Single-cell RNA-seq Datasets Research Articles

Modulator of TMB-associated immune infiltration (MOTIF) predicts immunotherapy response and guides combination therapy

Patients with high tumor mutational burden (TMB) levels do not consistently respond to immune checkpoint inhibitors (ICIs), possibly because a high TMB level does not necessarily result in adequate infiltration of CD8+ T cells. Using bulk ribonucleic acid sequencing (RNA-seq) data from 9311 tumor samples across 30 cancer types, we developed a novel tool called the modulator of TMB-associated immune infiltration (MOTIF), which comprises genes that can determine the extent of CD8+ T cell infiltration prompted by a certain TMB level. We confirmed that MOTIF can accurately reflect the integrity and defects of the cancer-immunity cycle. By analyzing 84 human single-cell RNA-seq datasets from 32 types of solid tumors, we revealed that MOTIF can provide insights into the diverse roles of various cell types in the modulation of CD8+ T cell infiltration. Using pretreatment RNA-seq data from 13 ICI-treated cohorts, we validated the use of MOTIF in predicting CD8+ T cell infiltration and ICI efficacy. Among the components of MOTIF, we identified EMC3 as a negative regulator of CD8+ T cell infiltration, which was validated via in vivo studies. Additionally, MOTIF provided guidance for the potential combinations of programmed death 1 blockade with certain immunostimulatory drugs to facilitate CD8+ T cell infiltration and improve ICI efficacy.

Abstract B044: Targeting integrin alpha V beta 3 remodels the tumor microenvironment in pancreatic cancer

Abstract In pancreatic ductal adenocarcinoma (PDAC) the tumor microenvironment (TME) plays a crucial role in therapy resistance, metastasis, and recurrence. ProAgio is a novel therapeutic cytotoxin rationally designed to bind outside the RGD ligand pocket of the alphaV-beta3 integrin pair and then kill cells expressing this target. Pre-clinical studies demonstrated the safety and anti-tumor efficacy of ProAgio in animal models, and ProAgio is currently being tested in a Phase I clinical trial. The effect of ProAgio on TME cellular components has not been closely examined. We hypothesized that ProAgio remodels the PDAC TME to decrease stromal density and local immunosuppression by killing stromal cells thought to express the integrin pair, such as cancer associated fibroblasts (CAFs), proliferating endothelial cells, and tumor associated macrophages (TAMs). To identify potential cellular targets of ProAgio in the PDAC TME, we re-analyzed publicly available single cell RNA-seq datasets of human and mouse PDAC samples. We assessed integrin co-expression using flow cytometry, performed immunophenotyping and histopathological analysis to identify TME cellular and structural alterations induced by ProAgio. Integrins αV and β3 were both expressed at the RNA level in TAMs, myeloid cells, lymphocytes (T, B and NK), endothelial cells and CAFs. In the autochthonous KPC mouse model, we confirmed that granulocytes, macrophages, monocytes, CD4+ and CD8+T cells co-expressed integrin αVβ3 at the protein level. Amongst CAFs, inflammatory CAFs (iCAFs) had the highest percentage of cells co-expressing αV and β3 integrins. No anti-tumor effect was observed after 14 days of ProAgio treatment in a syngeneic KPC-derived PDAC orthotopic model, however, in the KPC autochthonous model the same treatment retarded tumor growth within 1 week. ProAgio treated autochthonous tumors displayed no changes in immune components or CAF subsets, but increased collagen area was observed. In addition, ProAgio treatment resulted in higher blood vessel area while integrin β3 protein levels remained stable. In conclusion, short-course ProAgio remodels the TME and delays tumor growth in an autochthonous PDAC model with mature stromal components, but does not deplete CAFs, TAMs or collagen area. Future studies will seek to refine our understanding of the cell subtypes affected by more prolonged ProAgio treatment and to determine the cellular and inflammatory mediators responsible for these changes. Citation Format: Mayrel Palestino Dominguez, Philip Homan, Xianyu Zhang, Sandra Navas Reyes, Theresa Guerin, Laura Bassel, Liu Zhi-ren, Serguei Kozlov, Christine Alewine. Targeting integrin alpha V beta 3 remodels the tumor microenvironment in pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr B044.

The shared molecular mechanism of spinal cord injury and sarcopenia: a comprehensive genomics analysis.

