CLEC5A expressed on myeloid cells as a M2 biomarker relates to immunosuppression and decreased survival in patients with glioma

Sexual-biased necroinflammation is revealed as a predictor of bevacizumab benefit in glioblastoma

BACKGROUND

Glioblastoma (GBM) is a highly malignant brain tumor that affects men more often than women. In addition, the former shows a poorer survival prognosis. To date, the reason for this sex-specific aggressiveness remains unclear. Therefore, the aim of this study is to investigate tumor processes that explain these sex differences.

METHODS

This was a retrospective study of GBM patients which was stratified according to sex. A cohort with 73 tumors was analyzed with immunohistochemistry, RNA-seq and RT-qPCR to characterize differences in vascular and immunological profiles. Transcriptomic profiling, gene set enrichment analysis, and pathway enrichment analysis were used for discovering molecular pathways predominant in each group. We further investigated the therapeutic effect of bevacizumab (vascular endothelial growth factor A (VEGFA) blocking antibody) in a retrospective GBM cohort (36 tumors) based on sex differences.

RESULTS

We found that under hypoxic tumor conditions, 2 distinct tumor immuno-angiogenic ecosystems develop linked to sex differences and ESR1 expression is generated. One of these subgroups, which includes male patients with low ESR1 expression, is characterized by vascular fragility associated with the appearance of regions of necrosis and high inflammation (called necroinflamed tumors). This male-specific tumor subtype shows high inflammation related to myeloid-derived suppressor cells infiltration. Using this stratification, we identified a possible group of patients who could respond to bevacizumab (BVZ) and revealed a genetic signature that may find clinical applications as a predictor of those who may benefit most from this treatment.

CONCLUSIONS

This study provides a stratification based on the sexual differences in GBM, which associates the poor prognosis with the presence of immunosuppressive myeloid cells in the necrotic areas. This new stratification could change the current prognosis of GBM and identifies those who respond to BVZ treatment.

Sarcoma microenvironment cell states and ecosystems are associated with prognosis and predict response to immunotherapy

Characterization of the diverse malignant and stromal cell states that make up soft tissue sarcomas and their correlation with patient outcomes has proven difficult using fixed clinical specimens. Here, we employed EcoTyper, a machine-learning framework, to identify the fundamental cell states and cellular ecosystems that make up sarcomas on a large scale using bulk transcriptomes with clinical annotations. We identified and validated 23 sarcoma-specific, transcriptionally defined cell states, many of which were highly prognostic of patient outcomes across independent datasets. We discovered three conserved cellular communities or ecotypes associated with underlying genomic alterations and distinct clinical outcomes. We show that one ecotype defined by tumor-associated macrophages and epithelial-like malignant cells predicts response to immune-checkpoint inhibition but not chemotherapy and validate our findings in an independent cohort. Our results may enable identification of patients with soft tissue sarcomas who could benefit from immunotherapy and help develop new therapeutic strategies.

The genes significantly associated with an improved prognosis and long-term survival of glioblastoma

BACKGROUND AND PURPOSE

Glioblastoma multiforme (GBM) is the most devastating brain tumor with less than 5% of patients surviving 5 years following diagnosis. Many studies have focused on the genetics of GBM with the aim of improving the prognosis of GBM patients. We investigated specific genes whose expressions are significantly related to both the length of the overall survival and the progression-free survival in patients with GBM.

METHODS

We obtained data for 12,042 gene mRNA expressions in 525 GBM tissues from the Cancer Genome Atlas (TCGA) database. Among those genes, we identified independent genes significantly associated with the prognosis of GBM. Receiver operating characteristic (ROC) curve analysis was performed to determine the genes significant for predicting the long-term survival of patients with GBM. Bioinformatics analysis was also performed for the significant genes.

