Rare Cell Populations Research Articles

Single Cell Transcriptomic Analysis of the Bone Marrow Microenvironment Uncovers a Role for Antigen Presentation Processes in MDS/AML Relapse after Allogeneic Hematopoietic Stem Cell Transplantation

Background: Bone marrow (BM) diseases such as myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) are characterized by a poor overall survival with allogeneic hematopoietic stem cell transplantation (allo-HSCT) often representing the only curative treatment option. However, patient mortality even after allo-HSCT remains high, mainly due to relapse. Previous studies showed involvement of immune escape processes in relapsed patients via downregulation of human leukocyte antigen class II (HLA-II) genes on leukemic blasts, or T cell exhaustion. Nevertheless, other components of the BM microenvironment (BMME) including mesenchymal stromal cells (MSC), endothelial cells and immune cells from the innate and adaptive immune system might play a role in relapse after allo-HSCT. This role remains unclear and needs further characterization. Therefore, we performed single cell transcriptomic analysis of different subpopulations of the BMME in MDS/AML patients who either achieved a long-term complete remission (CR) or relapsed after allo-HSCT. Methods: Patient BM aspirates were obtained before and after 3-6 months post allo-HSCT after written informed consent, and mononuclear cells were stored in liquid nitrogen. To reduce confounding factors (i.e., pre-conditioning treatment, age, sex, diagnosis, graft versus host disease), "best-matched" patient pairs in CR or relapse were established. Subsequently, 2 pairs of matched CR/relapse patients were chosen for further evaluation (Table 1). From each patient, 6 different BM subpopulations were FACS-sorted to enrich for rare cell populations: hematopoietic stem and progenitor cells (HSPC, CD45dim/CD34+), MSC (CD45-/CD271+), endothelial cells (CD45-/CD31+), monocytes (CD45dim/CD14+), granulocytes (CD45dim/CD11b+), T cells (SSClow/CD45hi/CD3+) and NK cells (SSClow/CD45hi/CD3-/CD56+/CD16+). A maximum number of 5x103 cells from each of these 6 cell populations from a single patient and time point were pooled back together in one lane of a 10X Genomics chip for single cell RNA sequencing library preparation. Data analysis was performed in R. Results: After UMAP clustering, 15 groups of cells could be identified by their conserved expression patterns, recapitulating the different input sorted subpopulations. Gene set enrichment analysis comparing cell types from patients in CR and relapse revealed enrichment in immune related pathways in many clusters from relapsing patients both before and after allo-HSCT. In contrast, this pathway enrichment was only observed in classical monocytes from patients in CR after allo-HSCT. Further gene expression analysis showed that within these pathways, the most significantly differentially expressed genes were HLA class I (HLA-I) and HLA-II genes, as well as the transcription factor STAT1. Of note, STAT1 expression was increased 1.2 to 2.3 fold in several cell types from patients in relapse compared to patients in CR. Similarly, the known STAT1 target genes HLA-A and HLA-C showed a 1.2 to 7.5 fold higher expression in several cell types from relapsed patients. Importantly, upregulations were observed in progenitor cells as well as in lymphocytes both before and after allo-HSCT, suggesting that STAT1 upregulation might trigger HLA-I genes expression and play a role in and/or serve as predictive marker of post-transplant relapse. Interestingly, HLA-II gene enrichment patterns were more heterogeneous. Indeed, before transplantation, genes such as HLA-DRA, HLA-DPB1 or CD74 were upregulated 1.4 to 3.0 fold in most cell types of patients in relapse, while after allo-HSCT a downregulation of 1.5 to 3.5 fold was observed in progenitor cells from patients in relapse, and was even more prominent in classical monocytes showing a 2 to 8 fold downregulation (Figure 1). This observation suggests that by preventing T cell activation via HLA-II antigen presentation, monocytes might also play a role in relapse mechanisms after allo-HSCT. Conclusions: Altogether, our results suggest that antigen presentation processes in the BMME via HLA-I and HLA-II could be involved in relapse mechanisms. Their expression level even before transplantation might be used as a predictor of relapse after allo-HSCT. Further analyses are ongoing to confirm our preliminary findings including functional analyses linking relapse with those observed differences in gene expression. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

From phenotypical investigation to RNA-sequencing for gene expression analysis: A workflow for single and pooled rare cells.

