Cell-cell Communication Networks Research Articles

A brain cell atlas integrating single-cell transcriptomes across human brain regions.

While single-cell technologies have greatly advanced our comprehension of human brain cell types and functions, studies including large numbers of donors and multiple brain regions are needed to extend our understanding of brain cell heterogeneity. Integrating atlas-level single-cell data presents a chance to reveal rare cell types and cellular heterogeneity across brain regions. Here we present the Brain Cell Atlas, a comprehensive reference atlas of brain cells, by assembling single-cell data from 70 human and 103 mouse studies of the brain throughout major developmental stages across brain regions, covering over 26.3 million cells or nuclei from both healthy and diseased tissues. Using machine-learning based algorithms, the Brain Cell Atlas provides a consensus cell type annotation, and it showcases the identification of putative neural progenitor cells and a cell subpopulation of PCDH9high microglia in the human brain. We demonstrate the gene regulatory difference of PCDH9high microglia between hippocampus and prefrontal cortex and elucidate the cell-cell communication network. The Brain Cell Atlas presents an atlas-level integrative resource for comparing brain cells in different environments and conditions within the Human Cell Atlas.

Reconstitution of the Multiple Myeloma Microenvironment Following Lymphodepletion with BCMA CAR-T Therapy.

To investigate the remodeling of multiple myeloma (MM) microenvironment after BCMA-targeted chimeric antigen receptor T cell (CAR-T) therapy. We performed single-cell RNA sequencing (scRNA-seq) on paired bone marrow specimens (n = 14) from 7 MM patients before (i.e., baseline, 'day -4') and after (i.e., 'day 28') post-lymphodepleted BCMA CAR-T therapy. Our analysis revealed heterogeneity in gene expression profiles among MM cells, even those harboring the same cytogenetic abnormalities. The best overall responses (BORs) of patients over the 15-month follow-up are positively correlated with the abundance and targeted cytotoxic activity of CD8+ effector CAR-T cells on day 28 after CAR-T cell infusion. Additionally, favorable responses are associated with attenuated immunosuppression mediated by regulatory T cells (Tregs), enhanced CD8+ effector T cell cytotoxic activity, and elevated type 1 conventional dendritic cell (cDC1) antigen presentation ability. DC re-clustering inferred intramedullary-originated cDC3s with extramedullary migration. Cell-cell communication network analysis indicated BCMA CAR-T therapy mitigates BAFF/GALECTIN/MK pathway-mediated immunosuppression and activates MIF pathway-mediated anti-MM immunity. Our study sheds light on MM microenvironment dynamics after BCMA CAR-T therapy, offering clues for predicting treatment responsivity.

Single-cell RNA sequencing uncovers cellular heterogeneity and the progression of heterotopic ossification of the elbow.

Heterotopic ossification of the elbow (HOE) is a complicated pathologic process characterized by extra bone formation in the elbow. Bone formation is a complex developmental process involving the differentiation of mesenchymal stem cells into osteoblasts. The aim of this study was to explore the cellular origin and progression of HOE by single-cell RNA sequencing. We identified 13 clusters of cells in HOE and further analyzed the subclusters for 4 of the main cell types. Six subclusters of osteoblasts, nine subclusters of chondrocytes, six subclusters of fibroblasts, and five subclusters of mononuclear phagocytes (MPs) were identified and analyzed. The new findings on osterix (OSX) and SOX9 expression in osteoblast subclusters and chondrocyte subclusters indicate that HOE is mediated through endochondral ossification. Further identification of the corresponding signature gene sets of distinct subclusters indicated that subclusters of osteoblasts_3, osteoblasts_4, osteoblasts_5, and osteoblasts_6 are relatively more mature during the osteoblastic progression of HOE. The trajectory analysis of the osteoblasts demonstrated that some genes were gradually downregulated, such as CRYAB, CCL3, SFRP4, WIF1, and IGFBP3, while other critical genes were upregulated, such as VCAN, IGFBP4, FSTL1, POSTN, MDK, THBS2, and ALPL, suggesting that these factors may participate in HOE progression. Cell-cell communication networks revealed extensive molecular interactions among the 13 HOE clusters. Ligand-receptor pairs for IL6, COL24A1, COL22A1, VWF, FZD6, FGF2, and NOTCH1 were identified, suggesting that multiple signaling pathways may be involved in HOE. In conclusion, this study provided the cellular atlas for HOE. We have established a greater extent of the heterogeneity of HOE cells than previously known through transcriptomic analysis at the single-cell level. We have observed gradual patterns of signature gene expression during the differentiation and maturation progression of osteoblasts from stem cells in HOE with higher resolution. The cell heterogeneity of HOE deserves further investigation to pave the way for identification of potential targets for HOE early diagnosis and therapeutic treatment.

