Cell-specific Expression Research Articles

Spatial transcriptomic analysis reveals significant differences in tumor microenvironment in HPV-dependent and HPV-independent vulvar squamous cell carcinoma.

Vulvar squamous cell carcinoma (VSCC) can be either HPV-dependent (HPVd) or HPV-independent (HPVi). HPVd VSCC typically occurs in younger women, has a more favorable prognosis, and develops from high-grade squamous intraepithelial lesions (HSIL). HPVi VSCC predominantly affects older women and arises within areas of chronic inflammation, particularly lichen sclerosis (LS). We utilized sequencing-based spatial transcriptomics to explore gene expression in a cohort of patients with HPVi and HPVd VSCC. We analysed gene expression in distinct areas (SCC, inflammation, LS, HSIL) from four early-stage VSCC cases (two HPVi, two HPVd) using the 10× Genomics Visium spatial transcriptomics platform. Cell-specific type expression was inferred using CIBERSORTx. 28,183 Visium spots were detected; each contained an estimated 20-50 cells. Reads per spot ranged from 9903 to 68,527. More genes were upregulated in HPVd (N=601) than HPVi (N=72) with distinct differences in Keratin and Collagen genes between etiologies. Gene expression was strikingly similar between SCC and adjacent inflammatory areas, regardless of etiology. IL-17 signaling was upregulated in HPVd samples. Surprisingly, CIBERSORTx inferred significantly more CD45+ cells in HPVi tissues than HPVd, especially CD4+ resting memory and follicular helper T cells in SCC areas. Immune cells moved from resting states in the pre-invasive tissues to activated states in the SCC and peri-tumoral inflammatory areas. This study represents the first application of spatial transcriptomics in VSCC, with significantly more immune cells identified in HPVi SCC than in HPVd SCC. These data will act as a baseline for future studies.

The molecular and cellular landscape of hypertrophic cardiomyopathy phenotypes: transition from obstructive to end-stage heart failure.

Hypertrophic cardiomyopathy (HCM) is a myocardial disorder which commonly presents as an obstructive or end-stage disease. This study aims to investigate the transcriptomic changes related to cardiac cell-specific expression profiles that underpin the molecular transition between the HCM phenotypes. This study utilizes bioinformatics meta-analysis to integrate independent datasets to generate a comprehensive gene expression profile of obstructive HCM and end-stage HCM phenotypes compared to donor hearts. Gene set enrichment and cellular deconvolution were applied to identify ontologies and pathways related to each phenotype and to enumerate cell abundances. The intersection between cell lineage genes and meta-genes was identified to explore the cellular contribution to the phenotypic molecular signatures. Meta-analysis revealed, enhanced muscle function and myocardial remodeling, alongside impaired immune and inflammatory processes in obstructive HCM. In contrast, enriched tissue matrix remodeling pathways and altered metabolic and signaling cascades were identified in end-stage HCM, indicating a shift towards cellular dysfunction and loss of homeostasis. These molecular profiles were associated with an altered cellular landscape, with increased cardiomyocytes and lower immune cell populations in obstructive samples but increased fibroblasts and smooth muscle cells in end-stage HCM, implicating extensive tissue remodeling. This study provides novel insights into the cellular contributions of contractile, immune, homeostatic, and vascular alterations underpinning each of the HCM phenotypes. KEY MESSAGES: HCM phenotypes are characterized by distinct molecular and cellular profiles. Obstructive HCM has an enriched contractile profile underpinned by an expanded cardiomyocyte population. End-stage HCM shifts the cellular profile towards extracellular and vascular remodeling.

SCPL48 regulates the vessel cell programmed cell death during xylem development in Arabidopsis thaliana.

Secondary cell wall (SCW) deposition is tightly coordinated with programmed cell death (PCD) during xylem development and plays a crucial role in plant stress responses. In this study, we characterized a serine carboxypeptidase-like gene, SCPL48, which exhibits xylem cell-specific expression patterns in stem xylem during vascular development. The scpl48 plants exhibited reduced stem xylem cell numbers, particularly vessel cells, accompanied by delayed organelle degradation during PCD and increased secondary wall thickness in xylem vessel cells. In contrast, SCPL48 overexpression resulted in increased vessel cell abundance and accelerated degradation of vessel cell contents, suggesting its critical role in xylem vessel cell differentiation. Notably, SCPL48 expression was significantly up-regulated in response to ABA treatment and drought stress, with SCPL48 overexpression lines demonstrating enhanced drought resistance. Further molecular analyses revealed that SCPL48 was directly targeted and transcriptionally activated by key SCW regulators VND6, and MYB46. Furthermore, the expression of PCD-related protease genes, including XCP1, XSP1, RNS3, MC9, γVPE, and CEP1, showed compensatory changes in both scpl48 mutants and SCPL48 overexpression lines. Collectively, our findings demonstrate that SCPL48 functions as a key regulator in xylem vessel cell differentiation, PCD and drought stress responses.

