Identification of immunologic subtype and prognosis of GBM based on TNFSF14 and immune checkpoint gene expression profiling

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

Introduction

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

Objectives

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

Methods

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

Results

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

Conclusion

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

Acircadian rhythm-related gene signature for predicting survival and drug response in HNSC

Head and neck squamous cell carcinoma (HNSC) represents one of the most common malignant carcinomas worldwide. Because the 5-year survival rate of patients with HNSC is poor, it is necessary to develop an effective signature for predicting the risk of HNSC. To identify a circadian rhythm (CR)-related predictive signature, we analyzed the RNA-seq data of patients with HNSC from The Cancer Genome Atlas and Gene Expression Omnibus cohorts. Nine CR-related genes (PER2, PER3, GHRL, CSF2, HDAC3, KLF10, PRKAA2, PTGDS, and RORB) were identified to develop a CR-related signature. The area under the curve values for 5-year overall survival were 0.681, 0.700, and 0.729 in the training set, validation set, and an external independent test set (GSE41613), respectively. The Kaplan‒Meier curve analysis showed that the high-risk group had a reduced relapse-free survival compared with the low-risk group in the training set, validation set, and test set (P < 0.05). Finally, we observed that the CR-related gene signature was associated with the tumor immune microenvironment, somatic nucleotide variation, and drug response in HNSC. In conclusion, we developed a circadian rhythm-related gene signature for predicting overall survival in HNSC.

Comprehensive characterization of TNFSF14/LIGHT with implications in prognosis and immunotherapy of human gliomas

Glioblastoma multiforme (GBM) is a common central neural system malignant tumor among adults. Alongside its microscopic spread, immunosuppression in the tumor microenvironment also induces its refractoriness, which makes immunotherapy for GBM particularly important. Unfortunately, traditional immune checkpoint inhibitors (ICIs) often show limited therapeutic effects in GBM clinical trials, and new therapeutic strategies or targets are urgently needed. TNFSF14/LIGHT is a novel immune checkpoint molecule that plays essential roles in both innate and acquired immunity. Despite recent advances in our understanding of the function of TNFSF14/LIGHT in a variety of cancer types, the clinical and immunological importance of TNFSF14/LIGHT in human gliomas has not been fully explained. Here, we employed a comprehensive in silico analysis with publicly available data to analyze the molecular and immune characteristics of TNFSF14/LIGHT to explore its feasibility as an immunotherapy target. Totally, 2215 glioma cases were enrolled in the current study. Immunohistochemistry staining based on patient tissues (n = 34) was performed for the validation. TNFSF14/LIGHT was expressed higher in higher-WHO-grade gliomas and mesenchymal subtypes, and it was sensitive as a prognostic marker in GBM and low-grade glioma (LGG). A nomogram prognostic model was established based on TNFSF14/LIGHT expression together with other risk factors. Additionally, Gene Ontology and pathway analysis revealed that TNFSF14/LIGHT participated in T-cell activities and inflammatory processes. Moreover, analysis based on the structure and interactions of TNFSF14/LIGHT revealed its mutation sites in tumors as well as crucial interacting proteins. Analysis of IMvigor210 indicated the role of TNFSF14/LIGHT in immunotherapy. Altogether, our results reveal an underlying role of TNFSF14/LIGHT as an immunotherapy target in GBM.

The prognostic significance of PD-L1 expression in patients with glioblastoma: A meta-analysis

Background

Glioblastoma (GBM) is a malignant brain tumor associated with high morbidity and mortality rates with a poor prognosis. In recent years, studies on prognostic markers such as programmed death ligand 1 (PD-L1) have increased; however, their conclusions remain controversial. Here, relevant literature was reviewed and a meta-analysis was performed to clarify the correlation between PD-L1 expression and overall survival (OS) in GBM.

Methods

The non-foundational literature on PD-L1 expression associated with OS in GBM up to February 2022 was searched in the PubMed, Metstr, Cochrane, and Web of Science databases. Literature was rigorously screened according to inclusion and exclusion criteria, the total hazard ratio (HR), and corresponding 95% confidence intervals (CIs).

