Ligand-receptor Pairs Research Articles

Single-cell RNA sequencing identifies endothelial-derived HBEGF as promoting pancreatic beta cell proliferation in mice via the EGFR-Kmt5a-H4K20me pathway.

Pancreatic beta cell mass is dynamically regulated in response to increased physiological and pathological demands. Understanding the mechanisms that control physiological beta cell proliferation could provide valuable insights into novel therapeutic approaches to diabetes. Here, we aimed to analyse the intracellular and extracellular signalling pathways involved in regulating the physiological proliferation of beta cells using single-cell RNA-seq (scRNA-seq) and in vitro functional assays. Islets isolated from nulliparous mice, mice at different time points of gestation and mice at day 4 after delivery were analysed using scRNA-seq. Bioinformatics analyses of scRNA-seq data were performed to determine the heterogeneous transcriptomic characteristics of beta cells and to identify the proliferating subpopulation. CellChat was used to analyse cell-cell communication and identify the ligand-receptor pairs between beta cell subclusters as well as between non-beta cells and proliferating beta cells. In vitro functional assays were conducted in mouse and rat beta cell lines and isolated mouse primary islets to validate the role of Kmt5a- mono-methylation of histone H4 at lysine 20 (H4K20me) signalling and endothelial-derived heparin-binding EGF-like growth factor (HBEGF) in beta cell proliferation. Of 43,724 endocrine and non-endocrine cells within islets analysed by scRNA-seq, 15,569 beta cells were clustered into eight distinct populations, each exhibiting unique heterogeneity. A proliferating beta cell subcluster was identified that highly expressed the histone methyltransferase Kmt5a. Activation of Kmt5a-H4K20me signalling upregulated the expression of Cdk1 and promoted beta cell proliferation. The crosstalk between endothelial cells and the proliferating beta cell subcluster, mediated by the HBEGF-EGF receptor (EGFR) ligand-receptor interaction, increased as beta cell mass expanded. HBEGF increased the expression levels of genes involved in the cell cycle and promoted beta cell proliferation by regulating the Kmt5a-H4K20me signalling pathway. Our study demonstrates that, under physiological conditions, endothelial-derived HBEGF regulates beta cell proliferation through the Kmt5a-H4K20me signalling pathway, which may serve as a potential target to promote beta cell expansion and treat diabetes. The scRNA-seq and RNA-seq datasets are available from the Gene Expression Omnibus (GEO) using the accession numbers GSE278860 and GSE278861, respectively.

DeepDoublet identifies neighboring cell-dependent gene expression

Cells interact with each other for proper function and homeostasis. Often, co-expression of ligand-receptor pairs from the single-cell RNAseq (scRNAseq) has been used to identify interacting cell types. Recently, RNA sequencing of physically interacting multi-cells has been used to identify interacting cell types without relying on co-expression of ligand-receptor pairs. This opens a new avenue to study the expression of interacting cell types. We present DeepDoublet, a deep-learning-based tool to decompose the transcriptome of physically interacting two cells (or doublet) into two sets of transcriptome. Applying DeepDoublet to the doublets of hepatocyte and liver endothelial cells (LECs), we successfully decomposed into the transcriptome of each cell type. Especially, DeepDoublet identified specific expression of hepatocytes when they are interacting with LECs. Among them was Angptl3 which has a role in blood vessel formation. DeepDoublet is a tool to identify neighboring cell-dependent gene expression.

Integrative multi-omics analysis reveals a novel subtype of hepatocellular carcinoma with biological and clinical relevance

BackgroundHepatocellular carcinoma (HCC) is a highly heterogeneous tumor, and the development of accurate predictive models for prognosis and drug sensitivity remains challenging.MethodsWe integrated laboratory data and public cohorts to conduct a multi-omics analysis of HCC, which included bulk RNA sequencing, proteomic analysis, single-cell RNA sequencing (scRNA-seq), spatial transcriptomics sequencing (ST-seq), and genome sequencing. We constructed a tumor purity (TP) and tumor microenvironment (TME) prognostic risk model. Proteomic analysis validated the TP-TME-related signatures. Joint analysis of scRNA-seq and ST-seq revealed characteristic clusters associated with TP high-risk subtypes, and immunohistochemistry confirmed the expression of key genes. We conducted functional enrichment analysis, transcription factor activity inference, cell-cell interaction, drug efficacy analysis, and mutation information analysis to identify a novel subtype of HCC.ResultsOur analyses constructed a robust HCC prognostic risk prediction model. The patients with TP-TME high-risk subtypes predominantly exhibit hypoxia and activation of the Wnt/beta-catenin, Notch, and TGF-beta signaling pathways. Furthermore, we identified a novel subtype, XPO1+Epithelial. This subtype expresses signatures of the TP risk subtype and aligns with the biological behavior of high-risk patients. Additional analyses revealed that XPO1+Epithelial is influenced primarily by fibroblasts via ligand-receptor interactions, such as FN1-(ITGAV+ITGB1), and constitute a significant component of the TP-TME subtype. Moreover, XPO1+Epithelial interact with monocytes/macrophages, T/NK cells, and endothelial cells through ligand-receptor pairs, including MIF-(CD74+CXCR4), MIF-(CD74+CD44), and VEGFA-VEGFR1R2, respectively, thereby promoting the recruitment of immune-suppressive cells and angiogenesis. The ST-seq cohort treated with Tyrosine Kinase Inhibitors (TKIs) and Programmed Cell Death Protein 1 (PD-1) presented elevated levels of TP and TME risk subtype signature genes, as well as XPO1+Epithelial, T-cell, and endothelial cell infiltration in the treatment response group. Drug sensitivity analyses indicated that TP-TME high-risk subtypes, including sorafenib and pembrolizumab, were associated with sensitivity to multiple drugs. Further exploratory analyses revealed that CTLA4, PDCD1, and the cancer antigens MSLN, MUC1, EPCAM, and PROM1 presented significantly increase expression levels in the high-risk subtype group.ConclusionsThis study constructed a robust prognostic model for HCC and identified novel subgroups at the single-cell level, potentially assisting in the assessment of prognostic risk for HCC patients and facilitating personalized drug therapy.

