Immune-Related Gene SERPINE1 Is a Novel Biomarker for Diffuse Lower-Grade Gliomas via Large-Scale Analysis

HLTF/SERPINE1 Axis Plays a Crucial Pro-Oncogenic Role in the Progression from Cervical Precancerous Lesions to Cervical Carcinoma in vitro

OBJECTIVES

Cervical carcinoma (CC) is prevalent among women worldwide with increasing risk. Finding effective methods for treating CC is of utmost importance. The aim of this study was to investigate the effect of SERPINE1 on the progression of cervical precancerous lesions to CC.

DESIGN

This study used transcriptome sequencing and in vitro cell line. Participants/Materials: Cervical precancerous lesions and CC samples and human cervical epithelial immortalized cell line H8, human CC cell lines HeLa, and CaSki were involved in this study.

SETTING AND METHODS

Next-generation sequencing was applied to identify 100 differentially expressed genes from cervical precancerous lesions and CC samples. With the application of the Search Tool for the Retrieval of Interacting Genes (STRING) database, we carried out the protein-protein interaction network analysis, thus screening out serine protease inhibitor clade E member 1 (SERPINE1) with significant upregulation in CC cells. The helicase-like transcription factor (HLTF) was predicted as the upstream transcription factor using Human Transcription Factor Database (HumanTFDB). The chromatin immunoprecipitation (ChIP) experiment was conducted to validate the interaction between SERPINE1 and HLTF. The immunohistochemistry was employed to determine the expression of SERPINE1 and HLTF in CC tissues. Following the upregulation or downregulation of SERPINE1 and HLTF, the real-time quantitative reverse transcription polymerase chain reaction was carried out to assess mRNA expression levels of SERPINE1 and HLTF in cells. Cell viability, migration, and invasion were evaluated using MTT assay, cell scratch assay, and Transwell assay, respectively. Western blot analysis was conducted to assess changes in the expression levels of matrix metalloproteinases and proteins related to epithelial-mesenchymal transition (EMT).

RESULTS

The ChIP experiment confirmed the interaction between HLTF and SERPINE1. HLTF and SERPINE1 were upregulated in CC tissues and cells, and silencing SERPINE1 inhibited the EMT process and viability, migration, and invasion of CC cells. However, overexpression of SERPINE1 in CC cells showed the opposite trend. Rescue experiments demonstrated that silencing HLTF repressed CC cell viability, migration, and invasion, which could be restored by overexpressing SERPINE1.

LIMITATIONS

The effect of the HLTF/SERPINE1 axis on CC malignant progression has not been confirmed by in vivo experiments.

CONCLUSION

HLTF transcriptionally activates SERPINE1, promoting the progression from cervical precancerous lesions to CC.

Integrated pan-cancer and scRNA-seq analyses identify a prognostic coagulation-related gene signature associated with tumor microenvironment in lower-grade glioma

Cancer-associated thrombosis is a significant complication in cancer patients, leading to increased morbidity and mortality. The expression of coagulation/fibrinolysis genes, termed the "coagulome", plays a critical role in this process. Using the single-sample gene set enrichment analysis (ssGSEA), we identified seven cancer types with significantly activated coagulation pathways, focusing on lower-grade glioma (LGG) and stomach adenocarcinoma due to their predictive value for overall survival. Through 1000 iterations of the Least Absolute Shrinkage and Selection Operator (LASSO), we selected prognostic genes and constructed effective Cox regression models, particularly for LGG. Incorporating clinical characteristics, we constructed a nomogram for LGG, achieving an impressive area under the curve (AUCs) of 0.79, 0.82, and 0.81 at 1, 3, and 5 years in the test dataset, indicating strong potential for clinical application. Functional enrichment analysis between high-risk and low-risk LGG groups revealed significant enrichment of genes involved in the inflammatory response, interferon-gamma response, and epithelial-mesenchymal transition pathways. Combined with CIBERSORT and single-cell RNA sequencing analysis of LGG, our results demonstrated that the interplay between coagulation and the tumor microenvironment, particularly involving gliomas and myeloid cells, significantly influences tumor progression and patient outcomes.

Single-cell RNA sequencing analysis of vestibular schwannoma reveals functionally distinct macrophage subsets

BACKGROUND

Vestibular schwannomas (VSs) remain a challenge due to their anatomical location and propensity to growth. Macrophages are present in VS but their roles in VS pathogenesis remains unknown.

OBJECTIVES

The objective was to assess phenotypic and functional profile of macrophages in VS with single-cell RNA sequencing (scRNAseq).

METHODS

scRNAseq was carried out in three VS samples to examine characteristics of macrophages in the tumour. RT-qPCR was carried out on 10 VS samples for CD14, CD68 and CD163 and a panel of macrophage-associated molecules.

