Revealing cell-cell communication pathways with their spatially coupled gene programs.

Inference of cell-cell communication (CCC) provides valuable information in understanding the mechanisms of many important life processes. With the rise of spatial transcriptomics in recent years, many methods have emerged to predict CCCs using spatial information of cells. However, most existing methods only describe CCCs based on ligand-receptor interactions, but lack the exploration of their upstream/downstream pathways. In this paper, we proposed a new method to infer CCCs, called Intercellular Gene Association Network (IGAN). Specifically, it is for the first time that we can estimate the gene associations/network between two specific single spatially adjacent cells. By using the IGAN method, we can not only infer CCCs in an accurate manner, but also explore the upstream/downstream pathways of ligands/receptors from the network perspective, which are actually exhibited as a new panoramic cell-interaction-pathway graph, and thus provide extensive information for the regulatory mechanisms behind CCCs. In addition, IGAN can measure the CCC activity at single cell/spot resolution, and help to discover the CCC spatial heterogeneity. Interestingly, we found that CCC patterns from IGAN are highly consistent with the spatial microenvironment patterns for each cell type, which further indicated the accuracy of our method. Analyses on several public datasets validated the advantages of IGAN.

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.

Dynamic YAP expression in the non-parenchymal liver cell compartment controls heterologous cell communication.

INTRODUCTION: The Hippo pathway and its transcriptional effectors yes-associated protein (YAP) and transcriptional coactivator with PDZ-binding motif (TAZ) are targets for cancer therapy. It is important to determine if the activation of one factor compensates for the inhibition of the other. Moreover, it is unknown if YAP/TAZ-directed perturbation affects cell-cell communication of non-malignant liver cells. MATERIALS AND METHODS: To investigate liver-specific phenotypes caused by YAP and TAZ inactivation, we generated mice with hepatocyte (HC) and biliary epithelial cell (BEC)-specific deletions for both factors (YAPKO, TAZKO and double knock-out (DKO)). Immunohistochemistry, single-cell sequencing, and proteomics were used to analyze liver tissues and serum. RESULTS: The loss of BECs, liver fibrosis, and necrosis characterized livers from YAPKO and DKO mice. This phenotype was weakened in DKO tissues compared to specimens from YAPKO animals. After depletion of YAP in HCs and BECs, YAP expression was induced in non-parenchymal cells (NPCs) in a cholestasis-independent manner. YAP positivity was detected in subgroups of Kupffer cells (KCs) and endothelial cells (ECs). The secretion of pro-inflammatory chemokines and cytokines such as C-X-C motif chemokine ligand 11 (CXCL11), fms-related receptor tyrosine kinase 3 ligand (FLT3L), and soluble intercellular adhesion molecule-1 (ICAM1) was increased in the serum of YAPKO animals. YAP activation in NPCs could contribute to inflammation via TEA domain transcription factor (TEAD)-dependent transcriptional regulation of secreted factors. CONCLUSION: YAP inactivation in HCs and BECs causes liver damage, and concomitant TAZ deletion does not enhance but reduces this phenotype. Additionally, we present a new mechanism by which YAP contributes to cell-cell communication originating from NPCs.

Pancreatic cancer environment: from patient-derived models to single-cell omics.

Pancreatic cancer (PC) is a highly malignant cancer characterized by poor prognosis, high heterogeneity, and intricate heterocellular systems. Selecting an appropriate experimental model for studying its progression and treatment is crucial. Patient-derived models provide a more accurate representation of tumor heterogeneity and complexity compared to cell line-derived models. This review initially presents relevant patient-derived models, including patient-derived xenografts (PDXs), patient-derived organoids (PDOs), and patient-derived explants (PDEs), which are essential for studying cell communication and pancreatic cancer progression. We have emphasized the utilization of these models in comprehending intricate intercellular communication, drug responsiveness, mechanisms underlying tumor growth, expediting drug discovery, and enabling personalized medical approaches. Additionally, we have comprehensively summarized single-cell analyses of these models to enhance comprehension of intercellular communication among tumor cells, drug response mechanisms, and individual patient sensitivities.

