Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics

scPair: Boosting single cell multimodal analysis by leveraging implicit feature selection and single cell atlases

Multimodal single-cell assays profile multiple sets of features in the same cells and are widely used for identifying and mapping cell states between chromatin and mRNA and linking regulatory elements to target genes. However, the high dimensionality of input features and shallow sequencing depth compared to unimodal assays pose challenges in data analysis. Here we present scPair, a multimodal single-cell data framework that overcomes these challenges by employing an implicit feature selection approach. scPair uses dual encoder-decoder structures trained on paired data to align cell states across modalities and predict features from one modality to another. We demonstrate that scPair outperforms existing methods in accuracy and execution time, and facilitates downstream tasks such as trajectory inference. We further show scPair can augment smaller multimodal datasets with larger unimodal atlases to increase statistical power to identify groups of transcription factors active during different stages of neural differentiation.

A multimodal zebrafish developmental atlas reveals the state-transition dynamics of late-vertebrate pluripotent axial progenitors

Elucidating organismal developmental processes requires a comprehensive understanding of cellular lineages in the spatial, temporal, and molecular domains. In this study, we introduce Zebrahub, a dynamic atlas of zebrafish embryonic development that integrates single-cell sequencing time course data with lineage reconstructions facilitated by light-sheet microscopy. This atlas offers high-resolution and in-depth molecular insights into zebrafish development, achieved through the sequencing of individual embryos across ten developmental stages, complemented by reconstructions of cellular trajectories. Zebrahub also incorporates an interactive tool to navigate the complex cellular flows and lineages derived from light-sheet microscopy data, enabling in silico fate-mapping experiments. To demonstrate the versatility of our multimodal resource, we utilize Zebrahub to provide fresh insights into the pluripotency of neuro-mesodermal progenitors (NMPs) and the origins of a joint kidney-hemangioblast progenitor population.

CRISPR screens unveil nutrient-dependent lysosomal and mitochondrial nodes impacting intestinal tissue-resident memory CD8+ T cell formation

Nutrient availability and organelle biology direct tissue homeostasis and cell fate, but how these processes orchestrate tissue immunity remains poorly defined. Here, using in vivo CRISPR-Cas9 screens, we uncovered organelle signaling and metabolic processes shaping CD8+ tissue-resident memory T (TRM) cell development. TRM cells depended on mitochondrial translation and respiration. Conversely, three nutrient-dependent lysosomal signaling nodes-Flcn, Ragulator, and Rag GTPases-inhibited intestinal TRM cell formation. Depleting these molecules or amino acids activated the transcription factor Tfeb, thereby linking nutrient stress to TRM programming. Further, Flcn deficiency promoted protective TRM cell responses in the small intestine. Mechanistically, the Flcn-Tfeb axis restrained retinoic acid-induced CCR9 expression for migration and transforming growth factor β (TGF-β)-mediated programming for lineage differentiation. Genetic interaction screening revealed that the mitochondrial protein Mrpl52 enabled early TRM cell formation, while Acss1 controlled TRM cell development under Flcn deficiency-associated lysosomal dysregulation. Thus, the interplay between nutrients, organelle signaling, and metabolic adaptation dictates tissue immunity.

Multi-modal analysis of human hepatic stellate cells identifies novel therapeutic targets for metabolic dysfunction-associated steatotic liver disease

BACKGROUND & AIMS

Metabolic dysfunction-associated steatotic liver disease ranges from metabolic dysfunction-associated steatotic liver (MASL) to metabolic dysfunction-associated steatohepatitis (MASH) with fibrosis. Transdifferentiation of hepatic stellate cells (HSCs) into fibrogenic myofibroblasts plays a critical role in the pathogenesis of MASH liver fibrosis. We compared transcriptome and chromatin accessibility of human HSCs from NORMAL, MASL, and MASH livers at single-cell resolution. We aimed to identify genes that are upregulated in activated HSCs and to determine which of these genes are key in the pathogenesis of MASH fibrosis.

METHODS

Eighteen human livers were profiled using single-nucleus (sn)RNA-seq and snATAC-seq. High priority targets were identified, then tested in 2D human HSC cultures, 3D human liver spheroids, and HSC-specific gene knockout mice.

RESULTS

MASH-enriched activated HSC subclusters are the major source of extracellular matrix proteins. We identified a set of concurrently upregulated and more accessible core genes (GAS7, SPON1, SERPINE1, LTBP2, KLF9, EFEMP1) that drive activation of HSCs. Expression of these genes was regulated via crosstalk between lineage-specific (JUNB/AP1), cluster-specific (RUNX1/2) and signal-specific (FOXA1/2) transcription factors. The pathological relevance of the selected targets, such as SERPINE1 (PAI-1), was demonstrated using dsiRNA-based HSC-specific gene knockdown or pharmacological inhibition of PAI-1 in 3D human MASH liver spheroids, and HSC-specific Serpine1 knockout mice.

CONCLUSION

This study identified novel gene targets and regulatory mechanisms underlying activation of MASH fibrogenic HSCs and demonstrated that genetic or pharmacological inhibition of select genes suppressed liver fibrosis.

IMPACT AND IMPLICATIONS

Herein, we present the results of a multi-modal sequencing analysis of human hepatic stellate cells (HSCs) from NORMAL, MASL (metabolic dysfunction-associated steatotic liver), and metabolic dysfunction-associated steatohepatitis (MASH) livers. We identified additional subclusters that were not detected by previous studies and characterized the mechanism by which HSCs are activated in MASH livers, including the transcriptional machinery that induces the transdifferentiation of HSCs into myofibroblasts. For the first time, we described the pathogenic role of activated HSC-derived PAI-1 (a product of the SERPINE1 gene) in the development of MASH liver fibrosis. Targeting the RUNX1/2-SERPINE1 axis could be a novel strategy for the treatment of liver fibrosis in patients.

Alveolar regeneration by airway secretory-cell-derived p63+ progenitors

Lung injury activates epithelial stem or progenitor cells for alveolar repair and regeneration. Unraveling the origin and fate of injury-induced progenitors is crucial for elucidating lung repair mechanisms. Here, we report that p63-expressing progenitors emerge upon bleomycin-induced mouse lung injury. Single-cell RNA sequencing and clonal analysis reveal that these p63+ progenitors proliferate rapidly and differentiate into alveolar type 1 and type 2 cells through different trajectories. Dual recombinase-mediated sequential genetic-lineage tracing demonstrates that p63+ progenitors originate from airway secretory cells and subsequently generate alveolar cells. Functionally, p63 activation is essential for efficient alveolar regeneration from secretory cells post injury. Our study identifies secretory-cell-derived p63+ progenitors as contributors to alveolar repair, suggesting a potential therapeutic avenue for lung regeneration following injury.

GraphPCA: a fast and interpretable dimension reduction algorithm for spatial transcriptomics data

The rapid advancement of spatial transcriptomics technologies has revolutionized our understanding of cell heterogeneity and intricate spatial structures within tissues and organs. However, the high dimensionality and noise in spatial transcriptomic data present significant challenges for downstream data analyses. Here, we develop GraphPCA, an interpretable and quasi-linear dimension reduction algorithm that leverages the strengths of graphical regularization and principal component analysis. Comprehensive evaluations on simulated and multi-resolution spatial transcriptomic datasets generated from various platforms demonstrate the capacity of GraphPCA to enhance downstream analysis tasks including spatial domain detection, denoising, and trajectory inference compared to other state-of-the-art methods.

Joint representation and visualization of derailed cell states with Decipher

Biological insights often depend on comparing conditions such as disease and health, yet we lack effective computational tools for integrating single-cell genomics data across conditions or characterizing transitions from normal to deviant cell states. Here, we present Decipher, a deep generative model that characterizes derailed cell-state trajectories. Decipher jointly models and visualizes gene expression and cell state from normal and perturbed single-cell RNA-seq data, revealing shared and disrupted dynamics. We demonstrate its superior performance across diverse contexts, including in pancreatitis with oncogene mutation, acute myeloid leukemia, and gastric cancer.

Approaches for Benchmarking Single-Cell Gene Regulatory Network Methods

Gene regulatory networks are powerful tools for modeling genetic interactions that control the expression of genes driving cell differentiation, and single-cell sequencing offers a unique opportunity to build these networks with high-resolution genomic data. There are many proposed computational methods to build these networks using single-cell data, and different approaches are used to benchmark these methods. However, a comprehensive discussion specifically focusing on benchmarking approaches is missing. In this article, we lay the GRN terminology, present an overview of common gold-standard studies and data sets, and define the performance metrics for benchmarking network construction methodologies. We also point out the advantages and limitations of different benchmarking approaches, suggest alternative ground truth data sets that can be used for benchmarking, and specify additional considerations in this context.

