Single-cell RNA Sequencing Datasets Research Articles

Essential blood molecular signature for progression of sepsis-induced acute lung injury: Integrated bioinformatic, single-cell RNA Seq and machine learning analysis.

In this study, we aimed to identify an essential blood molecular signature for chacterizing the progression of sepsis-induced acute lung injury using integrated bioinformatic and machine learning analysis. The results showed that a total of 88 functionally related ALI-associated hub genes in sepsis were identified by MCODE analysis and they were enriched in infection and inflammtory responses, lung and cardiovascular disease pathways. These hub genes stratified ALI-sepsis and sepsis and further stratified two subtypes of sepsis-ALI with differential ALI scores, hub gene expression patterns, and levels of immune cells. A seven-gene signature including TNFRSF1A, NFKB1, FCGR2A, NFE2L2, ICAM1 and SOCS3 and PDCD1 was derived from the hub genes. These genes were significantly implicated in immune and metabolism pathways. They were expressed in six circulatory immune cells based on analysis of a single cell RNA sequencing dataset. Furthermore, the seven-gene signature was corrobarated using by integrating 12 machine learning algorithms. A premium three-gene signature NFE2L2, FCGR2A and PDCD1 for differentiating ALI-sepsis from sepsis were also derived from the seven-gene signature based on analysis of the seven core hub genes by the machine learning algorithms. Furthermore, the expressions of hub genes were verified in sepsis mice models. Therefore, our study provided an avenue to develop a molecular tool for identify and characterize progression of acute lung injury associated with sepsis.

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.

Discovering Explainable Biomarkers for Breast Cancer Anti-PD1 Response via Network Shapley Value Analysis

Background and objectiveImmunotherapy holds promise in enhancing pathological complete response rates in breast cancer, albeit confined to a select cohort of patients. Consequently, pinpointing factors predictive of treatment responsiveness is of paramount importance. Gene expression and regulation, inherently operating within intricate networks, constitute fundamental molecular machinery for cellular processes and often serve as robust biomarkers. Nevertheless, contemporary feature selection approaches grapple with two key challenges: opacity in modeling and scarcity in accounting for gene-gene interactions MethodsTo address these limitations, we devise a novel feature selection methodology grounded in cooperative game theory, harmoniously integrating with sophisticated machine learning models. This approach identifies interconnected gene regulatory network biomarker modules with priori genetic linkage architecture. Specifically, we leverage Shapley values on network to quantify feature importance, while strategically constraining their integration based on network expansion principles and nodal adjacency, thereby fostering enhanced interpretability in feature selection. We apply our methods to a publicly available single-cell RNA sequencing dataset of breast cancer immunotherapy responses, using the identified feature gene set as biomarkers. Functional enrichment analysis with independent validations further illustrates their effective predictive performance ResultsWe demonstrate the sophistication and excellence of the proposed method in data with network structure. It unveiled a cohesive biomarker module encompassing 27 genes for immunotherapy response. Notably, this module proves adept at precisely predicting anti-PD1 therapeutic outcomes in breast cancer patients with classification accuracy of 0.905 and AUC value of 0.971, underscoring its unique capacity to illuminate gene functionalities ConclusionThe proposed method is effective for identifying network module biomarkers, and the detected anti-PD1 response biomarkers can enrich our understanding of the underlying physiological mechanisms of immunotherapy, which have a promising application for realizing precision medicine.

Abstract B037: Expression of MRTFA facilitates an immunosuppressive tumor microenvironment via upregulation of VSIR

