Biology subjects

Li, Z.

Publications and source records attributed to Li, Z..

At least 379 records · Page 21Linked to original sources

bioRxiv2025

New Evidence of Altered Gut Microbiota in Autism Spectrum Disorders through Metagenomic Analysis

Cumulative evidence suggests alterations of gut microbiota in children with Autism Spectrum Disorder (ASD). However, due to highly diverse research approaches, the distinctive microbial patterns and underlying mechanisms driving ASD etiology remain elusive. Here, we constructed the metagenomic dataset of gut microbiota derived from Chinese children with ASD, incorporating a longitudinal study to explore the pivotal role of gut microbiota in the pathogenesis of ASD. At the bacterial species level, we identified a notable increase in the relative abundance of Clostridium scindens, which exhibited a positive correlation with the cholate degradation pathway and showing a decline concurrent with improved behavior in ASD children. Within the fungal community, we observed significant dysbiosis in twenty-six species, underlining their robust discriminatory potential between ASD and neurotypical subjects. Metabolic pathways related to mitochondrial dysfunction were enriched in ASD, alongside peptidoglycan, glutamate, and nucleotide pathways, suggesting potential interactions between the gut and brain through the innate immune system and vagus nerve in ASD. Our findings underscore the significance of the fungal community and mitochondrial dysfunction in ASD etiology, while also shedding light on how perturbed metabolic functions of gut microbiota collectively contribute to the pathogenesis of ASD.

microbiology↗

bioRxiv2025

Human-scATAC-Corpus: a comprehensive database of scATAC-seq data

Single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) profiles chromatin accessibility at cellular resolution, making it possible to reveal epigenomic landscapes that govern gene regulation in a variety of cells. Nevertheless, heterogeneous feature spaces and complex processing pipelines have impeded the construction of an ensemble resource capable of supporting diverse downstream analytical scenarios. To address this gap, we present Human-scATAC-Corpus (https://health.tsinghua.edu.cn/human-scatac-corpus/), a comprehensive database of human scATAC-seq comprising 5,407,621 cells from 35 datasets across 37 tissues or cell lines. To support complementary use cases, each dataset is distributed in three aligned formats: cell-by-candidate cis-regulatory element matrices for cross-dataset integration, raw fragment files for flexible processing, and cell-by-peak matrices for within-dataset analyses. This resource spans diverse biological contexts and includes rich metadata, enabling method benchmarking and development, as well as pretraining of foundation models. The website offers searchable browsing, detailed dataset pages, on-demand downloads, and tutorials. EpiAgent, a foundation model pretrained on Human-scATAC-Corpus, is further integrated to provide online analyses, including reference mapping, embedding extraction, and cell type annotation. Human-scATAC-Corpus establishes a unified and scalable substrate for single-cell epigenomics and is intended to accelerate discovery while standardizing evaluation across tasks. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/674505v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@e2c4c3org.highwire.dtl.DTLVardef@1e3eaf8org.highwire.dtl.DTLVardef@5768c1org.highwire.dtl.DTLVardef@9e96ad_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

