Specific Cell Populations Research Articles

Abstract 3533: Spatially Resolved Laser-Activated Cell Sorting (SLACS) and AI integration for enhanced pathological analysis and biomarker discovery

Abstract This study focuses on the integration of Artificial Intelligence (AI) with Spatially Resolved Laser-Activated Cell Sorting (SLACS) for enhanced pathological analysis and biomarker discovery. The primary approach involves using AI to automatically analyze slide images, identifying critical areas associated with diseases such as cancer or cells emitting specific signals. AI algorithms efficiently segment these significant regions or cellular groups, facilitating targeted analysis. Following the AI-driven segmentation, SLACS comes into play, isolating the identified cells from the slide for further examination. This precise sorting allows for the focused study of cells relevant to disease processes, enhancing the efficiency and accuracy of pathological analysis. The separated samples obtained through SLACS are then subjected to detailed analysis. This step is crucial for understanding the cellular mechanisms at play in disease states and for the identification of potential biomarkers. These biomarkers are vital for developing targeted therapeutic strategies and advancing personalized medicine. By combining AI's advanced image processing and pattern recognition capabilities with the precision of SLACS, this integrated approach significantly improves the identification and analysis of disease-related cellular characteristics. It streamlines the process of isolating and studying specific cell populations, contributing to a deeper understanding of disease mechanisms and progression. In conclusion, the synergistic application of AI and SLACS represents a significant advancement in pathological research and biomarker discovery. This methodology not only enhances the accuracy of disease marker identification but also opens new avenues for research and clinical application. Citation Format: Haewook Jang, Amos Chungwon Lee, Sumin Lee, Sunghoon Kwon. Spatially Resolved Laser-Activated Cell Sorting (SLACS) and AI integration for enhanced pathological analysis and biomarker discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3533.

Data-driven classification of individual cells by their non-Markovian motion

We present a method to differentiate organisms solely by their motion based on the generalized Langevin equation (GLE) and use it to distinguish two different swimming modes of strongly confined unicellular microalgae Chlamydomonas reinhardtii. The GLE is a general model for active or passive motion of organisms and particles that can be derived from a time-dependent general many-body Hamiltonian and in particular includes non-Markovian effects (i.e., the trajectory memory of its past). We extract all GLE parameters from individual cell trajectories and perform an unbiased cluster analysis to group them into different classes. For the specific cell population employed in the experiments, the GLE-based assignment into the two different swimming modes works perfectly, as checked by control experiments. The classification and sorting of single cells and organisms is important in different areas; our method, which is based on motion trajectories, offers wide-ranging applications in biology and medicine.

Cell type-specific transforming growth factor-β (TGF-β) signaling in the regulation of salivary gland fibrosis and regeneration

Salivary gland damage and hypofunction result from various disorders, including autoimmune Sjögren's disease (SjD) and IgG4-related disease (IgG4-RD), as well as a side effect of radiotherapy for treating head and neck cancers. There are no therapeutic strategies to prevent the loss of salivary gland function in these disorders nor facilitate functional salivary gland regeneration. However, ongoing aquaporin-1 gene therapy trials to restore saliva flow show promise. To identify and develop novel therapeutic targets, we must better understand the cell-specific signaling processes involved in salivary gland regeneration. Transforming growth factor-β (TGF-β) signaling is essential to tissue fibrosis, a major endpoint in salivary gland degeneration, which develops in the salivary glands of patients with SjD, IgG4-RD, and radiation-induced damage. Though the deposition and remodeling of extracellular matrix proteins are essential to repair salivary gland damage, pathological fibrosis results in tissue hardening and chronic salivary gland dysfunction orchestrated by multiple cell types, including fibroblasts, myofibroblasts, endothelial cells, stromal cells, and lymphocytes, macrophages, and other immune cell populations. This review is focused on the role of TGF-β signaling in the development of salivary gland fibrosis and the potential for targeting TGF-β as a novel therapeutic approach to regenerate functional salivary glands. The studies presented highlight the divergent roles of TGF-β signaling in salivary gland development and dysfunction and illuminate specific cell populations in damaged or diseased salivary glands that mediate the effects of TGF-β. Overall, these studies strongly support the premise that blocking TGF-β signaling holds promise for the regeneration of functional salivary glands.