Spatial Transcriptomics of IPMN Reveals Divergent Indolent and Malignant Lineages

Purpose

Intraductal papillary mucinous neoplasms (IPMN) occur in 5-10% of the population, but only a small minority progress to pancreatic ductal adenocarcinoma (PDAC). The lack of accurate predictors of high-risk disease leads both to unnecessary operations for indolent neoplasms as well as missed diagnoses of PDAC. Digital spatial RNA profiling (DSP-RNA) provides an opportunity to define and associate transcriptomic states with cancer risk.

Experimental Design

Whole-transcriptome DSP-RNA profiling was performed on 10 IPMN specimens encompassing the spectrum of dysplastic changes from normal duct to cancer. Ductal epithelial regions within each tissue were annotated as normal duct (NL), low-grade dysplasia (LGD), high-grade dysplasia (HGD), or invasive carcinoma (INV). Gene expression count data was generated by Illumina sequencing and analyzed with R/Bioconductor.

Results

Dimension reduction analysis exposed three clusters reflecting IPMN transcriptomic states denoted "normal-like" ( cNL ), "low-risk" ( cLR ) and "high-risk" ( cHR ). In addition to specific marker genes, the three states exhibited significant enrichment for the exocrine, classical, and basal-like programs in PDAC. Specifically, exocrine function diminished in cHR , classical activation distinguished neoplasia from cNL , and basal-like genes were specifically upregulated in cHR . Intriguingly, markers of cHR were detected in NL and LGD regions from specimens with PDAC but not low-grade IPMN.

Conclusions

DSP-RNA of IPMN revealed low-risk (indolent) and high-risk (malignant) expression programs that correlated with the activity of exocrine and basal-like PDAC signatures, respectively, and distinguished pathologically low-grade from malignant specimens. These findings contextualize IPMN pathogenesis and have the potential to transform existing risk stratification models.

Statement of translational relevance

Current consensus guidelines for management of intraductal papillary mucinous neoplasms (IPMN) of the pancreas utilize clinical and radiographic criteria for risk stratification. Unfortunately, the estimated positive predictive value of these criteria for IPMN-associated pancreatic ductal adenocarcinoma (PDAC) is under 50%, indicating that over half of pancreatectomies are performed for benign disease. Moreover, nearly 15% of patients who were deemed "low risk" by the same criteria harbored PDAC. Surgical resection of IPMN has maximal benefit when performed prior to the development of PDAC, as evidence of carcinoma has been associated with a high rate of recurrence and poor overall survival. Thus, the development of molecular diagnostics that improve the accuracy of IPMN risk classification would have immediate relevance for patient care, both in terms of better selecting patients for potentially curative operations, as well as sparing patients with low-risk lesions from invasive procedures.

Effects of intergenerational transmission of small intestinal bacteria cultured from stunted Bangladeshi children with enteropathy

Environmental enteric dysfunction (EED), a small intestinal disorder found at a high prevalence in stunted children, is associated with gut mucosal barrier disruption and decreased absorptive capacity due to reduced intact small intestinal villi1-4. To test the hypothesis that intergenerational transmission of a perturbed small intestinal microbiota contributes to undernutrition by inducing EED5, we characterized two consortia of bacterial strains cultured from duodenal aspirates from stunted Bangladeshi children with EED - one of which induced local and systemic inflammation in gnotobiotic female mice. Offspring of dams that received this inflammatory consortium exhibited immunologic changes along their gut that phenocopied features of EED in children. Single nucleus plus bulk RNA-sequencing revealed alterations in inter-cellular signaling pathways related to intestinal epithelial cell renewal, barrier integrity and immune function while analyses of cerebral cortex disclosed alterations in glial- and endothelial-neuronal signaling pathways that regulate neural growth/axonal guidance, angiogenesis and inflammation. Analysis of ultrasonic vocalization calls in gnotobiotic P5-P9 pups indicated increased arousal and perturbed neurodevelopment in the offspring of dams harboring the inflammation-inducing consortium. Cohousing experiments and follow-up screening of candidate disease-promoting bacterial isolates identified a strain typically found in the oral microbiota (Campylobacter concisus) as a contributor to enteropathy. Given that fetal growth was also impaired in the dams with the consortium that induced enteropathy, this preclinical model allows the effects of the human small intestinal microbiota on both pre- and postnatal development to be ascertained, setting the stage for identification of small intestinal microbiota-targeted therapeutics for (intergenerational) undernutrition.

Spatial transcriptomics reveals organized and distinct immune activation in cutaneous granulomatous disorders

BACKGROUND

Noninfectious (inflammatory) cutaneous granulomatous disorders include cutaneous sarcoidosis (CS), granuloma annulare (GA), necrobiosis lipoidica (NL), and necrobiotic xanthogranuloma (NXG). These disorders share macrophage-predominant inflammation histologically, but the inflammatory architecture and the pattern of extracellular matrix alteration varies. The underlying molecular explanations for these differences remain unclear.

OBJECTIVE

We sought to understand spatial gene expression characteristics in these disorders.

METHODS

We performed spatial transcriptomics in cases of CS, GA, NL, and NXG to compare patterns of immune activation and other molecular features in a spatially resolved fashion.

RESULTS

CS is characterized by a polarized, spatially organized type 1-predominant response with classical macrophage activation. GA is characterized by a mixed but spatially organized pattern of type 1 and type 2 polarization with both classical and alternative macrophage activation. NL showed concomitant activation of type 1, type 2, and type 3 immunity with a mixed pattern of macrophage activation. Activation of type 1 immunity was shared among, CS, GA, and NL and included upregulation of IL-32. NXG showed upregulation of CXCR4-CXCL12/14 chemokine signaling and exaggerated alternative macrophage polarization. Histologic alteration of extracellular matrix correlated with hypoxia and glycolysis programs and type 2 immune activation.

CONCLUSIONS

Inflammatory cutaneous granulomatous disorders show distinct and spatially organized immune activation that correlate with hallmark histologic changes.

WENDY: Covariance dynamics based gene regulatory network inference

Determining gene regulatory network (GRN) structure is a central problem in biology, with a variety of inference methods available for different types of data. For a widely prevalent and challenging use case, namely single-cell gene expression data measured after intervention at multiple time points with unknown joint distributions, there is only one known specifically developed method, which does not fully utilize the rich information contained in this data type. We develop an inference method for the GRN in this case, netWork infErence by covariaNce DYnamics, dubbed WENDY. The core idea of WENDY is to model the dynamics of the covariance matrix, and solve this dynamics as an optimization problem to determine the regulatory relationships. To evaluate its effectiveness, we compare WENDY with other inference methods using synthetic data and experimental data. Our results demonstrate that WENDY performs well across different data sets.

scGRN-Entropy: Inferring cell differentiation trajectories using single-cell data and gene regulation network-based transfer entropy

Research on cell differentiation facilitates a deeper understanding of the fundamental processes of life, elucidates the intrinsic mechanisms underlying diseases such as cancer, and advances the development of therapeutics and precision medicine. Existing methods for inferring cell differentiation trajectories from single-cell RNA sequencing (scRNA-seq) data primarily rely on static gene expression data to measure distances between cells and subsequently infer pseudotime trajectories. In this work, we introduce a novel method, scGRN-Entropy, for inferring cell differentiation trajectories and pseudotime from scRNA-seq data. Unlike existing approaches, scGRN-Entropy improves inference accuracy by incorporating dynamic changes in gene regulatory networks (GRN). In scGRN-Entropy, an undirected graph representing state transitions between cells is constructed by integrating both static relationships in gene expression space and dynamic relationships in the GRN space. The edges of the undirected graph are then refined using pseudotime inferred based on cell entropy in the GRN space. Finally, the Minimum Spanning Tree (MST) algorithm is applied to derive the cell differentiation trajectory. We validate the accuracy of scGRN-Entropy on eight different real scRNA-seq datasets, demonstrating its superior performance in inferring cell differentiation trajectories through comparative analysis with existing state-of-the-art methods.

