Biology subjects

Song, D.

Publications and source records attributed to Song, D..

At least 19 recordsLinked to original sources

bioRxiv2026

Spatially resolved host-fungal transcriptomics profiling by fungal-DBiT

Hosts and their associated fungi coexist within a shared tissue environment, engaging in dynamic interactions that influence immune regulation, tissue homeostasis, and disease progression. Dissecting these interactions requires spatially resolved and unbiased approaches capable of capturing gene expression from both host and fungal cells within intact tissue architecture. Here, we present fungal-DBiT, a spatial transcriptomic platform that enables simultaneous, high-resolution mapping of host and fungal RNAs, directly in tissue sections. Using fungal-DBiT, we profiled the spatial distribution of host and fungal transcripts in a fungal infection mouse model, and review pronounced spatial heterogeneity in fungal localization and activity, accompanied by region-specific host transcriptional responses. We further applied fungal-DBiT to intestinal tissues under physiological conditions, demonstrating its sensitivity in detecting low-abundance fungal species in the absence of overt inflammation. Together, these results demonstrate the ability of fungal-DBiT to resolve host-fungal interactions in situ and highlight its utility for studying mycobiome associated immune responses and disease processes with spatial precision.

microbiology↗

bioRxiv2026

Reversion to the Meta Body Form of Life after Complete Cell Death in Pure Liquid Water

The prevailing view holds that simpler animate beings predating the dawn of cellular life once existed, yet they have long since vanished from the present-day Earth. Our hypothesis posits that these animate beings persist to this day. To this end, we devised a long-term experiment spanning over a decade, keeping Staphylococcus aureus (S. aureus) within a sealed aqueous system of pure water. The findings illustrated that, upon the complete cell death (CCD) of the S. aureus, as cellular remnants progressively succumbed to dissolution, the aqueous solution underwent self-purification, bringing forth a class of lipid bilayer membrane microspheres containing RNA and proteins. These structures maintained long-term sustainable stability within the thermodynamic storm of water molecules and underwent dynamic size fluctuations over time - collectively exhibited phenomena indicative of being "alive". This study reveals that the cell, upon complete cell death, undergoes reversion to a living entity simpler than the cell itself - the Meta Body (MB). The discovery of MB opens an entire re-conceptualization of what death ultimately brings.

biophysics↗

bioRxiv2026

Trustworthy super-resolution reconstruction across spatial omics modalities

Sequencing-based spatial omics platforms provide scalable and unbiased profiling of transcriptomic, epigenomic, and isoform-resolved signals, but their spatial resolution remains limited because each capture unit aggregates molecular information from multiple cells. Existing computational enhancement methods reconstruct high-resolution spatial gene expression from spot-level data by integrating histology, but most are designed primarily for spatial transcriptomics, rely predominantly on histological features, and lack appropriate validation strategies, leading to overfitting, spurious spatial patterns, and limited reliability. Here we present spEnhance, a generalizable and trustworthy computational framework for super-resolution enhancement of spot-level spatial omics data. spEnhance integrates histological features with complementary molecular information, including single-cell RNA-seq references and gene co-expression structure, to reconstruct high-resolution spatial molecular profiles. To enable reliable model selection from a single tissue section, spEnhance introduces a count-splitting strategy that generates statistically independent training and validation sets from spot-level measurements. spEnhance further quantifies prediction reliability through predictive residuals, providing an interpretable proxy for spatially resolved uncertainty. Comprehensive benchmarking across multiple tissues, platforms, and molecular modalities demonstrates that spEnhance achieves state-of-the-art accuracy, recovers fine-grained tissue structures, mitigates overfitting, and provides calibrated reliability estimates. Beyond spatial transcriptomics, spEnhance extends to isoform-level, epigenomics, proteomic and metabolomic spatial omics. Collectively, spEnhance establishes a modality-general and trustworthy framework for enhancing spatial omics data, enabling more accurate and reliable investigation of spatially resolved molecular regulation.

bioinformatics↗

bioRxiv2026

OmniTCR: a foundation model unifying T cell receptor recognition prediction and conditional sequence generation