RESULTS

scRNAseq revealed macrophages to be a major constituent of VS microenvironment with three distinct subclusters based on gene expression. The subclusters were also defined by expression of CD163, CD68 and IL-1β. AREG and PLAUR were expressed in the CD68+CD163+IL-1β+ subcluster, PLCG2 and NCKAP5 were expressed in CD68+CD163+IL-1β- subcluster and AUTS2 and SPP1 were expressed in the CD68+CD163-IL-1β+ subcluster. RT-qPCR showed expression of several macrophage markers in VS of which CD14, ALOX15, Interleukin-1β, INHBA and Colony Stimulating Factor-1R were found to have a high correlation with tumour volume.

CONCLUSIONS

Macrophages form an important component of VS stroma. scRNAseq reveals three distinct subsets of macrophages in the VS tissue which may have differing roles in the pathogenesis of VS.

Phase 1 dose expansion and biomarker study assessing first-in-class tumor microenvironment modulator VT1021 in patients with advanced solid tumors

BACKGROUND

Preclinical studies have demonstrated that VT1021, a first-in-class therapeutic agent, inhibits tumor growth via stimulation of thrombospondin-1 (TSP-1) and reprograms the tumor microenvironment. We recently reported data from the dose escalation part of a phase I study of VT1021 in solid tumors. Here, we report findings from the dose expansion phase of the same study.

METHODS

We analyzed the safety and tolerability, clinical response, and biomarker profile of VT1021 in the expansion portion of the phase I study (NCT03364400). Safety/tolerability is determined by adverse events related to the treatment. Clinical response is determined by RECIST v1.1 and iRECIST. Biomarkers are measured by multiplexed ion beam imaging and enzyme-linked immunoassay (ELISA).

RESULTS

First, we report the safety and tolerability data as the primary outcome of this study. Adverse events (AE) suspected to be related to the study treatment (RTEAEs) are mostly grade 1-2. There are no grade 4 or 5 adverse events. VT1021 is safe and well tolerated in patients with solid tumors in this study. We report clinical responses as a secondary efficacy outcome. VT1021 demonstrates promising single-agent clinical activity in recurrent GBM (rGBM) in this study. Among 22 patients with rGBM, the overall disease control rate (DCR) is 45% (95% confidence interval, 0.24-0.67). Finally, we report the exploratory outcomes of this study. We show the clinical confirmation of TSP-1 induction and TME remodeling by VT1021. Our biomarker analysis identifies several plasmatic cytokines as potential biomarkers for future clinical studies.

CONCLUSIONS

VT1021 is safe and well-tolerated in patients with solid tumors in a phase I expansion study. VT1021 has advanced to a phase II/III clinical study in glioblastoma (NCT03970447).

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.

TGF-β Score based on Silico Analysis can Robustly Predict Prognosis and Immunological Characteristics in Lower-grade Glioma: The Evidence from Multicenter Studies

INTRODUCTION

Nowadays, mounting evidence shows that variations in TGF-β signaling pathway-related components influence tumor development. Current research has patents describing the use of anti-TGF-β antibodies and checkpoint inhibitors for the treatment of proliferative diseases. Importantly, TGF-β signaling pathway is significant for lower-grade glioma (LGG) to evade host immunity. Loss of particular tumor antigens and shutdown of professional antigenpresenting cell activity may render the anti-tumor response ineffective in LGG patients. However, the prognostic significance of TGF-β related genes in LGG is still unknown.

METHODS

We collected RNA-seq data from the GTEx database (normal cortical tissues), the Cancer Genome Atlas database (TCGA-LGG), and the Chinese Glioma Genome Atlas database (CGGA-693 and CGGA-325) for conducting our investigation.

RESULTS

In addition, previous publications were explored for the 223 regulators of the TGF-β signaling pathway, and 30 regulators with abnormal expression in TCGA and GTEx database were identified. In order to identify hub prognostic regulators, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis were used to screen from differentially expressed genes (DEGs). On the basis of 11 genes from LASSO-Cox regression analysis (NEDD8, CHRD, TGFBR1, TP53, BMP2, LRRC32, THBS2, ID1, NOG, TNF, and SERPINE1), TGF-β score was calculated. Multiple statistical approaches verified the predictive value of the TGF-β score for the training cohort and two external validation cohorts. Considering the importance of the TGF-β signaling pathway in immune regulation, we evaluated the prediction of the TGF-β score for immunological characteristics and the possible application of the immunotherapeutic response using six algorithms (TIMER, CIBERSORT, QUANTISEQ, MCP-counter, XCELL and EPIC) and three immunotherapy cohorts (GSE78820, Imvigor-210 and PRJEB23709). Notably, we compared our risk signature with the signature in ten publications in the meta-cohort (TCGA-LGG, CGGA-693 and CGGA-325), and the TGF-β score had the best predictive efficiency (C-index =0.812).

CONCLUSION

In conclusion, our findings suggest that TGF-β signaling pathway-related signatures are prognostic biomarkers in LGG and provide a novel tool for tumor microenvironment (TME) assessment.