Abstract Breast cancer, the second highest cause of cancer-related deaths in women, accounts for 31% of female cancer diagnoses. African American women have lower survival rates than White American women, influenced by both biological factors (age, family history, genetic factors, tumor biology) and social determinants (socio-economic status, insurance status, health care access). However, precise biological determinants remain unclear. The primary reason for breast cancer mortality is metastasis to organs like the lung, liver, and brain, with transcription factors playing a key role in this process. Myocardin related transcription factor A/B (MRTFA/B) are co-activators of serum-response factor (SRF), and the MRTF-SRF complex promotes breast cancer cell migration, invasion, and metastasis by regulating genes involved in actin cytoskeleton remodeling. MRTFA also supports tumor growth by modulating cancer-associated fibroblasts (CAFs) and remodeling the extracellular matrix (ECM) in the tumor microenvironment. While the pro-metastatic role of MRTFA/B is established in vitro and in mice, their impact on human cancer progression and metastasis requires further investigation. Therefore, understanding MRTFA's role in breast cancer metastasis is crucial for improving patient outcomes, making it essential to investigate MRTFA/B expression patterns in both tumor cells and the tumor microenvironment (TME). To explore the clinical, demographic, tumor-intrinsic, and tumor microenvironmental patterns of MRTFA/B’s expression and activation, we utilized multiplex imaging methods on multiple racially diverse tissue microarrays (TMA) and bioinformatics analyses of The Cancer Genome Atlas (TCGA), Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), and available single-cell RNA sequencing datasets. Strikingly, MRTFA expression levels were higher in African American patients than in White American patients. Next, we investigated MRTFA expression patterns in the TME by using single-cell sequencing databases and found more abundant MRTFA expression in dendritic cells (DCs) within the TME compared to any other cell subtype. Moreover, our multiplex-imaging of tumor microarray (TMA) samples showed prominent MRTFA expression in HLA-DRA+CD45+ cells, indicative of antigen-presenting cells (APC). Notably, public single-cell RNA sequencing data indicated that breast cancer DCs strongly express the V-set immunoregulatory receptor (VSIR), an immune checkpoint protein, implying the immunosuppressive nature of the TME and we found that this increased VSIR expression is mediated by the MRTF-SRF complex. These findings suggest that DCs expressing MRTFA in breast cancer microenvironment contribute to creating the immunosuppressive TME via upregulation of VSIR expression, resulting in racial breast cancer disparities. Citation Format: Kihak Lee, Stephanie M. Wilk, Alexa M. Gajda, Mohamed Haloul, Virgilia Macias, Elizabeth L. Wiley, Zhengjia Chen, Xinyi Liu, Xiaowei Wang, Maria Sverdlov, Kent F. Hoskins, Ekrem Emrah Er. Expression of MRTFA facilitates an immunosuppressive tumor microenvironment via upregulation of VSIR [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 B037.

Abstract A039: Characterization of the heterogeneous nature of the peritumoral zone of glioblastomas and its relevance for the clinical progression of the disease

Abstract Glioblastoma (GBM) is one of the most aggressive forms of cancer, with a recurrence rate of nearly 100% within 12 months of diagnosis. This is attributable to the persistence of residual tumor cells following surgical resection, which can repopulate the tumor even after the administration of aggressive chemoradiotherapy. These cells are embedded in a specific microenvironment in the peritumoral zone (PTZ), which is formed by their interaction with the brain parenchyma. The PTZ can be classified radiologically into two distinct categories: areas of clear tumor infiltration (non-contrast-enhancing (non-CE) tumor) and areas of vascular edema. Recent data suggest that the extent of surgical resection to non-CE regions may confer substantial benefits to patients with GBM. However, while the tumor core niche has been the subject of extensive study, there is a paucity of knowledge regarding the nature of the PTZ. In this study, we prospectively collected a large cohort of radiologically guided biopsies from GBM patients and performed a comprehensive cellular analysis. To this end, we initially integrated publicly available single-cell RNA sequencing (scRNA-seq) datasets from non-pathogenic human brains and gliomas, resulting in an integrated atlas representing the major cell types: immune (myeloid cells and T cells), astrocytic, oligodendroglial, and vascular. By means of a meticulous multi-stage examination of differentially expressed genes in glioma and cell type-specific markers, we were able to identify several genes that could serve to characterize the cellular content of the biopsies obtained from the tumor core and the periphery, comprising non-CE tumor, edema, and what was deemed "normal" tissue. The application of unsupervised clustering enabled the separation of the most pathogenic samples (including CE and non-CE tumor biopsies) based on the enrichment of proliferative markers and the pronounced absence of normal endothelial and oligodendrocyte expression. The tumorigenic samples were clustered into two main groups: one group that was enriched in astrocytic and proliferative markers and another one that was enriched in myeloid cells. Furthermore, our findings indicate the existence of inter- and intra-tumor heterogeneity in the cellular composition of the PTZ in GBM, with observed differences associated with the degree of tumor infiltration, but also patient age and gender. In particular, a distinct pathological pattern was discerned in select edema and normal biopsies from multiple patients, particularly those of an advanced age. Moreover, several markers of neural and immune cells associated with a favorable prognosis were identified, though only when expressed in the periphery. In conclusion, our study offers a comprehensive scRNA-seq resource for investigating the involvement of diverse cell types in the pathobiology of GBM. Additionally, it highlights the heterogeneous nature of the glioma periphery, which could explain the gender and age-related prognostic differences that have been observed among patients with GBM. Citation Format: Olaya de Dios, María de los Ángeles Ramírez-González, Beatriz Herranz, Juan Romero, Ana Ramos, Juan Manuel Sepúlveda-Sánchez, Ricardo Gargini, Aurelio Hernández-Laín, Pedro González, Luis Jiménez-Roldán, Guillermo García-Posadas, Ángel Pérez-Núñez, Pilar Sánchez-Gómez. Characterization of the heterogeneous nature of the peritumoral zone of glioblastomas and its relevance for the clinical progression of the disease [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 A039.