STING agonist inflames the cervical cancer immune microenvironment and overcomes anti-PD-1 therapy resistance.

Cervical cancer poses a significant global threat to women's health. However, current therapeutic interventions, such as radiotherapy, chemotherapy, surgical resection, and immune checkpoint inhibitors, face limitations in the advanced stages of the disease. Given the immunosuppressive microenvironment in cervical cancer, it is imperative to explore novel perspectives. In this regard, STING agonists have emerged as promising candidates. The expression profiles and clinicopathological data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Prognostic analysis of STING downstream genes (CCL5, CXCL9, CXCL10) and immune infiltration analysis were conducted using Kaplan-Meier Plotter, ESTIMATE, and deconvo_CIBERSOR. Single-cell RNA-seq (scRNA-seq) analysis was conducted to evaluate the potential of MSA-2 in cervical cancer treatment employing SingleR, chi-squared test, and Gene Set Enrichment Analysis (GSEA). Cellular interaction analysis utilized the CellChat package to assess the potentiation of cellular interaction following MSA-2 administration. Murine tumor models involving U14 and TC-1, were conducted, and the IF of tissue was subsequently conducted to assess the tumor microenvironment status after treatment. Prognosis in cervical cancer correlated with elevated expression of STING downstream genes, indicating prolonged survival and reduced recurrence. These genes positively correlated with immune infiltration, influencing stromal scores, immune scores, and estimate scores. Specific immune cell populations, including CD8+ T cells, M1-type macrophages, NK cells, and T follicular helper cells, were associated with STING downstream genes. scRNA-seq in a classic immune-excluded model revealed that MSA-2 exerts priming and activating functions on vital components within TME, and intensifies their intercellular communications. The in vivo assay ultimately demonstrated that MSA-2, either as a standalone treatment or in combination with anti-PD-1, effectively suppressed the growth of subcutaneous cervical tumors. Moreover, the combination strategy significantly augmented efficacy compared to anti-PD-1 monotherapy by eliciting a robust antitumor immune response. This study highlights the pivotal role of the STING pathway and the potential of MSA-2 in reshaping the immune microenvironment in cervical cancer. Combining MSA-2 with immune checkpoint inhibitors presents a transformative approach, holding promise for improved prognosis. Further investigations are warranted to explore the broader immune landscape and potential long-term effects of MSA-2 in cervical cancer treatment.

Machine learning aided single cell image analysis improves understanding of morphometric heterogeneity of human mesenchymal stem cells

The multipotent stem cells of our body have been largely harnessed in biotherapeutics. However, as they are derived from multiple anatomical sources, from different tissues, human mesenchymal stem cells (hMSCs) are a heterogeneous population showing ambiguity in their in vitro behavior. Intra-clonal population heterogeneity has also been identified and pre-clinical mechanistic studies suggest that these cumulatively depreciate the therapeutic effects of hMSC transplantation. Although various biomarkers identify these specific stem cell populations, recent artificial intelligence-based methods have capitalized on the cellular morphologies of hMSCs, opening a new approach to understand their attributes. A robust and rapid platform is required to accommodate and eliminate the heterogeneity observed in the cell population, to standardize the quality of hMSC therapeutics globally.Here, we report our primary findings of morphological heterogeneity observed within and across two sources of hMSCs namely, stem cells from human exfoliated deciduous teeth (SHEDs) and human Wharton jelly mesenchymal stem cells (hWJ MSCs), using real-time single-cell images generated on immunophenotyping by imaging flow cytometry (IFC). We used the ImageJ software for identification and comparison between the two types of hMSCs using statistically significant morphometric descriptors that are biologically relevant. To expand on these insights, we have further applied deep learning methods and successfully report the development of a Convolutional Neural Network-based image classifier. In our research, we introduced a machine learning methodology to streamline the entire procedure, utilizing convolutional neural networks and transfer learning for binary classification, achieving an accuracy rate of 97.54%. We have also critically discussed the challenges, comparisons between solutions and future directions of machine learning in hMSC classification in biotherapeutics.