RESULTS

We identified 33 independent genes whose expressions were significantly associated with the prognosis of 525 patients with GBM. Among them, the expressions of five genes were independently associated with an improved prognosis of GBM, and the expressions of 28 genes were independently related to a poorer prognosis of GBM. The expressions of the ADAM22, ATP5C1, RAC3, SHANK1, AEBP1, C1RL, CHL1, CHST2, EFEMP2, and PGCP genes were either positively or negatively related to the long-term survival of GBM patients.

CONCLUSIONS

Using a large-scale and open database, we found genes significantly associated with both the prognosis and long-term survival of patients with GBM. We believe that our findings may contribute to improving the understanding of the mechanisms underlying GBM.

Effective Reprogramming of Patient-Derived M2-Polarized Glioblastoma-Associated Microglia/Macrophages by Treatment with GW2580

PURPOSE

Targeting immunosuppressive and pro-tumorigenic glioblastoma (GBM)-associated macrophages and microglial cells (GAM) has great potential to improve patient outcomes. Colony-stimulating factor-1 receptor (CSF1R) has emerged as a promising target for reprograming anti-inflammatory M2-like GAMs. However, treatment data on patient-derived, tumor-educated GAMs and their influence on the adaptive immunity are lacking.

EXPERIMENTAL DESIGN

CD11b+-GAMs freshly isolated from patient tumors were treated with CSF1R-targeting drugs PLX3397, BLZ945, and GW2580. Phenotypical changes upon treatment were assessed using RNA sequencing, flow cytometry, and cytokine quantification. Functional analyses included inducible nitric oxide synthase activity, phagocytosis, transmigration, and autologous tumor cell killing assays. Antitumor effects and changes in GAM activation were confirmed in a complex patient-derived 3D tumor organoid model serving as a tumor avatar.

RESULTS

The most effective reprogramming of GAMs was observed upon GW2580 treatment, which led to the downregulation of M2-related markers, IL6, IL10, ERK1/2, and MAPK signaling pathways, while M1-like markers, gene set enrichment indicating activated MHC-II presentation, phagocytosis, and T-cell killing were substantially increased. Moreover, treatment of patient-derived GBM organoids with GW2580 confirmed successful reprogramming, resulting in impaired tumor cell proliferation. In line with its failure in clinical trials, PLX3397 was ineffective in our analysis.

CONCLUSIONS

This comparative analysis of CSF1R-targeting drugs on patient-derived GAMs and human GBM avatars identified GW2580 as the most powerful inhibitor with the ability to polarize immunosuppressive GAMs to a proinflammatory phenotype, supporting antitumor T-cell responses while also exerting a direct antitumor effect. These data indicate that GW2580 could be an important pillar in future therapies for GBM.

Six potential biomarkers in septic shock: a deep bioinformatics and prospective observational study

Background

Septic shock occurs when sepsis is related to severe hypotension and leads to a remarkable high number of deaths. The early diagnosis of septic shock is essential to reduce mortality. High-quality biomarkers can be objectively measured and evaluated as indicators to accurately predict disease diagnosis. However, single-gene prediction efficiency is inadequate; therefore, we identified a risk-score model based on gene signature to elevate predictive efficiency.

Methods

The gene expression profiles of GSE33118 and GSE26440 were downloaded from the Gene Expression Omnibus (GEO) database. These two datasets were merged, and the differentially expressed genes (DEGs) were identified using the limma package in R software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments of DEGs were performed. Subsequently, Lasso regression and Boruta feature selection algorithm were combined to identify the hub genes of septic shock. GSE9692 was then subjected to weighted gene co-expression network analysis (WGCNA) to identify the septic shock-related gene modules. Subsequently, the genes within such modules that matched with septic shock-related DEGs were identified as the hub genes of septic shock. To further understand the function and signaling pathways of hub genes, we performed gene set variation analysis (GSVA) and then used the CIBERSORT tool to analyze the immune cell infiltration pattern of diseases. The diagnostic value of hub genes in septic shock was determined using receiver operating characteristic (ROC) analysis and verified using quantitative PCR (qPCR) and Western blotting in our hospital patients with septic shock.