Combining phenotypical and molecular characterization of rare cells is challenging due to their scarcity and difficult handling. In oncology, circulating tumor cells (CTCs) are considered among the most important rare cell populations. Their phenotypic and molecular characterization is necessary to define the molecular mechanisms underlying their metastatic potential. Several approaches that require cell fixation make difficult downstream molecular investigations on RNA. Conversely, the DEPArray technology allows phenotypic analysis and handling of both fixed and unfixed cells, enabling a wider range of applications. Here, we describe an experimental workflow that allows the transcriptomic investigation of single and pooled OE33 cells undergone to DEPArray analysis and recovery. In addition, cells were tested at different conditions (unfixed, CellSearch fixative (CSF)- and ethanol (EtOH)-fixed cells). In a forward-looking perspective, this workflow will pave the way for novel strategies to characterize gene expression profiles of rare cells, both single-cell and low-resolution input.

Single-cell atlas of epithelial and stromal cell heterogeneity by lobe and strain in the mouse prostate.

Evaluating the complex interplay of cell types in the tissue microenvironment is critical to understanding the origin and progression of diseases in the prostate and potential opportunities for intervention. Mouse models are an essential tool to investigate the molecular and cell-type-specific contributions of prostate disease at an organismal level. While there are well-documented differences in the extent, timing, and nature of disease development in various genetically engineered and exposure-based mouse models in different mouse strains and prostate lobes within each mouse strain, the underlying molecular phenotypic differences in cell types across mouse strains and prostate lobes are incompletely understood. In this study, we used single-cell RNA-sequencing (scRNA-seq) methods to assess the single-cell transcriptomes of 6-month-old mouse prostates from two commonly used mouse strains, friend virus B/NIH jackson (FVB/NJ)(N = 2) and C57BL/6J (N = 3). For each mouse, the lobes of the prostate were dissected (anterior, dorsal, lateral, and ventral), and individual scRNA-seq libraries were generated. In situ and pathological analyses were used to explore the spatial and anatomical distributions of novel cell types and molecular markers defining these cell types. Data dimensionality reduction and clustering analysis of scRNA-seq data revealed that basal and luminal cells possessed strain-specific transcriptomic differences, with luminal cells also displaying marked lobe-specific differences. Gene set enrichment analysis comparing luminal cells by strain showed enrichment of proto-Oncogene targets in FVB/NJ mice. Additionally, three rare populations of epithelial cells clustered independently of strain and lobe: one population of luminal cells expressing Foxi1 and components of the vacuolar ATPase proton pump (Atp6v0d2 and Atp6v1g3), another population expressing Psca and other stem cell-associated genes (Ly6a/Sca-1, Tacstd2/Trop-2), and a neuroendocrine population expressing Chga, Chgb, and Syp. In contrast, stromal cell clusters, including fibroblasts, smooth muscle cells, endothelial cells, pericytes, and immune cell types, were conserved across strain and lobe, clustering largely by cell type and not by strain or lobe. One notable exception to this was the identification of two distinct fibroblast populations that we term subglandular fibroblasts and interstitial fibroblasts based on their strikingly distinct spatial distribution in the mouse prostate. Altogether, these data provide a practical reference of the transcriptional profiles of mouse prostate from two commonly used mouse strains and across all four prostate lobes.

Isolating and targeting a highly active, stochastic dendritic cell subpopulation for improved immune responses.

