EGFRvIII Promotes the Proneural-Mesenchymal Transition of Glioblastoma Multiforme and Reduces Its Sensitivity to Temozolomide by Regulating the NF-κB/ALDH1A3 Axis.

(1) Background: Glioblastoma multiforme (GBM) is the most common and malignant intracranial tumor in adults. At present, temozolomide (TMZ) is recognized as the preferred chemotherapeutic drug for GBM, but some patients have low sensitivity to TMZ or chemotherapy resistance to TMZ. Our previous study found that GBM patients with EGFRvIII (+) have low sensitivity to TMZ. However, the reasons and possible mechanisms of the chemoradiotherapy resistance in GBM patients with EGFRvIII (+) are not clear. (2) Methods: In this study, tissue samples of patients with GBM, GBM cell lines, glioma stem cell lines, and NSG mice were used to explore the causes and possible mechanisms of low sensitivity to TMZ in patients with EGFRvIII (+)-GBM. (3) Results: The study found that EGFRvIII promoted the proneural-mesenchymal transition of GBM and reduced its sensitivity to TMZ, and EGFRvIII regulated of the expression of ALDH1A3. (4) Conclusions: EGFRvIII activated the NF-κB pathway and further regulated the expression of ALDH1A3 to promote the proneural-mesenchymal transition of GBM and reduce its sensitivity to TMZ, which will provide an experimental basis for the selection of clinical drugs for GBM patients with EGFRvIII (+).

Immunological profiles of human oligodendrogliomas define two distinct molecular subtypes.

BACKGROUND: Human oligodendroglioma presents as a heterogeneous disease, primarily characterized by the isocitrate dehydrogenase (IDH) mutation and 1p/19q co-deletion. Therapy development for this tumor is hindered by incomplete knowledge of somatic driving alterations and suboptimal disease classification. We herein aim to identify intrinsic molecular subtypes through integrated analysis of transcriptome, genome and methylome. METHODS: 137 oligodendroglioma patients from the Cancer Genome Atlas (TCGA) dataset were collected for unsupervised clustering analysis of immune gene expression profiles and comparative analysis of genome and methylome. Two independent datasets containing 218 patients were used for validation. FINDINGS: We identified and independently validated two reproducible subtypes associated with distinct molecular characteristics and clinical outcomes. The proliferative subtype, named Oligo1, was characterized by more tumors of CNS WHO grade 3, as well as worse prognosis compared to the Oligo2 subtype. Besides the clinicopathologic features, Oligo1 exhibited enrichment of cell proliferation, regulation of cell cycle and Wnt signaling pathways, and significantly altered genes, such as EGFR, NOTCH1 and MET. In contrast, Oligo2, with favorable outcome, presented increased activation of immune response and metabolic process. Higher T cell/APC co-inhibition and inhibitory checkpoint levels were observed in Oligo2 tumors. Finally, multivariable analysis revealed our classification was an independent prognostic factor in oligodendrogliomas, and the robustness of these molecular subgroups was verified in the validation cohorts. INTERPRETATION: This study provides further insights into patient stratification as well as presents opportunities for therapeutic development in human oligodendrogliomas. FUNDING: The funders are listed in the Acknowledgement.

Identification of tumor-associated antigens and immune subtypes of lower-grade glioma and glioblastoma for mRNA vaccine development.

