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PubMed2026

Understanding tumor adaptations and resistance to MET inhibitors in MET-altered non-small cell lung cancer.

AIM: Type Ib MET inhibitors are clinically active in selected MET-altered non-small cell lung cancer, particularly tumors with MET exon 14 skipping or MET amplification, but acquired resistance remains incompletely understood. Here, we investigated resistance across biologically distinct MET-altered contexts, including MET exon 14 skipping, MET amplification, and MET overexpression. METHODS: Paired baseline and progression samples from seven patients treated with tepotinib or capmatinib were analyzed using spatial transcriptomics, whole-exome sequencing, RNA sequencing, CRISPR screening, and drug-combination assays. Patient-derived cultures and resistant cell-line models were used to explore resistance-associated changes. RESULTS: MET inhibitor resistance was heterogeneous, with persistence of the initial MET alteration in most evaluable cases and emergence of patient-specific genomic events. Three main resistance-associated, often overlapping, routes were identified: on-target MET evolution through kinase-domain alterations; extracellular matrix and tumor-microenvironment remodeling, including collagen and fibronectin upregulation, complement-related signaling, and partial EMT-associated programs; and bypass signaling involving EGFR/HER, MAPK, and PI3K/Akt pathways. In vitro models reproduced several tumor-cell-intrinsic features but only partially captured microenvironment-associated changes. CONCLUSIONS: MET inhibitor resistance in this cohort involved overlapping, context-dependent genomic, phenotypic, and signaling adaptations, supporting combination strategies for MET-altered lung cancer.

CRISPR screen↗
PubMed2026

Metabolic depot for nucleated erythrocyte degradation: molecular and structural elucidation of the teleost melanomacrophage center.

The function of melanomacrophage centers (MMCs) has long been controversial. While their foundational function is widely accepted as "metabolic dumps" for waste processing, a widely circulated hypothesis posits that they are primitive germinal centers (GCs) executing adaptive immunity. To elucidate this controversy, this study systematically evaluated the splenic MMCs in a higher teleost ( Micropterus salmoides) by combining transmission electron microscopy (TEM) and high-resolution spatial transcriptomics. Structurally, TEM revealed that the MMC comprises a core with characteristic sparse cellular density, filled with cellular debris and encapsulated by a fibrous layer. Molecularly, under physiological conditions, MMC regions exhibited low transcriptional activity. We did not detect clear enrichment of B cell and T cell lineage genes, and the key GC marker aicda was not observed. Conversely, its predominant molecular signature was characterized by macrophage-driven iron metabolism (e.g., ferritin) and erythrocyte degradation (e.g., hba1). Furthermore, the physicochemical properties of MMCs pigments (e.g., argyrophilia) suggest that traditional histological staining methods warrant cautious interpretation regarding potential non-specific signals. In conclusion, our findings characterize the MMC as a highly specialized metabolic processing and sequestration niche. This study provides new perspectives on the evolution of immune-metabolic homeostasis in poikilothermic vertebrates, advances comparative immunology, and offers a critical scientific reference for the accurate interpretation of MMCs as a biological indicator in pathology and ecotoxicology.

Animals↗
PubMed2026

Striping artifact removal in VisiumHD data through nuclear counts modeling.

