Integrated Analysis Reveals Prognostic Value and Immune Correlates of CD86 Expression in Lower Grade Glioma

Focusing on tumor and it's microenvironmental immune members for head and neck cancer patients

OBJECTIVE

Immune-related gene expression levels in the tumor microenvironment (TM) of head and neck squamous cell carcinoma (HNSCC) patients was compared.

MATERIALS AND METHODS

The CD163, CD274, CD86, FUT4, FOXP3, and ITGAX levels of HNSCC patients in their tumor tissues (n =76) and surrounding tissues adjacent to the tumor (n =76) were determined using quantitative real-time PCR (qRT-PCR). Changes in these genes were also evaluated by associating with demographical data of the patients.

RESULTS

CD163, CD274, FUT4, and FOXP3 gene expression levels were significantly higher in tumor tissue than in surrounding tissue. FUT4 fold change was statistically higher in patients with lymph node involvement. CD86 expression was statistically lower in smokers of 50 boxes per year or more. CD163, CD274, and FUT4 expressions were increased in response to the presence of extranodal extension (ENE).

CONCLUSIONS

These preliminary results demonstrate the alterations in expression levels of immunologic markers are associated with the clinical presentations of HNSCC.

AVAILABILITY OF DATA AND MATERIALS

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

Based on scRNA-seq and bulk RNA-seq to establish tumor immune microenvironment-associated signature of skin melanoma and predict immunotherapy response

Skin cutaneous melanoma (SKCM), a form of skin cancer, ranks among the most formidable and lethal malignancies. Exploring tumor microenvironment (TME)-based prognostic indicators would help improve the efficacy of immunotherapy for SKCM patients. This study analyzed SKCM scRNA-seq data to cluster non-malignant cells that could be used to explore the TME into nine immune/stromal cell types, including B cells, CD4 T cells, CD8 T cells, dendritic cells, endothelial cells, Fibroblasts, macrophages, neurons, and natural killer (NK) cells. Using data from The Cancer Genome Atlas (TCGA), we employed SKCM expression profiling to identify differentially expressed immune-associated genes (DEIAGs), which were then incorporated into weighted gene co-expression network analysis (WGCNA) to investigate TME-associated hub genes. Discover candidate small molecule drugs based on pivotal genes. Tumor immune microenvironment-associated genes (TIMAGs) for constructing TIMAS were identified and validated. Finally, the characteristics of TIAMS subgroups and the ability of TIMAS to predict immunotherapy outcomes were analyzed. We identified five TIMAGs (CD86, CD80, SEMA4D, C1QA, and IRF1) and used them to construct TIMAS. In addition, five potential SKCM drugs were identified. The results showed that TIMAS-low patients were associated with immune-related signaling pathways, high MUC16 mutation frequency, high T cell infiltration, and M1 macrophages, and were more favorable for immunotherapy. Collectively, TIMAS constructed by comprehensive analysis of scRNA-seq and bulk RNA-seq data is a promising marker for predicting ICI treatment outcomes and improving individualized therapy for SKCM patients.

Integrative analysis of metabolism subtypes and identification of prognostic metabolism-related genes for glioblastoma

Increasing evidence has demonstrated that cancer cell metabolism is a critical factor in tumor development and progression; however, its role in glioblastoma (GBM) remains limited. In the present study, we classified GBM into three metabolism subtypes (MC1, MC2, and MC3) through cluster analysis of 153 GBM samples from the RNA-sequencing data of The Cancer Genome Atlas (TCGA) based on 2752 metabolism-related genes (MRGs). We further explored the prognostic value, metabolic signatures, immune infiltration, and immunotherapy sensitivity of the three metabolism subtypes. Moreover, the metabolism scoring model was established to quantify the different metabolic characteristics of the patients. Results showed that MC3, which is associated with a favorable survival outcome, had higher proportions of isocitrate dehydrogenase (IDH) mutations and lower tumor purity and proliferation. The MC1 subtype, which is associated with the worst prognosis, shows a higher number of segments and homologous recombination defects and significantly lower mRNA expression-based stemness index (mRNAsi) and epigenetic-regulation-based mRNAsi. The MC2 subtype has the highest T-cell exclusion score, indicating a high likelihood of immune escape. The results were validated using an independent dataset. Five MRGs (ACSL1, NDUFA2, CYP1B1, SLC11A1, and COX6B1) correlated with survival outcomes were identified based on metabolism-related co-expression module analysis. Laboratory-based validation tests further showed the expression of these MRGs in GBM tissues and how their expression influences cell function. The results provide a reference for developing clinical management approaches and treatments for GBM.

