Biology subjects

Zhang, K.

Publications and source records attributed to Zhang, K..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

IgG-Bridging-Seeded Synergistic Aggregation of SARS-CoV-2 Spikes Underlies Potent Neutralization by A Low-Affinity Antibody

Mechanistic studies of viral neutralization typically prioritize high-affinity antibodies, relegating low-affinity binders to the sidelines. We report P5-1C8, a Class 1 SARS-CoV-2 antibody that exemplifies this underexplored "low-affinity yet high-potency" phenotype, retaining strong neutralization of Omicron JN.1 despite markedly weakened trimer binding (KD = 225 nM; IC50 = 0.06 nM). Structural and biophysical analyses reveal that P5-1C8 engages WT and BA.1 spikes through canonical intra-spike bivalency, but with JN.1 it induces aggregation. Using virion-like nanoparticles displaying multiple spikes, we show that IgG remains bound with no detectable dissociation and triggers pronounced aggregation. Coarse-grained molecular dynamics delineate the stepwise pathway in which weak IgG-spike contacts seed aggregation via transient inter-spike bridging. Together, these findings establish the first mechanistic framework demonstrating how weak-binding antibodies can nonetheless achieve potent neutralization through higher-order aggregation, thereby expanding the conceptual landscape of antibody function and opening new directions for antibody evaluation and design. Graphical AbstractLow-affinity antibodies are frequently disregarded in discovery pipelines. This work reports P5-1C8, a Class 1 SARS-CoV-2 antibody with weak trimer binding (KD-to-IC50 > 3,700-fold) yet potent neutralization of Omicron JN.1. Structural, biophysical, functional and coarse-grained simulations collectively demonstrate that transient inter-spike IgG bridging seeds higher-order aggregation, which in turn drives neutralization and provides a mechanistic framework. O_FIG O_LINKSMALLFIG WIDTH=199 HEIGHT=200 SRC="FIGDIR/small/691454v1_ufig1.gif" ALT="Figure 1000"> View larger version (79K): org.highwire.dtl.DTLVardef@1d4f132org.highwire.dtl.DTLVardef@1274400org.highwire.dtl.DTLVardef@e186a6org.highwire.dtl.DTLVardef@4f1870_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2025

Scalable integration and prediction of unpaired single-cell and spatial multi-omics via regularized disentanglement

Deciphering cellular states requires methods capable of integrating large-scale heterogeneous single-cell and spatial omics data. However, these data are typically unpaired due to destructive assays and further confounded by modality heterogeneity, technical noise, and immense scale. Here we present scMRDR, a scalable computational framework based on regularized disentangled representation learning for integrating fully unpaired single-cell and spatial multi-omics datasets. Built on a unified and structure-preserving architecture, scMRDR removes the need for pairing supervision while maintaining computational efficiency, enabling scaling to large datasets spanning multiple disparate omics modalities. Across diverse real-world benchmarks, scMRDR demonstrates strong performance in batch correction, modality alignment, and biological signal preservation. The framework further supports cross-modal translation across omics modalities and enables spatial coordinate imputation for non-spatial single-cell datasets using a reference atlas. The resulting spatial mapping allows spatially resolved analyses, including identification of spatially variable genes and characterization of epigenetic regulatory programs in their native tissue context. These capabilities position scMRDR as a scalable and versatile framework for large-scale multi-omics integration.

genomics↗

bioRxiv2025

Single-cell disentangled representations for perturbation modeling and treatment effect estimation

Dissecting cell-state-specific changes in gene regulation induced by perturbations is crucial for understanding biological mechanisms. However, single-cell sequencing provides only unmatched snapshots of cells under different conditions. This destructive measurement process hinders the estimation of individualized treatment effects (ITEs), which are essential for pinpointing these heterogeneous mechanistic responses. We develop scDRP, a generative framework that leverages disentangled representation learning with asymptotic correctness guarantees to separate perturbation-induced and perturbation-invariant latent variables via a sparsity regularized {beta}-VAE. Assuming quantile-preserving effects of perturbations conditional on confounders, scDRP performs conditional optimal transport in the disentangled latent space to infer counterfactual states and estimate ITEs. Applied to simulated and real single-cell perturbation data, scDRP accurately estimates treatment effects and individual counterfactual responses, with subsequent biclustering analysis further elucidating cell-type-specific functional gene module dynamics. Specifically, it captures distinct cellular patterns under rhinovirus and cigarette-smoke extract exposures, reveals heterogeneous responses to interferon stimulation across diverse immune cell types, and identifies distinct functional module activation in chronic myeloid leukemia cells following CRISPR activation targeting different genes. scDRP also generalizes to unseen perturbation doses and combinations. Our framework provides a principled computational approach to extracting heterogeneous causal relationships from single-cell perturbation data, enabling a deeper understanding of cellular and molecular mechanisms.

