Heterogeneity Of Subpopulations Research Articles

CD169+ Skin Macrophages Function as a Specialized Subpopulation in Promoting Psoriasis-like Skin Disease in Mice

Skin macrophages are critical to maintain and restore skin homeostasis. They serve as major producers of cytokines and chemokines in the skin, participating in diverse biological processes such as wound healing and psoriasis. The heterogeneity and functional diversity of macrophage subpopulations endow them with multifaceted roles in psoriasis development. A distinct subpopulation of skin macrophages, characterized by high expression of CD169, has been reported to exist in both mouse and human skin. However, its role in psoriasis remains unknown. Here, we report that CD169+ macrophages exhibit increased abundance in imiquimod (IMQ) induced psoriasis-like skin lesions. Specific depletion of CD169+ macrophages in CD169-ditheria toxin receptor (CD169-DTR) mice inhibits IMQ-induced psoriasis, resulting in milder symptoms, diminished proinflammatory cytokine levels and reduced proportion of Th17 cells within the skin lesions. Furthermore, transcriptomic analysis uncovers enhanced activity in CD169+ macrophages when compared with CD169− macrophages, characterized by upregulated genes that are associated with cell activation and cell metabolism. Mechanistically, CD169+ macrophages isolated from IMQ-induced skin lesions produce more proinflammatory cytokines and exhibit enhanced ability to promote Th17 cell differentiation in vitro. Collectively, our findings highlight the crucial involvement of CD169+ macrophages in psoriasis development and offer novel insights into the heterogeneity of skin macrophages in the context of psoriasis.

Comprehensive single-cell analysis reveals heterogeneity of fibroblast subpopulations in ovarian cancer tissue microenvironment

BackgroundOvarian cancer, as a highly malignant tumor, features the critical involvement of tumor-associated fibroblasts in the ovarian cancer tissue microenvironment. However, due to the apparent heterogeneity within fibroblast subpopulations, the specific functions of these subpopulations in the ovarian cancer tissue microenvironment remain insufficiently elucidated. MethodsIn this study, we integrated single-cell sequencing data from 32 ovarian cancer samples derived from four distinct cohorts and 3226 bulk RNA-seq data from GEO and TCGA-OV cohorts. Utilizing computational frameworks such as Seurat, Monocle 2, Cellchat, and others, we analyzed the characteristics of the ovarian cancer tissue microenvironment, focusing particularly on fibroblast subpopulations and their differentiation trajectories. Employing the CIBERSORTX computational framework, we assessed various cellular components within the ovarian cancer tissue microenvironment and evaluated their associations with ovarian cancer prognosis. Additionally, we conducted Mendelian randomization analysis based on cis-eQTL to investigate causal relationships between gene expression and ovarian cancer. ResultsThrough integrative analysis, we identified 13 major cell types present in ovarian cancer tissues, including CD8+ T cells, malignant cells, and fibroblasts. Analysis of the tumor microenvironment (TME) cell proportions revealed a significant increase in the proportion of CD8+ T cells and CD4+ T cells in tumor tissues compared to normal tissues, while fibroblasts predominated in normal tissues. Further subgroup analysis of fibroblasts identified seven subgroups, with the MMP11+Fib subgroup showing the highest activity in the TGFβ signaling pathway. Single-cell analysis suggested that oxidative phosphorylation could be a key pathway driving fibroblast differentiation, and the ATRNL1+KCN + Fib subgroup exhibited chromosomal copy number variations. Prognostic analysis using a large sample size indicated that high infiltration of MMP11+ fibroblasts was associated with poor prognosis in ovarian cancer. SMR analysis identified 132 fibroblast differentiation-related genes, which were linked to pathways such as platinum drug resistance. ConclusionsIn the context of ovarian cancer, fibroblasts expressing MMP11 emerge as the primary drivers of the TGF-beta signaling pathway. Their presence correlates with an increased risk of adverse ovarian prognoses. Additionally, the genetic regulation governing the differentiation of fibroblasts associated with ovarian cancer correlates with the emergence of drug resistance.

Macrophage plasticity and function in cancer and pregnancy.