The occurrence of Spinal cord injury (SCI) brings economic burden and social burden to individuals, families and society, and the complications after SCI greatly affect the rehabilitation and treatment of patients in the later stage.This study focused on the potential biomarkers that co-exist in SCI and sarcopenia, with the expectation to diagnose and prognose patients in the acute phase and rehabilitation phase using comprehensive data analysis. The datasets used in this study were downloaded from Gene Expression Omnibus (GEO) database. Firstly, the datasets were analyzed with the "DEseq2" and "Limma" R package to identify differentially expressed genes (DEGs), which were then visualized using volcano plots. The SCI and sarcopenia DEGs that overlapped were used to construct a protein-protein interaction (PPI) network. Three algorithms were used to obtain a list of the top 10 hub genes. Next, validation of the hub genes was performed using three datasets. According to the results, the top hub genes were DCN, FSTL1, and COL12A1, which subsequently underwent were Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. We also assessed immune cell infiltration with the CIBERSORT algorithm to explore the immune cell landscape. The correlations between the hub genes and age and body mass index were investigated. To illustrate the biological mechanisms of the hub genes more clearly, a single-cell RNA-seq dataset was assessed to determine gene expression when muscle injury occurred. According to our analysis and the role in muscle, we chose the fibro/adipogenic progenitors (FAPs) cluster in the next step of the analysis. In the sub cluster analysis, we use the "Monocle" package to perform the trajectory analysis in different injury time points and different cell states. A total of 144 overlapped genes were obtained from two datasets. Following PPI network analysis and validation, we finally identified three hub-genes (DCN, FSTL1, and COL12A1), which were significantly altered in sarcopenic SCI patients both before and after rehabilitation training. The three hub genes were also significantly expressed in the FAPs clusters. Furthermore, following injury, the expression of the hub genes changed with the time points, changing in FAPs cluster. Our study provides comprehensive insights into how muscle changes after SCI are associated with sarcopenia by moving from RNA-seq to RNA-SEQ, including Immune infiltration landscape, pesudotime change and so on. The three hub genes identified in this study could be used to distinguish the sarcopenia state at the genomic level. Additionally, they may also play a prognostic role in evaluating the efficiency of rehabilitation training.

Proteomic analysis of serum small extracellular vesicles identifies diagnostic biomarkers for neuroblastoma.

Neuroblastoma (NB) primarily arises in children who are <10 years of age, and originates from developing sympathetic nervous system, which results in tumors in adrenal glands and/or sympathetic ganglia. The diagnosis of NB involves a combination of laboratory and imaging tests, and biopsies. Small extracellular vesicles (sEVs) have gained attention as potential biomarkers for various types of tumors. Here, we performed proteomic analysis of serum sEVs and identified potential biomarkers for NB. Label-free proteomics of serum sEVs were performed in the discovery phase. A bulk RNA-seq dataset of NB tissues was used to analyze the association between genes encoding sEVs proteins and prognosis. Potential biomarkers were validated via multiple reaction monitoring (MRM) or western blot analysis in the validation phase. A public single-cell RNA-seq (scRNA-seq) dataset was integrated to analyze the tissue origin of sEVs harboring biomarkers. A total of 104 differentially expressed proteins were identified in NB patients with label-free proteomics, and 26 potential biomarkers were validated with MRM analysis. Seven proteins BSG, HSP90AB1, SLC44A1, CHGA, ATP6V0A1, ITGAL and SELL showed the strong ability to distinguish NB patients from healthy controls and non-NB patients as well. Integrated analysis of scRNA-seq and sEVs proteomics revealed that these sEVs-derived biomarkers originated from different cell populations in tumor tissues. sEVs-based biomarkers may aid the molecular diagnosis of NB, representing an innovative strategy to improve NB detection and management.

Short-chain fatty acids regulate erastin-induced cardiomyocyte ferroptosis and ferroptosis-related genes.