ITGA5+ synovial fibroblasts orchestrate proinflammatory niche formation by remodelling the local immune microenvironment in rheumatoid arthritis

OBJECTIVES

To investigate the phenotypic heterogeneity of tissue-resident synovial fibroblasts and their role in inflammatory response in rheumatoid arthritis (RA).

METHODS

We used single-cell and spatial transcriptomics to profile synovial cells and spatial gene expressions of synovial tissues to identify phenotypic changes in patients with osteoarthritis, RA in sustained remission and active state. Immunohistology, multiplex immunofluorescence and flow cytometry were used to identify synovial fibroblasts subsets. Deconvolution methods further validated our findings in two cohorts (PEAC and R4RA) with treatment response. Cell coculture was used to access the potential cell-cell interactions. Adoptive transfer of synovial cells in collagen-induced arthritis (CIA) mice and bulk RNA sequencing of synovial joints further validate the cellular functions.

RESULTS

We identified a novel tissue-remodelling CD45-CD31-PDPN+ITGA5+ synovial fibroblast population with unique transcriptome of POSTN, COL3A1, CCL5 and TGFB1, and enriched in immunoregulatory pathways. This subset was upregulated in active and lympho-myeloid type of RA, associated with an increased risk of multidrug resistance. Transforming growth factor (TGF)-β1 might participate in the differentiation of this subset. Moreover, ITGA5+ synovial fibroblasts might occur in early stage of inflammation and induce the differentiation of CXCL13hiPD-1hi peripheral helper T cells (TPHs) from naïve CD4+ T cells, by secreting TGF-β1. Intra-articular injection of ITGA5+ synovial fibroblasts exacerbates RA development and upregulates TPHs in CIA mice.

CONCLUSIONS

We demonstrate that ITGA5+ synovial fibroblasts might regulate the RA progression by inducing the differentiation of CXCL13hiPD-1hi TPHs and remodelling the proinflammatory microenvironments. Therapeutic modulation of this subpopulation could therefore be a potential treatment strategy for RA.

Astrocyte allocation during brain development is controlled by Tcf4-mediated fate restriction

Astrocytes in the brain exhibit regional heterogeneity contributing to regional circuits involved in higher-order brain functions, yet the mechanisms controlling their distribution remain unclear. Here, we show that the precise allocation of astrocytes to specific brain regions during development is achieved through transcription factor 4 (Tcf4)-mediated fate restriction based on their embryonic origin. Loss of Tcf4 in ventral telencephalic neural progenitor cells alters the fate of oligodendrocyte precursor cells to transient intermediate astrocyte precursor cells, resulting in mislocalized astrocytes in the dorsal neocortex. These ectopic astrocytes engage with neocortical neurons and acquire features reminiscent of dorsal neocortical astrocytes. Furthermore, Tcf4 functions as a suppressor of astrocyte fate during the differentiation of oligodendrocyte precursor cells derived from the ventral telencephalon, thereby restricting the fate to the oligodendrocyte lineage in the dorsal neocortex. Together, our findings highlight a previously unappreciated role for Tcf4 in regulating astrocyte allocation, offering additional insights into the mechanisms underlying neurodevelopmental disorders linked to Tcf4 mutations.

A spatial human thymus cell atlas mapped to a continuous tissue axis

T cells develop from circulating precursor cells, which enter the thymus and migrate through specialized subcompartments that support their maturation and selection1. In humans, this process starts in early fetal development and is highly active until thymic involution in adolescence. To map the microanatomical underpinnings of this process in pre- and early postnatal stages, we established a quantitative morphological framework for the thymus-the Cortico-Medullary Axis-and used it to perform a spatially resolved analysis. Here, by applying this framework to a curated multimodal single-cell atlas, spatial transcriptomics and high-resolution multiplex imaging data, we demonstrate establishment of the lobular cytokine network, canonical thymocyte trajectories and thymic epithelial cell distributions by the beginning of the the second trimester of fetal development. We pinpoint tissue niches of thymic epithelial cell progenitors and distinct subtypes associated with Hassall's corpuscles and identify divergence in the timing of medullary entry between CD4 and CD8 T cell lineages. These findings provide a basis for a detailed understanding of T lymphocyte development and are complemented with a holistic toolkit for cross-platform imaging data analysis, annotation and OrganAxis construction (TissueTag), which can be applied to any tissue.

Neuropeptide signalling orchestrates T cell differentiation

The balance between T helper type 1 (TH1) cells and other TH cells is critical for antiviral and anti-tumour responses1-3, but how this balance is achieved remains poorly understood. Here we dissected the dynamic regulation of TH1 cell differentiation during in vitro polarization, and during in vivo differentiation after acute viral infection. We identified regulators modulating T helper cell differentiation using a unique TH1-TH2 cell dichotomous culture system and systematically validated their regulatory functions through multiple in vitro and in vivo CRISPR screens. We found that RAMP3, a component of the receptor for the neuropeptide CGRP (calcitonin gene-related peptide), has a cell-intrinsic role in TH1 cell fate determination. Extracellular CGRP signalling through the receptor RAMP3-CALCRL restricted the differentiation of TH2 cells, but promoted TH1 cell differentiation through the activation of downstream cAMP response element-binding protein (CREB) and activating transcription factor 3 (ATF3). ATF3 promoted TH1 cell differentiation by inducing the expression of Stat1, a key regulator of TH1 cell differentiation. After viral infection, an interaction between CGRP produced by neurons and RAMP3 expressed on T cells enhanced the anti-viral IFNγ-producing TH1 and CD8+ T cell response, and timely control of acute viral infection. Our research identifies a neuroimmune circuit in which neurons participate in T cell fate determination by producing the neuropeptide CGRP during acute viral infection, which acts on RAMP3-expressing T cells to induce an effective anti-viral TH1 cell response.

Exercise Induced Endothelial Mesenchymal Transition (EndMT) Facilitates Meniscal Fibrocartilage Regeneration

The meniscus is a semilunar wedge-shaped fibrocartilage tissue within the knee joint that is important for withstanding mechanical shock during joint motion. The intrinsic healing capacity of meniscus tissue is very limited, which makes meniscectomy the primary treatment method in the clinic. An effective translational strategy for regenerating the meniscus after total or subtotal meniscectomy, particularly for extensive meniscal lesions or degeneration, is yet to be developed. The present study demonstrates that the endothelial mesenchymal transition (EndMT) contributes to meniscal regeneration. The mechanical stimulus facilitated EndMT by activating TGF-β2 signaling. A handheld bioprinter system to intraoperatively fabricate a porous meniscus scaffold according to the resected meniscus tissue is developed; this can simplify the scaffold fabrication procedure and period. The transplantation of a porous meniscus scaffold combined with a postoperative regular exercise stimulus facilitated the regeneration of anisotropic meniscal fibrocartilaginous tissue and protected the joint cartilage from degeneration in an ovine subtotal meniscectomy model. Single-cell RNA sequencing and immunofluorescence co-staining analyses further confirmed the occurrence of EndMT during meniscal regeneration. EndMT-transformed cells gave rise to fibrochondrocytes, subsequently contributing to meniscal fibrocartilage regeneration. Thus, an efficient translational strategy to facilitate meniscal regeneration is developed.

FGF8-mediated gene regulation affects regional identity in human cerebral organoids

The morphogen FGF8 establishes graded positional cues imparting regional cellular responses via modulation of early target genes. The roles of FGF signaling and its effector genes remain poorly characterized in human experimental models mimicking early fetal telencephalic development. We used hiPSC-derived cerebral organoids as an in vitro platform to investigate the effect of FGF8 signaling on neural identity and differentiation. We found that FGF8 treatment increases cellular heterogeneity, leading to distinct telencephalic and mesencephalic-like domains that co-develop in multi-regional organoids. Within telencephalic regions, FGF8 affects the anteroposterior and dorsoventral identity of neural progenitors and the balance between GABAergic and glutamatergic neurons, thus impacting spontaneous neuronal network activity. Moreover, FGF8 efficiently modulates key regulators responsible for several human neurodevelopmental disorders. Overall, our results show that FGF8 signaling is directly involved in both regional patterning and cellular diversity in human cerebral organoids and in modulating genes associated with normal and pathological neural development.

Single-nucleus sequencing unveils heterogeneity in renal cell carcinomas microenvironment: Insights into pathogenic origins and treatment-responsive cellular subgroups

BACKGROUND

Different individuals with renal cell carcinoma (RCC) exhibit substantial heterogeneity in histomorphology, genetic alterations in the proteome, immune cell infiltration patterns, and clinical behavior.

