Cell Type-specific Expression Research Articles

FOXP1 regulates the development of excitatory synaptic inputs onto striatal neurons and induces phenotypic reversal with reinstatement.

Long-range glutamatergic inputs originating from the cortex and thalamus are indispensable for striatal development, providing the foundation for motor and cognitive functions. Despite their significance, transcriptional regulation governing these inputs remains largely unknown. We investigated the role of a transcription factor encoded by a high-risk autism-associated gene, FOXP1, in sculpting glutamatergic inputs onto spiny projection neurons (SPNs) within the striatum. We find a neuron subtype-specific role of FOXP1 in strengthening and maturing glutamatergic inputs onto dopamine receptor 2-expressing SPNs (D2 SPNs). We also find that FOXP1 promotes synaptically driven excitability in these neurons. Using single-nuclei RNA sequencing, we identify candidate genes that mediate these cell-autonomous processes through postnatal FOXP1 function at the post-synapse. Last, we demonstrate that postnatal FOXP1 reinstatement rescues electrophysiological deficits, cell type-specific gene expression changes, and behavioral phenotypes. Together, this study enhances our understanding of striatal circuit development and provides proof of concept for a therapeutic approach for FOXP1 syndrome and other neurodevelopmental disorders.

Deletion of CD44 promotes adipogenesis by regulating PPARɣ and cell cycle-related pathways.

CD44, a cell surface adhesion receptor and stem cell biomarker, is recently implicated in chronic metabolic diseases. Ablation of CD44 ameliorates adipose tissue inflammation and insulin resistance in obesity. Here, we investigated cell type specific CD44 expression in human and mouse adipose tissue and further studied how CD44 in preadipocytes regulates adipocyte function. Using Crispr Cas9-mdediated gene deletion and lentivirus-mediated gene re-expression, we discovered that deletion of CD44 promotes adipocyte differentiation and adipogenesis, whereas re-expression of CD44 abolishes this effect and decreases insulin responsiveness and adiponectin secretion in 3T3-L1 cells. Mechanistically, CD44 does so via suppressing Pparg expression. Using quantitative proteomics analysis, we further discovered that cell cycle-regulated pathways were mostly decreased by deletion of CD44. Indeed, re-expression of CD44 moderately restored expression of proteins involved in all phases of the cell cycle. These data were further supported by increased preadipocyte proliferation rates in CD44 deficient cells and re-expression of CD44 diminished this effect. Our data suggest that CD44 plays a crucial role in regulating adipogenesis and adipocyte function possibly through regulating PPARɣ and cell cycle-related pathways. This study provides evidence for the first time that CD44 expressed in preadipocytes plays key roles in regulating adipocyte function outside immune cells where CD44 is primarily expressed. Therefore, targeting CD44 in (pre)adipocytes may provide therapeutic potential to treat obesity-associated metabolic complications.

DISSECT: deep semi-supervised consistency regularization for accurate cell type fraction and gene expression estimation.

Cell deconvolution is the estimation of cell type fractions and cell type-specific gene expression from mixed data. An unmet challenge in cell deconvolution is the scarcity of realistic training data and the domain shift often observed in synthetic training data. Here, we show that two novel deep neural networks with simultaneous consistency regularization of the target and training domains significantly improve deconvolution performance. Our algorithm, DISSECT, outperforms competing algorithms in cell fraction and gene expression estimation by up to 14 percentage points. DISSECT can be easily adapted to other biomedical data types, as exemplified by our proteomic deconvolution experiments.

Identifying tumor type and cell type-specific gene expression alterations in pediatric central nervous system tumors.

Central nervous system (CNS) tumors are the leading cause of pediatric cancer death, and these patients have an increased risk for developing secondary neoplasms. Due to the low prevalence of pediatric CNS tumors, major advances in targeted therapies have been lagging compared to other adult tumors. We collect single nuclei RNA-seq data from 84,700 nuclei of 35 pediatric CNS tumors and three non-tumoral pediatric brain tissues and characterize tumor heterogeneity and transcriptomic alterations. We distinguish cell subpopulations associated with specific tumor types including radial glial cells in ependymomas and oligodendrocyte precursor cells in astrocytomas. In tumors, we observe pathways important in neural stem cell-like populations, a cell type previously associated with therapy resistance. Lastly, we identify transcriptomic alterations among pediatric CNS tumor types compared to non-tumor tissues, while accounting for cell type effects on gene expression. Our results suggest potential tumor type and cell type-specific targets for pediatric CNS tumor treatment. Here we address current gaps in understanding single nuclei gene expression profiles of previously under-investigated tumor types and enhance current knowledge of gene expression profiles of single cells of various pediatric CNS tumors.

