Distribution Of Immune Cells Research Articles

Flow Cytometric Analysis of Leukocyte Populations in the Lung Tissue of Dromedary Camels.

Respiratory tract infections are among the most common infections in dromedary camels, with a high impact on animal health, production, and welfare. Tissue-specific distribution of immune cells is one of the important factors that influence the nature and outcome of the immune response to pathogens. Several protocols have recently been described for the flow cytometric analysis of immune cells in the lung tissue of several species. However, no such protocol currently exists for dromedary camels. The aim of the present study was, therefore, to establish a flow cytometric protocol for the identification of immune cell populations in the camel lung tissue and the evaluation of some of their phenotypic and functional properties. Combined staining of camel lung leukocytes with monoclonal antibodies to the pan-leukocyte marker CD45 and the myeloid cell marker CD172a allowed the identification of myeloid cells (CD45+CD172a+) and lymphoid cells (CD45+CD172a−) in the lung of healthy camels. The cell adhesion molecules CD11a and CD18 were found in a higher abundance on myeloid cells compared to lymphoid cells. Based on their differential expression of the LPS receptor CD14, macrophages (CD172a+CD14high cells) were identified as the most abundant immune cell population in the camel lung tissue. In contrast to their dominance in camel peripheral blood, granulocytes (CD172a+CD14low) presented only a minor population in the lung tissue. The higher frequency of γδ T cells in the lung tissue than in peripheral blood suggests a role for these cells in the pulmonary immune system. Flow cytometric analysis of bacterial phagocytosis and ROS production upon bacterial stimulation revealed high antimicrobial activity of camel lung phagocytes, which was comparable with the antimicrobial activity of blood granulocytes. Comparative analysis of immune cell distribution between the cranial and caudal lobes of the camel lung revealed a higher frequency of granulocytes and a lower frequency of macrophages in the cranial compared to the caudal lung lobe. In addition, the higher frequency of cells expressing the M2 macrophage marker CD163 in the caudal lung tissue, with a slightly higher fraction of MHCII-positive cells (M1 phenotype) in the cranial lung tissue, may suggest the distribution of different macrophage subtypes in the different lobes of the camel lung. Such differences between lung lobes could influence the effectiveness of the immune response to infection or vaccination with respiratory pathogens. Collectively, the present study identified some similarities and differences between camels and other farm animals regarding the distribution of the main immune cell populations in their lungs. Further studies are required for comprehensive immunophenotyping of the cellular pulmonary immune system in camels.

Machine learning analyses of highly-multiplexed immunofluorescence identifies distinct tumor and stromal cell populations in primary pancreatic tumors.

Pancreatic ductal adenocarcinoma (PDAC) is a formidable challenge for patients and clinicians. To analyze the distribution of 31 different markers in tumor and stromal portions of the tumor microenvironment (TME) and identify immune cell populations to better understand how neoplastic, non-malignant structural, and immune cells, diversify the TME and influence PDAC progression. Whole slide imaging (WSI) and cyclic multiplexed-immunofluorescence (MxIF) was used to collect 31 different markers over the course of nine distinctive imaging series of human PDAC samples. Image registration and machine learning algorithms were developed to largely automate an imaging analysis pipeline identifying distinct cell types in the TME. A random forest algorithm accurately predicted tumor and stromal-rich areas with 87% accuracy using 31 markers and 77% accuracy using only five markers. Top tumor-predictive markers guided downstream analyses to identify immune populations effectively invading into the tumor, including dendritic cells, CD4+ T cells, and multiple immunoregulatory subtypes. Immunoprofiling of PDAC to identify differential distribution of immune cells in the TME is critical for understanding disease progression, response and/or resistance to treatment, and the development of new treatment strategies.

27MO Integrated digital pathology and single-cell analysis identify the spatial and temporal evolution of immune cells networks in epithelial ovarian cancer

Immune checkpoint blockade (ICB) failed to demonstrate activity in epithelial ovarian cancer (EOC) so far. What controls the complex spatial distribution of tumor-infiltrating lymphocytes (TILs) and immune cells in EOC is poorly understood and it remains challenging to systematically define tumor-immune phenotype due to its highly heterogeneous nature.