SigPrimedNet: A Signaling-Informed Neural Network for scRNA-seq Annotation of Known and Unknown Cell Types

Single-cell RNA sequencing is increasing our understanding of the behavior of complex tissues or organs, by providing unprecedented details on the complex cell type landscape at the level of individual cells. Cell type definition and functional annotation are key steps to understanding the molecular processes behind the underlying cellular communication machinery. However, the exponential growth of scRNA-seq data has made the task of manually annotating cells unfeasible, due not only to an unparalleled resolution of the technology but to an ever-increasing heterogeneity of the data. Many supervised and unsupervised methods have been proposed to automatically annotate cells. Supervised approaches for cell-type annotation outperform unsupervised methods except when new (unknown) cell types are present. Here, we introduce SigPrimedNet an artificial neural network approach that leverages (i) efficient training by means of a sparsity-inducing signaling circuits-informed layer, (ii) feature representation learning through supervised training, and (iii) unknown cell-type identification by fitting an anomaly detection method on the learned representation. We show that SigPrimedNet can efficiently annotate known cell types while keeping a low false-positive rate for unseen cells across a set of publicly available datasets. In addition, the learned representation acts as a proxy for signaling circuit activity measurements, which provide useful estimations of the cell functionalities.

Senescence-related genes define prognosis, immune contexture, and pharmacological response in gastric cancer

As one of the prevalent tumors worldwide, gastric cancer (GC) has obtained sufficient attention in its clinical management and prognostic stratification. Senescence-related genes are involved in the tumorigenesis and progression of GC. A machine learning algorithm-based prognostic signature was developed from six senescence-related genes including SERPINE1, FEN1, PDGFRB, SNCG, TCF3, and APOC3. The TCGA-STAD cohort was utilized as a training set while the GSE84437 and GSE13861 cohorts were analyzed for validation. Immune cell infiltration and immunotherapy efficacy were investigated in the PRJEB25780 cohort. Data from the genomics of drug sensitivity in cancer (GDSC) database revealed pharmacological response. The GSE13861 and GSE54129 cohorts, single-cell dataset GSE134520, and The Human Protein Atlas (THPA) database were utilized for localization of the key senescence-related genes. Association of a higher risk-score with worse overall survival (OS) was identified in the training cohort (TCGA-STAD, P<0.001; HR = 2.03, 95% CI, 1.45-2.84) and the validation cohorts (GSE84437, P = 0.005; HR = 1.48, 95% CI, 1.16-1.95; GSE13861, P = 0.03; HR = 2.23, 95% CI, 1.07-4.62). The risk-score was positively correlated with densities of tumor-infiltrating immunosuppressive cells (P < 0.05) and was lower in patients who responded to pembrolizumab monotherapy (P = 0.03). Besides, patients with a high risk-score had higher sensitivities to the inhibitors against the PI3K-mTOR and angiogenesis (P < 0.05). Expression analysis verified the promoting roles of FEN1, PDGFRB, SERPINE1, and TCF3, and the suppressing roles of APOC3 and SNCG in GC, respectively. Immunohistochemistry staining and single-cell analysis revealed their location and potential origins. Taken together, the senescence gene-based model may potentially change the management of GC by enabling risk stratification and predicting response to systemic therapy.

Identification of three metabolic subtypes in gastric cancer and the construction of a metabolic pathway-based risk model that predicts the overall survival of GC patients

Gastric cancer (GC) is highly heterogeneous and GC patients have low overall survival rates. It is also challenging to predict the prognosis of GC patients. This is partly because little is known about the prognosis-related metabolic pathways in this disease. Hence, our objective was to identify GC subtypes and genes related to prognosis, based on changes in the activity of core metabolic pathways in GC tumor samples. Differences in the activity of metabolic pathways in GC patients were analyzed using Gene Set Variation Analysis (GSVA), leading to the identification of three clinical subtypes by non-negative matrix factorization (NMF). Based on our analysis, subtype 1 showed the best prognosis while subtype 3 exhibited the worst prognosis. Interestingly, we observed marked differences in gene expression between the three subtypes, through which we identified a new evolutionary driver gene, CNBD1. Furthermore, we used 11 metabolism-associated genes identified by LASSO and random forest algorithms to construct a prognostic model and verified our results using qRT-PCR (five matched clinical tissues of GC patients). This model was found to be both effective and robust in the GSE84437 and GSE26253 cohorts, and the results from multivariate Cox regression analyses confirmed that the 11-gene signature was an independent prognostic predictor (p < 0.0001, HR = 2.8, 95% CI 2.1-3.7). The signature was found to be relevant to the infiltration of tumor-associated immune cells. In conclusion, our work identified significant GC prognosis-related metabolic pathways in different GC subtypes and provided new insights into GC-subtype prognostic assessment.

MCM4 is a novel prognostic biomarker and promotes cancer cell growth in glioma

BACKGROUND

Gliomas account for 75% of all primary malignant brain tumors in adults and result in high mortality. Accumulated evidence has declared the minichromosome maintenance protein complex (MCM) gene family plays a critical role in modulating the cell cycle and DNA replication stress. However, the biological function and clinic characterization of nine MCM members in low-grade glioma are not yet clarified.