Mitochondrial complex I deficiency stratifies idiopathic Parkinson’s disease

Idiopathic Parkinson’s disease (iPD) is believed to have a heterogeneous pathophysiology, but molecular disease subtypes have not been identified. Here, we show that iPD can be stratified according to the severity of neuronal respiratory complex I (CI) deficiency, and identify two emerging disease subtypes with distinct molecular and clinical profiles. The CI deficient (CI-PD) subtype accounts for approximately a fourth of all cases, and is characterized by anatomically widespread neuronal CI deficiency, a distinct cell type-specific gene expression profile, increased load of neuronal mtDNA deletions, and a predilection for non-tremor dominant motor phenotypes. In contrast, the non-CI deficient (nCI-PD) subtype exhibits no evidence of mitochondrial impairment outside the dopaminergic substantia nigra and has a predilection for a tremor dominant phenotype. These findings constitute a step towards resolving the biological heterogeneity of iPD with implications for both mechanistic understanding and treatment strategies.

Single cell transcriptomics unveiled that early life BDE-99 exposure reprogrammed the gut-liver axis to promote a pro-inflammatory metabolic signature in male mice at late adulthood.

Polybrominated diphenyl ethers (PBDEs) are legacy flame retardants that bioaccumulate in the environment. The gut microbiome is an important regulator of liver functions including xenobiotic biotransformation and immune regulation. We recently showed that neonatal exposure to polybrominated diphenyl ether-99 (BDE-99), a human breast milk-enriched PBDE congener, up-regulated pro-inflammation- and down-regulated drug metabolism-related genes predominantly in males in young adulthood. However, the persistence of dysregulation into late adulthood, differential impact of hepatic cell types, and the involvement of the gut microbiome from neonatal BDE-99 exposure remains unknown. To address these knowledge gaps, male C57BL/6 mouse pups were orally exposed to corn oil (10 ml/kg) or BDE-99 (57 mg/kg) once daily from postnatal days 2-4. At 15 months of age, neonatal BDE-99 exposure down-regulated xenobiotic and lipid metabolizing enzymes and up-regulated genes involved in microbial influx in hepatocytes. Neonatal BDE-99 exposure also increased the hepatic proportion of neutrophils and led to a predicted increase of macrophage migration inhibitory factor signaling. This was associated with decreased intestinal tight junction protein (Tjp) transcripts, altered gut environment, and dysregulation of inflammation-related metabolites. ScRNA-seq using germ-free (GF) mice demonstrated the necessity of a normal gut microbiome in maintaining hepatic immune tolerance. Microbiota transplant to GF mice using large intestinal microbiome from adults neonatally exposed to BDE-99 down-regulated Tjp transcripts and up-regulated several cytokines in the large intestine. In conclusion, neonatal BDE-99 exposure reprogrammed cell type-specific gene expression and communication in liver towards pro-inflammation, and BDE-99-mediated pro-inflammatory signatures may be partly due to the dysregulated gut environment.

Expression of GCaMP6s in the dentate gyrus induces tonic–clonic seizures

GCaMP is a genetically encoded calcium indicator (GECI) widely used in neuroscience research. It measures intracellular Ca2+ level by fluorescence changes as it directly binds to Ca2+. In this process, the effect of this calcium buffer on the intracellular calcium signaling and cell physiology is often not taken into consideration. However, growing evidence from calcium imaging studies shows GCaMP expression under certain conditions can generate aberrant activity, such as seizures. In this study, we examined the effect of GCaMP6 expression in the dentate gyrus (DG) on epileptogenesis. We found that viral expression of GCaMP6s but not GCaMP6f in the DG induces tonic–clonic seizures several weeks after viral injection. Cell-type specific expression of GCaMP6s revealed the granule cells (GCs) as the key player in GCaMP6s-induced epilepsy. Finally, by using slice electrophysiology, we demonstrated that GCaMP6s expression increases neuronal excitability in the GCs. Together, this study highlights the ability of GCaMP6s in DG-associated epileptogenesis.