A Limited Role for AMD3100 Induced Stem Cell Mobilization for Modulation of Thoracic Trauma Outcome.

Thoracic trauma is a major cause of mortality due to the associated inflammatory acute respiratory distress syndrome and morbidity due to impaired tissue regeneration. Trauma-induced lung inflammation is characterized by the early recruitment of cells with pro- or anti-inflammatory activity to the lung. Therapeutic interventions reducing the level of tissue inflammation may result in decreased tissue damage and improved healing and recovery. Stem cells might be able to improve trauma outcome via immunomodulation or by enhancing tissue regeneration.Here, we describe the migratory dynamics of murine mesenchymal, hematopoietic and endothelial stem and progenitor cells (SPCs) as well as mature inflammatory cells (monocytes, neutrophils, lymphocytes) to peripheral blood (PB) and lung tissue between 0.2 and 48 h post-blunt chest trauma (TXT). We demonstrate that the kinetics of immune cell and SPC distribution upon trauma are both cell-type and tissue-dependent. We identified a transient, early increase in the number of inflammatory cells in PB and lung at 2 h post-TXT and a second wave of infiltrating SPCs in lungs by 48 h after TXT induction, suggesting a role for SPCs in tissue remodeling after the initial inflammatory phase. Cxcl12/Cxcr4 blockade by AMD3100 within the first 6 h after TXT, while inducing a strong and coordinated mobilization of SPCs and leukocytes to PB and lung tissue, did not significantly affect TXT associated inflammation or tissue damage as determined by inflammatory cytokine levels, plasma markers for organ function, lung cell proliferation and survival, and myofibroblast/fibroblast ratio in the lung. Further understanding the dynamics of the distribution of endogenous SPCs and inflammatory cells will therefore be indispensable for stem cell-based or immunomodulation therapies in trauma.

The RNA signature of immune-related genes and distinct spatial distribution of immune cells are closely associated with the treatment outcomes in the malignant melanoma patients receiving immune checkpoint inhibitors.

e21504 Background: The immune checkpoint inhibitors (ICIs), have improved survival with durable response for advanced malignant melanomas, but, only a minority of patients has achieved. To stay sway failure of triage patients, considerable side effects and costs of ICB therapies, the development of robust signatures predictive of response to ICB therapies is warranted. Methods: Clinical data were collected at Seoul St. Mary’s Hospitals. Among them, we examined RNA expression profile by QuantSeq 3’ mRNA-Sequencing and the composition, and spatial distance of immune cells by multiplex immunofluorescent staining. Results: The gene sets with relatively higher RNA expression in the good response group, were as follows; hematopoietic cell dedifferentiation gene, T-cell related adaptive immunity gene, IFN-related cytokine gene, and macrophage (TAM), NK cell, innate immunity gene set. Meanwhile, in the poor response group, inflammatory response, fibrosis response genes was increased.The cell densities of T cells, cytotoxic T cells, Treg cells, CD8+Treg cells, and exhausted T cells in the good response group tended to be higher, which was clearer in the peritumoral (PT) area than the intratumoral (IT) area. For the good response group, M1/M2 ratio in the IT area was significantly higher compared to that of poor response group (p = 0.045). According to the nearest neighbor analysis for % of melanoma cells within 15um distance present a close distance from M1, M2, and NK cells tended to be higher in the IT area than PT area. For the cases with higher spatial distribution from M1 in the IT area, PFS and OS was significantly extended (PFS, p = 0.0021; OS, p = 0.036). The gene sets with relatively higher mRNA expression in high neighborhood macrophage group, were cell death, apoptosis process gene set. In low neighboring M1 macrophage group, relatively higher mRNA expressions of extracellular component inflammation and fibrosis gene, cell migration, and cell de-differentiation gene set were observed. Conclusions: Taken together, our results suggest 4 key points. First, good and poor responder groups for ICB show marked differences from mRNA profiling to protein expression according to central dogma. Second, immune cells can be distributed sporadically in many places, but the actionable ground of the adaptive immune cells of the T cell family is the PT, and the playground of innate immune cells such as TAM and NK cells is the IT. In particular, the anti-tumor response of M1 macrophage and M2 macrophage was oppositely in IT. Third, high TAMs in IT are interpreted to have a tumoricidal effect because they show a stationery state while coding the killing effect gene set. In addition, topologically, spatial analysis as well as bulk genomics are important for predicting tumor response for ICIs.

