Biology subjects

Rendeiro, A. F.

Publications and source records attributed to Rendeiro, A. F..

At least 19 recordsLinked to original sources

bioRxiv2026

A single-cell view of human tissue aging reveals architectural decline beyond cellular composition

Aging reshapes the human body at the cellular level, yet how cell identity, morphology, and spatial organization remodel across organs and the adult lifespan remains poorly mapped, at a scale and lifespan coverage that molecular spatial assays cannot yet reach. Treating the GTEx histopathology archive as a population-scale, lifespan-resolved resource for spatial biology, we detected over 3.5 billion single cells across 16 human organs from nearly one thousand individuals. Cell density declined pervasively but organ-specifically, and vision-language phenotyping resolved epithelial cells into nine subtypes with divergent aging trajectories, including loss of ovarian granulosa cells at ~45% per decade. Community detection on spatial cell graphs identified functional tissue units, over a quarter of which remodeled with age along a shared trajectory from dense, specialized units toward sparser, stromal- and immune-enriched structures. Critically, this architectural remodeling was largely decoupled from cell composition (R2=0.07), showing that human tissues age along two partly independent axes, a pervasive loss of cells and a distinct remodeling of the architecture they form, with structural decline exceeding what cellular composition alone predicts.

systems biology↗

bioRxiv2026

StainX: GPU-accelerated batch stain normalization for computational pathology at scale

Stain normalization reduces color variability in histopathology whole-slide images, but cohort-scale pipelines lack fused multi-image batch transforms for classical methods. We present StainX, a GPU-accelerated batch stain normalization framework built around a two-stage fit/transform interface. It implements histogram matching, Macenko, and Reinhard normalizers through a portable PyTorch backend and an optional CUDA backend that fuses per-pixel operations for batch throughput. On NVIDIA GPUs, the fused CUDA path outperforms the torch CPU backend by 168x, 70x, and 48x for Reinhard, histogram matching, and Macenko respectively, and exceeds the fastest GPU peers by 7-8x (Reinhard) and 2x (Macenko) at comparable accuracy. StainX also provides user-selectable precision modes, a documented Python API, continuous integration testing, and online documentation. Source code available at https://github.com/rendeirolab/stainx, and documentation at https://stainx.readthedocs.io. Implemented in Python. Runs on Linux, macOS, and Windows.

bioinformatics↗

bioRxiv2026

Spatially organized cancer-associated fibroblast subtypes partition cutaneous carcinomas into immune-active and contracted, immune-repressed niches

Basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (SCC) are the most common keratinocyte-derived malignancies, yet they differ markedly in invasiveness, metastatic potential, and immune contexture. Although cancer-associated fibroblasts (CAFs) are increasingly recognized as key regulators of tumor architecture and tumor immunity, the spatial organization of distinct CAF subtypes in cutaneous carcinomas and their functional relationship with immune cells remains incompletely understood. Using a 33-plex imaging mass cytometry (IMC) panel, we profiled 28 regions of interest (ROIs) from 17 human BCC and SCC specimens, encompassing more than 739,000 single cells, and integrated these data with RNA fluorescence in situ hybridization (RNA-FISH), immunohistochemistry (IHC), multiplex immunofluorescence, and in vitro functional assays. We identified four fibroblast populations, including immunomodulatory CAFs (iCAFs), matrix CAFs (mCAFs), myofibroblast-like CAFs (myoCAFs), and reticular fibroblasts (retFIBs), and found that aggressive tumor subtypes were characterized by increased stromal area, extracellular matrix deposition, and altered CAF composition. CAF composition differed most prominently across BCC subtypes, with nodular BCC enriched for mCAFs and infiltrative BCC showing increased myoCAF density, consistent with a shift toward a contractile stromal program. Spatial analyses revealed distinct CAF-immune niches: iCAFs localized to immune-cell-rich, inflamed niches enriched for activated and/or exhaustion-associated immune-cell marker programs, whereas myoCAFs occupied fibroblast-dense, immune-poor niches with globally reduced immune activation. mCAFs were preferentially associated with immune cell accumulation in the stroma and spatial immune compartmentalization, with limited immune cell presence within tumor nests. At the invasive front, CAF-immune coupling was highly subset-dependent, with iCAFs linked to antigen-experienced T-cell states and myoCAFs linked to immune exclusion. In vitro, patient-derived CAF cultures from myoCAF-rich biopsies showed enhanced collagen-gel contraction, with cultures enriched for MCAM+ CAFs displaying increased contractile capacity. Aggressive tumor variants displayed increased stromal nuclear YAP/TAZ, while complementary single-cell pathway analysis supported a mechanically remodeled stromal microenvironment in which mCAFs contribute ECM/matrix-remodeling programs and RGS5/myoCAF-like populations show enhanced mechanotransduction-associated signaling, rather than a uniform CAF-wide increase in canonical YAP/TAZ transcriptional output. Together, these findings define spatially organized CAF programs in cutaneous carcinomas and identify myoCAF-rich stromal niches as a recurrent feature of aggressive, immune-repressed tumor architecture. These results nominate CAF composition as a biomarker of immune architecture and a potential determinant of therapeutic response.