METHODS

In this study, we utilized diverse public databases, including The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), Rembrandt, Human Protein Atlas (HPA), Linkedomics, cbioportal, Tumor and Immune System Interaction Database (TISIDB), single-sample GSEA (ssGSEA), Tumor Immune Estimation Resource (TIMER), Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Therapeutics Response Portal databases to explore the mRNA and protein expression profiles, gene mutation, clinical features, diagnosis, prognosis, signaling pathway, tumor mutational burden (TMB), immune subtype, immune cell infiltration, immune modulator and drug sensitivity of nine MCMs. Afterward, qRT-PCR was utilized to detect the expression of the MCM family in glioblastoma multiforme (GBM) cell lines. The one-, three-, or five-year survival rate was predicted by utilizing a nomogram established by cox proportional hazard regression.

RESULTS

In this study, we found that nine MCMs were consistently up-regulated in glioma tissues and glioma cell lines. Elevated nine MCMs expressions were significantly correlated with a higher tumor stage, isocitrate dehydrogenase (IDH) mutates, 1p/19q codeletion, histological type, and primary therapy outcome. Survival analyses showed that higher expression of MCM2-MCM8 (minichromosome maintenance protein2-8) and MCM10 (minichromosome maintenance protein 10) were linked with poor overall survival (OS) and progression-free survival (PFS) in glioma patients. On the other hand, up-regulated MCM2-MCM8 and MCM10 were significantly associated with shorter disease-specific survival (DSS) in glioma patients. Univariate and multivariate analyses revealed that MCM2 (minichromosome maintenance protein2), MCM4 (minichromosome maintenance protein 4), MCM6 (minichromosome maintenance protein 6), MCM7 (minichromosome maintenance protein 7) expression and tumor grade, 1p/19q codeletion, age, and primary therapy outcome were independent factors correlated with the clinical outcome of glioma patients. More importantly, a prognostic MCMs model constructed using the above five prognostic genes could predict the overall survival of glioma patients with medium-to-high accuracy. Furthermore, functional enrichment analysis indicated that MCMs principal participated in regulating cell cycle and DNA replication. DNA copy number variation (CNV) and DNA methylation significantly affect the expression of MCMs. Finally, we uncover that MCMs expression is highly correlated with immune cell infiltration, immune modulator, TMB, and drug sensitivity.

CONCLUSIONS

In summary, this finding confirmed that MCM4 is a potential target of precision therapy for patients with glioma.

A novel necroptosis-related gene index for predicting prognosis and a cold tumor immune microenvironment in stomach adenocarcinoma

Background

Gastric cancer (GC) represents a major global clinical problem with very limited therapeutic options and poor prognosis. Necroptosis, a recently discovered inflammatory form of cell death, has been implicated in carcinogenesis and inducing necroptosis has also been considered as a therapeutic strategy.

Objective

We aim to evaluate the role of this pathway in gastric cancer development, prognosis and immune aspects of its tumor microenvironment.

Methods and results

In this study, we evaluated the gene expression of 55 necroptosis-related genes (NRGs) that were identified via carrying out a comprehensive review of the medical literature. Necroptosis pathway was deregulated in gastric cancer samples (n=375) as compared to adjacent normal tissues (n=32) obtained from the “The Cancer Genome Atlas (TCGA)”. Based on the expression of these NRGs, two molecular subtypes were obtained through consensus clustering that also showed significant prognostic difference. Differentially expressed genes between these two clusters were retrieved and subjected to prognostic evaluation via univariate cox regression analysis and LASSO cox regression analysis. A 13-gene risk signature, termed as necroptosis-related genes prognostic index (NRGPI), was constructed that comprehensively differentiated the gastric cancer patients into high- and low-risk subgroups. The prognostic significance of NRGPI was validated in the GEO cohort (GSE84437: n=408). The NRGPI-high subgroup was characterized by upregulation of 10 genes (CYTL1, PLCL1, CGB5, CNTN1, GRP, APOD, CST6, GPX3, FCN1, SERPINE1) and downregulation of 3 genes (EFNA3, E2F2, SOX14). Further dissection of these two risk groups by differential gene expression analysis indicated involvement of signaling pathways associated with cancer cell progression and immune suppression such as WNT and TGF-β signaling pathway. Para-inflammation and type-II interferon pathways were activated in NRGPI-high patients with an increased infiltration of Tregs and M2 macrophage indicating an exhausted immune phenotype of the tumor microenvironment. These molecular characteristics were mainly driven by the eight NRGPI oncogenes (CYTL1, PLCL1, CNTN1, GRP, APOD, GPX3, FCN1, SERPINE1) as validated in the gastric cancer cell lines and clinical samples. NRGPI-high patients showed sensitivity to a number of targeted agents, in particular, the tyrosine kinase inhibitors.

Conclusions

Necroptosis appears to play a critical role in the development of gastric cancer, prognosis and shaping of its tumor immune microenvironment. NRGPI can be used as a promising prognostic biomarker to identify gastric cancer patients with a cold tumor immune microenvironment and poor prognosis who may response to selected molecular targeted therapy.