Schwann Cell-Mediated M2-Like Macrophage Polarization in Rhabdomyosarcoma.

To investigate the cellular components and immunological characteristics of the head and neck rhabdomyosarcoma (RMS) microenvironment. We conducted single-cell transcriptomics to analyze the cellular components of the RMS microenvironment. CellChat was utilized for analyzing intercellular interactions. The cancer genome atlas database was used for validation. CIBERSORT was applied for immune infiltration profiling. Functional enrichment analyses were performed using the Kyoto Encyclopedia of Genes and Genomes. Gene set scores were calculated using single-sample gene set enrichment analysis. Subcutaneous allograft models and bulk RNA sequencing were used for validation. Flow cytometry and immunohistochemistry were used to identify M2-like macrophages. Our findings revealed an extremely low presence of neutrophils in RMS samples compared with normal sample. RMS sample with high Schwann cell infiltration exhibited an increase in M2-like macrophage infiltration. Receptor-ligand pairs, specifically MIF-CD74 and PTN-SDC3, were identified between Schwann cells and M2-like macrophages. In the RMS sample characterized by significant Schwann cell infiltration, M2-like macrophages demonstrate robust expression of axon guidance factors and are enriched in the axon guidance pathway. Our study provides valuable insights into the microenvironment and immunological characteristics of RMS, offering crucial information for further research and potential therapeutic strategies.

Spatial Transcriptome and Single Nucleus Transcriptome Sequencing Reveals Tetrahydroxy Stilbene Glucoside Promotes Ovarian Organoids Development Through the Vegfa-Ephb2 Pair.

Ovarian dysfunction is a major factor leading to female infertility. Understanding how to improve or reshape ovarian function has become an important entry point for preventing and treating female infertility caused by ovarian dysfunction. Here, plant-derived compounds are screened for in vitro activity upon ovarian organoids derived from feeder-free female germline stem cells. Tetrahydroxy stilbene glucoside (TSG) is found to promote the development of ovarian organoids. Single nucleus transcriptome sequencing and spatial transcriptome sequencing are used to establish a comprehensive spatiotemporal map to elucidate the role of TSG in ovarian organoid development, encompassing cell types and subtypes, transcription factors, pseudo-time sequence, and cell communication dynamics. This analysis indicates that TSG promotes ovarian organoid development through the vascular endothelial growth factor A-Eph receptor B2 ligand-receptor pair between granulosa cells and oocytes. This study has enhanced the understanding of the mechanisms of ovarian organoid development, establishes a technical platform for screening compounds for treating infertility and related diseases, and lays a foundation for clinically applying plant-derived compounds.

Single-cell RNA Sequencing Analysis Reveals the Role of Cancerassociated Fibroblasts in Skin Melanoma.

Mechanism of fibroblasts in skin melanoma (SKME) revealed by single-cell RNA sequencing data. SKME is responsible for more than 80% of skin-related cancer deaths. Cancer-associated fibroblasts (CAFs) generate inflammatory factors, growth factors and extracellular matrix proteins to facilitate cancer cell growth, metastasis, drug resistance and immune exclusion. However, molecular mechanisms of CAFs in SKME are still lacking. Our goal was to reveal the role of CAFs in SKME. We downloaded the single-cell RNA sequencing (scRNA-seq) dataset from the Gene Expression Omnibus (GSE215120) database. Then, the Seurat package was applied to analyze the single-cell atlas of SKME data, and cell subsets were annotated with the CellMarker database. The molecular mechanisms of CAFs in SKME were disclosed via differential gene expression and enrichment analysis, Cellchat and SCENIC methods. Using scRNA-seq data, three SKME cases were used and downscaled and clustered to identify 11 cell subgroups and 5 CAF subsets. The enrichment of highly expressed genes among the 5 CAF subsets suggests that cell migration-inducing hyaluronan-binding protein (CEMIP) + fibroblasts and naked cuticle homolog 1 (NKD1)+ fibroblasts were closely associated with epithelial to mesenchymal transition. Cellchat analysis revealed that CAF subpopulations promoted melanocyte proliferation through Jagged1 (JAG1)-Notch homolog 1 (NOTCH1), JAG1-NOTCH3 and migration through pleiotrophin (PTN)-syndecan-3 (SDC3) receptor-ligand pairs. The SCENIC analysis identified that most of the transcription factors in each CAF subpopulation played a certain role in the metastasis of melanoma and were highly expressed in metastatic SKME samples. Specifically, we observed that CEMIP+ fibroblasts and NKD1+ fibroblasts had potential roles in participating in immune therapy resistance. Collectively, we uncovered a single-cell atlas of SKME and revealed the molecular mechanisms of CAFs in SKME development, providing a base for immune therapy and prognosis assessment. Our study reveals that 5 CAFs in SKME have a promoting effect on melanocyte proliferation and metastasis. More importantly, CEMIP+ fibroblasts and NKD1+ fibroblasts displayed close connections with immune therapy resistance. These findings help provide a good basis for future immune therapy and prognosis assessment targeting CAFs in SKME.