cancer biology↗

bioRxiv2026

Tumor Heterogeneity Induces Pro- and Anti-metastatic Myeloid Cell Phenotypes in Breast Cancer Lung Metastasis

Metastasis is a major cause of cancer-related mortality, yet targeting metastatic cells directly has been largely unsuccessful due to their plasticity and heterogeneity. Myeloid cells play diverse pro- and anti-metastatic functions and are an attractive alternative target for treating metastasis, but how tumor heterogeneity influences myeloid cell phenotypes during metastasis remains poorly understood. Here, we profiled myeloid cells from primary tumors and matched metastatic lungs of 12 heterogeneous and differentially metastatic patient-derived xenograft models of breast cancer. Comparative analysis of cell type abundances revealed distinct myeloid remodeling specific to primary tumors or metastatic lungs. Beyond compositional differences, we identified gene expression programs that were associated with metastatic burden, such as number or size of metastatic nodules, indicating distinct microenvironmental requirements for metastatic seeding and outgrowth. Examining these metastasis-associated programs using time-course datasets, we discovered an evolution from anti- to pro-metastatic monocyte phenotypes during metastatic progression. We further showed that this phenotypic shift was driven by an increase in two distinct myeloid-derived suppressor cell signatures, and a transcriptionally regulated impairment of monocyte differentiation leading to the depletion of non-classical monocytes. Our results comprehensively dissect the heterogeneity of myeloid cell phenotypes across primary tumor and metastatic sites, opening novel avenues for myeloid-targeting therapies specific to metastasis.

cancer biology↗

bioRxiv2025

Systematic mapping of human tissue microanatomy reveals age-associated remodeling and resilience

Aging disrupts tissue structure at various scales, from cellular alterations to tissue and organ-level integrity. Microanatomical domains - recurrent cellular arrangements essential to organ-specific function, provide a highly physiologically relevant perspective on tissue homeostasis but are severely understudied in human aging. To address this gap, we developed H&E-UTAG, an unsupervised algorithm to detect microanatomical domains in whole slide histopathological images, which enables large-scale, label-free analysis of human microanatomy. Applying it to 24,945 whole-slide images from 40 human tissues of 983 individuals aged 20 to 70 years old, we identified 218 recurrent microanatomical domains categorized into 74 types across tissues. Domain types varied widely in tissue specificity, with 16% shared across 3 or more tissues and 69% restricted to a specific tissue. Age emerged as the dominant factor in influencing domain abundance, with 28% of domains changing significantly over the adult lifespan. By integrating tissue-level pathology annotations, we distinguished structural changes associated with healthy aging from those linked to subclinical disease, revealing that these processes often remodel distinct tissue compartments. Finally, mapping higher-order networks of domain-domain interactions uncovered age-associated reorganization of organ architecture, while a core framework of interactions remained resilient with age. Our novel analytical framework reveals fundamental principles of tissue organization and how they are restructured across the human lifespan, offering new insights into aging biology and tissue architecture in health and in the path to age-associated diseases. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=116 SRC="FIGDIR/small/682110v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@1d05840org.highwire.dtl.DTLVardef@151e211org.highwire.dtl.DTLVardef@d0de41org.highwire.dtl.DTLVardef@afb744_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2025

Uncovering the transcriptional hallmarks of endothelial cell aging via integrated single-cell analysis