A Four-Gene Signature Associated with Radioresistance in Head and Neck Squamous Cell Carcinoma Identified by Text Mining and Data Analysis

Purpose

Head and neck squamous cell carcinoma (HNSCC) is the sixth leading cancer globally, and radiotherapy plays a crucial part in its treatment. This study was designed to identify potential genes related to radiation resistance in HNSCC.

Method

We first used text mining to obtain common genes related to radiotherapy resistance and HNSCC in published articles. Functional enrichment analyses were conducted to identify the significantly enriched pathways and genes. Protein and protein interactions were performed, and the most significant gene modules were determined; then, genes in the gene modules were validated at transcriptional levels and overall survival. Gene set variation analysis (GSVA) score was calculated, and the association between GSVA score and survival/pathway was estimated. Immune cell infiltration, methylation, and genetic alteration analysis of these genes was conducted in HNSCC patients. Finally, potential sensitive anticancer drugs related to target genes were obtained.

Result

We identified 583 common genes through text mining. After further validation, a four-gene signature (EPHB2, SPP1, SERPINE1, and VEGFC) was constructed. The patients with higher GSVA scores have a worse prognosis than those with lower GSVA scores. Differences in methylation of these four genes in HNSCC tumor tissue and normal tissue were compared, with higher methylation levels of EBPH2 and SPP1 in normal tissue and higher methylation levels of SERPINE1 in the tumor. Immune cell infiltration revealed that the increased expression of these genes was closely related to the infiltration level of CD4+ T cell, neutrophil, macrophage, and dendritic cell. Thirty drugs, including 22 positively and eight negatively correlated drugs that most correlated with related genes, were available for treating HNSCC.

Conclusion

In this study, we identified four potential genes as well as corresponding drugs that might be related to radioresistance in HNSCC patients. These candidate genes may provide a promising avenue to further elevate radiotherapy efficacy.

Single Cell Analysis Reveals Reciprocal Tumor-Macrophage Intercellular Communications Related with Metabolic Reprogramming in Stem-like Gastric Cancer

Metabolic alterations and direct cell–cell interactions in the tumor microenvironment (TME) affect the prognostic molecular landscape of tumors; thus, it is imperative to investigate metabolic activity at the single-cell level rather than in bulk samples to understand the high-resolution mechanistic influences of cell-type specific metabolic pathway alterations on tumor cells. To investigate tumor metabolic reprogramming and intercellular communication at the single-cell level, we analyzed eighty-four metabolic pathways, seven metabolic signatures, and tumor-stroma cell interaction using 21,084 cells comprising gastric cancer and paired normal tissue. High EMT-score cells and stem-like subtype tumors showed elevated glycosaminoglycan metabolism, which was associated with poor patient outcome. Adenocarcinoma and macrophage cells had higher reactive oxidative species levels than the normal controls; they largely constituted the highest stemness cluster. They were found to reciprocally communicate through the common ligand RPS19. Consequently, ligand-target regulated transcriptional reprogramming resulted in HS6ST2 expression in adenocarcinoma cells and SERPINE1 expression in macrophages. Gastric cancer patients with increased SERPINE1 and HS6ST2 expression had unfavorable prognoses, suggesting these as potential drug targets. Our findings indicate that malignant stem-like/EMT cancer cell state might be regulated through reciprocal cancer cell-macrophage intercellular communication and metabolic reprogramming in the heterogeneous TME of gastric cancer at the single-cell level.

NCAPG2 Is a Novel Prognostic Biomarker and Promotes Cancer Stem Cell Maintenance in Low-Grade Glioma

Gliomas account for 75% of all primary malignant brain tumors in adults and are associated with high mortality. Mounting evidence has shown that NCAPG2 is differentially expressed in various cancers. However, the prognostic value and immune functions of NCAPG2 in low-grade glioma (LGG) remain unresolved. In the present study, we revealed that NCAPG2 was up-regulated in LGG, and its higher expression was associated with adverse clinical outcomes and poor clinical characteristics, including WHO grade, IDH mutation, 1p/19q codeletion, and primary therapy outcome. The results of the Cox regression analysis revealed that NCAPG2 was an independent factor for the prognosis of low-grade glioma. Meanwhile, we also established a nomogram based on NCAPG2 to predict the 1-, 3-, or 5-year survival in LGG patients. Furthermore, we found that Copy number variation (CNV) and DNA hypomethylation results in its overexpression in LGG. In addition, functional annotation confirmed that NCAPG2 was mainly involved in the immune regulation and WNT signaling pathways. Finally, we determined that increased expression of NCAPG2 was correlated with infiltration levels of various immune cells and immune checkpoint in LGG. Importantly, we found that NCAPG2 was highly expressed in glioma stem cells lines and knockdown of NCAPG2 significantly inhibited the self-renewal ability of GSC. This is the first study to identify NCAPG2 as a new potential prognostic biomarker and characterize the functional roles of NCAPG2 in the progression of LGG, and provides a novel potential diagnostic and therapeutic biomarker for LGG in the future.