Integration of Single-Cell and Spatial Transcriptomic Data Reveals Spatial Architecture and Potential Biomarkers in Alzheimer's Disease.

Alzheimer's disease (AD) is a complex neurodegenerative disorder characterized by the gradual loss of neurons and the accumulation of amyloid plaques and neurofibrillary tangles. Despite advancements in the understanding of AD's pathophysiology, the cellular organization and interactions in the prefrontal cortex (PFC) remain elusive. Eight single-cell RNA sequencing (scRNA-seq) datasets from both normal controls and individuals with AD were harmonized. Stringent preprocessing protocols were implemented to uphold dataset integrity. Unsupervised clustering and annotation revealed 22 distinct cell clusters corresponding to 19 unique cell types. The spatial architecture of the PFC region was constructed using the CARD tool. Further analyses encompassed trajectory examination of Oligodendrocyte subtypes, evaluation of regulon activity scores, and spot clustering within white matter regions (WM). Differential expression analysis and functional enrichment assays unveiled molecular signatures linked to AD progression and were validated using microarray data sourced from neurodegenerative disorder patients. Our investigation employs scRNA-seq and spatial transcriptomics to uncover the cellular atlas and spatial architecture of the human PFC in AD. Moreover, our results indicate that Oligodendrocytes are more prevalent in AD patients, showcasing diverse subtypes and spatial organization within WM regions. Each subtype appears to be associated with distinct biological processes and transcriptional regulators, shedding light on their involvement in AD pathology. Notably, the Oligodendrocyte_C6 subtype is linked to neurological damage in AD patients, characterized by heightened expression of genes involved in cell-cell connections, cell membrane stability, and myelination. Additionally, 12 target genes regulated by NFIA were identified, which are upregulated in AD patients and associated with disease progression. Elevated PLXDC2 expression in peripheral blood was also identified, suggesting its potential as a non-invasive biomarker for early AD detection. Our study provides novel insights into the role of Oligodendrocytes in AD and highlights the potential of PLXDC2 as a blood biomarker for non-invasive diagnosis and monitoring of AD patients.

A comprehensive human embryo reference tool using single-cell RNA-sequencing data.

Stem cell-based embryo models offer unprecedented experimental tools for studying early human development. The usefulness of embryo models hinges on their molecular, cellular and structural fidelities to their in vivo counterparts. To authenticate human embryo models, single-cell RNA sequencing has been utilized for unbiased transcriptional profiling. However, an organized and integrated human single-cell RNA-sequencing dataset, serving as a universal reference for benchmarking human embryo models, remains unavailable. Here we developed such a reference through the integration of six published human datasets covering development from the zygote to the gastrula. Lineage annotations are contrasted and validated with available human and nonhuman primate datasets. Using stabilized Uniform Manifold Approximation and Projection, we constructed an early embryogenesis prediction tool, where query datasets can be projected on the reference and annotated with predicted cell identities. Using this reference tool, we examined published human embryo models, highlighting the risk of misannotation when relevant references are not utilized for benchmarking and authentication.

GTO: a comprehensive gene therapy omnibus.

Gene therapy, which involves the delivery of genetic material into cells to correct an underlying genetic problem, has emerged as a promising approach for treating various conditions. To promote research in this rapidly evolving field, we developed the Gene Therapy Omnibus (GTO) (http://www.inbirg.com/gto/), a comprehensive resource containing detailed clinical trial data and molecular information related to gene therapy. The GTO includes 6333 clinical trial records and 3466 transcriptome profiles, with information on 614 altered genes and 22 types of gene therapy, including DNA therapies, RNA therapies and genetically-modified cell therapies. For each gene therapy product in a clinical trial, detailed information, such as altered gene name, structural components, indication, vector information, phase of the clinical trial, clinical outcomes and adverse effects, is provided when available. Additionally, 345 comparison datasets, including 29 single-cell RNA-sequencing datasets comprising information on both gene therapy and control samples, were established. Differential gene expression and downstream functional enrichment analyses were performed through standardized pipelines to elucidate the molecular alterations induced by gene therapy. The user-friendly interface of the GTO supports efficient data retrieval, visualization and analysis, making it an invaluable resource for researchers and clinicians performing clinical research on gene therapy and the underlying mechanisms.