O-265 Mapping decidualization resistance at multi-omic level

Abstract Study question What are the cellular and molecular features of decidualization resistance (DR) at single-cell resolution? Summary answer There is an absence of the stromal-epithelial transition with aberrant crosstalk among cell types in essential pathways (e.g., endoglin, WNT) confirmed at the protein level. What is known already DR refers to the inability of the endometrium to undergo decidualization changes preparing the endometrium for a conceptus, noted in disorders like endometriosis, recurrent pregnancy loss, miscarriage and preeclampsia. The molecular mechanisms causing this disorder remains unknown. It has been demonstrated that there is a transcriptomic signature of DR in the endometrium of former preeclampsia patients, during and years after suffering from the disease. Our objective is to dilucidated what is DR at single-cell resolution. Study design, size, duration This cross-sectional study compares late secretory phase endometrial biopsies from patients that previously have suffered severe Preeclampsia (sPE). The sample size consisted of 11 sPE patients and 12 control participants for single-cell RNA sequencing (scRNA-seq), 8 sPE patients and 8 controls for spatial transcriptomic mapping covering 95 tissue regions, and 10 sPE patients and 10 controls for proteomic analysis. The study spanned 2 years, from sample collection to omics analysis. Participants/materials, setting, methods Late secretory phase endometrial biopsies from sPE patients and controls underwent molecular analyses. Methods included 10x Genomics protocol for single-cell RNA sequencing, MiloR to calculate cell abundance, CellChat to infer cell-to-cell communication and ClusterProfiler for gene ontology. We solved spatial mapping at transcriptomic level using Nanostring. Proteomics data was collected by laser-capture microdissection coupled mass spectrometry. Protein-protein networks, involving PR and ESR1 receptors as master regulators of decidualization, were built using String. Main results and the role of chance Initial morphological analyses of endometrial biopsies collected during the late secretory phase revealed gross anatomical defects in glandular morphology that were histologically confirmed. scRNA-seq revealed sPE-associated alterations in cell composition involving stromal and epithelial subtypes, denoting a higher proportion of cells expressing proliferative markers in the stroma (MMP11, SFRP1) and epithelium (IHH, EMID), and a near absent epithelial-stromal transition that is normally linked to decidualization. Further, abnormal abundance and gene dysregulation were detected in the three decidualized stages identified. Mapping cell-cell communication networks confirmed aberrant crosstalk among cell types involved in essential pathways (e.g., endoglin, WNT, SPP1). Spatial transcriptomic in a replication cohort of samples revealed a landscape of dysregulated genes in stromal, luminal and glandular enriched regions, corroborating sPE-associated DR. Laser capture microdissection/mass spectrometry of samples revealed differential protein expression at a global level and confirmed many of the scRNA-seq results, such as sPE-exclusive proteins related to proliferation and the absence of a stromal to epithelial transition at a pathway level. These data lend insights into potential molecular mechanisms underlying the pathogenesis of DR. Limitations, reasons for caution DR analysed in this work is associated with sPE but we do not know if this decidualization defect would be the same in other DR associated conditions such as endometriosis, recurrent pregnancy loss, or miscarriage. Wider implications of the findings Here we present the most comprehensive snapshot of DR to date, providing a full range of markers potentially responsible for this decidualization disorder linked to sPE. We concluded that stromal and epithelial cell populations are altered revealing a near absence of the stromal-epithelial transition, cellular crosstalk and glandular constitution. Trial registration number not aplicable

Differential Contributions of Fibroblast Subpopulations to Intercellular Communication in Eosinophilic Esophagitis.