As the soil of life, the composition and shaping process of the immune microenvironment of the uterus is worth exploring. Macrophages, indispensable constituents of the innate immune system, are essential mediators of inflammation and tissue remodeling as well. Recent insights into the heterogeneity of macrophage subpopulations have renewed interest in their functional diversity in both physiological and pathological settings. Macrophages display remarkable plasticity and switch from one phenotype to another. Intrinsic plasticity enables tissue macrophages to perform a variety of functions in response to changing tissue contexts, such as cancer and pregnancy. The remarkable diversity and plasticity make macrophages particularly intriguing cells given their dichotomous role in either attacking or protecting tumors and semi-allogeneic fetuses, which of both are characterized functionally by immunomodulation and neovascularization. Here, we reviewed and compared novel perspectives on macrophage biology of these two settings, including origin, phenotype, differentiation, and essential roles in corresponding microenvironments, as informed by recent studies on the heterogeneity of macrophage identity and function, as well as their mechanisms that might offer opportunities for new therapeutic strategies on malignancy and pregnancy complications.

Spatially resolved transcriptomic profiling of placental development in dairy cow.

The placenta plays a crucial role in successful mammalian reproduction. Ruminant animals possess a semi-invasive placenta characterized by a highly vascularized structure formed by maternal endometrial caruncles and fetal placental cotyledons, essential for full-term fetal development. The cow placenta harbors at least two trophoblast cell populations: uninucleate (UNC) and binucleate (BNC) cells. However, the limited capacity to elucidate the transcriptomic dynamics of the placental natural environment has resulted in a poor understanding of both the molecular and cellular interactions between trophoblast cells and niches, and the molecular mechanisms governing trophoblast differentiation and functionalization. To fill this knowledge gap, we employed Stereo-seq to map spatial gene expression patterns at near single-cell resolution in the cow placenta at 90 and 130 days of gestation, attaining high-resolution, spatially resolved gene expression profiles. Based on clustering and cell marker gene expression analyses, key transcription factors, including YBX1 and NPAS2, were shown to regulate the heterogeneity of trophoblast cell subpopulations. Cell communication and trajectory analysis provided a framework for understanding cell-cell interactions and the differentiation of trophoblasts into BNCs in the placental microenvironment. Differential analysis of cell trajectories identified a set of genes involved in regulation of trophoblast differentiation. Additionally, spatial modules and co-variant genes that help shape specific tissue structures were identified. Together, these findings provide foundational insights into important biological pathways critical to the placental development and function in cows.

Astrocyte S100β expression and selective differentiation to GFAP and GS in the entorhinal cortex during ageing in the 3xTg-Alzheimer's disease mouse model

The study of astrocytes and its role in the development and evolution of neurodegenerative diseases, including Alzheimer’s disease (AD) is essential to fully understand their aetiology. The aim if this study is to deepen into the concept of the heterogeneity of astrocyte subpopulations in the EC and in particular the identification of differentially functioning astrocyte subpopulations that respond differently to AD progression. S100β protein belongs to group of small calcium regulators of cell membrane channels and pumps that are expressed by astrocytes and is hypothesised to play and have a relevant role in AD development. We analysed the selective differentiation of S100β-positive astrocytes into Glutamine synthetase (GS) and Glial fibrillary acidic protein (GFAP)-positive sub-groups in the entorhinal cortex (EC) of AD triple transgenic animal model (3xTg-AD). EC is the brain region earliest affected in humans AD but also in this closest animal model regarding their pathology and time course. We observed no changes in the number of S100β-positive astrocytes between 1 and 18 months of age in the EC of 3xTg-AD mice. However, we identified relevant morphological changes in S100β/GFAP positive astrocytes showing a significant reduction in their surface and volume whilst an increase in number and percentage. Furthermore, the percentage of S100β/GS positive astrocyte population was also increased in 18 months old 3xTg-AD mice compared to the non-Tg mice. Our findings reveal the presence of differentially controlled astrocyte populations that respond differently to AD progression in the EC of 3xTg-AD mice. These results highpoints the major astrocytic role together with its early and marked affection in AD and arguing in favour of its importance in neurogenerative diseases and potential target for new therapeutic approaches.