Computing hematopoiesis plasticity in response to genetic mutations and environmental stimulations.

Cell plasticity (CP), describing a dynamic cell state, plays a crucial role in maintaining homeostasis during organ morphogenesis, regeneration, and trauma-to-repair biological process. Single-cell-omics datasets provide an unprecedented resource to empower CP analysis. Hematopoiesis offers fertile opportunities to develop quantitative methods for understanding CP. In this study, we generated high-quality lineage-negative single-cell RNA-sequencing datasets under various conditions and introduced a working pipeline named scPlasticity to interrogate naïve and disturbed plasticity of hematopoietic stem and progenitor cells with mutational or environmental challenges. Using embedding methods UMAP or FA, a continuum of hematopoietic development is visually observed in wild type where the pipeline confirms a low proportion of hybrid cells ( P hc , with bias range: 0.4∼0.6) on a transition trajectory. Upon Tet2 mutation, a driver of leukemia, or treatment of DSS, an inducer of colitis, P hc is increased and plasticity of hematopoietic stem and progenitor cells was enhanced. We prioritized several transcription factors and signaling pathways, which are responsible for P hc alterations. In silico perturbation suggests knocking out EGR regulons or pathways of IL-1R1 and β-adrenoreceptor partially reverses P hc promoted by Tet2 mutation and inflammation.

Kaempferol Remodels Liver Monocyte Populations and Treats Hepatic Fibrosis in Mice by Modulating Intestinal Flora and Metabolic Reprogramming.

Changes in gut flora are associated with liver fibrosis. The interactions of host with intestinal flora are still unknown, with little research investigating such interactions with comprehensive multi-omics data. The present work analyzed and integrated large-scale multi-omics transcriptomics, microbiome, metabolome, and single-cell RNA-sequencing datasets from Kaempferol-treated and untreated control groups by advanced bioinformatics methods. This study concludes that kaempferol dose-dependently improved serum markers (like AST, ALT, TBil, Alb, and PT) and suppressed fibrosis markers (including HA, PC III, LN, α-SMA, and Collagen I), while kaempferol also increased body weight. Mechanistically, kaempferol improved the metabolic levels of intestinal flora dysbiosis and associated lipids. This was achieved by increasing the abundance of g__Robinsoniella, g__Erysipelotrichaceae_UCG-003, g__Coriobacteriaceae_UCG-002, and 5-Methylcytidine, all-trans-5,6- Epoxyretinoic acid, LPI (18:0), LPI (20:4), etc. to achieve this. Kaemferol exerts anti-inflammatory and immune-enhancing effects by down-regulating the Th17/IL-17 signaling pathway in PDGF-induced LX2 cells. In addition, kaempferol administration remarkably elevated CD4 + T and CD8 + T cellular proportions, thereby activating immune cells for protecting the body and controlling inflammatory conditions. The combined interaction of multiple data may explain how Kaempferol modulates the intestinal flora thereby remodeling the hepatocyte population and alleviating liver fibrosis.

Abstract 4137833: The plasma cell-free transcriptome non-invasively profiles the immune response and myocardial damage in immune checkpoint inhibitor-induced myocarditis.