BACKGROUND: mRNA became a promising therapeutic approach in many diseases. This study aimed to identify the tumor antigens specifically expressed in tumor cells for lower-grade glioma (LGG) and glioblastoma (GBM) patients. METHODS: In this work, the mRNA microarray expression profile and clinical data were obtained from 301 samples in the Chinese Glioma Genome Atlas (CGGA) database, the mRNA sequencing data and clinical data of 701 samples were downloaded from The Cancer Genome Atlas (TCGA) database. Genetic alterations profiles were extracted from CGGA and cBioPortal datasets. R language and GraphPad Prism software were applied for the statistical analysis and graph work. RESULTS: PTBP1 and SLC39A1, which were overexpressed and indicated poor prognosis in LGG patients, were selected as tumor-specific antigens for LGG patients. Meanwhile, MMP9 and SLC16A3, the negative prognostic factors overexpressed in GBM, were identified as tumor-specific antigens for GBM patients. Besides, three immune subtypes (LGG1-LGG3) and eight WGCNA modules were identified in LGG patients. Meanwhile, two immune subtypes (GBM1-GBM2) and 10 WGCNA modules were selected in GBM. The immune characteristics and potential functions between different subtypes were diversity. LGG2 and GBM1 immune subtype were associated with longer overall survival than other subtypes. CONCLUSION: In this study, PTBP1 and SLC39A1 are promising antigens for mRNA vaccines development in LGG, and MMP9 and SLC16A3 were potential antigens in GBM. Our analyses indicated that mRNA vaccine immunotherapy was more suitable for LGG2 and GBM1 subtypes. This study was helpful for the development of glioma immunotherapies.

MET overexpression contributes to STAT4-PD-L1 signaling activation associated with tumor-associated, macrophages-mediated immunosuppression in primary glioblastomas.

BACKGROUND: Dysregulated receptor tyrosine kinases, such as the mesenchymal-epidermal transition factor (MET), have pivotal role in gliomas. MET and its interaction with the tumor microenvironment have been previously implicated in secondary gliomas. However, the contribution of MET gene to tumor cells' ability to escape immunosurveillance checkpoints in primary gliomas, especially in glioblastoma (GBM), which is a WHO grade 4 glioma with the worst overall survival, is still poorly understood. METHODS: We investigated the relationship between MET expression and glioma microenvironment by using multiomics data and aimed to understand the potential implications of MET in clinical practice through survival analysis. RNA expression data from a total of 1243 primary glioma samples (WHO grades 2-4) were assembled, incorporating The Cancer Genome Atlas, Chinese Glioma Genome Atlas, and GSE16011 data sets. RESULTS: Pearson's correlation test from the three data sets indicated that MET showed a robust correlation with programmed death-ligand 1 (PD-L1) and STAT pathways. Western blot analysis revealed that in GBM cell lines (N33 and LN229), PD-L1 and phosphorylated STAT4 were upregulated by MET activation treatment with hepatocyte growth factor and were downregulated on MET suppression by PLB-1001. Tumor tissue microarray analysis indicated a positive correlation between MET and PD-L1 and macrophage-associated markers. Chromatin immunoprecipitation-PCR assay showed enrichment of STAT4 in the PD-L1 DNA. Transwell co-culture and chemotaxis assays revealed that knockdown of MET in GBM cells inhibited macrophage chemotaxis. Moreover, we performed CIBERSORTx and single-cell RNA sequencing data analysis which revealed an elevated number of macrophages in glioma samples with MET overexpression. Kaplan-Meier survival analysis indicated that activation of the MET/STAT4/PD-L1 pathway and upregulation of macrophages were associated with shorter survival time in patients with primary GBM. CONCLUSIONS: These data indicated that the MET-STAT4-PD-L1 axis and tumor-associated macrophages might enforce glioma immune evasion and were associated with poor prognosis in GBM samples, suggesting potential clinical strategies for targeted therapy combined with immunotherapy in patients with primary GBM.

Metabolic expression profiling stratifies diffuse lower-grade glioma into three distinct tumour subtypes.

BACKGROUND: Lower-grade gliomas (LGGs) show highly metabolic heterogeneity and adaptability. To develop effective therapeutic strategies targeting metabolic processes, it is necessary to identify metabolic differences and define metabolic subtypes. Here, we aimed to develop a classification system based on metabolic gene expression profile in LGGs. METHODS: The metabolic gene profile of 402 diffuse LGGs from the Cancer Genome Atlas (TCGA) was used for consensus clustering to determine robust clusters of patients, and the reproducibility of the classification system was evaluated in three Chinese Glioma Genome Atlas (CGGA) cohorts. Then, the metadata set for clinical characteristics, immune infiltration, metabolic signatures and somatic alterations was integrated to characterise the features of each subtype. RESULTS: We successfully identified and validated three highly distinct metabolic subtypes in LGGs. M2 subtype with upregulated carbohydrate, nucleotide and vitamin metabolism correlated with worse prognosis, whereas M1 subtype with upregulated lipid metabolism and immune infiltration showed better outcome. M3 subtype was associated with low metabolic activities and displayed good prognosis. Three metabolic subtypes correlated with diverse somatic alterations. Finally, we developed and validated a metabolic signature with better performance of prognosis prediction. CONCLUSIONS: Our study provides a new classification based on metabolic gene profile and highlights the metabolic heterogeneity within LGGs.