Endothelial cells (ECs) are critical regulators of vascular function and exhibit specialized, organ-specific roles across tissues. During aging, these cells become dysfunctional, resulting in increased susceptibility to cardiovascular disease and its associated mortality. While single-cell transcriptomics studies have revealed extensive endothelial heterogeneity across tissues and conditions, a comprehensive atlas of human EC transcriptomes over the course of the adult human lifespan is still lacking. Here, we present the Human Aging Endothelial Cell Atlas (HAECA), a harmonized single-cell transcriptomic compendium of over 375,000 ECs from 12 human tissues throughout adulthood. Using HAECA, we identified age-associated transcriptional shifts, including a decline in angiogenic gene expression in venous ECs and widespread alterations in extracellular matrix (ECM)- and mechanotransduction-associated pathways. We validated these findings in aging human skin and further uncovered a p21-linked transcriptional program in ECs, confirmed in both in vitro and in vivo models and linked to cellular senescence. Together, our study provides a high-resolution transcriptome reference across spatial as well as temporal axes of the human endothelium.

cell biology↗

bioRxiv2025

Sequential PIDD1 auto-processing is essential for ploidy control in liver and heart

Polyploidization refers to the balanced increase in gene copy number and is a feature of specialized cells in different mammalian tissues, including the liver and the heart. During organogenesis, hepatocytes and cardiomyocytes undergo scheduled polyploidization events to increase their cellular or nuclear DNA content. This is thought to improve cellular output and enable for rapid genetic adaptation in response to stress. Yet, excessive increases in ploidy can also be disadvantageous and increase the risk of genome instability. Hence, a dedicated machinery, the PIDDosome multi-protein complex, has evolved to prevent exacerbated increases in DNA content. Using targeted mutagenesis in mice, we show that the PIDDosome controls hepatocyte ploidy in a cell-autonomous manner and that sequential and quantitative auto-processing of PIDD1 is key for accurate control of ploidy in postnatal development of liver and heart. Stoichiometric imbalances in bioactive PIDD1-fragments impair p53-dependent and independent cell cycle arrest responses during organogenesis, as well as caspase-2-dependent apoptosis caused by centrosome amplification. Strikingly, targeted mutagenesis of the caspase cleavage motif in the critical E3-ligase controlling p53 protein levels, Mdm2, impairs ploidy control in hepatocytes, but not in cardiomyocytes, indicative of the existence of alternative caspase-2 substrates that help to restrict ploidy in the heart.

cell biology↗

bioRxiv2025

The Spatial Atlas of Human Anatomy (SAHA): A Multimodal Subcellular-Resolution Reference Across Human Organs

The Spatial Atlas of Human Anatomy (SAHA) represents the first multimodal, subcellular- resolution reference of healthy adult human tissues across multiple organ systems. Integrating spatial transcriptomics, proteomics, and histological features across over 15 million cells from more than 100 donors, SAHA maps conserved and organ-specific cellular niches in gastrointestinal and immune tissues. High-resolution profiling using CosMx SMI, 10x Xenium, RNAscope, GeoMx DSP, and single-nucleus RNA-seq reveals spatially organized cell states, rare adaptive immune populations, and tissue-specific cell-cell interactions and ligand-receptor pairs. Comparative analyses with colorectal cancer and inflammatory bowel disease demonstrate the power of SAHA to detect disease-associated spatial disruptions, including crypt dedifferentiation, perineural invasion, and therapy-resistant immune remodeling. All data are openly accessible through a FAIR-compliant interactive portal to support exploration, benchmarking, and machine learning model training. Through SAHA, we provide a foundational framework for spatial diagnostics and next-generation precision medicine grounded in a comprehensive human tissue atlas, enabling the development of context-aware models that simulate tissue behavior, decode complex pathologies, and accelerate therapeutic innovation at unprecedented scale.

systems biology↗

bioRxiv2025

LazySlide: accessible and interoperable whole slide image analysis

Histopathological data are foundational in both biological research and clinical diagnostics but remain siloed from modern multimodal and single-cell frameworks. We introduce LazySlide, an open-source Python package built on the scverse ecosystem for efficient whole-slide image (WSI) analysis and multimodal integration. By leveraging vision-language foundation models and adhering to scverse data standards, LazySlide bridges histopathology with omics workflows. It supports tissue and cell segmentation, feature extraction, cross-modal querying, and zero-shot classification, with minimal setup. Its modular design empowers both novice and expert users, lowering the barrier to advanced histopathology analysis and accelerating AI-driven discovery in tissue biology and pathology.