Tumor immune microenvironment of primary prostate cancer with and without germline mutations in homologous recombination repair genes

BackgroundAberrations in homologous recombination repair (HRR) genes are emerging as important biomarkers for personalized treatment in prostate cancer (PCa). HRR deficiency (HRD) could affect the tumor immune microenvironment (TIME), potentially...

Profiling Immune Cells in the Kidney Using Tissue Cytometry and Machine Learning.

The immune system governs key functions that maintain renal homeostasis through various effector cells that reside in or infiltrate the kidney. These immune cells play an important role in shaping adaptive or maladaptive responses to local or systemic stress and injury. We increasingly recognize that microenvironments within the kidney are characterized by a unique distribution of immune cells, the function of which depends on this unique spatial localization. Therefore, quantitative profiling of immune cells in intact kidney tissue becomes essential, particularly at a scale and resolution that allow the detection of differences between the various "nephro-ecosystems" in health and disease. In this review, we discuss advancements in tissue cytometry of the kidney, performed through multiplexed confocal imaging and analysis using the Volumetric Tissue Exploration and Analysis (VTEA) software. We highlight how this tool has improved our understanding of the role of the immune system in the kidney and its relevance in the pathobiology of renal disease. We also discuss how the field is increasingly incorporating machine learning to enhance the analytic potential of imaging data and provide unbiased methods to explore and visualize multidimensional data. Such novel analytic methods could be particularly relevant when applied to profiling immune cells. Furthermore, machine-learning approaches applied to cytometry could present venues for nonexhaustive exploration and classification of cells from existing data and improving tissue economy. Therefore, tissue cytometry is transforming what used to be a qualitative assessment of the kidney into a highly quantitative, imaging-based "omics" assessment that complements other advanced molecular interrogation technologies.

Predicting Differences in Treatment Response and Survival Time of Lung Adenocarcinoma Patients Based on a Prognostic Risk Model of Glycolysis-Related Genes

Background: Multiple factors influence the survival of patients with lung adenocarcinoma (LUAD). Specifically, the therapeutic outcomes of treatments and the probability of recurrence of the disease differ among patients with the same stage of LUAD. Therefore, effective prognostic predictors need to be identified. Methods: Based on the tumor mutation burden (TMB) data obtained from The Cancer Genome Atlas (TCGA) database, LUAD patients were divided into high and low TMB groups, and differentially expressed glycolysis-related genes between the two groups were screened. The least absolute shrinkage and selection operator (LASSO) and Cox regression were used to obtain a prognostic model. A receiver operating characteristic (ROC) curve and a calibration curve were generated to evaluate the nomogram that was constructed based on clinicopathological characteristics and the risk score. Two data sets (GSE68465 and GSE11969) from the Gene Expression Omnibus (GEO) were used to verify the prognostic performance of the gene. Furthermore, differences in immune cell distribution, immune-related molecules, and drug susceptibility were assessed for their relationship with the risk score. Results: We constructed a 5-gene signature (FKBP4, HMMR, B4GALT1, SLC2A1, STC1) capable of dividing patients into two risk groups. There was a significant difference in overall survival (OS) times between the high-risk group and the low-risk group (p < 0.001), with the low-risk group having a better survival outcome. Through multivariate Cox analysis, the risk score was confirmed to be an independent prognostic factor (HR = 2.709, 95% CI = 1.981–3.705, p < 0.001), and the ROC curve and nomogram exhibited accurate prediction performance. Validation of the data obtained in the GEO database yielded similar results. Furthermore, there were significant differences in sensitivity to immunotherapy, cisplatin, paclitaxel, gemcitabine, docetaxel, gefitinib, and erlotinib between the low-risk and high-risk groups. Conclusion: Our results reveal that glycolysis-related genes are feasible predictors of survival and the treatment response of patients with LUAD.