Ferroptosis has been proven to contribute to the progression of myocardial ischemia/reperfusion (I/R) injury and can be inhibited or promoted by ATF3. Short-chain fatty acids (SCFAs) have shown benefits in various cardiovascular diseases with anti-inflammatory and antioxidant effects. However, the impact of SCFAs on ferroptosis in ischemic-stimulated cardiomyocytes remains unknown. This study aimed to investigate the effect of SCFAs on cardiomyocyte ferroptosis, the expression of ATF3, and its potential upstream regulators. The expression of ATF3, ferroptosis pathway geneset (FPG), and geneset of potential regulators for ATF3 (GPRA, predicted by the PROMO database) was explored in the public human myocardial infarction single-cell RNA-seq (sma) dataset. Cardiomyocyte data was extracted from the dataset and re-clustered to explore the FPG, ATF3, and GPRA expression patterns in cardiomyocyte subclusters. A dose-dependent toxic experiment was run to detect the suitable dose for SCFA treatment. The erastin-induced ferroptosis model and hypoxia-reoxygenation (H/R) model (10h of hypoxia followed by 6h of reoxygenation) were adopted to assess the effect of SCFAs via the CCK8 assay. Gene expression was examined via RT-PCR and western blot. Ferroptosis markers, including lipid peroxides and Fe2+, were detected using the liperfluo and ferroOrange probes, respectively. In the sma dataset, upregulated ferroptosis pathway genes were mainly found in the infarction-stimulated cardiac cells (border zone and fibrotic zone), particularly the cardiomyocytes and adipocytes. The ATF3 and some of its potential transcription factors (VDR, EGR3, PAX5, and SP1) can be regulated by SCFA. SCFA can attenuate erastin-induced lipid peroxidation in cardiomyocytes. SCFA treatment can also reverse erastin-induced Fe2+ increase but may strengthen the Fe2+ in the H/R model. We also precisely defined a ferroptosis subcluster of cardiomyocytes (CM09) that highly expressed FPG, ATF3, and GPRA. The ATF3 and the ferroptosis pathway are elevated in cardiomyocytes of injury-related cardiac regions (border zone, ischemic zone, and fibrotic zone). SCFA can attenuate cardiomyocyte ferroptosis and regulate the expression of ATF3. Our study offers novel insights into the potential targets of SCFAs in the cardiovascular system.

Polycystic ovarian syndrome (PCOS) and recurrent spontaneous abortion (RSA) are associated with the PI3K-AKT pathway activation.

We aimed to elucidate the mechanism leading to polycystic ovarian syndrome (PCOS) and recurrent spontaneous abortion (RSA). PCOS is an endocrine disorder. Patients with RSA also have a high incidence rate of PCOS, implying that PCOS and RSA may share the same pathological mechanism. The single-cell RNA-seq datasets of PCOS (GSE168404 and GSE193123) and RSA GSE113790 and GSE178535) were downloaded from the Gene Expression Omnibus (GEO) database. Datasets of PSCO and RSA patients were retrieved from the Gene Expression Omnibus (GEO) database. The "WGCNA" package was used to determine the module eigengenes associated with the PCOS and RSA phenotypes and the gene functions were analyzed using the "DAVID" database. The GSEA analysis was performed in "clusterProfiler" package, and key genes in the activated pathways were identified using the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Real-time quantitative PCR (RT-qPCR) was conducted to determine the mRNA level. Cell viability and apoptosis were measured by cell counting kit-8 (CCK-8) and flow cytometry, respectively. The modules related to PCOS and RSA were sectioned by weighted gene co-expression network analysis (WGCNA) and positive correlation modules of PCOS and RSA were all enriched in angiogenesis and Wnt pathways. The GSEA further revealed that these biological processes of angiogenesis, Wnt and regulation of cell cycle were significantly positively correlated with the PCOS and RSA phenotypes. The intersection of the positive correlation modules of PCOS and RSA contained 80 key genes, which were mainly enriched in kinase-related signal pathways and were significant high-expressed in the disease samples. Subsequently, visualization of these genes including PDGFC, GHR, PRLR and ITGA3 showed that these genes were associated with the PI3K-AKT signal pathway. Moreover, the experimental results showed that PRLR had a higher expression in KGN cells, and that knocking PRLR down suppressed cell viability and promoted apoptosis of KGN cells. This study revealed the common pathological mechanisms between PCOS and RSA and explored the role of the PI3K-AKT signaling pathway in the two diseases, providing a new direction for the clinical treatment of PCOS and RSA.

The role of ARL4C in predicting prognosis and immunotherapy drug susceptibility in pan-cancer analysis.