OBJECTIVES

This study aims to use single-nucleus sequencing on ten samples (four normal, three clear cell renal cell carcinoma (ccRCC), and three chromophobe renal cell carcinoma (chRCC)) to uncover pathogenic origins and prognostic characteristics in patients with RCC.

METHODS

By using two algorithms, inferCNV and k-means, the study explores malignant cells and compares them with the normal group to reveal their origins. Furthermore, we explore the pathogenic factors at the gene level through Summary-data-based Mendelian Randomization and co-localization methods. Based on the relevant malignant markers, a total of 212 machine-learning combinations were compared to develop a prognostic signature with high precision and stability. Finally, the study correlates with clinical data to investigate which cell subtypes may impact patients' prognosis.

RESULTS & CONCLUSION

Two main origin tumor cells were identified: Proximal tubule cell B and Intercalated cell type A, which were highly differentiated in epithelial cells, and three gene loci were determined as potential pathogenic genes. The best malignant signature among the 212 prognostic models demonstrated high predictive power in ccRCC: (AUC: 0.920 (1-year), 0.920 (3-year) and 0.930 (5-year) in the training dataset; 0.756 (1-year), 0.828 (3-year), and 0.832 (5-year) in the testing dataset. In addition, we confirmed that LYVE1+ tissue-resident macrophage and TOX+ CD8 significantly impact the prognosis of ccRCC patients, while monocytes play a crucial role in the prognosis of chRCC patients.

Integrating amyloid imaging and genetics for early risk stratification of Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD) initiates years prior to symptoms, underscoring the importance of early detection. While amyloid accumulation starts early, individuals with substantial amyloid burden may remain cognitively normal, implying that amyloid alone is not sufficient for early risk assessment.

METHODS

Given the genetic susceptibility of AD, a multi-factorial pseudotime approach was proposed to integrate amyloid imaging and genotype data for estimating a risk score. Validation involved association with cognitive decline and survival analysis across risk-stratified groups, focusing on patients with mild cognitive impairment (MCI).

RESULTS

Our risk score outperformed amyloid composite standardized uptake value ratio in correlation with cognitive scores. MCI subjects with lower pseudotime risk score showed substantial delayed onset of AD and slower cognitive decline. Moreover, pseudotime risk score demonstrated strong capability in risk stratification within traditionally defined subgroups such as early MCI, apolipoprotein E (APOE) ε4+ MCI, APOE ε4- MCI, and amyloid+ MCI.

DISCUSSION

Our risk score holds great potential to improve the precision of early risk assessment.

HIGHLIGHTS

Accurate early risk assessment is critical for the success of clinical trials. A new risk score was built from integrating amyloid imaging and genetic data. Our risk score demonstrated improved capability in early risk stratification.

Prenatal p25-activated Cdk5 induces pituitary tumorigenesis through MCM2 phosphorylation-mediated cell proliferation

Aberrant expression of cyclin-dependent kinase 5 (Cdk5) has been reported in pituitary adenomas. However, the role of Cdk5 in the tumorigenesis remains unclear. We show that prenatal p25-activated Cdk5 phosphorylates minichromosome maintenance protein 2 (Mcm2), enhancing minichromosome maintenance (MCM) family proteins and driving intermediate lobe-located melanotrope-originated pituitary tumorigenesis. In a mouse model with CaMKII promoter-driven transgenic induction of p25, we observed intermediate lobe-originated pituitary adenoma producing non-functional proopiomelanocortin (POMC)-derived peptides under persistent p25 overexpression. Single-cell RNA sequencing revealed Mcm2 may play an important role during tumor progression. Subsequently, Mcm2 was identified as a potential phosphorylated substrate of Cdk5, mediating the tumorous proliferation of melanotrope cells. Silencing Cdk5 or Mcm2 suppressed cell proliferation and colony formation in the 293T cell lines. Therefore, our findings provide a new mouse model of intermediate lobe-originated pituitary adenoma induced by p25/Cdk5 and unveil a previously unappreciated role of Cdk5 and Mcm2 in pituitary adenoma tumorigenesis.

Identify novel therapeutic targets for type II diabetes and periodontitis: insights from single-cell analysis and Mendelian randomization analysis

Background

Periodontitis is a common complication of type II diabetes (T2D). However, the existing research cannot fully elucidate the association between them, let alone identify therapeutic targets for precise treatment of diabetic periodontitis. Therefore, we employed integrated genetic approaches such as single-cell analysis, Mendelian randomization (MR) analysis and colocalization analysis to uncover novel therapeutic targets for T2D and periodontitis.

Methods

This study integrated single-cell analysis, MR analysis, colocalization analysis, phenotype scanning, cell-cell communication analysis and metabolic pathway activity analysis to unveil novel therapeutic targets for periodontitis and T2D. We firstly identified core cell clusters of T2D and periodontitis, and important marker genes were selected. The causal associations between these genes and the two diseases were evaluated through MR analysis. Reverse MR analysis, colocalization analysis, additional validation and phenotype scanning further supported our findings. Finally, cell-cell communication analysis and metabolic pathway activity analysis were employed to preliminarily investigate the mechanisms of the observed causal associations.

Results

Through analysis of scRNA-seq data, we identified classical monocytes and intermediate monocytes as core cell subclusters. Differential analysis identified 221 differentially expressed genes (DEGs). MR analysis identified 13 genes exhibiting causal associations with T2D, and 11 causal genes with periodontitis. Colocalization analysis, reverse MR analysis, additional validation and phenotype scanning further enhanced the robustness of our results. Finally, we identified NCF1 as the core therapeutic target for T2D (OR = 1.09, 95% CI: 1.03-1.14, p = 1.85   × 10 - 3 ) and LRRC25 for T2D (OR = 0.96, 95% CI: 0.93-0.99, p = 3.44   × 10 - 2 ) and periodontitis (OR = 0.92, 95% CI: 0.84-0.99, p = 4.45   × 10 - 2 ). At last, cell-cell communication analysis indicated significant differences in functions and metabolic pathway activity between monocytes expressing or not expressing the core causal genes, which preliminarily interpreted the observed causal associations.

Conclusion

This study integrated single-cell analysis, MR analysis and colocalization analysis to identified novel therapeutic targets for T2D and periodontitis. 13 causal genes were identified for T2D, and 11 for periodontitis. Among them, NCF1 and LRRC25 were regarded as core therapeutic targets. Our findings bridge the gap in the understanding of the association between T2D and periodontitis, and pave the way for targeted therapy of the two diseases.

Smooth muscle expression of RNA editing enzyme ADAR1 controls activation of RNA sensor MDA5 in atherosclerosis

Mapping the genomic architecture of complex disease has been predicated on the understanding that genetic variants influence disease risk through modifying gene expression. However, recent discoveries have revealed that a significant burden of disease heritability in common autoinflammatory disorders and coronary artery disease is mediated through genetic variation modifying post-transcriptional modification of RNA through adenosine-to-inosine (A-to-I) RNA editing. This common RNA modification is catalyzed by ADAR enzymes, where ADAR1 edits specific immunogenic double stranded RNA (dsRNA) to prevent activation of the double strand RNA (dsRNA) sensor MDA5 ( IFIH1 ) and stimulation of an interferon stimulated gene (ISG) response. Multiple lines of human genetic data indicate impaired RNA editing and increased dsRNA sensing by MDA5 to be an important mechanism of coronary artery disease (CAD) risk. Here, we provide a crucial link between observations in human genetics and mechanistic cell biology leading to progression of CAD. Through analysis of human atherosclerotic plaque, we implicate the vascular smooth muscle cell (SMC) to have a unique requirement for RNA editing, and that ISG induction occurs in SMC phenotypic modulation, implicating MDA5 activation. Through culture of human coronary artery SMCs, generation of a conditional SMC specific Adar1 deletion mouse model on a pro-atherosclerosis background with additional constitutive deletion of MDA5 ( Ifih1 ), and with incorporation of single cell RNA sequencing cellular profiling, we further show that Adar1 controls SMC phenotypic state by regulating Mda5 activation, is required to maintain vascular integrity, and controls progression of atherosclerosis and vascular calcification. Through this work, we describe a fundamental mechanism of CAD, where cell type and context specific RNA editing and sensing of dsRNA mediates disease progression, bridging our understanding of human genetics and disease causality.

One Sentence Summary

Smooth muscle expression of RNA editing enzyme ADAR1 regulates activation of double strand RNA sensor MDA5 in novel mechanism of atherosclerosis.