bioinformatics↗

bioRxiv2025

Molecular dynamics driving phenotypic divergence among KRAS mutants in pancreatic tumorigenesis

Inflammation in the pancreas drives acinar-to-ductal metaplasia (ADM), a progenitor-like state that can be hijacked by mutant Kras in the formation of pancreatic cancer (PDAC). How these cell fate decisions vary according to KRAS mutation remains poorly understood. To define mutation-specific lineage reversion and tumor initiation, we implement novel Ptf1a-TdTomato mice and multiple KRAS mutants across an array of genetic, pharmacologic, and inflammatory perturbations in vivo. Whereas KRASG12D co-opts injury to enable lineage reversion, enhancer reprogramming, and tumor initiation, KRASG12R/V can initiate but not sustain dedifferentiated and neoplastic transcriptional and epigenetic programs. We find the KRASG12R/V defects consist of a failure to invoke robust EGFR signaling and activate Rac1/Vav1, with constitutive Akt activation in vivo sufficient to rescue the tumorigenic potential of KRASG12R. As the marked heterogeneity among KRAS variants begins early in tumorigenesis, these data are crucial to understanding mutation-specific oncogenic trajectories and directing the implementation of KRAS-directed therapeutics. SIGNIFICANCEDefining how KRAS mutants drive distinct outcomes in human pancreatic cancer is critical for developing allele-specific therapeutic approaches. This study unveils a hierarchy among KRASG12D, KRASG12V, and KRASG12R to drive tumor initiation, owing to heterogeneous activation of EGFR, PI3K/AKT, and RAC1 signaling, thus revealing mutation-specific evolutionary paths in pancreatic tumorigenesis.

cancer biology↗

bioRxiv2025

A multilayer network approach elucidates time- and tissue-specific developmental and aging processes

Understanding the dynamic interplay of proteins across different life stages and tissues is essential for deciphering the molecular mechanisms underpinning development, aging, and disease. Here, we present a comprehensive network-based framework that constructs and integrates 119 time- and tissue-specific protein-protein interaction (PPI) networks derived from transcriptomic data, offering insights into proteomic dynamics across the human lifespan. Based on this, we observed three distinct protein groups: (i) common-core proteins, expressed universally across all tissues and time points; (ii) time-/tissue-specific proteins, selectively expressed within specific temporal or spatial contexts; and (iii) time-/tissue-unique proteins, whose expression is restricted to specific points in space and time. Our analysis shows a clear gradient of network centrality, transitioning from the highly connected common-core proteins to more specialized time-/tissue-specific and unique proteins, mirroring a progressive shift in functional specificity. Further, we characterized the distinct molecular signatures of intrauterine to extrauterine life, delineating two key protein networks: the embryonic development network (EDev) and the environmental aging network (EAgi). Their network characterization and comparison highlighted specific communities within the EDev network enriched for developmental diseases, and specific EAgi communities involved in aging. This network classification allowed us to rank candidate anti-aging drugs and their molecular targets, laying the foundation for a systematic, data-driven, network-based investigation of development and aging, providing a roadmap for future research aimed at mitigating age-related diseases and promoting longevity.

systems biology↗

bioRxiv2025

Simultaneous immunomodulation and epithelial-to-mesenchymal transition drives lung adenocarcinoma progression

Lung cancer remains the deadliest cancer in the United States, with lung adenocarcinoma (LUAD) as its most prevalent subtype. While computed tomography (CT)-based screening has improved early detection and enabled curative surgeries, the molecular and cellular dynamics driving early-stage LUAD progression remain poorly understood, limiting non-surgical treatment options. To address this gap, we profiled 2.24 million cells from 122 early-stage LUAD patients using multiplexed imaging mass cytometry (IMC). This analysis revealed the molecular, spatial, and temporal dynamics of LUAD development. Our findings uncover a binary progression model. LUAD advances through either inflammation, driven by a balance of cytotoxic and regulatory immune activity, or fibrosis, characterized by stromal activation. Surprisingly, tumor cell populations did not increase significantly. Instead, they displayed a mixed phenotypic profile consistent with epithelial-to-mesenchymal transition (EMT), effectively masking the expansion of malignant cells. Furthermore, we addressed discrepancies between CT-based and histology-based subtyping. CT scans, while non-invasive, often mischaracterize invasive fibrotic tumors--which account for 20.5% of LUAD cases--as mild, non-solid ground glass opacities (GGOs). Using high-content IMC imaging, we demonstrate that these tumors harbor significant risks and advocate for improved diagnostic strategies. These strategies should integrate molecular profiling to refine patient stratification and therapeutic decision-making. Altogether, our study provides a high-resolution, systems-level view of the tumor microenvironment in early-stage LUAD. We characterize key transitions in oncogenesis and propose a precision-driven framework to enhance the detection and management of aggressive disease subtypes.