Background: ARLs, which are a class of small GTP-binding proteins, play a crucial role in facilitating tumor tumorigenesis and development. ARL4C, a vital member of the ARLs family, has been implicated in the progression of tumors, metastatic dissemination, and development of resistance to therapeutic drugs. Nevertheless, the precise functional mechanisms of ARL4C concerning tumor prognosis and immunotherapy drug susceptibility remain elusive. Methods: By combining the GTEx and TCGA databases, the presence of ARL4C was examined in 33 various types of cancer. Immunohistochemistry and immunofluorescence staining techniques were utilized to confirm the expression of ARL4C in particular tumor tissues. Furthermore, the ESTIMATE algorithm and TIMER2.0 database were utilized to analyze the tumor microenvironment and immune infiltration associated with ARL4C. The TISCH platform facilitated the utilization of single-cell RNA-seq datasets for further analysis. ARL4C-related immune escape was investigated using the TISMO tool. Lastly, drug sensitivity analysis was conducted to assess the sensitivity of different types of tumors to compounds based on the varying levels of ARL4C expression. Results: The study found that ARL4C was highly expressed in 23 different types of cancer. Moreover, the presence of high ARL4C expression was found to be associated with a poor prognosis in BLCA, COAD, KIRP, LGG, and UCEC. Notably, ARL4C was also expressed in immune cells, and its high expression was found to be correlated with cancer immune activation. Most importantly, the drug sensitivity analysis revealed a positive correlation between ARL4C expression and the heightened sensitivity of tumors to Staurosporine, Midostaurin, and Nelarabine. Conclusion: The findings from our study indicate that the expression level of ARL4C may exert an influence on cancer development, prognosis, and susceptibility to immunotherapy drugs. In addition, the involvement of ARL4C in the tumor immune microenvironment has expanded the concept of ARL4C-targeted immunotherapy.

Abstract B100: Charting the transcriptomic landscape of primary and metastatic cancers in relation to their origin and target normal tissues

Abstract Introduction. Over two-thirds of cancer-related deaths are due to metastasis. Here, we aim to determine the similarity of primary and metastatic cancers to their normal origin and target tissues in a genome-wide, pan-cancer manner. Studying a collection of bulk and single-cell RNA-seq datasets, we ask two fundamental questions: (1) Are primary and metastatic tumors transcriptomically more similar to the organ from which they originate or to the organ to which they metastasize? (2) Which specific pathways expressions remain akin to the origin tissue and which ones shift their expression towards their target tissues? Methods. We analyzed the gene expression profiles of both paired and unpaired primary and metastatic tumor patient cohorts, studying single-cell, bulk-deconvolved, and bulk RNA-seq data. Overall, we used expression data from primary tumors of 11 cancer types marked as developing future metastases with a known target, and metastases of 14 cancer types with their corresponding non-cancerous origin and target tissue samples. To quantify the similarities between tumor samples and their origin and target tissues, we computed the Euclidean distance between their expression profiles, termed their transcriptomic distances, at both the whole-genome and pathway level. Results. (1) In multiple bulk RNA-seq datasets, the expression patterns of metastases are markedly altered, becoming more similar to their target tissues than the tissues of origin. In stark contrast, primary tumors’ expressions remain more similar to their origin tissues. Metastases become superficially more transcriptomically similar to their target tissues than to other non-cancerous tissues. (2) Liver metastases’ expressions shift to express liver-specialized cellular functions such as bile acid metabolism and coagulation, while the cell cycle and growth pathways mainly change in a cancer type manner, maintaining their characteristic expression in the origin tissue. Adipogenesis and fatty acid metabolism are closer to the brain in both primary and brain-metastatic samples. (3) Reassuringly, when analyzing paired primary-metastases in deconvolved-bulk and single-cell cohorts, primary and metastatic tumor cells mirror the trends found in the bulk. Deconvolved breast cancer brain metastases show expression upregulation of adipogenesis and fatty acid metabolism, as well as oxidative phosphorylation pathways, reflecting the transcriptome of these pathways in the brain. Conclusions. This first-of-its-kind systematic analysis of the expression landscape of primary tumors and metastases with respect to their healthy origin and target tissues provides a transcriptome-wide, pan-cancer view of cancer tumor adaptations to their metastatic niches. By highlighting these alterations across the bulk, deconvolved bulk, and single-cell levels, we identify pathways that are altered in the metastatic process to adapt to the transcriptomic landscape of their target tissues. Citation Format: Neel Sanghvi, Camilo Calvo-Alcañiz, Padma S Rajagopal, Sanju Sinha, Fiorella Schischlik, Kun Wang, Sanna Madan, Antonios Papanicolau-Sengos, Eytan Ruppin, Nishanth Ulhas Nair. Charting the transcriptomic landscape of primary and metastatic cancers in relation to their origin and target normal tissues [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr B100.

Absence of Slc39a14/Zip14 in mouse pancreatic beta cells results in hyperinsulinemia.