Fibroblast heterogeneity remains undefined in eosinophilic esophagitis (EoE), an allergic inflammatory disorder complicated by fibrosis. We utilized publicly available single-cell RNA sequencing data (GSE201153) of EoE esophageal biopsies to identify fibroblast sub-populations, related transcriptomes, disease status-specific pathways and cell-cell interactions. IL13-treated fibroblast cultures were used to model active disease. At least 2 fibroblast populations were identified, F_A and F_B. Several genes including ACTA2 were more enriched in F_A. F_B percentage was greater than F_A and epithelial-mesenchymal transition upregulated in F_B vs. F_A in active and remission EoE. Epithelial-mesenchymal transition was also upregulated in F_B in active vs. remission EoE and TNF-α signaling via NFKB was downregulated in F_A. IL-13 treatment upregulated ECM-related genes more profoundly in ACTA2- fibroblasts than ACTA2+ myofibroblasts. After proliferating epithelial cells, F_B and F_A contributed most to cell-cell communication networks. ECM-Receptor interaction strength was stronger than secreted or cell-cell contact signaling in active vs. remission EoE and significant ligand-receptor pairs were driven mostly by F_B. This unbiased analysis identifies at least 2 fibroblast sub-populations in EoE in vivo, distinguished in part by ACTA2. Fibroblasts play a critical role in cell-cell interactions in EoE, most profoundly via ECM-receptor signaling via the F_B sub-group.

Single-cell sequencing of the substantia nigra reveals microglial activation in a model of MPTP.

N-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) is a neurotoxin widely used to induce PD models, but the effect of MPTP on the cells and genes of PD has not been fully elucidated. Single-nucleus RNA sequencing was performed in the Substantia Nigra (SN) of MPTP mice. UMAP analysis was used for the dimensionality reduction visualization of the SN in the MPTP mice. Known marker genes highly expressed genes in each cluster were used to annotate most clusters. Specific Differentially Expressed Genes (DEGs) and PD risk genes analysis were used to find MPTP-associated cells. GO, KEGG, PPI network, GSEA and CellChat analysis were used to reveal cell type-specific functional alterations and disruption of cell-cell communication networks. Subset reconstruction and pseudotime analysis were used to reveal the activation status of the cells, and to find the transcription factors with trajectory characterized. Initially, we observed specific DEGs and PD risk genes enrichment in microglia. Next, We obtained the functional phenotype changes in microglia and found that IGF, AGRN and PTN pathways were reduced in MPTP mice. Finally, we analyzed the activation state of microglia and revealed a pro-inflammatory trajectory characterized by transcription factors Nfe2l2 and Runx1. Our work revealed alterations in microglia function, signaling pathways and key genes in the SN of MPTP mice.

Single-cell transcriptome atlas of testes from mice with high-fat diets

Obesity is accompanied by multiple known health risks and increased morbidity, and obese men display reduced reproductive health. However, the impact of obesity on the testes at the molecular levels remain inadequately explored. This is partially attributed to the lack of monitoring tools for tracking alterations within cell clusters in testes associated with obesity. Here, we utilized single-cell RNA sequencing to analyze over 70,000 cells from testes of obese and lean mice, and to study changes related to obesity in non-spermatogenic cells and spermatogenesis. The Testicular Library encompasses all non-spermatogenic cells and spermatogenic cells spanning from spermatogonia to spermatozoa, which will significantly aid in characterizing alterations in cellular niches and the testicular microenvironment during high-fat diet (HFD)-induced obesity. This comprehensive dataset is indispensable for studying how HFD disrupts cell-cell communication networks within the testis and impacts alterations in the testicular microenvironment that regulate spermatogenesis. Being the inaugural dataset of single-cell RNA-seq in the testes of diet-induced obese (DIO) mice, this holds the potential to offer innovative insights and directions in the realm of single-cell transcriptomics concerning male reproductive injury associated with HFD.