Comparative analysis of cell-cell communication at single-cell resolution.

Inference of cell-cell communication from single-cell RNA sequencing data is a powerful technique to uncover intercellular communication pathways, yet existing methods perform this analysis at the level of the cell type or cluster, discarding single-cell-level information. Here we present Scriabin, a flexible and scalable framework for comparative analysis of cell-cell communication at single-cell resolution that is performed without cell aggregation or downsampling. We use multiple published atlas-scale datasets, genetic perturbation screens and direct experimental validation to show that Scriabin accurately recovers expected cell-cell communication edges and identifies communication networks that can be obscured by agglomerative methods. Additionally, we use spatial transcriptomic data to show that Scriabin can uncover spatial features of interaction from dissociated data alone. Finally, we demonstrate applications to longitudinal datasets to follow communication pathways operating between timepoints. Our approach represents a broadly applicable strategy to reveal the full structure of niche-phenotype relationships in health and disease.

Identification of cytokine-induced cell communications by pan-cancer meta-analysis.

Cancer immune responses are complex cellular processes in which cytokine-receptor interactions play central roles in cancer development and response to therapy; dysregulated cytokine-receptor communication may lead to pathological processes, including cancer, autoimmune diseases, and cytokine storm; however, our knowledge regarding cytokine-mediated cell-cell communication (CCI) in different cancers remains limited. The present study presents a single-cell and pan-cancer-level transcriptomics integration of 41,900 cells across 25 cancer types. We developed a single-cell method to actively express 62 cytokine-receptor pairs to reveal stable cytokine-mediated cell communications involving 84 cytokines and receptors. The correlation between the sample-based CCI profile and the interactome analysis indicates multiple cytokine-receptor modules including TGFB1, IL16ST, IL15, and the PDGF family. Some isolated cytokine interactions, such as FN1-IL17RC, displayed diverse functions within over ten single-cell transcriptomics datasets. Further functional enrichment analysis revealed that the constructed cytokine-receptor interaction map is associated with the positive regulation of multiple immune response pathways. Using public TCGA pan-cancer mutational data, co-mutational analysis of the cytokines and receptors provided significant co-occurrence features, implying the existence of cooperative mechanisms. Analysis of 10,967 samples from 32 TCGA cancer types revealed that the 84 cytokine and receptor genes are significantly associated with clinical survival time. Interestingly, the tumor samples with mutations in any of the 84 cytokines and receptors have a substantially higher mutational burden, offering insights into antitumor immune regulation and response. Clinical cancer stage information revealed that tumor samples with mutations in any of the 84 cytokines and receptors stratify into earlier tumor stages, with unique cellular compositions and clinical outcomes. This study provides a comprehensive cytokine-receptor atlas of the cellular architecture in multiple cancers at the single-cell level.

Advances in Intercellular Communication Mediated by Exosomal ncRNAs in Cardiovascular Disease.

Cardiovascular diseases are a leading cause of worldwide mortality, and exosomes have recently gained attention as key mediators of intercellular communication in these diseases. Exosomes are double-layered lipid vesicles that can carry biomolecules such as miRNAs, lncRNAs, and circRNAs, and the content of exosomes is dependent on the cell they originated from. They can be involved in the pathophysiological processes of cardiovascular diseases and hold potential as diagnostic and monitoring tools. Exosomes mediate intercellular communication, stimulate or inhibit the activity of target cells, and affect myocardial hypertrophy, injury and infarction, ventricular remodeling, angiogenesis, and atherosclerosis. Exosomes can be released from various types of cells, including endothelial cells, smooth muscle cells, cardiomyocytes, fibroblasts, platelets, adipocytes, immune cells, and stem cells. In this review, we highlight the communication between different cell-derived exosomes and cardiovascular cells, with a focus on the roles of RNAs. This provides new insights for further exploring targeted therapies in the clinical management of cardiovascular diseases.