Integrated analysis reveals the potential of cluster of differentiation 86 as a key biomarker in high-grade glioma

This study aimed to evaluate the potential of cluster of differentiation 86 (CD86) as a biomarker in high-grade glioma (HGG). The TCGA and TCIA databases were used to obtain the CD86 expression value, clinical data, and MRI images of HGG patients. Prognostic values were assessed by the Kaplan-Meier method, Receiver operating characteristic curve (ROC), Cox regression, logistic regression, and nomogram analyses. CD86-associated pathways were also explored. We found that CD86 was significantly upregulated in HGG compared with the normal group. Survival analysis showed a significant association between CD86 high expression and shorter overall survival time. Its independent prognostic value was also confirmed. These results suggested the possibility of CD86 as a biomarker in HGG. We also innovatively established 2 radiomics models with Support Vector Machine (SVM) and Logistic regression (LR) algorithms to predict the CD86 expression. The 2 models containing 5 optimal features by SVM and LR methods showed similar favorable performance in predicting CD86 expression in the training set, and their performance were also confirmed in validation set. These results indicated the successful construction of a radiomics model for non-invasively predicting biomarker in HGG. Finally, pathway analysis indicated that CD86 might be involved in the natural killer cell-mediated cytotoxicity in HGG progression.

Medical gas plasma technology: Roadmap on cancer treatment and immunotherapy

Despite continuous therapeutic progress, cancer remains an often fatal disease. In the early 2010s, first evidence in rodent models suggested promising antitumor action of gas plasma technology. Medical gas plasma is a partially ionized gas depositing multiple physico-chemical effectors onto tissues, especially reactive oxygen and nitrogen species (ROS/RNS). Today, an evergrowing body of experimental evidence suggests multifaceted roles of medical gas plasma-derived therapeutic ROS/RNS in targeting cancer alone or in combination with oncological treatment schemes such as ionizing radiation, chemotherapy, and immunotherapy. Intriguingly, gas plasma technology was recently unraveled to have an immunological dimension by inducing immunogenic cell death, which could ultimately promote existing cancer immunotherapies via in situ or autologous tumor vaccine schemes. Together with first clinical evidence reporting beneficial effects in cancer patients following gas plasma therapy, it is time to summarize the main concepts along with the chances and limitations of medical gas plasma onco-therapy from a biological, immunological, clinical, and technological point of view.

Expression and Prognostic Value of CD80 and CD86 in the Tumor Microenvironment of Newly Diagnosed Glioblastoma

BACKGROUND

Strategies to modulate the tumor microenvironment (TME) have opened new therapeutic avenues with dramatic yet heterogeneous intertumoral efficacy in multiple cancers, including glioblastomas (GBMs). Therefore, investigating molecular actors of TME may help understand the interactions between tumor cells and TME. Immune checkpoint proteins such as a Cluster of Differentiation 80 (CD80) and CD86 are expressed on the surface of tumor cells and infiltrative tumor lymphocytes. However, their expression and prognostic value in GBM microenvironment are still unclear.

METHODS

In this study, we investigated, in a retrospective local discovery cohort and a validation TCGA dataset, expression of CD80 and CD86 at mRNA level and their prognostic significance in response to standard of care. Furthermore, CD80 and CD86 at the protein level were investigated in the discovery cohort.