cancer biology↗

bioRxiv2024

Tissue clocks derived from histological signatures of biological aging enable tissue-specific aging predictions from blood

Aging, the leading risk factor for numerous diseases, manifests through diverse structural and architectural changes in human tissues, providing an opportunity to quantify and interpret tissue-specific aging. To address this, we present a comprehensive assessment of tissue changes occurring during human aging, utilizing a vast array of whole slide histopathological images from the Genotype-Tissue Expression Project (GTEx), primarily reflecting non-diseased tissue samples. Using deep learning, we analyzed 25,712 images from 40 distinct tissue types across 983 individuals, quantifying nuanced morphological changes that tissues undergo with age. We developed tissue clocks--predictors of biological age based on tissue images--which achieved a mean prediction error of 4.9 years. These clocks were associated with established aging markers, including telomere attrition, subclinical pathologies, and comorbidities. In a systematic assessment of biological age rates across organs, we identified pervasive non-uniform rates of aging across the human lifespan, with some organs exhibiting earlier changes (20-40 years old) and others showing bimodal patterns of age-related changes. We also uncovered several associations between demographic, lifestyle, and medical history factors and tissue-specific acceleration or deceleration of biological age, highlighting potential modifiable risk factors that influenced the aging process at the tissue level. Finally, by combining paired histological images and gene expression data, we developed a strategy to predict tissue-specific age gaps from blood samples. This approach was validated in independent cohorts covering eight diseases, ranging from acute conditions like stroke to chronic diseases such as cystic fibrosis and Alzheimers disease. It successfully recovered significant associations with disease-relevant organs and revealed patterns of systemic and tissue-specific aging that may reflect broader physiological changes in health and disease. This work offers a new perspective on the aging process by positioning tissue structure as an integrator of cellular and molecular changes that reflect the physiological state of organs in health and disease. It underscores the value of histopathological imaging as a tool for understanding human aging and provides a foundation for the monitoring of tissue-specific aging processes in age-associated diseases.

physiology↗

bioRxiv2024

Marsilea: An intuitive generalized visualization paradigm for complex datasets

Contemporary data visualization is challenged by the growing complexity and size of datasets, often comprising numerous interrelated features. Traditional visualization methods struggle to capture these complex relationships fully or are specialized to a domain requiring familiarity with multiple visualization tools. We introduce a novel and intuitive general visualization paradigm, termed "cross-layout visualization", which integrates multiple plot types in a cross-like structure. This paradigm allows for a central main plot surrounded by secondary plots, each capable of layering additional features for enhanced context and understanding. To operationalize this paradigm, we present "Marsilea", a Python library designed for creating complex visualizations with ease. Marsilea is notable for its modularity, diverse plot types, compatibility with various data formats, and is available in a coding-free web-based interface for users of all experience levels. We showcase its versatility and broad applicability by re-creating existing visualizations and creating novel visualizations that include elements such as heatmaps, sequence motifs, and set intersections that are typically beyond the scope of existing general visualization tools. The cross-layout paradigm, exemplified by Marsilea, offers a flexible, customizable, and intuitive approach to complex data visualization, promising to enhance data analysis across scientific domains.

bioinformatics↗

bioRxiv2022

Unsupervised discovery of tissue architecture in multiplexed imaging

Multiplexed imaging and spatial transcriptomics enable highly resolved spatial characterization of cellular phenotypes, but still largely depend on laborious manual annotation to understand higher-order patterns of tissue organization. As a result, higher-order patterns of tissue organization are poorly understood and not systematically connected to disease pathology or clinical outcomes. To address this gap, we developed UTAG, a novel method to identify and quantify microanatomical tissue structures in multiplexed images without human intervention. Our method combines information on cellular phenotypes with the physical proximity of cells to accurately identify organ-specific microanatomical domains in healthy and diseased tissue. We apply our method to various types of images across physiological and disease states to show that it can consistently detect higher level architectures in human organs, quantify structural differences between healthy and diseased tissue, and reveal tissue organization patterns with relevance to clinical outcomes in cancer patients.