Immune cell expression patterns of CD39/CD73 ectonucleotidases in rodent models of cardiac arrest and resuscitation.

Cardiac arrest (CA) is a significant public health concern. There is the high imminent mortality and survival in those who are resuscitated is substantively compromised by the post-CA syndrome (PCAS), characterized by multiorgan ischemia-reperfusion injury (IRI). The inflammatory response in PCAS is complex and involves various immune cell types, including lymphocytes and myeloid cells that have been shown to exacerbate organ IRI, such as myocardial infarction. Purinergic signaling, as regulated by CD39 and CD73, has emerged as centrally important in the context of organ-specific IRI. Hence, comprehensive understanding of such purinergic responses may be likewise imperative for improving outcomes in PCAS. We have investigated alterations of immune cell populations after CA by utilizing rodent models of PCAS. Blood and spleen were collected after CA and resuscitation and underwent flow cytometry analysis to evaluate shifts in CD3+CD4+ helper T cells, CD3+CD8a+ cytotoxic T cells, and CD4/CD8a ratios. We then examined the expression of CD39 and CD73 across diverse cell types, including myeloid cells, T lymphocytes, and B lymphocytes. In both rat and mouse models, there were significant increases in the frequency of CD3+CD4+ T lymphocytes in PCAS (rat, P < 0.01; mouse, P < 0.001), with consequently elevated CD4/CD8a ratios in whole blood (both, P < 0.001). Moreover, CD39 and CD73 expression on blood leukocytes were markedly increased (rat, P < 0.05; mouse, P < 0.01 at 24h). Further analysis in the experimental mouse model revealed that CD11b+ myeloid cells, with significant increase in their population (P < 0.01), had high level of CD39 (88.80 ± 2.05 %) and increased expression of CD73 (P < 0.05). CD19+ B lymphocytes showed slight increases of CD39 (P < 0.05 at 2h) and CD73 (P < 0.05 at 2h), while, CD3+ T lymphocytes had decreased levels of them. These findings suggested a distinct patterns of expression of CD39 and CD73 in these specific immune cell populations after CA. These data have provided comprehensive insights into the immune response after CA, highlighting high-level expressions of CD39 and CD73 in myeloid cells.

Enhancing precision medicine: Bispecific antibody-mediated targeted delivery of lipid nanoparticles for potential cancer therapy

The precise delivery of therapeutic agents to specific cell populations, including cancer cells, remains a target in modern medicine, to enhance treatment efficacy, while minimizing unintended side effects. This study presents a strategy utilizing bispecific antibodies for the targeted delivery of nucleic acid drugs to the surface of glucose-regulated protein 78 (GRP78)-overexpressing cancer cells. Strong binding affinity of the bispecific antibodies to GRP78-overexpressing cancer cells, including HEPG2 cells, confirmed the tumor-targeting potential of this platform. Functional analyses demonstrated the role of the bispecific antibodies in enhancing lipid nanoparticle (LNP) uptake, causing increased gene expression levels of nucleic acid drugs loaded within LNPs. In vivo imaging confirmed the potency of the bispecific-antibody-modified LNPs in delivering nucleic acid drugs to tumors and sustaining therapeutic expression levels. In vivo therapy results indicated that the bispecific antibodies improved the antitumor activity of PE38-loaded LNPs in tumors overexpressing surface GRP78. This study pioneered a bispecific-antibody-centered platform for the targeted delivery of nucleic acid drugs. The robust antigen–antibody binding affinity, tumor-selective interactions, enhanced cellular uptake, and proficient gene expression promise to advance precision therapeutics in oncology. Continued refinement and translation of this drug delivery strategy are important to unlock its full clinical potential.