Diploid genomes of the booklouse reveal evolutionary consequences ofasexuality

The "Meselson Effect"--a cornerstone of evolutionary theory predicting that asexual organisms accumulate mutations independently across haplotypes due to the absence of recombination--has long eluded robust empirical validation. Here, we address this gap using three high-quality diploid genome assemblies of the obligately parthenogenetic booklouse Liposcelis bostrychophila, a species characterized by apomictic meiosis and striking intraspecific variation. Combining Illumina, PacBio, and Hi-C sequencing, we generated three diploid genomes of three populations (Lb_1, Lb_2, Lb_3), revealing exceptionally high heterozygosity rates (1.67-3.92%) and minimal recombination--hallmarks of prolonged asexuality. Critically, in population Lb_2, intra-individual SNP divergence surpassed inter-population levels, directly demonstrating the Meselson Effect. Phylogenetic analyses of 7,029 genes revealed that while haplotypes within populations clustered as expected under sexual reproduction, nearly 15% of gene trees exhibited topologies consistent with asexual divergence--a signature of incipient Meselson-driven evolution. Comparative genomic analyses further uncovered a twofold expansion of repetitive elements in asexual lineages relative to their sexual relatives (L. brunnea) and widespread relaxation of purifying selection, particularly affecting transcription factor activities. We propose that relaxed selection on transcriptional regulators may act as a compensatory mechanism, buffering the functional consequences of escalating heterozygosity in non-recombining genomes. By integrating population genomics, phylogenomics, and selection analyses, this work not only provides the clearest evidence to date of the Meselson Effect but also establishes L. bostrychophila as a pivotal model for unraveling the genomic paradox of parthenogenesis. Significance StatementThe Meselson Effect, a theoretical prediction that asexual organisms should accumulate mutations independently in their two haplotypes, has been difficult to confirm empirically due to limited genomic data and contradictory findings in prior studies. Here, we provide strong evidence for the Meselson Effect in the parthenogenetic booklouse Liposcelis bostrychophila, using high-quality diploid genomes from three populations. We show that one population exhibits higher genetic divergence within individuals than between populations, a key signature of the Meselson Effect. Additionally, we found a possible novel compensatory mechanism for maintaining genomic stability in the face of increased heterozygosity. These findings advance our understanding of the genomic impacts under asexuality and establish L. bostrychophila as a model for studying the evolutionary consequences of parthenogenesis.

evolutionary biology↗

bioRxiv2025

Hypoimmunogenic human motor neurons induced from iPSCs in vivo substantially ameliorate ALS disease in large animal models

Stem cell-based therapy holds great potential for substituting degenerated motor neurons (MNs) in amyotrophic lateral sclerosis (ALS). Missing protocols for advanced differentiation of transplanted cells into MNs, immune rejection, and the lack of suitable ALS models for preclinical trials have slowed the development of effective therapies. Here, we employed multiplex genetic-editing to generate a novel human pluripotent stem cell line containing doxycycline (Dox)-inducible MNs-specific transcription factors and comprehensively modified immunomodulatory genes. We transplanted these cells into the spinal cord of ALS large animal models (SOD1G93A pigs and TIA1P362L rabbits), which faithfully recapitulate pathologies and symptoms observed in ALS patients. The transplanted cells could efficiently differentiate into functional MNs upon Dox treatment in vivo, distribute throughout the spinal cord and motor cortex via extensive migration, survive long-term without the need for immunosuppression. Notably, these MNs integrated into host neural circuits, as evidenced by their long projection of peripheral axons to target muscle and reformation of neuromuscular junctions. As result, pathologies and motor deficits were substantially ameliorated in both animal models. One Sentence SummaryHypoimmunogenic human motor neurons induced from iPSCs in vivo reform neuromuscular junctions and ameliorate ALS disease in pig and rabbit models.

neuroscience↗

bioRxiv2025

Integrative Multi-omics Deciphers the Assembly Rules of the Human Skin Microbiome and Highlights Lipid-Mediated Niche Partitioning

Understanding the ecological assembly mechanisms of microbial communities is critical for deciphering host-microbiota interactions, however, such processes remain poorly characterized in cutaneous ecosystems. By profiling a non-industrialized rural cohort, this study deciphers the assembly rules governing the human skin microbiome and reveals an evolutionarily conserved core microbiota structured by niche selection. Microbial -diversity peaks when C. acnes and M. osloensis reach equilibrium, supporting the Intermediate Disturbance Hypothesis. Host lipids, rather than aqueous compounds, emerged as the primary drivers of microbial niche partitioning. We further demonstrate that C. acnes and Malassezia restricta function as core metabolic engineers, expressing diverse lipases that hydrolyze triglycerides (TGs) into free fatty acids (FFAs), thereby maintaining skin surface lipid homeostasis ([~]85% TG + FFA). Notably, virtually all skin surface FFAs are microbially derived and function as "public goods", enabling cross-feeding that supports auxotrophic members and fosters mutualistic interactions. Importantly, in vitro coculture experiments confirm that C. acnes establish a survival niche for M. restricta. Our findings support a paradigm shift from a taxonomic to a functional understanding of the skin ecosystem, underscoring microbial lipid metabolism as a central orchestrator of ecological stability and a promising target for therapeutic intervention. O_FIG O_LINKSMALLFIG WIDTH=182 HEIGHT=200 SRC="FIGDIR/small/674196v1_ufig1.gif" ALT="Figure 1"> View larger version (62K): org.highwire.dtl.DTLVardef@1274fa5org.highwire.dtl.DTLVardef@1ddfa07org.highwire.dtl.DTLVardef@49f917org.highwire.dtl.DTLVardef@807a14_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGRAPHIC ABSTRACTC_FLOATNO C_FIG

microbiology↗

bioRxiv2025

Mining genes underlying perennial-to-annual transitions in Oryza with comparative genomics