Crosstalk Between Cancer-associated Fibroblasts and Myeloid Cells Shapes the Heterogeneous Microenvironment of Gastric Cancer.

Targeted therapies have improved the clinical outcomes of most patients with cancer. However, the heterogeneity of gastric cancer remains a major hurdle for precision treatment. Further investigations into tumor microenvironment heterogeneity are required to resolve these problems. In this study, bioinformatic analyses, including metabolism analysis, pathway enrichment, differentiation trajectory inference, regulatory network construction, and survival analysis, were applied to gain a comprehensive understanding of tumor microenvironment biology within gastric cancer using single-cell RNA-seq and public datasets and experiments were carried out to confirm the conclusions of these analyses. We profiled heterogeneous single-cell atlases and identified eight cell populations with differential expression patterns. We identified two cancer-associated fibroblasts (CAFs) subtypes, with particular emphasis on the role of inflammatory cancer-associated fibroblasts (iCAFs) in EMT and lipid metabolic crosstalk within the tumor microenvironment. Notably, we detected two differentiation states of iCAFs that existed in different tissues with discrepant expression of genes involved in immuno-inflammation or ECM remodeling. Moreover, investigation of tumor-infiltrating myeloid cells has revealed the functional diversity of myeloid cell lineages in gastric cancer. Of which a proliferative cell lineage named C1QC+MKI67+TAMs was recognized with high immunosuppressive capacities, suggesting it has immune suppression and cell proliferation functions in the tumor niche. Finally, we explored regulatory networks based on ligand-receptor pairs and found crucial pro-tumor crosstalk between CAFs and myeloid cells in the tumor microenvironment (TME). These findings provide insights for future cancer treatments and drug discovery.

Competitive binding of small antagonistic peptides to the OsER1 receptor optimizes rice panicle architecture.

Rice panicle architecture is a pivotal trait that strongly contributes to grain yield. Small peptide ligands from the OsEPF/EPFL family synergistically control panicle architecture by recognition of the OsER1 receptor and subsequent activation of the OsMKKK10-OsMKK4-OsMPK6 cascade, indicating that specific ligand-receptor pairs orchestrate rice panicle development. However, how small homologous peptides fine-tune organ morphogenesis by targeting a common receptor remains elusive. Here, we report that the small peptide OsEPFL5 acts as a ligand of the OsER1 receptor that inactivates the OsMKKK10-OsMKK4-OsMPK6 cascade, suggesting that OsEPFL5 plays the opposite role to that of the OsEPFL6/7/8/9 subfamily in regulating spikelet number per panicle and grain size. Notably, OsEPFL5 competitively replaces the OsEPFL6, OsEPFL7, OsEPFL8, or OsEPFL9 binding to the OsER1 receptor, exposing antagonistic competition between small homologous peptides. Specifically enhancing expression of OsEPFL5 significantly improves grain yield by suppressing functions of the ligand-receptor pairs of OsEPFL6-OsER1, OsEPFL7-OsER1, OsEPFL8-OsER1, and OsEPFL9-OsER1, suggesting that competitive binding to the OsER1 receptor by small antagonistic peptides can optimize rice panicle architecture. Our findings elucidate how a receptor agonist and antagonist define inductive and inhibitory cues to shape rice panicle architecture, thus providing a new method of rationally breaking yield trait coupling by manipulating small antagonistic peptides.

THGB: predicting ligand-receptor interactions by combining tree boosting and histogram-based gradient boosting

Ligand-receptor interaction (LRI) prediction has great significance in biological and medical research and facilitates to infer and analyze cell-to-cell communication. However, wet experiments for new LRI discovery are costly and time-consuming. Here, we propose a computational model called THGB to uncover new LRIs. THGB first extracts feature information of Ligand-Receptor (LR) pairs using iFeature. Next, it adopts a tree boosting model to obtain representative LR features. Finally, it devises the histogram-based gradient boosting model to capture high-quality LRIs. To assess the THGB performance, we compared it with three new LRI prediction models (i.e., CellEnBoost, CellGiQ, and CellComNet) and one classical protein-protein interaction inference model PIPR. The results demonstrated that THGB achieved the best overall predictions in terms of six evaluation indictors (i.e., precision, recall, accuracy, F1-score, AUC, and AUPR). To measure the effect of LR feature selection on the prediction, THGB was compared with four feature selection methods (i.e., PCA, NMF, LLE, and TSVD). The results showed that the tree boosting model was more appropriate to select representative LR features and improve LRI prediction. We also conducted ablation study and found that THGB with feature selection outperformed THGB without feature selection. We hope that THGB is a useful tool to find new LRIs and further infer cell-to-cell communication.