Exploration of the molecular mechanism of intercellular communication in paediatric neuroblastoma by single-cell sequencing.

Neuroblastoma (NB) is an embryonic tumour that originates in the sympathetic nervous system and occurs most often in infants and children under 2 years of age. Moreover, it is the most common extracranial solid tumour in children. Increasing studies suggest that intercellular communication within the tumour microenvironment is closely related to tumour development. This study aimed to construct a prognosis-related intercellular communication-associated genes model by single-cell sequencing and transcriptome sequencing to predict the prognosis of patients with NB for precise management. Single-cell data from patients with NB were downloaded from the gene expression omnibus database for comprehensive analysis. Furthermore, prognosis-related genes were screened in the TARGET database based on epithelial cell marker genes through a combination of Cox regression and Lasso regression analyses, using GSE62564 and GSE85047 for external validation. The patients' risk scores were calculated, followed by immune infiltration analysis, drug sensitivity analysis, and enrichment analysis of risk scores, which were conducted for the prognostic model. I used the Lasso regression feature selection algorithm to screen characteristic genes in NB and developed a 21-gene prognostic model. The risk scores were highly correlated with multiple immune cells and common anti-tumour drugs. Furthermore, the risk score was identified as an independent prognostic factor for NB. In this study, I constructed and validated a prognostic signature based on epithelial marker genes, which may provide useful information on the development and prognosis of NB.

Starvation induces changes in abundance and small RNA cargo of extracellular vesicles released from Plasmodium falciparum infected red blood cells.

The lethal malaria parasite Plasmodium falciparum needs to constantly respond and adapt to changes within the human host in order to survive and transmit. One such change is composed of nutritional limitation, which is augmented with increased parasite loads and intimately linked to severe disease development. Extracellular vesicles released from infected red blood cells have been proposed as important mediators of disease pathogenesis and intercellular communication but whether important for the parasite response to nutritional availability is unknown. Therefore, we investigated the abundance and small RNA cargo of extracellular vesicles released upon short-term nutritional starvation of P. falciparum in vitro cultures. We show that primarily ring-stage parasite cultures respond to glucose and amino acid deprivation with an increased release of extracellular vesicles. Small RNA sequencing of these extracellular vesicles further revealed human miRNAs and parasitic tRNA fragments as the main constituent biotypes. Short-term starvations led to alterations in the transcriptomic profile, most notably in terms of the over-represented biotypes. These data suggest a potential role for extracellular vesicles released from P. falciparum infected red blood cells in the response to nutritional perturbations, their potential as prognostic biomarkers and point towards an evolutionary conserved role among protozoan parasites.

Decoding functional cell-cell communication events by multi-view graph learning on spatial transcriptomics.

Cell-cell communication events (CEs) are mediated by multiple ligand-receptor (LR) pairs. Usually only a particular subset of CEs directly works for a specific downstream response in a particular microenvironment. We name them as functional communication events (FCEs) of the target responses. Decoding FCE-target gene relations is: important for understanding the mechanisms of many biological processes, but has been intractable due to the mixing of multiple factors and the lack of direct observations. We developed a method HoloNet for decoding FCEs using spatial transcriptomic data by integrating LR pairs, cell-type spatial distribution and downstream gene expression into a deep learning model. We modeled CEs as a multi-view network, developed an attention-based graph learning method to train the model for generating target gene expression with the CE networks, and decoded the FCEs for specific downstream genes by interpreting trained models. We applied HoloNet on three Visium datasets of breast cancer and liver cancer. The results detangled the multiple factors of FCEs by revealing how LR signals and cell types affect specific biological processes, and specified FCE-induced effects in each single cell. We conducted simulation experiments and showed that HoloNet is more reliable on LR prioritization in comparison with existing methods. HoloNet is a powerful tool to illustrate cell-cell communication landscapes and reveal vital FCEs that shape cellular phenotypes. HoloNet is available as a Python package at https://github.com/lhc17/HoloNet.