DNA Reaction Circuits to Establish Designated Biological Functions in Multicellular Community.

In multicellular organisms, individual cells are coordinated through complex communication networks to accomplish various physiological tasks. Aiming to establish new biological functions in the multicellular community, we used DNA as the building block to develop a cascade of nongenetic reaction circuits to establish a dynamic cell-cell communication network. Utilizing membrane-anchored amphiphilic DNA tetrahedra (TDN) as the nanoscaffold, reaction circuits were incorporated into three unrelated cells in order to uniquely regulate their sense-and-response behaviors. As a proof-of-concept, this step enabled these cells to simulate significant biological events involved in T cell-mediated anticancer immunity. Such events included cancer-associated antigen recognition and the presentation of antigen-presenting cells (APCs), APC-facilitated T cell activation and dissociation, and T cell-mediated cancer targeting and killing. By combining the excellent programmability and molecular recognition ability of DNA, our cell-surface reaction circuits hold promise for mimicking and manipulating many biological processes.

Single-cell RNA-sequencing reveals the transcriptional landscape of lacrimal gland in GVHD mouse model

PurposeTo investigate the global transcriptional landscape of lacrimal gland cell populations in the GVHD mouse model. MethodsSingle-cell RNA sequencing and further bioinformatic analysis of dissociated lacrimal gland (LG) cells from the mouse model were performed. Parts of transcriptional results were confirmed by immunofluorescence staining. ResultsWe identified 23 cell populations belonging to 11 cell types. In GVHD LG, the proportion of acinar cells, myoepithelial cells, and endothelial cells was remarkably decreased, while T cells and macrophages were significantly expanded. Gene expression analysis indicated decreased secretion function, extracellular matrix (ECM) synthesis, and increased chemokines of myoepithelial cells. A newly described epithelial population named Lrg1high epithelial cells, expressing distinct gene signatures, was exclusively identified in GVHD LG. The fibroblasts exhibited an inflammation gene pattern. The gene pattern of endothelial cells suggested an increased ability to recruit immune cells and damaged cell-cell junctions. T cells were mainly comprised of Th2 cells and effective memory CD8+ T cells. GVHD macrophages exhibited a Th2 cell-linked pattern. ConclusionsThis single-cell atlas uncovered alterations of proportion and gene expression patterns of cell populations and constructed cell-cell communication networks of GVHD LG. These data may provide some new insight into understanding the development of ocular GVHD.

SEnSCA: Identifying possible ligand-receptor interactions and its application in cell-cell communication inference.

Multicellular organisms have dense affinity with the coordination of cellular activities, which severely depend on communication across diverse cell types. Cell-cell communication (CCC) is often mediated via ligand-receptor interactions (LRIs). Existing CCC inference methods are limited to known LRIs. To address this problem, we developed a comprehensive CCC analysis tool SEnSCA by integrating single cell RNA sequencing and proteome data. SEnSCA mainly contains potential LRI acquisition and CCC strength evaluation. For acquiring potential LRIs, it first extracts LRI features and reduces the feature dimension, subsequently constructs negative LRI samples through K-means clustering, finally acquires potential LRIs based on Stacking ensemble comprising support vector machine, 1D-convolutional neural networks and multi-head attention mechanism. During CCC strength evaluation, SEnSCA conducts LRI filtering and then infers CCC by combining the three-point estimation approach and single cell RNA sequencing data. SEnSCA computed better precision, recall, accuracy, F1 score, AUC and AUPR under most of conditions when predicting possible LRIs. To better illustrate the inferred CCC network, SEnSCA provided three visualization options: heatmap, bubble diagram and network diagram. Its application on human melanoma tissue demonstrated its reliability in CCC detection. In summary, SEnSCA offers a useful CCC inference tool and is freely available at https://github.com/plhhnu/SEnSCA.