Next-generation sequencing identifies HOXA6 as a novel oncogenic gene in low grade glioma

Background: Low grade glioma is one of the most common lethal cancers in the human nervous system. Emerging evidence has demonstrated that homeobox A cluster (HOXA) gene family plays a critical role in the transcriptional regulation as well as cancer initiation and progression. However, the expression, biological functions and upstream regulatory mechanism of 11 HOXAs in low grade glioma are not yet clear.

Methods: In this study, we utilized various public databases and bioinformatics analyzed, including TCGA, CGGA, Rembrandt, HPA, LinkedOmics, cBioPortal, TISDIB, single-sample GSEA (ssGSEA), TIMER, LnCeVar, LASSO regression, Cox regression, Kaplan-Meier plot, and receiver operating, characteristic (ROC) analyses, GDSC and CTRP databases to analyzed the mRNA and protein expression profiles, gene mutation, clinical features, diagnosis, prognosis, signaling pathway, TMB, immune subtype, immune cell infiltration, immune modulator, ceRNA network and drug sensitivity of 11 HOXAs. Growth curve and transwell assays were utilized to study the biological characteristics of HOXA6 in LGG progression.

Results: In the present study, we found that 11 HOXAs (HOXA1, HOXA2, HOXA3, HOXA4, HOXA5, HOXA6, HOXA7, HOXA9, HOXA10, HOXA11 and HOXA3) were consistently up-regulated in LGG tissues and GBM tissues. Up-regulated of the HOXAs expression were significantly correlated with higher tumor stage, IDH mutation status, 1p/19q co-deletion, histological type and primary therapy outcome. Survival analyses showed that higher expression of HOXA1, HOXA2, HOXA3, HOXA4, HOXA5, HOXA7, HOXA9, HOXA10, HOXA11 and HOXA13 were correlated with shorter overall survival (OS), disease-specific survival (DSS) and progression-free survival (PFS) in LGG patients. Univariate and multivariate analyses revealed that HOXA1, HOXA6 expression and tumor grade, age, primary therapy outcome and age were independent factors affecting the prognosis of LGG patients. ROC curve analysis of HOXAs showed that HOXAs had a high accuracy (AUC > 0.80) in predicting LGG. Furthermore, gene functional enrichment analysis indicated that HOXAs mainly involved in the inflammatory response and immune regulation signaling pathway. CNV and DNA methylation significantly affect the expression of HOXAs. Finally, we uncover that HOXAs expression are highly correlated with immune cells infiltrate, immune modulator and drug sensitivity. We also uncover that the HOXAs related ceRNA network in LGG. More importantly, we found that HOXA6 was highly expressed in LGG cells lines and significantly affected their proliferation and migration abilities.

Conclusions: In conclusion, our data demonstrated that HOXA was correlated with progression and immune infiltration, and could serve as a prognostic biomarker for LGG.

MD2 Is a Potential Biomarker Associated with Immune Cell Infiltration in Gliomas

BACKGROUND

Glioma is the most common primary malignant tumor in the central nervous system. Myeloid differentiation protein 2 (MD2) acts as a coreceptor of toll-like receptor 4 (TLR4) to mediate innate immune response. However, the actual roles of MD2 in the regulation of progression and immune cell infiltration in gliomas remain largely unclear. This study aims to explore whether MD2 could be an independent prognostic factor through the mediation of immune cell infiltration in gliomas.

METHODS

The mRNA expression and DNA methylation differential analyses of MD2 were performed using CGGA, TCGA and Rembrandt databases and survival analyses were performed using Kaplan-Meier plotter. Univariate and multivariate Cox regression was applied to analyze the prognostic value of MD2 and nomograms were constructed to evaluate the clinical value of MD2. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were utilized to analyze MD2-related signal pathways. Furthermore, correlations between MD2 and immune cell infiltration were calculated by TIMER and CIBERSOPT. The correlation between MD2 expression and the infiltrations of macrophages and neutrophils was experimentally verified by the knockdown of MD2 expression using small interfering RNA (siRNA) in glioma cells.

RESULTS

We found that MD2 was overexpressed and associated with a poor prognosis in gliomas. Meanwhile, higher expression of MD2 could be a result of lower DNA methylation of MD2 gene in gliomas. In addition, univariate and multivariate Cox regression analysis indicated that MD2 could be an independent prognostic factor for gliomas. Further functional enrichment analysis revealed that the functions of MD2 were closely related to immune responses. Moreover, the expression level of MD2 was strongly correlated with the infiltration and polarization of pro-tumor phenotype of tumor-associated macrophages and tumor-associated neutrophils in gliomas.

CONCLUSIONS

These findings have provided strong evidence that MD2 could be served as a valuable immune-related biomarker to diagnose and predict the progression of gliomas.