MOTIVATION: 10x Genomics VisiumHD enables spatial transcriptomics at 2 µm × 2 µm resolution but exhibits slide-specific, non-periodic striping artifacts due to lane-width variability. These multiplicative row/column effects distort bin total counts and can bias downstream analyses. The state-of-the-art destriping approach is the normalization procedure used as a preprocessing step in bin2cell; it applies sequential high-quantile row- then column-wise normalization, which is asymmetric and can introduce edge effects/macro-stripes and distortions of large-scale total-count structure. RESULTS: We propose a statistical destriping approach that leverages nuclei segmentation from the co-registered H&E image. Assuming transcript abundance is constant within each nucleus, we model bin counts with a negative binomial distribution whose mean is a product of a nucleus-specific concentration and row- and column-specific stripe-factors reflecting lane-width variation. We fit all parameters in a generalized linear modeling framework with cross-validated regularization on stripe-factors and iterative dispersion estimation, and use the fitted parameters to correct the observed counts into a destriped image. On synthetic data with known ground truth, our method improves stripe-factor estimation accuracy and reduces error in corrected counts relative to bin2cell and bin2cell-derived baselines. Across four public VisiumHD slides, it consistently lowers striping intensity while substantially better preserving biological signal present in the large-scale global count structure and avoiding the artifacts introduced by other methods. AVAILABILITY AND IMPLEMENTATION: All source code and links to publicly available data used for this study are available at https://github.com/paolamalsot/destriping-GLM.

Artifacts↗
PubMed2026

Spatial mapping of RNA turnover kinetics in the mouse brain.

Gene regulation requires coordinated control of RNA synthesis and degradation, yet measuring RNA turnover across intact tissues remains challenging. Here we present spatial NT-seq, a method that combines transgenesis-free metabolic RNA labeling with in situ chemical recoding on spatial transcriptomics platforms to co-map newly synthesized and pre-existing RNAs. Applying spatial NT-seq to the mouse brain reveals pronounced regional heterogeneity in RNA turnover and identifies the dentate gyrus as a spatial hotspot marked by coordinated upregulation of basal RNA synthesis and decay. Moreover, spatial NT-seq uncovers rapid, brain region-specific transcriptional and post-transcriptional responses to electroconvulsive stimulation, a clinically relevant treatment for refractory depression. Finally, we leverage computational modeling to identify sequence features and post-transcriptional regulators that shape transcriptome-wide mRNA stability across spatial and cellular contexts in the mouse brain. Together, this integrated 'in vivo timescope' framework provides a spatially resolved view of RNA turnover kinetics and reveals the regulatory architecture of RNA stability in vivo.

Journal Article↗
PubMed2026

Emerging Principles in Spatial Functional Genomics.

Spatial transcriptomic and proteomic atlases have enabled mapping of gene programs within intact tissues, but these measurements remain largely descriptive and do not define the mechanisms controlling tissue biology. Pooled CRISPR screening provides scalable causal interrogation of gene function but remains largely confined to dissociated systems that lack spatial context. In vivo spatial functional genomics (SFG) bridges these approaches by integrating genetic perturbations with in situ transcriptomic and proteomic readouts to measure gene function within intact tissue ecosystems. By preserving spatial organization, SFG enables interpretation of perturbations through effects on cell-cell interactions, diffusible signals, multicellular niches, and tissue architecture. Here, we outline key design axes of SFG: perturbation strategy, barcoding strategy, and phenotypic readout. We discuss computational challenges, including spatial autocorrelation, neighborhood dependence, and context-aware null modeling, and highlight how SFG reveals non-cell-autonomous, architecture-dependent mechanisms of gene function, advancing toward predictive models of tissue organization and gene function.