Results

Calculating the combined HR value and corresponding 95% CI of HR=1.124 (95% CI: 1.047–1.201, P=0.000, I2 (I-squared)=48.8%), it was shown that PD-L1 expression was significantly associated with low OS in GBM patients. Although I2 = 48.8% < 50%, to make the results more credible, in the cutoff values ≥10% subgroup HR=1.37 (95% CI: 1.07–1.67, P=0.000, I2 = 0%), which was also the result found in the first meta-analysis. In contrast, in the cutoff value ≥5% subgroup HR=1.14 (95% CI: 0.98–1.30, P=0.000, I2 = 59.8%) and in the cutoff value median PD-L1 expression levels subgroup HR=1.05 (95% CI: 0.92–1.18, P=0.000, I2 = 0%), indicating that PD-L1 expression was not associated with low OS in GBM. Furthermore, in four studies, we found no significant correlation between PD-L1 expression and the progression-free survival of GBM (HR=1.14, 95% CI:0.40–1.88, P=0.03, I2 = 29.3%).

Conclusion

PD-L1 expression was significantly associated with low OS in GBM patients; however, this result needs to be interpreted with caution and requires a large, multicenter clinical study in patients with similar baseline data for further evaluation.

SAA1 Expression as a Potential Prognostic Marker of the Tumor Microenvironment in Glioblastoma

Background

Glioblastoma (GBM) is the most common primary brain malignant tumor, and patients with GBM have a poor prognosis. The tumor microenvironment (TME) is connected to tumorigenesis and prognosis. However, the TME-related genes and therapeutic targets in GBM are yet to be identified. Thus, the presented study aimed to identify TME-related biomarkers in GBM and develop a novel target for the treatment of the disease.

Methods

ESTIMATE computational methods were utilized to estimate the amounts of stromal and immune components in 697 patients with glioma from the Cancer Genome Atlas database. Then, the protein–protein interaction network and univariate Cox regression analyzed the differentially expressed genes. Serum amyloid A1 (SAA1) was determined to be a predictive factor. SAA1 expression was statistically significant in GBM compared to the normal samples and other glioma subtypes and negatively associated with survival. Independent prognostic analysis identified SAA1 as a TME-related prognostic factor. Furthermore, Western blot analysis showed that SAA1 is upregulated in GBM, which was confirmed by the external validation in the Chinese Glioma Genome Atlas. The gene set enrichment analysis in GBM revealed enrichment of immune-related activities in the SAA1 high-expression group, while mitosis and cell cycle were enriched in the low-expression group. CIBERSORT analysis of the tumor-infiltrating immune cell proportion revealed that M2 macrophages, neutrophils, activated mast cells, resting mast cells, and regulatory T cells were correlated with SAA1 expression. Finally, immune checkpoint genes, tumor mutation burden, and drug sensitivity were also analyzed between the high- and low-expression groups.

Conclusion

SAA1 could be a distinctive gene between GBM and other subtype gliomas, and thus a novel biomarker for estimating the survival and TME status. The altered expression level shifts the primary function of SAA1 from cell cycle and mitosis to immune activity. High expression of SAA1 is associated with poor survival and upregulates the expression of LAIR1 and TNFSF14, thereby deeming it as the drug sensitivity indicator for XAV939, TGX-221, and lapatinib in GBM immune therapy.

CD44-Mediated Poor Prognosis in Glioma Is Associated With M2-Polarization of Tumor-Associated Macrophages and Immunosuppression

Background

Glioma is the most common primary brain tumor with a poor prognosis. Key genes that are negatively related to prognosis may provide the therapy targets to cure glioma. To clarify the role of CD44 in glioma, we explored its function at bulk-transcriptome, spatial and single-cell transcriptome levels.

Methods

In total, expression profiles with survival data of whole-grade glioma from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA), RNA-seq data with anatomic information of glioblastoma (GBM) from the Ivy Glioblastoma Atlas Project, RNA-sequencing (RNA-seq) data from recurrent GBM receiving adjuvant anti-PD-1 immunotherapy accessed through GSE121810, and single-cell RNA-seq data of GBM under accession GSE103224 were enrolled in this study. CD44-specific findings were further analyzed by R language.

