Biology subjects

Weinberg, R.

Publications and source records attributed to Weinberg, R..

7 recordsLinked to original sources

bioRxiv2026

A Spatio-Temporal Analysis Framework for Characterizing Radiation-Induced Genomic Instability

Chronic low-dose ionizing radiation induces complex genomic instability encompassing both structural variants and point mutations, yet these alterations are typically analyzed as independent events, limiting detection of mechanistic coupling between rearrangement formation and localized mutagenesis at breakpoint junctions. This gap is particularly consequential given the widespread occupational and environmental exposure contexts such as nuclear energy, medical imaging, and environmental contamination, where coupled genomic alterations may contribute to cancer risk through mechanisms invisible to type-agnostic analyses. We developed an integrated analytical framework combining temporal pattern tracking, breakpoint-proximal mutation enrichment analysis, and systematic testing across all structural variant types to resolve these coupled dynamics across dose and time. Applying this framework to whole-genome sequencing data from primary human endothelial cells (HUVEC) exposed to chronic low-dose gamma radiation (0.20-2.62 mGy/hr) over three weeks, we identified inversion-specific mutagenic coupling; doublet base substitutions (DBS) were 7.13-fold enriched within 10bp of inversion breakpoints, a signal absent from other structural variant types, with sharp distance-dependent decay indicating localized mutagenesis at these junctions. Temporal analysis further revealed divergent fates of co-occurring alterations: inversions appeared transiently while DBS mutations showed greater persistence. These results illustrate how systematic integration of dose, time, and variant-type dimensions can uncover coupled mutagenic mechanisms that remain invisible in static or type-agnostic analyses. The framework is broadly applicable to longitudinal sequencing studies of genotoxic exposures, with applications to cancer genomics, radiation risk assessment, and mechanistic studies of DNA repair fidelity.

bioinformatics↗

bioRxiv2026

Interpretable transcriptome-to-phenotype modeling of cell-painting nuclear morphology features from RNA-seq under low-dose radiation exposure

With rapid advancements in high-throughput multi-modal profiling techniques across molecular, cellular to tissue scales, translating such multi-modal data into knowledge discovery for foundational understanding of cellular mechanisms is central in modern biomedical sciences. In this study, we focus on understanding how low-dose radiation exposure perturbs cellular morphology by linking high-dimensional transcriptomic responses to quantitative cell-phenotype readouts over time. We present a time-resolved inverse modeling framework that associates gene expression changes via RNA-sequencing with nuclear morphology features obtained from cell-painting imaging. Morphology responses were defined as treated-control differences for multiple nuclear features including size, shape, intensity, and textures, indexed by radiation dose and week. To capture time-dependent associations while maintaining interpretability, both RNA-sequencing and cell-painting data were stratified into four temporal phases (weeks 1-2, 3-4, 5-6, 7-9) and phase-dependent effects are encoded via gene-phase interaction predictors. To reduce confounding by dose trends and to evaluate generalization across time, we used a two-stage leave-one-week-out procedure: (i) a dose-only baseline model produced out-of-week residuals for each morphology feature, and (ii) elastic-net regression on phase-aware predictors modeled residual variation not explained by dose. Hyperparameters were selected via an exhaustive grid search scored by the correlation between observed residuals and out-of-week residual predictions, with additional sparsity diagnostics based on nonzero coefficient counts per fold. Stable predictors were identified by selection frequency and sign consistency across folds, then pruned further for multicollinearity and parsimony. Final reduced models were fit using ordinary least squares with heteroskedasticity-consistent standard errors to report effect estimates robust to non-constant variance. This workflow yields a transparent, time-stratified set of transcriptomic predictors associated with longitudinal nuclear morphology changes and provides a reproducible foundation for downstream biological interpretation and validation.

bioinformatics↗

bioRxiv2024

CD47 predominates over CD24 as a macrophage immune checkpoint in cancer.

Macrophages hold tremendous promise as effectors of cancer immunotherapy, but the best strategies to provoke these cells to attack tumors remain unknown. Here, we evaluated the therapeutic potential of targeting two distinct macrophage immune checkpoints: CD47 and CD24. We found that antibodies targeting these antigens could elicit maximal levels of phagocytosis when combined together in vitro. However, to our surprise, via unbiased genome-wide CRISPR screens, we found that CD24 primarily acts as a target of opsonization rather than an immune checkpoint. In a series of in vitro and in vivo genetic validation studies, we found that CD24 was neither necessary nor sufficient to protect cancer cells from macrophage phagocytosis in most mouse and human tumor models. Instead, anti-CD24 antibodies exhibit robust Fc-dependent activity, and as a consequence, they cause significant on-target hematologic toxicity in mice. To overcome these challenges and leverage our findings for therapeutic purposes, we engineered a collection of 77 novel bispecific antibodies that bind to a tumor antigen with one arm and engage macrophages with the second arm. We discovered multiple novel bispecifics that maximally activate macrophage-mediated cytotoxicity and reduce binding to healthy blood cells, including bispecifics targeting macrophage immune checkpoint molecules in combination with EGFR, TROP2, and CD71. Overall, our findings indicate that CD47 predominates over CD24 as a macrophage immune checkpoint in cancer, and that the novel bispecifics we created may be optimal immunotherapies to direct myeloid cells to eradicate solid tumors.