Results

A total of 975 DEGs in the GSE33118 and GSE26440 databases were obtained, of which 30 DEGs were remarkably upregulated. With the use of Lasso regression and Boruta feature selection algorithm, six hub genes (CD177, CLEC5A, CYSTM1, MCEMP1, MMP8, and RGL4) with expression differences in septic shock were screened as potential diagnostic markers for septic shock among the significant DEGs and were further validated in the GSE9692 dataset. WGCNA was used to identify the co-expression modules and module-trait correlation. Enrichment analysis showed significant enrichment in the reactive oxygen species pathway, hypoxia, phosphatidylinositol 3-kinases (PI3K)/Protein Kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling, nuclear factor-κβ/tumor necrosis factor alpha (NF-κβ/TNF-α), and interleukin-6 (IL-6)/Janus Kinase (JAK)/Signal Transducers and Activators of Transcription 3 (STAT3) signaling pathways. The receiver operating characteristic curve (ROC) of these signature genes was 0.938, 0.914, 0.939, 0.956, 0.932, and 0.914, respectively. In the immune cell infiltration analysis, the infiltration of M0 macrophages, activated mast cells, neutrophils, CD8 T cells, and naive B cells was more significant in the septic shock group. In addition, higher expression levels of CD177, CLEC5A, CYSTM1, MCEMP1, MMP8, and RGL4 messenger RNA (mRNA) were observed in peripheral blood mononuclear cells (PBMCs) isolated from septic shock patients than from healthy donors. Higher expression levels of CD177 and MMP8 proteins were also observed in the PBMCs isolated from septic shock patients than from control participants.

Conclusions

CD177, CLEC5A, CYSTM1, MCEMP1, MMP8, and RGL4 were identified as hub genes, which were of considerable value in the early diagnosis of septic shock patients. These preliminary findings are of great significance for studying immune cell infiltration in the pathogenesis of septic shock, which should be further validated in clinical studies and basic studies.

Cancer immune profiling unveils biomarkers, immunological pathways, and cell type score associated with glioblastoma patients' survival

Introduction

Glioblastoma (GBM), isocitrate dehydrogenase (IDH) wild-type (IDH ^wt), and grade 4 astrocytomas, IDH mutant (IDH ^mut), are the most common and aggressive primary malignant brain tumors in adults. A better understanding of the tumor immune microenvironment may provide new biomarkers and therapeutic opportunities.

Objectives

We aimed to evaluate the expression profile of 730 immuno-oncology-related genes in patients with IDH ^wt GBM and IDH ^mut tumors and identify prognostic biomarkers and a gene signature associated with patient survival.

Methods

RNA was isolated from formalin-fixed, paraffin-embedded sections of 99 tumor specimens from patients treated with standard therapy. Gene expression profile was assessed using the Pan-Cancer Immune Profiling Panel (Nanostring Technologies, Inc., Seattle, WA, USA). Data analysis was performed using nSolverSoftware and validated in The Cancer Genome Atlas. In addition, we developed a prognostic signature using the cox regression algorithm (Least Absolute Shrinkage and Selection Operator).

Results

We found 88 upregulated genes, high immunological functions, and a high macrophage score in IDH ^wt GBM compared to IDH ^mut tumors. Regarding IDH ^wt GBM, we found 24 upregulated genes in short-term survivors (STS) and overexpression of CD274 (programmed death-ligand 1, PD-L1). Immune pathways, CD45, cytotoxic, and macrophage scores were upregulated in STS. Two different prognostic groups were found based on the 12-gene signature (CXCL14, PSEN2, TNFRSF13C, IL13RA1, MAP2K1, TNFSF14, THY1, CTSL, ITGAE, CHUK, CD207, and IFITM1).