ScRNA-Seq Analysis of Tongue Tissues in Chronic Hyperplastic Candidiasis.

Chronic hyperplastic candidiasis (CHC) is a rare but severe subtype of oral candidiasis distinguished by its potential malignant transformation and suboptimal response to antifungal therapies. However, the cells and mechanisms that play key roles in this process remain unclear. Therefore, we performed the first single-cell RNA sequencing (scRNA-seq) analysis of CHC-affected tongue tissues to reveal the microenvironmental changes and immunological etiology of CHC. First, the features of CHC lesions manifesting as thickening and hardening nodular lesions, including their pathological and microbiological characteristics, were elucidated. Then, a comprehensive cellular atlas and distinct immune landscape in CHC compared with healthy tissues were characterized using scRNA-seq, highlighting significant modifications in the cell number and functionality of fibroblasts and T/NK cells. Importantly, the central role of fibroblasts in cell-cell interactions in CHC was hinted, and possible ligand-receptor pairs mainly associated with inflammation and carcinogenesis were identified. Moreover, it was revealed that significant functional activation of fibroblasts, related to the activation of the epithelial-mesenchymal transition pathways and increased expression of collagen I, matrix metalloproteinase 1 (MMP1), and MMP2, could be a hallmark of CHC, correlating with CHC's clinical characteristics of tongue hardening and intense inflammation. Notably, there is sequencing evidence of the recruitment of CD8+Tex cells and activation of PD-1 and TIGIT immune checkpoint pathways. Moreover, cDC_LAMP3 cells exhibited high CD274 expression, suggesting immune exhaustion and an increased susceptibility to carcinogenesis. This pioneering study provides valuable insights into CHC pathogenesis and immune responses, enhancing our understanding of potential therapeutic strategies.

Abstract B016: Utilizing gene expression profiles (GEP) to assess tumor microenvironment (TME) and response to immunotherapy

Abstract Background: Despite the success of anti-PD-1/PD-L1 immunotherapies, outcomes for lung cancer patients remain suboptimal. There is a critical need to incorporate multi-omics data focused on the tumor microenvironment (TME) to enhance patient selection and treatment individualization. This study aimed to identify predictive and prognostic biomarkers of immunotherapy response by characterizing transcriptional profiles of lung adenocarcinoma patients who underwent genomic profiling at diagnosis. Methods: RNA sequencing data were obtained from 68 lung adenocarcinoma patients who underwent next-generation sequencing with CARIS at our institution. We analyzed gene expression profiles (GEP) comprising 18 inflammatory genes associated with antigen presentation, chemokine expression, cytolytic activity, and adaptive immune resistance, identified as potential biomarkers for immune checkpoint inhibitor (ICI) response (Cristescu et al., 2018). The genes included were CCL5, CD27, CD274 (PD-L1), CD276 (B7-H3), CD8A, CMKLR1, CXCL9, CXCR6, HLA-DQA1, HLA-DRB1, HLA-E, IDO1, LAG3, NKG7, PDCD1LG2 (PD-L2), PSMB10, STAT1, and TIGIT. GEP scores were calculated, and hierarchical clustering identified tumor subsets with similar GEPs. Gene set variation analysis was conducted to assess enrichment of cell-cell interaction activities of specific ligand-receptor pairs of immune checkpoint genes, partially overlapping with the 18 GEP genes. Results: Hierarchical clustering identified four distinct GEP clusters: "T cell-inflamed GEP," "T cell-non-inflamed GEP high," "T cell-non-inflamed GEP medium," and "T cell-non-inflamed low GEP," with average scores of 0.18 (N=9, 13%), 0.11 (N=29, 43%), 0.08 (N=19, 28%), and 0.04 (N=11, 16%), respectively. The gene scores among these clusters showed significant differences (P = 3.3e-09). Additionally, analysis of specific ligand-receptor pairs of immune checkpoint genes (PD1/PD-L1, PD-L2; CTLA4/CD28, CD80, CD86; ICOS/ICOSLG; TIM3/GAL9; SIRP1/CD47) showed consistent positive enrichment in the “T cell-inflamed” cluster, with no or negative enrichment in the “T cell-non-inflamed” clusters. This suggests active immune checkpoint interactions in clusters with high GEP scores. Conclusion: We identified four different clusters among tissues from patients with NSCLC based on GEP scoring highlighting differences in immune activation and TME makeup, which may play a role in predicting response to immunotherapies. Our results suggest that GEP may provide information on identifying optimal immunotherapeutic approaches based on TME. Our findings underscore the importance of using biomarker-guided strategies to improve patient selection for precision immunotherapy approaches in lung cancer. Citation Format: Changde Cheng, Doug Welsch, Kayla F. Goliwas, Jessy Deshane, Sameer Deshmukh, Sanad Ahlushki, Yanis Boumber, Darshan Shimoga Chandrashekar, Alexander C. Mackinnon, Aakash Desai. Utilizing gene expression profiles (GEP) to assess tumor microenvironment (TME) and response to immunotherapy [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr B016.