Dendritic cell (DC) activation via pathogen-associated molecular patterns (PAMPs) is critical for antigen presentation and development of adaptive immune responses, but the stochastic distribution of DC responses to PAMP signaling, especially during the initial stages of immune activation, is poorly understood. In this study, we isolate a unique DC subpopulation via preferential phagocytosis of microparticles (MPs) and characterize this subpopulation of "first responders" (FRs). We present results that show these cells (1) can be isolated and studied via both increased accumulation of the micron-sized particles and combinations of cell surface markers, (2) show increased responses to PAMPs, (3) facilitate adaptive immune responses by providing the initial paracrine signaling, and (4) can be selectively targeted by vaccines to modulate both antibody and Tcell responses invivo. This study presents insights into a temporally controlled, distinctive cell population that influences downstream immune responses. Furthermore, it demonstrates potential for improving vaccine designs via FR targeting.

Targeting Key Signaling Pathways in Glioblastoma Stem Cells for the Development of Efficient Chemo- and Immunotherapy

Glioblastoma multiforme (GBM) is the most aggressive and most common malignant brain tumor with poor patient survival despite therapeutic intervention. On the cellular level, GBM comprises a rare population of glioblastoma stem cells (GSCs), driving therapeutic resistance, invasion, and recurrence. GSCs have thus come into the focus of therapeutic strategies, although their targeting remains challenging. In the present study, we took advantage of three GSCs-populations recently established in our lab to investigate key signaling pathways and subsequent therapeutic strategies targeting GSCs. We observed that NF-κB, a crucial transcription factor in GBM progression, was expressed in all CD44+/CD133+/Nestin+-GSC-populations. Exposure to TNFα led to activation of NF-κB-RELA and/or NF-κB-c-REL, depending on the GBM type. GSCs further expressed the proto-oncogene MYC family, with MYChigh GSCs being predominantly located in the tumor spheres ("GROW"-state) while NF-κB-RELAhigh GSCs were migrating out of the sphere ("GO"-state). We efficiently targeted GSCs by the pharmacologic inhibition of NF-κB using PTDC/Bortezomib or inhibition of MYC by KJ-Pyr-9, which significantly reduced GSC-viability, even in comparison to the standard chemotherapeutic drug temozolomide. As an additional cell-therapeutic strategy, we showed that NK cells could kill GSCs. Our findings offer new perspectives for developing efficient patient-specific chemo- and immunotherapy against GBM.

Single-cell RNA sequencing reveals different signatures of mesenchymal stromal cell pluripotent-like and multipotent populations

Somatic stem cells are advantageous research targets for understanding the properties required to maintain stemness. Human bone marrow-mesenchymal stromal cells (BM-MSCs) were separated into pluripotent-like SSEA-3(+) Muse cells (Muse-MSCs) and multipotent SSEA-3(-) MSCs (MSCs) and were subjected to single-cell RNA sequencing analysis. Compared with MSCs, Muse-MSCs exhibited higher expression levels of the p53 repressor MDM2; signal acceptance-related genes EGF, VEGF, PDGF, WNT, TGFB, INHB, and CSF; ribosomal protein; and glycolysis and oxidative phosphorylation. Conversely, MSCs had higher expression levels of FGF and ANGPT; Rho family and caveola-related genes; amino acid and cofactor metabolism; MHC class I/II, and lysosomal enzyme genes than Muse-MSCs. Unsupervised clustering further divided Muse-MSCs into two clusters stratified by the expression of cell cycle-related genes, and MSCs into three clusters stratified by the expression of cell cycle-, cytoskeleton-, and extracellular matrix-related genes. This study evaluating the differentiation ability of BM-MSC subpopulations provides intriguing insights for understanding stemness.