Unraveling molecular mechanisms in growth plate development advancing pediatric orthopedic interventions

Dynamic Growth Plate based on Molecular Profiling (DGMP) represents a pioneering approach to understanding the intricate molecular processes governing growth plate development, essential for advancing pediatric orthopedic treatments. Growth plates, located at the ends of long bones, are pivotal for bone elongation during childhood and adolescence, but disruptions in their molecular and cellular regulation can result in developmental abnormalities and orthopedic deformities. DGMP integrates genomic, transcriptomic, proteomic, and epigenomic analyses to uncover cell-specific expression patterns and regulatory elements critical to growth plate formation. By leveraging high-throughput sequencing, single-cell RNA (Ribonucleic Acid) sequencing, and spatial transcriptomics, DGMP facilitates the identification of diagnostic biomarkers and enables the development of targeted pharmacological therapies tailored to children with defective growth plates. Furthermore, in silico models simulating cellular differentiation and pathway interactions provide predictive insights into the long-term effects of interventions on bone development. This innovative framework not only enhances early and accurate detection of growth-related disorders but also supports the design of personalized treatments, ultimately improving clinical outcomes for affected children. As a precision medicine tool, DGMP has the potential to transform pediatric orthopedics by resolving challenges related to molecular data integration, spatiotemporal dynamics, and therapeutic application, thereby advancing the understanding and treatment of growth plate disorders.

Urinary TYROBP and HCK as genetic biomarkers for non-invasive diagnosis and therapeutic targeting in IgA nephropathy.

IgA nephropathy (IgAN) is a leading cause of renal failure, but its pathogenesis remains unclear, complicating diagnosis and treatment. The invasive nature of renal biopsy highlights the need for non-invasive diagnostic biomarkers. Bulk RNA sequencing (RNA-seq) of urine offers a promising approach for identifying molecular changes relevant to IgAN. We performed bulk RNA-seq on 53 urine samples from 11 untreated IgAN patients and 11 healthy controls, integrating these data with public renal RNA-seq, microarray, and scRNA-seq datasets. Machine learning was used to identify key differentially expressed genes, with protein expression validated by immunohistochemistry (IHC) and drug-target interactions explored via molecular docking. Urine RNA-seq analysis revealed differential expression profiles, from which TYROBP and HCK were identified as key biomarkers using machine learning. These biomarkers were validated in both a test cohort and an external validation cohort, demonstrating strong predictive accuracy. scRNA-seq confirmed their cell-specific expression patterns, correlating with renal function metrics such as GFR and serum creatinine. IHC further validated protein expression, and molecular docking suggested potential therapeutic interactions with IgAN treatments. TYROBP and HCK are promising non-invasive urinary biomarkers for IgAN. Their predictive accuracy, validated through machine learning, along with IHC confirmation and molecular docking insights, supports their potential for both diagnostic and therapeutic applications in IgAN.

NKX2.2 and KLF4 cooperate to regulate α-cell identity.

Transcription factors (TFs) are indispensable for maintaining cell identity through regulating cell-specific gene expression. Distinct cell identities derived from a common progenitor are frequently perpetuated by shared TFs, yet the mechanisms that enable these TFs to regulate cell-specific targets are poorly characterized. We report that the TF NKX2.2 is critical for the identity of pancreatic islet α cells by directly activating α-cell genes and repressing alternate islet cell fate genes. When compared with the known role of NKX2.2 in islet β cells, we demonstrate that NKX2.2 regulates α-cell genes, facilitated in part by α-cell-specific DNA binding at gene promoters. Furthermore, we have identified the reprogramming factor KLF4 as having enriched expression in α cells, where it co-occupies NKX2.2-bound α-cell promoters, is necessary for NKX2.2 promoter occupancy in α cells, and coregulates many NKX2.2 α-cell transcriptional targets. Overexpression of Klf4 in β cells is sufficient to manipulate chromatin accessibility, increase binding of NKX2.2 at α-cell-specific promoter sites, and alter expression of NKX2.2-regulated cell-specific targets. This study identifies KLF4 as a novel α-cell factor that cooperates with NKX2.2 to regulate α-cell identity.