SEGCECO: Subgraph Embedding of Gene expression matrix for prediction of CEll-cell COmmunication.

Recent advances in single-cell RNA sequencing technology have eased analyses of signaling networks of cells. Recently, cell-cell interaction has been studied based on various link prediction approaches on graph-structured data. These approaches have assumptions about the likelihood of node interaction, thus showing high performance for only some specific networks. Subgraph-based methods have solved this problem and outperformed other approaches by extracting local subgraphs from a given network. In this work, we present a novel method, called Subgraph Embedding of Gene expression matrix for prediction of CEll-cell COmmunication (SEGCECO), which uses an attributed graph convolutional neural network to predict cell-cell communication from single-cell RNA-seq data. SEGCECO captures the latent and explicit attributes of undirected, attributed graphs constructed from the gene expression profile of individual cells. High-dimensional and sparse single-cell RNA-seq data make converting the data into a graphical format a daunting task. We successfully overcome this limitation by applying SoptSC, a similarity-based optimization method in which the cell-cell communication network is built using a cell-cell similarity matrix which is learned from gene expression data. We performed experiments on six datasets extracted from the human and mouse pancreas tissue. Our comparative analysis shows that SEGCECO outperforms latent feature-based approaches, and the state-of-the-art method for link prediction, WLNM, with 0.99 ROC and 99% prediction accuracy. The datasets can be found at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE84133 and the code is publicly available at Github https://github.com/sheenahora/SEGCECO and Code Ocean https://codeocean.com/capsule/8244724/tree.

CPPLS-MLP: a method for constructing cell-cell communication networks and identifying related highly variable genes based on single-cell sequencing and spatial transcriptomics data.

In the growth and development of multicellular organisms, the immune processes of the immune system and the maintenance of the organism's internal environment, cell communication plays a crucial role. It exerts a significant influence on regulating internal cellular states such as gene expression and cell functionality. Currently, the mainstream methods for studying intercellular communication are focused on exploring the ligand-receptor-transcription factor and ligand-receptor-subunit scales. However, there is relatively limited research on the association between intercellular communication and highly variable genes (HVGs). As some HVGs are closely related to cell communication, accurately identifying these HVGs can enhance the accuracy of constructing cell communication networks. The rapid development of single-cell sequencing (scRNA-seq) and spatial transcriptomics technologies provides a data foundation for exploring the relationship between intercellular communication and HVGs. Therefore, we propose CPPLS-MLP, which can identify HVGs closely related to intercellular communication and further analyze the impact of Multiple Input Multiple Output cellular communication on the differential expression of these HVGs. By comparing with the commonly used method CCPLS for constructing intercellular communication networks, we validated the superior performance of our method in identifying cell-type-specific HVGs and effectively analyzing the influence of neighboring cell types on HVG expression regulation. Source codes for the CPPLS_MLP R, python packages and the related scripts are available at 'CPPLS_MLP Github [https://github.com/wuzhenao/CPPLS-MLP]'.

Single-cell profiling transcriptomic reveals cellular heterogeneity and cellular crosstalk in choroidal neovascularization model

Choroidal neovascularization (CNV) is a hallmark of neovascular age-related macular degeneration (nAMD) and a major contributor to vision loss in nAMD cases. However, the identification of specific cell types associated with nAMD remains challenging. Herein, we performed single-cell sequencing to comprehensively explore the cellular diversity and understand the foundational components of the retinal pigment epithelium (RPE)/choroid complex. We unveiled 10 distinct cell types within the RPE/choroid complex. Notably, we observed significant heterogeneity within endothelial cells (ECs), fibroblasts, and macrophages, underscoring the intricate nature of the cellular composition in the RPE/choroid complex. Within the EC category, four distinct clusters were identified and EC cluster 0 was tightly associated with choroidal neovascularization. We identified five clusters of fibroblasts actively involved in the pathogenesis of nAMD, influencing fibrotic responses, angiogenic effects, and photoreceptor function. Additionally, three clusters of macrophages were identified, suggesting their potential roles in regulating the progression of nAMD through immunomodulation and inflammation regulation. Through CellChat analysis, we constructed a complex cell-cell communication network, revealing the role of EC clusters in interacting with fibroblasts and macrophages in the context of nAMD. These interactions were found to govern angiogenic effects, fibrotic responses, and inflammatory processes. In summary, this study reveals noteworthy cellular heterogeneity in the RPE/choroid complex and provides valuable insights into the pathogenesis of CNV. These findings will open up potential avenues for deep understanding and targeted therapeutic interventions in nAMD.