DNA methylation-based depiction of the immune microenvironment and immune-associated long non-coding RNAs in oral cavity squamous cell carcinomas

Oral cavity squamous cell carcinoma (OSCC) is a complex and dynamic disease characterized by clinicopathological and molecular heterogeneity. Spatial and temporal heterogeneity of cell subpopulations has been associated with cancer progression and implicated in the prognosis and therapy response. Emerging evidence indicates that aberrant epigenetic profiles in OSCC may foster an immunosuppressive tumor microenvironment by modulating the expression of immune-related long non-coding RNAs (lncRNAs). DNA methylation analysis was performed in 46 matched OSCC and normal adjacent tissue samples using a genome-wide platform (Infinium HumanMethylation450 BeadChip). Reference-based computational deconvolution (MethylCIBERSORT) was applied to infer the immune cell composition of the bulk samples. The expression levels of genes encoding immune markers and differentially methylated lncRNAs were investigated using The Cancer Genome Atlas dataset. OSCC specimens presented distinct immune cell composition, including the enrichment of monocyte lineage cells, natural killer cells, cytotoxic T-lymphocytes, regulatory T-lymphocytes, and neutrophils. In contrast, B-lymphocytes, effector T-lymphocytes, and fibroblasts were diminished in tumor samples. The hypomethylation of three immune-associated lncRNAs (MEG3, MIR155HG, and WFDC21P) at individual CpG sites was confirmed by bisulfite-pyrosequencing. Also, the upregulation of a set of immune markers (FOXP3, GZMB, IL10, IL2RA, TGFB, IFNG, TDO2, IDO1, and HIF1A) was detected. The immune cell composition, immune markers alteration, and dysregulation of immune-associated lncRNAs reinforce the impact of the immune microenvironment in OSCC. These concurrent factors contribute to tumor heterogeneity, suggesting that epi-immunotherapy could be an efficient alternative to treat OSCC.

Pancreatic β-cell senescence in diabetes: mechanisms, markers and therapies.

Cellular senescence is a response to a wide variety of stressors, including DNA damage, oncogene activation and physiologic aging, and pathologically accelerated senescence contributes to human disease, including diabetes mellitus. Indeed, recent work in this field has demonstrated a role for pancreatic β-cell senescence in the pathogenesis of Type 1 Diabetes, Type 2 Diabetes and monogenic diabetes. Small molecule or genetic targeting of senescent β-cells has shown promise as a novel therapeutic approach for preventing and treating diabetes. Despite these advances, major questions remain around the molecular mechanisms driving senescence in the β-cell, identification of molecular markers that distinguish senescent from non-senescent β-cell subpopulations, and translation of proof-of-concept therapies into novel treatments for diabetes in humans. Here, we summarize the current state of the field of β-cell senescence, highlighting insights from mouse models as well as studies on human islets and β-cells. We identify markers that have been used to detect β-cell senescence to unify future research efforts in this field. We discuss emerging concepts of the natural history of senescence in β-cells, heterogeneity of senescent β-cells subpopulations, role of sex differences in senescent responses, and the consequences of senescence on integrated islet function and microenvironment. As a young and developing field, there remain many open research questions which need to be addressed to move senescence-targeted approaches towards clinical investigation.

Integration analysis of single-cell and spatial transcriptomics reveal the cellular heterogeneity landscape in glioblastoma and establish a polygenic risk model.

Glioblastoma (GBM) is adults' most common and fatally malignant brain tumor. The heterogeneity is the leading cause of treatment failure. However, the relationship between cellular heterogeneity, tumor microenvironment, and GBM progression is still elusive. Integrated analysis of single-cell RNA sequencing (scRNA-seq) and spatial transcriptome sequencing (stRNA-seq) of GBM were conducted to analyze the spatial tumor microenvironment. We investigated the subpopulation heterogeneity of malignant cells through gene set enrichment analyses, cell communications analyses, and pseudotime analyses. Significantly changed genes of the pseudotime analysis were screened to create a tumor progress-related gene risk score (TPRGRS) using Cox regression algorithms in the bulkRNA-sequencing(bulkRNA-seq) dataset. We combined the TPRGRS and clinical characteristics to predict the prognosis of patients with GBM. Furthermore, functional analysis was applied to uncover the underlying mechanisms of the TPRGRS. GBM cells were accurately charted to their spatial locations and uncovered their spatial colocalization. The malignant cells were divided into five clusters with transcriptional and functional heterogeneity, including unclassified malignant cells and astrocyte-like, mesenchymal-like, oligodendrocytes-progenitor-like, and neural-progenitor-like malignant cells. Cell-cell communications analysis in scRNA-seq and stRNA-seq identified ligand-receptor pairs of the CXCL, EGF, FGF, and MIF signaling pathways as bridges implying that tumor microenvironment may cause malignant cells' transcriptomic adaptability and disease progression. Pseudotime analysis showed the differentiation trajectory of GBM cells from proneural to mesenchymal transition and identified genes or pathways that affect cell differentiation. TPRGRS could successfully divide patients with GBM in three datasets into high- and low-risk groups, which was proved to be a prognostic factor independent of routine clinicopathological characteristics. Functional analysis revealed the TPRGRS associated with growth factor binding, cytokine activity, signaling receptor activator activity functions, and oncogenic pathways. Further analysis revealed the association of the TPRGRS with gene mutations and immunity in GBM. Finally, the external datasets and qRT-PCR verified high expressions of the TPRGRS mRNAs in GBM cells. Our study provides novel insights into heterogeneity in GBM based on scRNA-seq and stRNA-seq data. Moreover, our study proposed a malignant cell transition-based TPRGRS through integrated analysis of bulkRNA-seq and scRNA-seq data, combined with the routine clinicopathological evaluation of tumors, which may provide more personalized drug regimens for GBM patients.