Metacell-based differential expression analysis identifies cell type specific temporal gene response programs in COVID-19 patient PBMCs

By profiling gene expression in individual cells, single-cell RNA-sequencing (scRNA-seq) can resolve cellular heterogeneity and cell-type gene expression dynamics. Its application to time-series samples can identify temporal gene programs active in different cell types, for example, immune cells’ responses to viral infection. However, current scRNA-seq analysis has limitations. One is the low number of genes detected per cell. The second is insufficient replicates (often 1-2) due to high experimental cost. The third lies in the data analysis—treating individual cells as independent measurements leads to inflated statistics. To address these, we explore a new computational framework, specifically whether “metacells” constructed to maintain cellular heterogeneity within individual cell types (or clusters) can be used as “replicates” for increasing statistical rigor. Toward this, we applied SEACells to a time-series scRNA-seq dataset from peripheral blood mononuclear cells (PBMCs) after SARS-CoV-2 infection to construct metacells, and used them in maSigPro for quadratic regression to find significantly differentially expressed genes (DEGs) over time, followed by clustering expression velocity trends. We showed that such metacells retained greater expression variances and produced more biologically meaningful DEGs compared to either metacells generated randomly or from simple pseudobulk methods. More specifically, this approach correctly identified the known ISG15 interferon response program in almost all PBMC cell types and many DEGs enriched in the previously defined SARS-CoV-2 infection response pathway. It also uncovered additional and more cell type-specific temporal gene expression programs. Overall, our results demonstrate that the metacell-pseudoreplicate strategy could potentially overcome the limitation of 1-2 replicates.

Abstract LB248: Interrogating the cancer-immunity cycle through the lens of a large-scale single-cell atlas of immune checkpoint inhibition response and resistance

Abstract Introduction. The cancer-immunity cycle (CIC; Chen et al. 2013; Mellman et al. 2023) systematizes the current understanding of the factors (both suppressive and promoting) that together determine the anticancer immune responses. While the CIC is not limited to any single therapeutic modality, the framework is useful for understanding the mechanisms of immune checkpoint inhibition (ICI) response and resistance. Given its importance in the field, it is critical to be able to systematically examine and expand the CIC (or related frameworks) using new high-throughput data. Here we intersect the CIC framework with a large-scale atlas of single-cell RNA-seq data to provide a window into the CIC factors supported across multiple tumor types. Approach. We have previously developed the Single-Cell Immune Checkpoint Inhibition Atlas (ICI Atlas) which in its original version spanned 27 datasets and 1.9 million cells across a range of tumor types and ICI therapies. Motivated by rapid growth of data in the field, here we develop version 2 of the Atlas, over twice as large and consisting of 55 datasets and 4.4 million cells with cross-dataset integration via a transformer-based deep learning model. Of the 55 datasets, 47 contain both pre- and post-treatment samples, 2 contain only pre-treatment samples, and 6 contain only post-treatment samples. The Atlas spans 124 cell types and covers 19 different cancer types as well as 31 treatment strategies including 19 ICI therapies. Results. To determine the ICI Atlas support for each factor in the CIC, we analyzed the percent of studies where the factor’s cell type-specific pre-treatment expression was significantly higher in ICI responders (for promoting factors) or in non-responders (for inhibiting factors). We found that 16 cell type-specific CIC factors (12 promoting and 4 inhibiting) had strong support in the ICI Altas (supported in ≥ 50% of relevant studies). Specific steps of the CIC were associated with well-supported promoting factors, e.g. Step 2: interferon alpha/beta signaling pathway (dendritic cells/APCs, 50-100% of studies); Step 3: TCR signaling pathway (T cells; 58%); Step 5: CXCL9/10/11 (macrophages, 50-75%) and CCL5 (T cells, 58%); Step 5a: SELL (T cells, 68%); or inhibiting factors, e.g. Step 5b: IL10 (T cells, 53%). For some factors the support is tissue-specific, e.g. in tumor samples type-I IFN signaling was higher in dendritic cells and monocytes of responders while in blood this was reversed. Interestingly, certain co-stimulatory factors showed higher expression in non-responders (e.g. OX40 in T-cells, 53% of analyses, and 4-1BBL in macrophages, 50%). Our analysis also identifies a number of new factors whose expression is associated with response to ICI across the majority of ICI Atlas studies, providing opportunities for expanding current knowledge of cancer-immune system interplay and ICI response. Citation Format: Piotr Topolewski, Zofia Kochańska, Marlena Osipowicz, Roy Ronen, Janusz Dutkowski. Interrogating the cancer-immunity cycle through the lens of a large-scale single-cell atlas of immune checkpoint inhibition response and resistance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB248.