Cells coexpressing both myeloid and endothelial markers are detectable in the spleen and bone marrow of patients with primary myelofibrosis

Different bodies of evidence support the existence of a common origin of hematopoietic and endothelial lineages; moreover, recent studies have indicated the presence of a hemogenic endothelium and a common hemato-endothelial precursor both in the embryo and in the cord blood. Conversely, to our knowledge, there is no evidence of such bipotential cells in human postnatal tissues or blood. In this study, we investigated the presence and phenotype of "transitional" cells in different tissues of patients with primary myelofibrosis (PMF). Using confocal microscopy and flow cytometry, we identified a rare cell population in the bone marrow and spleen of patients with PMF, which coexpresses the endothelial marker CD144 (vascular endothelial (VE)-cadherin), the pan-hematopoietic marker CD45, the early myeloid marker CD33, and CD34, a common endothelial and hematopoietic antigen.

Criteria for Accepting or Rejecting Cord Blood Units

Rare hematopoietic stem cell populations are responsible for the transplantation engraftment process. Umbilical cord blood (UCB) is usually processed to the total nucleated cell (TNC), but not to the mononuclear cell (MNC) fraction. TNC counts are used to determine UCB unit storage, release for transplantation and correlation with time to engraftment [1]. It has been mentioned in the literature that there are several factors that affect harvesting of cord blood stem cells [2]. It was set to analyze the relationship between fetal weight and other factors that led to rejection of CBUs brought to DCRC from public and private donations. In this retrospective study, 375 donations of CBUs from January 2018 to October 2018 at DCRC were recorded. From literature, factors that are usually involved in rejection of CBUs were recorded and analyzed to mark the leading cause of rejection criteria. In this study, it showed that results did not find infants’ birth weight or mother’s age to have any value in rejection. Other factors’ results will be discussed.

Metabolomics: Going Deeper, Going Broader, Going Further.

Metabolomics is a continuously dynamic field of research that is driven by demanding research questions and technological advances alike. In this review we highlight selected recent and ongoing developments in the area of mass spectrometry-based metabolomics. The field of view that can be seen through the metabolomics lens can be broadened by adoption of separation techniques such as hydrophilic interaction chromatography and ion mobility mass spectrometry (going broader). For a given biospecimen, deeper metabolomic analysis can be achieved by resolving smaller entities such as rare cell populations or even single cells using nano-LC and spatially resolved metabolomics or by extracting more useful information through improved metabolite identification in untargeted metabolomic experiments (going deeper). Integration of metabolomics with other (omics) data allows researchers to further advance in the understanding of the complex metabolic and regulatory networks in cells and model organisms (going further). Taken together, diverse fields of research from mechanistic studies to clinics to biotechnology applications profit from these technological developments.

Claudin-6 increases SNAI1, NANOG and SOX2 gene expression in human gastric adenocarcinoma AGS cells.

Gastric cancer is a heterogeneous disease associated to deregulated gastric epithelia tight junction barrier function and di novo expression of claudin-6; these changes are associated with epithelial-mesenchymal transition, enhanced invasiveness, metastatic progression, resistance to chemotherapy, and poor prognosis. Gastric cancer stem cells represent a rare population of cells within the tumor implicated in tumor growth and higher tumorigenic capacity. The possible relation between claudin-6 expression and the expression of some markers associated to epithelial mesenchymal transition and cancer stem cells in gastric cancer cells have never been explored. CD44, CD24, Twist, Villin, DCLK1, claudin-6, NANOG, E-Cadherin, SOX2, and SNAI1 expression was evaluated by immunofluorescence and cytofluorometry in wild type and Claudin-6 transfected AGS cells. Cell migration assays were also performed. Differentially expressed genes and biological processes analysis was performed to determine gene preponderance. The results showed that claudin-6 overexpression enriched the CD44 + /CD24- subpopulation with an overall increase in the expression and the number of CD44 + cells. A significant increase in NANOG, SOX2 and SNAI1 expression and enhanced cell migration was observed in claudin-6 transfected cells. Transcriptome analysis revealed 271 genes involved in enhanced biological processes with only 31 with a significantly p value; thirteen of those genes are closely associated to epithelial mesenchymal transition processes and folding and unfolding processes of proteins in the endoplasmic reticulum. The pro-tumorigenic effect of claudin-6 in gastric cancer could be associated to dedifferentiation of epithelial cells and an increase in di novo cancer stem cell genesis.