Isolation of PD-L1 Extracellular Vesicle Subpopulations Using DNA Computation Mediated Microfluidic Tandem Separation.

Accurate isolation of targeted extracellular vesicle (EV) is challenging due to the antigenic heterogeneity of EV subpopulations which are from different cell origins. Most EV subpopulations lack a single marker whose expression cleanly distinguishes them from mixed populations of closely related EVs. Here, a modular platform capable of taking multiple binding events as input, performing logic computations, and producing two independent outputs for tandem microchips for EV subpopulation isolation, is developed. Taking advantages of the excellent selectivity of dual-aptamer recognition and the sensitivity of tandem microchips, this method achieves, for the first time, sequential isolation of tumor PD-L1 EVs and non-tumor PD-L1 EVs. As a result, the developed platform can not only effectively distinguish cancer patients from healthy donors but also provides new clues for assessing immune heterogeneity. Moreover, the captured EVs can be released through a DNA hydrolysis reaction with high efficiency, which is compatible with downstream mass spectrometry for EV proteome profiling. Overall, this strategy is expected to isolate different EV subpopulations, translate EVs into reliable clinical biomarkers, and accurately investigate the biological functions of different EV subsets.

Is Separately Modeling Subpopulations Beneficial for Sequential Decision-Making?

When applying decision models, we often estimate input parameters using data. In healthcare and some other applications, data are collected from a population of different entities, such as patients. Thus, one faces a modeling question of whether to estimate different models for subpopulations (called stratifying). The potential benefit of stratifying comes from the heterogeneity of subpopulations. For example, patients who progress faster than others require a separate model and a tailored treatment plan. In “Is Separately Modeling Subpopulations Beneficial for Sequential Decision-Making?,” Lee provides theoretical results and empirical methods for deciding whether to stratify subpopulations. The article also presents how to use its results to select the best stratification among many. Improving medical decisions by tailoring to each subpopulation is a building block of precision medicine, and thus, this work aligns closely with the precision medicine paradigm.

THE MORFOFUNCTIONAL STATE OF PERIPHERAL ERYTHROCYTES AT CHRONIC HEART FAILURE AND VITAMIN D DEFICIENCY IN

The aim of the work To study the effect of vitamin D deciency in blood plasma on the morphofunctional state of peripheral blood erythrocytes after exercise in patients with chronic heart failure. Methods: scanning electron microscopy of peripheral blood erythrocytes, enzyme immunoassay to determine the level of vitamin D. Results. A morphological study revealed heterogeneity of erythrocyte subpopulations in 90% of patients with CHF and vitamin D deciency. In peripheral blood, in addition to normocytes with sufcient hemoglobinization, subpopulations of macro- and microcytes were recorded. In most patients with vitamin D deciency, several types of morphological changes in the shape of erythrocytes were revealed, manifested in the form of echino-, acantho- and stomatocytosis, which indicates destabilization of the erythrocyte's membrane. After a 6-minute walk test in CHF patients with vitamin D deciency, the number of discocytes decreases, the ability to deform decreases, lytic cells were recorded with a reduced number of normocytes. The Conclusion: identied morphobiochemical changes indicate the destructurization of the erythrocyte membrane components and have negative consequences, taking into account the likely impact on the somatic health of patients who, in addition to changes characteristic of CHF, receive signicant stress during physical exertion against the background of hypovitaminosis. D.