Perennial rice has shown great potential for alleviating multidimensional sustainability issues that are prevalent in current rice agriculture, prompting widespread interest in its breeding. Currently, one major hurdle for these breeding efforts is our scarce knowledge about the evolutionary mechanisms of the perennial-to-annual transition in Oryza. Here, by performing comparative genomics of three annual-perennial pairs of Oryza species (Oryza rufipogon/O. nivara, O. glumaepatula/O. glaberrima, and O. meyeriana/O. brachyantha), we identified 91 gene families that are present in all the perennial species but are missing in any of the annual species. Annotations and functional prediction of these gene families demonstrated that they may be associated with a battery of physiological components of perenniality, such as phenology, energy allocation, and source-sink dynamics. Furthermore, comparative co-expression analysis revealed that many of these families may also play important regulatory roles for orchestrating diverse processes that differ between perennial and annual Oryza species, including reproduction, root development, and response to environmental stimuli. These results highlight the potential complexity of the emergence of annuality in the Oryza genus and offer promising candidates for future functional studies.

plant biology↗

bioRxiv2025

Fast Fourier Transform is a training-free, ultrafast, highly efficient, and fully interpretable approach for epigenomic data compression

Improving the efficiency of data compression remains essential for feature selection and data modelling. Current approaches for compressing epigenomic/genomic data highly rely on autoencoder that requires substantial computing resources, parameter fine-tuning, training, and time. Here, we developed a training-free, Fast Fourier Transform (FFT)-based method, for data compression with high efficiency and full interpretability. Our FFT method compresses epigenomic data of histone modification up to 1,000-fold while still maintaining high reconstruction fidelity (cosine similarity, 99.7%), does not require any training and completes ultrafast within 70 milliseconds on GPU or 20 seconds on CPU opposite to extensive training in hours/days for autoencoder on GPU/CPU, and offers full interpretability of compressed features from frequency components of original signals in contrast to the uninterpretable "black box" from autoencoder. This enables high accuracy in the classification model prediction (AUC, 0.960). Thus, our novel FFT method represents a major paradigm shift in data compression.

bioinformatics↗

bioRxiv2025

A novel deep learning method using contrastive learning enables interpretable outputs from relationships between gene expression and histone modification

Current methods for predicting gene expression from histone modifications rely on arbitrary binary classification thresholds such as the median to distinguish between high and low expression for genes. This approach lacks biological justification, creates dataset-dependent classifications, and ignores the relative regulatory relationships between genes that are often more biologically meaningful than absolute cutoffs. We introduce a novel pairwise ranking approach that compares relative expression levels between gene pairs based on their histone modification patterns, eliminating arbitrary threshold selection. Evaluation using the REMC E066 and GSE76344 datasets showed that our pairwise classification framework demonstrated consistent ranking performance in both datasets. The ablation study found that only a subset of histone modification types is necessary, giving evidence of redundancy in the biological code.

bioinformatics↗

bioRxiv2025

Automated analysis of C. elegans behavior by LabGym: an open-source, AI-powered platform

The genetic tractability, well-mapped circuitry, and diverse behavioral repertoire of the nematode C. elegans make it an ideal model for physiological and behavioral studies. A wide range of methods has been developed for analyzing C. elegans behaviors, evolving with advances in technology such as videography and computer-assisted analysis. Here, we introduce LabGym--an open-source, artificial intelligence (AI)-based platform we recently developed--to the C. elegans research community. We trained deep learning models in LabGym capable of automatically categorizing and quantifying multiple user-defined parameters of worm locomotion behavior in multi-worm videos with high accuracy. Furthermore, we demonstrated their efficacy in quantifying locomotion changes in aging worms. Our work offers a cost-effective, user-accessible approach to behavioral analysis in C. elegans.