Identification of Novel Multi-Omics Expression Landscapes and Meta-Analysis of Landscape-Based Competitive Endogenous RNA Networks in ALDH+ Lung Adenocarcinoma Stem Cells.

ALDH+ H1975 lung adenocarcinoma stem cells (LSCs) are a rare cell population identified in lung adenocarcinoma (LUAD). LSCs can self-renew, drive tumor initiation, growth, metastasis, and recurrence and are also the predominant cause of poor prognosis due to their intrinsic resistance to drugs and chemotherapy. Consequently, LSCs are a promising target for LUAD therapy. Noncoding RNAs (ncRNAs), including microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs), exert many significant regulatory functions in the pathogenesis of human cancers, showing the necessity for a comprehensive understanding of the mechanisms that underlie lung carcinogenesis. Nonetheless, research on many known transcripts and messenger RNAs (mRNAs) has already generated new information. Unknown biomarkers in ncRNAs and systematic and comprehensive interrelation with unknown ncRNAs and mRNAs may provide further insights into the biology of LUAD. Herein, a set of novel ncRNAs that include miRNAs, lncRNAs, and circRNAs were identified, and differentially expressed patterns of ncRNAs and mRNAs in LSCs and ALDH-H1975 LUAD tumor cells (LTCs) were obtained using stringent bioinformatics pipelines. Through a meta-analysis of the identified landscapes, novel competitive endogenous RNA (ceRNA) networks were constructed to reveal the potential molecular mechanisms that regulate the hallmarks of LSCs and LTCs. This study presents a summary of novel ncRNAs and the fundamental roles of differentially expressed ncRNAs implicated in the activity of LSCs and LTCs. In addition, the study also provides a comprehensive resource for the future identification of diagnostic, therapeutic, and prognostic biomarkers in LUAD.

Silibinin exhibits anti-tumor effects in a breast cancer stem cell model by targeting stemness and induction of differentiation and apoptosis.

Introduction: Malignant breast cancer (BC) frequently contains a rare population of cells called cancer stem cells which underlie tumor relapse and metastasis, and targeting these cells may improve treatment options and outcomes for patients with BC. The aim of the present study was to determine the effect of silibinin on the self-renewal capacity, tumorgenicity, and metastatic potential of mammospheres. Methods: The effect of silibinin on viability and proliferation of MCF-7, MDA-MB-231 mammospheres, and MDA-MB-468 cell aggregation was determined after 72-120 hours of treatment. Colony and sphere formation ability, and the expression of stemness, differentiation, and epithelial-mesenchymal-transition (EMT)-associated genes were assessed by reverse transcription-quantitative polymerase chain reaction (qRT-PCR) in mammospheres treated with an IC50 dose of silibinin. Additionally, the antitumor capacity of silibinin was assessed in vivo, in mice. Results: The results of the present study showed that silibinin decreased the viability of all mammospheres derived from MCF-7, MDA-MB-231, and MDA-MB-468 cell aggregation in a dose-dependent manner. Colony and sphere-forming ability, as well as the expression of genes associated with EMT were reduced in mammospheres treated with silibinin. Additionally, the expression of genes associated with stemness and metastasis was also decreased and the expression of genes associated with differentiation were increased. Intra-tumoral injection of 2 mg/kg silibinin decreased tumor volumes in mice by 2.8 fold. Conclusion: The present study demonstrated that silibinin may have exerted its anti-tumor effects in BC by targeting the BC stem cells, reducing the tumorgenicity and metastasis. Therefore, silibinin may be a potential adjuvant for treatment of BC.