Detecting significant expression patterns in single-cell and spatial transcriptomics with a flexible computational approach

Gene expression data holds the potential to shed light on multiple biological processes at once. However, data analysis methods for single cell sequencing mostly focus on finding cell clusters or the principal progression line of the data. Data analysis for spatial transcriptomics mostly addresses clustering and finding spatially variable genes. Existing data analysis methods are effective in finding the main data features, but they might miss less pronounced, albeit significant, processes, possibly involving a subset of the samples. In this work we present SPIRAL: Significant Process InfeRence ALgorithm. SPIRAL is based on Gaussian statistics to detect all statistically significant biological processes in single cell, bulk and spatial transcriptomics data. The algorithm outputs a list of structures, each defined by a set of genes working simultaneously in a specific population of cells. SPIRAL is unique in its flexibility: the structures are constructed by selecting subsets of genes and cells based on statistically significant and consistent differential expression. Every gene and every cell may be part of one structure, more or none. SPIRAL also provides several visual representations of structures and pathway enrichment information. We validated the statistical soundness of SPIRAL on synthetic datasets and applied it to single cell, spatial and bulk RNA-sequencing datasets. SPIRAL is available at https://spiral.technion.ac.il/ .

Integrative Network Analysis Reveals Novel Moderators of Aβ-Tau Interaction in Alzheimer's Disease

Background

Although interactions between amyloid-beta and tau proteins have been implicated in Alzheimer's disease (AD), the precise mechanisms by which these interactions contribute to disease progression are not yet fully understood. Moreover, despite the growing application of deep learning in various biomedical fields, its application in integrating networks to analyze disease mechanisms in AD research remains limited. In this study, we employed BIONIC, a deep learning-based network integration method, to integrate proteomics and protein-protein interaction data, with an aim to uncover factors that moderate the effects of the Aβ-tau interaction on mild cognitive impairment (MCI) and early-stage AD.

Methods

Proteomic data from the ROSMAP cohort were integrated with protein-protein interaction (PPI) data using a Deep Learning-based model. Linear regression analysis was applied to histopathological and gene expression data, and mutual information was used to detect moderating factors. Statistical significance was determined using the Benjamini-Hochberg correction (p < 0.05).

Results

Our results suggested that astrocytes and GPNMB+ microglia moderate the Aβ-tau interaction. Based on linear regression with histopathological and gene expression data, GFAP and IBA1 levels and GPNMB gene expression positively contributed to the interaction of tau with Aβ in non-dementia cases, replicating the results of the network analysis.

Conclusions

These findings indicate that GPNMB+ microglia moderate the Aβ-tau interaction in early AD and therefore are a novel therapeutic target. To facilitate further research, we have made the integrated network available as a visualization tool for the scientific community (URL: https://igcore.cloud/GerOmics/AlzPPMap).

Assessing personalized molecular portraits underlying endothelial-to-mesenchymal transition within pulmonary arterial hypertension

Pulmonary arterial hypertension (PAH) is a progressive and rapidly fatal disease with an intricate etiology. Identifying biomarkers for early PAH lesions based on the exploration of subtle biological processes is significant for timely diagnosis and treatment. In the present study, nine distinct cell populations identified based on gene expression profiles revealed high heterogeneity in cell composition ratio, biological function, distribution preference, and communication patterns in PAH. Notably, compared to other cells, endothelial cells (ECs) showed prominent variation in multiple perspectives. Further analysis demonstrated the endothelial-to-mesenchymal transition (EndMT) in ECs and identified a subgroup exhibiting a contrasting phenotype. Based on these findings, a machine-learning integrated program consisting of nine learners was developed to create a PAH Endothelial-to-mesenchymal transition Signature (PETS). This study identified cell populations underlying EndMT and furnished a potential tool that might be valuable for PAH diagnosis and new precise therapies.

High-resolution subtyping of fibroblasts in gastric cancer reveals diversity among fibroblast subsets and an association between the MFAP5-fibroblast subset and immunotherapy

Backgrounds

Gastric cancer (GC) remains a global health threat due to frequent treatment failures caused by primary or acquired resistance. Although cancer-associated fibroblasts (CAFs) have been implicated in this process, it is still unclear which specific subtype(s) of CAFs hinder T-cell infiltration and promote resistance to immunotherapy.

Methods

We analyzed the GC fibroblast atlas in detail by combining 63,955 single cells from 14 scRNA-seq datasets. We also performed RNA-seq data in a local GC cohort and examined 13 bulk RNA-seq datasets to understand the biological and clinical roles of different CAF subsets. Additionally, we conducted in vitro experiments to study the role of specific proteins in GC development.

Results

We identified a total of 17 fibroblast subsets in gastric cancer, nine of which did not fit into the existing CAFs classification. These subsets exhibited significant heterogeneity in distribution and biological characteristics (metabolism, cell-cell interactions, differentiation state), as well as clinical functions such as prognosis and response to immunotherapy. In particular, cluster 6 stood out for its high expression of MFAP5, CFD, and PI16; it was found to be negatively associated with both overall survival and response to immunotherapy in GC. This association was linked to an immunosuppressive microenvironment characterized by an increase in M2 macrophages but higher levels of T cell dysfunction and exclusion-a feature shared by tumors expressing MFAP5. Furthermore, the addition of human recombinant MFAP5 promoted proliferation and migration of HGC-27 cells by inducing the MFAP5/NOTCH1/HEY1 signaling pathway.

Conclusion

We introduce a high-resolution GC fibroblast atlas. The 17 identified fibroblast clusters provide valuable opportunities for gaining deeper biological insights into the relationship between fibroblasts and GC development. Particularly, cluster 6 and its specific marker MFAP5 could serve as prognostic factors in GC and form a foundation for personalized therapeutic combinations to address primary resistance to ICIs.

The landscape of RNA binding proteins in mammalian spermatogenesis

Despite continuous expansion of the RNA binding protein (RBP) world, there is a lack of systematic understanding of RBPs in the mammalian testis, which harbors one of the most complex tissue transcriptomes. We adapted RNA interactome capture to mouse male germ cells, building an RBP atlas characterized by multiple layers of dynamics along spermatogenesis. Trapping of RNA-cross-linked peptides showed that the glutamic acid-arginine (ER) patch, a residue-coevolved polyampholytic element present in coiled coils, enhances RNA binding of its host RBPs. Deletion of this element in NONO (non-POU domain-containing octamer-binding protein) led to a defective mitosis-to-meiosis transition due to compromised NONO-RNA interactions. Whole-exome sequencing of over 1000 infertile men revealed a prominent role of RBPs in the human genetic architecture of male infertility and identified risk ER patch variants.

Interaction between subventricular zone microglia and neural stem cells impacts the neurogenic response in a mouse model of cortical ischemic stroke

After a stroke, the neurogenic response from the subventricular zone (SVZ) to repair the brain is limited. Microglia, as an integral part of the distinctive SVZ microenvironment, control neural stem / precursor cell (NSPC) behavior. Here, we show that discrete stroke-associated SVZ microglial clusters negatively impact the innate neurogenic response, and we propose a repository of relevant microglia-NSPC ligand-receptor pairs. After photothrombosis, a mouse model of ischemic stroke, the altered SVZ niche environment leads to immediate activation of microglia in the niche and an abnormal neurogenic response, with cell-cycle arrest of neural stem cells and neuroblast cell death. Pharmacological restoration of the niche environment increases the SVZ-derived neurogenic repair and microglial depletion increases the formation and survival of newborn neuroblasts in the SVZ. Therefore, we propose that altered cross-communication between microglial subclusters and NSPCs regulates the extent of the innate neurogenic repair response in the SVZ after stroke.

PCLAF-DREAM drives alveolar cell plasticity for lung regeneration

Cell plasticity, changes in cell fate, is crucial for tissue regeneration. In the lung, failure of regeneration leads to diseases, including fibrosis. However, the mechanisms governing alveolar cell plasticity during lung repair remain elusive. We previously showed that PCLAF remodels the DREAM complex, shifting the balance from cell quiescence towards cell proliferation. Here, we find that PCLAF expression is specific to proliferating lung progenitor cells, along with the DREAM target genes transactivated by lung injury. Genetic ablation of Pclaf impairs AT1 cell repopulation from AT2 cells, leading to lung fibrosis. Mechanistically, the PCLAF-DREAM complex transactivates CLIC4, triggering TGF-β signaling activation, which promotes AT1 cell generation from AT2 cells. Furthermore, phenelzine that mimics the PCLAF-DREAM transcriptional signature increases AT2 cell plasticity, preventing lung fibrosis in organoids and mice. Our study reveals the unexpected role of the PCLAF-DREAM axis in promoting alveolar cell plasticity, beyond cell proliferation control, proposing a potential therapeutic avenue for lung fibrosis prevention.