Introduction: Immune checkpoint inhibitor-induced myocarditis (ICI-m) is a severe complication of cancer immunotherapy, marked by cardiac inflammation. Despite its high mortality rate, diagnosing ICI-m remains challenging due to the lack of sensitive and non-invasive diagnostic modalities. Plasma cell-free mRNA (cf-mRNA) has recently been highlighted as a promising tool for non-invasive tissue profiling. Hypothesis: The plasma cf-mRNA profile contains disease-specific immune and tissue transcriptomic signatures of ICI-m that can be leveraged for disease-specific precision diagnostics. Aims: To establish and validate a novel cf-mRNA bench and bioinformatic pipeline for noninvasive profiling of the immune and tissue landscape of patients with ICI-m. Methods: We isolated, DNase-treated, and sequenced bulk cfRNA from frozen plasma of patients with ICI-treated cancer patients with no autoimmunity (group A, n=5), extracardiac autoimmunity (group B, n=7), and ICI-m with or without extracardiac autoimmunity (group C, n=10). Publicly available healthy control cfRNA was downloaded (n=30) as external controls. We used cell type-specific gene panels curated from single-cell RNA-sequencing datasets of circulating immune cells and cardiac cells for cellular deconvolution of the cf-mRNA. Signature scores of the sum of the counts of each cell type-specific gene were used to compare cell type contributions between patient groups. Results: Cancer and inflammatory gene pathways were significantly enriched in the cf-mRNA of all ICI-treated cancer patients. Cardiac pathways and conduction genes were significantly enriched in group C vs. A and B patients. Signature scores of Temra CD8+ T cells and cardiomyocytes, and gene expression of CCL5 and MYH6 were elevated in group C patients. Our custom ICI-m classifier containing 3 cardiac- and 3 immune cell-specific genes differentiated group C from A (AUC 0.903, 95% CI 0.858-0.903) and B patients (AUC 0.983, 95% CI 0.970-0.983) effectively, outperforming a diagnostic classifier obtained from unsupervised feature selection from all differentially expressed genes. Conclusions: Using our novel plasma cf-mRNA platform, we developed a diagnostic classifier that captures the disease-specific immune and tissue transcriptomic signatures of ICI-m, highlighting the advantages of this disease-specific approach over conventional biomarker discovery, and demonstrating the broader implications of the platform for the field of precision diagnostics.

STEM-19. TARGETINGGIHCG LNCRNA IN GLIOBLASTOMA STEM CELLS: A POTENTIAL THERAPEUTIC STRATEGY

Abstract Glioblastoma multiforme (GBM) remains the most lethal and prevalent primary brain tumor worldwide. Despite advances in understanding its biology and multimodal therapy options, the overall prognosis for GBM patients remains bleak, primarily due to the high recurrence rate, which is intimately linked to tumor resistance against standard therapeutic interventions. Glioblastoma stem cells (GSCs) contribute to therapeutic resistance and cellular heterogeneity through their self-renewal properties and ability to adapt. Thus, identifying new molecular targets driving GBM progression is crucial for developing effective therapies. Recent advancements in genome biology have revealed that long non-coding RNAs (lncRNAs) play roles in various biological functions, and the dysregulation of numerous lncRNAs has been shown to be associated with specific cancers. To identify GSC-associated lncRNAs, a comprehensive analysis was performed using single-cell RNA sequencing datasets from GBM tumors, GBM organoids, GSC-enriched GBM tumors, as well as normal human brain samples. A chromatin-enriched lncRNA, GIHCG, was identified as being highly expressed in GSCs compared to non-neoplastic neural stem cells. The GIHCG gene, located on human chromosome 12q14.1, is frequently amplified in glioblastoma and impacts overall survival. Bioinformatic and functional analyses revealed that GIHCG is amplified in 13% of GBM patient samples, and high expression of GIHCG is a negative prognostic marker for GBM patients, with significantly reduced overall survival compared to the low expression group. In addition, the depletion of GIHCG significantly reduced GSC proliferation and migration. Further, the knockdown of GIHCG decreased both mRNA and protein expression levels of critical GSC stemness factors, including SOX2, NESTIN, and OLIG2. Moreover, GIHCG depletion reduced the sphere formation capacity of GSCs, demonstrating the functional importance of GIHCG in the maintenance of GSC stemness. These results indicate that GIHCG is essential for GSC proliferation, migration, and stemness, underscoring its potential therapeutic value in RNA-based therapies for combating glioblastoma malignancy.

M5C related-regulator-mediated methylation modification patterns and prognostic significance in breast cancer