ENPP1/CD203a-targeting heavy-chain antibody reveals cell-specific expression on human immune cells

ENPP1/CD203a is a membrane-bound ectonucleotidase capable of hydrolyzing ATP, cGAMP and other substrates. Its enzymatic activity plays an important role in the balance of extracellular adenine nucleotides and the modulation of purinergic signaling, in soft tissue calcification, and in the regulation of the cGAS/STING pathway. However, a detailed analysis of ENPP1 surface expression on human immune cells has not been performed. Here, we selected VHH domains from human ENPP1-immunized alpacas to generate heavy-chain antibodies targeting ENPP1, and analyzed cell surface expression on all circulating immune cell subsets using flow cytometry. We find high expression of ENPP1 in CD141high conventional dendritic cells (cDC1), while ENPP1 was not detectable on other dendritic cells and monocytes. In the lymphocytic compartment, only CD56bright natural killer cells and mucosal-associated invariant T cells (MAIT) express ENPP1. In contrast, all other T cell subpopulations, CD56dim natural killer cells and B lymphocytes do not or only minimally express ENPP1. In summary, we describe highly cell type-specific expression of ENPP1 in the immune system using a newly generated heavy-chain antibody. This reagent will help to decipher the function of ENPP1 in the regulation of the immune response, allow a quick identification of ENPP1-deficiency and of ENPP1-positive tumors, and constitutes the basis for targeted anti-tumor intervention.

Cell-Specific Control of Mammalian Gene Expression Using DNA Repair Inducible Ribozyme Switches.

The ability to control gene expression is vital for elucidating gene functions and developing next-generation therapeutics. Current techniques are challenged by the lack of cell-specific control designs or immunogenicity risk from foreign proteins. We develop a DNA repair inducible ribozyme switch that enables cell-specific control of gene expression in cells and in vivo. This strategy designs plasmids with a DNA lesion (8-oxoG and O6-MeG) site-specifically installed within the ribozyme encoding region, generating active hammerhead ribozyme for mRNA degradation due to transcriptional mutagenesis, whereas DNA repair yields a single-base mismatch in the ribozyme to abrogate its activity. This strategy is demonstrated to allow specific control of gene expression in cancer cells with overexpressed DNA repair enzymes such as MutY DNA glycosylase and O6-methylguanine-DNA-methyltransferases. It also shows the capability of conditionally regulating the expression of different proteins for signal reporting and gene editing, enabling DNA repair monitoring and targeted gene therapy in cancer cells. This strategy is demonstrated using the inducible CRISPR/Cas9 system for in vivo editing of oncogenic Polo-like kinase 1 in a mouse model, resulting in significant tumor growth suppression. The DNA repair inducible ribozyme switch may provide a compact system for cell-specific gene expression control toward precise gene therapy.

Long Noncoding RNA Function in Smooth Muscle Cell Plasticity and Atherosclerosis.

In the healthy mature artery, vascular cells, including endothelial cells, smooth muscle cells (SMCs), and fibroblasts are organized in different layers, performing specific functions. SMCs located in the media are in a differentiated state and exhibit a contractile phenotype. However, in response to vascular injury within the intima, stimuli from activated endothelial cells and recruited inflammatory cells reach SMCs and induce a series of remodeling events in them, known as phenotypic switching. Indeed, SMCs retain a certain degree of plasticity and are able to transdifferentiate into other cell types that are crucial for both the formation and development of atherosclerotic lesions. Because of their highly cell-specific expression profiles and their widely recognized contribution to physiological and disease-related biological processes, long noncoding RNAs have received increasing attention in atherosclerosis research. Dynamic fluctuations in their expression have been implicated in the regulation of SMC identity. Sophisticated technologies are now available to allow researchers to access single-cell transcriptomes and study long noncoding RNA function with unprecedented precision. Here, we discuss the state of the art of long noncoding RNAs regulation of SMC phenotypic switching, describing the methodologies used to approach this issue and evaluating the therapeutic perspectives of exploiting long noncoding RNAs as targets in atherosclerosis.