A Novel Polymer Nanoparticle Polydimethyl Diallyl Ammonium Chloride as An Adjuvant Enhances the Immune Response of SARS-CoV-2 Subunit Vaccine.

The Coronavirus Disease 2019 (COVID-19) pandemic caused by SARS-CoV-2 has a significant impact on global health and the economy. It has underscored the urgent need for a stable, easily produced and effective vaccine. This study presents a novel approach using SARS-CoV-2 spike (S) protein-conjugated nanoparticles (NPs) in combination with cyclic GMP-AMP (cGAMP) (S-NPs-cGAMP) as a subunit vaccine. When mice are immunized, the antiserum of S-NPs-cGAMP group exhibits a 16-fold increase in neutralizing activity against a pseudovirus, compared to S protein group. Additionally, S-NPs-cGAMP induces even higher levels of neutralizing antibodies. Remarkably, the vaccine also triggers a robust humoral immune response, as evidenced by a notable elevation in virus-specific IgG and IgM antibodies. Furthermore, after 42 days of immunization, there is an observed increase in specific immune cell populations in the spleen. CD3+CD4+ and CD3+CD8+T lymphocytes, as well as B220+CD19+ and CD3-CD49b+ NK lymphocytes, show an upward trend, indicating a positive cellular immune response. Moreover, the S-NPs-cGAMP demonstrates promising results against the Delta strain and exhibits good cross-neutralization potential against other variants. These findings suggest that pDMDAAC NPs is potential adjuvant and could serve as a versatile platform for future vaccine development.

Analysis of the differences in the characteristics of mesenchymal stem cells derived from jaw and long bones based on single-cell RNA-sequencing

Objective: To study the whole bone marrow cellular composition of jaw and long bones, and further analyze the heterogeneity of mesenchymal stem cells (MSCs) derived from these two tissue, aiming at exploring the differences in functional characteristics of bone MSCs from different lineage sources. Methods: The Seurat package of R language was used to analyze the mandibular and femur whole bone marrow single-cell RNA-sequencing (scRNA-seq) datasets in the literature, and the subpopulations were annotated by reference to the marker genes reported by previous studies. The differentially expressed genes between mandible-derived MSCs (M-MSCs) and femur-derived MSCs (F-MSCs) were calculated, and cell-cell communication analysis between M-MSCs or F-MSCs with other cell populations was performed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on up-regulated and down-regulated differentially expressed genes of M-MSCs, and Gene Set Enrichment Analysis (GSEA) was performed on M-MSCs or F-MSCs. Results: cRNA-seq analysis showed that the mandible and femur had the same bone marrow cell composition, but there were differences in the proportion of specific cell populations. Also, there were significantly differentially expressed genes between M-MSCs and F-MSCs. In addition, cell-cell communication analysis revealed differences in numbers of ligand-receptor pairs between M-MSCs or F-MSCs with other cell populations. Furthermore, GO, KEGG and GSEA analysis showed that M-MSCs had higher extracellular matrix production potential than F-MSCs, but had lower ability to regulate other cells in the bone marrow, especially immune cells. Conclusions: M-MSCs and F-MSCs showed distinct differences in the gene expression pattern and up-regulated signaling pathways, which may be closely related to the developmental sources and functional characteristics of jaw and long bones.

Immune landscape and response to oncolytic virus-based immunotherapy.

