C-type lectin domain family 5, member A (CLEC5A, MDL-1) promotes brain glioblastoma tumorigenesis by regulating PI3K/Akt signalling

Hypoxia-related THBD+ macrophages as a prognostic factor in glioma: Construction of a powerful risk model

Glioma is a prevalent malignant tumour characterized by hypoxia as a pivotal factor in its progression. This study aims to investigate the impact of the most severely hypoxic cell subpopulation in glioma. Our findings reveal that the THBD+ macrophage subpopulation is closely associated with hypoxia in glioma, exhibiting significantly higher infiltration in tumours compared to non-tumour tissues. Moreover, a high proportion of THBD+ cells correlates with poor prognosis in glioblastoma (GBM) patients. Notably, THBD+ macrophages exhibit hypoxic characteristics and epithelial-mesenchymal transition features. Silencing THBD expression leads to a notable reduction in the proliferation and metastasis of glioma cells. Furthermore, we developed a THBD+ macrophage-related risk signature (THBDMRS) through machine learning techniques. THBDMRS emerges as an independent prognostic factor for GBM patients with a substantial prognostic impact. By comparing THBDMRS with 119 established prognostic features, we demonstrate the superior prognostic performance of THBDMRS. Additionally, THBDMRS is associated with glioma metastasis and extracellular matrix remodelling. In conclusion, hypoxia-related THBD+ macrophages play a pivotal role in glioma pathogenesis, and THBDMRS emerges as a potent and promising prognostic tool for GBM, contributing to enhanced patient survival outcomes.

Bioinformatics strategies to identify differences in molecular biomarkers for ischemic stroke and myocardial infarction

Ischemic strokes (ISs) are commonly treated by intravenous thrombolysis using a recombinant tissue plasminogen activator; however, successful treatment can only occur within 3 hours after the stroke. Therefore, it is crucial to determine the causes and underlying molecular mechanisms, identify molecular biomarkers for early diagnosis, and develop precise preventive treatments for strokes. We aimed to clarify the differences in gene expression, molecular mechanisms, and drug prediction approaches between IS and myocardial infarction (MI) using comprehensive bioinformatics analysis. The pathogenesis of these diseases was explored to provide directions for future clinical research. The IS (GSE58294 and GSE16561) and MI (GSE60993 and GSE141512) datasets were downloaded from the Gene Expression Omnibus database. IS and MI transcriptome data were analyzed using bioinformatics methods, and the differentially expressed genes (DEGs) were screened. A protein-protein interaction network was constructed using the STRING database and visualized using Cytoscape, and the candidate genes with high confidence scores were identified using Degree, MCC, EPC, and DMNC in the cytoHubba plug-in. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the DEGs were performed using the database annotation, visualization, and integrated discovery database. Network Analyst 3.0 was used to construct transcription factor (TF) - gene and microRNA (miRNA) - gene regulatory networks of the identified candidate genes. The DrugBank 5.0 database was used to identify gene-drug interactions. After bioinformatics analysis of IS and MI microarray data, 115 and 44 DEGS were obtained in IS and MI, respectively. Moreover, 8 hub genes, 2 miRNAs, and 3 TFs for IS and 8 hub genes, 13 miRNAs, and 2 TFs for MI were screened. The molecular pathology between IS and MI presented differences in terms of GO and KEGG enrichment pathways, TFs, miRNAs, and drugs. These findings provide possible directions for the diagnosis of IS and MI in the future.

Phellopterin attenuates ovarian cancer proliferation and chemoresistance by inhibiting the PU.1/CLEC5A/PI3K-AKT feedback loop

Ovarian cancer is known as the second leading cause of gynecologic cancer-associated deaths in women worldwide. Developing new and effective compounds to alleviate chemoresistance is an urgent priority in ovarian cancer. Here, we aimed to reveal the biological function and underlying mechanisms of phellopterin, a naturally sourced ingredient of Angelica dahurica, in ovarian cancer progression as well as evaluate the therapeutic potential of phellopterin in ovarian cancer patients. In this investigation, we found that phellopterin mitigated DNA replication and induced cell cycle arrest, apoptosis, and DNA damage, attenuating cell proliferation and chemoresistance of ovarian cancer. Interestingly, bioinformatics analyses of data from our RNA sequencing and The Cancer Genome Atlas ovarian cancer dataset suggested that phellopterin presented anti-cancer activities in ovarian cancer cells by modulating signals affecting ovarian cancer progression and identified phellopterin as a potential compound in improving ovarian cancer patients' prognosis. In addition, the C-Type Lectin Domain Containing 5A (CLEC5A) was demonstrated as a downstream effector of phellopterin and involved in a positive PU.1/CLEC5A/PI3K-AKT feedback loop. Interestingly, phellopterin might inactivate the positive feedback circuit to suppress ovarian cancer progression. Collectively, our investigation revealed that phellopterin mitigated ovarian cancer proliferation and chemoresistance through suppressing the PU.1/CLEC5A/PI3K-AKT feedback loop, and predicted phellopterin as a new and effective cytotoxic drug and CLEC5A as a potential target for the treatment of ovarian cancer.