Zinc is an essential component of the insulin protein complex synthesized in β cells. The intracellular compartmentalization and distribution of zinc are controlled by 24 transmembrane zinc transporters belonging to the ZnT or Zrt/Irt-like protein (ZIP) family. Downregulation of SLC39A14/ZIP14 has been reported in pancreatic islets of patients with type 2 diabetes (T2D) as well as mouse models of high-fat diet (HFD)- or db/db-induced obesity. Our previous studies observed mild hyperinsulinemia in mice with whole body knockout of Slc39a14 (Zip14 KO). Based on our current secondary data analysis from an integrative single-cell RNA-seq dataset of human whole pancreatic tissue, SLC39A14 (coding ZIP14) is the only other zinc transporter expressed abundantly in human β cells besides well-known zinc transporter SLC30A8 (coding ZnT8). In the present work, using pancreatic β cell-specific knockout of Slc39a14 (β-Zip14 KO), we investigated the role of SLC39A14/ZIP14-mediated intracellular zinc trafficking in glucose-stimulated insulin secretion and subsequent metabolic responses. Glucose-stimulated insulin secretion, zinc concentrations, and cellular localization of ZIP14 were assessed using in vivo, ex vivo, and in vitro assays using β-Zip14 KO, isolated islets, and murine cell line MIN6. Metabolic evaluations were done on both chow- and HFD-fed mice using time-domain nuclear magnetic resonance and a comprehensive laboratory animal monitoring system. ZIP14 localizes on the endoplasmic reticulum regulating intracellular zinc trafficking in β cells and serves as a negative regulator of glucose-stimulated insulin secretion. Deletion of Zip14 resulted in greater glucose-stimulated insulin secretion, increased energy expenditure, and shifted energy metabolism toward fatty acid utilization. HFD caused β-Zip14 KO mice to develop greater islet hyperplasia, compensatory hyperinsulinemia, and mild insulin resistance and hyperglycemia. This study provided new insights into the contribution of metal transporter ZIP14-mediated intracellular zinc trafficking in glucose-stimulated insulin secretion and subsequent metabolic responses.NEW & NOTEWORTHY Metal transporter SLC39A14/ZIP14 is downregulated in pancreatic islets of patients with T2D and mouse models of HFD- or db/db-induced obesity. However, the function of ZIP14-mediated intracellular zinc trafficking in β cells is unknown. Our analyses revealed that SLC39A14 is the only Zn transporter expressed abundantly in human β cells besides SLC30A8. Within the β cells, ZIP14 is localized on the endoplasmic reticulum and serves as a negative regulator of insulin secretion, providing a potential therapeutic target for T2D.

Cross-species single-cell landscape of vertebrate pineal gland.

The pineal gland has evolved from a photoreceptive organ in fish to a neuroendocrine organ in mammals. This study integrated multiple daytime single-cell RNA-seq datasets from the pineal glands of zebrafish, rats, and monkeys, providing a detailed examination of the evolutionary transition at single-cell resolution. We identified key factors responsible for the anatomical and functional transformation of the pineal gland. We retrieved and integrated daytime single-cell transcriptomic datasets from the pineal glands of zebrafish, rats, and monkeys, resulting in a total of 22 431 cells after rigorous quality filtering. Comparative analysis was then conducted to elucidate the evolution of pineal cells, their photosensitivity, their role in melatonin production, and the signaling processes within the glands of these species. Our analysis identified distinct cellular compositions of the pineal gland in zebrafish, rats, and monkeys. Zebrafish photoreceptors exhibited comprehensive phototransduction gene expression, while specific genes, including transducin (Gngt1, Gnb3, and Gngt2) and phosducin (Pdc), were consistently present in mammalian pinealocytes. We found transcriptional similarities between the pineal gland and retina, underscoring shared evolutionary and functional pathways. Zebrafish displayed unique light-responsive circadian gene activity compared to rats and monkeys. Key ligand-receptor interactions were identified, especially involving MDK and PTN, influencing melatonin synthesis across species. Furthermore, we observed species-specific GPCR (G protein-coupled receptors) expressions related to melatonin synthesis and their alignment with retinal expressions. Our findings also highlighted specific transcription factors (TFs) and regulatory networks associated with pineal gland evolution and function. Our study provides a detailed analysis of the pineal gland's evolution from fish to mammals. We identified key transcriptional changes and controls that highlight the gland's functional diversity. Notably, we found significant ligand-receptor interactions influencing melatonin synthesis and demonstrated parallels between pineal and retinal expressions. These insights enhance our understanding of the pineal gland's role in phototransduction, melatonin production, and circadian rhythms in vertebrates.