Scarf enables a highly memory-efficient analysis of large-scale single-cell genomics data

As the scale of single-cell genomics experiments grows into the millions, the computational requirements to process this data are beyond the reach of many. Herein we present Scarf, a modularly designed Python package that seamlessly interoperates with other single-cell toolkits and allows for memory-efficient single-cell analysis of millions of cells on a laptop or low-cost devices like single-board computers. We demonstrate Scarf’s memory and compute-time efficiency by applying it to the largest existing single-cell RNA-Seq and ATAC-Seq datasets. Scarf wraps memory-efficient implementations of a graph-based t-stochastic neighbour embedding and hierarchical clustering algorithm. Moreover, Scarf performs accurate reference-anchored mapping of datasets while maintaining memory efficiency. By implementing a subsampling algorithm, Scarf additionally has the capacity to generate representative sampling of cells from a given dataset wherein rare cell populations and lineage differentiation trajectories are conserved. Together, Scarf provides a framework wherein any researcher can perform advanced processing, subsampling, reanalysis, and integration of atlas-scale datasets on standard laptop computers. Scarf is available on Github: https://github.com/parashardhapola/scarf.

ScGENA: A Single-Cell Gene Coexpression Network Analysis Framework for Clustering Cell Types and Revealing Biological Mechanisms.

Single-cell RNA-sequencing (scRNA-seq) is a recent high-throughput technique that can measure gene expression, reveal cell heterogeneity, rare and complex cell populations, and discover cell types and their relationships. The analysis of scRNA-seq data is challenging because of transcripts sparsity, replication noise, and outlier cell populations. A gene coexpression network (GCN) analysis effectively deciphers phenotypic differences in specific states by describing gene–gene pairwise relationships. The underlying gene modules with different coexpression patterns partially bridge the gap between genotype and phenotype. This study presents a new framework called scGENA (single-cell gene coexpression network analysis) for GCN analysis based on scRNA-seq data. Although there are several methods for scRNA-seq data analysis, we aim to build an integrative pipeline for several purposes that cover primary data preprocessing, including data exploration, quality control, normalization, imputation, and dimensionality reduction of clustering as downstream of GCN analysis. To demonstrate this integrated workflow, an scRNA-seq dataset of the human diabetic pancreas with 1600 cells and 39,851 genes was implemented to perform all these processes in practice. As a result, scGENA is demonstrated to uncover interesting gene modules behind complex diseases, which reveal biological mechanisms. scGENA provides a state-of-the-art method for gene coexpression analysis for scRNA-seq data.

LB971 HiCuT: An efficient and low input method to identify protein-centric chromatin interactions

Protein-DNA interactions regulate gene expression, and some interactions occur over large distances, such that they are nearby in 3-D space but are separated by many nucleotides in the linear genome. These long-range chromatin loops are essential for gene regulation but remain difficult to interrogate. Methods to capture these chromatin interactions mediated by a specific protein factor include Hi-C sequencing coupled with ChIP-seq, ChIA-PET, PLAC-seq, and HiChIP. These methods all require high amounts of starting material (0.5M – 100M cells) and sequencing at high depth (a minimum of 150M reads per sample), which limits their general use. Here, we describe Hi-C Coupled chromatin cleavage and Tagmentation (HiCuT), an enzyme-based tagmentation strategy that provides efficient and high-resolution protein-centric chromatin mapping from as few as 100,000 cells and 12M sequencing reads per sample. Activated transposase generates fragment libraries with extremely low background signal that are easily interpreted with minimal computational processing. This permits cost-effective protein-centric 3D genome profiling in systems previously unmeasurable, including primary cells and human tissue samples. We validated HiCuT method for two different proteins, CTCF and RNA polymerase 2 in GM12878 cells. Next, we performed HiCuT on primary skin cells with an anti H3K27ac antibody and identified previously validated long-range chromatin interactions. Importantly, the high resolution generated by HiCuT permitted annotation of previously identified single nucleotide polymorphisms (SNPs) in skin disease to potential target genes. Thus, HiCuT will permit protein-centric 3-D genome binding assessment in rare cell populations that were not feasible previously, including primary cells, human tissue samples, and personalized epigenomics.