Abstract 1587: Multimodal spatial transcriptomics uncover distinct tumor microenvironment states and cell-cell communication networks in molecular pancreatic cancer subtypes

Abstract The tumor microenvironment (TME) presents a complex ecosystem comprising a diversity of immune and stromal cell populations that influence tumor progression, drug delivery and therapy outcome. High levels of inter- and intra-tumor heterogeneity in TME state are driven by molecular tumor phenotypes. Pancreatic ductal adenocarcinoma (PDAC), one of the most lethal cancer types, displays a high genetic heterogeneity along with an immunosuppressive TME. However, it remains largely elusive how distinct TME states are mechanistically influenced, and which molecular processes dictate the emergence of different modes of immunosuppression within the TME of molecular PDAC subtypes.Here, we performed a systematic analysis of functional associations between the major molecular PDAC subtypes, the classical and mesenchymal subtype, and their TME states. We describe the TME composition and complex cell-cell communication networks within PDAC subtypes using a multimodal integration of spatial transcriptomics (ST) with complementary approaches, such as scRNA-seq, MS-based Secretomics and multiplexed histocytometry. We generated ST data sets (Visium) of a tumor cohort derived from a Kras-driven PDAC mouse model. To analyze TME composition as well as spatial niches and cell type communities, we computationally enhanced the spot-resolution of ST datasets, followed by cell type deconvolution and cell-cell communication analysis to identify subtype-specific TME communities and communication networks.To this end, we generated a large resource of PDAC mouse models which represent molecular subtypes of the disease and mimic the heterogeneity of TME states found in human PDAC cohorts. This analysis revealed that a set of subtype-specific secreted factors shape the immunosuppressive PDAC TME via direct and indirect communication networks with immunosuppressive myeloid and T cells in molecular PDAC subtypes. Multimodal ST analysis delineated spatial subtype-specific TME communities as well as spatial communication patterns. We functionally investigate the tumor cell intrinsic regulation of the identified subtype-specific secreted factors, providing potential therapeutic vulnerabilities for more effective combinatorial subtype-specific therapies including immunotherapeutic approaches. Citation Format: Stefanie Baerthel, Chiara Falcomatà, Vanessa Goelling, Daniele Lucarelli, Rushin Gindra, Constantin Schmitt, Jonathan Swietlik, Felix Meissner, Marc Schmidt-Supprian, Dieter Saur. Multimodal spatial transcriptomics uncover distinct tumor microenvironment states and cell-cell communication networks in molecular pancreatic cancer subtypes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1587.

Abstract 1152: Pan-cancer single-cell and subcellular characterization of lymphoid aggregates and tertiary lymphoid structures using high-plex spatial molecular imaging