T cell receptor (TCR) recognition prediction and receptor generation are traditionally modelled separately, leaving vast TCR sequence collections disconnected from smaller TCR-peptide-MHC datasets. Here we present OmniTCR, a 113-million-parameter autoregressive foundation model pretrained on 328 million formatted human immune-sequence records. Sequence-type tokens and complementary component orders enable joint learning from individual TCR chains and partial or complete TCR-pMHC associations. On unseen epitopes, OmniTCR achieved AUPRCs of 0.7009 for peptide-TCR{beta}; recognition and 0.8235 for TCR-pMHC interaction prediction, exceeding the strongest evaluated comparators by 0.3396 and 0.3451, respectively. It distinguishes cancer from healthy repertoires across 11 independent pan-cancer cohorts (mean AUROC, 0.9436). The model achieved the highest sequence recovery on internal and external generation benchmarks. Structural modelling supported the plausibility of selected pMHC-conditioned CDR3{beta}; candidates. OmniTCR bridges heterogeneous immune sequence data, providing a foundation for computational immunology and receptor design.

bioinformatics↗

bioRxiv2026

spAlignDE unifies cross-sample and cross-modal spatial alignment with mismatch-aware differential expression

Comparative analysis of spatial omics requires aligning data across samples and modalities to a common coordinate system. Existing methods can be computationally intensive for large datasets, and cross-modal alignment is difficult when datasets lack comparable molecular features. In addition, residual alignment errors can cause locations assigned to the same coordinates to represent different biological regions, producing false differential expression signals. Here we propose spAlignDE, a computational method that integrates structure-guided spatial alignment with mismatch-aware local differential expression analysis. spAlignDE represents structures from spatial transcriptomics, spatial ATAC-seq, histology, and anatomical atlases as continuous fields and aligns them by shooting-based diffeomorphic registration without requiring shared molecular features. In cross-sample benchmarks against 12 methods, spAlignDE achieved the highest agreement in gene expression patterns and anatomical annotations. It also scaled to 20 MERFISH brain sections containing 1.45 million cells. For cross-modal tasks, spAlignDE accurately aligned spatial transcriptomics with histology, the Allen Mouse Brain Common Coordinate Framework, and spatial ATAC-seq. After alignment, spAlignDE estimates local expression contrasts on a shared grid and inflates their variances according to mismatch risk estimated from putatively stable genes and local observation density. The analysis can also adjust for cell-type composition. Simulations showed improved false discovery control without systematic loss of power. In real-data applications, spAlignDE localized age-associated changes in gene expression and T-cell distribution in the mouse brain and spatially restricted expression differences between normal and injured kidney sections.

bioinformatics↗

bioRxiv2026

The Capillary endothelial cell-governed niche sustains angiogenesis in proliferating infantile hemangioma via multilayer stromal support

Infantile hemangioma (IH), the most common benign vascular tumor in infants, is characterized by the aberrant proliferation of hemangioma endothelial cells (HemECs) and excessive angiogenesis. However, it is unclear how the tumor microenvironment sustains these active angiogenic signals. We performed single-cell RNA sequencing and spatial transcriptomic to profile 30 samples from proliferating IH, involuting IH, and normal skin. The results indicated that HemECs comprised distinct subpopulations. Among them, capillary endothelial cells (Cap.ECs) had an immature phenotype and functioned as the core drivers of IH. The endothelial-to-mesenchymal transition endothelial cells (endoMT-ECs) secreted collagen and engaged in CD44-mediated crosstalk with Cap.ECs to construct the angiogenesis-active niche in the tumor microenvironment (TME) of proliferating IH. Blockade of CD44-mediated intercellular communication effectively suppresses the angiogenesis of HemECs and promotes tumor regression. Beyond the endothelial layer, pericytes tightly enveloped Cap.ECs, with SERPINE2+ subtypes sustaining their angiogenic activity via ANGPT signaling. Pseudotime trajectory analysis revealed that the mesenchymal stem cells (MSCs)-enriched niche serves as a progenitor pool for Cap.ECs in proliferating IH. Our findings thus revealed that IH progression relies on CD44-mediated endoMT-EC-Cap.EC crosstalk and on both pericyte and MSC niches to sustain angiogenesis. HIGHLIGHTSO_LICapillary endothelial cells drive infantile hemangioma progression, with pericytes tightly ensheathing them. C_LIO_LICD44-mediated capillary and endoMT-derived endothelial cells crosstalk construct the angiogenic-active niche in the tumor microenvironment of proliferating infantile hemangioma. C_LIO_LIThe MSC-enriched niche provides a progenitor pool for the capillary endothelial cells in proliferating infantile hemangioma. C_LI

cancer biology↗

bioRxiv2026

Early and current environments exert distinct effects on immune function in the Orang Asli