Conclusion

The elevated expression of immune-oncology-related genes was associated with worse outcome in IDH ^wt GBM patients. Increased immune functions, CD45, cytotoxic cells, and macrophage scores were associated with a more aggressive phenotype and may provide promising possibilities for therapy. Moreover, a 12 gene-based signature could predict patients' prognosis.

TMEM158 promotes the proliferation and migration of glioma cells via STAT3 signaling in glioblastomas

Glioblastoma is the most common primary intracranial malignant tumor in adults and has high morbidity and high mortality. TMEM158 has been reported to promote the progression of solid tumors. However, its potential role in glioma is still unclear. Here, we found that TMEM158 expression in human glioma cells in the tumor core was significantly higher than that in noncancerous cells at the tumor edge using bioinformatics analysis. Cancer cells in patients with primary GBMs harbored significantly higher expression of TMEM158 than those in patients with WHO grade II or III gliomas. Interestingly, regardless of tumor grading, human glioma samples that were IDH1-wild-type (IDH1-WT) exhibited higher expression of TMEM158 than those with IDH1-mutant (IDH1-Mut). We also illustrated that TMEM158 mRNA expression was correlated with poor overall survival in glioma patients. Furthermore, we demonstrated that silencing TMEM158 inhibited the proliferation of glioma cells and that TMEM158 overexpression promoted the migration and invasion of glioma cells by stimulating the EMT process. We found that the underlying mechanism involves STAT3 activation mediating TMEM158-driven glioma progression. In vivo results further confirmed the inhibitory effect of the TMEM158 downregulation on glioma growth. Collectively, these findings further our understanding of the oncogenic function of TMEM158 in gliomas, which represents a potential therapeutic target, especially for GBMs.

A Pan-Cancer Analysis Reveals CLEC5A as a Biomarker for Cancer Immunity and Prognosis

Background

CLEC5A is a member of the C-type lectin superfamily. It can activate macrophages and lead to a series of immune-inflammation reactions. Previous studies reveal the role of CLEC5A in infection and inflammation diseases.

Method

We acquire and analyze data from The Cancer Genome Atlas (TCGA) database, Genotype-Tissue Expression (GTEx) database, and other comprehensive databases via GSCALite, cBioPortal, and TIMER 2.0 platforms or software. Single-cell sequencing analysis was performed for quantifying the tumor microenvironment of several types of cancers.

Results

CLEC5A is differentially expressed in a few cancer types, of which overexpression accompanies low overall survival of patients. DNA methylation mainly negatively correlates with CLEC5A expression. Moreover, CLEC5A is positively related to immune infiltration, including macrophages, cancer-associated fibroblasts (CAFs), and regulatory T cells (Tregs). Immune checkpoint genes are significantly associated with CLEC5A expression in diverse cancers. In addition, CLEC5A expression correlates with mismatch repair (MMR) in several cancers. Tumor mutation burden (TMB), microsatellite instability (MSI), and neoantigens show a positive association with CLEC5A expression in several cancers. Furthermore, CLEC5A in cancer correlates with signal transduction, the immune system, EMT, and apoptosis process. The drug sensitivity analysis screens out potential therapeutic agents associated with CLEC5A expression, including FR-180204, Tivozanib, OSI-930, Linifanib, AC220, VNLG/124, Bexarotene, omacetaxine mepesuccinate, narciclasine, leptomycin B, PHA-793887, LRRK2-IN-1, and CR-1-31B.

Conclusion

CLEC5A overexpresses in multiple cancers in contrast to normal tissues, and high CLEC5A expression predicts poor prognosis of patients and immune infiltration. CLEC5A is a potential prognostic biomarker of diverse cancers and a target for anti-tumor therapy.