Transcriptional Characteristics of IDH-Wild Type Glioma Subgroups Highlight the Biological Processes Underlying Heterogeneity of IDH-Wild Type WHO Grade IV Gliomas.

Isocitric dehydrogenase (IDH)-wild type diffuse gliomas, which have a poorer prognosis than their IDH-mutant counterparts, are also accompanied with high heterogeneity. Here, we aimed to identify the key biological processes associated with the three groups of IDH-wild type diffuse gliomas in 323 patients. By The Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy (cIMPACT-NOW) update 3 recommendation, the three groups are Group A, diffuse astrocytic glioma, World Health Organization (WHO) grade II/III; Group B, diffuse astrocytic glioma, with one (or more) of the three genetic alterations: TERT promoter mutation, EGFR gene amplification, gain of chromosome 7 combined with loss of chromosome 10, WHO grade IV; and Group C, glioblastoma, WHO grade IV. Consistent with their histologic and genetic molecular features, we successfully identified that biological activities associated with "cell cycle" and "cell mitosis" are significantly elevated in Group B compared with Group A; microenvironment-related hallmarks "angiogenesis" and "hypoxia," and biological processes of "extracellular matrix," "immune response," and "positive regulation of transcriptional activities" were more enriched in Group C than Group B. We also constructed a nine-gene signature from differentially expressed genes among the three groups to further stratify the WHO grade IV gliomas (Groups B and C) whose survival cannot be clearly stratified by current classification systems. This signature was an independent prognosis factor for WHO grade IV gliomas and had better prognostic value than other known factors in both training and validation dataset. In addition, the signature risk score was positively correlated with the amount of infiltrated immune cells, expression of immune checkpoints, and the genes enriched in biological processes of "immune response," "cell cycle," and "extracellular matrix." The bioinformatic analysis results were also validated by immunohistochemistry and patient-derived cell proliferation assay. Overall, our findings revealed the key biological processes underlying the new classifications of IDH-wild type diffuse glioma. Meanwhile, we constructed a signature, which could properly stratify the prognosis, cell proliferation activates, extracellular matrix-mediated biological activities, and immune-microenvironment of IDH-wild type WHO grade IV gliomas.

Characterization and prognostic significance of alternative splicing events in lower-grade diffuse gliomas.

Alternative splicing (AS) is assumed to play important roles in the progression and prognosis of cancer. Currently, the comprehensive analysis and clinical relevance of AS in lower-grade diffuse gliomas have not been systematically addressed. Here, we gathered alternative splicing data of lower-grade diffuse gliomas from SpliceSeq. Based on the Percent Spliced In (PSI) values of 515 lower-grade diffuse glioma patients from the Cancer Genome Atlas (TCGA), we performed subtype-differential AS analysis and consensus clustering to determine robust clusters of patients. A total of 48 050 AS events in 10 787 genes in lower-grade diffuse gliomas were profiled. Subtype-differential splicing analysis and functional annotation revealed that spliced genes were significantly enriched in numerous cancer-related biological phenotypes and signalling pathways. Consensus clustering using AS events identified three robust clusters of patients with distinguished pathological and prognostic features. Moreover, each cluster was also associated with distinct genomic alterations. Finally, we developed and validated an AS-related signature with Cox proportional hazards model. The signature, significantly associated with clinical and molecular features, could serve as an independent prognostic factor for lower-grade diffuse gliomas. Thus, our results indicated that AS events could discriminate molecular subtypes and have prognostic impact in lower-grade diffuse gliomas.