ESICCC as a systematic computational framework for evaluation, selection, and integration of cell-cell communication inference methods.

Cell-cell communication (CCC) is critical for determining cell fates and functions in multicellular organisms. With the advent of single-cell RNA-sequencing (scRNA-seq) and spatial transcriptomics (ST), an increasing number of CCC inference methods have been developed. Nevertheless, a thorough comparison of their performances is yet to be conducted. To fill this gap, we developed a systematic benchmark framework called ESICCC to evaluate 18 ligand-receptor (LR) inference methods and five ligand/receptor-target inference methods using a total of 116 data sets, including 15 ST data sets, 15 sets of cell line perturbation data, two sets of cell type-specific expression/proteomics data, and 84 sets of sampled or unsampled scRNA-seq data. We evaluated and compared the agreement, accuracy, robustness, and usability of these methods. Regarding accuracy evaluation, RNAMagnet, CellChat, and scSeqComm emerge as the three best-performing methods for intercellular ligand-receptor inference based on scRNA-seq data, whereas stMLnet and HoloNet are the best methods for predicting ligand/receptor-target regulation using ST data. To facilitate the practical applications, we provide a decision-tree-style guideline for users to easily choose best tools for their specific research concerns in CCC inference, and develop an ensemble pipeline CCCbank that enables versatile combinations of methods and databases. Moreover, our comparative results also uncover several critical influential factors for CCC inference, such as prior interaction information, ligand-receptor scoring algorithm, intracellular signaling complexity, and spatial relationship, which may be considered in the future studies to advance the development of new methodologies.

The role of non-coding RNAs in extracellular vesicles in breast cancer and their diagnostic implications.

Breast Cancer (BC) is the most common form of cancer worldwide, responsible for 25% of cancers in women. Whilst treatment is effective and often curative in early BC, metastatic disease is incurable, highlighting the need for early detection. Currently, early detection relies on invasive procedures, however recent studies have shown extracellular vesicles (EVs) obtained from liquid biopsies may have clinical utility. EVs transport diverse bioactive cargos throughout the body, play major roles in intercellular communication and, importantly, mirror their cell of origin. In cancer cells, EVs alter the behaviour of the tumour microenvironment (TME), forming a bridge of communication between cancerous and non-cancerous cells to alter all aspects of cancer progression, including the formation of a pre-metastatic niche. Through gene regulatory frameworks, non-coding RNAs (ncRNAs) modulate vital molecular and cellular processes and can act as both tumour suppressors and oncogenic drivers in various cancer types. EVs transport and protect ncRNAs, facilitating their use clinically as liquid biopsies for early BC detection. This review summarises current research surrounding ncRNAs and EVs within BC, focusing on their roles in cancer progression through bi-directional communication with the microenvironment and their diagnostic implications. The role of EV ncRNAs in breast cancer. A representation of the different EV ncRNAs involved in tumourigenic processes in breast cancer. Pro-tumourigenic ncRNAs displayed in green and ncRNAs which inhibit oncogenic processes are shown in red.

miRNA-126a plays important role in myoblast and endothelial cell interaction.

Muscle satellite cells (SCs) are stem cells and the main players in skeletal muscle reconstruction. Since satellite cells are located near or in direct contact with blood vessels their niche is formed, inter alia, by endothelial cells. The cross-talk between satellite cells and endothelial cells determines quiescence or proliferation of these cells. However, little is known about the role of miRNA in these interactions. In the present study we identified miRNA that were up-regulated in SC-derived myoblasts treated with stromal derived factor-1 (SDF-1) and/or down-regulated in cells in which the expression of CXCR4 or CXCR7, that is, SDF-1 receptors, was silenced. SDF-1 is one of the important regulators of cell migration, mobilization, skeletal muscle regeneration, and angiogenesis. We hypothesized that selected miRNAs affect SC-derived myoblast fate and interactions with endothelial cells. We showed that miR-126a-3p inhibited both, myoblast migration and fusion. Moreover, the levels of Cxcl12, encoding SDF-1 and Ackr3, encoding CXCR7, were reduced by miR-126a-3p mimic. Interestingly, the miR-126a-3p mimic significantly decreased the level of numerous factors involved in myogenesis and the miR-126a-5p mimic increased the level of Vefga. Importantly, the treatment of endothelial cells with medium conditioned by miR-126-5p mimic transfected SC-derived myoblasts promoted tubulogenesis.