animal behavior and cognition↗

bioRxiv2025

The anti-phage mechanism of a widespread trypsin-MBL module

Protease mediate activation of immune effectors is a conserved mechanism across life. This study identified a widespread and co-evolving trypsin-MBL module as a core effector in diverse bacterial immune systems (e.g., Hachiman, Argonaute, AVAST), protecting host via abortive infection. Focusing on Hachiman-trypsin-MBL, we demonstrated that, the protease activity of trypsin*HamAB is inhibited in the presence of ATP and MBL is an autoinhibited DNase with two inserted loops blocking the catalytic pocket. Upon infection, the HamB helicase senses invading nucleic acids and catalyzes the hydrolysis of ATP, activating the associated trypsin-like protease that cleaves specifically at two non-canonical KSS motif of MBL and releases its DNase activity. Cryo-EM structures of activated trypsin*HamAB bound with DNA reveal DNA binding and ATP hydrolysis lead to the release of the trypsin-like domain, enabling activation. Our work provides a comprehensive understanding on the mechanism of widely distributed trypsin-MBL module, wherein proteolytic activation of a toxic nuclease enables robust bacterial immunity while preventing self-toxicity through multi-layered control.

biochemistry↗

bioRxiv2025

Comprehensive analysis of metabolic reprogramming-related gene signaturesmetabolic reprogramming related gene signature for predicting ovarian cancer prognosis, immune landscape, and potential treatment options

Ovarian cancer (OV) is the most lethal gynecologic malignancy. Metabolic reprogramming is a distinctive feature of cancer and is associated with tumorigenesis and progression. It could be a potential therapeutic target for cancer treatments and a biomarker for assessing cancer prognosis. In this study, we identified metabolic reprogramming-related differentially expressed genes (MRRDEGs) in OV through differential gene expression analysis and conducted a comprehensive characterization of these MRRDEGs. Based on the MRRDEGs, we constructed an effective prognostic risk model including five model genes for OV. The risk score was a valid independent prognostic factor that could more accurately predict the survival of OV patients. It could classify OV patients into distinct risk groups with significant differences in survival. We observed significant differences between risk groups in biological pathway activity, immune cell infiltration patterns, and immunotherapy responses. Specifically, the low-risk group demonstrated superior immunotherapy response compared to the high-risk group. These findings significantly advance our understanding of the relationship between metabolic reprogramming and OV pathogenesis, progression, prognosis, and immunotherapy response, laying a foundation for developing novel biomarkers and therapeutic targets in the future and providing an important reference for the formulation of precision medicine strategies.

bioinformatics↗

bioRxiv2025

Endocytome profiling uncovers cell-surface protein dynamics underlying neuronal connectivity

Endocytosis actively remodels the neuronal surface proteome to drive diverse cellular processes, yet its global extent and circuit-level consequences have defied comprehensive interrogation. Here, we introduce endocytome profiling: a systematic, cell-type-specific approach for mapping cell-surface protein (CSP) dynamics in situ. Quantitative proteomic analysis of developing olfactory receptor neuron (ORN) axons generated an endocytic atlas comprising over 1,100 proteins and revealed the extent to which the surface proteome is remodeled to meet distinct developmental demands. Targeted interrogation of a junctional CSP showed that its endosome-to-surface ratio is precisely balanced to enable developmental axon pruning while preserving mature axon integrity. Multi-omic integration uncovered wide-spread transcellular signaling and identified a growth factor secreted by neighboring neurons to direct ORN axon targeting via endocytic regulation of its receptor. Endocytome profiling thus provides unprecedented access to cell-surface proteome dynamics and offers a powerful platform for dissecting proteome remodeling across diverse cell types and contexts.

neuroscience↗

bioRxiv2025

The Disruption and Normalization of Cortical Language Network Dynamics After Post-Stroke White Matter Disconnection