cancer biology↗

bioRxiv2024

Primary cilia promote EMT-induced triple-negative breast tumor heterogeneity and resistance to therapy

Tumor heterogeneity and plasticity, driven by Epithelial-Mesenchymal Transition (EMT), enable cancer therapeutic resistance. We previously showed that EMT promotes primary cilia formation, which enables stemness and tumorigenesis in triple-negative breast cancer (TNBC). Here, we establish a role for primary cilia in human TNBC chemotherapeutic resistance. We developed patient-derived organoids, and showed that these recapitulated the cellular heterogeneity of TNBC biopsies. Notably, one of the identified cell states bore a quasi-mesenchymal phenotype, primary cilia, and stemness signatures. We treated our TNBC organoids with chemotherapeutics and observed partial killing. The surviving cells with organoid-reconstituting capacity showed selective enrichment for the quasi-mesenchymal ciliated cell subpopulation. Genomic analyses argue that this enrichment reflects a combination of pre-existing cells and ones that arose through drug-induced cellular plasticity. We developed a family of small-molecule inhibitors of ciliogenesis and show that these, or genetic ablation of primary cilia, suppress chemoresistance. We conclude that primary cilia help TNBC to evade chemotherapy. SignificanceCancer cells that activate EMT to acquire a quasi-mesenchymal state form primary cilia to evade chemotherapy in human triple-negative breast cancer. Pharmacological inhibition of primary ciliogenesis counteracts EMT-induced chemoresistance.

cancer biology↗

bioRxiv2022

Type 1 interferon remodels normal and neoplastic hematopoiesis in human

Inflammation perturbs evolutionary dynamics of hematopoietic stem cell (HSC) clones in clonal hematopoiesis and myeloid neoplasms. We studied HSCs, progenitors and immune cells from patients with myeloproliferative neoplasm (MPN) at baseline and following interferon- (IFN) treatment, the only MPN therapy to deplete clonal stem cells. We focused on essential thrombocythemia, an informative model of early-phase neoplastic hematopoiesis. We integrated somatic genotyping, transcriptomes, immunophenotyping, and chromatin accessibility across single cells. IFN simultaneously activated HSCs into two polarized states, a lymphoid progenitor expansion associated with an anti-inflammatory state and an IFN-specific inflammatory granulocytic progenitor (IGP) state derived directly from HSCs. The augmented lymphoid differentiation balanced the typical MPN-induced myeloid bias, associated with normalized blood counts. Clonal fitness upon IFN exposure was due to resistance of clonal stem cells to differentiate into IGPs. These results support a paradigm wherein inflammation perturbs clonal dynamics by HSC induction into the precipitous IGP differentiation program. One-Sentence SummaryInflammation accelerates clonal evolution by driving stem cell differentiation into an alternate interferon--induced progenitor state.

cancer biology↗

bioRxiv2020

An EMT-primary cilium-GLIS2 signaling axis regulates mammogenesis and claudin-low breast tumorigenesis

The Epithelial-Mesenchymal Transition (EMT) and primary ciliogenesis induce stem cell properties in basal Mammary Stem Cells (MaSCs) to promote mammogenesis, but the underlying mechanisms remain incompletely understood. Here, we show that EMT transcription factors promote ciliogenesis at intermediate EMT transition states by activating ciliogenesis inducers, including FGFR1. The resulting primary cilia promote BBS11-dependent ubiquitination and inactivation of a central signaling node, GLIS2. We show that GLIS2 inactivation promotes MaSC stemness, and GLIS2 is required for normal mammary gland development. Moreover, GLIS2 inactivation is required to induce the proliferative and tumorigenic capacities of the Mammary-Tumor-initiating cells (MaTICs) of claudin-low breast cancers. Claudin-low breast tumors can be segregated from other breast tumor subtypes based on a GLIS2-dependent gene expression signature. Collectively, our findings establish molecular mechanisms by which EMT programs induce ciliogenesis to control MaSC and MaTIC biology, mammary gland development, and claudin-low breast cancer formation.

cell biology↗

bioRxiv2020

Measuring kinetics and metastatic propensity of CTCs by blood exchange between mice

Existing pre-clinical methods for acquiring dissemination kinetics of rare circulating tumor cells (CTCs) en route to forming metastases have not been capable of providing a direct measure of CTC intravasation rate and subsequent half-life in the circulation. Here, we demonstrate an approach for measuring endogenous CTC kinetics by continuously exchanging CTC-containing blood over several hours between un-anesthetized, tumor-bearing mice and healthy, tumor-free counterparts. By tracking CTC transfer rates using an autochthonous small cell lung cancer model, we extrapolated half-life times in the circulation of 50-100 seconds and intravasation rates between 4,000 and 27,000 CTCs/hour - an average daily shedding rate equivalent to [~]0.07% of the total number of primary tumor cells in the lung. Additionally, transfer of 1-2% of daily-shed CTCs from late-stage tumor-bearing mice generated macrometastases in healthy recipient mice. We envision that our technique will help further elucidate the role of CTCs and the rate-limiting steps in metastasis.

cancer biology↗