Whole-transcriptome sequencing profiling identifies functional and prognostic signatures in patients with PTPRZ1-MET fusion-negative secondary glioblastoma multiforme.

Gliomas are the most common type of primary brain tumor in adults with a high mortality rate. Low-grade gliomas progress to glioblastoma multiforme (GBM) in the majority of cases, forming secondary GBM (sGBM), followed by rapid fatal clinical outcomes. Protein tyrosine phosphatase receptor type Z1 (PTPRZ1)-MET proto-oncogene receptor tyrosine kinase (MET) (ZM) fusion has been identified as a biomarker for sGBM that is involved in glioma progression, but the mechanism of gliomagenesis and pathology of ZM-negative sGBM has remained to be fully elucidated. A whole-transcriptome signature is thus required to improve the outcome prediction for patients with sGBM without ZM fusion. In the present study, whole-transcriptome sequencing on 42 sGBM samples with or without ZM fusion from the Chinese Glioma Genome Atlas database identified mRNAs with differential expression between patients with and without ZM fusion and the most significant survival-associated genes were identified. A 6-gene signature was identified as a novel prognostic model reflecting survival probability in patients with ZM-negative sGBM. Clinical characteristics in patients with a high or low risk score value were analyzed with the Kaplan-Meier method and a two-sided log-rank test. In addition, ZM-negative sGBM patients with a high risk score exhibited an increase in immune cells, NF-κB-induced pathway activation and a decrease in endothelial cells compared with those with a low risk score. The present study demonstrated the potential use of a next-generation sequencing-based cancer gene signature in patients with ZM-negative sGBM, indicating possible clinical therapeutic strategies for further treatment of such patients.

Ferroptosis-Related Gene Signature Predicts Glioma Cell Death and Glioma Patient Progression.

Glioma is a fatal brain tumor characterized by rapid proliferation and treatment resistance. Ferroptosis is a newly discovered programmed cell death and plays a crucial role in the occurrence and progression of tumors. In this study, we identified ferroptosis specific markers to reveal the relationship between ferroptosis-related genes and glioma by analyzing whole transcriptome data from Chinese Glioma Genome Atlas, The Cancer Genome Atlas dataset, GSE16011 dataset, and the Repository of Molecular Brain Neoplasia Data dataset. Nineteen ferroptosis-related genes with clinical and pathological features of glioma were identified as highly correlated. Functional assays in glioma cell lines indicated the association of ferroptosis with temozolomide resistance, autophagy, and glioma cell migration. Therefore, the identified ferroptosis-related genes were significantly correlated with glioma progression.

Classification of diffuse lower-grade glioma based on immunological profiling.

Transcriptomic data derived from bulk sequencing have been applied to delineate the tumor microenvironment (TME) and define immune subtypes in various cancers, which may facilitate the design of immunotherapy treatment strategies. We herein gathered published gene expression data from diffuse lower-grade glioma (LGG) patients to identify immune subtypes. Based on the immune gene profiles of 402 LGG patients from The Cancer Genome Atlas, we performed consensus clustering to determine robust clusters of patients, and evaluated their reproducibility in three Chinese Glioma Genome Atlas cohorts. We further integrated immunogenomics methods to characterize the immune environment of each subtype. Our analysis identified and validated three immune subtypes-Im1, Im2, and Im3-characterized by differences in lymphocyte signatures, somatic DNA alterations, and clinical outcomes. Im1 had a higher infiltration of CD8+ T cells, Th17, and mast cells. Im2 was defined by elevated cytolytic activity, exhausted CD8+ T cells, macrophages, higher levels of aneuploidy, and tumor mutation burden, and these patients had worst outcome. Im3 displayed more prominent T helper cell and APC coinhibition signatures, with elevated pDCs and macrophages. Each subtype was associated with distinct somatic alterations. Moreover, we applied graph structure learning-based dimensionality reduction to the immune landscape and revealed significant intracluster heterogeneity with Im2 subtype. Finally, we developed and validated an immune signature with better performance of prognosis prediction. Our results demonstrated the immunological heterogeneity within diffuse LGG and provided valuable stratification for the design of future immunotherapy.