Cell-type specific molecular expression levels by restricted-dimensional cytometry.

Cytometric analysis has been commonly used to delineate distinct cell subpopulations among peripheral blood mononuclear cells by the differential expression of surface receptors. This capability has reached its apogee with high-dimensional approaches such as mass cytometry and spectral cytometry that include simultaneous assessment of 20-50 analytes. Unfortunately, this approach also engenders significant complexity with analytical and interpretational pitfalls. Here, we demonstrate a complementary approach with restricted-dimensionality to assess cell-type specific intracellular molecular expression levels at exceptional levels of precision. The expression of five analytes was individually assessed in four mononuclear cell-types from peripheral blood. Distinctions in expression levels were seen between cell-types and between samples from different donor groups. Mononuclear cell-type specific molecular expression levels distinguished pregnant from nonpregnant women and G-CSF-treated from untreated persons. Additionally, the precision of our analysis was sufficient to quantify a novel relationship between two molecules-Rel A and translocator protein-by correlational analysis. Restricted-dimensional cytometry can provide a complementary approach to define characteristics of cell-type specific intracellular protein and phosphoantigen expression in mononuclear cells.

302 Diagnostic Evidence Gauge of Spatial Transcriptomics (DEGAS-ST): Using transfer learning to map clinical data to spatial transcriptomics in prostate cancer

OBJECTIVES/GOALS: The 'field effect' is a concept in pathology that pre-malignant tissue changes forecast health. Spatial transcriptomics could detect these changes earlier than histopathology, suggesting new early cancer screening methods. Knowing how normal tissue damage relates to cancer’s origin and progression may improve long-term outcomes. METHODS/STUDY POPULATION: We trained DEGAS, our machine learning framework, with prostate cancer data, combining both general cancer patterns and in-depth genetic information from individual tumors. The Tumor Cancer Genome Atlas (TCGA) shows how gene patterns in tumors relate to patient outcomes, emphasizing the differences between tumors from different patients (intertumor). On the other hand, spatial transcriptomics (ST) shows the genetic variety within a single tumor (intratumor) but has limited samples, making it hard to know which genetic differences are important for treatment. DEGAS bridges these areas by finding tissue sections that resemble those in TCGA profiles and are key indicators of patient survival. DEGAS serves as a valuable tool for generating clinically-important hypotheses. RESULTS/ANTICIPATED RESULTS: DEGAS identified benign-appearing glands in a normal prostate as being highly associated with poor progression-free survival. These glands have transcriptional signatures similar to high-grade prostate cancer. We confirmed this finding in a separate prostate cancer ST dataset. By integrating single cell (SC) data we demonstrated that cells annotated as cancerous in the SC data map to regions of benign glands in the ST dataset. We pinpoint several genes, chiefly Microseminoprotein-β (MSMB, PSP94), where reduced expression is highly correlated with poor progression-free survival. Cell type specific differential expression analysis further revealed that loss of MSMB expression associated with poor outcomes occurs specifically in luminal epithelia, the putative progenitor of prostate cancer. DISCUSSION/SIGNIFICANCE: DEGAS reveals that normal-appearing tissue can be highly-associated with tumor progression and underscores the importance of the 'field effect' in cancer research. Traditional analysis may miss such nuance, hiding key transitional cell states. Validating gene markers could boost early cancer detection and understanding of metastasis.