Results

CD44 is positively correlated with WHO grade of malignancy and is negatively related to prognosis in glioma. Meanwhile, CD44 predominantly expresses in GBM mesenchymal subtype, and gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses reveal that CD44 positively coexpressed genes are closely related to glioma immunity. Moreover, CD44+ cells mainly distribute in perinecrotic region with high expression of immune factors. At single-cell resolution, only malignant tumor cells, tumor-associated macrophages (TAMs), and T cells express CD44 in GBM. CD44+ malignant tumor cells are in mesenchymal-1-like (MES1-like) cellular state, and CD44+ TAMs are in M2 phenotype. CD44+ T cells have high expression of both PD-1 and PD-L1. CD44 and its directly interacted inhibitory immunomodulators are upregulated in patients with nonresponder recurrent GBM treated with PD-1 blockade therapy.

Conclusion

Our work demonstrates that CD44, a new M2 TAM biomarker, is involved in immune suppressor and promote glioma progression in glioma microenvironment. These results expand our understanding of CD44-specific clinical and immune features in glioma.

Construction of an immune-related prognostic model by exploring the tumor microenvironment of clear cell renal cell carcinoma

OBJECTIVE

In this study, bioinformatics methods were performed to screen the candidate prognosis-related genes of clear cell renal cell carcinoma (ccRCC) by analyzing the tumor microenvironment (TME).

METHODS

Gene expression and clinical data of ccRCC patients were accessed from TCGA, and R package ESTIMATE was applied to calculate immune, stromal, and ESTIMATE scores of the patients. Survival analysis was conducted per median of these three scores. Based on the scoring results, differentially expressed genes (DEGs) were screened. Regression algorithms were utilized to screen prognostic genes and establish a risk model. Finally, pathway activity differences were analyzed through GSEA.

RESULTS

Patients with the unfavorable prognosis had high immune scores. 619 DEGs (499 up-regulated and 120 down-regulated) were screened based on the differences in gene expression of the patients with high and low immune scores. These genes mainly participated in immune-related signaling pathways. A prognostic risk model for ccRCC patients was constructed and 7 immune-related signature genes (RORB, TNFSF14, UCN2, USP2, TOX3, KLRC2, SLAMF9) were obtained through regression analysis. The constructed prognostic risk model could be used for determining prognoses of patients with ccRCC.

CONCLUSION

We unraveled the association between TME and prognosis of ccRCC patients and established a prognostic risk model based on the differentially expressed genes. These results contributed to understanding of TME that affected patients' prognosis and progression of ccRCC and conduced to finding potential biomarkers of ccRCC.

Immune Checkpoint Gene Expression Profiling Identifies Programmed Cell Death Ligand-1 Centered Immunologic Subtypes of Oral and Squamous Cell Carcinoma With Favorable Survival

Objective

This study aimed to identify the programmed death ligand-1 (PDL1, also termed as CD274) and its positively correlated immune checkpoint genes (ICGs) and to determine the immune subtypes of CD274-centered ICG combinations in oral and squamous cell carcinoma (OSCC).

Materials and Methods

Firstly, the 95 ICGs obtained via literature reviews were identified in the Cancer Genome Atlas (TCGA) database in relation to OSCC, and such 88 ICG expression profiles were extracted. ICGs positively correlated with CD274 were utilized for subsequent analysis. The relationship between ICGs positively correlated with CD274 and immunotherapy biomarkers (tumor mutation burden (TMB), and adaptive immune resistance pathway genes) was investigated, and the relationships of these genes with OSCC clinical features were explored. The prognostic values of CD274 and its positively correlated ICGs and also their associated gene pairs were revealed using the survival analysis.