Molecular subtyping reveals immune alterations in IDH wild-type lower-grade diffuse glioma.

Isocitrate dehydrogenase (IDH) wild-type diffuse lower-grade glioma (LGG) is usually associated with poor outcome, but there have been disputes over its clinical outcome and classification. We present here a robust gene expression-based molecular classification of IDH wild-type diffuse LGG into two subtypes with distinct biological and clinical features. A discovery cohort of 49 IDH wild-type diffuse LGGs from the Chinese Glioma Genome Atlas (CGGA) was subjected to clustering and function analysis. Seventy-three tumors from The Cancer Genome Atlas (TCGA) were used to validate our findings. Consensus clustering of transcriptional data uncovered concordant classification of two robust and prognostically significant subtypes of IDH wild-type LGG. Subtype 1, associated with poorer outcomes, was characterized by significantly higher immune and cytolytic scores, M2 macrophages, and up-regulation of immune exhaustion markers, while Subtype 2, which had elevated lymphocytes and plasma cells, showed relatively favorable survival. Somatic alteration analysis revealed that Subtype 1 showed more frequently deleted regions, such as the locus of CDKN2A/CDKN2B, DMRTA1, C9orf53, and MTAP. Furthermore, we developed and validated a five-gene signature for better application of this acquired stratification. Our data demonstrate the biological and prognostic heterogeneity within IDH wild-type diffuse LGGs and deepen our molecular understandi-g of this tumor entity. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Siglecs, Novel Immunotherapy Targets, Potentially Enhance The Effectiveness of Existing Immune Checkpoint Inhibitors in Glioma Immunotherapy.

BACKGROUND: Inhibitors of immune checkpoints have shown little effect in clinical trials involving glioma patients. Here, we explored novel targets for use in future treatments. Previous studies showed the sialic acid-binding Ig-like lectin (Siglec) family to have a specific role in immunosuppression. We aimed to study the characteristics and immune function of Siglec family members. METHODS: Transcriptome data from 1024 glioma samples and 1551 glioma single cells were used in our study. Clinical and molecular pathology information was also included. Statistical, bioinformatical methods, and single-cell sequencing analysis were applied to investigate the role of Siglec family members. RESULTS: Siglecs-5, -7, -9, and -16 showed a significant correlation with immunosuppression in glioma. They are typically expressed in higher grade, IDH-wildtype, and mesenchymal subtype gliomas. Siglec-5, -7, and -9 had a similar immune function to TIM-3, while Siglec-16 was similar to PD-L1, suppressing tumor immunity via different mechanisms. Joint use of Siglec-inhibitors and immune checkpoint inhibitors could prolong the survival of glioma patients. CONCLUSION: Siglec-5, -7, -9, and -16 suppressed tumor immunity in different ways. Joint usage of inhibitors may be an effective means to improve the efficacy of glioma immunotherapy.

Prognostic power of a lipid metabolism gene panel for diffuse gliomas.

Lipid metabolism reprogramming plays important role in cell growth, proliferation, angiogenesis and invasion in cancers. However, the diverse lipid metabolism programmes and prognostic value during glioma progression remain unclear. Here, the lipid metabolism-related genes were profiled using RNA sequencing data from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) database. Gene ontology (GO) and gene set enrichment analysis (GSEA) found that glioblastoma (GBM) mainly exhibited enrichment of glycosphingolipid metabolic progress, whereas lower grade gliomas (LGGs) showed enrichment of phosphatidylinositol metabolic progress. According to the differential genes of lipid metabolism between LGG and GBM, we developed a nine-gene set using Cox proportional hazards model with elastic net penalty, and the CGGA cohort was used for validation data set. Survival analysis revealed that the obtained gene set could differentiate the outcome of low- and high-risk patients in both cohorts. Meanwhile, multivariate Cox regression analysis indicated that this signature was a significantly independent prognostic factor in diffuse gliomas. Gene ontology and GSEA showed that high-risk cases were associated with phenotypes of cell division and immune response. Collectively, our findings provided a new sight on lipid metabolism in diffuse gliomas.