5-Methylcytosine (m5C) is closely associated with cancer. However, the role of m5C in breast cancer(BC)remains unclear. This study combined single-cell RNA sequencing (scRNA-Seq) and transcriptomics datasets to screen m5C regulators associated with BC progression and analyze their clinical values. Firstly, This study elucidates the mechanisms of the m5C landscape and the specific roles of m5C regulators in BC patients. we found that the dysregulation of m5C regulators with m5Cscore play the essential role of the carcinogenesis and progression in epithelial cells and myeloid cells of BC at single cell level. External validation was conducted using an independent scRNA-Seq datasets. Then, three distinct m5C modification patterns were identified by transcriptomics datasets. Based on the m5C differentially expressed regulators, the m5Cscore was constructed, and used to divide patients with BC into high and low m5Cscore groups. Patients with a high m5Cscore had more abundant immune cell infiltration, stronger antitumor immunity, and better prognoses. Finally, Quantitative real-time (PCR) and immunohistochemistry were used for the in vitro experimental validation, which had extensive prognostic value. In this study, we aimed to assess the expression of m5C regulators involved in BC and investigate their correlation with the tumor microenvironment, clinicopathological characteristics, and prognosis of BC. The m5C regulators could be used to effectively assess the cell specific regulation prognosis of patients with BC and develop more effective immunotherapy strategies.

IMMU-45. MYELOID-ASSOCIATED WILD-TYPE IDH1 PROMOTES IMMUNOSUPPRESSION IN GLIOBLASTOMA

Abstract Tumor-associated myeloid cells (TAMCs) promote immunosuppression in the GBM tumor microenvironment (TME) and resistance to immune checkpoint therapy (ICT). However, the metabolic and epigenetic mechanisms underlying TAMC activation and the therapeutic potential of fine-tuning TAMC activation remain largely unexplored. Our analyses of GBM patient single-cell RNA sequencing (scRNA-Seq) datasets demonstrated that in addition to tumor cells, wild-type isocitrate dehydrogenase (wt-IDH1) is also highly expressed in TAMCs. Using a murine model with myeloid cell-specific deletion of wt-IDH1 (LysM-cre-ERT2; wt-IDH1L/L), we demonstrated that the loss of wt-IDH1 promoted inflammatory myeloid phenotypes, increased CD8+ T cells in the TME, improved survival of GBM tumor-bearing mice, and enhanced anti-tumor effects of PD1 checkpoint blockade. Further, the pharmacological inhibition of wt-IDH1 using systemic administration of a first-in-class wt-IDH1-specific, brain-penetrant small molecule inhibitor or intrathecal delivery of siRNA targeted to wt-IDH1 mirrored the functional phenotype of wt-IDH1-deleted myeloid cells, overcame ICT resistance, and promoted long-term survival and anti-tumor immune memory. Mechanistically, in myeloid cells, the genetic or pharmacological inactivation of wt-IDH1 inhibited oxidative phosphorylation, reduced myeloid cell proliferation, increased their tumoricidal activity, and altered chromatin accessibility of key transcription factors implicated in the regulation of myeloid cell states, including AP-1, IRFs, STAT1/2, NFATs, and CEPBPs. These studies define wt-IDH1 as a metabolic checkpoint of myeloid cell activation and credential the inhibition of wt-IDH1 as a novel immunotherapeutic strategy to increase ICT efficacy for patients with GBM.

Dysregulation of R-loop homeostasis shapes the immunosuppressive microenvironment and induces malignant progression in melanoma.

Dysregulated R-loop homeostasis leads to DNA replication stress and genomic instability, a major driver of cancer. However, the role of R-loops in melanoma development remains unclear. We established an R-loop scoring model based on a single-cell RNA sequencing dataset and evaluated the association between the R-loop score with the melanoma immune microenvironment and treatment response. We explored the role of CENPA-mediated changes in R-loop distribution during melanoma progression by DNA/RNA immunoprecipitation and sequencing and a series of functional experiments. We found that malignant cells with high R-loop scores may be involved in melanoma progression by modulating immune evasion, metabolic reprogramming, and cancer-related pathways. A cell communication analysis revealed that high-score R-loops play an important role in altering cell-cell interactions and limiting the CD8 + cytotoxic T cell response and T cell accumulation. CENPA silencing induced changes in R-loop distribution, upregulated Hippo signaling activity, and inhibited tumor cell proliferation and migration. Moreover, the R-loop score can predict the prognosis and immunotherapy effect of melanoma patients. Our work reveals the potential molecular mechanism by which abnormal R-loops promote melanoma progression, which may help develop anticancer therapies based on R-loops or R-loop regulators.

PKMζ, a brain-specific PKCζ isoform, is required for glycolysis and myofibroblastic activation of hepatic stellate cells.