Abstract IA019: Regulation of EMT tumor states by stromal cells

Abstract Epithelial-to-mesenchymal transition (EMT) is a reversible process during which epithelial cells lose their epithelial characteristics and acquire mesenchymal features, that are important for tumor initiation, progression, stemness, metastasis, and therapy resistance. Different EMT states, each with distinct functional properties, have been identified across various tumor models. These EMT states reside within specific physical niches, characterized by unique stromal cell populations. Understanding the cellular interactions within the tumor microenvironment (TME) and their influence on EMT could lead to novel therapeutic strategies. To understand how the TME regulates the distinct tumor states, we performed single-cell RNA sequencing of the tumor cells and their TME in mouse cancer models presenting EMT. We identified distinct subsets of cancer-associated fibroblasts (CAFs), macrophages, neutrophils, endothelial cells, pericytes, adipocytes, dendritic cells, mast cells, Schwann cells, and T cells in different tumor types. To unravel how TME-tumor cell interactions regulates EMT, we used different bioinformatic approaches to identify ligand-receptor pairs that are likely to organize the tumor niche and to regulate tumor transition states. In vitro treatment of tumor cells with some of these ligands demonstrated their EMT-promoting effects. These findings provide novel mechanistic insights on the crosstalk between tumor cells and the surrounding TME, that may have important implications for anti-cancer therapy. Citation Format: Cédric Blanpain. Regulation of EMT tumor states by stromal cells [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr IA019.

Abstract C025: Identification of cell-cell signaling programs across the tumor-tumor microenvironment ecosystem and associated with clinical status in neoadjuvant osimertinib treated patient samples revealed by spatial profiling

Abstract Lung cancer is the leading cause of cancer mortality, and despite improvements in treatment, tumors typically respond incompletely and resume growth after acquisition of drug resistance. Recent completion of a neoadjuvant osimertinib Phase II trial treating patients with surgically resectable stage I-IIIA EGFR-mutated non-small cell lung cancer (EGFRm NSCLC) (NCT03433469) (Blakely et. Al, JCO 2024) has highlighted the importance of further identifying non-genomic mechanisms of persistence and resistance to targeted therapy. Here we analyzed these patient samples to identify transcriptionally regulated signaling patterns enriched at Residual Disease (RD) after neoadjuvant osimertinib treatment compared to treatment naïve samples (TN), as well as signaling patterns enriched at RD in patients who ultimately develop disease recurrence after surgical resection compared to those who remain disease-free. Spatially resolved transcriptomic sequencing was performed, using the 10X Genomics Visium platform, on 36 tissue sections (n=9 TN, n=19 RD, n=4 Progressive Disease (PD), n=4 Tumor Adjacent Normal), from 25 patients. TN and PD samples were from standard-of-care surgical resections. 18 of 19 RD samples were from NCT03433469. The Visium array spots that tile the sequencing capture area are 55 µm in diameter, and thus can contain an estimated 1-10 cells within each array spot. After quality control, 91,582 array spots remained for downstream analysis. We identified high confidence tumor array spots annotated both as “Cancer” by a board-certified pathologist and with tumor characteristic copy number variations. Through dimensionality reduction clustering, we identified 10 major array spot clusters, including the high confidence tumor array spot cluster. These clusters were further subset into 44 high resolution clusters of array spot niches, 32 of which were shared across at least nine patients. Because array spots are not single-cell resolution, these niches represent spots with similar mixed cell type composition and transcriptional signatures. We identified significant increases in the CCL14+ Endothelial Cell Niche, CXCL2+ Endothelial Cell Niche, Lymphocytes + Endothelial Niche, and CXCL12+ Fibroblast Niche in RD samples compared to TN. We identified a cell signaling program defined by spatially co-expressed ligand-receptor pairs associated with focal adhesion, enriched in PD samples. This same pattern was enriched in RD samples from patients who had recurrent disease after surgical resection compared to RD samples from patients who remained disease free. These data describe an increase in immune trafficking in RD samples, as well as identify an EGFR- alternative signaling pathway correlating with osimertinib resistance. Identification of spatially resolved, differential architectural organization and signaling patterns in RD and PD states will expand our understanding of targeted therapy resistance in EGFRm NSCLC, with the potential to identify additional clinically actionable targets. Citation Format: Whitney Tamaki, Daniel L. Kerr, Wei Wu, Grant Eilers, Anatoly Urisman, Yu-Ting Chou, Philippe Gui, Shigeki Nanjo, Johannes R. Kratz, David M. Jablons, Trever G. Bivona, Collin M. Blakely. Identification of cell-cell signaling programs across the tumor-tumor microenvironment ecosystem and associated with clinical status in neoadjuvant osimertinib treated patient samples revealed by spatial profiling [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr C025.