RESULTS

Both CD80 and CD86 are expressed heterogeneously in the TME at mRNA and protein levels. In a univariate analysis, the mRNA expression of CD80 and CD86 was not significantly correlated with OS in both local OncoNeuroTek dataset and TCGA datasets. CD80 and CD86 mRNA high expression was significantly associated with shorter progression free survival (PFS) (p < 0.05). These findings were validated using the TCGA cohort; higher CD80 and CD86 expressions were correlated with shorter PFS (p < 0.05). In multivariate analysis, CD86 mRNA expression was an independent prognostic factor for PFS in the TCGA dataset only (p < 0.05).

CONCLUSION

CD86 could be used as a potential biomarker for the prognosis of GBM patients treated with immunotherapy; however, additional studies are needed to validate these findings.

The Importance of the Immune System and Molecular Cell Signaling Pathways in the Pathogenesis and Progression of Lung Cancer

Lung cancer is a disease that in recent years has become one of the greatest threats to modern society. Every year there are more and more new cases and the percentage of deaths caused by this type of cancer increases. Despite many studies, scientists are still looking for answers regarding the mechanisms of lung cancer development and progression, with particular emphasis on the role of the immune system. The aim of this literature review was to present the importance of disorders of the immune system and the accompanying changes at the level of cell signaling in the pathogenesis of lung cancer. The collected results showed that in the process of immunopathogenesis of almost all subtypes of lung cancer, changes in the tumor microenvironment, deregulation of immune checkpoints and abnormalities in cell signaling pathways are involved, which contribute to the multistage and multifaceted carcinogenesis of this type of cancer. We, therefore, suggest that in future studies, researchers should focus on a detailed analysis of tumor microenvironmental immune checkpoints, and to validate their validity, perform genetic polymorphism analyses in a wide range of patients and healthy individuals to determine the genetic susceptibility to lung cancer development. In addition, further research related to the analysis of the tumor microenvironment; immune system disorders, with a particular emphasis on immunological checkpoints and genetic differences may contribute to the development of new personalized therapies that improve the prognosis of patients.

A New Potential Therapeutic Target for Cancer in Ubiquitin-Like Proteins-UBL3

Ubiquitin-like proteins (Ubls) are involved in a variety of biological processes through the modification of proteins. Dysregulation of Ubl modifications is associated with various diseases, especially cancer. Ubiquitin-like protein 3 (UBL3), a type of Ubl, was revealed to be a key factor in the process of small extracellular vesicle (sEV) protein sorting and major histocompatibility complex class II ubiquitination. A variety of sEV proteins that affects cancer properties has been found to interact with UBL3. An increasing number of studies has implied that UBL3 expression affects cancer cell growth and cancer prognosis. In this review, we provide an overview of the relationship between various Ubls and cancers. We mainly introduce UBL3 and its functions and summarize the current findings of UBL3 and examine its potential as a therapeutic target in cancers.

An in silico approach to the identification of diagnostic and prognostic markers in low-grade gliomas

Low-grade gliomas (LGG) are central nervous system Grade I tumors, and as they progress they are becoming one of the deadliest brain tumors. There is still great need for timely and accurate diagnosis and prognosis of LGG. Herein, we aimed to identify diagnostic and prognostic biomarkers associated with LGG, by employing diverse computational approaches. For this purpose, differential gene expression analysis on high-throughput transcriptomics data of LGG versus corresponding healthy brain tissue, derived from TCGA and GTEx, respectively, was performed. Weighted gene co-expression network analysis of the detected differentially expressed genes was carried out in order to identify modules of co-expressed genes significantly correlated with LGG clinical traits. The genes comprising these modules were further used to construct gene co-expression and protein-protein interaction networks. Based on the network analyses, we derived a consensus of eighteen hub genes, namely, CD74, CD86, CDC25A, CYBB, HLA-DMA, ITGB2, KIF11, KIFC1, LAPTM5, LMNB1, MKI67, NCKAP1L, NUSAP1, SLC7A7, TBXAS1, TOP2A, TYROBP, and WDFY4. All detected hub genes were up-regulated in LGG, and were also associated with unfavorable prognosis in LGG patients. The findings of this study could be applicable in the clinical setting for diagnosing and monitoring LGG.