TimeTalk uses single-cell RNA-seq datasets to decipher cell-cell communication during early embryo development.

Early embryonic development is a dynamic process that relies on proper cell-cell communication to form a correctly patterned embryo. Early embryo development-related ligand-receptor pairs (eLRs) have been shown to guide cell fate decisions and morphogenesis. However, the scope of eLRs and their influence on early embryo development remain elusive. Here, we developed a computational framework named TimeTalk from integrated public time-course mouse scRNA-seq datasets to decipher the secret of eLRs. Extensive validations and analyses were performed to ensure the involvement of identified eLRs in early embryo development. Process analysis identified that eLRs could be divided into six temporal windows corresponding to sequential events in the early embryo development process. With the interpolation strategy, TimeTalk is powerful in revealing paracrine settings and studying cell-cell communication during early embryo development. Furthermore, by using TimeTalk in the blastocyst and blastoid models, we found that the blastoid models share the core communication pathways with the epiblast and primitive endoderm lineages in the blastocysts. This result suggests that TimeTalk has transferability to other bio-dynamic processes. We also curated eLRs recognized by TimeTalk, which may provide valuable clues for understanding early embryo development and relevant disorders.

Single-cell analysis of human prepuce reveals dynamic changes in gene regulation and cellular communications.

BACKGROUND: The cellular and molecular dynamics of human prepuce are crucial for understanding its biological and physiological functions, as well as the prevention of related genital diseases. However, the cellular compositions and heterogeneity of human prepuce at single-cell resolution are still largely unknown. Here we systematically dissected the prepuce of children and adults based on the single-cell RNA-seq data of 90,770 qualified cells. RESULTS: We identified 15 prepuce cell subtypes, including fibroblast, smooth muscle cells, T/natural killer cells, macrophages, vascular endothelial cells, and dendritic cells. The proportions of these cell types varied among different individuals as well as between children and adults. Moreover, we detected cell-type-specific gene regulatory networks (GRNs), which could contribute to the unique functions of related cell types. The GRNs were also highly dynamic between the prepuce cells of children and adults. Our cell-cell communication network analysis among different cell types revealed a set of child-specific (e.g., CD96, EPO, IFN-1, and WNT signaling pathways) and adult-specific (e.g., BMP10, NEGR, ncWNT, and NPR1 signaling pathways) signaling pathways. The variations of GRNs and cellular communications could be closely associated with prepuce development in children and prepuce maintenance in adults. CONCLUSIONS: Collectively, we systematically analyzed the cellular variations and molecular changes of the human prepuce at single-cell resolution. Our results gained insights into the heterogeneity of prepuce cells and shed light on the underlying molecular mechanisms of prepuce development and maintenance.

A Comparison of Cell-Cell Interaction Prediction Tools Based on scRNA-seq Data.

Computational prediction of cell-cell interactions (CCIs) is becoming increasingly important for understanding disease development and progression. We present a benchmark study of available CCI prediction tools based on single-cell RNA sequencing (scRNA-seq) data. By comparing prediction outputs with a manually curated gold standard for idiopathic pulmonary fibrosis (IPF), we evaluated prediction performance and processing time of several CCI prediction tools, including CCInx, CellChat, CellPhoneDB, iTALK, NATMI, scMLnet, SingleCellSignalR, and an ensemble of tools. According to our results, CellPhoneDB and NATMI are the best performer CCI prediction tools, among the ones analyzed, when we define a CCI as a source-target-ligand-receptor tetrad. In addition, we recommend specific tools according to different types of research projects and discuss the possible future paths in the field.