Identifying gene expression programs in single-cell RNA-seq data using linear correlation explanation

ObjectiveGene expression analysis through single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of gene regulation in diverse cell types, tissues, and organisms. While existing methods primarily focus on identifying cell type-specific gene expression programs (GEPs), the characterization of GEPs associated with biological processes and stimuli responses remains limited. In this study, we aim to infer biologically meaningful GEPs that are associated with both cellular phenotypes and activity programs directly from scRNA-seq data. MethodsWe applied linear CorEx, a machine-learning-based approach, to infer GEPs by grouping genes based on total correlation optimization function in simulated and real-world scRNA-seq datasets. Additionally, we utilized a transfer learning approach to project CorEx-inferred GEPs to other scRNA-seq datasets. ResultsBy leveraging total correlation optimization, linear CorEx groups genes and demonstrates superior performance in identifying cell types and activity programs compared to similar methods using simulated data. Furthermore, we apply this same approach to real-world scRNA-seq data from the mouse dentate gyrus and embryonic colon development, uncovering biologically relevant GEPs related to cell types, developmental ages, and cell cycle programs. We also demonstrate the potential for transfer learning by evaluating similar datasets, showcasing the cross-species sensitivity of linear CorEx. ConclusionOur findings validate linear CorEx as a valuable tool for comprehensively analyzing complex signals in scRNA-seq data, leading to deeper insights into gene expression dynamics, cellular heterogeneity, and regulatory mechanisms.

272 Integrative Genomics Implicates Primary Impact on Cortical Development in Spina Bifida

INTRODUCTION: Spina bifida is one of the most common malformation of the central nervous system that is associated with poor neurodevelopmental outcomes. Altered neurodevelopment in spina bifida has been attributed to venting of CSF through the neural tube defect. Despite correction of the spinal defect, some patients still develop hydrocephalus with poor neurodevelopmental outcomes, suggesting incomplete understanding of disease pathogenesis. Recent human genetic efforts have identified candidate genes that confer spina bifida risk, however, the mechanisms linking gene mutations to altered neurodevelopment remain poorly understood. METHODS: We curated a list of 439 genes that confer risk to spina bifida from a whole-genome sequencing study of 310 individuals. We then mapped the spatiotemporal and cell-type specific expression of these risk genes onto bulk and single-cell RNA sequencing data of normally developing human brains covering the entire lifespan of human development. RESULTS: We found that spina bifida risk genes are enriched at post-conception weeks 5-6 and 25-38 in the developing human brain. After birth, spina bifida risk genes are enriched at postnatal months 6-10 and then after 60 years of age. At the cell type level, spina bifida risk genes are enriched in proliferative neuroprogenitor cells and microglia in the prenatal human cortex. CONCLUSIONS: Our analyses show that spina bifida risk genes are expressed in the developing human brain, suggesting a primary impact on brain development that is independent from the open caudal end of the neural tube defect. The finding that spina bifida risk genes continue to be expressed postnatally suggests a window for therapeutic intervention to optimize neurodevelopmental outcomes after birth in at least a subset of patients.

Single-nucleus RNA velocity reveals critical synaptic and cell-cycle dysregulations in neuropathologically confirmed Alzheimer’s disease

Typical differential single-nucleus gene expression (snRNA-seq) analyses in Alzheimer’s disease (AD) provide fixed snapshots of cellular alterations, making the accurate detection of temporal cell changes challenging. To characterize the dynamic cellular and transcriptomic differences in AD neuropathology, we apply the novel concept of RNA velocity to the study of single-nucleus RNA from the cortex of 60 subjects with varied levels of AD pathology. RNA velocity captures the rate of change of gene expression by comparing intronic and exonic sequence counts. We performed differential analyses to find the significant genes driving both cell type-specific RNA velocity and expression differences in AD, extensively compared these two transcriptomic metrics, and clarified their associations with multiple neuropathologic traits. The results were cross-validated in an independent dataset. Comparison of AD pathology-associated RNA velocity with parallel gene expression differences reveals sets of genes and molecular pathways that underlie the dynamic and static regimes of cell type-specific dysregulations underlying the disease. Differential RNA velocity and its linked progressive neuropathology point to significant dysregulations in synaptic organization and cell development across cell types. Notably, most of the genes underlying this synaptic dysregulation showed increased RNA velocity in AD subjects compared to controls. Accelerated cell changes were also observed in the AD subjects, suggesting that the precocious depletion of precursor cell pools might be associated with neurodegeneration. Overall, this study uncovers active molecular drivers of the spatiotemporal alterations in AD and offers novel insights towards gene- and cell-centric therapeutic strategies accounting for dynamic cell perturbations and synaptic disruptions.