Single-cell data revealed the regulatory mechanism of TNK cell heterogeneity in liver metastasis from gastric cancer

AimThe present work set out to classify cell subpopulations related to liver metastasis from gastric cancer (GC) and the mechanisms of their interactions with other immune cell subpopulations.BackgroundGC is characterized by a high degree of heterogeneity and liver metastasis. Exploring the mechanism of liver metastasis of GC from the perspective of heterogeneity of the tumor microenvironment (TME) might help improve the efficacy of GC treatment.ObjectiveBased on the cellular subpopulation characteristics of GC with liver metastasis, the regulatory mechanisms contributing to GC progression were analyzed, with special focuses on the roles of signaling pathways, transcription factors (TFs) and ligand–receptor pairs.MethodsThe GSE163558 dataset was downloaded from the Gene Expression Omnibus (GEO) database to collect single-cell transcriptomic data of GC patients and their metastasis groups for cell clustering and relevant analyses. Differentially expressed genes (DEGs) in the GC and GC liver metastasis groups were screened and subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. SCENIC analysis was used to mine TFs that affected cellular subpopulations during liver metastasis from GC. The relative expression levels of TFs in GC were determined using qRT-PCR. Transwell and wound healing assays were utilized to verify the regulation of the TFs on the migration and invasion of GC cells. Interaction network between the cellular subpopulations was developed applying CellChat.ResultsSingle-cell clustering was performed to group six major cell subpopulations, namely, Myeloid cells, B cells, Mast cells, Epithelial cells, Fibroblasts, and TNK cells, among which the number of TNK cells was significantly increased in the GC liver metastasis group. Differentially enriched pathways of TNK cells between GC and GC liver metastasis groups mainly included IL-17 and Pi3k–Akt signaling pathways. TNK cell subsets could be further categorized into CD8 T cells, Exhausted T cells, NK cells, NKT cells, and Treg cells, with the GC liver metastasis group showing significantly more CD8 T cells and NKT cells. FOS and JUNB were the TFs of TNK cell marker genes that contributed to liver metastasis from GC and the invasion and migration of GC cell lines. Significant differences in immune cell communication ligand–receptor pairs existed between the GC and GC liver metastasis groups.ConclusionThis study revealed the critical role of TNK cell subsets in GC with liver metastasis applying single-cell transcriptomics analysis. The findings provided an important theoretical basis for developing novel therapies to inhibit liver metastasis from GC.

Abstract PR010: DICER1 cancer predisposition tumor promotion mediated non-cell autonomously via neutrophils and NETosis

Abstract DICER1 cancer predisposition syndrome is a heritable condition where affected patients have increased risk of neoplasms including fusion-negative rhabdomyosarcoma (FN-RMS). The syndrome is defined by germline heterozygous loss of function mutations in DICER1, but it remains unclear exactly how these mutations predispose children to cancer. To gain insight into the role of Dicer1 loss in DICER1 cancer predisposition, we deleted the Dicer1 gene both in the germline or conditionally within the tumor cell in our previously established mouse model of FN-RMS. One would expect the germline loss of one allele to provide a sensitized background in the tumor cell to acquire a second hit mutation. However, we observed faster tumor onset and increased penetrance in mice with germline heterozygous Dicer1 loss (Dicer1 +/- ) but not in mice when Dicer1 loss was restricted to the tumor cells (Dicer1 Flox/+ ), demonstrating that haploinsufficient tumor suppressor activity of Dicer1 loss requires non-cell autonomous cell types. Single cell RNA sequencing (scRNA-Seq) revealed significant expansion of immature neutrophils in Dicer1 +/- tumors, which were enriched for proteases associated with neutrophil extracellular traps (NETs). NETs are webs of chromatin and proteases released when neutrophils in response to inflammatory stimuli in process termed NETosis. We show Dicer1 +/- murine and human tumors are enriched for neutrophils and tumor-bearing mice had abundant circulating NETs. NETs cause significant damage to the local extracellular matrix (ECM) and have been implicated in tumor promotion. In addition, neutrophil enrichment, we found that Dicer1 +/- tumors show significant ECM remodeling and are increased C5a, a potent neutrophil chemoattractant and NET-priming factor. These results suggest NETosis is upregulated in Dicer1 +/- FN-RMS tumors. Ligand-receptor pair analysis (iTALK) on the scRNA- Seq data revealed a putative interaction between a NET-derived ligand and EGFR and IGF1R on tumor cells, suggesting direct tumor promoting signaling from NET-to-tumor. We validated this novel FN-RMS promotion mechanism in vitro using human FN-RMS cell lines and observed that this NET-derived ligand promoted FN-RMS growth through both EGFR and IGF1R signaling. NET release requires citrullination of histone H3 mediated by peptidyl arginine deiminase 4 (PADI4) to facilitate decondensation of chromatin. We intercrossed the Padi4 -/- allele into our tumor model to genetically block NETosis and observed complete rescue of the accelerated tumor onset and increased penetrance observed in Dicer1 +/- mice. These results demonstrate that NETosis promotes the growth of Dicer1 +/- FN-RMS tumors and is required for Dicer1 +/- haploinsufficiency. These findings may be applicable to many DICER1 syndrome- associated cancers, as neutrophils which get converted to tumor promoters by heterozygous DICER1 loss are present in DICER1 syndrome patients regardless of tumor type and suggest targeting neutrophils/NET-release may reduce cancer risk in DICER1 +/- individuals. Citation Format: Randolph K Larsen, Jason A Hanna, Hongjian Jin, Kristen B Reed, Darden W Kimbrough, Kyna Voung, Myron K Evans, Casey G Langdon, Catherine J Drummond, Matthew R Garcia, David Finkelstein, Patrick A Schreiner, Jerold E Rehg, Kris Ann P Schultz, Mark E Hatley. DICER1 cancer predisposition tumor promotion mediated non-cell autonomously via neutrophils and NETosis [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: RNAs as Drivers, Targets, and Therapeutics in Cancer; 2024 Nov 14-17; Bellevue, Washington. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(11_Suppl):Abstract nr PR010.