Abstract Tertiary lymphoid structures (TLSs), clusters of immune cells that form in non-lymphoid tissues, are frequently identified in a wide range of solid tumors. They function as immunological “hubs”, driving anti-tumor responses. Previous studies have demonstrated that the presence of TLSs is often associated with improved responses to immunotherapy and superior clinical outcomes. Despite these insights, our understanding of their phenotypic diversity, spatial organization, intercellular communication, and interactions with cancer cells and the tumor microenvironment remains incomplete. Existing methods lack the resolution, depth, and scale required for a thorough understanding of these complex structures. We have obtained in-house and public spatial multi-omics data generated on various tissues across 9 different cancer types using the cutting-edge single-cell spatial transcriptomics and high-plex spatial molecular imaging platforms. We have developed innovative computational approaches for the detailed characterization of TLSs at single-cell and subcellular resolution and carried out an extensive analysis of lymphoid aggregates (LAs) and TLSs in tissue sections across these different solid cancer types. We defined the phenotypic state of each individual cell within TLSs including B/plasma cells, follicular helper/regulatory/stressed/exhausted T cells, follicular dendritic cells, fibroblasts and high endothelial venules. Then, we performed unbiased phenotyping and classification of TLSs based on their cellular states, compositions and organization patterns across various types of tissues. Additionally, we performed spatial neighborhood analysis, characterized the neighboring cells of each TLS and analyzed their cell-cell communication networks. Our approach allowed an unprecedented examination of the spatial phenotypes of TLSs in large, complex tissues at super resolution, in ways that were not previously described. We comprehensively characterized TLSs across different solid tumor types. Our analysis revealed a high degree of spatial and phenotypic heterogeneity in LAs and TLSs. We created a comprehensive spatial atlas of LAs and TLSs across solid tumor types, profiled TLSs at various maturation states with distinct cellular composition and organization patterns, and discovered new TLS states. Notably, we observed distinct communication networks associated with TLS phenotypic states. Our innovative methods and analytical approaches offer a more comprehensive way to study LAs and TLSs, enhancing detection capabilities and providing deeper insights into their spatial interaction and functional phenotypes. This research holds the potential to significantly advance our understanding of TLSs and their roles in immunobiology and immunotherapy responses across a broad range of cancers and diseases. Citation Format: Yunhe Liu, Yuanyuan Zhang, Guangchun Han, Guangsheng Pei, Kyung Serk Cho, Enyu Dai, Yanshuo Chu, Jiahui Jiang, Ansam Sinjab, Luisa M. Soto, Alejandra Serrano, Jianjun Gao, Humam Kadara, Catherine Fridman, Wolf Herve Fridman, Linghua Wang. Pan-cancer single-cell and subcellular characterization of lymphoid aggregates and tertiary lymphoid structures using high-plex spatial molecular imaging [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1152.

ICELLNET v2: a versatile method for cell-cell communication analysis from human transcriptomic data.

Several methods have been developed in the past years to infer cell-cell communication networks from transcriptomic data based on ligand and receptor expression. Among them, ICELLNET is one of the few approaches to consider the multiple subunits of ligands and receptors complexes to infer and quantify cell communication. In here, we present a major update of ICELLNET. As compared to its original implementation, we (i) drastically expanded the ICELLNET ligand-receptor database from 380 to 1669 biologically curated interactions, (ii) integrated important families of communication molecules involved in immune crosstalk, cell adhesion, and Wnt pathway, (iii) optimized ICELLNET framework for single-cell RNA sequencing data analyses, (iv) provided new visualizations of cell-cell communication results to facilitate prioritization and biological interpretation. This update will broaden the use of ICELLNET by the scientific community in different biological fields. ICELLNET package is implemented in R. Source code, documentation and tutorials are available on GitHub (https://github.com/soumelis-lab/ICELLNET).

Single-cell transcriptomics identifies senescence-associated secretory phenotype (SASP) features of testicular aging in human.

The male reproductive system experiences degradation with age, predominantly impacting the testes. Testicular aging can result in failure to produce physiological testosterone levels, normal sperm concentrations, or both. However, we cannot predict the onset of testicular aging in advance. Using single-cell RNA sequencing (scRNA-seq) from Gene Expression Omnibus (GEO) database, we conducted cell-cell communication network of human testis between older and young group, indicating Leydig cells' potential role in spermatogenesis microenvironment of aging testis. And we depicted the senescence-Associated Secretory Phenotype (SASP) features of aging testis by identifying differentially expressed senescence-associated secretory phenotype (SASP)-related genes between two group. Notably, IGFBP7 mainly expressed in Leydig cells of those differentially expressed SASP-related genes in aging testis. Furthermore, IGFBP7 protein located in the interstitial compartment of older mice confirmed by immunofluorescence and highly expressed in both human seminal plasma and mouse testis in the older group confirmed through Western blot. Together, our findings suggest that IGFBP7 may be a new biomarker of testicular aging.