Integrative pan-cancer landscape of MMS22L and its potential role in hepatocellular carcinoma

Methyl methanesulfonate-sensitivity protein 22-like (MMS22L) is crucial in protecting genome integrity during DNA replication by preventing DNA damage and maintaining efficient homologous recombination. However, the role of MMS22L in human cancers remains unclear. Here, we reported the landscape of MMS22L using multi-omics data and identified the relationship between the MMS22L status and pan-cancer prognosis. In addition, the correlation of MMS22L mRNA expression levels with tumor mutational burden, microsatellite instability, homologous recombination deficiency, and loss of heterozygosity in pan-cancer was also described in this study. Furthermore, this study was the first to characterize the relationship between mRNA expression of MMS22L and immune cell infiltration in the tumor microenvironment in human cancer. Concurrently, this study explored the crucial role of MMS22L in different immunotherapy cohorts through current immunotherapy experiments. Eventually, we investigated the role of MMS22L in hepatocellular carcinoma (HCC). The results demonstrated that MMS22L is widely expressed in multiple HCC cell lines, and our results emphasized that MMS22L was involved in HCC progression and affects the prognosis of patients with HCC through multiple independent validation cohorts. Collectively, our findings reveal the essential role of MMS22L as a tumor-regulating gene in human cancers while further emphasizing its feasibility as a novel molecular marker in HCC. These findings provide an essential reference for the study of MMS22L in tumors.

The Identification of Necroptosis-Related Subtypes, the Construction of a Prognostic Model, and the Characterization of the Tumor Microenvironment in Gliomas

Necroptosis is a recently discovered form of cell death that plays a vital role in the progression of cancer, the spread of metastases, and the immunologic response to tumors. Due to the dual role of necrotic apoptotic processes in tumor pathogenesis and the heterogeneity of gliomas, the function of necroptosis in the glioma microenvironment is still poorly understood. We characterized the expression of necroptosis-related genes (NRGs) within glioma samples at both the genetic and transcriptional levels, identifying three distinct subtypes. Additionally, we constructed a risk score, which is capable of accurately predicting patient prognosis, correlates with tumor mutation burden (TMB), tumor stem cell index (CSC), immune checkpoints, and predicts tumor drug sensitivity. To facilitate its application in the clinic, we developed a nomogram and demonstrated that it predicts the prognosis of glioma patients with good accuracy and reliability using multiple datasets. We examined the function of necroptosis in the tumor microenvironment (TME) and the prognosis of gliomas, which may be useful for guiding individualized treatment plans for gliomas targeting necroptosis.

Development and validation of a leukocyte-associated immunoglobulin-like receptor-1 prognostic signature for lower-grade gliomas

OBJECTIVE

Leukocyte-associated immunoglobulin-like receptor-1 (LAIR-1), is an immunosuppressive receptor, widely expressed by immune cells, but the part of LAIR-1 in glioma progression remains unclear. The purpose of this study was to explore the relationship between LAIR-1 expression and the development of lower-grade glioma (LGG) using publicly available data sets.

METHODS

We took advantage of The Cancer Genome Atlas (TCGA) to analyze the expression of LAIR-1 in patients with LGG. Second, Kaplan-Meier methods and univariate and multivariate Cox regression analyses were used to examine the clinical significance of LAIR-1 expression in combination with CGGA databases, and then receiver operating characteristic curve analysis was used to verify the prognostic utility of LAIR-1. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis (GSEA) were used to explore the function of LAIR-1. Analysis of the correlation with immune infiltration was conducted using the ESTIMATE algorithm and single sample gene set enrichment analysis.