Age, sex, and cell type-resolved hypothalamic gene expression across the pubertal transition in mice

BACKGROUND

The hypothalamus plays a central role in regulating puberty. However, our knowledge of the postnatal gene regulatory networks that control the pubertal transition in males and females is incomplete. Here, we investigate the age-, sex- and cell-type-specific gene regulation in the hypothalamus across the pubertal transition.

METHODS

We used RNA-seq to profile hypothalamic gene expression in male and female mice at five time points spanning the onset of puberty (postnatal days (PD) 12, 22, 27, 32, and 37). By combining this data with hypothalamic single nuclei RNA-seq data from pre- and postpubertal mice, we assigned gene expression changes to their most likely cell types of origin. In our colony, pubertal onset occurs earlier in male mice, allowing us to focus on genes whose expression is dynamic across ages and offset between sexes, and to explore the bases of sex effects.

RESULTS

Our age-by-sex pattern of expression enriched for biological pathways involved hormone production, neuronal activation, and glial maturation. Additionally, we inferred a robust expansion of oligodendrocytes precursor cells into mature oligodendrocytes spanning the prepubertal (PD12) to peri-pubertal (PD27) timepoints. Using spatial transcriptomic data from postpubertal mice, we observed the lateral hypothalamic area and zona incerta were the most oligodendrocyte-rich regions and that these cells expressed genes known to be involved in pubertal regulation.

CONCLUSION

Together, by incorporating multiple biological timepoints and using sex as a variable, we identified gene and cell-type changes that may participate in orchestrating the pubertal transition and provided a resource for future studies of postnatal hypothalamic gene regulation.

A spatiotemporal molecular atlas of mouse spinal cord injury identifies a distinct astrocyte subpopulation and therapeutic potential of IGFBP2

Spinal cord injury (SCI) triggers a cascade of intricate molecular and cellular changes that determine the outcome. In this study, we resolve the spatiotemporal organization of the injured mouse spinal cord and quantitatively assess in situ cell-cell communication following SCI. By analyzing existing single-cell RNA sequencing datasets alongside our spatial data, we delineate a subpopulation of Igfbp2-expressing astrocytes that migrate from the white matter (WM) to gray matter (GM) and become reactive upon SCI, termed Astro-GMii. Further, Igfbp2 upregulation promotes astrocyte migration, proliferation, and reactivity, and the secreted IGFBP2 protein fosters neurite outgrowth. Finally, we show that IGFBP2 significantly reduces neuronal loss and remarkably improves the functional recovery in a mouse model of SCI in vivo. Together, this study not only provides a comprehensive molecular atlas of SCI but also exemplifies how this rich resource can be applied to endow cells and genes with functional insight and therapeutic potential.

Decoding the multiple functions of ZBP1 in the mechanism of sepsis-induced acute lung injury

Sepsis-induced acute lung injury (ALI), characterized by severe hypoxemia and pulmonary leakage, remains a leading cause of mortality in intensive care units. The exacerbation of ALI during sepsis is largely attributed to uncontrolled inflammatory responses and endothelial dysfunction. Emerging evidence suggests an important role of Z-DNA binding protein 1 (ZBP1) as a sensor in innate immune to drive inflammatory signaling and cell death during infections. However, the role of ZBP1 in sepsis-induced ALI has yet to be defined. We utilized ZBP1 knockout mice and combined single-cell RNA sequencing with experimental validation to investigate ZBP1's roles in the regulation of macrophages and lung endothelial cells during sepsis. We demonstrate that in sepsis, ZBP1 deficiency in macrophages reduces mitochondrial damage and inhibits glycolysis, thereby altering the metabolic status of macrophages. Consequently, this metabolic shift leads to a reduction in the differentiation of macrophages into pro-inflammatory states and decreases macrophage pyroptosis triggered by activation of the NLRP3 inflammasome. These changes significantly weaken the inflammatory signaling pathways between macrophages and endothelial cells and alleviate endothelial dysfunction and cellular damage. These findings reveal important roles for ZBP1 in mediating multiple pathological processes involved in sepsis-induced ALI by modulating the functional states of macrophages and endothelial cells, thereby highlighting its potential as a promising therapeutic target.

Myeloid Mir34a suppresses colitis-associated colon cancer: characterization of mediators by single-cell RNA sequencing

We have previously shown that general deletion of the gene encoding the p53-inducible Mir34a microRNA enhances the number and invasion of colitis-associated colorectal cancers (CACs) in mice. Since the p53-pathway has been implicated in tumor-suppression mediated by cells in the tumor microenvironment (TME) we deleted Mir34a in myeloid cells and characterized CACs in these with scRNA-Seq (single cell RNA sequencing). This revealed an increase in specific macrophage subtypes, such as Cdk8+ macrophages and Mrc1+, M2-like macrophages. The latter displayed elevated expression of 21 known Mir34a target mRNAs, including Csf1r, Axl, Foxp1, Ccr1, Nampt, and Tgfbr2, and 32 predicted Mir34a target mRNAs. Furthermore, Mir34a-deficient BMDMs showed enhanced migration, elevated expression of Csf1r and a shift towards M2-like polarization when compared to Mir34a-proficient BMDMs. Concomitant deletion of Csf1r or treatment with a Csf1r inhibitor reduced the CAC burden and invasion in these mice. Notably, loss of myeloid Mir34a function resulted in a prominent, inflammatory CAC cell subtype, which displayed epithelial and macrophage markers. These cells displayed high levels of the EMT transcription factor Zeb2 and may therefore enhance the invasiveness of CACs. Taken together, our results provide in vivo evidence for a tumor suppressive role of myeloid Mir34a in CACs which is, at least in part, mediated by maintaining macrophages in an M1-like state via repression of Mir34a targets, such as Csf1r. Collectively, these findings may serve to identify new therapeutic targets and approaches for treatment of CAC.

Cell Fate Dynamics Reconstruction Identifies TPT1 and PTPRZ1 Feedback Loops as Master Regulators of Differentiation in Pediatric Glioblastoma-Immune Cell Networks

Pediatric glioblastoma is a complex dynamical disease that is difficult to treat due to its multiple adaptive behaviors driven largely by phenotypic plasticity. Integrated data science and network theory pipelines offer novel approaches to studying glioblastoma cell fate dynamics, particularly phenotypic transitions over time. Here we used various single-cell trajectory inference algorithms to infer signaling dynamics regulating pediatric glioblastoma-immune cell networks. We identified GATA2, PTPRZ1, TPT1, MTRNR2L1/2, OLIG1/2, SOX11, FXYD6, SEZ6L, PDGFRA, EGFR, S100B, WNT, TNF α , and NF-kB as critical transition genes or signals regulating glioblastoma-immune network dynamics, revealing potential clinically relevant targets. Further, we reconstructed glioblastoma cell fate attractors and found complex bifurcation dynamics within glioblastoma phenotypic transitions, suggesting that a causal pattern may be driving glioblastoma evolution and cell fate decision-making. Together, our findings have implications for developing targeted therapies against glioblastoma, and the continued integration of quantitative approaches and artificial intelligence (AI) to understand pediatric glioblastoma tumor-immune interactions.

A latent Axin2+/Scx+ progenitor pool is the central organizer of tendon healing

A tendon's ordered extracellular matrix (ECM) is essential for transmitting force but is also highly prone to injury. How tendon cells embedded within and surrounding this dense ECM orchestrate healing is not well understood. Here, we identify a specialized quiescent Scx+/Axin2+ population in mouse and human tendons that initiates healing and is a major functional contributor to repair. Axin2+ cells express stem cell markers, expand in vitro, and have multilineage differentiation potential. Following tendon injury, Axin2+-descendants infiltrate the injury site, proliferate, and differentiate into tenocytes. Transplantation assays of Axin2-labeled cells into injured tendons reveal their dual capacity to significantly proliferate and differentiate yet retain their Axin2+ identity. Specific loss of Wnt secretion in Axin2+ or Scx+ cells disrupts their ability to respond to injury, severely compromising healing. Our work highlights an unusual paradigm, wherein specialized Axin2+/Scx+ cells rely on self-regulation to maintain their identity as key organizers of tissue healing.