The human language network undergoes reorganization across different spatiotemporal scales, limited by its fixed structural neurobiological foundations. Although stroke often damages white matter, its effect on temporary language network reorganization is not fully understood. This study examined longitudinal behavioral and resting-state fMRI data from post-stroke patients with exclusive subcortical lesions at three time points: two weeks (n = 38), three months (n = 29), and one year (n = 27). Patients showed mild to moderate language impairments during the acute phase, which improved within three months. The extent of disconnection in several left-hemispheric white matter tracts was negatively associated with language deficits. Healthy controls (HC, n = 25) exhibited domain-segregation dynamics in the cortical language network, limited by the underlying white matter pathways. In patients, severe, state- and track-specific network disruptions were observed in the acute phase, characterized by hypo- and hyper-connectivity and abnormal topological features. As language recovery progressed, connectivity patterns began to return to normal, resembling those of HC, and the domain-segregation dynamics reappeared. These results deepen our understanding of structure-function coupling and indicate significant post-lesional plasticity within the cortical language network.

neuroscience↗

bioRxiv2025

NuSAP1 promotes bipolar spindle assembly in Trypanosoma brucei by bundling spindle microtubules

The parasitic protozoan Trypanosoma brucei assembles a bipolar mitotic spindle and undergoes a closed mitosis to segregate its megabase chromosomes and mini-chromosomes through mechanisms that are distinct from its mammalian host. This parasite employs a subset of trypanosome-specific nucleus- and spindle-associated proteins (NuSAPs) to regulate mitosis, but the mechanistic roles of these proteins remain poorly understood. Here, we performed biochemical and molecular characterization of NuSAP1 and analyzed the functional interplay of NuSAP1 with its interacting and proximal proteins. NuSAP1 localizes to the mitotic spindle with spindle pole enrichment, and interacts with the spindle-associated and spindle pole-enriched proteins NuSAP4 and SPB1 through distinct structural motifs. NuSAP1 and NuSAP4 are interdependent for protein stability, and NuSAP1 is required for SPB1 localization. Further, NuSAP1 bundles microtubules in vitro, and depletion of NuSAP1 disrupts bipolar spindle assembly. Finally, knockdown of NuSAP1 disrupts the localization of its proximal proteins MAP103 and TbMlp2 to spindle poles. Together, these results uncover the mechanistic role of NuSAP1 in bipolar spindle assembly by bundling spindle microtubules and promoting spindle pole complex formation, underscoring unusual regulatory mechanisms for mitosis in this early divergent unicellular eukaryote.

cell biology↗

bioRxiv2025

A Practical Preprocessing Pipeline for Concurrent TMS-iEEG: Critical Steps and Methodological Considerations

Transcranial magnetic stimulation combined with intracranial EEG (TMS-iEEG) has emerged as a powerful approach for probing the causal organization and dynamics of the human brain. Despite its promise, the presence of TMS-induced artifacts poses significant challenges for accurately characterizing and interpreting evoked neural responses. In this study, we present a practical preprocessing pipeline for single pulse TMS-iEEG data, incorporating key steps of re-referencing, filtering, artifact interpolation, and detrending. Using both real and simulated data, we systematically evaluated the effects of each step and compared alternative methodological choices. Our results demonstrate that this pipeline effectively attenuated various types of artifacts and noise, yielding cleaner signals for the subsequent analysis of intracranial TMS-evoked potentials (iTEPs). Moreover, we showed that methodological choices can substantially influence iTEPs outcomes. In particular, referencing methods might strongly affect iTEP morphology and amplitude, underscoring the importance of tailoring the referencing strategy to specific signal characteristics and research objectives. For filtering, we recommend a segment-based strategy, i.e., applying filters to data segments excluding the artifact window, to minimize distortion from abrupt TMS-related transients. Overall, this work represents an important step toward establishing a general preprocessing framework for TMS-iEEG data. We hope it encourages broader adoption and methodological development in concurrent TMS-iEEG research, ultimately advancing our understanding of brain organization and TMS mechanisms. HighlightsO_LIWe presented a practical preprocessing pipeline for single pulse TMS-iEEG data, incorporating key steps of re-referencing, filtering, artifact interpolation, and detrending. C_LIO_LIThe pipeline effectively attenuates multiple types of artifacts and noise, enabling accurate characterization of evoked neural responses. C_LIO_LIMethodological alternatives for each preprocessing step were evaluated using real and/or simulated datasets. C_LIO_LIRe-referencing substantially affects the morphology and amplitude of intracranial TMS-evoked potentials and requires careful consideration. C_LIO_LIA segment-based filtering strategy is recommended to better minimize distortion from TMS-related artifacts. C_LI