Single-cell multiomics reveal divergent effects of DNMT3A- and TET2-mutant clonal hematopoiesis in inflammatory response.

DNMT3A and TET2 are epigenetic regulator genes commonly mutated in age-related clonal hematopoiesis (CH). Despite having opposed epigenetic functions, these mutations are associated with increased all-cause mortality and a low risk for progression to hematologic neoplasms. Although individual impacts on the epigenome have been described using different model systems, the phenotypic complexity in humans remains to be elucidated. Here, we make use of a natural inflammatory response occurring during coronavirus disease 2019 (COVID-19), to understand the association of these mutations with inflammatory morbidity (acute respiratory distress syndrome [ARDS]) and mortality. We demonstrate the age-independent, negative impact of DNMT3A mutant (DNMT3Amt) CH on COVID-19-related ARDS and mortality. Using single-cell proteogenomics we show that DNMT3A mutations involve myeloid and lymphoid lineage cells. Using single-cell multiomics sequencing, we identify cell-specific gene expression changes associated with DNMT3A mutations, along with significant epigenomic deregulation affecting enhancer accessibility, resulting in overexpression of interleukin-32 (IL-32), a proinflammatory cytokine that can result in inflammasome activation in monocytes and macrophages. Finally, we show with single-cell resolution that the loss of function of DNMT3A is directly associated with increased chromatin accessibility in mutant cells. Hence, we demonstrate the negative prognostic impact of DNMT3Amt CH on COVID-19-related ARDS and mortality. DNMT3Amt CH in the context of COVID-19, was associated with inflammatory transcriptional priming, resulting in overexpression of IL32. This overexpression was secondary to increased chromatic accessibility, specific to DNMT3Amt CH cells. DNMT3Amt CH can thus serve as a potential biomarker for adverse outcomes in COVID-19.

Identification of Brain Cell Type-Specific Therapeutic Targets for Glioma From Genetics.

Previous research has demonstrated correlations between the complex types and functions of brain cells and the etiology of glioma. However, the causal relationship between gene expression regulation in specific brain cell types and glioma risk, along with its therapeutic implications, remains underexplored. Utilizing brain cell type-specific cis-expression quantitative trait loci (cis-eQTLs) and glioma genome-wide association study (GWAS) datasets in conjunction with Mendelian randomization (MR) and colocalization analyses, we conducted a systematic investigation to determine whether an association exists between the gene expression of specific brain cell types and the susceptibility to glioma, including its subtypes. Additionally, the potential pathogenicity was explored utilizing mediation and bioinformatics analyses. This exploration ultimately led to the identification of a series of brain cell-specific therapeutic targets. A total of 110 statistically significant and robust associations were identified through MR analysis, with most genes exhibiting causal effects exclusively in specific brain cell types or glioma subtypes. Bayesian colocalization analysis validated 36 associations involving 26 genes as potential brain cell-specific therapeutic targets. Mediation analysis revealed genes indirectly influencing glioma risk via telomere length. Bioinformatics analysis highlighted the involvement of these genes in glioma pathogenesis pathways and supported their enrichment in specific brain cell types. This study, employing an integrated approach, demonstrated the genetic susceptibility between brain cell-specific gene expression and the risk of glioma and its subtypes. Its findings offer novel insights into glioma etiology and underscore potential therapeutic targets specific to brain cell types.

Physical inactivity exacerbates pathologic inflammatory signalling at the single cell level in patients with systemic lupus