Improvement of STING-mediated cancer immunotherapy using immune checkpoint inhibitors as a game-changer.

Various cancer therapies, such as surgery, radiotherapy, chemotherapy, and immunotherapy, have been used to treat cancer. Among cancer immunotherapies, stimulators of interferon genes (STING) activate various immune cells and induce them to attack cancer cells. However, the secretion of type I interferon (IFN α and β) increases after stimulation of the immune cell as a side effect of STING agonist, thereby increasing the expression of programmed death-ligand 1 (PD-L1) in the tumor microenvironment (TME). Therefore, it is necessary to reduce the side effects of STING agonists and maximize cancer treatment by administering combination therapy. Tumor-bearing mice were treated with cisplatin, tumor-specific peptide, neoantigen, DMXAA (STING agonist), and immune checkpoint inhibitor (ICI). The combination vaccine group showed a reduction in tumor mass, an increased survival rate, and IFN-γ+ (interferon gamma) CD8+ (cluster of differentiation 8) T cells in the spleen and TME. The distribution of immune cells in the spleen and TME was confirmed, and the number of active immune cells increased, whereas that of immunosuppressive cells decreased. When measuring cytokine levels in the tumor and serum, the levels of pro-inflammatory cytokines increased and anti-inflammatory cytokines decreased. This study demonstrated that when various cancer therapies are combined to treat cancer, it can lead to an anticancer immune synergistic effect by increasing the immune response and reducing side effects.

The Construction and Analysis of Immune Infiltration and Competing Endogenous RNA Network in Acute Ischemic Stroke.

Acute ischemic stroke (AIS) is a common neurological disease that seriously endangers both the physical and mental health of human. After AIS, activated immune cells are recruited to the stroke site, where inflammatory mediators are released locally, and severe immune inflammatory reactions occur within a short time, which affects the progress and prognosis of IS. Circular RNA (circRNA) is a type of non-coding RNA (ncRNA) with a closed-loop structure and high stability. Studies have found that circRNA can affect the course of IS. However, there is no report on ceRNA’s pathogenesis in AIS that is mediated by circRNA. In this study, the CIBERSORT algorithm was used to analyze the distribution of immune cells in patients with AIS. mRNA dataset was downloaded from the GEO database, and the weighted gene co-expression network analysis (WGCNA) method was used to construct weighted gene co-expression to determine 668 target genes, using GO, KEGG enrichment analysis, construction of protein-protein interaction (PPI) network analysis, and molecular complex detection (MCODE) plug-in analysis. The results showed that the biological function of the target gene was in line with the activation and immune regulation of neutrophils; signal pathways were mostly enriched in immune inflammation-related pathways. A Venn diagram was used to obtain 52 intersection genes between target genes and disease genes. By analyzing the correlation between the intersection genes and immune cells, we found that the top 5 hub genes were TOM1, STAT3, RAB3D, MDM2, and FOS, which were all significantly positively correlated with neutrophils and significantly negatively correlated with eosinophils. A total of 52 intersection genes and the related circRNA and miRNA were used as input for Cytoscape software to construct a circRNA-mediated ceRNA competition endogenous network, where a total of 18 circRNAs were found. Further analysis of the correlation between circRNA and immune cells found that 4 circRNAs are positively correlated with neutrophils. Therefore, we speculate that there may be a regulatory relationship between circRNA-mediated ceRNA and the immune mechanism in AIS. This study has important guiding significance for the progress, outcome of AIS, and the development of new medicine.