Humans evolved in environments characterized by subsistence foraging and hunting, high levels of physical activity, and regular and diverse pathogen exposure. Industrialization has rapidly altered these environments, leading to increased metabolic and inflammatory disease risk. These observations have motivated studies of how industrialization shapes immune function, but whether industrialization alters immune biology through developmental embedding of early-life environments or ongoing plastic responses to current conditions remains poorly understood. To address this gap, we worked with the Orang Asli--the Indigenous peoples of Peninsular Malaysia--who currently span a gradient from subsistence horticulture, foraging, and hunting to industrialized, urban environments with substantial inter-individual variation in life course experiences. Leveraging continuous measures of both early-life and current lifestyle, we found that current lifestyle exerts stronger effects on adult immune gene expression than early-life conditions, impacting 1,428 as compared to 223 genes, respectively. Early-life associated genes were enriched for pathways regulating adaptive immunity, particularly T cell development and differentiation, consistent with higher predicted T cell abundance and circulating IL-8 in urban-born individuals. In contrast, current exposure to urban, industrialized conditions was linked to innate immune and inflammatory activation, including dendritic cell abundance, metabolic pathway upregulation, and elevated CRP. Finally, consistent with lower rates of immune disorders in non-industrial settings, current exposure to this lifestyle was associated with up-regulation of genes involved in Th1/Th2 differentiation. Together, these results emphasize that industrialized immune profiles reflect both early-life developmental embedding and ongoing environmental responses, highlighting the importance of considering exposures across the life course. Significance statementHumans evolved in environments with high levels of physical activity, subsistence-based diets, and constant pathogen exposure. Rapid industrialization has dramatically changed these conditions, coinciding with rising rates of non-communicable diseases with inflammatory underpinnings. Our study with the Orang Asli, the Indigenous peoples of Peninsular Malaysia, tests how exposure to industrialization across the life course shapes immune variation. We find that early-life environments leave lasting marks on adaptive immune function particularly T cells, while industrialized adult lifestyle influences innate immune activity and inflammation. These results clarify how different stages of life contribute to immune remodeling and point to a mechanistic link between industrialization and disease risk, highlighting the importance of both early-life and current environments in shaping later life health.

genetics↗

bioRxiv2026

A Tripartite Map of the Ventromedial Prefrontal Cortex

The ventromedial prefrontal cortex (VMPFC) has been repeatedly implicated in affect, valuation, and social cognition, yet how these diverse functions are organized within a single cortical territory has remained unresolved. Here, we integrate large-scale meta-analysis, individual-level task fMRI, artificial neural-network encoding models, and multimodal connectivity analyses to reveal the internal functional architecture of the human VMPFC. Across four complementary studies, we identify a robust tripartite organization along the anterior-posterior axis, comprising posterior affective, middle valuation, and anterior social functional motifs. Connectivity fingerprinting demonstrates that each motif is preferentially embedded within distinct large-scale brain networks, providing a mechanistic account of VMPFC functional specialization. This organization is reproducible at the level of individual subjects, generalizes to naturalistic stimuli, extends across development, and shows cross-species correspondence with non-human primates and multiple neurobiological markers. Together, these findings resolve a long-standing organizational question and establish a biologically grounded framework for interpreting VMPFC function.

neuroscience↗

bioRxiv2026

Single-chip End-to-End Ingestible Electronics for Gut Neurotransmitter Sensing

Neurotransmitters in the gut play a vital role in human health and neuroscience, and their real-time monitoring is essential for understanding underlying physiological mechanisms. However, bioelectronic systems capable of measuring neurotransmitters in vivo at the anatomical site of interest remain underdeveloped and largely depend on bulky, off-the-shelf electronic components, thereby constraining the development of systems that are both practical and minimally invasive. Here, we report a miniature ingestible pill that is capable of real-time in vivo sensing of two key neurotransmitters: serotonin (5-HT) and dopamine (DA). The system incorporates a fully printed three-electrode-based electrochemical sensor for neurotransmitter sensing and a custom application-specific integrated circuit (ASIC) that integrates all major functional blocks on a single chip, enabling a platform for fully wireless monitoring of gut neurotransmitters. The pill, measuring 5.8 mm in diameter and 19 mm in length, supports multiple electrochemical sensing techniques, including amperometry and voltammetry, with only 42 A of average current consumption. We demonstrate the ingestible platform through in vivo studies in rat animal models, enabling real-time monitoring of gut neurotransmitters.