Interleukin-17A Directly Signals to Bone Marrow-Derived Hematopoietic Stem and Progenitor Cells to Promote Their Expansion and Differentiation in Vitro

Rationale: IL-17 is a family of six pro-inflammatory cytokines (named from A to F) with distinct patterns of cellular expression. Among these, IL-17A is secreted by lymphoid subsets such as T-helper 17 cells and innate lymphoid cells type 3. Through its action on many tissues, IL-17A is recognized as a key mediator of response to infection and pathogenic states such as cancer and auto-immunity. Until now, the main effect of IL-17A on hematopoiesis has been attributed to an indirect loop through IL-17RA signaling on bone marrow stromal cells, which stimulates secretion of hematopoietic factors such as G-CSF. However, we hypothesized that IL-17A can directly signal to hematopoietic stem and progenitor cells (HSPCs) to determine their self-renewal and differentiation. Methodology: We analyzed the expression of the IL-17 signaling pathway in publicly available human and mouse hematopoietic single-cell RNAseq datasets. Mouse HSPCs were isolated using FACS to perform clonogenic and differentiation assays in Methocult (StemCell Technologies) and StemPro-34 (Gibco). Spectral flow cytometry (SONY ID7000) was used for analysing IL-17RA expression and differentiation of mouse HSPCs. IL-17A levels were measured in blood and bone marrow serum using ELISA (Invitrogen). Results: IL-17RA is expressed at the surface of mouse HSPCs, with greatest levels in common lymphoid progenitors and granulocyte-monocyte progenitors. mRNA expression of IL-17RA signaling pathway is also detectable in human HSPCs, with greatest levels in young individuals. IL-17A supplementation leads to an increase in clonogenic capacity of mouse HSPCs in methylcellulose colony-formation assays. In liquid culture, supplementation with IL-17A leads to a greater expansion of sorted Lin -/s-kit +/Sca-1 + progenitors, accompanied by an increased proportion of myeloid-committed cells.IL-17A is also detected in the bone marrow serum, with possible production from subsets of cells expressing RORγt, a master regulator in development of T helper 17 (Th17) cells. Conclusions: Our work suggests the ability of IL-17A to directly promote clonogenic potential of HSPCs and drive a myeloid-biased lineage commitment in progenitor subsets. Additional studies are required to characterize the response of HSPCs to direct IL-17A signaling in vivo. Considering the important role of IL-17A as a mediator of immune response, and tissue repair, further studies are warranted to elucidate whether modulation of this pathway may be therapeutic in the context of hematopoietic failure or malignancy.

Iron inhibits glioblastoma cell migration and polarization.

Glioblastoma is one of the deadliest malignancies facing modern oncology today. The ability of glioblastoma cells to diffusely spread into neighboring healthy brain makes complete surgical resection nearly impossible and contributes to the recurrent disease faced by most patients. Although research into the impact of iron on glioblastoma has addressed proliferation, there has been little investigation into how cellular iron impacts the ability of glioblastoma cells to migrate-a key question, especially in the context of the diffuse spread observed in these tumors. Herein, we show that increasing cellular iron content results in decreased migratory capacity of human glioblastoma cells. The decrease in migratory capacity was accompanied by a decrease in cellular polarization in the direction of movement. Expression of CDC42, a Rho GTPase that is essential for both cellular migration and establishment of polarity in the direction of cell movement, was reduced upon iron treatment. We then analyzed a single-cell RNA-seq dataset of human glioblastoma samples and found that cells at the tumor periphery had a gene signature that is consistent with having lower levels of cellular iron. Altogether, our results suggest that cellular iron content is impacting glioblastoma cell migratory capacity and that cells with higher iron levels exhibit reduced motility.

Single-cell analysis reveals specific neuronal transition during mouse corticogenesis.

Background: Currently, the mechanism(s) underlying corticogenesis is still under characterization. Methods: We curated the most comprehensive single-cell RNA-seq (scRNA-seq) datasets from mouse and human fetal cortexes for data analysis and confirmed the findings with co-immunostaining experiments. Results: By analyzing the developmental trajectories with scRNA-seq datasets in mice, we identified a specific developmental sub-path contributed by a cell-population expressing both deep- and upper-layer neurons (DLNs and ULNs) specific markers, which occurred on E13.5 but was absent in adults. In this cell-population, the percentages of cells expressing DLN and ULN markers decreased and increased, respectively, during the development suggesting direct neuronal transition (namely D-T-U). Whilst genes significantly highly/uniquely expressed in D-T-U cell population were significantly enriched in PTN/MDK signaling pathways related to cell migration. Both findings were further confirmed by co-immunostaining with DLNs, ULNs and D-T-U specific markers across different timepoints. Furthermore, six genes (co-expressed with D-T-U specific markers in mice) showing a potential opposite temporal expression between human and mouse during fetal cortical development were associated with neuronal migration and cognitive functions. In adult prefrontal cortexes (PFC), D-T-U specific genes were expressed in neurons from different layers between humans and mice. Conclusion: Our study characterizes a specific cell population D-T-U showing direct DLNs to ULNs neuronal transition and migration during fetal cortical development in mice. It is potentially associated with the difference of cortical development in humans and mice.