Abstract 208: FGFR2 splice variant as a cell fate adjudicator determines clinical outcomes in non-small cell lung cancer

Abstract The splice variants specific protein expression in tumor cells presents promising targets for cancer therapy. The concept is supported by the recent introduction of the splice variant-specific antibody against FGFR2 IIIb (FGFR2b) in gastric cancer. Indeed, signaling of the two FGFR2 splice variants FGFR2b and FGFR2 IIIc (FGFR2c), whose expression is mutually exclusive on a cellular level, is mediated by different ligands and distinct downstream responses that can contribute to many aspects of tumorigenesis. Our study aimed to characterize the expression FGFR2b and 2c in non-malignant lung and non-small cell lung cancer (NSCLC) tissue and relate splice variant-specific expression to the histological and molecular background of cancer and its clinical impact.FGFR2b/FGFR2c isoforms expression was determined in RNA-seq data from 180 NSCLC patients and 19 tissues from normal lung (patient-matched). Cell-type specific expression and pan-cancer analysis of FGFR2 were explored using a public database, including DBTSS (NSCLC: 26, normal lung epithelium: 1, normal lung fibroblast 1) and CCLE (Total: 1019, NSCLC: 131), GTEx (normal lung tissue: 578) and HPA (scRNAseq for lung).Our results confirm a cell-specific expression in normal cells with dominance of FGFR2b in epithelial cells and FGFR2c in mesenchymal cells. In normal lung tissue, the FGFR2b variant showed high abundance. Pan-cancer analysis revealed FGFR2c dominant cancers (e.g., CNS tumors, kidney, liver) as well as FGFR2b dominant cancer types (e.g., breast, colon, lung cancer). The RNAseq data from our NSCLC cohort showed a chief expression of FGFR2b in 116 cases (64%), FGFR2c in 31 cases (17%), and a mixed FGFR2c/FGFR2b transcriptomics (18%). The ratio of FGFR2b/FGFR2c as a metric for splice variant dominance was associated with squamous histology, higher stage, and KRAS mutations. Differential gene expression analysis of cancer tissue and cell lines revealed an association of the splice variant FGFR2c to epithelial-mesenchymal transition (EMT) and the regulation of genes (ZEP1, ERSP1, CDH1) involved in the TGF-beta signal pathway. Finally, the ratio of FGFR2b/FGFR2c demonstrated a strong association with overall survival in NSCLC patients with the FGFR2c variant as unfavorable predictors (High vs low ratio, p = 0.01). Our study indicates cell-specific splice variant expression in non-malignant and malignant cells. The prognostic unfavorable impact of the FGFR2c variant on NSCLC patient survival might be explained by its association with TGF signaling and EMT. The observed clinical and biological difference between FGFR2b and FGFR2c dominated cancers gives further rationale to exploit splice variants as therapeutical targets. Citation Format: Hui Yu, Masafumi Horie, Amanda Lindberg, Max Backman, Neda Hekmati, Johanna Mattsson, Naoya Miyashita, Hans Brunnström, Fredrik Ponten, Akira Saito, Carina Strell, Patrick Micke. FGFR2 splice variant as a cell fate adjudicator determines clinical outcomes in non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 208.

Abstract 1243: Shifted mSWI/SNF complex assembly and function underlie therapeutically targetable dependencies in endometrial carcinoma