genomics↗

bioRxiv2025

GBoost-CTL: A novel method in multi-tissue transcriptome-wide associations studies in cross-tissue learner incorporating GWAS information

Genome-wide association studies (GWAS) have uncovered numerous genetic variants linked to complex human diseases, yet linking these variants to transcripts and tissues that drive pathology remains difficult. Multi-tissue transcriptome-wide association studies (TWAS) offer a powerful bridge, but existing analytical methods have some limitations, either by discarding important signals by separately analyzing and then aggregating results across tissues, implying imputation models in individual tissues, or fusing them with weights that ignore how much GWAS signal each tissue actually carries. Therefore, most of the existing methods do not work uniformly across different GWAS cohorts. Here, we propose GBoost-CTL - a GWAS-boosted cross-tissue learner that can overcome those aforementioned limitations. The method starts with any collection of single-tissue learners (STLs), allowing investigators to choose the most suitable imputation engine for each tissue. It then (i) allocates weights according to each STLs out-of-sample predictive accuracy and (ii) refines those weights incorporating the GWAS-derived information, so that informative tissues are automatically up-weighted while uninformative tissues are down-weighted. This dual weighting strategy lets GBoost CTL adapt to fully shared, partially shared, or highly tissue-specific regulatory architectures while preserving nominal type I error control and delivering substantially higher power than existing linear or covariance-based methods. Through extensive simulation, we have found that this dual weighting strategy lets GBoost-CTL adapt to fully shared, partially shared, or highly tissue-specific regulatory architectures while preserving nominal type I error control and delivering substantially higher power than existing linear or covariance-based methods. When applied to real data, GBoost-CTL consistently outperformed some existing multi-tissue TWAS methods (e.g., TWAS-CTL, UTMOST and PrediXcan) by identifying a greater number of disease-associated genes with more stringent p-values. Given its modular design, computational scalability, and demonstrable gains in discovery power, we believe that GBoost-CTL offers a practical tool for the analysis of multi-tissue TWAS.

bioinformatics↗

bioRxiv2025

Developmental deviations of structural connectivity in youths with ADHD predict symptom and treatment outcomes

Attention-deficit/hyperactivity disorder (ADHD) lacks validated biomarkers to track symptom development or guide treatment selection in youth. We quantified individual deviations from normative age-related trajectories of white-matter structural connectivity (SC) across two independent cohorts: 6,687 typically developing and 1,114 ADHD scans from the ABCD study, and 292 typically developing and 482 ADHD participants from a Chinese cohort. Youth with ADHD showed pronounced SC deviations, especially in higher-order association pathways. A subset of connections showed ADHD-specific developmental reductions in deviations beyond typical developmental patterns, and these changes mediated the age-related decline in ADHD symptoms. Longitudinal within-individual analyses demonstrated that decreases in deviation over two years tracked symptom improvement. Baseline deviations also predicted 12-week treatment response to atomoxetine, but not methylphenidate, and follow-up imaging revealed treatment-related reductions in deviation. Together, these findings identify SC deviation as a robust developmental biomarker with prognostic and theragnostic relevance for ADHD, supporting precision care through risk stratification, individualized pharmacotherapy selection, and objective monitoring of treatment effects.

neuroscience↗

bioRxiv2025

FAM19A4 Enhances Neutrophil Respiratory Burst via p38 MAPK in Lethal Sepsis

Sepsis causes high mortality and resource strain, with neutrophil-derived reactive oxygen species (ROS) contributing to excessive inflammation. The secretory protein FAM19A4 modulates ROS release, but its role in sepsis was unclear. We measured elevated FAM19A4 levels in septic patients and cecal ligation and puncture (CLP) mice, correlating with increased mortality. Fam19a4-/- mice subjected to CLP showed significantly improved survival and attenuated multiorgan injury without impaired peritoneal bacterial clearance or altered circulating neutrophil counts. Deficiency reduced the cell counts of neutrophil (Ly6G+) and macrophage (F4/80+) in lungs and liver, diminished systemic ROS production tracked by bioluminescence, and decreased neutrophil extracellular trap (NET) formation in serum and lung tissue. In vitro, FAM19A4 enhanced neutrophil phagocytosis and ROS generation but did not affect lipopolysaccharide-induced chemotaxis. Mechanistically, bulk RNA sequencing, western blotting, and the p38 inhibitor SB203580 demonstrated that FAM19A4 drives neutrophil ROS release specifically through p38 MAPK signaling activation. These results indicate that FAM19A4 is upregulated during sepsis and exacerbates outcomes by enhancing neutrophil ROS production via p38 MAPK, representing a promising therapeutic target for this condition.