Physical activity is an adjunctive therapy that improves symptoms in people living with systemic lupus erythematosus (SLE), yet the mechanisms underlying this benefit remain unclear. We carried out a cohort study of 123 patients with SLE enrolled in the California Lupus Epidemiology Study (CLUES). The primary predictor variable was self-reported physical activity, which was measured using a previously validated instrument. We analyzed peripheral blood mononuclear cell (PBMC) single-cell RNA sequencing (scRNA-seq) data available from the cohort. From the scRNA-seq data, we compared immune cell frequencies, cell-specific gene expression, biological signalling pathways, and upstream cytokine activation states between physically active and inactive patients, adjusting for age, sex and race. We found that physical activity influenced immune cell frequencies, with sedentary patients most notably demonstrating greater CD4+ T cell lymphopenia (Padj=0.028). Differential gene expression analysis identified a transcriptional signature of physical inactivity across five cell types. In CD4+ and CD8+ T cells, this signature was characterized by 686 and 445 differentially expressed genes (Padj<0.1). Gene set enrichment analysis demonstrated enrichment of proinflammatory genes in the TNF-α signalling through NF-kB, interferon-γ (IFN-γ), IL2/STAT5, and IL6/JAK/STAT3 signalling pathways. Computational prediction of upstream cytokine activation states suggested CD4+ T cells from physically inactive patients exhibited increased activation of TNF-α, IFN-γ, IL1Β, and other proinflammatory cytokines. Network analysis demonstrated interconnectivity of genes driving the proinflammatory state of sedentary patients. Findings were consistent in sensitivity analyses adjusting for corticosteroid treatment and physical function. Taken together, our findings suggest a mechanistic explanation for the observed benefits of physical activity in patients with SLE. Specifically, we find that physical inactivity is associated with altered frequencies and transcriptional profiles of immune cell populations and may exacerbate pathologic inflammatory signalling via CD4+ and CD8+ T cells. This work was supported by the US National Institutes of Health (NIH) (R01 AR069616, K23HL138461-01A1, K23AT011768) the US CDC (U01DP0670), and the CZ Biohub.

A prognostic molecular signature of hepatic steatosis is spatially heterogeneous and dynamic in human liver.

Hepatic steatosis is a central phenotype in multi-system metabolic dysfunction and is increasing in parallelwith the obesity pandemic. We use a translational approach integrating clinical phenotyping and outcomes, circulating proteomics, and tissue transcriptomics to identify dynamic, functional biomarkers of hepatic steatosis. Using multi-modality imaging and broad proteomic profiling, we identify proteins implicated in the progression of hepatic steatosis that are largely encoded by genes enriched at the transcriptional level in the human liver. These transcripts are differentially expressed across areas of steatosis in spatial transcriptomics, and several are dynamic during stages of steatosis. Circulating multi-protein signatures of steatosis strongly associate with fatty liver disease and multi-system metabolic outcomes. Using a humanized "liver-on-a-chip" model, we induce hepatic steatosis, confirming cell-specific expression of prioritized targets. These results underscore the utility of this approach to identify a prognostic, functional, dynamic "liquid biopsy" of human liver, relevant to biomarker discovery and mechanistic research applications.

18F]NP3-627, a Candidate PET Imaging Agent Targeting the NLRP3 Inflammasome in the Central Nervous System.

We describe the identification of a candidate positron emission tomography (PET) imaging agent for the NLRP3 protein. NLRP3 plays a critical role in the immune system and has proven a difficult target for the development of imaging agents due to its low and cell-specific expression profile. A recently described series of pyridazine-based inhibitors, with improved permeability and brain-penetration properties, was used as a starting point for the development of a suitable PET imaging agent. Optimization of affinity, non-specific binding and pharmacokinetic properties led to the identification of aminopyridazine (R)-2-(6-((1-cyclopropylpiperidin-3-yl)amino)pyridazin-3-yl)-5-fluoro-3-methylphenol (17 b), which meets the preclinical profile of a successful imaging agent, and whose tritiated version demonstrated excellent specificity in a radioligand saturation binding assay, confirming its imaging potential.18F labeling led to [18F]NP3-627, the proposed PET imaging agent.

Decreased prefrontal glutamatergic function is associated with a reduced astrocyte-related gene expression in treatment-resistant depression

Glutamatergic dysfunction is involved in the pathophysiology of treatment-resistant depression (TRD). However, few physiological studies have evaluated its pathophysiology in vivo in individuals with TRD. Transcranial magnetic stimulation-electroencephalography (TMS-EEG) techniques can assess intracortical facilitation (ICF), which reflects glutamatergic neurophysiological function in specific cortical regions. The objectives of this study were (1) to compare glutamatergic receptor-mediated function as indexed with ICF TMS-EEG in the dorsolateral prefrontal cortex (DLPFC) between participants with TRD and healthy controls (HCs) and (2) to explore the relationships between cell-specific gene expression levels and the group difference in glutamatergic neural propagation using virtual histology approach. Sixty participants with TRD and thirty HCs were examined with ICF TMS-EEG measure (80 single-pulse TMS and paired-pulse ICF) in the left DLPFC. Both sensor and source-level ICF measures were computed to compare them between the TRD and HC groups. Furthermore, we conducted spatial correlation analyses interregionally between ICF glutamatergic activity and cell-specific gene expression levels employing the Allen Human Brain Atlas dataset. DLPFC-ICF at the sensor level was not significantly different between the two groups, whereas DLPFC-ICF at the source level was reduced in the TRD group compared with the HC group (p = 0.026). Moreover, the reduced ICF signal propagation of TRD correlated with astrocyte-specific gene expression level (p < 0.0001). The glutamatergic neural activities indexed by ICF in the left DLPFC were decreased in participants with TRD. Additionally, a relative reduction in glutamatergic signal propagation originating from the DLPFC in TRD may be associated with astrocytic abnormality.