Characterization of cellular subpopulations and their gene expression by single-cell RNA sequencing in canine atopic dermatitis

Abstract Atopic Dermatitis (AD) is the most common, chronic, and inflammatory allergic skin disease worldwide, with a high prevalence both in children and adults, particularly in developed countries. There are limited effective treatments for severe allergic skin diseases available, thus, there is an unmet need of better understanding the molecular mechanisms and cellular populations involved in AD. Since AD in canines closely resembles the disease in humans, they are an attractive animal model for further studies. Leveraging single-cell RNA sequencing, we identified the cellular composition and shifts in cell populations in canine epidermis of atopic dogs compared to the epidermis from healthy controls. Fibroblasts and keratinocytes represented the largest cell populations, with fibroblasts decreasing in the atopic epidermis. Other populations such as endothelial vascular cells showed differences as well. Shifts in immune cell distribution included changes in subpopulations of dendritic cells and monocytes in the atopic skin. NK and T cells, particularly CD8 T cells were increased. Subclustering revealed specific cellular changes in AD dogs. We found signifiant changes in gene expression in most cell populations, with some genes differentially expressed across cells, while others were expressed in a cell specific manner. We also observed subtle differences between samples from animals with different disease progression, identifying gene expression markers changing with AD severity. Here we show that single-cell sequencing is a useful tool to define the cellular composition in canine atopic dermatitis, resolving changes in gene expression at the cellular level to advance our understanding of disease development and progression. Supported by intramural funds from Western University of Health Sciences

The Trinity: Interplay among Cancer Cells, Fibroblasts, and Immune Cells in Pancreatic Cancer and Implication of CD8+ T Cell-Orientated Therapy

The microenvironment in tumors is complicated and is constituted by different cell types and stromal proteins. Among the cell types, the abundance of cancer cells, fibroblasts, and immune cells is high and these cells work as the “Trinity” in promoting tumorigenesis. Although unidirectional or bidirectional crosstalk between two independent cell types has been well characterized, the multi-directional interplays between cancer cells, fibroblasts, and immune cells in vitro and in vivo are still unclear. We summarize recent studies in addressing the interaction of the “Trinity” members in the tumor microenvironment and propose a functional network for how these members communicate with each other. In addition, we discuss the underlying mechanisms mediating the interplay. Moreover, correlations of the alterations in the distribution and functionality of cancer cells, fibroblasts, and immune cells under different circumstances are reviewed. Finally, we point out the future application of CD8+ T cell-oriented therapy in the treatment of pancreatic cancer.

Macrophage and T-Cell Infiltration and Topographic Immune Cell Distribution in Non-Melanoma Skin Cancer of the Head and Neck.

Non-melanoma skin cancer (NMSC) is a heterogeneous tumor entity that is vastly determined by age and UV-light exposure leading to a great mutational burden in cancer cells. However, the success of immune checkpoint blockade in advanced NMSC and the incidence and disease control rates of NMSC in organ transplant recipients compared to immunologically uncompromised patients point toward the emerging importance of the immunologic activity of NMSC. To gain first insight into the role of T-cell and macrophage infiltration in NMSC of the head and neck and capture their different immunogenic profiles, which appear to be highly relevant for the response to immunotherapy, we conducted a whole slide analysis of 107 basal cell carcinoma (BCC) samples and 117 cutaneous squamous cell carcinoma (cSCC) samples. The CD8+ and CD68+ immune cell expression in both cancer types was evaluated by immunohistochemistry and a topographic distribution profile, and the proportion of both cell populations within the two tumor entities was assessed. The results show highly significant differences in terms of CD8+ T-cell and CD68+ macrophage infiltration in BCC and cSCC and indicate cSCC as a highly immunogenic tumor. Yet, BCC presents less immune cell infiltration; the relation between the immune cells compared to cSCC does not show any significant difference. These findings help explain disparities in local aggressiveness, distant metastasis, and eligibility for immune checkpoint blockade in both tumor entities and encourage further research.

Interspatial Distribution of Tumor and Immune Cells in Correlation with PD-L1 in Molecular Subtypes of Gastric Cancers.