bioengineering↗

bioRxiv2026

scDesignPop generates realistic population-scale single-cell RNA-seq for power analysis, benchmarking, and privacy protection

Single-cell RNA sequencing (scRNA-seq) combined with genotyping in large cohorts has enabled the discovery of genetic associations with molecular traits (e.g., eQTLs) at cell-type resolution. However, generating population-scale data remains cost-prohibitive, selecting appropriate analysis methods lacks consensus, and sharing eQTL results alongside scRNA-seq data raises privacy risks. To address these challenges, we introduce scDesignPop, a flexible statistical simulator for generating realistic population-scale scRNA-seq data with genetic effects. scDesignPop models cell- and individual-level covariates, putative cell-type-specific eQTLs (cts-eQTLs), and either real or synthetic genotypes. We validated scDesignPop using the OneK1K and CLUES cohorts across 4 qualitative and 16 quantitative metrics. Unlike splatPop, the only existing population-scale simulator, scDesignPop better preserves eQTL effects and gene-gene dependencies within cell types, closely recapitulating characteristics of the reference data. Leveraging its generative framework, scDesignPop enables power analysis in cell types under multiple eQTL model specifications to guide experimental design; facilitates benchmarking of single-cell eQTL mapping methods through user-defined ground truths; and mitigates re-identification risk using synthetic data while retaining cts-eQTL effects.

bioinformatics↗

bioRxiv2026

Lacticaseibacillus rhamnosus GR-1 attenuates Escherichia coli-induced endometritis in mice, accompanied by modulation of uterine microbiota and metabolite profiles

ObjectiveEndometritis in dairy cows is a highly prevalent infectious disease in cattle farming, which can cause persistent inflammatory responses in the uterus. This study aimed to evaluate the therapeutic efficacy of Lacticaseibacillus rhamnosus (L. rhamnosus) GR-1 against Escherichia coli (E. coli)-induced endometritis in mice and investigate its regulatory effects on uterine microbiota and metabolites. MethodsA total of 36 female BALB/c mice aged 7-8 weeks were randomly divided into 4 groups: CONT group, ECOL group (1.0x108 CFU/mL E. coli), AMP group (0.1 mg/kg ampicillin), and GR-1 group (1.0x109 CFU/mL L. rhamnosus GR-1). Uterine morphological characteristics were observed, and the expression of uterine inflammatory cytokines, oxidative apoptosis-related genes and proteins, as well as related reproductive indices were detected. 16S rRNA sequencing and metabolomic sequencing were performed to evaluate the profiles of uterine microbiota and metabolites. ResultsL. rhamnosus GR-1 effectively alleviated E. coli-induced uterine edema and inflammatory infiltration, and modulated the levels of inflammatory factors (MPO, IL-6, IL-1{beta}, TNF-, IL-10 and MDA) in the uterus. Meanwhile, this strain elevated the levels of antioxidant factors (GSH-Px and SOD), inhibited the expression of the oxidative apoptosis-related factors Keap1, Bax and caspase-3, and upregulated that of Nrf2, HO-1, NQO1 and Bcl-2. Furthermore, treatment with L. rhamnosus GR-1 increased the abundance of beneficial uterine microbiota, promoted the accumulation of L-isoleucyl-L-proline and N-acetylcysteine, and ameliorated the pregnancy status of mice. ConclusionL. rhamnosus GR-1 enhanced uterine anti-inflammatory and antioxidant stress capacity to alleviate E. coli-induced endometritis in mice. It modulated uterine microbiota and metabolites, and also improved the reproductive capacity of mice. Thus it may provide a potential antibiotic alternative for the treatment of dairy cow endometritis.

microbiology↗

bioRxiv2025

Deep-learning model guided discovery and characterization of bacterial unspecific peroxygenases