T-follicular helper cells are epigenetically poised to transdifferentiate into T-regulatory type 1 cells.

Chronic antigenic stimulation can trigger the formation of interleukin 10 (IL-10)-producing T-regulatory type 1 (TR1) cells in vivo. We have recently shown that murine T-follicular helper (TFH) cells are precursors of TR1 cells and that the TFH-to-TR1 cell transdifferentiation process is characterized by the progressive loss and acquisition of opposing transcription factor gene expression programs that evolve through at least one transitional cell stage. Here, we use a broad range of bulk and single-cell transcriptional and epigenetic tools to investigate the epigenetic underpinnings of this process. At the single-cell level, the TFH-to-TR1 cell transition is accompanied by both, downregulation of TFH cell-specific gene expression due to loss of chromatin accessibility, and upregulation of TR1 cell-specific genes linked to chromatin regions that remain accessible throughout the transdifferentiation process, with minimal generation of new open chromatin regions. By interrogating the epigenetic status of accessible TR1 genes on purified TFH and conventional T-cells, we find that most of these genes, including Il10, are already poised for expression at the TFH cell stage. Whereas these genes are closed and hypermethylated in Tconv cells, they are accessible, hypomethylated, and enriched for H3K27ac-marked and hypomethylated active enhancers in TFH cells. These enhancers are enriched for binding sites for the TFH and TR1-associated transcription factors TOX-2, IRF4, and c-MAF. Together, these data suggest that the TR1 gene expression program is genetically imprinted at the TFH cell stage.

A multi-perspective deep learning framework for enhancer characterization and identification

Enhancers are vital elements in the genome that boost the transcriptional activity of neighboring genes and are essential in regulating cell-specific gene expression. Therefore, accurately identifying and characterizing enhancers is essential for comprehending gene regulatory networks and the development of related diseases. This study introduces MPDL-Enhancer, a novel multi-perspective deep learning framework aimed at enhancer characterization and identification. In this study, enhancer sequences are encoded using the dna2vec model along with features derived from the structural properties of DNA sequences. Subsequently, these representations are processed through a novel dual-scale deep neural network designed to discern subtle correlations and extended interactions embedded within the semantic content of DNA. The predictive phase of our methodology employs a Support Vector Machine classifier to render the final classification. To rigorously assess the efficacy of our approach, a comprehensive evaluation was executed utilizing an independent test dataset, thereby substantiating the robustness and accuracy of our model. Our methodology demonstrated superior performance over existing computational techniques, with an accuracy (ACC) of 81.00 %, a sensitivity (SN) of 79.00 %, and specificity (SP) of 83.00 %. The innovative dual-scale deep neural network and the unique feature representation strategy contributed to this performance improvement. MPDL-Enhancer has effectively characterized enhancer sequences and achieved excellent predictive performance. Building upon this foundation, we conducted an interpretability analysis of the model, which can assist researchers in identifying key features and patterns that affect the functionality of enhancers, thereby promoting a deeper understanding of gene regulatory networks.

Kidney mRNA-protein expression correlation: what can we learn from the Human Protein Atlas?