[Overexpression of CLEC5A inhibits cell proliferation and metastasis and reverses epithelial-mesenchymal transition in hepatocellular carcinoma]

OBJECTIVE

To evaluate the effects of CLEC5A expression level on cell proliferation, migration and invasion and epithelial-mesenchymal transition (EMT) in hepatocellular carcinoma (HCC) and explore the role of CLEC5A in the tumorigenesis and progression of HCC.

METHODS

The expression level of CLEC5A was detected in 50 pairs of HCC and adjacent tissues using immunohistochemical staining, and its association with clinicopathological parameters of HCC patients was analyzed. Cultured HCC cell line SK-HEP-1 was transfected with a lentiviral vector overexpressing CLEC5A, and the transfection efficiency was verified using real-time fluorescence quantitative PCR and Western blotting. The changes in proliferation, migration and invasion abilities of the transfected cells were analyzed using CCK-8, 5-ethynyl-29-deoxyuridine (EdU) and Transwell assays, and EMT of the cells was determined using Western blotting.

RESULTS

The protein expression level of CLEC5A was significantly lower in HCC tissues than in the adjacent tissues (P < 0.001). The expression level of CLEC5A was significantly correlated with tumor size (P=0.008), tumor number (P=0.010), histological differentiation (P=0.016), microvascular invasion (P=0.024) and BCLC stage (P=0.040). In SK-HEP-1 cells, overexpression of CLEC5A obviously inhibited the cell proliferation, migration and invasion and reversed EMT phenotype of the cells.

CONCLUSION

CLEC5A is a potential HCC suppressor gene and may serve as a promising therapeutic target for HCC.

Development of a novel glycolysis-related genes signature for isocitrate dehydrogenase 1-associated glioblastoma multiforme

Background

The significant difference in prognosis between IDH1 wild-type and IDH1 mutant glioblastoma multiforme (GBM) may be attributed to their metabolic discrepancies. Hence, we try to construct a prognostic signature based on glycolysis-related genes (GRGs) for IDH1-associated GBM and further investigate its relationships with immunity.

Methods

Differentially expressed GRGs between IDH1 wild-type and IDH1 mutant GBM were screened based on the TCGA database and the Molecular Signature Database (MSigDB). Consensus Cluster Plus analysis and KEGG pathway analyses were used to establish a new GRGs set. WGCNA, univariate Cox, and LASSO regression analyses were then performed to construct the prognostic signature. Then, we evaluated association of the prognostic signature with patients’ survival, clinical characteristics, tumor immunogenicity, immune infiltration, and validated one hub gene.

Results

956 differentially expressed genes (DEGs) between IDH1 wild-type and mutant GBM were screened out and six key prognostically related GRGs were rigorously selected to construct a prognostic signature. Further evaluation and validation showed that the signature independently predicted GBM patients’ prognosis with moderate accuracy. In addition, the prognostic signature was also significantly correlated with clinical traits (sex and MGMT promoter status), tumor immunogenicity (mRNAsi, EREG-mRNAsi and HRD-TAI), and immune infiltration (stemness index, immune cells infiltration, immune score, and gene mutation). Among six key prognostically related GRGs, CLEC5A was selected and validated to potentially play oncogenic roles in GBM.

Conclusion

Construction of GRGs prognostic signature and identification of close correlation between the signature and immune landscape would suggest its potential applicability in immunotherapy of GBM in the future.

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.

Glycan-Lectin Interactions as Novel Immunosuppression Drivers in Glioblastoma

Despite diagnostic and therapeutic improvements, glioblastoma (GB) remains one of the most threatening brain tumor in adults, underlining the urgent need of new therapeutic targets. Lectins are glycan-binding proteins that regulate several biological processes through the recognition of specific sugar motifs. Lectins and their ligands are found on immune cells, endothelial cells and, also, tumor cells, pointing out a strong correlation among immunity, tumor microenvironment and vascularization. In GB, altered glycans and lectins contribute to tumor progression and immune evasion, shaping the tumor-immune landscape promoting immunosuppressive cell subsets, such as myeloid-derived suppressor cells (MDSCs) and M2-macrophages, and affecting immunoeffector populations, such as CD8⁺ T cells and dendritic cells (DCs). Here, we discuss the latest knowledge on the immune cells, immune related lectin receptors (C-type lectins, Siglecs, galectins) and changes in glycosylation that are involved in immunosuppressive mechanisms in GB, highlighting their interest as possible novel therapeutical targets.