Exosomal miRNA-mediated intercellular communications and immunomodulatory effects in tumor microenvironments.

Extracellular communication, in other words, crosstalk between cells, has a pivotal role in the survival of an organism. This communication occurs by different methods, one of which is extracellular vesicles. Exosomes, which are small lipid extracellular vesicles, have recently been discovered to have a role in signal transduction between cells inside the body. These vesicles contain important bioactive molecules including lipids, proteins, DNA, mRNA, and noncoding RNAs such as microRNAs (miRNAs). Exosomes are secreted by all cells including immune cells (macrophages, lymphocytes, granulocytes, dendritic cells, mast cells) and tumor cells. The tumor microenvironment (TME) represents a complex network that supports the growth of tumor cells. This microenvironment encompasses tumor cells themselves, the extracellular matrix, fibroblasts, endothelial cells, blood vessels, immune cells, and non-cellular components such as exosomes and cytokines. This review aims to provide insights into the latest discoveries concerning how the immune system communicates internally and with other cell types, with a specific focus on research involving exosomal miRNAs in macrophages, dendritic cells, B lymphocytes, and T lymphocytes. Additionally, we will explore the role of exosomal miRNA in the TME and the immunomodulatory effect.

BCR-ABL1-driven exosome-miR130b-3p-mediated gap-junction Cx43 MSC intercellular communications imply therapies of leukemic subclonal evolution.

Rationale: In the bone marrow microenvironment (BMME), mesenchymal stem/stromal cells (MSCs) control the self-renewal of both healthy and cancerous hematopoietic stem/progenitor cells (HSPCs). We previously showed that in vivo leukemia-derived MSCs change neighbor MSCs into leukemia-permissive states and boost leukemia cell proliferation, survival, and chemotherapy resistance. But the mechanisms behind how the state changes are still not fully understood. Methods: Here, we took a reverse engineering approach to determine BCR-ABL1+ leukemia cells activated transcriptional factor C/EBPß, resulting in miR130a/b-3p production. Then, we back-tracked from clinical specimen transcriptome sequencing to cell co-culture, molecular and cellular assays, flow cytometry, single-cell transcriptome, and transcriptional regulation to determine the molecular mechanisms of BCR-ABL1-driven exosome-miR130b-3p-mediated gap-junction Cx43 MSC intercellular communications. Results: BCR-ABL1-driven exosome-miR130a/b-3p mediated gap-junction Cx43 (a.k.a., GJA1) BMSC intercellular communications for subclonal evolution in leukemic microenvironment by targeting BMSCs-expressed HLAs, thereby potentially maintaining BMSCs with self-renewal properties and reduced BMSC immunogenicity. The Cx43low and miR-130a/bhigh subclonal MSCs subsets of differentiation state could be reversed to Cx43high and miR-130a/blow subclones of the higher stemness state in Cx43-overexpressed subclonal MSCs. Both miR-130a and miR-130b might only inhibit Cx43 translation or degrade Cx43 proteins and did not affect Cx43 mRNA stability. The subclonal evolution was further confirmed by single-cell transcriptome profiling of MSCs, which suggested that Cx43 regulated their stemness and played normal roles in immunomodulation antigen processing. Thus, upregulated miR-130a/b promoted osteogenesis and adipogenesis from BMSCs, thereby decreasing cancer progression. Our clinical data validated that the expression of many genes in human major histocompatibility was negatively associated with the stemness of MSCs, and several immune checkpoint proteins contributing to immune escape in tumors were overexpressed after either miR-130a or miR-130b overexpression, such as CD274, LAG3, PDCD1, and TNFRSF4. Not only did immune response-related cytokine-cytokine receptor interactions and PI3K-AKT pathways, including EGR3, TNFRSF1B, but also NDRG2 leukemic-associated inflammatory factors, such as IFNB1, CXCL1, CXCL10, and CCL7 manifest upon miR-130a/b overexpression. Either BCR siRNAs or ABL1 siRNAs assay showed significantly decreased miR-130a and miR-130b expression, and chromatin immunoprecipitation sequencing confirmed that the regulation of miR-130a and miR-130b expression is BCR-ABL1-dependent. BCR-ABL1 induces miR-130a/b expression through the upregulation of transcriptional factor C/EBPß. C/EBPß could bind directly to the promoter region of miR-130b-3p, not miR-130a-3p. BCR-ABL1-driven exosome-miR130a-3p could interact with Cx43, and further impact GJIC in TME. Conclusion: Our findings shed light on how leukemia BCR-ABL1-driven exosome-miR130b-3p could interact with gap-junction Cx43, and further impact GJIC in TME, implications for leukemic therapies of subclonal evolution.