The Human Protein Atlas, with more than 10 million immunohistochemical images showing tissue- and cell-specific protein expression levels and subcellular localization information, is widely used in kidney research. The Human Protein Atlas contains comprehensive data on multi-tissue transcript and protein abundance, allowing for comparisons across tissues. However, while visual and intuitive to interpret, immunohistochemistry is limited by its semi-quantitative nature. This can lead to mismatches in protein expression measurements across different platforms. We performed a comparison of the Human Protein Atlas' kidney-specific RNA sequencing and immunohistochemistry data to determine whether the mRNA and protein abundance levels are concordant. Our study shows that there is a discordance between mRNA and protein expression in the kidney based on the Human Protein Atlas data. Using an external validation mass spectrometry dataset, we show that more than 500 proteins undetected by immunohistochemistry are robustly measured by mass spectrometry. The Human Protein Atlas transcriptome data, on the other hand, exhibit similar transcript detection levels as other kidney RNA-seq datasets. Discordance in mRNA-protein expression could be due to both biological and technical reasons, such as transcriptional dynamics, translation rates, protein half-lives, and measurement errors. This is further complicated by the heterogeneity of the kidney tissue itself, which can increase the discordance if the cell populations or tissue compartment samples do not match. As such, shedding light on the mRNA-protein relationship of the kidney-specific Human Protein Atlas data can provide context to our scientific inferences onrenal gene and protein quantification.

TMIC-51. NEUROIMMUNE-COMPETENT ORGANOID MODELING OF MICROGLIA/TUMOR INTERACTIONS AND DRUG RESPONSIVENESS

Abstract INTRODUCTION Due to its highly aggressive and infiltrative nature, lack of effective treatment options and localization in the skull base, diffuse intrinsic pontine glioma (DIPG) is universally fatal with less than a year median survival time. Studying how DIPG cells interact with brain cells in its microenvironment, including microglia which is the primary brain immune cell type, may lead to new therapeutic strategies to halt the invasion of DIPG into brain tissue. We developed a clinically relevant human immunocompetent brain organoid-DIPG fusion model for investigating the tumor invasion process at the cellular and molecular levels. METHODS Neuronal progenitor and GFP-labeled myeloid precursor cells were derived from human embryonic stem cells and combined to self-assemble and co-develop over two months into microglia-containing brain organoids (MiCBOs). The development of the MiCBOs as well as the distribution and motility of the microglia within the brain organoid was characterized by confocal and multiphoton microscopy, immunofluorescence staining and Western Blots. Confocal live-cell imaging was used to investigate the invasion of TdTomato-labeled tumor cells into MiCBO. We further performed single-cell RNA-Sequencing (scRNA-Seq) analysis to gain insight into the cell-specific gene expression changes after the confrontation of the MiCBOs with tumor spheroids. RESULTS MiCBOs contain viable, widely distributed and highly motile microglia as well as functionally mature neurons, highly resembling those in the human brain. scRNA-Seq showed distinct gene expression patterns in both microglia and tumor cells after confronting MiCBOs with DIPG spheroids, suggesting candidate signaling pathways between those two cell types. CONCLUSION Our novel MiCBO-DIPG fusion model provides a pathophysiologically-relevant system to elucidate molecular mechanisms underlying cell-cell interactions during tumor invasion in a human brain tissue context. This scalable model can be adapted to drug screening applications to identify therapeutics that modulate neuroimmune/tumor interactions and to establish the therapeutic index for anti-cancer medications.

Stress induces nucleobindin-1 mRNA and nesfatin-1-like peptide stimulates cortisol secretion in goldfish

Stress is a state of disrupted homeostasis triggered by physical or psychological stimuli that elicit adaptive responses at the molecular and cellular levels. In fish, the hypothalamus-pituitary-interrenal (HPI) axis mediates stress responses. Nesfatin-1 and a nesfatin-1-like peptide (NLP), derived from nucleobindin-1 (NUCB1), have been implicated in stress hormone regulation in mammals. This study investigated the cell-specific expression of NUCB1/NLP in HPI tissues and its effects on stress response in goldfish (Carassius auratus). NUCB1 mRNA is abundant in the hypothalamus, pituitary, and several other peripheral tissues of goldfish. NUCB1/NLP-like immunoreactivity was found in the brain and pituitary, co-localized with corticotropin-releasing factor receptor 1 (CRF-R1) in the hypothalamus, and with adrenocorticotrophic hormone (ACTH) in the pituitary. In vivo netting and restraint stress increased nucb1 and crf-r1 mRNAs in the brain and acth mRNA in the pituitary, as determined by RT-qPCR. Intraperitoneal injection of NLP increased cortisol in circulation, crf-r1 mRNA in the brain and acth mRNA in the pituitary. These findings suggest that NUCB1/NLP is a new player in mediating the endocrine stress response of goldfish through the HPI axis.