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.

A comprehensive prognostic signature for glioblastoma patients based on transcriptomics and single cell sequencing

PURPOSE

Glioblastoma (GBM) is the most common and deadly brain tumor. We aimed to reveal potential prognostic GBM marker genes, elaborate their functions, and build an effective a prognostic model for GBM patients.

METHODS

Through data mining of The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA), we screened for significantly differentially expressed genes (DEGs) to calculate risk scores for individual patients. Published data of somatic mutation and copy number variation profiles were analyzed for distinct genomic alterations associated with risk scores. In addition, single-cell sequencing was used to explore the biological functions of the identified prognostic marker genes. By combining risk scores and other clinical features, we built a comprehensive prognostic GBM model.

RESULTS

Seven DEGs (CLEC5A, HOXC6, HOXA5, CCL2, GPRASP1, BSCL2 and PTX3) were identified as being prognostic for GBM. Expression of these genes was confirmed in different GBM cell lines using real-time PCR. Risk scores calculated from the seven DEGs revealed prognostic value irrespective of other clinical factors, including IDH mutation status, and were negatively correlated with TP53 expression. The prognostic genes were found to be associated with tumor proliferation and progression based on pseudo-time analysis in neoplastic cells. A final prognostic model was developed and validated with a good performance, especially in geriatric GBM patients.

CONCLUSIONS

Using genetic profiles, age, IDH mutation status, and chemotherapy and radiotherapy, we constructed a comprehensive prognostic model for GBM patients. The model has a good performance, especially in geriatric GBM patients.

Bioinformatic Profiling of Prognosis-Related Genes in Malignant Glioma Microenvironment

BACKGROUND Gliomas are the most common primary tumors of the brain and spinal cord. The tumor microenvironment (TME) is the cellular environment in which tumors exist. This study aimed to identify the role of the TME and the effects of genes involved in the TME of malignant glioma. MATERIAL AND METHODS The ESTIMATE algorithms in the R package were used to calculate the immune and stromal scores of samples in the TCGA and GSE4290 datasets. The associations of stromal and immune scores with clinicopathological characteristics and overall survival of malignant glioma patients were assessed by analysis of variance and Kaplan-Meier analysis. Differentially expressed genes (DEGs) were obtained through the median immune and stromal score using the R package "limma". Functional enrichment analysis and the PPI network MCODE were used to analyze DEGs. RESULTS Increased immune and stromal scores were closely related with advanced glioma grade and poor prognosis (all P<0.01). In total, 558 DEGs were found and most were related to tumor prognosis. Functional enrichment analysis showed that DEGs were associated with cell-matrix regulation and immune response. Four hub modules related to tumor angiogenesis, collagen formation, and immune response were found and analyzed. Previously overlooked microenvironment-related genes such as LAMB1, FN1, ACTN1, TRIM, SERPINH1, CYBA, LAIR1, and LILRB2 showed prognostic values in malignant glioma patients. CONCLUSIONS The glioma stromal/immune scores are closely related to glioma grade, histology, and survival time. Some glioma microenvironment-related genes including LAMB1, FN1, ACTN1, TRIM6, SERPINH1, CYBA, LAIR1, and LILRB2 show prognostic values in malignant gliomas and serve as potential biomarkers.

CLEC5A promotes the proliferation of gastric cancer cells by activating the PI3K/AKT/mTOR pathway

Gastric cancer (GC), as one of the most prevalent malignancies, contributes to the high morbidity and mortality worldwide. By analyzing the bioinformatics, qRT-PCR and IHC assays, we found that CLEC5A is overexpressed in GC and associated with poorer prognosis. CLEC5A silencing inhibits cell growth and DNA replication and induces cell cycle arrest and cell apoptosis. Bioinformatics analyses and Western blotting revealed that CLEC5A depletion led to the dysregulation of the PI3K/AKT/mTOR pathway. CLEC5A-mediated GC proliferation and anti-apoptosis were impaired by blocking the PI3K/AKT/mTOR pathway with LY294002. We hypothesize that CLEC5A is of vital importance to GC initiation and progression via the PI3K/AKT/mTOR pathway, and that our results might represent promising therapeutic strategies for GC patients.