molecular biology↗

bioRxiv2025

Blind Prediction of Complex Water and Ion Ensembles Around RNA in CASP16

Biomolecules rely on water and ions for stable folding, but these interactions are often transient, dynamic, or disordered and thus hidden from experiments and evaluation challenges that represent biomolecules as single, ordered structures. Here, we compare blindly predicted ensembles of water and ion structure to the cryo-EM densities observed around the Tetrahymena ribozyme at 2.2-2.3 [A] resolution, collected through target R1260 in the CASP16 competition. 26 groups participated in this solvation cryo-ensemble prediction challenge, submitting over 350 million atoms in total, offering the first opportunity to compare blind predictions of dynamic solvent shell ensembles to cryo-EM density. Predicted atomic ensembles were converted to density through local alignment and these densities were compared to the cryo-EM densities using Pearson correlation, Spearman correlation, mutual information, and precision-recall curves. These predictions show that an ensemble representation is able to capture information of transient or dynamic water and ions better than traditional atomic models, but there remains a large accuracy gap to the performance ceiling set by experimental uncertainty. Overall, molecular dynamics approaches best matched the cryo-EM density, with blind predictions from bussilab_plain_md, SoutheRNA, bussilab_replex, coogs2, and coogs3 outperforming the baseline molecular dynamics prediction. This study indicates that simulations of water and ions can be quantitatively evaluated with cryo-EM maps. We propose that further community-wide blind challenges can drive and evaluate progress in modeling water, ions and other previously hidden components of biomolecular systems.

biophysics↗

bioRxiv2025

JNK integrates immune and stress signals to balance apoptosis and proliferation in airway progenitors

Chronic inflammation disrupts epithelial regeneration, yet how immune signaling reprograms progenitor fate remains unclear. Using the Drosophila airway as a model of epithelial remodeling, we identify the c-Jun N-terminal kinase (JNK) pathway as a central integrator of immune and stress cues that balances apoptosis and compensatory proliferation in airway progenitors. Persistent activation of the innate immune IMD pathway induces simultaneous cell death and proliferation through a non-canonical route that bypasses NF-{kappa}B/Relish and instead engages JNK. Downstream, distinct transcriptional modules orchestrate these divergent fates: Foxo and AP-1 drive apoptosis, whereas the ETS factor Ets21C mediates proliferation. Genetic inhibition of JNK or its effectors restores progenitor homeostasis, while constitutive activation recapitulates inflammation-induced tissue remodeling. These responses are cell-autonomous, revealing that airway progenitors actively interpret immune and stress signals to determine their fate. Collectively, our findings uncover a modular signaling architecture that links inflammation to regeneration and highlight conserved JNK-dependent transcriptional programs as potential therapeutic targets to prevent progenitor exhaustion in chronic airway disease.

cell biology↗

bioRxiv2025

Hippo signaling differentially regulates distal progenitor subpopulations and their transitional states to construct the mammalian lungs

Lung size control and cell type specification are key unresolved issues. In this study, we have engineered mosaic patterns of Hippo signaling to reveal the developmental potential of SOX9+ progenitors at the distal lung buds. Our results show that the distal SOX9+ subdomain is sufficient to direct lung outgrowth through bifurcation, providing a mechanism for lung size control. Through single-cell analyses, we identify transitional cell states and candidates for promoting cell fates. Moreover, genetic analysis reveals that Hippo signaling induces distinct cell fates at different SOX9+ subdomains to produce the conducting airways and the alveolar epithelium. These results provide the first extensive map of the developmental paths of lung cells. Some of the developmental paths of transitional cell states in mice correspond to those in human lungs. Together, these studies provide mechanistic insight into how Hippo signaling controls the sequential expansion and differentiation of SOX9+ progenitors to construct the mammalian lungs.