Simple SummaryThe majority of gastric cancers are negative for the Epstein–Barr virus (EBV) and mismatch repair-proficient, or microsatellite stable. Molecular subtyping currently does not influence clinical decision making, and accurate response prediction towards immunotherapy remains a major challenge. We therefore analyzed PD-L1 expression, tumor-infiltrating lymphocytes, and their spatial relationship to tumor cells in EBV-negative mismatch repair-proficient gastric cancers compared to EBV-positive and mismatch repair-deficient tumors to identify an immunogenic phenotype that is susceptible to immunotherapy in this large group. We demonstrated a close relationship between the total number of tumor-infiltrating lymphocytes, their proximity to tumor cells, and the expression of PD-L1 across all subtypes, including the EBV-negative and mismatch repair-proficient cancers. However, we also identified a subgroup of PD-L1-negative, EBV-negative, and mismatch repair-proficient cancers with high numbers of tumor-associated CD8+ lymphocytes. This is indicative of an immunoreactive phenotype in a subgroup of gastric cancers along or independent of PD-L1 status and molecular type.(1) Background: EBV-positive and mismatch repair-deficient (MMRd) gastric cancers (GCs) show higher levels of tumor-infiltrating lymphocytes (TILs) and PD-L1 expression and thus a more profound response to immunotherapy. However, the majority of GCs are EBV-negative (EBV−) and MMR proficient (MMRp). We analyzed PD-L1 expression and TILs in EBV-MMRpGCs in comparison to EBV-positive (EBV+) and MMRdGCs to identify an immunogenic phenotype susceptible to immunotherapy. (2) Methods: A next-generation tissue microarray of 409 primary resected GCs was analyzed by Epstein-Barr encoding region (EBER) in situ hybridization for MSH1, PMS2, MSH2, MSH6, PD-L1, and CD8 immunohistochemistry. PD-L1 positivity was defined as a combined positive score (CPS) of ≥1. CD8+ TILs and their proximity to cancer cells were digitally analyzed on the HALO™ image analysis platform. (3) Results: Eleven cases were EBV+, 49 cases MMRd, and 349 cases EBV-MMRpGCs. The highest rate of PD-L1 positivity was seen in EBV+GCs, followed by MMRdGCs and EBV-MMRpGCs (81.8%, 73.5%, and 27.8%, respectively). EBV+ and MMRdGCs also demonstrated increased numbers and proximity of CD8+ TILs to tumor cells compared to EBV-MMRpGCs (p < 0.001 each). PD-L1 status positively correlated with the total numbers of CD8+ TILs and their proximity to tumor cells in all subtypes, including EBV-MMRpGCs (p < 0.001 each). A total of 28.4% of EBV-MMRpGCs showed high CD8+ TILs independent of PD-L1. (4) Conclusions: PD-L1 and CD8 immunohistochemistry, supplemented by digital image analysis, may identify EBV-MMRpGCs with high immunoreactivity indices, indicating susceptibility to immunotherapy.

Tracking fluorescently labeled IL-15 and anti-PD-1 in the tumor microenvironment and draining lymph nodes

Understanding the dynamics of the tumor microenvironment (TME) has become vital in discovering new targets for effective immunotherapies and enhancing current treatments. However, localization and distribution of immune cells and treatment biomolecules are poorly characterized to date. In this study, a murine Luminal B mammary adenocarcinoma model received a combinatorial treatment of fluorescently labeled anti-PD-1-Cy3 and IL-15 complex-Cy5 injected interperitoneally and intratumorally, respectively. Fluorescent labeling allowed for the visualization of the distribution of IL-15 complexes and anti-PD-1, as well as their localization to immune cells in the TME and tumor-draining lymph node. Using fluorescent microscopy and light sheet microscopy of whole-clarified tumors and draining lymph nodes, the localization of IL-15 complexes was found to be distributed around the periphery of the tumor at 4 h post injection and medially located at the center of the tumor at 24 h post injection, corresponding with high densities of CD8 cells in the tumor present at 48 h and 72 h post injection. Anti-PD-1 was distributed around the perimeter of the tumor and colocalized to IL-15 in the draining lymph nodes 24 h post injection. Colocalization of IL-15 was also established with NK cells, CD8+ T cells, and macrophages. This study develops a novel method to spatiotemporally track fluorescently labeled immunotherapeutic biomolecules in vivo, with implications for optimizing and further understanding the pharmacokinetics of clinical immunotherapies.