Umbilical cord-derived mesenchymal stromal/stem cells expressing IL-24 induce apoptosis in gliomas

Although much progress has been made in the treatment of gliomas, the prognosis for patients with gliomas is still very poor. Stem cell-based therapies may be promising options for glioma treatment. Recently, many studies have reported that umbilical cord-derived mesenchymal stromal/stem cells (UC-MSCs) are ideal gene vehicles for tumor gene therapy. Interleukin 24 (IL-24) is a pleiotropic immunoregulatory cytokine that has an apoptotic effect on many kinds of tumor cells and can inhibit the growth of tumors specifically without damaging normal cells. In this study, we investigated UC-MSCs as a vehicle for the targeted delivery of IL-24 to tumor sites. UC-MSCs were transduced with lentiviral vectors carrying green fluorescent protein (GFP) or IL-24 complementary DNA. The results indicated that UC-MSCs could selectively migrate to glioma cells in vitro and in vivo. Injection of IL-24-UC-MSCs significantly suppressed tumor growth of glioma xenografts. The restrictive efficacy of IL-24-UC-MSCs was associated with the inhibition of proliferation as well as the induction of apoptosis in tumor cells. These findings indicate that UC-MSC-based IL-24 gene therapy may be able to suppress the growth of glioma xenografts, thereby suggesting possible future therapeutic use in the treatment of gliomas.

C-type lectin domain family 5, member A (CLEC5A, MDL-1) promotes brain glioblastoma tumorigenesis by regulating PI3K/Akt signalling

OBJECTIVES

Glioblastoma is the most common malignant glioma of all brain tumours. It is difficult to treat because of its poor response to chemotherapy and radiotherapy and high recurrence rate after treatment. The aetiology of glioblastoma is a result of disorders of multiple factors. Depending on cell signal transduction, these glioblastoma-associated factors lead to cell proliferation, differentiation and apoptosis. Therefore, investigation of the potential factors which involved in the development of glioblastoma could provide a new target for the treatment of glioblastoma.

MATERIALS AND METHODS

We analysed the transcript expression of CLEC5A in glioblastoma by accessing The Cancer Genome Atlas (TCGA). qRT-PCR was performed to detect the RNA expression of genes in cells and tissues, and Western blot was used to measure the protein levels (Cyclin D1, Bcl-2, BAX, PCNA, MMP2, MMP9, Akt and Akt phosphorylation) in tissues and cells. Cell proliferation, migration, invasion, cycle and apoptosis were measured by CCK-8, transwell and flow cytometry assays, respectively. Ki67 level and lung metastasis were determined by immunochemistry and H&E staining.

RESULTS

In this study, we found that CLEC5A was highly upregulated in glioblastoma compared to normal brain tissues, which had an opposite relation with the overall patient survival. Downregulation of CLEC5A could inhibit cell proliferation, migration and invasion via promoting apoptosis and G1 arrest. In contrast, overexpression of CLEC5A stimulated cell proliferation, migration and invasion. In addition, we found that CLEC5A level was positively correlated with Akt phosphorylation level. Akt inhibitor or agonist could reverse the modulation effects of CLEC5A in glioblastoma. Moreover, In vivo results suggested that inhibition of CLEC5A significantly reduced tumour size, weight, cell proliferation ability and lung metastasis via inhibition of phosphorylation Akt.

CONCLUSION

Both in vitro and in vivo evidences supported that CLEC5A was involved in glioblastoma pathogenesis via regulation of PI3K/Akt pathway. Thus, CLEC5A might serve as a potential therapeutic target in the treatment of glioblastoma in the future.

A Risk Classification System With Five-Gene for Survival Prediction of Glioblastoma Patients

Objective: Glioblastoma (GBM) is the most common and fatal primary brain tumor in adults. It is necessary to identify novel and effective biomarkers or risk signatures for GBM patients. Methods: Differentially expressed genes (DEGs) between GBM and low-grade glioma (LGG) in TCGA samples were screened out and weight correlation network analysis (WGCNA) was performed to confirm WHO grade-related genes. Five genes were selected via multivariate Cox proportional hazards regression analysis and were used to construct a risk signature. A nomogram composed of the risk signature and clinical characters (age, radiotherapy, and chemotherapy experience) was established to predict 1, 3, 5-year survival rate for GBM patients. Results: One hundred ninety-four DEGs in blue gene module were found to be positively related to WHO grade via WGCNA. Five genes (DES, RANBP17, CLEC5A, HOXC11, POSTN) were selected to construct a risk signature for GBM via R language. This risk signature was identified to independently predict the outcome of GBM patients, as well as stratified by IDH1 status, MGMT promoter status, and radio-chemotherapy. The nomogram was established which combined the risk signature with clinical factors. The results of c-index, ROC curve and calibration plot revealed the nomogram showing a good accuracy for predicting 1, 3, or 5-year survival of GBM patients. Conclusion: The risk signature with five genes could serve as an independent factor for predicting the prognosis of patients with GBM. Moreover, the nomogram with the risk signature and clinical traits proved to perform better for predicting 1, 3, 5-year survival rate.