developmental biology↗

bioRxiv2025

Complete and haplotype-resolved maps of genomic and epigenetic discordance in monozygotic twins

Telomere-to-telomere (T2T) genome assemblies are indispensable for accurate detection of genetic variation and for resolving complex repetitive regions. Monozygotic (MZ) twin pedigrees provide a powerful model to investigate de novo mutations (DNMs), however, comprehensive, haplotype-resolved analyses of structural variation (SV), allele-specific inheritance in complex regions, and DNA methylation in diploid human genomes remain limited. Here, we generated complete, haplotype-resolved T2T assemblies for two female twins (C33 and C35) from a Han Chinese pedigree by integrating complementary, state-of-the-art sequencing technologies. The resulting T2T-C33 and T2T-C35 assemblies are highly contiguous and complete, with Genome Continuity Inspector (GCI) scores of 74.94 (maternal) and 77.94 (paternal), and consensus quality values (QV) >75 (k = 21). We comprehensively cataloged 62 inter-twin single-nucleotide variants (SNVs), 15 small indels, and identified both shared and private DNMs, revealing nascent genomic divergence between the MZ twins. Focused interrogation of complex regions uncovered pronounced haplotype-specific length polymorphisms and structural heterogeneity within centromeric higher-order repeat (HOR) arrays. Notably, we observed extensive HOR copy-number variation between haplotypes, including a large copy-number difference on maternal chromosome 18, underscoring dynamic HOR array evolution even among genetically identical individuals. Concurrently, genome-wide DNA methylation profiling delineated allele-specific epigenetic variation that may contribute to phenotypic discordance. Together, these high-quality, diploid T2T genomes from a Han Chinese pedigree provide a valuable resource for population-aware genomics and reveal fine-scale, haplotype-specific divergence in MZ twins. Our results advance understanding of repeat dynamics, centromeric architecture, epigenetic variation and the spectrum of human genomic variation at single-base and structural scales.

genomics↗

bioRxiv2025

TWAS-CTL: A robust and efficient method for multi-tissue transcriptome-wide association studies using cross-tissue learners

The advent of transcriptome-wide association studies (TWAS) has expanded the classical genome-wide association study (GWAS) framework by integrating gene expression with genetic variation to identify trait-associated variants. While multi-tissue TWAS approaches improve statistical power over single-tissue models, existing methods often lose information during result aggregation and require intensive computation. Here, we present TWAS-CTL (Cross-Tissue Learner), a novel framework that leverages heterogeneous gene expression across tissues by adaptively reweighting and optimizing multiple single-tissue learners. Simulations demonstrate that TWAS-CTL achieves higher statistical power than the leading method, UTMOST, while maintaining proper type I error control and reducing computational time by over half. When applied to the analysis of the Genetics of Kidneys in Diabetes (GoKinD) cohort, we observed that TWAS-CTL identified more susceptible genes associated with diabetes than both UTMOST and PrediXcan, another widely used method in TWAS. These results establish TWAS-CTL as a powerful and efficient tool for cross-tissue gene expression analysis, capable of integrating heterogeneous gene-trait associations to advance genetic discovery.

bioinformatics↗

bioRxiv2025

Modulating inter-mitochondrial contacts to increase membrane potential for mitigating blue light damage

Mitochondrial membrane potential (MMP) is essential for mitochondrial functions, yet current methods for modulating MMP lack precise spatial and temporal control. Here, we present an optogenetic system that enables reversible formation of inter-mitochondrial contacts (mito-contacts) with high spatiotemporal precision. Blue light stimulation induces rapid formation of mito-contacts, which fully dissipate upon cessation of illumination. These light-induced mito-contacts can enhance MMP, leading to increased ATP production under stress conditions. Moreover, in human retinal cells and C. elegans, high MMP induced by mito-contacts alleviates the deleterious effects of prolonged blue light exposure, restoring energy metabolism and extending organismal lifespan. This optogenetic approach provides a powerful tool for modulating MMP and offers potential therapeutic applications for diseases linked to mitochondrial dysfunction.