Activation of the Innate Immune Checkpoint CLEC5A on Myeloid Cells in the Absence of Danger Signals Modulates Macrophages’ Function but Does Not Trigger the Adaptive T Cell Immune Response

C-Type lectin receptor 5A (CLEC5A) is a spleen tyrosine kinase- (Syk-) coupled pattern recognition receptor expressed on myeloid cells and involved in the innate immune response to viral and bacterial infections. Activation of the CLEC5A receptor with pathogen-derived antigens leads to a secretion of proinflammatory mediators such as TNF-α and IL-6 that may provoke a systemic cytokine storm, and CLEC5A gene polymorphisms are associated with the severity of DV infection. In addition, the CLEC5A receptor was mentioned in the context of noninfectious disorders like chronic obstructive pulmonary disease (COPD) or arthritis. Altogether, CLEC5A may be considered as an innate immune checkpoint capable to amplify proinflammatory signals, and this way contributes to infection or to aseptic inflammation. In this study, we determined CLEC5A receptor expression on different macrophage subsets (in vitro and ex vivo) and the functional consequences of its activation in aseptic conditions. The CLEC5A surface expression appeared the highest on proinflammatory M1 macrophages while intermediate on tumor-associated phenotypes (M2c or TAM). In contrast, the CLEC5A expression on ex vivo-derived alveolar macrophages from healthy donors or macrophages from ovarian cancer patients was hardly detectable. Targeting CLEC5A on noninflammatory macrophages with an agonistic α-CLEC5A antibody triggered a release of proinflammatory cytokines, resembling a response to dengue virus, and led to phenotypic changes in myeloid cells that may suggest their reprogramming towards a proinflammatory phenotype, e.g., upregulation of CD80 and downregulation of CD163. Interestingly, the CLEC5A agonist upregulated immune-regulatory molecules like CD206, PD-L1, and cytokines like IL-10, macrophage-derived chemokine (MDC/CCL22), and thymus and activation chemokine (TARC/CCL17) which are associated with an anti-inflammatory or a protumorigenic macrophage phenotype. In the absence of concomitant pathogenic or endogenous danger signals, the CLEC5A receptor activation did not amplify an autologous T cell response, which may represent a protective innate mechanism to avoid an undesirable autoimmune adaptive response.

Identification of an Immune-Related Prognostic Gene CLEC5A Based on Immune Microenvironment and Risk Modeling of Ovarian Cancer

Objective: To understand the immune characteristics of the ovarian cancer (OC) microenvironment and explore the differences of immune-related molecules and cells to establish an effective risk model and identify the molecules that significantly affected the immune response of OC, to help guide the diagnosis. Methods: First, we calculate the TMEscore which reflects the immune microenvironment, and then analyze the molecular differences between patients with different immune characteristics, and determine the prognostic genes. Then, the risk model was established by least absolute shrinkage and selection operator (LASSO) analysis and combined with clinical data into a nomogram for diagnosis and prediction. Subsequently, the potential gene CLEC5A influencing the immune response of OC was identified from the prognostic genes by integrative immune-stromal analysis. The genomic alteration was explored based on copy number variant (CNV) and somatic mutation data. Results: TMEscore was a prognostic indicator of OC. The prognosis of patients with high TMEscore was better. The risk model based on immune characteristics was a reliable index to predict the prognosis of patients, and the nomogram could comprehensively evaluate the prognosis of patients. Besides, CLEC5A was closely related to the abundance of immune cells, immune response, and the expression of immune checkpoints in the OC microenvironment. OC cells with high expression of CLEC5A increased the polarization of M2 macrophages. CLEC5A expression was significantly associated with TTN and CDK12 mutations and affected the copy number of tumor progression and immune-related genes. Conclusion: The study of immune characteristics in the OC microenvironment and the risk model can reveal the factors affecting the prognosis and guide the clinical hierarchical treatment. CLEC5A can be used as a potential key gene affecting the immune microenvironment remodeling of OC, which provides a new perspective for improving the effect of OC immunotherapy.