Docetaxel in combination with metformin enhances antitumour efficacy in metastatic breast carcinoma models: a promising cancer targeting based on PEGylated liposomes.

Metformin has been shown to kill cancer stem-like cells in genetically various types of breast carcinoma. With the aim to simultaneously eradicate the bulk population of tumour cells and the rare population of cancer stem-like cells in breast cancer tissues, we used the combination chemotherapy of docetaxel (DTX) with metformin (MET). Furthermore, we introduce an active loading method based on ammonium sulphate 250 mM (SA) for encapsulating docetaxel into liposomes. Docetaxel and metformin encapsulated into PEGylated liposomes with two different methods based on remote or passive loading methods, respectively. The size and surface charge of the liposomes were characterized. DTX content in the nanoliposomes was measured by the high-performance liquid chromatography method. The drug release profiles were evaluated in phosphate-buffered dextrose 5% with the pH of 6.5 and 7.4. We examined the antitumour activity of Taxotere (TAX), and liposomal formulation of DTX and MET as a monotherapy or combination therapy. The biodistribution of liposomes was also investigated using 99mTc hexamethyl propylene amine oxime method in BALB/c mice bearing 4T1 breast carcinoma tumours. The final formulations were prepared according to the best physicochemical characteristics which were HSPC/mPEG2000-DSPE/Chol (DTX liposomes) and HSPC/DPPG/mPEG2000-DSPE/Chol (MET liposomes), at molar ratios of 85/5/10 and (55/5/5/35), respectively. In vivo experiments showed that when free or liposomal metformin used in combination with liposomal docetaxel, they prolonged median survival time (MST) from 31 in the control group to 46 days, which demonstrates their promising effects on the survival of the 4T1 breast carcinoma mice models. Moreover, combination therapies could significantly increase life span in comparison with phosphate-buffered saline (PBS) and Taxotere groups at the same dose. Furthermore, in the combination therapy study, treatment with DTX liposomes prepared by ammonium sulphate 250 mM buffer alone resulted in similar therapeutic efficacy to combination therapy. The biodistribution study exhibited significant accumulation of DTX liposomes in the tumours due to the Enhanced Permeability and Retention effect. This study also showed that metformin-based combinatorial chemotherapies have superior efficacy versus their corresponding monotherapy counterparts at same doses. The findings confirm that liposomes based on ammonium sulphate 250 mM could be as a promising formulation for efficient DTX delivering and cancer targeting and therefore merit further investigations.

Exploring the mechanisms of immunomodulation by a commensal Clostridium species

The microbiome is intricately linked to human health and, when dysregulated, can cause disease. It has been shown that specific members of the intestinal microbiota regulate immunity, a finding that offers an approach for treating autoimmune disease through microbiome engineering. In previously published work, we identified Clostridium immunis, a new human-derived commensal bacterial species that protects mice against colitis. To understand the host immunological response to C. immunis, we performed comprehensive flow cytometric analysis of the colonic immune system of C. immunis-treated mice. We observed a significant decrease in the number of group 3 innate lymphoid cells (ILC3s), a rare but critical tissue-resident immune cell population that has been implicated in autoimmune diseases. We hypothesize that C. immunisproduces a bioactive molecule that downregulates ILC3s. To identify the genetic determinants of ILC3 downregulation by C. immunis, we compared the ability of closely related clostridia to modulate ILC3-produced cytokines in a colonic explant model. By excluding genes encoded by two inactive clostridia strains, we managed to identify 40 genes that are associated with ILC3 modulation. We similarly observed that C. immunis culture supernatant contained activity. By excluding genes that have predicted intracellular products, we further narrowed this list to 8 candidate genes. Critically, we have recently developed a method to perform targeted genetic knockouts in C. immunis, and are currently generating mutants for these genes. This work will therefore identify the gene product required for ILC3 modulation and potentially identify novel classes of bacterially derived molecules to treat ILC3-driven disease.