biophysics↗

bioRxiv2025

Reverse transcribed ssDNA derepresses translation of a retron antiviral protein

Retrons are bacterial immune systems that prevent the spread of phages by initiating a toxic response within infected hosts. All previously characterized retrons produce high levels of multicopy single-stranded DNA (msDNA) in the cell by reverse transcription, which acts as an antitoxin in the absence of phage infection. However, we describe here a non-canonical mechanism for Type VI retrons, which do not produce detectable msDNA in the absence of phage, yet still provide phage defense. Focusing primarily on Retron-Vpa2, a Type VI retron from Vibrio parahaemolyticus, we show broad defense against phages and identify triggers of the system within phage recombination systems. Within the Retron-Vpa2 operon, we find a highly enriched, structured transcript that we term a hybrid RNA (hyRNA), which contains both the retrons reverse transcription template and a translationally repressed toxic effector coding sequence. We find that phage infection induces the accumulation of high levels of msDNA and that this msDNA is necessary for derepressing translation of the antiviral toxin. These findings present key biological and mechanistic insights into a distinct group of retrons while highlighting the diversity of systems that participate in bacterial immunity.

microbiology↗

bioRxiv2025

A human iPSC-derived motor neuron-myogenic cell coculture platform to evaluate neuromuscular junction innervation after axon injury and in Spinal Muscular Atrophy

Traumatic nerve injury is challenging as motor neurons with damaged axons repair slowly, which can lead to muscle degeneration, while in Spinal Muscular Atrophy (SMA), muscle innervation is reduced. While pro-regenerative or neuroprotective compounds have been identified, their specific ability to enhance or restore neuromuscular junction (NMJ) function in patients remains unclear due to a lack of in vitro human models that track axon growth, NMJ innervation and muscle function. We developed a human iPSC-derived motor neuron-myogenic coculture platform that enables real-time monitoring of axon growth NMJ innervation and axon regeneration and muscle activity following axonal injury, and for SMA-derived motor neurons. We identified spontaneous synchronized GCaMP6f muscle activity as a useful functional marker of NMJ formation. Using this platform, we show that blebbistatin, a pro-regenerative non-muscle myosin II (NMII) inhibitor differentially regulates growth cone dynamics in injured versus uninjured motor neurons, resulting in enhanced NMJ reinnervation. This highlights the therapeutic potential of developing pro-regenerative compounds to promote NMJ innervation. We also confirm that NMJ function is reduced in SMA type 0 (prenatal onset) and type I (pediatric onset) patient-derived motor neurons in the coculture. This human stem cell-based framework can be used, therefore, to evaluate pro-regenerative compounds for axon injury and neuroprotective one for neurodevelopmental and neurodegenerative disorders.

neuroscience↗

bioRxiv2025

Open source software for tube vocal tract modeling, resonance prediction, illustration, and 3D printing

We present accessible code-free tube vocal tract modeling software. The software implements a transfer function. Applications involve exploratory speech acoustics-based basic research and education in phonetic sciences. The program has been made publicly available and presents researchers and students in speech-centric sciences with easily accessible vocal tract modelling and vowel synthesis.

scientific communication and education↗

bioRxiv2025

Lipid peroxidation intrinsically induces mitochondrial iron overload via Bach1-HO-1 signaling to promote cardiac ferroptosis

BackgroundLipid peroxidation and iron accumulation are hallmarks of ferroptosis, a form of cell death characterized by iron-dependent oxidative damage to cellular membranes. However, the molecular link between lipid peroxidation and iron overload in the execution of ferroptosis remains elusive. Moreover, the pathophysiological implications of the interaction between lipid peroxidation and iron overload in cardiac homeostasis and remodeling are also unknown. MethodsWe assessed the role of lipid peroxidation in mediating cardiac iron overload and ferroptosis using genetic mouse models. We also performed molecular and cellular biology studies to elucidate the mechanisms by which lipid peroxidation regulates iron homeostasis and ferroptosis signaling in cardiomyocytes. ResultsCardiomyocyte-specific ablation of Gpx4 (glutathione peroxidase 4), a key suppressor of lipid peroxidation, promoted iron overload and ferroptosis in the heart, leading to dilated cardiomyopathy. Mice with heterozygous Gpx4 knockout were also predisposed to adverse cardiac remodeling and dysfunction following pressure overload. Mechanistically, elevated lipid peroxidation due to GPX4 inactivation intrinsically induced iron overload by promoting the nuclear export of Bach1 and subsequent induction of heme oxygenase-1 (HO-1). Genetic and pharmacologic inhibition of HO-1 markedly attenuated iron overload and ferroptosis in cardiomyocytes and rescued dilated cardiomyopathy associated with Gpx4 deficiency. Moreover, we identified HO-1 mitochondrial translocation as a key mechanism driving mitochondrial iron overload and ferroptosis. Targeted inhibition of mitochondrial iron overload or lipid peroxidation abrogated cardiac ferroptosis and pathological remodeling induced by Gpx4 deficiency. ConclusionsThese findings identified a mechanistic link between lipid peroxidation and iron overload via the Bach1-HO-1 signaling pathway, revealing new regulators and molecular targets for cardiac ferroptosis.