Abstract The mammalian SWI/SNF (mSWI/SNF) family of chromatin remodelers govern cell type-specific chromatin accessibility and gene expression and assemble as three distinct complexes: canonical BAF (cBAF), Polybromo-associated BAF (PBAF), and non-canonical BAF (ncBAF). ARID1A and ARID1B are paralog subunits that specifically nucleate the assembly of cBAF complexes and are the most frequently mutated mSWI/SNF components in human cancer, including in endometrial cancer. However, the biochemical and functional impacts of ARID1A/B loss, and hence cBAF complex disruption, on remaining PBAF and ncBAF complex activities, chromatin architecture, and gene expression remain poorly understood. Here, we define the molecular consequences of complete cBAF loss in models of aggressive de-differentiated endometrial carcinoma (DEC) harboring dual ARID1A/ARID1B mutations. Notably, re-expression of ARID1A in DEC cellular model systems biochemically restores cBAF complex assembly while reducing that of PBAF and ncBAF complexes, implicating functional contributions of differential mSWI/SNF family stoichiometry. We observe genome-wide increases in DNA accessibility at distal enhancer regions following ARID1A rescue, coupled with transcriptional changes at nearest genes including those associated with epithelial lineage differentiation, estrogen receptor signaling, and PI3K/AKT pathway signaling. Importantly, differential gene regulatory changes aligned with simultaneous cBAF restoration and reduction in ncBAF, and PBAF complex function mirror signatures derived from well-differentiated (WEC) and dedifferentiated (DEC) compartments of a collection of n= 15 primary human DEC cases profiled. Reduced ncBAF- and PBAF-mediated chromatin regulation resulting from either ARID1A rescue or ncBAF/PBAF genetic disruption attenuated oncogenic gene signature features such as MYC target genes, cell cycle checkpoint and DNA repair pathways and significantly reduced proliferative capacity. Finally, treatment of ARID1A/1B-mutant and ARID1A-mutant endometrial cell lines in culture and PDX models in vivo with a clinical-grade SMARCA4/2 ATPase inhibitor, FHD-286, markedly attenuated both cell proliferation and tumor growth. Further, FHD-286 synergized with carboplatin, leading to significant reduction in tumor burden in ARID1A- and ARID1A/B-mutant PDX models. Taken together, these findings reveal the oncogenic contributions of shifted of mSWI/SNF family complex abundance and chromatin-level gene regulatory function and suggest therapeutic utility of mSWI/SNF complex small molecule inhibitors in endometrial carcinoma and other cBAF-disrupted cancer types. Citation Format: Jessica Diane St. Laurent, Grace Xu, Alexander Ying, Bengul Gokbayrak, Ajinkya Patil, Akshay Sankar, Chae Young Shin, Daniel Same Guerra, David Kolin, David Huntsman, Yemin Wang, Cigall Kadoch. Shifted mSWI/SNF complex assembly and function underlie therapeutically targetable dependencies in endometrial carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1243.

ScDrugPrio: a framework for the analysis of single-cell transcriptomics to address multiple problems in precision medicine in immune-mediated inflammatory diseases.

Ineffective drug treatment is a major problem for many patients with immune-mediated inflammatory diseases (IMIDs). Important reasons are the lack of systematic solutions for drug prioritisation and repurposing based on characterisation of the complex and heterogeneous cellular and molecular changes in IMIDs. Here, we propose a computational framework, scDrugPrio, which constructs network models of inflammatory disease based on single-cell RNA sequencing (scRNA-seq) data. scDrugPrio constructs detailed network models of inflammatory diseases that integrate information on cell type-specific expression changes, altered cellular crosstalk and pharmacological properties for the selection and ranking of thousands of drugs. scDrugPrio was developed using a mouse model of antigen-induced arthritis and validated by improved precision/recall for approved drugs, as well as extensive in vitro, in vivo, and in silico studies of drugs that were predicted, but not approved, for the studied diseases. Next, scDrugPrio was applied to multiple sclerosis, Crohn's disease, and psoriatic arthritis, further supporting scDrugPrio through prioritisation of relevant and approved drugs. However, in contrast to the mouse model of arthritis, great interindividual cellular and gene expression differences were found in patients with the same diagnosis. Such differences could explain why some patients did or did not respond to treatment. This explanation was supported by the application of scDrugPrio to scRNA-seq data from eleven individual Crohn's disease patients. The analysis showed great variations in drug predictions between patients, for example, assigning a high rank to anti-TNF treatment in a responder and a low rank in a nonresponder to that treatment. We propose a computational framework, scDrugPrio, for drug prioritisation based on scRNA-seq of IMID disease. Application to individual patients indicates scDrugPrio's potential for personalised network-based drug screening on cellulome-, genome-, and drugome-wide scales. For this purpose, we made scDrugPrio into an easy-to-use R package ( https://github.com/SDTC-CPMed/scDrugPrio ).