neuroscience↗

bioRxiv2025

Conditional Protein Structure Generation with Protpardelle-1c

We present Protpardelle-1c, a collection of protein structure generative models with robust motif scaffolding and support for multi-chain complex generation under hotspot-conditioning. Enabling sidechain-conditioning to a backbone-only model increased Protpardelle-1cs MotifBench score from 4.97 to 28.16, outperforming RFdiffusions 21.27. The crop-conditional all-atom model achieved 208 unique solutions on the La-Proteina all-atom motif scaffolding benchmark, on par with La-Proteina while having ~10 times fewer parameters. At 22M parameters, Protpardelle-1c enables rapid sampling, taking 40 minutes to sample all 3000 MotifBench backbones on an NVIDIA A100-80GB, compared to 31 hours for RFdiffusion.

bioengineering↗

bioRxiv2025

Chemoenzymatically Synthesized O-Acetylated GD3 Gangliosides to Examine Viral Receptor Specificities in a Cellular Context

Gangliosides are a class of sialic acid-containing glycosphingolipids involved in a wide range of biological processes. The terminal sialic acid of gangliosides can be O-acetylated at C7 and/or C9 hydroxyl, contributing to ganglioside structural complexity and function. It has been difficult to obtain panels of structurally well-defined O-acetylated gangliosides for binding and functional studies. We describe here a chemoenzymatic strategy that can provide, for the first time, 7-O-, 9-O-, and 7,9-di-O-acetylated GD3 gangliosides. It is based on the chemical assembly of a common tetrasaccharide precursor as -glycosyl fluoride that is coupled to sphingosine by a glycosynthase, followed by O-acetyl editing by coronaviral hemagglutinin-esterases. The resulting synthetic glycosphingolipids have been employed for cell surface remodeling of erythrocytes. Analysis by liquid chromatography and ion mobility mass spectrometry (LC-IM-MS) demonstrated successful integration of the glycosphingolipids into the plasma membrane with preservation of acetyl ester patterns. Using human coronavirus HKU1 spike-functionalized virus-like particles, we demonstrate that the resulting glycan-remodeled erythrocytes can be utilized in hemagglutination studies as a label free method to investigate viral protein binding to individual glycoforms in a cellular environment. Entry for the Table of Contents O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/670503v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@37de01org.highwire.dtl.DTLVardef@1d043faorg.highwire.dtl.DTLVardef@1ee57borg.highwire.dtl.DTLVardef@6bf474_HPS_FORMAT_FIGEXP M_FIG Table of Contents 7-O-, 9-O-, and 7,9-di-O-acetylated GD3 gangliosides can be prepared by chemical assembly of a tetrasaccharide as -glycosyl fluoride that is coupled to sphingosine using a glycosynthase, followed by O-acetyl editing by coronaviral hemagglutinin-esterases. Cell surface remodeling of erythrocytes using the GD3 derivatives provide a tool to examine viral receptor specificities. C_FIG

biochemistry↗

bioRxiv2025

Immune and non-immune cell fencing of tumor cells is a widespread and functionally relevant spatial pattern in solid cancers

Solid tumors are characterized by a spatially heterogeneous mixture of cancer cells, immune cells and other non-tumor cells. Recent characterization of the heterogeneity at the single cell level has revealed spatial patterns of different cell types often lacking a simple geometric structure associated with cancer progression. Here we investigated the occurrence of physical fencing of tumor cells by specific immune and non-immune phenotypes in the tumor microenvironment (TME) and the association of these clusters to cancer progression in a wide range solid tumors formed in different organs. We analyzed published patient response and imaging mass cytometry (IMC) datasets from tumor microarrays obtained from tumor tissues in triple-negative breast cancer (279 patients), lung cancer (416 patients), melanoma (30 patients), colorectal cancer (9 patients), glioma (185 patients), and head and neck cancer (139 patients) to characterize the presence of fencing clusters of various cell types and their association with differing patient outcomes. Devising and employing simple mechanistic and stochastic spatially-resolved computational models we quantify the dependence of the pro- and anti-tumor roles of a fencing cluster on the size and the lifetime of the cluster, as well as the chemokine gradient in the local environment. We unveiled that spatial patterns of immune cells, especially through fencing tumor boundary, affects tumor progression and treatment responsiveness to immunotherapy.

cancer biology↗