Unspecific peroxygenases (UPOs) are capable of catalyzing the selective oxidation of organic substrates under mild conditions, using hydrogen peroxide (H2O2) as the sole oxidant. This makes them one of the most promising biocatalysts for chemical synthesis. However, the major limitation restricting the application of UPOs to date is their difficulty in heterologous expression. Although more than 4,000 putative UPO enzymes have been recorded in databases, only about 50 of them can currently be heterologously expressed. All UPOs discovered so far originate from eukaryotes (mainly basidiomycetes and some ascomycetes), and they rely on the complex expression systems and post-translational modifications of their native hosts. This further exacerbates the challenges associated with heterologous expression of eukaryotic UPOs. In this work, we developed a deep-learning-based enzyme mining strategy and, for the first time, discovered novel UPO enzymes from bacteria, achieving successful heterologous expression in Escherichia coli. Bacterial UPOs differ greatly from fungal UPOs in sequence similarity, displaying completely distinct evolutionary trajectories. The discovery of bacterial UPOs advances our understanding of the catalytic mechanisms and expression characteristics within the UPO family, breaking the long-held assumption that UPOs can only originate from eukaryotes. Their excellent heterologous expression performance and broad catalytic versatility will further expand the application potential of UPOs.

bioinformatics↗

bioRxiv2025

Prefrontal cortex and striatum dissociate modality and learning order in cross-modal sensorimotor learning

AO_SCPLOWBSTRACTC_SCPLOWSensorimotor learning is accompanied by the emergence and strengthening of sensory responses in the prefrontal cortex (PFC) and striatum. However, it remains unclear whether learning-evoked sensory responses in these structures are modality-specific, or whether they represent a more generalized signal for modality-independent but behaviorally relevant stimuli. To address this question, we performed widefield calcium imaging while mice were trained on sensorimotor tasks involving either visual or auditory stimuli, with mice first learning one modality and then switching to the other. We found that the anterior PFC (aPFC) exhibited a bilateral response to both visual and auditory stimuli after learning the respective tasks, indicating a generalized sensory representation. In contrast, the medial PFC (mPFC) showed modality-specific activity, responding only to contralateral visual stimuli after learning. Mice were able to learn sensorimotor associations for both modalities in sequence, and were only able to transfer learned behavior from visual to auditory stimuli but not the reverse. Despite differences in cross-modal learning transfer, cortical responses to learned stimuli were the same regardless of learning order. In contrast, electrophysiological recordings in the anterior striatum revealed that visually responsive regions became co-responsive to auditory stimuli only in mice trained on the visual task first. The additional auditory responses arose from distinct neurons rather than those previously responsive to visual stimuli, indicating that co-responsiveness occurred at the regional rather than single-neuron level. Together, these findings reveal that learned sensory responses in the PFC and striatum uniquely dissociate modality and learning order, suggesting a divergence in their roles during sensorimotor learning.

neuroscience↗

bioRxiv2025

Brain Entropy: Linking Brain Structure to Task Activation

Understanding how the brains complex and diverse functions emerge from its structure has long been a central goal of neuroscience. Entropy, a measure of system irregularity, has become a powerful tool for quantifying the dynamics of brain activity. While previous fMRI-based brain entropy (BEN) studies have established its relationships with brain morphology (e.g., gray matter volume, GMV) and task activation, the pathway from structure to function remains incompletely understood. Specifically, it is unclear whether controlling for brain morphology (GMV) significantly alters the observed BEN-task activation relationship. In this study, we first replicated key prior findings, including the effects of sex and age on BEN and GMV, their spatial and brain-wide voxel-wise correlations, and the relationship between BEN and task activation across social cognition, reward, and emotion tasks. Subsequently, we examined the correlation between GMV and task activation, as well as the correlation between BEN and task activation after controlling for GMV. Our results successfully replicated previous findings. Crucially, the relationship between BEN and task activation remained largely unchanged after controlling for GMV. This indicates that BEN captures unique variance in task activation beyond what is explained by GMV alone, establishing BEN as a functional bridge linking brain structure to task activation. Future work should employ predictive analyses to quantify the added value of BEN in predicting task activation from structural information.

neuroscience↗

bioRxiv2025

The development of the brain was revealed by brain entropy (BEN) during movie watching from the age of three to twelve years