MiRNAs regulate cell communication in osteogenesis-angiogenesis coupling during bone regeneration.

Bone regeneration is a complex process that requires not only the participation of multiple cell types, but also signal communication between cells. The two basic processes of osteogenesis and angiogenesis are closely related to bone regeneration and bone homeostasis. H-type vessels are a subtype of bone vessels characterized by high expression of CD31 and EMCN. These vessels play a key role in the regulation of bone regeneration and are important mediators of coupling between osteogenesis and angiogenesis. Molecular regulation between different cell types is important for coordination of osteogenesis and angiogenesis that promotes bone regeneration. MiRNAs are small non-coding RNAs that predominantly regulate gene expression at the post-transcriptional level and are closely related to cell communication. Specifically, miRNAs transduce external stimuli through various cell signaling pathways and cause a series of physiological and pathological effects. They are also deeply involved in the bone repair process. This review focuses on three signaling pathways related to osteogenesis-angiogenesis coupling, as well as the miRNAs involved in these pathways. Elucidation of the molecular mechanisms governing osteogenesis and angiogenesis is of great significance for bone regeneration.

Unveiling the functional paradigm of exosome-derived long non-coding RNAs (lncRNAs) in cancer: based on a narrative review and systematic review.

BACKGROUND AND PURPOSE: The intricate mechanisms underlying intercellular communication within the tumor microenvironment remain largely elusive. Recently, attention has shifted towards exploring the intercellular signaling mediated by exosomal long non-coding RNAs (lncRNAs) within this context. This comprehensive systematic review aims to elucidate the functional paradigm of exosome-derived lncRNAs in cancer. MATERIALS AND METHODS: The review provides a comprehensive narrative of lncRNA definition, characteristics, as well as the formation, sorting, and uptake processes of exosome-derived lncRNAs. Additionally, it describes comprehensive technology for exosome research and nucleic acid drug loading. This review further systematically examines the cellular origins, functional roles, and underlying mechanisms of exosome-derived lncRNAs in recipient cells within the cancer setting. RESULTS: The functional paradigm of exosome-derived lncRNAs in cancer mainly depends on the source cells and sorting mechanism of exosomal lncRNAs, the recipient cells and uptake mechanisms of exosomal lncRNAs, and the specific molecular mechanisms of lncRNAs in recipient cells. The source cells of exosomal lncRNAs mainly involved in the current review included tumor cells, cancer stem cells, normal cells, macrophages, and cancer-associated fibroblasts. CONCLUSION: This synthesis of knowledge offers valuable insights for accurately identifying exosomal lncRNAs with potential as tumor biomarkers. Moreover, it aids in the selection of appropriate targeting strategies and preclinical models, thereby facilitating the clinical translation of exosomal lncRNAs as promising therapeutic targets against cancer. Through a comprehensive understanding of the functional role of exosome-derived lncRNAs in cancer, this review paves the way for advancements in personalized medicine and improved treatment outcomes.