TGFβ1 induces plasma membrane (PM) accumulation of glucose transporter 1 (Glut1) required for glycolysis of hepatic stellate cells (HSCs) and HSC activation. This study aimed to understand how Glut1 is anchored/docked onto the PM of HSCs. HSC expression of protein kinase M zeta isoform (PKMζ) was detected by RT-PCR, Western blotting, and immunofluorescence. PKMζ level was manipulated by shRNA or overexpression; HSC activation was assessed by cell expression of activation markers; PM Glut1, glucose uptake, and glycolysis of HSCs were analyzed by biotinylation, 2-NBDG-based assay, and Seahorse Glycolysis Stress Test. Phospho-mutants of vasodilator-stimulated phosphorylated protein (VASP) were created by site-directed mutagenesis. TGFβ transcriptome was obtained by RNA sequencing. Single-cell RNA sequencing datasets and immunofluorescence were leveraged to analyze PKMζ expression in cancer-associated fibroblasts (CAFs) of colorectal liver metastases. Function of HSC PKMζ was determined by tumor/HSC co-implantation study. Primary human and murine HSCs express PKMζ, but not full-length PKCζ. PKMζ knockdown suppresses whereas PKMζ overexpression potentiates PM accumulation of Glut1, glycolysis, and HSC activation induced by TGFβ1. Mechanistically, PKMζ binds to and induces VASP phosphorylation at serines 157 and 239 facilitating anchoring/docking of Glut1 onto the PM of HSCs. PKMζ expression is increased in the CAFs of murine and patient colorectal liver metastases compared to quiescent HSC. Targeting PKMζ suppresses transcriptome, CAF activation of HSCs, and colorectal tumor growth in mice. Since HSCs are also a major contributor of liver fibrosis, our data highlight PKMζ and VASP as targets to inhibit metabolic reprogramming, HSC activation, liver fibrosis, and the pro-metastatic microenvironment of the liver.

RAC2 as a Tumor-Suppressive Biomarker Associated with T Cell Infiltration in Breast Cancer.

Background: RAC2 is critical in regulating the homeostasis of hematopoietic stem cells. Nonetheless, its role in breast cancer (BC) remains unclear, necessitating further investigation. Methods: The expression of RAC2 in the BC and healthy tissues was acquired from The Cancer Genome Atlas. Its validity was further assessed using datasets from the gene expression omnibus database. The Tumor Immune Single-cell Hub database was used to collect and analyze the single-cell RNA sequencing datasets of BC. The diagnostic relevance of RAC2 was evaluated using receiver operating characteristic curves. Further assessment was carried out via enrichment analyses; Gene Set Analysis, immune scoring, single-cell sequencing, and immunohistochemical analysis were conducted to confirm the relationship between RAC2 expression and immune infiltration. Results: RAC2 expression was notably heightened in BC (p < 0.001). It was observed that a better prognosis was linked to heightened expression of RAC2 (p < 0.01), with the diagnostic efficacy of the marker noted to be good (area under the curve = 0.858). We found a lower percentage of protumor immune cells and a greater proportion of antitumor immune cells in the high RAC2. Our analysis revealed alterations in gene expression and an enriched network of immune pathways influenced by RAC2. Notably, cytotoxic genes, chemokines, chemokine receptors, immunostimulators, and immunosuppressive molecules positively correlated with RAC2 expression. RAC2 expression reliably predicted how patients would respond to two different therapeutic approaches in BC. Conclusions: The RAC2 was found to be a key biomarker in BC in the current study, demonstrating considerable potential as a prognostic and diagnostic marker. These results highlight the RAC2 potential to improve precision medicine strategies and treatment outcomes for patients with BC.

New insight into the development of synpolydactyly caused by expansion of HOXD13 polyalanine based on weighted gene co-expression network analysis

BackgroundSynpolydactyly (SPD) is mainly caused by mutations of polyalanine expansion (PAE) in the transcription factor gene HOXD13 and the involved cell types and signal pathway are still not clear possible pathways and single-cell expression characteristics of limb bud in HOXD13 PAE mice was analyzed in this study.MethodWe investigated a previous study of a mouse model with SPD and conducted weighted gene co-expression network analysis (WGCNA) using a single-cell RNA sequencing dataset from limb bud cells of SPD mouse model of HOXD13 + 7A heterozygote.ResultsAnalysis of WGCNA revealed that synpolydactyly-associated Hoxd13 PAEs alter the immune response and osteoclast differentiation, and enhance DNA replication. Bmp4, Hand2, Hoxd12, Lnp, Prrx1, Gmnn, and Cdc6 were found to play potentially key roles in synpolydactyly.ConclusionsThese findings evaluated the main genes related to SPD with PAE mutations in HOXD13 and advance our understanding of human limb development.