Oncolytic virus (OV)-based immunotherapy has emerged as a promising strategy for cancer treatment, offering a unique potential to selectively target malignant cells while sparing normal tissues. However, the immunosuppressive nature of tumor microenvironment (TME) poses a substantial hurdle to the development of OVs as effective immunotherapeutic agents, as it restricts the activation and recruitment of immune cells. This review elucidates the potential of OV-based immunotherapy in modulating the immune landscape within the TME to overcome immune resistance and enhance antitumor immune responses. We examine the role of OVs in targeting specific immune cell populations, including dendritic cells, T cells, natural killer cells, and macrophages, and their ability to alter the TME by inhibiting angiogenesis and reducing tumor fibrosis. Additionally, we explore strategies to optimize OV-based drug delivery and improve the efficiency of OV-mediated immunotherapy. In conclusion, this review offers a concise and comprehensive synopsis of the current status and future prospects of OV-based immunotherapy, underscoring its remarkable potential as an effective immunotherapeutic agent for cancer treatment.

Bronchioalveolar organoids: A preclinical tool to screen toxicity associated with antibody-drug conjugates

Despite extensive preclinical testing, cancer therapeutics can result in unanticipated toxicity to non-tumor tissue in patients. These toxicities may pass undetected in preclinical experiments due to modeling limitations involving poor biomimicry of 2-dimensional in vitro cell cultures and due to lack of interspecies translatability in in vivo studies. Instead, primary cells can be grown into miniature 3-dimensional structures that recapitulate morphological and functional aspects of native tissue, termed “organoids.” Here, human bronchioalveolar organoids grown from primary alveolar epithelial cells were employed to model lung epithelium and investigate off-target toxicities associated with antibody-drug conjugates (ADCs). ADCs with three different linker-payload combinations (mafodotin, vedotin, and deruxtecan) were tested in bronchioalveolar organoids generated from human, rat, and nonhuman primate lung cells. Organoids demonstrated antibody uptake and changes in viability in response to ADC exposure that model in vivo drug sensitivity. RNA sequencing identified inflammatory activation in bronchioalveolar cells in response to deruxtecan. Future studies will explore specific cell populations involved in interstitial lung disease and incorporate immune cells to the culture.

Emerging Role of Autophagy in Governing Cellular Dormancy, Metabolic Functions, and Therapeutic Responses of Cancer Stem Cells.

Tumors are composed of heterogeneous populations of dysregulated cells that grow in specialized niches that support their growth and maintain their properties. Tumor heterogeneity and metastasis are among the major hindrances that exist while treating cancer patients, leading to poor clinical outcomes. Although the factors that determine tumor complexity remain largely unknown, several genotypic and phenotypic changes, including DNA mutations and metabolic reprograming provide cancer cells with a survival advantage over host cells and resistance to therapeutics. Furthermore, the presence of a specific population of cells within the tumor mass, commonly known as cancer stem cells (CSCs), is thought to initiate tumor formation, maintenance, resistance, and recurrence. Therefore, these CSCs have been investigated in detail recently as potential targets to treat cancer and prevent recurrence. Understanding the molecular mechanisms involved in CSC proliferation, self-renewal, and dormancy may provide important clues for developing effective therapeutic strategies. Autophagy, a catabolic process, has long been recognized to regulate various physiological and pathological processes. In addition to regulating cancer cells, recent studies have identified a critical role for autophagy in regulating CSC functions. Autophagy is activated under various adverse conditions and promotes cellular maintenance, survival, and even cell death. Thus, it is intriguing to address whether autophagy promotes or inhibits CSC functions and whether autophagy modulation can be used to regulate CSC functions, either alone or in combination. This review describes the roles of autophagy in the regulation of metabolic functions, proliferation and quiescence of CSCs, and its role during therapeutic stress. The review further highlights the autophagy-associated pathways that could be used to regulate CSCs. Overall, the present review will help to rationalize various translational approaches that involve autophagy-mediated modulation of CSCs in controlling cancer progression, metastasis, and recurrence.