bioinformatics↗

bioRxiv2022

A Unique Cellular Organization of Human Distal Airways and Its Disarray in Chronic Obstructive Pulmonary Disease

In the human lung, terminal bronchioles (TBs), the most distal conducting airways, open to respiratory bronchioles (RBs) that lead to the alveolar region where gas exchange takes place. This transition occurs in pulmonary lobules, lung tissue units supplied by pre-TBs, which give rise to TBs. Accumulating evidence suggests that remodeling and loss of pre-TBs and TBs underlies progressive airflow limitation in chronic obstructive pulmonary disease (COPD), the third leading cause of death worldwide. Understanding the nature of these changes at the single-cell level has so far been limited by poor accessibility of pre-TBs and TBs. Here, we introduce a novel method of region-precise airway dissection, which enables capture of the entire anatomical continuum of peripheral airways, from pre-TBs to RBs, and the associated alveolar region within the lobule. This approach allowed us to identify terminal airway-enriched secretory cells (TASCs), a unique epithelial cell population of distal airways expressing secretoglobin 3A2 (SCGB3A2) and/or surfactant protein B (SFTPB). TASCs were enriched in TBs, particularly, in areas of TB-RB transition and exhibited an intermediate, broncho-alveolar molecular pattern. TASC frequency was markedly decreased in pre-TBs and TBs of COPD patients compared to those in non-diseased lungs, accompanied by changes in cellular composition of vascular and immune microenvironments. In vitro regeneration assays identified basal cells (BCs) of pre-TBs and TBs as a cellular origin of TASCs in the human lung. Generation of TASCs by these region-specific progenitors was suppressed by IFN-{gamma} signaling that was augmented in distal airways of COPD patients. Thus, altered maintenance of region-specific cellular organization of pre-TBs and TBs represents a key component of distal airway pathology in COPD.

cell biology↗

bioRxiv2021

The evolution of genomic, transcriptomic, and single-cell protein markers of metastatic upper tract urothelial carcinoma

The molecular characteristics of metastatic upper tract urothelial carcinoma (UTUC) are unknown. The genomic and transcriptomic differences between primary and metastatic UTUC is not well described either. We combined whole-exome sequencing, RNA-sequencing, and Imaging Mass Cytometry (IMC) of 44 tumor samples from 28 patients with high-grade primary and metastatic UTUC. IMC enables spatially resolved single-cell analyses to examine the evolution of cancer cell, immune cell, and stromal cell markers using mass cytometry with lanthanide metal-conjugated antibodies. We discovered that actionable genomic alterations are frequently discordant between primary and metastatic UTUC tumors in the same patient. In contrast, molecular subtype membership and immune depletion signature were stable across primary and matched metastatic UTUC. Molecular and immune subtypes were consistent between bulk RNA-sequencing and mass cytometry of protein markers from 340,798 single-cells. Molecular subtyping at the single cell level was highly conserved between primary and metastatic UTUC tumors within the same patient.

cancer biology↗

bioRxiv2021

A lineage-specific epigenetic memory of inflammation potentiates Kras-driven pancreatic tumorigenesis

Inflammation is essential to the disruption of tissue homeostasis, and, in the pancreas, can destabilize the identity of terminally differentiated acinar cells. Herein we employ lineage-traced mouse models to delineate the chromatin dynamics that accompany the cycle of metaplasia and regeneration following pancreatitis, and unveil the presence of an epigenetic memory of inflammation in the pancreatic acinar cell compartment. We observe that despite histologic resolution of pancreatitis, acinar cells fail to return to their molecular baseline after several months, representing an incomplete cell fate decision. In vivo, this epigenetic memory controls lineage plasticity, with diminished metaplasia in response to a second inflammatory insult but increased tumorigenesis with an oncogenic Kras mutation. We demonstrate that both persistent chromatin and transcriptional changes constituting memory are recalled with oncogenic stress. Together, our findings define the dynamics and recall of an epigenetic memory of inflammation that impacts cell fate decisions in a context-dependent manner.

cancer biology↗