Integration of single-cell RNA-Seq and CyTOF data characterises heterogeneity of rare cell subpopulations

Background: The simultaneous measurement of cellular proteins and transcriptomes of single cell data has become an exciting new possibility with the advent of highly multiplexed multi-omics methodologies. However, mass cytometry (CyTOF) is a well-established, affordable technique for the analysis of proteomic data, which is well suited for the discovery and characterisation of very rare subpopulations of cells with a wealth of publicly available datasets. Methods: We present and evaluate the multimodal integration of single cell RNA-Seq and CyTOF datasets coming from both matched and unmatched samples, using two publicly available datasets. Results: We demonstrate that the integration of well annotated CyTOF data with single cell RNA sequencing can aid in the identification and annotation of cell populations with high accuracy. Furthermore, we show that the integration can provide imputed measurements of protein markers which are comparable to the current gold standard of antibody derived tags (ADT) from CITE-Seq for both matched and unmatched datasets. Using this methodology, we identify and transcriptionally characterise a rare subpopulation of CD11c positive B cells in high resolution using publicly available data and we unravel its heterogeneity in a single cell setting without the need to sort the cells in advance, in a manner which had not been previously possible. Conclusions: This approach provides the framework for using available proteomic and transcriptomic datasets in a unified and unbiased fashion to assist ongoing and future studies of cellular characterisation and biomarker identification.

Single-cell RNA sequencing reveals the role of cell heterogeneity in the sex difference in primary hyperparathyroidism.

To explore the difference in parathyroid tissue-derived cells between male and female PHPT patients. Resected parathyroid tissues were collected from PHPT patients of both sexes. Single cells were isolated and sequenced for RNA expression profiles. The cell sequencing data were annotated by cell type, followed by population analysis, functional analysis, pathway analysis, cell communication analysis, differential gene expression analysis, and pseudotime trajectory analysis. The subcluster analyses were also performed in the parathyroid cells. No substantial difference in the cell population, function, or communication is found between the two sexes. The interferon-a response, oxidative phosphorylation, and reactive oxygen species pathways are up-regulated in females than in male patients, mainly contributed by fibroblast cells, endothelial cells, parathyroid cells, and myeloid cells, which also have significantly more up-regulated pathways and cellular interactions than the other three cell types. The subcluster analysis of parathyroid cells identified five subpopulations: SPARCL1-OC and ISG15-OC are predominant in females, while more S100A13-PCC and PTHLH-OC are found in males. The cellular functions are also elevated in females compared with males. Cells from female patients show a higher expression level of parathyroid hormone (PTH) but a lower expression level of parathyroid hormone-like hormone (PTHLH). The cell pseudotime trajectory and pathway analyses show that the oxyphil cells may be more mature and functionally active than the chief cells in both sexes. These findings suggest that the sex difference in PHPT may be caused by the differentially expressed genes and activated pathways in different cell types in the parathyroid tissue. The heterogeneity of parathyroid cell subpopulations, especially in oxyphil cells, may be associated with the sex differences in PHPT pathogenesis.

Specialized functions and sexual dimorphism explain the functional diversity of the myeloid populations during glioma progression

Malignant gliomas are aggressive, hard-to-treat brain tumors. Their tumor microenvironment is massively infiltrated by myeloid cells, mostly brain-resident microglia, bone marrow (BM)-derived monocytes/macrophages, and dendritic cells that support tumor progression. Single-cell omics studies significantly dissected immune cell heterogeneity, but dynamics and specific functions of individual subpopulations were poorly recognized. We use Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-seq) to precisely dissect myeloid cell identities and functionalities in murine GL261 gliomas. We demonstrate that the diversity of myeloid cells infiltrating gliomas is dictated by cell type and cell state. Glioma-activated microglia are the major source of cytokines attracting other immune cells, whereas BM-derived cells show the monocyte-to-macrophage transition in the glioma microenvironment. This transition is coupled with a phenotypic switch from the IFN-related to antigen-presentation and tumor-supportive gene expression. Moreover, we found sex-dependent differences in transcriptional programs and composition of myeloid cells in murine and human glioblastomas.

The Convergence of FTIR and EVs: Emergence Strategy for Non-Invasive Cancer Markers Discovery.