cell biology↗

bioRxiv2025

An inverse Lansing effect: Older mothers produce offspring with improved development and growth efficiency

The Lansing effect predicts a decline in offspring performance with increasing maternal age. Maternal age and diet can influence offspring development and fitness via maternal effects, but how these two factors interact remains poorly understood. We examined how maternal age at oviposition and dietary conditions affect offspring developmental plasticity in a thelytokous predatory mite (Amblyseius herbicolus). Mothers were provided either a restricted or abundant prey diet, and their offspring were exposed to varying prey availability and monitored for hatching success, survival to adulthood, developmental time, size at maturity, and prey consumption. We addressed two main questions: How does maternal age affect offspring developmental time and size at maturity and does maternal diet modify the effect of maternal age on offspring? Our results suggest an inverse Lansing effect. Offspring of older mothers showed increased survival and reduced prey consumption without any compromise in terms of size at maturity. Interactions were found between maternal diet and age on offspring prey consumption and developmental plasticity. Notably, offspring from older, diet-restricted mothers achieved the best overall performance during development. Our study demonstrates that maternal age and diet jointly shape offspring development, and highlights the importance of incorporating maternal age into studies of maternal effects and phenotypic plasticity.

evolutionary biology↗

bioRxiv2025

Causal Modeling Reveals Cell-Cell Communication Dynamics in the Tumor Microenvironment During Anti-PD-1 Therapy in Breast Cancer Patients

BackgroundImmune checkpoint blockade (ICB) targeting PD-1/PD-L1 plays a crucial role in breast cancer treatment. Despite clinical success, how ICB reshapes the tumor microenvironment (TME) to enhance anti-tumor activity remains unclear. Anti-PD-1 therapy alters TME cells beyond PD-1+ T cells, with extensive cell-cell communication (CCC) playing a key role. Understanding the dynamic CCC changes upon anti-PD-1 treatment can illuminate ICB mechanisms of action and TME dynamics. MethodsWe analyzed single-cell RNA-seq data from 31 breast cancer patients before and after anti-PD-1 (pembrolizumab) treatment (Bassez et al., 2021). We identified differentially expressed genes (DEGs) induced by treatment in major cell types. We then applied an instrumental variable approach to uncover causal relationships between T-cell and non-T-cell DEGs. We further mapped ligand-receptor interactions mediating signal transduction between cells and constructed a CCC network from T to non-T cells. ResultsAnti-PD-1 therapy induced widespread transcriptional changes across multiple cell populations. Key pathways modulated in T cells included NF-{kappa}B, interferon-{gamma}, and interleukin signaling. CD4+ and CD8+ exhausted T cells engaged in distinct ligand-receptor interactions with tumor-associated macrophages (TAMs) and other types of cells, reshaping the TME. Our results indicated CD4+ exhausted T cells activated M1-like TAMs via TNF-TNFRSF1A and TNFSF14-LTBR, while CD8+ exhausted T cells engaged M1-like TAMs through ICAM1-ITGAL/ITGB2 and CCL8-CCR2, promoting anti-tumor immunity. Conversely, immunosuppressive interactions were also observed, such as TNF-TNFRSF1B (TNFR2) and TNFSF14-TNFRSF14 (HVEM) from CD4 T cells, as well as CSF1-CSF1R and RPS19-C5AR1 from CD8 T cells, which likely promote M2-like tumor-associated macrophage (TAM) polarization and contribute to pro-tumor immune regulation and resistance to therapy. Notably, key receptors in the causal CCC networks, such as C5AR1, TNFR2, and CSF1R, emerged as potential targets to enhance anti-PD-1 efficacy. ConclusionsThese findings elucidate TME remodeling during anti-PD-1 therapy and underscore the pivotal role of CCC in treatment response. Our study identifies critical communication networks that may be biomarkers for immunotherapy responsiveness and highlights novel therapeutic targets, including C5AR1 and HVEM. Furthermore, our application of causal inference methodologies provides a robust framework for dissecting CCC mechanisms in immunotherapy.

bioinformatics↗