Genomics↗
PubMed2026

A regulatory network underlying idiopathic pulmonary fibrosis.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease in which genetic susceptibility interacts with epithelial, immune, and mesenchymal remodeling. Although the chromosome 11p15.5 locus contains established IPF susceptibility signals near MUC5B and TOLLIP, the broader regulatory architecture of this region remains incompletely resolved. METHODS: We integrated IPF genome-wide association study summary statistics with methylation, expression, and protein quantitative trait loci using summary-data-based Mendelian randomization (SMR). SMR-prioritized candidates were evaluated in independent transcriptomic and methylation cohorts and further contextualized using microRNA, transcription-factor, protein-interaction, machine-learning, single-cell, and spatial transcriptomic analyses. Fibrosis-associated expression patterns were assessed in a bleomycin-induced pulmonary fibrosis rat model. RESULTS: The analyses recovered the established MUC5B and TOLLIP signals and prioritized BRSK2 as a comparatively underexplored candidate supported by eQTL-based SMR and independent molecular evidence. The BRSK2 pQTL association did not pass the HEIDI test and was therefore not interpreted as convergent protein-level genetic evidence. Network analyses linked BRSK2 to cell-cycle, metabolic-stress, and senescence-related programs, while cross-cohort machine learning prioritized FOXA2, CDC25B, and NFE2 as informative network features. Single-cell and spatial analyses localized BRSK2 preferentially to fibroblast and myofibroblast compartments and to regions with greater histological fibrosis severity. In fibrotic rat lungs, BRSK2 expression increased, whereas FOXA2 and CDC25B decreased at the transcript and protein levels. CONCLUSIONS: These findings refine the molecular landscape of the chromosome 11p15.5 IPF susceptibility locus and prioritize BRSK2 as a candidate component of an IPF-associated profibrotic fibroblast state. Its causal contribution, direct regulatory relationships, and therapeutic tractability require targeted mechanistic validation.

Idiopathic Pulmonary Fibrosis↗
PubMed2025

Unveiling the mechanism of micro-and-nano plastic phytotoxicity on terrestrial plants: A comprehensive review of omics approaches.

Micro-and-nano plastics (MNPs) are pervasive in terrestrial ecosystems and represent an increasing threat to plant health; however, the mechanisms underlying their phytotoxicity remain inadequately understood. MNPs can infiltrate plants through roots or leaves, causing a range of toxic effects, including inhibiting water and nutrient uptake, reducing seed germination rates, and impeding photosynthesis, resulting in oxidative damage within the plant system. The effects of MNPs are complex and influenced by various factors including size, shape, functional groups, and concentration. Recent advancements in omics technologies such as proteomics, metabolomics, transcriptomics, and microbiomics, coupled with emerging technologies like 4D omics, phenomics, spatial transcriptomics, and single-cell omics, offer unprecedented insight into the physiological, molecular, and cellular responses of terrestrial plants to MNPs exposure. This literature review synthesizes current findings regarding MNPs-induced phytotoxicity, emphasizing alterations in gene expression, protein synthesis, metabolic pathways, and physiological disruptions as revealed through omics analyses. We summarize how MNPs interact with plant cellular structures, disrupt metabolic processes, and induce oxidative stress, ultimately affecting plant growth and productivity. Furthermore, we have identified critical knowledge gaps and proposed future research directions, highlighting the necessity for integrative omics studies to elucidate the complex pathways of MNPs toxicity in terrestrial plants. In conclusion, this review underscores the potential of omics approaches to elucidate the mechanisms of MNPs-phytotoxicity and to develop strategies for mitigating the environmental impact of MNPs on plant health.

Plants↗
PubMed2025

Neoadjuvant Immunotherapy Promotes the Formation of Mature Tertiary Lymphoid Structures in a Remodeled Pancreatic Tumor Microenvironment.

Pancreatic ductal adenocarcinoma (PDAC) is a rapidly progressing cancer that responds poorly to immunotherapies. Intratumoral tertiary lymphoid structures (TLS) have been associated with rare long-term PDAC survivors, but the role of TLS in PDAC and their spatial relationships within the context of the broader tumor microenvironment remain unknown. In this study, we report the generation of a spatial multiomic atlas of PDAC tumors and tumor-adjacent lymph nodes from patients treated with combination neoadjuvant immunotherapies. Using machine learning-enabled hematoxylin and eosin image classification models, imaging mass cytometry, and unsupervised gene expression matrix factorization methods for spatial transcriptomics, we characterized cellular states within and adjacent to TLS spanning distinct spatial niches and pathologic responses. Unsupervised learning identified TLS-specific spatial gene expression signatures that are significantly associated with improved survival in patients with PDAC. We identified spatial features of pathologic immune responses, including intratumoral TLS-associated B-cell maturation colocalizing with IgG dissemination and extracellular matrix remodeling. Our findings offer insights into the cellular and molecular landscape of TLS in PDACs during immunotherapy treatment.

