basis of MYC immunohistochemistry, MYC activity and MEIS1 expression were inversely correlated. Knockdown of MYC expression in prostate cancer cells increased expression of MEIS1 and increased occupancy of MYC at the MEIS1 locus. Finally, we show in laser capture microdissected human prostate cancer samples and the prostate TCGA cohort that MEIS1 expression is inversely proportional to AR activity as well as HOXB13, a known interacting protein of both AR and MEIS1. Collectively, our data demonstrate that elevated MYC in a subset of primary prostate cancers functions in a negative role in regulating MEIS1 expression, and that this down-regulation may contribute to MYC-driven development and progression.

cancer biology↗

bioRxiv2019

Miswired enhancer logic drives translocation positive rhabdomyosarcoma

Core regularity transcription factors (CR TFs) define cell identity and lineage through an exquisitely precise and logical order during embryogenesis and development. These CR TFs regulate one another in three-dimensional space via distal enhancers that serve as logic gates embedded in their TF recognition sequences. Aberrant chromatin organization resulting in miswired circuitry of enhancer logic is a newly recognized feature in many cancers. Here, we report that PAX3-FOXO1 expression is driven by a translocated FOXO1 distal super enhancer (SE). Using 4C-seq, a technique detecting all genomic regions that interact with the translocated FOXO1 SE, we demonstrate its physical interaction with the PAX3 promotor only in the presence of the oncogenic translocation. Furthermore, RNA-seq and ChIP-seq in tumors bearing rare PAX translocations implicate enhancer miswiring is a pervasive feature across all FP-RMS tumors. HiChIP of enhancer mark H3K27ac showed extended connectivity between the distal FOXO1 SE and additional intra-domain enhancers and the PAX3 promoter. We show by CRISPR-paired-ChIP-Rx that PAX3-FOXO1 transcription is diminished when this network of enhancers is selectively ablated. Therefore, our data reveal a mechanism of a translocated hijacked enhancer which disrupts the normal CR TF logic during skeletal muscle development (PAX3 to MYOD to MYOG), replacing it with an infinite loop logic that locks rhabdomyosarcoma cells in an undifferentiated proliferating stage.

cancer biology↗