Lymphatic-macrophage crosstalk during neonatal mouse heart regeneration and transition to fibrotic repair

Abstract Background In adult mice, myocardial infarction (MI) activates the cardiac lymphatics, which undergo sprouting angiogenesis (lymphangiogenesis) and function to drain interstitial fluid and traffic macrophages to mediastinal lymph nodes (MLNs). This prevents oedema and reduces inflammatory immune cell content to improve cardiac function. Purpose Given the importance of the adult cardiac lymphatics in macrophage clearance after injury, we investigated their role across the neonatal "regenerative window". At post-natal day 1 (P1) neonatal mice fully regenerate their heart following MI, in a macrophage-dependent manner, whereas equivalent injury at day 7 (P7) leads to scarring driven by pro-fibrotic macrophages. We hypothesised that lymphatics respond and function differently during this "window," to clear macrophage-specific subtypes depending upon their requirement for regeneration versus fibrotic repair. Methods &amp; Results Extensive lymphatic growth and sprouting was evident in intact neonatal hearts until P16, with strain-dependent developmental differences. The response to injury revealed limited lymphangiogenesis and minimal clearance of macrophages from P1 compared to P7 infarcted hearts, as determined by adoptive transfer experiments and monitoring of cleared macrophages to MLNs. This is coincident with maturation of lymphatic endothelial cell junctions across the neonatal period via transition from "zipper" (impermeable) to "button" (permeable) -type junctions. To gain molecular insight into the mechanisms underpinning lymphatic endothelium macrophage interactions at P1 versus P7, we generated unbiased single cell RNA sequencing datasets from neonatal heart samples after MI and observed altered signalling between lymphatic endothelial cells and macrophages across the neonatal period, including altered expression of the lymphangiocrine factor Reelin (RELN). Finally, in mice lacking the lymphatic endothelial receptor-1 (LYVE1), that exhibit impaired transmigration of interstitial macrophages to lymphatic vessels, magnetic resonance imaging (MRI) revealed a surprising impaired functional outcome in P1 mice 28 days post-MI. Given our observations that pro-regenerative macrophages at P1 are not trafficked, this suggested a distinct role for LYVE1 in tissue-resident (TR) macrophages, consistent with its expression in developing and post-natal hearts. Macrophage-specific deletion of Lyve1 during neonatal heart injury revealed impaired heart regeneration, characterised by reduced neovascular response and function, suggesting a hitherto unappreciated role for LYVE1 in regulating the pro-regenerative function of TR macrophages. Conclusions Collectively, we reveal that cardiac lymphatics are developmentally compromised for immune cell clearance in early neonates, which enables retention of pro-regenerative TR macrophages, and that LYVE1 plays an essential role in TR macrophages enabling heart regeneration via the induction of coronary angiogenesis.

Impact of potential biomarkers, SNRPE, COX7C, and RPS27, on idiopathic Parkinson's disease.

Parkinson's disease (PD) is a progressive neuro-degenerative disorder most common in older adults which is associated with impairments in movement and other body functions. Most PD cases are classified as idiopathic PD (IPD), meaning that the etiology remains unidentified. To identify key genes and molecular mechanisms to identify biomarkers applicable to IPD. We applied a bioinformatics approach using a gene expression in whole blood dataset to pinpoint differentially expressed genes (DEGs) and pathways involved in IPD. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of DEGs were subsequently performed. A protein-protein interaction (PPI) network was then constructed to select hub genes that may influence IPD. We further investigated the levels of differentially methylated regions (DMRs) and differentially expressed microRNA (DEMs) of whole blood of patients with IPD to validate hub genes. Additionally, we examined the hub gene expression patterns in the substantia nigra (STN) using single-cell RNA sequencing datasets. In total, we identified 124 DEGs in the blood samples of patients with IPD, with GO and KEGG analyses highlighting their significant enrichment. Analysis of PPI networks revealed three major clusters and hub genes: small nuclear ribonucleoprotein polypeptide E (SNRPE), cytochrome C oxidase subunit 7C (COX7C), and ribosomal protein S27 (RPS27). DMRs and DEMs analyses revealed hub gene regulation via epigenetic and RNA interference. In particular, SNRPE and RPS27 showed identically regulated gene expression in the STN. This study suggests that SNRPE, COX7C, and RPS27 in whole-blood samples derived from patients may be useful biomarkers for IPD.