Humans↗
PubMed2026

Human and mouse adrenal glands are characterized by species-specific steroidogenic states and tissue turnover.

The adult adrenal cortex undergoes constant renewal, yet underlying human-specific mechanisms remain poorly understood. Here we generated single-cell and spatial transcriptomic atlases of adult human and mouse adrenal glands, leveraging single-cell-resolution spatial data and a rare clonal mosaic case for lineage inference. In humans, we identified age-associated zona glomerulosa (ZG) cell states with direct cortisol synthesis capacity and sex-specific differences in inferred cholesterol balance. Cross-species comparison revealed conserved aldosterone-producing ZG but notable divergence in zona fasciculata markers, absence of zona reticularis homologs in mice and differential SHH-WNT4 signaling in proliferating cells. We uncovered human WT1- capsule-to-ZG transition and vascular smooth muscle cell-to-steroidogenic transitions supported by mosaic lineage evidence. We revealed dispersed proliferating cortical SF1+EZH2+ cells throughout the human cortex in contrast with ZG restriction in mice. Taken together, our data expand the centripetal renewal model and establish a comparative framework for human adrenocortical biology.

Animals↗
PubMed2026

FZD5 drives macrophage-mediated immunomodulation and predicts prognosis in glioma: evidence from single-cell sequencing.

BACKGROUND: Gliomas are highly malignant brain tumors characterized by an immunosuppressive microenvironment, which limits therapeutic efficacy and contributes to poor clinical outcomes. The WNT/β-catenin signaling pathway is critically involved in tumor progression, and FZD5, a key receptor within this pathway, may participate in immune regulation. However, its specific role and underlying mechanisms in glioma remain unclear. METHODS: RNA-seq and microarray datasets from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA), together with single-cell RNA sequencing (scRNA-seq) datasets from GEO, were comprehensively analyzed. The Seurat package was used to identify macrophage-related clusters and mitophagy-associated pathways. Cox and LASSO regression analyses, along with a prognostic nomogram, were applied to evaluate the prognostic significance of FZD5. Immune infiltration, functional enrichment, and immunotherapy response analyses were conducted, followed by validation using spatial transcriptomics, immunohistochemistry, and in vitro assays. RESULTS: In bulk glioma transcriptomes, FZD5 emerged as an independent predictor of poor prognosis. Crucially, single-cell and spatial analyses revealed that the biologically significant FZD5 signal originated predominantly within tumor-associated macrophages (TAMs), where it colocalized with the M2 marker CD163. Consistently, elevated FZD5 levels correlated with increased myeloid infiltration and an immunosuppressive tumor microenvironment. Functionally, macrophage-expressed FZD5 was associated with mitophagy-related programs and promoted an M2-skewed phenotype, thereby enhancing glioma cell proliferation, migration, and invasion via macrophage-glioma crosstalk. CONCLUSION: FZD5 is a TAM-enriched marker in glioma tissues and a potential regulator of macrophage-associated immunosuppressive programs, supporting its utility as a prognostic biomarker and a candidate target for microenvironment-oriented interventions in glioma.

Humans↗
PubMed2026

Cell-type specific activation of the cGAS-STING pathway in tumor immunotherapy: mechanisms and therapeutic implications.