A topographical atlas of α-synuclein dosage and cell type-specific expression in adult mouse brain and peripheral organs

Parkinson’s disease (PD) is the second most common neurodegenerative disease worldwide and presents pathologically with Lewy pathology and dopaminergic neurodegeneration. Lewy pathology contains aggregated α-synuclein (αSyn), a protein encoded by the SNCA gene which is also mutated or duplicated in a subset of familial PD cases. Due to its predominant presynaptic localization, immunostaining for the protein results in a diffuse reactivity pattern, providing little insight into the types of cells expressing αSyn. As a result, insight into αSyn expression-driven cellular vulnerability has been difficult to ascertain. Using a combination of knock-in mice that target αSyn to the nucleus (SncaNLS) and in situ hybridization of Snca in wild-type mice, we systematically mapped the topography and cell types expressing αSyn in the mouse brain, spinal cord, retina, and gut. We find a high degree of correlation between αSyn protein and RNA levels and further identify cell types with low and high αSyn content. We also find high αSyn expression in neurons, particularly those involved in PD, and to a lower extent in non-neuronal cell types, notably those of oligodendrocyte lineage, which are relevant to multiple system atrophy pathogenesis. Surprisingly, we also found that αSyn is relatively absent from select neuron types, e.g., ChAT-positive motor neurons, whereas enteric neurons universally express some degree of αSyn. Together, this integrated atlas provides insight into the cellular topography of αSyn, and provides a quantitative map to test hypotheses about the role of αSyn in network vulnerability, and thus serves investigations into PD pathogenesis and other α-synucleinopathies.

Dysregulated N6-methyladenosine modification in peripheral immune cells contributes to the pathogenesis of amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a progressive neurogenerative disorder with uncertain origins. Emerging evidence implicates N6-methyladenosine (m6A) modification in ALS pathogenesis. Methylated RNA immunoprecipitation sequencing (MeRIP-seq) and liquid chromatography-mass spectrometry were utilized for m6A profiling in peripheral immune cells and serum proteome analysis, respectively, in patients with ALS (n = 16) and controls (n = 6). The single-cell transcriptomic dataset (GSE174332) of primary motor cortex was further analyzed to illuminate the biological implications of differentially methylated genes and cell communication changes. Analysis of peripheral immune cells revealed extensive RNA hypermethylation, highlighting candidate genes with differential m6A modification and expression, including C-X3-C motif chemokine receptor 1 (CX3CR1). In RAW264.7 macrophages, disrupted CX3CR1 signaling affected chemotaxis, potentially influencing immune cell migration in ALS. Serum proteome analysis demonstrated the role of dysregulated immune cell migration in ALS. Cell type-specific expression variations of these genes in the central nervous system (CNS), particularly microglia, were observed. Intercellular communication between neurons and glial cells was selectively altered in ALS CNS. This integrated approach underscores m6A dysregulation in immune cells as a potential ALS contributor.

Beyond Quiescent and Active: Intermediate Microglial Transcriptomic States in a Mouse Model of Down Syndrome.

Research on microglia in Down syndrome (DS) has shown that microglial activation, increased inflammatory gene expression, and oxidative stress occur at different ages in DS brains. However, most studies resulted in simplistic definitions of microglia as quiescent or active, ignoring potential intermediate states. Indeed, recent work on microglial cells in young DS brains indicated that those evolve through different intermediate activation phenotypes before reaching a fully activated state. Here we used single nucleus RNA sequencing, to examine how trisomy affects microglial states in the Ts65Dn mouse model of DS. Despite no substantial changes in the proportion of glial populations, differential expression analysis revealed cell type-specific gene expression changes, most notably in astroglia, microglia, and oligodendroglia. Focusing on microglia, we identified differential expression of genes associated with different microglial states, including disease-associated microglia (DAMs), activated response microglia (ARMs), and human Alzheimer's disease microglia (HAMs), in trisomic microglia. Furthermore, pseudotime analysis reveals a unique reactivity profile in Ts65Dn microglia, with fewer in a homeostatic state and more in an intermediate aberrantly reactive state than in euploid microglia. This comprehensive understanding of microglial transcriptional dynamics sheds light on potential pathogenetic mechanisms but also possible avenues for therapy for neurodevelopmental disorders.