Results

Eight ICGs, including CTLA4, ICOS, TNFRSF4, CD27, B- and T-lymphocyte attenuator (BTLA), ADORA2A, CD40LG, and CD28, were found to be positively correlated with CD274. Among the eight ICGs, seven ICGs (CTLA4, ICOS, TNFRSF4, CD27, BTLA, CD40LG, and CD28) were significantly negatively correlated with TMB. The majority of the adaptive immune resistance pathway genes were positively correlated with ICGs positively correlated with CD274. The survival analysis utilizing the TCGA-OSCC data showed that, although CD274 was not significantly associated with overall survival (OS), the majority of ICGs positively correlated with CD274 (BTLA, CD27, CTLA4, CD40LG, CD28, ICOS, and TNFRSF4) were significantly correlated with OS, whereby their low-expression predicted a favorable prognosis. The survival analysis based on the gene pair subtypes showed that the combination subtypes of CD274_low/BTLA_low, CD274_low/CD27_low, CD274_low/CTLA4_low, CD8A_high/BTLA_low, CD8A_high/CD27_low, and CD8A_high/CTLA4_low predicted favorable OS.

Conclusion

The results in this study provide a theoretical basis for prognostic immune subtyping of OSCC and highlight the importance of developing future immunotherapeutic strategies for treating oral cancer.

Prognostic value of programmed death ligand 1 (PD-L1) in glioblastoma: a systematic review, meta-analysis and validation based on dataset

Excellent prognostic value of programmed death ligand 1 (PD-L1) is observed in patients with other cancers; however, the prognostic value of PD-L1 in glioblastoma (GBM) remains unclear. Therefore, this meta-analysis evaluated the prognostic value of PD-L1 in GBM. We performed a systematic search in databases to screen eligible articles. The hazard ratio (HR) and 95% confidence interval (95% CI) were extracted from included articles. This meta-analysis included 15 studies, and the forest plot indicated that increased PD-L1 expression was associated with poorer overall survival (OS) of GBM (HR, 1.16; 95% CI, 1.05-1.27; P = 0.002). Furthermore, stratified analysis confirmed that PD-L1 expression was associated with unfavorable OS at the protein level (HR, 1.30; 95% CI, 1.13-1.48; P< 0.001) and messenger ribonucleic acid (mRNA) level (HR, 1.05; 95% CI, 1.00-1.09; P= 0.041). The analysis of a dataset verified the prognostic value of PD-L1 and revealed an association between PD-L1 mRNA expression and the status of isocitrate dehydrogenase (IDH). In conclusion, increased PD-L1 expression predicts unfavorable OS in GBM and may be a promising prognostic biomarker of GBM.

Molecular and Clinical Characterization of LIGHT/TNFSF14 Expression at Transcriptional Level via 998 Samples With Brain Glioma

LIGHT, also termed TNFSF14, has been reported to play a vital role in different tumors. However, its role in glioma remains unknown. This study is aimed at unveiling the characterization of the transcriptional expression profiling of LIGHT in glioma. We selected 301 glioma patients with mRNA microarray data from the CGGA dataset and 697 glioma patients with RNAseq data from the TCGA dataset. Transcriptome data and clinical data of 998 samples were analyzed. Statistical analyses and figure generation were performed with R language. LIGHT expression showed a positive correlation with WHO grade of glioma. LIGHT was significantly increased in mesenchymal molecular subtype. Gene Ontology analysis demonstrated that LIGHT was profoundly involved in immune response. Moreover, LIGHT was found to be synergistic with various immune checkpoint members, especially HVEM, PD1/PD-L1 pathway, TIM3, and B7-H3. To get further understanding of LIGHT-related immune response, we put LIGHT together with seven immune signatures into GSVA and found that LIGHT was particularly correlated with HCK, LCK, and MHC-II in both datasets, suggesting a robust correlation between LIGHT and activities of macrophages, T-cells, and antigen-presenting cells (APCs). Finally, higher LIGHT indicated significantly shorter survival for glioma patients. Cox regression models revealed that LIGHT expression was an independent variable for predicting survival. In conclusion, LIGHT was upregulated in more malignant gliomas including glioblastoma, IDH wildtype, and mesenchymal subtype. LIGHT was mainly involved in the immune function of macrophages, T cells, and APCs and served as an independent prognosticator in glioma.