BACKGROUND: The cyclic GMP–AMP synthase–stimulator of interferon genes (cGAS–STING) pathway acts as a pivotal innate immune sensor that detects cytosolic DNA and links genomic instability to antitumor immune activation. Therapeutic activation of this pathway has garnered substantial interest as a strategy to enhance cancer immunotherapy by promoting dendritic cell maturation, augmenting antigen presentation, and facilitating cytotoxic lymphocyte infiltration. However, the functional outcomes of cGAS–STING signaling are highly context dependent and influenced by both cell type and tumor microenvironmental (TME) conditions. MAIN BODY: Recent advances in single-cell and spatial transcriptomic profiling have revealed profound heterogeneity in cGAS–STING activation across distinct cellular and regional compartments within tumors. Acute and spatially restricted activation of the pathway can elicit potent antitumor immune responses, whereas chronic or dysregulated signaling may promote immune tolerance and tumor progression. Moreover, metabolic stress, epigenetic silencing, and microenvironmental immunosuppressive factors such as TGF-β and IL-10 can further modulate STING activity, leading to resistance to immunotherapy. Current translational efforts focus on next-generation STING agonists, nanoparticle-based delivery systems, and rational combination strategies with immune checkpoint blockade and metabolic modulators to overcome tumor-intrinsic resistance and minimize systemic toxicity. CONCLUSIONS: Understanding the cell-type-specific and spatial dynamics of cGAS–STING signaling is crucial for the rational design of precision immunotherapies. Future research should emphasize context-dependent modulation of STING activity to maximize therapeutic benefit while limiting adverse effects. Integrating multi-omics technologies and spatially guided drug delivery may ultimately enable personalized modulation of the cGAS–STING axis, transforming it into a clinically effective and safe strategy for cancer immunotherapy.

Humans↗
PubMed2025

Identification of marginal zone B cells in head and neck cancer with immunomodulatory characteristics.

INTRODUCTION: Recently we observed high numbers of marginal zone B cells (MZBs) within murine head and neck squamous cell carcinoma (HNSCC) with immunosuppressive potential. To date, MZBs have not been linked to tumor development or tumor prevention. OBJECTIVES: Based on our previous findings the present study aimed to validate the presence of MZB in HNSCC and to investigate their possible implications in tumorigenesis and prognosis. METHODS: Flow cytometry was used to uncover MZB within tumors and blood of HNSCC patients. A single-cell RNA sequencing cohort of 118 HNSCC patients across different disease stages and 6 healthy donors (HDs) was compiled. Comparative transcriptomic profiling of B lymphocytes between HNSCC and HDs were performed. Downstream analysis, such as pathway enrichment, cell-cell communication, pseudotime trajectory inference, survival correlation, and spatial transcriptomics were applied. RESULTS: Two MZB subsets were revealed in tissues and blood of HNSCC patients and HDs. The tumor-associated MZBs were featured with hypoxia stress and viral-related hallmark genes. MZB-2, characterized by elevated expression of activation markers and immune-regulatory genes, displayed strong interactions with CD4+ T cells and antigen-presenting cells. These interactions were supported by costimulatory signals in HDs but were absent in HNSCC patients. Co-localization of MZB-2, germinal center B cell (GCB), and CD4+ follicular helper T cell (Tfh) was detected in HNSCC, suggesting the presence of an intratumoral MZB-Tfh-GCB axis. Clinically, MZB-2 abundance was associated with favorable prognosis in early-stage HNSCC, but not in advanced disease. Immunosuppressive gene signatures were not exclusive to MZBs, indicating that they do not represent a purely regulatory B cell phenotype. CONCLUSION: Our findings demonstrate an immunomodulatory role of MZBs in tumor immunity, balancing antigen presentation, cytokine signaling, and immune suppression. The association of MZB-2 with improved prognosis in early-stage HNSCC highlights its potential as a beneficial regulator of antitumor immunity during early tumor progression.

Humans↗
PubMed2024

Digital pathology and spatial omics in steatohepatitis: Clinical applications and discovery potentials.