Biased cell adhesion organizes the Drosophila visual motion integration circuit.

Layer-specific brain computations depend on neurons synapsing with specific partners in distinct laminae. In the Drosophila lobula plate, axons of the four subtypes of T4 and T5 visual motion direction-selective neurons segregate into four layers, where they synapse with distinct subsets of postsynaptic neurons. Here, we identify a layer-specific expression of different receptor-ligand pairs of the Beat and Side families of cell adhesion molecules between T4/T5s and their postsynaptic partners. Developmental genetic analysis demonstrate that Beat/Side-mediated interactions are required to restrict innervation of T4/T5 axons and the dendrites of their partners to a single layer. We show that Beat/Side interactions are not required for synaptogenesis. Instead, they contribute to synaptic specificity by biasing cellular adjacency, causing neurons to segregate in discrete layers, restricting partner availability before synaptogenesis. We propose that the emergence of synaptic specificity relies on a competitive dynamic among postsynaptic partners with shared Beat/Side expression to adhere with T4/T5s.

Exploring the Spatial Distribution of Interstitial Cells in Kidney Tissue.

Interstitial cells are crucial to the development of kidney structure and function, although the mechanism underlying their role in it remains unclear to date. Our previous study identified cell clusters in human fetal kidney tissue, and we further analyzed the interstitial cell cluster within this context. We extracted the barcoded cDNA from tissue samples and prepared spatial transcriptome libraries. Sequencing data were quality-checked, normalized, and clusters were identified using Seurat. Single-cell and spatial data were integrated using multimodal intersection analysis, and cell types were deconvoluted. DEGs in interstitial cells were identified and functionally annotated using DAVID. CellPhoneDB was used to predict ligand-receptor interactions between cell types. The results of the present study revealed that this cluster of interstitial cells appeared to be scattered in the junction between the cortical and medullary regions. The subsequent Kyoto Encyclopedia of Genes and Genome pathway analysis revealed that the differentially expressed genes (DEGs) in this cluster of interstitial cells were involved in the WNT signaling pathway. The Gene Ontology (GO) analysis revealed that these DEGs were involved in multiple pathways associated with kidney development, with six of the genes (NKD2, TCF21, WNT5A, WNT4, MDK, and SFRP1) associated with kidney development exhibiting significant upregulation. Accordingly, it was inferred that these interstitial cells might be involved in regulating epithelial cell differentiation, ureteral bud development, and morphogenesis. The subsequent cell-cell communication analysis revealed that the cellular crosstalk was primarily regulated mainly by ligand-receptor pairs. Additionally, 17 genes reported to be associated with kidney disease were focused on, and these genes were found to be predominantly expressed in a single-cell type. In summary, the present study revealed the characteristics of a previously identified cluster of interstitial cells in the kidney tissue, thereby providing fresh insights into the process of kidney development.

EPCO-55. SPATIAL HETEROGENEITY IN THE TUMOR CORE AND INFILTRATING MARGIN OFIDHWT GLIOBLASTOMA

Abstract We integrated single-cell RNA-sequencing, Visium spatial transcriptomic, and Xenium in situ transcriptomic data to identify differences in cell composition between the tumor core and infiltrating edge in IDHWT glioblastoma (GBM). Using CellTrek, an algorithm that maps single cells to their most-likely locations in spatial transcriptomic data, we identified extensive spatial organization in GBM. Cell mapping revealed distinct regions enriched for tumor, immune, endothelial, neuronal, and glial cells. These were associated with the location of the tissue sample – edge regions were enriched for neurons and glia (as expected), while core regions were enriched for tumor cells and infiltrating immune cells, particularly macrophages. Within the core samples, the tumor and immune cells tended to occupy distinct spatial niches. Spatial clustering of mapped tumor cells across all samples revealed five spatially segregated tumor cell states, each associated with specific biological processes, including (1) histone methylation, (2) proliferation, (3) wound-healing, EMT, and antigen presentation, (4) hypoxia response, and (5) stem cell differentiation. These tumor cell states exhibited preferential colocalization with specific non-malignant cell types. For instance, antigen-presenting/wound-healing tumor cells tended to colocalize with diverse immune cells, while stem-like tumor cells tended to reside in neuron-rich regions at the tumor edge. Next, to identify ligand-receptor interactions governing this spatial organization, we analyzed known ligand-receptor pairs within all three data types. This revealed known and novel mediators of tumor cell interactions with vasculature, lymphoid cells, myeloid cells, neurons, and glia. While some interactions were shared across all tumor cell states (e.g. all tumor cell states interacted with myeloid cells via APP/CD74 interactions), others were specific to particular tumor cell states (e.g. wound-healing/antigen-presenting tumor cells interacted with macrophages via CSF1/CSF1R, while proliferating and stem-like tumor cells interacted with neurons through multiple known NRXN/NLGN interactions). These interactions suggest potential targets for clinical disruption of the tumor ecosystem.