Chemogenetic Tools in Focus: Proximity, Conformation, and Sterics

AbstractChemogenetic tools are genetically encoded systems regulated by user‐defined chemicals. Their ability to temporally modulate protein functions in specific cell populations has facilitated in‐depth understanding of dynamic biological systems. Many chemogenetic domains have been developed for regulating a wide range of biological processes, ranging from cellular events to animal behaviors. These tools share some common mechanisms, including proximity regulation, conformational change and allosteric control, as well as steric hinderance control. Here in this review, we aim to provide an overview of different chemogenetic tool designs that utilize the above three common mechanisms to control cellular events.

C9orf72 gene networks in the human brain correlate with cortical thickness in C9-FTD and implicate vulnerable cell types.

A hexanucleotide repeat expansion (HRE) intronic to chromosome 9 open reading frame 72 (C9orf72) is recognized as the most common genetic cause of amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and ALS-FTD. Identifying genes that show similar regional co-expression patterns to C9orf72 may help identify novel gene targets and biological mechanisms that mediate selective vulnerability to ALS and FTD pathogenesis. We leveraged mRNA expression data in healthy brain from the Allen Human Brain Atlas to evaluate C9orf72 co-expression patterns. To do this, we correlated average C9orf72 expression values in 51 regions across different anatomical divisions (cortex, subcortex, and cerebellum) with average gene expression values for 15,633 protein-coding genes, including 54 genes known to be associated with ALS, FTD, or ALS-FTD. We then performed imaging transcriptomic analyses to evaluate whether the identified C9orf72 co-expressed genes correlated with patterns of cortical thickness in symptomatic C9orf72 pathogenic HRE carriers (n = 19) compared to controls (n = 23). Lastly, we explored whether genes with significant C9orf72 imaging transcriptomic correlations (i.e., "C9orf72 imaging transcriptomic network") were enriched in specific cell populations in the brain and enriched for specific biological and molecular pathways. A total of 2,120 genes showed an anatomical distribution of gene expression in the brain similar to C9orf72 and significantly correlated with patterns of cortical thickness in C9orf72 HRE carriers. This C9orf72 imaging transcriptomic network was differentially expressed in cell populations previously implicated in ALS and FTD, including layer 5b cells, cholinergic neurons in the spinal cord and brainstem and medium spiny neurons of the striatum, and was enriched for biological and molecular pathways associated with protein ubiquitination, autophagy, cellular response to DNA damage, endoplasmic reticulum to Golgi vesicle-mediated transport, among others. Considered together, we identified a network of C9orf72 associated genes that may influence selective regional and cell-type-specific vulnerabilities in ALS/FTD.

Shared and Compartment-Specific Processes in Nucleus Pulposus and Annulus Fibrosus During Intervertebral Disc Degeneration.

Elucidating how cell populations promote onset and progression of intervertebral disc degeneration (IDD) has the potential to enable more precise therapeutic targeting of cells and mechanisms. Single-cell RNA-sequencing (scRNA-seq) is performed on surgically separated annulus fibrosus (AF) (19,978; 26,983 cells) and nucleus pulposus (NP) (20,884; 24,489 cells) from healthy and diseased human intervertebral discs (IVD). In both tissue types, depletion of cell subsets involved in maintenance of healthy IVD is observed, specifically the immature cell subsets - fibroblast progenitors and stem cells - indicative of an impairment of normal tissue self-renewal. Tissue-specific changes are also identified. In NP, several fibrotic populations are increased in degenerated IVD, indicating tissue-remodeling. In degenerated AF, a novel disease-associated subset is identified, which expresses disease-promoting genes. It is associated with pathogenic biological processes and the main gene regulatory networks include thrombospondin signaling and FOXO1 transcription factor. In NP and AF cells thrombospondin protein promoted expression of genes associated with TGFβ/fibrosis signaling, angiogenesis, and nervous system development. The data reveal new insights of both shared and tissue-specific changes in specific cell populations in AF and NP during IVD degeneration. These identified mechanisms and molecules are novel and more precise targets for IDD prevention and treatment.