RNA processing genes characterize RNA splicing and further stratify lower-grade glioma.

BACKGROUND: Aberrant expression of RNA processing genes may drive the alterative RNA profile in lower-grade gliomas (LGGs). Thus, we aimed to further stratify LGGs based on the expression of RNA processing genes. METHODS: This study included 446 LGGs from The Cancer Genome Atlas (TCGA, training set) and 171 LGGs from the Chinese Glioma Genome Atlas (CGGA, validation set). The least absolute shrinkage and selection operator (LASSO) Cox regression algorithm was conducted to develop a risk-signature. The receiver operating characteristic (ROC) curves and Kaplan-Meier curves were used to study the prognosis value of the risk-signature. RESULTS: Among the tested 784 RNA processing genes, 276 were significantly correlated with the OS of LGGs. Further LASSO Cox regression identified a 19-gene risk-signature, whose risk score was also an independently prognosis factor (P<0.0001, multiplex Cox regression) in the validation dataset. The signature had better prognostic value than the traditional factors "age", "grade" and "WHO 2016 classification" for 3- and 5-year survival both two datasets (AUCs > 85%). Importantly, the risk-signature could further stratify the survival of LGGs in specific subgroups of WHO 2016 classification. Furthermore, alternative splicing events for genes such as EGFR and FGFR were found to be associated with the risk score. mRNA expression levels for genes, which participated in cell proliferation and other processes, were significantly correlated to the risk score. CONCLUSIONS: Our results highlight the role of RNA processing genes for further stratifying the survival of patients with LGGs and provide insight into the alternative splicing events underlying this role.

Immune Cytolytic Activity Is Associated With Genetic and Clinical Properties of Glioma.

Background: Immunotherapy provided unprecedented advances in the treatment of several previously untreated cancers. However, these immunomodulatory maneuvers showed limited response to patients with glioma in clinical trials. Our aim was to depict the immune characteristics of glioma with immune cytolytic activity at genetic and transcriptome levels. Methods: In total, 325 gliomas from CGGA dataset as training cohort and 699 gliomas from TCGA dataset as validation cohort were enrolled in our analysis. We calculated the immune cytolytic activity for 1,000 of gliomas. The characteristics of immune cytolytic activity in gliomas were interpreted by the corresponding clinical, molecular genetics and radiological information. Results: We found that immune cytolytic activity was highly associated with molecular, clinical, and edema extent. High cytolytic activity gliomas were more likely to be diagnosed as glioblastoma and might be a potential marker of mesenchymal subtype. Moreover, those gliomas exhibited significantly increased copy number alterations including recurrent focal amplifications of PDGFA and EGFR, as well as recurrent deletions of CDKN2A/B. Subsequent biological function analysis revealed that the immune response and immune checkpoints expression were significantly correlated with the cytolytic activity of gliomas. Immune cytolytic activity was significantly positively associated with the extent of peri-tumor edema and was independently correlated with reduced survival time. Conclusion: Our results highlighted the immunoregulatory mechanism heterogeneity of gliomas. Cytolytic activity, indirectly reflected by the extent of peri-tumor edema, may provide a potential index to evaluate the status of immune microenvironment and immune checkpoints in glioma, which should be fully valued for precision classification and immunotherapy.

Molecular classification of IDH-mutant glioblastomas based on gene expression profiles.