Immune Cells in Pulmonary Arterial Hypertension

Pulmonary arterial hypertension (PAH) is a complex and serious cardiopulmonary disease; it is characterised by increased pulmonary arterial pressure and pulmonary vascular remodelling accompanied by disordered endothelial and smooth muscle cell proliferation within pulmonary arterioles and arteries. Although recent reports have suggested that dysregulated immunity and inflammation are key players in PAH pathogenesis, their roles in PAH progression remain unclear. Intriguingly, altered host immune cell distribution, number, and polarisation within the lung arterial vasculature have been linked to disease development. This review mainly focusses on the roles of different immune cells in PAH and discusses the underlying mechanisms.

The Role of Autophagy in Tumor Immune Infiltration in Colorectal Cancer.

Objective This study is aimed at exploring the association between autophagy and tumor immune infiltration (TII) in colorectal cancer (CRC). Methods and Materials We downloaded the transcriptome profiling and clinical data for CRC from The Cancer Genome Atlas (TCGA) database and obtained the normal colon transcriptome profiling data from Genotype-Tissue Expression Project (GTEx) database. The list of autophagy-related signatures was obtained from the Human Autophagy Database. We isolated the autophagy-related genes from the CRC gene expression matrix and constructed an autophagy-related prognostic (ARP) risk model. Then, we constructed a multiROC curve to validate the prognostic ability of the ARP risk model. CIBERSORT was used to determine the fractions of 22 immune cells in each CRC sample, and the association between these TII cells and CRC clinical variables was further investigated. Finally, we estimated the association of 3 hub-ARP signatures and 20 different types of TII cell distribution. Results We classified 447 CRC patients into 224 low-risk and 223 high-risk patients using the median ARP risk score. According to the univariate survival test results, except for gender (P = 0.672), age (P = 0.008), cancer stage, and pathological stage T, M, and N were closely correlated with the prognosis of CRC patients (P < 0.001). Multivariate survival analysis results indicate that age and rescore were the only independent prognostic indicators with significant differences (P < 0.05). After merging the immune cell distribution (by CIBERSORT) with the CRC clinical data, the results indicate that activated macrophage M0 cells exhibited the highest clinical response, which included cancer stage and stage T, N, and M. Additionally, six immune cells were closely associated with cancer stage, including regulatory T cells (Tregs), gamma delta T cells, follicular helper T cells, activated memory CD4 T cells, activated NK cells, and resting dendritic cells. Finally, we evaluated the correlation of ARP signatures with TII cell distribution. Compared with the other correlation, NRG1 and plasma cells (↑), risk score and macrophage M1 (↑), NRG1 and dendritic cell activated (↑), CDKN2A and T cell CD4 memory resting (↓), risk score and T cell CD8 (↑), risk score and T cell CD4 memory resting (↓), and DAPK1 and T cell CD4 memory activated (↓) exhibited a stronger association (P < 0.0001). Conclusions In summary, we explored the correlation between the risk of autophagy and the TII microenvironment in CRC patients. Furthermore, we integrated different CAR signatures with tumor-infiltrating immune cells and found robust associations between different levels of CAR signature expression and immune cell infiltrating density.