Transcriptional expression of ZICs as an independent indicator of survival in gliomas

The functional significance of the zinc-finger of the cerebellum (ZIC) gene family in gliomas remains to be elucidated. Clinical data from patients with gliomas, containing expression levels of ZIC genes, were extracted from CCLE, GEPIA2 and The Human Protein Atlas (HPA). Univariate survival analysis adjusted by Cox regression via OncoLnc was used to determine the prognostic significance of ZIC expression. We used cBioPortal to explore the correlation between gene mutations and overall survival (OS). ZIC expression was found to be related to immune cell infiltration in gliomas via TIMER analysis. GO term and KEGG pathway enrichment analyzes were performed with Metascape. PPI networks were constructed using STRING. The expression levels of ZIC1/3/4/5 in gliomas were significantly different from those in normal samples. High expression levels of ZIC1/5 were associated with poor OS in brain low-grade glioma (LGG) patients, while low ZIC3 expression combined was related to favorable OS in glioblastoma multiforme (GBM). ZIC alterations were associated with poor prognosis in LGG patients and related to favorable prognosis in GBM patients. We observed that the expression of ZICs was related to immune cell infiltration in glioma patients. ZICs were enriched in several pathways and biological processes involving Neuroactive ligand-receptor interaction (hsa04080). The PPI network revealed that some proteins coexpressed with ZICs played a role in the pathogenesis of gliomas. Differences in the expression levels of ZIC genes could provide a significant marker for predicting prognosis in gliomas.

A novel Foxp3-related immune prognostic signature for glioblastoma multiforme based on immunogenomic profiling

Foxp3⁺ regulatory T cells (Treg) play an important part in the glioma immunosuppressive microenvironment. This study analyzed the effect of Foxsp3 on the immune microenvironment and constructed a Foxp3-related immune prognostic signature (IPS)for predicting prognosis in glioblastoma multiforme (GBM). Immunohistochemistry (IHC) staining for Foxp3 was performed in 72 high-grade glioma specimens. RNA-seq data from 152 GBM samples were obtained from The Cancer Genome Atlas database (TCGA) and divided into two groups, Foxp3 High (Foxp3_H) and Foxp3 Low (Foxp3_L), based on Foxp3 expression. We systematically analyzed the influence of Foxp3 on the immune microenvironment. Least Absolute Shrinkage and Selection Operator (LASSO) Cox analysis was conducted for immune-related genes that were differentially expressed between Foxp3_H and Foxp3_L GBM patients. We found a differential expression of Foxp3 in high-grade glioma tissues. The presence of Foxp3 was significantly associated with poor OS. From the four-gene IPS developed, GBM patients were stratified into low-risk and high-risk groups in both the training set and validation sets. Furthermore, we developed a novel nomogram to evaluate the overall survival in GBM patients. This study offers innovative insights into the GBM immune microenvironment and these findings contribute to individualized treatment and improvement in the prognosis for GBM patients.

Progress in Natural Compounds/siRNA Co-delivery Employing Nanovehicles for Cancer Therapy

Chemotherapy using natural compounds, such as resveratrol, curcumin, paclitaxel, docetaxel, etoposide, doxorubicin, and camptothecin, is of importance in cancer therapy because of the outstanding therapeutic activity and multitargeting capability of these compounds. However, poor solubility and bioavailability of natural compounds have limited their efficacy in cancer therapy. To circumvent this hurdle, nanocarriers have been designed to improve the antitumor activity of the aforementioned compounds. Nevertheless, cancer treatment is still a challenge, demanding novel strategies. It is well-known that a combination of natural products and gene therapy is advantageous over monotherapy. Delivery of multiple therapeutic agents/small interfering RNA (siRNA) as a potent gene-editing tool in cancer therapy can maximize the synergistic effects against tumor cells. In the present review, co-delivery of natural compounds/siRNA using nanovehicles are highlighted to provide a backdrop for future research.