In conjunction with imaging analysis, pathology-based assessments of biopsied tissue are the gold standard for diagnosing solid tumors. However, the disadvantages of tissue biopsies, such as being invasive, time-consuming, and labor-intensive, have urged the development of an alternate method, liquid biopsy, that involves sampling and clinical assessment of various bodily fluids for cancer diagnosis. Meanwhile, extracellular vesicles (EVs) are circulating biomarkers that carry molecular profiles of their cell or tissue origins and have emerged as one of the most promising biomarkers for cancer. Owing to the biological information that can be obtained through EVs' membrane surface markers and their cargo loaded with biomolecules such as nucleic acids, proteins, and lipids, EVs have become useful in cancer diagnosis and therapeutic applications. Fourier-transform infrared spectroscopy (FTIR) allows rapid, non-destructive, label-free molecular profiling of EVs with minimal sample preparation. Since the heterogeneity of EV subpopulations may result in complicated FTIR spectra that are highly diverse, computational-assisted FTIR spectroscopy is employed in many studies to provide fingerprint spectra of malignant and non-malignant samples, allowing classification with high accuracy, specificity, and sensitivity. In view of this, FTIR-EV approach carries a great potential in cancer detection. The progression of FTIR-based biomarker identification in EV research, the rationale of the integration of a computationally assisted approach, along with the challenges of clinical translation are the focus of this review.

Subpopulation Heterogeneity of NK Cells during the Genetic Modification for Subsequent Use in Targeted Therapy

Obtaining genetically engineered NK cells is a developing area of immunotherapy. In this work, we analyzed the subset heterogeneity of NK cells subjected to retroviral transduction, taking into account the content of adaptive NK cell progenitors. It was shown that subsets KIR2DL2/DL3+, as well as CD57-KIR2DL2/DL3+NKG2C+, can be modified with greater efficiency than the corresponding subsets that do not carry the KIR2DL2/DL3 and NKG2C markers. After genetic modification, the CD57-KIR2DL2/DL3+NKG2C+ cells began to express CD57 de novo, acquiring the adaptive NK cell phenotype.

EVAnalyzer: High content imaging for rigorous characterisation of single extracellular vesicles using standard laboratory equipment and a new open-source ImageJ/Fiji plugin.

Extracellular vesicle (EV) research increasingly demands for quantitative characterisation at the single vesicle level to address heterogeneity and complexity of EV subpopulations. Emerging, commercialised technologies for single EV analysis based on, for example, imaging flow cytometry or imaging after capture on chips generally require dedicated instrumentation and proprietary software not readily accessible to every lab. This limits their implementation for routine EV characterisation in the rapidly growing EV field. We and others have shown that single vesicles can be detected as light diffraction limited fluorescent spots using standard confocal and widefield fluorescence microscopes. Advancing this simple strategy into a process for routine EV quantitation, we developed 'EVAnalyzer', an ImageJ/Fiji (Fiji is just ImageJ) plugin for automated, quantitative single vesicle analysis from imaging data. Using EVAnalyzer, we established a robust protocol for capture, (immuno-)labelling and fluorescent imaging of EVs. To exemplify the application scope, the process was optimised and systematically tested for (i) quantification of EV subpopulations, (ii) validation of EV labelling reagents, (iii) in situ determination of antibody specificity, sensitivity and species cross-reactivity for EV markers and (iv) optimisation of genetic EV engineering. Additionally, we show that the process can be applied to synthetic nanoparticles, allowing to determine siRNA encapsulation efficiencies of lipid-based nanoparticles (LNPs) and protein loading of SiO2 nanoparticles. EVAnalyzer further provides a pipeline for automated quantification of cell uptake at the single cell-single vesicle level, thereby enabling high content EV cell uptake assays and plate-based screens. Notably, the entire procedure from sample preparation to the final data output is entirely based on standard reagents, materials, laboratory equipment and open access software. In summary, we show that EVAnalyzer enables rigorous characterisation of EVs with generally accessible tools. Since we further provide the plugin as open-source code, we expect EVAnalyzer to not only be a resource of immediate impact, but an open innovation platform for the EV and nanoparticle research communities.

A solution to the biophysical fractionation of extracellular vesicles: Acoustic Nanoscale Separation via Wave-pillar Excitation Resonance (ANSWER).