MD2 Is a Potential Biomarker Associated with Immune Cell Infiltration in Gliomas

Background

Glioma is the most common primary malignant tumor in the central nervous system. Myeloid differentiation protein 2 (MD2) acts as a coreceptor of toll-like receptor 4 (TLR4) to mediate innate immune response. However, the actual roles of MD2 in the regulation of progression and immune cell infiltration in gliomas remain largely unclear. This study aims to explore whether MD2 could be an independent prognostic factor through the mediation of immune cell infiltration in gliomas.

Methods

The mRNA expression and DNA methylation differential analyses of MD2 were performed using CGGA, TCGA and Rembrandt databases and survival analyses were performed using Kaplan-Meier plotter. Univariate and multivariate Cox regression was applied to analyze the prognostic value of MD2 and nomograms were constructed to evaluate the clinical value of MD2. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were utilized to analyze MD2-related signal pathways. Furthermore, correlations between MD2 and immune cell infiltration were calculated by TIMER and CIBERSOPT. The correlation between MD2 expression and the infiltrations of macrophages and neutrophils was experimentally verified by the knockdown of MD2 expression using small interfering RNA (siRNA) in glioma cells.

Results

We found that MD2 was overexpressed and associated with a poor prognosis in gliomas. Meanwhile, higher expression of MD2 could be a result of lower DNA methylation of MD2 gene in gliomas. In addition, univariate and multivariate Cox regression analysis indicated that MD2 could be an independent prognostic factor for gliomas. Further functional enrichment analysis revealed that the functions of MD2 were closely related to immune responses. Moreover, the expression level of MD2 was strongly correlated with the infiltration and polarization of pro-tumor phenotype of tumor-associated macrophages and tumor-associated neutrophils in gliomas.

Conclusions

These findings have provided strong evidence that MD2 could be served as a valuable immune-related biomarker to diagnose and predict the progression of gliomas.

NCAPG as a Novel Prognostic Biomarker in Glioma

Background

Non-SMC condensin I complex subunit G (NCAPG) is expressed in various human cancers, including gliomas. However, its biological function in glioma remains unclear. The present study was designed to determine the biological functions of NCAPG in glioma and to evaluate the association of NCAPG expression with glioma progression.

Methods

Clinical data on patients with glioma were obtained from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), the Gene Expression Omnibus (GEO), and the Rembrandt and Gravendeel databases. The correlations among NCAPG expression, pathological characteristics, and clinical outcome were evaluated. In addition, the correlations of NCAPG expression with immune cell infiltration and glioma progression were analyzed.

Results

NCAPG expression was higher in gliomas than in adjacent normal tissues. Higher expression of NCAPG in gliomas correlated with poorer prognosis, unfavorable histological features, absence of mutations in the isocitrate dehydrogenase gene (IDH), absence of chromosome 1p and 19q deletions, and responses to chemoradiotherapy. Univariate and multivariate Cox analysis demonstrated, in addition to patient age, tumor grade, absence of IDH mutations, and absence of chromosome 1p and 19q deletions, NCAPG expression was independently prognostic of overall survival, disease-free survival, and progression-free survival in patients with glioma. In addition, high expression of NCAPG correlated with tumor infiltration of B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells. Gene set enrichment analysis (GSEA) indicated that high NCAPG expression was associated with cell proliferation and immune response-related signaling pathways. NCAPG knockdown in glioma cell lines significantly reduced cell survival, proliferation, and migration.

Conclusion

NCAPG expression correlates with glioma progression and immune cell infiltration, suggesting that NCAPG expression may be a useful prognostic biomarker for glioma.

The N6-Methylandenosine-Related Gene BIRC5 as a Prognostic Biomarker Correlated With Cell Migration and Immune Cell Infiltrates in Low Grade Glioma

Gliomas account for 75% of all primary malignant brain tumors in adults and are associated with high mortality. Emerging evidence has demonstrated that baculoviral inhibitor of apoptosis repeat containing 5 (BIRC5) plays a critical role in cell apoptosis and the progression of diverse cancers. However, no studies have yet focused on the immunological function and mechanisms of upstream BIRC5 regulation in the progression of low-grade gliomas (LGG). Here, we evaluated BIRC5 expression and clinical characteristics in people with LGG using the Chinese Glioma Genome Atlas, The Cancer Genome Atlas, Gene Expression Omnibus, Rembrandt, and Gravendeel databases. We used Kaplan–Meier statistics and receiver operating characteristic (ROC) curves to analyze the prognostic value of BIRC5 in LGG. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment terms were also explored to identify functional roles of BIRC5. The Tumor Immune Estimation Resource (TIMER) and Tumor Immune System Interaction (TISIDB) databases were used to examine the correlation between BIRC5 expression and immune cell infiltration in LGG. The Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Therapeutics Response Portal (CTRP) databases were used to examine the potential drugs targeting BIRC5. We used transwell and wound healing assays to determine the biological functions of BIRC5 in glioma cell migration. Our results demonstrated that BIRC5 was highly expressed in LGG and the expression level correlated with tumor grade, prognosis, histological subtype, isocitrate dehydrogenase 1 (IDH1) mutation, 1p/19q chromosomal co-deletion, chemotherapy status, and O[6]-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. GO and KEGG analysis showed that BIRC5 is primarily involved in cell proliferation and immune response-related signaling pathways. We also found that BIRC5 was significantly correlated with m6A modification and diverse drug sensitivity. TIMER and TISIDB database analysis showed that BIRC5 expression is associated with infiltration of diverse immune cells and immune modulation in LGG. BIRC5 knockdown inhibited LGG cell migration. Collectively, our results demonstrate that BIRC5 is correlated with cell migration and immune infiltration in LGG and may be a useful prognostic biomarker.