TMIC-37. GEMISTOCYTIC TUMOR CELLS AND IMMUNE REACTIVE MICROGLIA PROGRAMMED FOR GLIAL SCARRING CHARACTERIZE T CELL CONTAINMENT IN IDH-MUTANT ASTROCYTOMA

Abstract Isocitrate dehydrogenase 1/2 mutant (IDHmt) astrocytoma is considered a T cell-deprived tumor, yet little is known regarding the phenotype that relates to T cell exclusion. To aid better understanding of this mechanism, we systematically characterized the IDHmt astrocytoma immune microenvironment in a large cohort by multiplex immunofluorescence (IF) (n=75), bulk RNA sequencing (n=158), single nucleus RNA sequencing (n=7) and spatial RNA and protein profiling (n=12). We integrated and analyzed all datasets to acquire a robust characterization of the microenvironment organization and validated our results using IF stainings. We demonstrated that in IDHmt astrocytomas, T cells were contained in the perivascular space (i.e., T cell cuffs). In the tumor stroma surrounding T cell cuffs, we found a dense accumulation of gemistocytic tumor cells (GTCs), a histologically distinct tumor cell subtype. GTC-high tumors demonstrated enhanced expression of immune cell migration and activation pathways that were reliably expressed by TAMs and T cells. Notably, we found that GTCs formed a unique transcriptional cell sub-cluster that expressed markers including CD44, TNC and CRYAB, which are specific for glial scarring, a central nervous system specific mechanism for immune exclusion. Surrounding T cell cuffs, GTCs co-localized with immune-reactive microglia that expressed the chemoattractants CCL3 and CCL4. Together, co-localizing GTCs and reactive microglia expressed receptor-ligand pairs that take part in reactive astrogliosis and glial scarring, including Osteopontin – CD44 and IL-1β – IL1R1. Validation whole-slide multiplex IF stainings for this spatial relationship showed specific local accumulation of CD44 positive GTCs and TAMs around T cell cuffs in GTC-high tumors, which was absent in GTC-low tumors. Together, we show that IDHmt astrocytomas organize a network of tumor cells and leukocytes that mimics glial scarring and can aid T cell exclusion. Elucidating such specific immune exclusion mechanisms is vital for more appropriate target selection in novel immune therapies.

Single cell analysis identified a basal cell transition state associated with the development and progression of bladder cancer

BackgroundBladder cancer (BC) is a prevalent malignancy characterized by significant cellular heterogeneity. While single-cell multi-omics studies have provided valuable insights, much of the existing data remains underexplored, limiting our understanding of BC’s molecular mechanisms. Uncovering the pathogenesis of BC and finding new treatment methods are urgent problems to be solved. This study aims to address this gap by re-analyzing available single-cell datasets to uncover novel insights into BC.MethodsIn this study, we retrieved three single-cell transcriptome datasets by searching the Gene Expression Omnibus (GEO) database, focusing on single-cell sequencing of normal mouse bladder within the past 5 years. Through quality control and batch effect elimination, we obtained a total of 24,930 cells including epithelial, stromal, and immune cells. Subgroup analysis, pseudotemporal analysis, cell–cell communication, and transcription factor analysis were conducted specifically on epithelial cells to identify a transitional state during basal cell differentiation. We further compared the expression profiles of key transcription factors in cancer and normal tissues. In addition, we also performed immunohistochemical staining and survival analysis for key transcription factors.ResultsSubgroup analysis revealed multiple subtypes of epithelial cells, including basal, umbrella, and intermediate cells. Through pseudotemporal analysis, we discovered the developmental trajectory from basal cells to umbrella cells and further found that Basal_I is a transitional state for basal cell differentiation. Cell-to-cell communication analyses highlighted the pivotal role of Basal_I in cell–cell interactions, and key ligand-receptor pairs associated with cancer progression were also identified. Furthermore, elevated expression levels of key transcription factors in Basal_I were found to be closely associated with the stage and prognosis of BC. Immunohistochemical staining results further confirmed the upregulated expression of these transcription factors in BC.ConclusionsCollectively, we found a transitional state of basal cells in normal bladder epithelial cells in mice, which may be related to the occurrence and development of BC, providing important clues for further understanding of the pathogenesis of BC. Our study provided possible molecular mechanisms or target for the research and treatment of BC.