Steatohepatitis with diverse etiologies is the most common histological manifestation in patients with liver disease. However, there are currently no specific histopathological features pathognomonic for metabolic dysfunction-associated steatotic liver disease, alcohol-associated liver disease, or metabolic dysfunction-associated steatotic liver disease with increased alcohol intake. Digitizing traditional pathology slides has created an emerging field of digital pathology, allowing for easier access, storage, sharing, and analysis of whole-slide images. Artificial intelligence (AI) algorithms have been developed for whole-slide images to enhance the accuracy and speed of the histological interpretation of steatohepatitis and are currently employed in biomarker development. Spatial biology is a novel field that enables investigators to map gene and protein expression within a specific region of interest on liver histological sections, examine disease heterogeneity within tissues, and understand the relationship between molecular changes and distinct tissue morphology. Here, we review the utility of digital pathology (using linear and nonlinear microscopy) augmented with AI analysis to improve the accuracy of histological interpretation. We will also discuss the spatial omics landscape with special emphasis on the strengths and limitations of established spatial transcriptomics and proteomics technologies and their application in steatohepatitis. We then highlight the power of multimodal integration of digital pathology augmented by machine learning (ML)algorithms with spatial biology. The review concludes with a discussion of the current gaps in knowledge, the limitations and premises of these tools and technologies, and the areas of future research.

Humans↗
PubMed2026

A Multi-omics Regulated Cell Death Framework Defines Immune Phenotypes and Guides Precision Therapy in Colorectal Cancer.

Colorectal cancer (CRC) is molecularly and immunologically heterogeneous, contributing to variable treatment response. Because regulated cell death (RCD) intersects with tumor metabolism, immune regulation, and therapeutic susceptibility, we built an RCD-centered framework for CRC stratification. Multi-cohort transcriptomic data were used to infer RCD subtypes with non-negative matrix factorization (NMF) and non-negative least squares (NNLS). Genomic, bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomic datasets were integrated to characterize subtype-associated biology. Machine-learning models were developed for immunotherapy response and survival-risk estimation. Candidate compounds were screened by GDSC2-based drug-sensitivity modeling and molecular docking, and FSTL3 was functionally assessed in vitro. The framework separated CRC samples into two RCD-related phenotypes resembling immune-hot and immune-cold states. RCD1 showed immune activation and higher mutational burden, whereas RCD2 showed immune-suppressed features, intratumoral heterogeneity, and aggressive biology. RCD-associated signatures showed potential for predicting immunotherapy response and survival risk. Dasatinib was prioritized for immune-cold, high-risk tumors, with preliminary evidence supporting its activity in CRC cells, while functional assays suggested a role for FSTL3 in growth, invasion, epithelial-mesenchymal transition, and apoptosis regulation. These findings suggest that RCD-based multi-omics analysis may refine CRC stratification and help generate therapeutic hypotheses.

Colorectal cancer↗
PubMed2026

Extracellular vesicle miR-93-5p cargo regulates glomerular endothelial cell damage in Alport syndrome.

Modulation of miRNA expression in glomerular cells is associated with renal disease. Here, we investigated the role of miR-93-5p in mitigating glomerular damage in Alport syndrome and whether the disease-modifying activity of extracellular vesicles from human amniotic fluid stem cells (hAFSC-EVs) is mediated by their miR-93-5p cargo. We identified downregulation of miR-93-5p specifically in glomerular endothelial cells in Alport syndrome along disease progression. Silencing of miR-93-5p in hAFSC-EVs changed the transcriptomic and proteomic profile, regulating EV disease-modifying activity. Compared with naive hAFSC-EVs, silenced hAFSC-EVs did not rescue glomerular endothelial function in vitro and did not restore kidney function in vivo. We established that hAFSC-EVs regulate VEGFR1 and VEGFR2 signaling by miR-93-5p cargo transfer, highlighting that miR-93-5p can restore glomerular endothelial cell biology. Spatial transcriptomics analysis of hAFSC-EV-injected kidneys showed that these EVs can reverse pathways altered during disease progression by stimulating proregenerative processes, specifically in the glomerulus, by regulating miR-93-5p targets. Alteration of glomerular endothelial cell transcriptomics and miR-93-5p targets was also confirmed in biopsies of patients with Alport syndrome using spatial molecular imaging. We demonstrated the critical role of miR-93-5p in glomerular endothelial cells and the capability of hAFSC-EVs to regulate miR-93-5p and its targets in Alport syndrome.