Cella: 3D data visualization for plant single-cell transcriptomics in Blender.

Recent advancements in single-cell transcriptomics have facilitated the possibility of acquiring vast amounts of data at single-cell resolution. This development has provided a broader and more comprehensive understanding of complex biological processes. The growing datasets require a visualization tool that transforms complex data into an intuitive representation. To address this challenge, we have utilized an open-source 3D software Blender to design Cella, a cell atlas visualization tool, which transforms data into 3D heatmaps that can be rendered into image libraries. Our tool is designed to support especially research on plant development. To validate our method, we have created a 3D model representing the Arabidopsis thaliana root meristem and mapped an existing single-cell RNA-seq dataset into the 3D model. This provided a user-friendly visual representation of the expression profiles of 21,489 genes from two perspectives (42,978 images). This approach is not limited to single-cell RNA-seq data of the Arabidopsis root meristem. We provide detailed step-by-step instructions to generate 3D models and a script that can be customized to project data onto different tissues. Our tool provides a proof-of-concept method for how increasingly complex single-cell RNA-seq datasets can be visualized in a simple and cohesive manner.

RNA-seq analysis reveals prenatal alcohol exposure is associated with placental inflammatory cells and gene expression

BackgroundFetal alcohol spectrum disorders (FASD) are the most common preventable cause of birth defects and neurodevelopmental disorders worldwide. The placenta is the crucial interface between mother and fetus. Prenatal alcohol exposure (PAE) has been shown to alter placental structure and expression of genes in bulk placental tissue samples, but prior studies have not examined effects on placental cell-type composition or taken cell-type into consideration in transcriptome analyses. MethodsWe leveraged an existent placenta single-cell RNA-seq dataset to perform cell-type deconvolution of bulk placental RNA-seq data from 35 heavy drinking pregnant women and 33 controls in a prospective birth cohort in Cape Town, South Africa. We used bivariate analyses and multivariable adjusted linear regression models to assess the relation of PAE on inferred placental cell-type proportions. We also examined differential expression of inflammatory response genes and PAE, using multivariable adjusted linear models. ResultsDeconvolution analyses showed heterogeneous placenta cell-type composition in which stromal (27 %), endothelial (26 %) and cytotrophoblasts (18 %) were the predominant cell-types. PAE around conception was associated with a higher proportion of Hofbauer cells (B = 0.51, p = 0.035) in linear models adjusted for maternal age, infant sex, and gestational age. Among the 652 inflammatory genes examined, 35 were differential expressed in alcohol exposed placentas (FDR p < 0.05). ConclusionsOur findings suggest that heavy alcohol exposure during pregnancy can influence the proportion of fetal placental villi macrophages (Hofbauer cells) and increased expression of inflammatory genes. Future studies are needed to further characterize these effects and to assess the potential functional roles of placental inflammation in FASD.

On-demand chlorine dioxide solution enhances odontoblast differentiation through desulfation of cell surface heparan sulfate proteoglycan and subsequent activation of canonical Wnt signaling.

Heparan sulfate proteoglycans (HSPGs) surround the surface of odontoblasts, and their modification affects their affinity for Wnt ligands. This study proposes applying Matching Transformation System® (MA-T), a novel chlorinated oxidant, to enhance dentinogenesis. MA-T treatment in odontoblasts decreased sulfation of HSPG and upregulated the expression of dentin sialophosphoprotein (Dspp) and Dentin Matrix Protein 1 (Dmp1) via activation of canonical Wnt signaling in vitro. Ex vivo application of MA-T also enhanced dentin matrix formation in developing tooth explants. Reanalysis of a public single-cell RNA-seq dataset revealed significant Wnt activity in the odontoblast population, with enrichment for Wnt10a and Wnt6. Silencing assays showed that Wnt10a and Wnt6 were redundant in inducing Dspp and Dmp1 mRNA expression. These Wnt ligands' expression was upregulated by MA-T treatment, and TCF/LEF binding sites are present in their promoters. Furthermore, the Wnt inhibitors Notum and Dkk1 were enriched in odontoblasts, and their expression was also upregulated by MA-T treatment, together suggesting autonomous maintenance of Wnt signaling in odontoblasts. This study provides evidence that MA-T activates dentinogenesis by modifying HSPG and through subsequent activation of Wnt signaling.