Spatially Resolved Microglia/Macrophages in Recurrent Glioblastomas Overexpress Fatty Acid Metabolism and Phagocytic Genes.

Glioblastoma (GBM) tumors are rich in tumor-associated microglia/macrophages. Changes associated with treatment in this specific cell population are poorly understood. Therefore, we studied changes in gene expression of tumor-associated microglia/macrophages (Iba1+) cells in de novo versus recurrent GBMs. NanoString GeoMx® Digital Spatial Transcriptomic Profiling of microglia/macrophages (Iba1+) and glial cells (Gfap+) cells identified on tumor sections was performed on paired de novo and recurrent samples obtained from three IDH-wildtype GBM patients. The impact of differentially expressed genes on patient survival was evaluated using publicly available data. Unsupervised analyses of the NanoString GeoMx® Digital Spatial Profiling data revealed clustering based on the transcriptomic data from Iba1+ and Gfap+ cells. As expected, conventional differential gene expression and enrichment analyses revealed upregulation of immune-function-related genes in Iba1+ cells compared to Gfap+ cells. A focused differential gene expression analysis revealed upregulation of phagocytosis and fatty acid/lipid metabolism genes in Iba1+ cells in recurrent GBM samples compared to de novo GBM samples. Importantly, of these genes, the lipid metabolism gene PLD3 consistently correlated with survival in multiple different publicly available datasets. Tumor-associated microglia/macrophages in recurrent GBM overexpress genes involved in fatty acid/lipid metabolism. Further investigation is needed to fully delineate the role of PLD phospholipases in GBM progression.

Immune checkpoint inhibitor-related colitis in patients on immunotherapy for cancer.

Immune checkpoint inhibitors, a revolutionary class of cancer immunotherapy drugs, have transformed cancer treatment by bolstering antitumor immunity for various advanced-stage solid cancers. The US Food and Drug Administration has approved 7 immune checkpoint inhibitors that target 3 major immune checkpoint proteins: cytotoxic T-lymphocyte-associated protein 4, programmed cell death 1 protein, and programmed cell death 1 ligand 1. In addition to their remarkable efficacy, however, these inhibitors have been observed causing immune-related adverse events, particularly immune checkpoint inhibitor-related colitis, which often results in severe or life-threatening clinical issues. The diagnosis of immune checkpoint inhibitor-related colitis relies on incorporation of clinical evaluation as well as endoscopic and histopathologic examination, with exclusion of other potential etiologies. The common histopathologic manifestations of immune checkpoint inhibitor-related colitis are acute active colitis, chronic active colitis, microscopic colitis (collagenous or lymphocytic), and ischemic colitis, with patterns overlapping. Notably, enterocyte apoptosis is a unique feature of immune checkpoint inhibitor toxicity. The proposed mechanisms for the pathogenesis of immune checkpoint inhibitor-related colitis are primarily associated with autoimmune-type dysregulation and gut microbiome alteration. This review summarizes the clinical and pathologic characteristics of immune checkpoint inhibitor-related colitis and elucidates its underlying pathogenic mechanisms. Future successful management of this form of colitis relies on our comprehension of the intricate interplay between tumoral and systemic immune responses to immune checkpoint inhibitors and innovative approaches to modify these responses, along with specific immune cell populations, to preclude immune-related adverse events while achieving antitumor therapeutic outcomes.

Unraveling dystonia circuitry in rodent models using novel neuromodulation techniques

Dystonia is a network disorder presumed to result from abnormalities in multiple brain regions and in multiple cell populations. The specific pathomechanisms affecting the motor circuits in dystonia are, however, still largely unclear. Animal models for dystonia have long been used to advance our understanding on how specific brain regions and cell populations are involved in dystonia symptomatogenesis. Lesioning, pharmacological modulation and electrical stimulation paradigms were able to highlight that both the basal ganglia and the cerebellum are pathologically altered in these animal models for dystonia. Techniques such as optogenetics and chemogenetics now offer the opportunity for targeted modulation of brain regions and most importantly cell populations and circuits. This could not only allow for a better understanding of the dystonic brain, but potentially improve and expand treatment options. In hopes that the insights from these neuromodulation techniques will eventually translate into therapies, we aim to summarize and critically discuss the findings from different in vivo approaches used to dissect the network dysfunctions underlying dystonia.