RESULTS

Our results showed that LAIR-1 expression to be positively correlated with malignant clinicopathologic features of LGG. Univariate analysis and multivariate analysis revealed that overexpression of LAIR-1 was correlated with a worse prognosis in patients. A nomogram model combining LAIR-1 was more useful in guiding clinical diagnosis, and functional enrichment analysis showed that malignant development of glioma was closely affiliated with the tumor immune microenvironment.

CONCLUSION

These results indicate that LAIR 1 is a latent marker for determining the prognosis of LGG patients. LAIR 1 may also participate a critical part in TIME of LGG by regulating the infiltration of immune cells, suggesting that LAIR 1 might be used as a therapeutic target to regulate the antitumor immune response.

Integrated analysis reveals prognostic value and mesenchymal identity suppression by glycoprotein M6B in glioma

Glioblastoma (GBM) stem cells (GSCs) possess multilineage differentiation potential, which is responsible for cancer progression. Glycoprotein M6B (GPM6B) is a pivotal enzyme in regulating intracranial cell differentiation and neuronal myelination, and is widely studied in several cancers. However, research on GPM6B in glioma is limited. In this study, we analyzed the clinical and molecular characteristics of GPM6B using RNA sequencing data of glioma samples from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) datasets. Quantitative real-time PCR (qRT-PCR), western blot (WB), and immunohistochemistry (IHC) were performed for further validation. Moreover, a neurosphere formation assay, extreme limiting dilution assay, and bioluminescent imaging were employed to validate the therapeutic effects targeted on GPM6B in vitro and in vivo. We found lower expression of GPM6B in aggressive glioma. Receiver operating characteristic (ROC) analysis suggested that GPM6B is an indicator of mesenchymal subtype. Kaplan-Meier analysis also revealed that patients with glioma with high GPM6B expression levels had a tendency toward prolonged survival. The GPM6B expression level could predict favorable prognosis of patients independent of age, grade, IDH status, and 1p/19q status. Additionally, targeting GPM6B impaired the self-renewal and tumorgenicity of mesenchymal GSCs by inhibiting the activation of the Wnt pathway in vitro and in vivo. Our results demonstrated that GPM6B is a crucial predictor in glioma prognosis and represents an underlying therapeutic target in GSC therapy.

An Integrative Bioinformatics Analysis of the Potential Mechanisms Involved in Propofol Affecting Hippocampal Neuronal Cells

The aim of this study is to probe the possible molecular mechanisms underlying the effects of propofol on HT22 cells. HT22 cells treated with different concentrations were sequenced, and then the results of the sequencing were analyzed for dynamic trends. Expression pattern clustering analysis was performed to demonstrate the expression of genes in the significant trend modules in each group of samples. We first chose the genes related to the trend module for WGCNA analysis, then constructed the PPI network of module genes related to propofol treatment group, and screened the key genes. Finally, GSEA analysis was performed on the key genes. Overall, 2,506 genes showed a decreasing trend with increasing propofol concentration, and 1,871 genes showed an increasing trend with increasing propofol concentration. WGCNA analysis showed that among them, turquoise panel genes were negatively correlated with propofol treatment, and genes with Cor R >0.9 in the turquoise panel were selected for PPI network construction. The MCC algorithm screened a total of five key genes (CD86, IL10RA, PTPRC, SPI1, and ITGAM). GSEA analysis showed that CD86, IL10RA, PTPRC, SPI1, and ITGAM are involved in the PRION_DISEASES pathway. Our study showed that propofol sedation can affect mRNA expression in the hippocampus, providing new ideas to identify treatment of nerve injury induced by propofol anesthesia.