Spatial oncology: Translating contextual biology to the clinic

Microscopic examination of cells in their tissue context has been the driving force behind diagnostic histopathology over the past two centuries. Recently, the rise of advanced molecular biomarkers identified through single cell profiling has increased our understanding of cellular heterogeneity in cancer but have yet to significantly impact clinical care. Spatial technologies integrating molecular profiling with microenvironmental features are poised to bridge this translational gap by providing critical in situ context for understanding cellular interactions and organization. Here, we review how spatial tools have been used to study tumor ecosystems and their clinical applications. We detail findings in cell-cell interactions, microenvironment composition, and tissue remodeling for immune evasion and therapeutic resistance. Additionally, we highlight the emerging role of multi-omic spatial profiling for characterizing clinically relevant features including perineural invasion, tertiary lymphoid structures, and the tumor-stroma interface. Finally, we explore strategies for clinical integration and their augmentation of therapeutic and diagnostic approaches.

Multiplexed single-cell imaging reveals diverging subpopulations with distinct senescence phenotypes during long-term senescence induction

Cellular senescence is a phenotypic state that contributes to the progression of age-related disease through secretion of pro-inflammatory factors known as the senescence associated secretory phenotype (SASP). Understanding the process by which healthy cells become senescent and develop SASP factors is critical for improving the identification of senescent cells and, ultimately, understanding tissue dysfunction. Here, we reveal how the duration of cellular stress modulates the SASP in distinct subpopulations of senescent cells. We used multiplex, single-cell imaging to build a proteomic map of senescence induction in human epithelial cells induced to senescence over the course of 31 days. We map how the expression of SASP proteins increases alongside other known senescence markers such as p53, p21, and p16INK4a. The aggregated population of cells responded to etoposide with an accumulation of stress response factors over the first 11 days, followed by a plateau in most proteins. At the single-cell level, however, we identified two distinct senescence cell populations, one defined primarily by larger nuclear area and the second by higher protein concentrations. Trajectory inference suggested that cells took one of two discrete molecular paths from unperturbed healthy cells, through a common transitional subpopulation, and ending at the discrete terminal senescence phenotypes. Our results underscore the importance of using single-cell proteomics to identify the mechanistic pathways governing the transition from senescence induction to a mature state of senescence characterized by the SASP.

Comparative analysis of rhesus macaque and human placental organoids highlights evolutionary differences in placentation

Throughout evolution, the placenta has diversified in both structure and cellular composition while maintaining its fundamental function. Trophoblasts are fetal-derived cells responsible for nourishing and protecting the developing fetus and are a universal component of all placentas. While primate placentas exhibit many shared morphological features, species-specific differences in gene expression remain largely unexplored, primarily due to the lack of suitable in vitro models. To address this gap, we developed organoids from rhesus macaque placentas, including trophoblast and maternal-derived decidua types, and compared them with organoids derived from human placentas. We performed comparative single-cell RNA sequencing to delineate shared and distinct transcriptional signatures between rhesus macaque and human trophoblasts. We further defined the differentiation trajectories leading to the multinucleated syncytiotrophoblast, highlighting both shared and unique transcriptional signatures between rhesus macaque and human placentas. This work establishes novel in vitro models of the non-human primate placenta and characterizes distinct trophoblast gene profiles in rhesus macaques and humans, providing insights into interspecies variations in placental biology.

Single-cell RNA sequencing identifies a subtype of FN1 + tumor-associated macrophages associated with glioma recurrence and as a biomarker for immunotherapy

BACKGROUND

Glioma is the most common primary malignant tumor in the brain, and even with standard treatments including surgical resection, radiotherapy, and chemotherapy, the long-term survival rate of patients remains unsatisfactory. Recurrence is one of the leading causes of death in glioma patients. The molecular mechanisms underlying glioma recurrence remain unclear.

METHODS

Our study utilized single-cell sequencing, spatial transcriptomics, and RNA-seq data to identify a subtype of FN1 + tumor-associated macrophages (FN1 + TAMs) associated with glioma recurrence.

RESULTS

This study revealed an increased abundance of FN1 + TAMs in recurrent gliomas, indicating their potential involvement as a critical factor in glioma recurrence. A negative correlation was observed between the abundance of FN1 + TAMs in primary gliomas and the interval time to recurrence, suggesting poor prognosis for glioma patients with high levels of FN1 + TAMs. Further investigation showed that FN1 + TAMs were enriched in hypoxic tumor regions, implying that metabolic changes in tumors drive the production and recruitment of FN1 + TAMs. Additionally, FN1 + TAMs were found to contribute to the regulation of an immunosuppressive microenvironment in gliomas, and their abundance might serve as an indicator of patients' sensitivity to immunotherapy. Finally, we developed a user-friendly website, PRIMEG ( http://www.szflab.site/PRIMEG/ ), for exploring the immune microenvironment of primary and recurrent gliomas.

CONCLUSION

Our findings highlight a subtype of FN1 + TAMs associated with glioma recurrence, providing new insights into potential therapeutic targets. Moreover, the abundance of FN1 + TAMs hold promise for predicting immune therapy response and aiding in more precise risk stratification of recurrent glioma patients.

Adjusting to self in the thymus: CD4 versus CD8 lineage commitment and regulatory T cell development

During thymic development, thymocytes adjust their TCR response based on the strength of their reactivity to self-peptide MHC complexes. This tuning process allows thymocytes with a range of self-reactivities to survive positive selection and contribute to a diverse T cell pool. In this review, we will discuss recent advances in our understanding of how thymocytes tune their responsiveness during positive selection, and we present a "sequential selection" model to explain how MHC specificity influences lineage choice. We also discuss recent evidence for cell type diversity in the medulla and discuss how this heterogeneity may contribute to medullary niches for negative selection and regulatory T cell development.

An atlas of small non-coding RNAs in human preimplantation development

Understanding the molecular circuitries that govern early embryogenesis is important, yet our knowledge of these in human preimplantation development remains limited. Small non-coding RNAs (sncRNAs) can regulate gene expression and thus impact blastocyst formation, however, the expression of specific biotypes and their dynamics during preimplantation development remains unknown. Here we identify the abundance of and kinetics of piRNA, rRNA, snoRNA, tRNA, and miRNA from embryonic day (E)3-7 and isolate specific miRNAs and snoRNAs of particular importance in blastocyst formation and pluripotency. These sncRNAs correspond to specific genomic hotspots: an enrichment of the chromosome 19 miRNA cluster (C19MC) in the trophectoderm (TE), and the chromosome 14 miRNA cluster (C14MC) and MEG8-related snoRNAs in the inner cell mass (ICM), which may serve as 'master regulators' of potency and lineage. Additionally, we observe a developmental transition with 21 isomiRs and in tRNA fragment (tRF) codon usage and identify two novel miRNAs. Our analysis provides a comprehensive measure of sncRNA biotypes and their corresponding dynamics throughout human preimplantation development, providing an extensive resource. Better understanding the sncRNA regulatory programmes in human embryogenesis will inform strategies to improve embryo development and outcomes of assisted reproductive technologies. We anticipate broad usage of our data as a resource for studies aimed at understanding embryogenesis, optimising stem cell-based models, assisted reproductive technology, and stem cell biology.

Cross-disorder and disease-specific pathways in dementia revealed by single-cell genomics

The development of successful therapeutics for dementias requires an understanding of their shared and distinct molecular features in the human brain. We performed single-nuclear RNA-seq and ATAC-seq in Alzheimer's disease (AD), frontotemporal dementia (FTD), and progressive supranuclear palsy (PSP), analyzing 41 participants and ∼1 million cells (RNA + ATAC) from three brain regions varying in vulnerability and pathological burden. We identify 32 shared, disease-associated cell types and 14 that are disease specific. Disease-specific cell states represent glial-immune mechanisms and selective neuronal vulnerability impacting layer 5 intratelencephalic neurons in AD, layer 2/3 intratelencephalic neurons in FTD, and layer 5/6 near-projection neurons in PSP. We identify disease-associated gene regulatory networks and cells impacted by causal genetic risk, which differ by disorder. These data illustrate the heterogeneous spectrum of glial and neuronal compositional and gene expression alterations in different dementias and identify therapeutic targets by revealing shared and disease-specific cell states.