Cell-cell communication network-based interpretable machine learning predicts cancer patient response to immune checkpoint inhibitors.

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment. However, only some patients respond to ICIs, and current biomarkers for ICI efficacy have limited performance. Here, we devised an interpretable machine learning (ML) model trained using patient-specific cell-cell communication networks (CCNs) decoded from the patient's bulk tumor transcriptome. The model could (i) predict ICI efficacy for patients across four cancer types (median AUROC: 0.79) and (ii) identify key communication pathways with crucial players responsible for patient response or resistance to ICIs by analyzing more than 700 ICI-treated patient samples from 11 cohorts. The model prioritized chemotaxis communication of immune-related cells and growth factor communication of structural cells as the key biological processes underlying response and resistance to ICIs, respectively. We confirmed the key communication pathways and players at the single-cell level in patients with melanoma. Our network-based ML approach can be used to expand ICIs' clinical benefits in cancer patients.

Characterization of CD4+ and CD8+ T cells responses in the mixed lymphocyte reaction by flow cytometry and single cell RNA sequencing.

The Mixed Lymphocyte Reaction (MLR) consists in the allogeneic co-culture of monocytes derived dendritic cells (MoDCs) with T cells from another donor. This in vitro assay is largely used for the assessment of immunotherapy compounds. Nevertheless, the phenotypic changes associated with lymphocyte responsiveness under MLR have never been thoroughly evaluated. Here, we used multiplex cytokine and chemokine assays, multiparametric flow cytometry and single cell RNA sequencing to deeply characterize T cells activation and function in the context of CD4+- and CD8+-specific MLR kinetics. We showed that CD4+ and CD8+ T cells in MLR share common classical markers of response such as polyfunctionality, increased proliferation and CD25 expression but differ in their kinetics and amplitude of activation as well as their patterns of cytokines secretion and immune checkpoints expression. The analysis of immunoreactive Ki-67+CD25+ T cells identified PBK, LRR1 and MYO1G as new potential markers of MLR response. Using cell-cell communication network inference and pathway analysis on single cell RNA sequencing data, we also highlighted key components of the immunological synapse occurring between T cells and the stimulatory MoDCs together with downstream signaling pathways involved in CD4+ and CD8+ T cells activation. These results provide a deep understanding of the kinetics of the MLR assay for CD4+ or CD8+ T cells and may allow to better characterize compounds impacting MLR and eventually identify new strategies for immunotherapy in cancer.

Bioengineered hydrogels enhance ex vivo preservation of patient-derived tumor explants for drug evaluation

Ex vivo patient-derived tumor slices (PDTS) are currently limited by short-term viability in culture. Here, we show how bioengineered hydrogels enable the identification of key matrix parameters that significantly enhance PDTS viability compared to conventional culture systems. As demonstrated using single-cell RNA sequencing and high-dimensional flow cytometry, hydrogel-embedded PDTS tightly preserved cancer, cancer-associated fibroblast, and various immune cell populations and subpopulations in the corresponding original tumor. Cell-cell communication networks within the tumor microenvironment, including immune checkpoint ligand-receptor interactions, were also maintained. Remarkably, our results from a co-clinical trial suggest hydrogel-embedded PDTS may predict sensitivity to immune checkpoint inhibitors (ICIs) in head and neck cancer patients. Further, we show how these longer term-cultured tumor explants uniquely enable the sampling and detection of temporal evolution in molecular readouts when treated with ICIs. By preserving the compositional heterogeneity and complexity of patient tumors, hydrogel-embedded PDTS provide a valuable tool to facilitate experiments targeting the tumor microenvironment.