Humans↗
PubMed2025

Drought recovery in plants triggers a cell-state-specific immune activation.

All organisms experience stress as an inevitable part of life, from single-celled microorganisms to complex multicellular beings. The ability to recover from stress is a fundamental trait that determines the overall resilience of an organism, yet stress recovery is understudied. To investigate how plants recover from drought, we examine a fine-scale time series of RNA sequencing starting 15 min after rehydration following moderate drought. We reveal that drought recovery is a rapid process involving the activation of thousands of recovery-specific genes. To capture these rapid recovery responses in different Arabidopsis thaliana (A. thaliana) leaf cell types, we perform a single-nucleus transcriptome analysis at the onset of drought recovery, identifying a cell type-specific transcriptional state developing independently across cell types. To further validate the cell-type specific transcriptional changes observed during drought recovery, we employ spatial transcriptomics using multiplexed error-robust fluorescence in situ hybridization (MERFISH), revealing anatomical localization of recovery-induced gene expression programs across Arabidopsis leaf tissues. Furthermore, we reveal a recovery-induced activation of the immune system that occurs autonomously, and which enhances pathogen resistance in vivo in A. thaliana, wild tomato (Solanum pennellii) and domesticated tomato (Solanum lycopersicum cv. M82). Since rehydration promotes microbial proliferation and thereby increases the risk of infection, the activation of drought recovery-induced immunity may be crucial for plant survival in natural environments. These findings indicate that drought recovery coincides with a preventive defense response, unraveling the complex regulatory mechanisms that facilitate stress recovery in different plant cell types.

Arabidopsis↗
PubMed2026

Follicular Lymphoma Transformation is Characterized by Cytokine-associated Remodeling of Stromal and Macrophage Compartments.

Across cancer, one of the most frequent examples of histologic transformation is the evolution of follicular lymphoma (FL) to an aggressive large cell lymphoma. Despite recent progress, understanding of the molecular and cellular underpinnings of transformation remains incomplete. Here, we dissect the interplay of tumor and microenvironment cell populations across transformation through a multimodal investigation of 95 FL and transformed FL (tFL) samples, including single-cell and bulk RNA-sequencing alongside spatial transcriptomics and proteomics, and validate findings across independent FL-tFL pairs. Upon transformation, fibroblasts and GPNMB+ macrophages increase while lymph-node organizing follicular dendritic and CCL21+ fibroblastic reticular cells were lost, resulting in an altered spatial distribution of cytokines that impacts T cell infiltration and macrophage differentiation and function. Secreted stromal and macrophage signals were further evident by non-invasive plasma proteomics. Taken together, our data reveal expansion of macrophages and fibroblasts as key features of transformation with potential diagnostic and therapeutic implications.

Journal Article↗
PubMed2026

scSurv: a deep generative model for single-cell survival analysis.

MOTIVATION: Single-cell omics analysis has unveiled the heterogeneity of various cell types within tumors. However, no methodology currently reveals how this heterogeneity influences cancer patient survival at single-cell resolution. Here, we introduce scSurv, combining a Cox proportional hazards model with a deep generative model of single-cell transcriptome, to estimate individual cellular contributions to clinical outcomes. RESULTS: The accuracy of scSurv was validated using both simulated and real datasets. This method identifies cells associated with favorable or adverse prognoses and extracts genes correlated with their contribution levels. In melanoma, scSurv reproduces known prognostic macrophage classifications and facilitates hazard mapping through spatial transcriptomics in renal cell carcinoma. We also identified genes consistently associated with prognosis across multiple cancers and demonstrated the applicability of this method to infectious diseases. scSurv is a novel framework for quantifying the heterogeneity of individual cellular effects on clinical outcomes. AVAILABILITY: The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054).

Humans↗