GoM DE: interpreting structure in sequence count data with differential expression analysis allowing for grades of membership

Parts-based representations, such as non-negative matrix factorization and topic modeling, have been used to identify structure from single-cell sequencing data sets, in particular structure that is not as well captured by clustering or other dimensionality reduction methods. However, interpreting the individual parts remains a challenge. To address this challenge, we extend methods for differential expression analysis by allowing cells to have partial membership to multiple groups. We call this grade of membership differential expression (GoM DE). We illustrate the benefits of GoM DE for annotating topics identified in several single-cell RNA-seq and ATAC-seq data sets.

Spatial transcriptomics map of the embryonic mouse brain - a tool to explore neurogenesis.

The developing brain has a well-organized anatomical structure comprising different types of neural and non-neural cells. Stem cells, progenitors and newborn neurons tightly interact with their neighbouring cells and tissue microenvironment, and this intricate interplay ultimately shapes the output of neurogenesis. Given the relevance of spatial cues during brain development, we acknowledge the necessity for a spatial transcriptomics map accessible to the neurodevelopmental community. To fulfil this need, we generated spatially resolved RNA sequencing (RNAseq) data from embryonic day 13.5 mouse brain sections immunostained for mitotic active neural and vascular cells. Unsupervised clustering defined specific cell type populations of diverse lineages and differentiation states. Differential expression analysis revealed unique transcriptional signatures across specific brain areas, uncovering novel features inherent to particular anatomical domains. Finally, we integrated existing single-cell RNAseq datasets into our spatial transcriptomics map, adding tissue context to single-cell RNAseq data. In summary, we provide a valuable tool that enables the exploration and discovery of unforeseen molecular players involved in neurogenesis, particularly in the crosstalk between different cell types.

Single-cell RNA seq analysis of erythroid cells reveals a specific sub-population of stress erythroid progenitors

ABSTRACTBackground: Erythroid cells play important roles in hemostasis and disease. However, there is still significant knowledge gap regarding stress erythropoiesis.Methods: Two single-cell RNAseq datasets of erythroid cells on GEO with accession numbers GSE149938 and GSE184916 were obtained. The datasets from two sources, bone marrow and peripheral blood were analyzed using Seurat v4.1.1, and other tools in R. QC metrics were performed, data were normalized and scaled. Principal components that capture the variation of the data were determined. In clustering the cells, KNN graph was constructed and Louvain algorithm was applied to optimize the standard modularity function. Clusters were defined via differential expression of features.ResultsWe identified 9 different cell types, with a particular cluster representing the stress erythroids. The clusters showed differentially expressed genes as observed from the gene signature plot. The stress erythroid cluster differentially expressed some genes including ALAS2, HEMGN, and GUK1.ConclusionThe erythroid population was found to be heterogeneous, with a distinct sub-cell type constituting the stress erythroids; this may have important implications for our knowledge of steady-state and stress erythropoiesis, and the markers found in this cluster may prove useful for future research into the dynamics of stress erythroid progenitor cell differentiation.

High-resolution single-cell transcriptomic survey of cardiomyocytes from patients with hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is a common inherited cardiovascular disease, which can cause heart failure and lead to death. In this study, we performed high-resolution single-cell RNA-sequencing of 2115 individual cardiomyocytes obtained from HCM patients and normal controls. Signature up- and down-regulated genes in HCM were identified by integrative analysis across 37 patients and 41 controls from our data and published human single-cell and single-nucleus RNA-seq datasets, which were further classified into gene modules by single-cell co-expression analysis. Using our high-resolution dataset, we also investigated the heterogeneity among individual cardiomyocytes and revealed five distinct clusters within HCM cardiomyocytes. Interestingly, we showed that some extracellular matrix (ECM) genes were up-regulated in the HCM cardiomyocytes, suggesting that they play a role in cardiac remodelling. Taken together, our study comprehensively profiled the transcriptomic programs of HCM cardiomyocytes and provided insights into molecular mechanisms underlying the pathogenesis of HCM.