SERPINE1 Overexpression Promotes Malignant Progression and Poor Prognosis of Gastric Cancer

The serine protease inhibitor clade E member 1 (SERPINE1) is a major inhibitor of tissue plasminogen activator and urokinase, and has been implicated in the development and progression of a variety of tumors. In this study, mRNA microarray and TCGA database were used to comprehensively analyze the upregulation of SERPINE1 in gastric cancer (GC) tissues compared with the normal stomach tissues. Kaplan-Meier results confirmed that patients with high SERPINE1 expression exhibited worse overall survival and disease-free survival. In addition, cell proliferation, cell scratches, transwell migration and invasion assay showed that SERPINE1 knockdown inhibited the proliferation, migration and invasion of GC ells. Western blot showed that the expression of VEGF and IL-6 was significantly upregulated after overexpression of SERPINE1. Meanwhile, SERPINE1 was positively correlated with the level of immune infiltration using the online analysis tools TISIDB and TIMER. And SERPINE1 expression increased with the increase of malignancy of GC which were detected by Immunohistochemistry. Finally, tumorigenesis experiments in nude mice further demonstrated that SERPINE1 could promote the occurrence and development of GC, while deletion of SERPINE1 inhibited the progression of GC. In summary, SERPINE1 was highly expressed in GC tissues, and SERPINE1 was helpful for differential diagnosis of pathological grade of gastric mucosal lesions. SERPINE1 might regulate the expression of VEGF and IL-6 through the VEGF signaling pathway and JAK-STAT3 inflammatory signaling pathway, thus ultimately affecting the invasion and migration of GC cells.

Prognostic modeling of patients with metastatic melanoma based on tumor immune microenvironment characteristics

Most of the malignant melanomas are already in the middle and advanced stages when they are diagnosed, which is often accompanied by the metastasis and spread of other organs. Besides, the prognosis of patients is bleak. The characteristics of the local immune microenvironment in metastatic melanoma have important implications for both tumor progression and tumor treatment. In this study, data on patients with metastatic melanoma from the TCGA and GEO datasets were selected for immune, stromal, and estimate scores, and overlapping differentially expressed genes were screened. A nine-IRGs prognostic model (ALOX5AP, ARHGAP15, CCL8, FCER1G, GBP4, HCK, MMP9, RARRES2 and TRIM22) was established by univariate COX regression, LASSO and multivariate COX regression. Receiver operating characteristic curves were used to test the predictive accuracy of the model. Immune infiltration was analyzed by using CIBERSORT and Xcell in high-risk and low-risk groups. The immune infiltration of the high-risk group was significantly lower than that of the low-risk group. Immune checkpoint analysis revealed that the expression of PDCD1, CTLA4, TIGIT, CD274, HAVR2 and LAG3 demonstrated the visible difference in groups with different levels of risk scores. WGCNA analysis found that the yellow-green module contained seven genes from the nine-IRG prognostic model, and the yellow-green module had the highest correlation with risk scores. The results of GO and KEGG suggested that the genes in the yellow-green module were mainly enriched in immune-related biological processes. Finally, the expression characteristics of ALOX5AP, ARHGAP15, CCL8, FCER1G, GBP4, HCK, MMP9, RARRES2 and TRIM22 were analyzed between metastatic melanoma and normal samples. Overall, a prognostic model for metastatic melanoma based on the tumor immune microenvironment characteristics was established, which left plenty of space for further studies. It could function well in helping people to understand characteristics of the immune microenvironment in metastatic melanoma.

CD86 Molecule Might Be a Novel Immune-Related Prognostic Biomarker for Patients With Bladder Cancer by Bioinformatics and Experimental Assays

As one of the most common malignancies in the urinary system, bladder cancer (BC) occupies a high mortality and recurrence rate. BC carries an ominous prognosis. Thus, we aimed to identify a novel immune-related prognostic biomarker and therapeutic target for immunotherapy in the present study. We first constructed a co-expression network based on immune-related genes (IRGs). Two key modules showed high association with the clinical feature interested us most were further identified. Forty-five IRGs were screened out and regarded as hub genes in the co-expression network. We further constructed a protein-protein interaction (PPI) network, and five independent methods were used for hub gene identification. Three hub genes were identified in the present study. CD86 molecule (CD86) was screened out by performing overall survival (OS) analysis. Subsequent analyses by using some bioinformatics and experimental assays confirmed that CD86 was an immune-related prognostic biomarker, which might be a novel target for immunotherapy in BC. A small molecule drug named suloctidil was also identified, which showed potential for BC treatment.