High-precision isolation of small extracellular vesicles (sEVs) from biofluids is essential toward developing next-generation liquid biopsies and regenerative therapies. However, current methods of sEV separation require specialized equipment and time-consuming protocols and have difficulties producing highly pure subpopulations of sEVs. Here, we present Acoustic Nanoscale Separation via Wave-pillar Excitation Resonance (ANSWER), which allows single-step, rapid (<10 min), high-purity (>96% small exosomes, >80% exomeres) fractionation of sEV subpopulations from biofluids without the need for any sample preprocessing. Particles are iteratively deflected in a size-selective manner via an excitation resonance. This previously unidentified phenomenon generates patterns of virtual, tunable, pillar-like acoustic field in a fluid using surface acoustic waves. Highly precise sEV fractionation without the need for sample preprocessing or complex nanofabrication methods has been demonstrated using ANSWER, showing potential as a powerful tool that will enable more in-depth studies into the complexity, heterogeneity, and functionality of sEV subpopulations.

TMET-30. ENHANCED RADIOSENSITIZATION OF GLIOMAS BY METABOLIC TARGETING OF SALVAGE PATHWAY OF NAD SYNTHESIS THROUGH NAMPT INHIBITION

Abstract BACKGROUND Pathway-specific targeted agents have failed to improve outcome in patients with high grade gliomas. Tumor recurrence is driven by glioma heterogeneity and emergence of therapy-resistant subpopulations. We have previously reported that metabolic targeting of NAMPT, the rate limiting enzyme in the NAD salvage synthesis pathway, circumvents glioma heterogeneity and induces cytotoxicity by mitochondrial membrane depolarization and generation of reactive oxygen species. Based on these data, we examined the potential for NAMPT inhibition to synergize with ionizing radiation to enhance glioma cytotoxicity in vitro and in vivo. METHODS Using a panel of genetically heterogeneous patient-derived glioma stem-like cells (GSC), we examined the effects of NAD targeting using KPT9274, a potent NAMPT inhibitor, in combination with ionizing radiation on cell proliferation and clonogenicity using Cell Titre Glo assay, colony formation assays and secondary sphere formation. Changes in DNA damage-related proteins were visualized by immunofluorescence assay and confocal microscopy. Effects on gene expression and protein levels were assessed using western blot, reverse phase protein array (RPPA) and RNA Seq. RESULTS NAMPT inhibition reduced cell proliferation rate, self-renewal and clonogenic capacity in vitro. Combining KPT-9274 with ionizing radiation caused synergistic inhibition of secondary sphere and colony formation of GSC. RPPA and RNASeq results showed downregulation of several DNA repair proteins which was further confirmed using immunofluorescence staining indicating a crucial role for these proteins in glioma resistance to therapies. Results of ongoing in vivo studies to assess the PK/PD, drug toxicity and survival benefits of this combination therapy in orthotopic GSC intracranial glioma mouse model will be reported. CONCLUSIONS Our results suggest that metabolic targeting through NAMPT inhibition sensitizes glioma cells to radiotherapy. Ongoing studies delineating the mechanistic basis of these effects and their impact in vivo as a potential rationale for clinical assessment will be reported.

Integration of single-cell RNA-Seq and CyTOF data characterises heterogeneity of rare cell subpopulations

Background: The simultaneous measurement of cellular proteins and transcriptomes of single cell data has become an exciting new possibility with the advent of highly multiplexed multi-omics methodologies. However, mass cytometry (CyTOF) is a well-established, affordable technique for the analysis of proteomic data, which is well suited for the discovery and characterisation of very rare subpopulations of cells with a wealth of publicly available datasets. Methods: We present and evaluate the multimodal integration of single cell RNA-Seq and CyTOF datasets coming from both matched and unmatched samples, using two publicly available datasets. Results: We demonstrate that the integration of well annotated CyTOF data with single cell RNA sequencing can aid in the identification and annotation of cell populations with high accuracy. Furthermore, we show that the integration can provide imputed measurements of protein markers which are comparable to the current gold standard of antibody derived tags (ADT) from CITE-Seq for both matched and unmatched datasets. Using this methodology, we identify and transcriptionally characterise a rare subpopulation of CD11c positive B cells in high resolution using publicly available data and we unravel its heterogeneity in a single cell setting without the need to sort the cells in advance, in a manner which had not been previously possible. Conclusions: This approach provides the framework for using available proteomic and transcriptomic datasets in a unified and unbiased fashion to assist ongoing and future studies of cellular characterisation and biomarker identification.