Investigating the causal relationship and potential shared diagnostic genes between primary biliary cholangitis and systemic lupus erythematosus using bidirectional Mendelian randomization and transcriptomic analyses.

The co-occurrence of primary biliary cholangitis (PBC) and systemic lupus erythematosus (SLE) has been consistently reported in observational studies. Nevertheless, the underlying causal correlation between these two conditions still needs to be established. We performed a bidirectional two-sample Mendelian randomization (MR) study to assess their causal association. Five MR analysis methods were utilized for causal inference, with inverse-variance weighted (IVW) selected as the primary method. The Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) and the IVW Radial method were applied to exclude outlying SNPs. To assess the robustness of the MR results, five sensitivity analyses were carried out. Multivariable MR (MVMR) analysis was also employed to evaluate the effect of possible confounders. In addition, we integrated transcriptomic data from PBC and SLE, employing Weighted Gene Co-expression Network Analysis (WGCNA) to explore shared genes between the two diseases. Then, we used Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment methods to perform on the shared genes. The Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm was utilized to identify potential shared diagnostic genes. Finally, we verified the potential shared diagnostic genes in peripheral blood mononuclear cells (PBMCs)-specific cell populations of SLE patients by single-cell analysis. Our MR study provided evidence that PBC had a causal relationship with SLE (IVW, OR: 1.347, 95% CI: 1.276 - 1.422, P < 0.001) after removing outliers (MR-PRESSO, rs35464393, rs3771317; IVW Radial, rs11065987, rs12924729, rs3745516). Conversely, SLE also had a causal association with PBC (IVW, OR: 1.225, 95% CI: 1.141 - 1.315, P < 0.001) after outlier correction (MR-PRESSO, rs11065987, rs3763295, rs7774434; IVW Radial, rs2297067). Sensitivity analyses confirmed the robustness of the MR findings. MVMR analysis indicated that body mass index (BMI), smoking and drinking were not confounding factors. Moreover, bioinformatic analysis identified PARP9, ABCA1, CEACAM1, and DDX60L as promising diagnostic biomarkers for PBC and SLE. These four genes are highly expressed in CD14+ monocytes in PBMCs of SLE patients and potentially associated with innate immune responses and immune activation. Our study confirmed the bidirectional causal relationship between PBC and SLE and identified PARP9, ABCA1, CEACAM1, and DDX60L genes as the most potentially shared diagnostic genes between the two diseases, providing insights for the exploration of the underlying mechanisms of these disorders.

Analysis of secreted small extracellular vesicles from activated human microglial cell lines reveals distinct pro- and anti-inflammatory proteomic profiles.

Microglia are a specialized population of innate immune cells located in the central nervous system. In response to physiological and pathological changes in their microenvironment, microglia can polarize into pro-inflammatory or anti-inflammatory phenotypes. A dysregulation in the pro-/anti-inflammatory balance is associated with many pathophysiological changes in the brain and nervous system. Therefore, the balance between microglia pro-/anti-inflammatory polarization can be a potential biomarker for the various brain pathologies. A non-invasive method of detecting microglia polarization in patients would have promising clinical applications. Here, we perform proteomic analysis of small extracellular vesicles (sEVs) derived from microglia cells to identify sEVs biomarkers indicative of pro-inflammatory and anti-inflammatory phenotypic changes. sEVs were isolated from microglia cell lines under different inflammatory conditions and analyzed by proteomics by liquid chromatography with mass spectrometry. Our findings provide the potential roles of sEVs that could be related to the pathogenesis of various brain diseases.