Atlas of clinically distinct cell states and ecosystems across human solid tumors

Determining how cells vary with their local signaling environment and organize into distinct cellular communities is critical for understanding processes as diverse as development, aging, and cancer. Here we introduce EcoTyper, a machine learning framework for large-scale identification and validation of cell states and multicellular communities from bulk, single-cell, and spatially resolved gene expression data. When applied to 12 major cell lineages across 16 types of human carcinoma, EcoTyper identified 69 transcriptionally defined cell states. Most states were specific to neoplastic tissue, ubiquitous across tumor types, and significantly prognostic. By analyzing cell-state co-occurrence patterns, we discovered ten clinically distinct multicellular communities with unexpectedly strong conservation, including three with myeloid and stromal elements linked to adverse survival, one enriched in normal tissue, and two associated with early cancer development. This study elucidates fundamental units of cellular organization in human carcinoma and provides a framework for large-scale profiling of cellular ecosystems in any tissue.

Immunological and clinicopathological characteristics of C1RL in 2120 glioma patients

BACKGROUND

Glioma is a deadly and immunosuppressive brain tumour. Complement C1r subcomponent like (C1RL), a prognostic biomarker in several kinds of tumours, has attracted increasing attention from oncologists. However, the role of C1RL in glioma remains unclear.

METHODS

Through analysis of 2120 glioma patients from 5 public datasets, the relationships between C1RL expression and clinicopathological characteristics were evaluated. Furthermore, the C1RL-associated genes were screened, and Gene Ontology (GO) analysis was conducted to investigate biological process enrichment. In addition, tumour purity, leukocyte infiltration and overall survival were evaluated based on C1RL expression.

RESULTS

We found that C1RL expression was upregulated in glioblastoma (GBM), especially mesenchymal GBM and primary GBM. Increased C1RL expression accompanied the IDH1-wt phenotype in both lower grade glioma (LGG) and GBM. C1RL- associated genes were mainly enriched in biological processes related to the immune response. C1RL expression was also correlated with reduced tumour purity and increased M2 macrophage infiltration. Higher C1RL expression predicted unfavourable survival in patients with glioma and therapeutic resistance in GBM.

CONCLUSIONS

Our results imply that C1RL is involved in immunological activities and is an independent unfavourable prognostic biomarker in patients with glioma. C1RL is a potential clinical immunotherapeutic target for glioma treatment in the future.

Lactobacillus plantarum-derived extracellular vesicles induce anti-inflammatory M2 macrophage polarization in vitro

Probiotics offer various health benefits. Lactobacillus plantarum has been used for decades to enhance human intestinal mucosal immunity and improve skin barrier integrity. Extracellular vesicles (EVs) derived from eukaryotic or prokaryotic cells have been recognized as efficient carriers for delivery of biomolecules to recipient cells, and to efficiently regulate human pathophysiology. However, the mechanism underlying the beneficial effects of probiotic bacteria-derived EVs on human skin is unclear. Herein, we investigated how L. plantarum-derived EVs (LEVs) exert beneficial effects on human skin by examining the effect of LEVs on cutaneous immunity, particularly on macrophage polarization. LEVs promoted differentiation of human monocytic THP1 cells towards an anti-inflammatory M2 phenotype, especially M2b, by inducing biased expression of cell-surface markers and cytokines associated with M2 macrophages. Pre- or post-treatment with LEVs under inflammatory M1 macrophage-favouring conditions, induced by LPS and interferon-γ, inhibited M1-associated surface marker, HLA-DRα expression. Moreover, LEV treatment significantly induced expression of macrophage-characteristic cytokines, IL-1β, GM-CSF and the representative anti-inflammatory cytokine, IL-10, in human skin organ cultures. Hence, LEVs can trigger M2 macrophage polarization in vitro, and induce an anti-inflammatory phenomenon in the human skin, and may be a potent anti-inflammatory strategy to alleviate hyperinflammatory skin conditions.