Mapping the developmental landscape of brain function is a key objective in modern neuroscience, greatly advanced by the public release of neuroimaging datasets. Here, we utilized movie-watching fMRI to study brain entropy (BEN) in 3-12-year-olds from OpenNeuro. The results of the analysis revealed that decreasing BEN within the action-mode network (AMN) serves as a key developmental marker in children. The AMN underpins goal-directed cognition, and its entropy reduction may signify a crucial shift from early, externally driven sensorimotor processing toward the emergence of more internalized, self-referential thought processes associated with the default-mode network. These findings highlight BEN as a powerful and sensitive tool for deciphering the principles of functional brain development.

neuroscience↗

bioRxiv2025

Wearable Focused Ultrasound Neuromodulation and Electrophysiological Recording Patch for REM Sleep Enhancement

The rise in sleep disease affecting the general population globally in the past decade has been detrimental to individually and socioeconomically. As of now, approaches often are temporary through medication, permanently using invasive implants with surgical complications or neuromodulation therapy. However, non-invasive, state-dependent neuromodulation during sleep is technically challenging, especially with the lack of flexibility, comfortability and robustness for sleep conditions. Here, we introduce a Non-invasive Electrophysiological Recording and Ultrasound Neuromodulation Sleep Patch (NEUSLeeP) in delivering focused ultrasound stimulation to the subthalamic nucleus (STN) overnight with simultaneous stable polysomnography recording. Our sleep patch integrates a custom eight-channel concentric ring transducer array with real-time electroencephalography (EEG), electrooculography (EOG), electromyography (EMG) recording, and individualized line-of-sight targeting to sonicate deep brain areas while preserving mobility. Our platform operated safely and comfortably across the two-nights sleep study. Stimulation of the left STN was delivered every 90 minutes throughout the night and was associated with a 25% increase in REM (Rapid Eye Movement) sleep duration and a 43 minutes reduction in REM sleep latency compared to a sham night in a study of 26 subjects. Blood Oxygen Level Dependent (BOLD) signal attenuation in functional Magnetic Resonance Imaging (fMRI) was localized primarily to a left ipsilateral basal-ganglia-midbrain-temporal circuit, consistent with selective network modulation rather than global arousal changes. Overall, NEUSLeeP demonstrates feasibility by (i) a light weight and wearable ultrasound neuromodulation and sleep recording during natural sleep; (ii) establishing a potential mechanism relating targeted ultrasound stimulation of STN/sleep networks to REM enhancement.

bioengineering↗

bioRxiv2025

spCorr: flexible and scalable inference of spatially varying correlation in spatial transcriptomics

Spatial transcriptomics has transformed our ability to explore gene expression within its tissue context, enabling us to dissect subtle yet biologically significant variations in situ. While numerous computational methods have been proposed for detecting Spatially Varying Genes (SVGs) expression by modeling each individual gene separately, much less effort has been devoted to understanding how correlations between genes change across space. Such Spatially Varying Correlations (SVCs) are critical for understanding biological processes such as gene regulatory mechanisms shaped by local tissue environments, yet existing tools remain limited for this task. To address this gap, we present spCorr, a flexible and scalable regression framework for studying SVCs. spCorr provides interpretable, spot-level estimates of gene correlation and detects gene pairs whose correlations vary across locations or between tissue domains. Through extensive simulations and real-data analyses, we show that spCorr achieves high detection power, reliably controls the False Discovery Rate (FDR), and is computationally efficient. Importantly, spCorr reveals biologically meaningful correlation patterns that highlight fine-scale tissue structures, gene module functions, and region-specific interactions, offering new opportunities to study coordinated gene regulation in spatial transcriptomics.

bioinformatics↗

bioRxiv2025

Tumors mimic the niche to inhibit neighboring stem cell differentiation

Although it is well-established that stem cells maintain tissue homeostasis while tumors disrupt it, the mechanisms by which tumors influence the development of nearby stem cells remain poorly understood. Using Drosophila ovaries as a model system, here we discovered that bam or bgcn mutant germline tumors inhibit the differentiation of neighboring wild-type germline stem cells (GSCs). Mechanistically, these tumor cells mimic the stem cell niche by secreting the BMP ligands Dpp and Gbb, but at reduced levels, resulting in moderate BMP signaling activation in adjacent GSCs. Such BMP signaling activation is sufficient to repress bam transcription, thereby blocking GSC differentiation. To our knowledge, this is the first example that tumors can functionally mimic a stem cell niche to inhibit the differentiation of neighboring wild-type stem cells. Similar regulatory paradigms may operate in mammalian tissues, including humans, during tumorigenesis.

developmental biology↗