Continuous cell type diversification throughout the embryonic and postnatal mouse visual cortex development

The mammalian cortex is composed of a highly diverse set of cell types and develops through a series of temporally regulated events that build out the cell type and circuit foundation for cortical function. The mechanisms underlying the development of different cell types remain elusive. Single-cell transcriptomics provides the capacity to systematically study cell types across the entire temporal range of cortical development. Here, we present a comprehensive and high-resolution transcriptomic and epigenomic cell type atlas of the developing mouse visual cortex. The atlas was built from a single-cell RNA-sequencing dataset of 568,674 high-quality single-cell transcriptomes and a single-nucleus Multiome dataset of 194,545 high-quality nuclei providing both transcriptomic and chromatin accessibility profiles, densely sampled throughout the embryonic and postnatal developmental stages from E11.5 to P56. We computationally reconstructed a transcriptomic developmental trajectory map of all excitatory, inhibitory, and non-neuronal cell types in the visual cortex, identifying branching points marking the emergence of new cell types at specific developmental ages and defining molecular signatures of cellular diversification. In addition to neurogenesis, gliogenesis and early postmitotic maturation in the embryonic stage which gives rise to all the cell classes and nearly all subclasses, we find that increasingly refined cell types emerge throughout the postnatal differentiation process, including the late emergence of many cell types during the eye-opening stage (P11-P14) and the onset of critical period (P21), suggesting continuous cell type diversification at different stages of cortical development. Throughout development, we find cooperative dynamic changes in gene expression and chromatin accessibility in specific cell types, identifying both chromatin peaks potentially regulating the expression of specific genes and transcription factors potentially regulating specific peaks. Furthermore, a single gene can be regulated by multiple peaks associated with different cell types and/or different developmental stages. Collectively, our study provides the most detailed dynamic molecular map directly associated with individual cell types and specific developmental events that reveals the molecular logic underlying the continuous refinement of cell type identities in the developing visual cortex.

Interleukin-11 causes alveolar type 2 cell dysfunction and prevents alveolar regeneration

In lung disease, persistence of KRT8-expressing aberrant basaloid cells in the alveolar epithelium is associated with impaired tissue regeneration and pathological tissue remodeling. We analyzed single cell RNA sequencing datasets of human interstitial lung disease and found the profibrotic Interleukin-11 (IL11) cytokine to be highly and specifically expressed in aberrant KRT8+ basaloid cells. IL11 is similarly expressed by KRT8+ alveolar epithelial cells lining fibrotic lesions in a mouse model of interstitial lung disease. Stimulation of alveolar epithelial cells with IL11 causes epithelial-to-mesenchymal transition and promotes a KRT8-high state, which stalls the beneficial differentiation of alveolar type 2 (AT2)-to-AT1 cells. Inhibition of IL11-signaling in AT2 cells in vivo prevents the accumulation of KRT8+ cells, enhances AT1 cell differentiation and blocks fibrogenesis, which is replicated by anti-IL11 therapy. These data show that IL11 inhibits reparative AT2-to-AT1 differentiation in the damaged lung to limit endogenous alveolar regeneration, resulting in fibrotic lung disease.

Single-cell analysis reveals hypoxia-induced immunosuppressive microenvironment in intrahepatic cholangiocarcinoma

The role of hypoxia in the tumor microenvironment of intrahepatic cholangiocarcinoma (iCCA) remains unclear. Here, we generated a comprehensive atlas of the entire tumor microenvironment and delineated the multifaceted cell-cell interactions to decipher hypoxia-induced pro-tumor immune suppression. We discovered hypoxia is significantly associated with iCCA progression via the activation of HIF1A expression. Moreover, hypoxia-dependent PPARγ-mediated fatty acid oxidation in APOE+ TAMs promoted M2 macrophage polarization by activating the HIF1A-PPARG-CD36 axis. These polarized APOE+ TAMs recruited Treg cell infiltration via the CCL3-CCR5 pair to form an immunosuppressive microenvironment. APOE+ TAMs tended to co-localize spatially with Treg cells in the malignant tissue based on spatial transcriptome data and immunofluorescence analysis results. We identified tumor-reactive CXCL13+ CD8-PreTex with specific high expression of ENTPD1 and ITGAE, which acted as precursors of CD8-Tex and had higher cytotoxicity, lower exhaustion, and more vigorous proliferation. Consequently, CXCL13+ CD8-PreTex functioned as a positive regulator of antitumor immunity by expressing the pro-inflammatory cytokines IFNG and TNF, associated with a better survival outcome. Our study reveals the mechanisms involved in hypoxia-induced immunosuppression and suggests that targeting precursor-exhausted CXCL13+CD8+ T cells might provide a pratical immunotherapeutic approach.

Deciphering the dynamic single-cell transcriptional landscape in the ocular surface ectoderm differentiation system

The ocular surface ectoderm (OSE) is essential for the development of the ocular surface, yet the molecular mechanisms driving its differentiation are not fully understood. In this study, we used single-cell transcriptomic analysis to explore the dynamic cellular trajectories and regulatory networks during the in vitro differentiation of embryonic stem cells (ESCs) into the OSE lineage. We identified nine distinct cell subpopulations undergoing differentiation along three main developmental branches: neural crest, neuroectodermal, and surface ectodermal lineages. Key marker gene expression, transcription factor activity, and signaling pathway insights revealed stepwise transitions from undifferentiated ESCs to fate-specified cell types, including a PAX6 + TP63 + population indicative of OSE precursors. Comparative analysis with mouse embryonic development confirmed the model's accuracy in mimicking in vivo epiblast-to-surface ectoderm dynamics. By integrating temporal dynamics of transcription factor activation and cell-cell communication, we constructed a comprehensive molecular atlas of the differentiation pathway from ESCs to distinct ectodermal lineages. This study provides new insights into the cellular heterogeneity and regulatory mechanisms of OSE development, aiding the understanding of ocular surface biology and the design of cell-based therapies for ocular surface disorders.

Retinoic acid, an essential component of the roof plate organizer, promotes the spatiotemporal segregation of dorsal neural fates

Dorsal neural tube-derived retinoic acid promotes the end of neural crest production and transition into a definitive roof plate. Here, we analyze how this impacts the segregation of central and peripheral lineages, a process essential for tissue patterning and function. Localized in ovo inhibition in quail embryos of retinoic acid activity followed by single-cell transcriptomics unraveled a comprehensive list of differentially expressed genes relevant to these processes. Importantly, progenitors co-expressed neural crest, roof plate and dI1 interneuron markers, indicating a failure in proper lineage segregation. Furthermore, separation between roof plate and dI1 interneurons is mediated by Notch activity downstream of retinoic acid, highlighting their crucial role in establishing the roof plate-dI1 boundary. Within the peripheral branch, where absence of retinoic acid resulted in neural crest production and emigration extending into the roof plate stage, sensory progenitors failed to separate from melanocytes, leading to formation of a common glia-melanocyte cell with aberrant migratory patterns. In summary, the implementation of single-cell RNA sequencing facilitated the discovery and characterization of a molecular mechanism responsible for the segregation of dorsal neural fates during development.

Sex-dependent APOE4 neutrophil-microglia interactions drive cognitive impairment in Alzheimer's disease

APOE4 is the strongest genetic risk factor for Alzheimer's disease (AD), with increased odds ratios in female carriers. Targeting amyloid plaques shows modest improvement in male non-APOE4 carriers. Leveraging single-cell transcriptomics across APOE variants in both sexes, multiplex flow cytometry and validation in two independent cohorts of APOE4 female carriers with AD, we identify a new subset of neutrophils interacting with microglia associated with cognitive impairment. This phenotype is defined by increased interleukin (IL)-17 and IL-1 coexpressed gene modules in blood neutrophils and in microglia of cognitively impaired female APOE ε4 carriers, showing increased infiltration to the AD brain. APOE4 female IL-17+ neutrophils upregulated the immunosuppressive cytokines IL-10 and TGFβ and immune checkpoints, including LAG3 and PD-1, associated with accelerated immune aging. Deletion of APOE4 in neutrophils reduced this immunosuppressive phenotype and restored the microglial response to neurodegeneration, limiting plaque pathology in AD mice. Mechanistically, IL-17F upregulated in APOE4 neutrophils interacts with microglial IL-17RA to suppress the induction of the neurodegenerative phenotype, and blocking this axis supported cognitive improvement in AD mice. These findings provide a translational basis to target IL-17F in APOE ε4 female carriers with cognitive impairment.