Id3 expression identifies CD4+ memory Th1 cells

Memory CD4+ T cells play a pivotal role in mediating long-term protective immunity, positioning them as an important target in vaccine development. However, multiple functionally distinct helper CD4+ T-cell subsets can arise in response to a single invading pathogen, complicating the identification of rare populations of memory precursor cells during the effector phase of infection and memory CD4+ T cells following pathogen clearance and the contraction phase of infection. Furthermore, current literature remains unclear regarding whether a single CD4+ memory T-cell lineage gives rise to secondary CD4+ T helper subsets or if there are unique memory precursor cells within each helper lineage. A majority of T follicular helper (Tfh) cells, which have established memory potential, express Id3, an inhibitor of E protein transcription factors, following acute viral infection. We show that expression of Id3 definitively identified a subset of cells within both the CD4+ Tfh and T helper 1 (Th1) lineages at memory time points that exhibited memory potential, with the capacity for significant re-expansion in response to secondary infection. Notably, we demonstrate that a subset of Th1 cells that survive into the memory phase were marked by Id3 expression and possessed the potential for enhanced expansion and generation of both Th1 and Tfh secondary effector cell populations in a secondary response to pathogen. Additionally, these cells exhibited enrichment of key molecules associated with memory potential when compared with Id3lo Th1 cells. Therefore, we propose that Id3 expression serves as an important marker to indicate multipotent potential in memory CD4+ T cells.

Circulating tumor cells from melanoma patients show phenotypic plasticity and metastatic potential in xenograft NOD.CB17 mice

BackgroundInnovative therapies have improved the overall survival in melanoma, although a high number of patients still experience disease progression or recurrence. Ex-vivo culture of circulating tumour cells (CTCs) represents a valuable laboratory resource for in-depth characterization of rare cell populations responsible for disease progression.MethodsCTCs from patients with metastatic melanoma were in-vitro established. Their stemness was demonstrated by both phenotypic and genotypic assays, as well as by functional studies. Xenograft experiments in NOD.CB17 mice injected with CTCs from a single patient were completed. Data were analysed by Student’s test and results expressed as mean ± SEM.ResultsCTCs share the mutational profile with primary cells, an intermediate epithelial-mesenchymal transition (EMT) phenotype and high expression of the immunosuppressive factors. A subclonal CTC population exhibited stem cell properties as high aldehyde dehydrogenase 1 activity, melanosphere-forming ability, and expression of major stemness transcription factors. Xenograft experiments confirmed the CTC ability to generate melanoma in-vivo and revealed enhanced metastatic propensity.ConclusionsCTCs play a relevant role in melanoma and may actively contribute to drive the disease progression and metastasis. Thus, they are a unique potential tool for pharmacogenomic studies to guide treatment strategies in advanced disease.

Single-Cell RNA Sequencing of Cerebrospinal Fluid as an Advanced Form of Liquid Biopsy for Neurological Disorders.

Diagnosis and longitudinal monitoring of neurological diseases are limited by the poor specificity and limited resolution of currently available techniques. Analysis of circulating cells in cerebrospinal fluid (CSF) has emerged as a promising strategy for the diagnosis, molecular characterization, and monitoring of neurological disease. In comparison to bulk sequencing analysis, single-cell sequencing studies can provide novel insights into rare cell populations and uncover heterogeneity in gene expression at a single-cell resolution, which has several implications for understanding disease pathology and treatment. Parallel development of standardized biofluid collection protocols, pre-processing strategies, reliable single-cell isolation strategies, downstream genomic analysis, and robust computational analysis is paramount for comprehensive single-cell sequencing analysis. Here we perform a comprehensive review of studies focusing on single-cell sequencing of cells in the CSF of patients with oncological or non-oncological diseases of the central nervous system.