Ferroptosis-Related Gene Contributes to Immunity, Stemness and Predicts Prognosis in Glioblastoma Multiforme

Ferroptosis, a recently discovered regulated programmed cell death, is associated with tumorigenesis and progression in glioblastoma. Based on widely recognized ferroptosis-related genes (FRGs), the regulation of ferroptosis patterns and corresponding characteristics of immune infiltration of 516 GBM samples with GSE13041, TCGA-GBM, and CGGA-325 were comprehensively analyzed. Here, we revealed the expression, mutations, and CNV of FRGs in GBM. We identified three distinct regulation patterns of ferroptosis and found the hub genes of immunity and stemness among DEGs in three patterns. A prognostic model was constructed based on five FRGs and verified at the mRNA and protein level. The risk score can not only predict the prognosis but also the degree of immune infiltration and ICB responsiveness by functional annotation. The overall assessment of FRGs in GBM patients will guide the direction of improved research and develop new prognostic prediction tools.

Patient-Derived Human Basal and Cutaneous Squamous Cell Carcinoma Tissues Display Apoptosis and Immunomodulation following Gas Plasma Exposure with a Certified Argon Jet

Reactive oxygen species (ROS) have been subject of increasing interest in the pathophysiology and therapy of cancers in recent years. In skin cancer, ROS are involved in UV-induced tumorigenesis and its targeted treatment via, e.g., photodynamic therapy. Another recent technology for topical ROS generation is cold physical plasma, a partially ionized gas expelling dozens of reactive species onto its treatment target. Gas plasma technology is accredited for its wound-healing abilities in Europe, and current clinical evidence suggests that it may have beneficial effects against actinic keratosis. Since the concept of hormesis dictates that low ROS levels perform signaling functions, while high ROS levels cause damage, we investigated herein the antitumor activity of gas plasma in non-melanoma skin cancer. In vitro, gas plasma exposure diminished the metabolic activity, preferentially in squamous cell carcinoma cell (SCC) lines compared to non-malignant HaCaT cells. In patient-derived basal cell carcinoma (BCC) and SCC samples treated with gas plasma ex vivo, increased apoptosis was found in both cancer types. Moreover, the immunomodulatory actions of gas plasma treatment were found affecting, e.g., the expression of CD86 and the number of regulatory T-cells. The supernatants of these ex vivo cultured tumors were quantitatively screened for cytokines, chemokines, and growth factors, identifying CCL5 and GM-CSF, molecules associated with skin cancer metastasis, to be markedly decreased. These findings suggest gas plasma treatment to be an interesting future technology for non-melanoma skin cancer topical therapy.

The CXCL Family Contributes to Immunosuppressive Microenvironment in Gliomas and Assists in Gliomas Chemotherapy

Gliomas are a type of malignant central nervous system tumor with poor prognosis. Molecular biomarkers of gliomas can predict glioma patient's clinical outcome, but their limitations are also emerging. C-X-C motif chemokine ligand family plays a critical role in shaping tumor immune landscape and modulating tumor progression, but its role in gliomas is elusive. In this work, samples of TCGA were treated as the training cohort, and as for validation cohort, two CGGA datasets, four datasets from GEO database, and our own clinical samples were enrolled. Consensus clustering analysis was first introduced to classify samples based on CXCL expression profile, and the support vector machine was applied to construct the cluster model in validation cohort based on training cohort. Next, the elastic net analysis was applied to calculate the risk score of each sample based on CXCL expression. High-risk samples associated with more malignant clinical features, worse survival outcome, and more complicated immune landscape than low-risk samples. Besides, higher immune checkpoint gene expression was also noticed in high-risk samples, suggesting CXCL may participate in tumor evasion from immune surveillance. Notably, high-risk samples also manifested higher chemotherapy resistance than low-risk samples. Therefore, we predicted potential compounds that target high-risk samples. Two novel drugs, LCL-161 and ADZ5582, were firstly identified as gliomas' potential compounds, and five compounds from PubChem database were filtered out. Taken together, we constructed a prognostic model based on CXCL expression, and predicted that CXCL may affect tumor progression by modulating tumor immune landscape and tumor immune escape. Novel potential compounds were also proposed, which may improve malignant glioma prognosis.