ETV4 potentiates nuclear YAP retention and activities to enhance the progression of hepatocellular carcinoma

Dysregulation of the Hippo pathway that promotes cell survival, proliferation and tumorigenesis, relays on the coordinated interactions of YAP with the factors that determine YAP translocation and the related transcriptional programming. Here, we demonstrate that ETV4, a transcriptional factor participating in various protumorigenic processes, enhances YAP-mediated transactivation and hepatocellular carcinoma (HCC) progression. Mechanistically, the enhancement of YAP activities is mediated by the interaction between ETV4 and YAP, which not only increases nuclear YAP accumulation but also directly augments the YAP/TEAD4-mediated transcriptional activation in tumor cells. Functionally, the interplay of ETV4 and YAP promotes growth of liver tumor cells, and activates the genes related to myeloid cell recruitment, including CXCL1 and CXCL5, leading to an enriched presence of myeloid-derived suppressive cells and macrophages but a decreased infiltration of T cells and NK cells in transplanted tumors. More importantly, the correlations between YAP activation, the altered immune cell distribution and ETV4 expression are observed in human HCCs. Therefore, our study reveals a functional interaction between ETV4 and YAP that contributes to HCC progression, and provides mechanistic insights into the regulation of nuclear YAP retention and transactivation.

Comprehensive Assessment of Selected Immune Cell Subpopulations Changes in Chemotherapy-Naïve Germ Cell Tumor Patients.

The pattern of immune cell distribution in testicular germ cell tumors (GCT) significantly differs from the immune environment in normal testicular tissues. The present study aimed to evaluate the role of different leukocyte subpopulation in GCTs. A cohort of 84 chemotherapy-naïve GCT patients was analyzed. Immunophenotyping of peripheral blood leukocyte subpopulations was carried out by flow cytometry. In addition, the data assessing the immunophenotypes and the baseline clinicopathological characteristics of the included subjects were statistically evaluated. Their prognostic value for the assessment of progression-free survival (PFS) and overall survival (OS) was estimated. The percentage of different innate/adaptive immune cell subpopulations was significantly associated with poor risk-related clinical features, including the number of metastatic sites, presence of retroperitoneal, mediastinal, lung, brain and non-pulmonary visceral metastases as well as with the S-stage and International Germ Cell Consensus Classification Group (IGCCCG) risk groups. In univariate analysis, the percentages of neutrophils, eosinophils, dendritic cells type 2, lymphocytes and T cytotoxic cells were significantly associated with PFS, while the neutrophil, non-classical monocyte and lymphocyte percentage were associated with OS. However, all these outcome correlations were not independent of IGCCCG in multivariate analysis. The data indicated a link among different innate/adaptive peripheral immune cell subpopulations in GCT patients. In addition, the association between these subpopulations and tumor characteristics was also investigated. The findings of the present study may contribute to a deeper understanding of the interactions between cancer and innate/adaptive immune response in GCT patients.

Immune cells in the small intestinal mucosa of newborn yaks.

This study aimed to characterise and evaluate the main markers of T lymphocytes, B lymphocytes, immunoglobulin (Ig) A and IgG plasmocytes, macrophages, and dendritic cells of the intestinal mucosa of newborn yaks. Ten newborn yaks (2-4 weeks old) were chosen. Immunohistochemistry and real-time quantitative polymerase chain reaction were used to analyse the immune cell distribution and specific markers at the mRNA expression level in the duodenum, jejunum, and ileum. The results showed in the epithelium, CD3e-positive T lymphocyte levels were higher than other immune cell levels (p < 0.05). Additionally, in the lamina propria, the number of cells positive for CD3e, CD68, and signal inhibitory regulatory protein alpha (SIRPa) were higher in the villi, while CD79a, IgA and IgG cells were more common at the base of the crypt. Moreover, both in the epithelium and lamina propria, the number of CD3e, CD68 and SIRPa were decreased from the duodenum to the ileum (p < 0.05), additionally the number of CD79a, IgA and IgG positive cells were increased from the duodenum to the ileum of newborn yaks (p < 0.05). Furthermore, the mRNA expression levels of CD3e, CD68, and SIRPa increased from the duodenum to the ileum (p < 0.05), while the mRNA expression levels of CD79a, IgA and IgG decreased from the duodenum to the ileum. Immunohistochemical characterisation and expression levels of immune factors in the small intestinal mucosa of newborn yaks suggest that the intestinal mucosa is an important part of the natural barrier and provides useful references for immunity functions of newborn yak intestinal mucosa.