Isocitrate dehydrogenase (IDH) mutant glioblastoma (GBM), accounts for ~10% GBMs, arises from lower grade diffuse glioma and preferentially appears in younger patients. Here, we aim to establish a robust gene expression-based molecular classification of IDH-mutant GBM. A total of 33 samples from the Chinese Glioma Genome Atlas RNA-sequencing data were selected as training set, and 21 cases from Chinese Glioma Genome Atlas microarray data were used as validation set. Consensus clustering identified three groups with distinguished prognostic and molecular features. G1 group, with a poorer clinical outcome, mainly contained TERT promoter wild-type and male cases. G2 and G3 groups had better prognosis differed in gender. Gene ontology analysis showed that genes enriched in G1 group were involved in DNA replication, cell division and cycle. On the basis of the differential genes between G1 and G2/G3 groups, a six-gene signature was developed with a Cox proportional hazards model. Kaplan-Meier analysis found that the acquired signature could differentiate the outcome of low- and high-risk cases. Moreover, the signature could also serve as an independent prognostic factor for IDH-mutant GBM in the multivariate Cox regression analysis. Gene ontology and gene set enrichment analyses revealed that gene sets correlated with high-risk group were involved in cell cycle, cell proliferation, DNA replication and repair. These finding highlights heterogeneity within IDH-mutant GBMs and will advance our molecular understanding of this lethal cancer.

ADAMTSL4, a Secreted Glycoprotein, Is a Novel Immune-Related Biomarker for Primary Glioblastoma Multiforme.

BACKGROUND: Researches on immunotherapy of glioblastoma multiforme (GBM, WHO grade IV) have increased exponentially in recent years. As a targeted therapy, a series of biomarkers have been identified in local tumor tissue, while circulating marker which could be detected in the body fluids is still lacking. ADAMTSL4, a secreted glycoprotein, was earlier found to play a critical role in a prognostic signature for primary GBM (pGBM). We aimed to investigate the role of ADAMTSL4 at transcriptome level and its relationship with clinical practice in pGBM. METHODS: A cohort of 88 pGBM patients with RNA-seq data from the Chinese Glioma Genome Atlas (CGGA) was analyzed, and 168 pGBM patients from TCGA were included as validation. Several bioinformatic methods and predictive tools were applied to investigate the ADAMTSL4-associated immune microenvironment status. RESULTS: We found that ADAMTSL4 was enriched in GBM (WHO grade IV), especially for those with IDH1/2 wild-type and MGMT unmethylated groups. According to the TCGA classification scheme, ADAMTSL4 can act as a potential marker for subtypes with poorer prognosis. Bioinformatic analyses revealed that ADAMTSL4 was significantly correlated to the immune-related processes in GBM (WHO grade IV), especially representing the infiltration of immune cells and complicated tumor microenvironment. Clinically, high expression of ADAMTSL4 was an independent indicator for poor prognosis. CONCLUSION: The expression of ADAMTSL4 is closely related to the clinicopathologic characteristics of pGBM. Meanwhile, it may play a critical role in immune-related processes. As a secreted glycoprotein, ADAMTSL4 is a promising circulating biomarker for pGBM, deserving further investigations.

PD-L2 expression is correlated with the molecular and clinical features of glioma, and acts as an unfavorable prognostic factor.

Background: Gliomas are aggressive tumors with various molecular and clinical characteristics and exhibit strongly resistance to radio-chemotherapy. Programmed cell death 1 ligand 2 (PD-L2) is a cell surface protein, which was reported in many cancers, modulating cancer-associated immune responses, while the role of PD-L2 in gliomas remained unclear. Herein, we aimed to investigate the biological behaviors and clinical prognostic values of PD-L2 in gliomas. Methods: Totally, we enrolled RNA sequencing data of 325 glioma samples from Chinese Glioma Genome Atlas (CGGA) as training cohort and RNA expression data of 1032 samples from The Cancer Genome Atlas (TCGA) dataset as validation cohort in this research. Then, the clinical and molecular characteristics, and the prognostic value of PD-L2 were analyzed. Results: We found that PD-L2 expression level was significantly upregulated in higher grade glioma and IDH wild-type glioma. Receiver Operating Characteristic (ROC) analysis revealed that PD-L2 was a potential indicator of mesenchymal subtype. PD-L2 exhibited tight relationship with immune response and immune-modulating process in glioma. Moreover, PD-L2 expression level could predict unfavorable prognoses of patients independent of age, grade, IDH status and 1p/19q status. Conclusions: Our study revealed that PD-L2 was closely related with inflammation and immune response. Patients with lower PD-L2 expression level tended to experience improved survival. Targeting PD-L2 may become a valuable approach for the treatment of gliomas in clinical practice.