Tumor microenvironment remodeling plus immunotherapy could be used in mesenchymal-like tumor with high tumor residual and drug resistant rate.

Epithelial-mesenchymal transition (EMT) is a common process during tumor progression and is always related to residual tumor, drug resistance and immune suppression. However, considering the heterogeneity in EMT process, there is still a need to establish robust EMT classification system with reasonable molecular, biological and clinical implications to investigate whether these unfavorable survival factors are common or unique in different individuals. In our work, we classify tumors with four EMT status, that is, EMTlow, EMTmid, EMThigh-NOS (Not Otherwise Specified), and EMThigh-AKT (AKT pathway overactivation) subtypes. We find that EMThigh-NOS subtype is driven by intrinsic somatic alterations. While, EMThigh-AKT subtype is maintained by extrinsic cellular interplay between tumor cells and macrophages in an AKT-dependent manner. EMThigh-AKT subtype is both unresectable and drug resistant while EMThigh-NOS subtype can be treated with cell cycle related drugs. Importantly, AKT activation in EMThigh-AKT not only enhances EMT process, but also contributes to the immunosuppressive microenvironment. By remodeling tumor immune-microenvironment by AKT inhibition, EMThigh-AKT can be treated by immune checkpoint blockade therapies. Meanwhile, we develop TumorMT website ( http://tumormt.neuroscience.org.cn/ ) to apply this EMT classification and provide reasonable therapeutic guidance.

Dissecting multifunctional roles of forkhead box transcription factor D1 in cancers.

As a member of the forkhead box (FOX) family of transcription factors (TF), FOXD1 has recently been implicated as a crucial regulator in a variety of human cancers. Accumulating evidence has established dysregulated and aberrant FOXD1 signaling as a prominent feature in cancer development and progression. However, there is a lack of systematic review on this topic. Here, we summarized the present understanding of FOXD1 functions in cancer biology and reviewed the downstream targets and upstream regulatory mechanisms of FOXD1 as well as the related signaling pathways within the context of current reports. We highlighted the functional features of FOXD1 in cancers to identify the future research consideration of this multifunctional transcription factor and potential therapeutic strategies targeting its oncogenic activity.

Cancer cell intrinsic TIM-3 induces glioblastoma progression.

Glioblastoma (GBM) is identified to share common signal pathways between glioma and immune cells. Here, we find that T cell immunoglobulin domain and mucin domain protein 3 (TIM-3) is one of the most common co-inhibitory immune checkpoints in GBM shared by tumor and non-tumor cells. Glioma cell-intrinsic TIM-3 is involved in not only regulating malignant behaviors of glioma cells but also inducing macrophage migration and transition to anti-inflammatory/pro-tumorigenic phenotype by a TIM-3/interleukin 6 (IL6) signal. In mechanism, as one of the major regulators of IL6, TIM-3 regulates its expression through activating NF-κB. Blocking this feedback loop by Tocilizumab, an IL6R inhibitor, inhibited the above effects and repressed the tumorigenicity of GBM in vivo. Our work identifies glioma cell-intrinsic functions of TIM-3/IL6 signal mediating the crosstalk feedback loop between glioma cells and tumor-associated macrophages (TAMs). Blocking this feedback loop may provide a novel therapeutic strategy for GBM.

Molecular profiling identifies distinct subtypes across TP53 mutant tumors.

Tumor protein 53 mutation (TP53mut) is one of the most important driver events facilitating tumorigenesis, which could induce a series of chain reactions to promote tumor malignant transformation. However, the malignancy progression patterns under TP53 mutation remain less known. Clarifying the molecular landscapes of TP53mut tumors will help us understand the process of tumor development and aid precise treatment. Here, we distilled genetic and epigenetic features altered in TP53mut cancers for cluster-of-clusters analysis. Using integrated classification, we derived 5 different subtypes of TP53mut patients. These subtypes have distinct features in genomic alteration, clinical relevance, microenvironment dysregulation, and potential therapeutics. Among the 5 subtypes, COCA3 was identified as the subtype with worst prognosis, causing an immunosuppressive microenvironment and immunotherapeutic resistance. Further drug efficacy research highlighted olaparib as the most promising therapeutic agents for COCA3 tumors. Importantly, the therapeutic efficacy of olaparib in COCA3 and immunotherapy in non-COCA3 tumors was validated via in vivo experimentation. Our study explored the important molecular events and developed a subtype classification system with distinct targeted therapy strategies for different subtypes of TP53mut tumors. These multiomics classification systems provide a valuable resource that significantly expands the knowledge of TP53mut tumors and may eventually benefit in clinical practice.

Ferroptosis, as the most enriched programmed cell death process in glioma, induces immunosuppression and immunotherapy resistance.

BACKGROUND: Immunosuppressive microenvironment is a major cause of immunotherapeutic resistance in glioma. In addition to secreting compounds, tumor cells under programmed cell death (PCD) processes release abundant mediators to modify the neighboring microenvironment. However, the complex relationship among PCD status, immunosuppressive microenvironment, and immunotherapy is still poorly understood. METHODS: Four independent glioma cohorts comprising 1,750 patients were enrolled for analysis. The relationships among PCD status, microenvironment cellular components, and biological phenotypes were fully explored. Tissues from our hospital and experiments in vitro and in vivo were used to confirm the role of ferroptosis in glioma. RESULTS: Analyses to determine enriched PCD processes showed that ferroptosis was the main type of PCD in glioma. Enriched ferroptosis correlated with progressive malignancy, poor outcomes, and aggravated immunosuppression in glioblastoma (GBM) patients. Enhanced ferroptosis was shown to induce activation and infiltration of immune cells but attenuated antitumor cytotoxic killing. Tumor-associated macrophages (TAMs) were found to participate in ferroptosis-mediated immunosuppression. Preclinically, ferroptosis inhibition combined with Programmed Cell Death 1 (PD-1) and Programmed Cell Death Ligand-1 (PD-L1) blockade generated a synergistic therapeutic outcome in GBM murine models. CONCLUSIONS: This work provides a molecular, clinical, and biological landscape of ferroptosis, suggesting a role of ferroptosis in glioma malignancy and a novel synergic immunotherapeutic strategy that combines immune checkpoint blockade treatment with ferroptosis inhibition.

Dual role of ARPC1B in regulating the network between tumor-associated macrophages and tumor cells in glioblastoma.

The tumor microenvironment (TME) plays a critical role in promoting the growth and metastasis of glioblastoma (GBM). Tumor-associated macrophages (TAMs), the most abundant myeloid cells infiltrating in TME, produce proinflammatory cytokines, regulate glioma cell pools, and lead to GBM progression. Understanding the mechanism of GBM-TAMs regulation can help to find new targeted therapeutic strategies against GBM. Based on the CGGA and TCGA GBM cohorts, ARPC1B was defined as the key macrophage-associated gene with prognostic value. Higher ARPC1B expression was associated with progressive malignancy, poor outcomes and TAM infiltration. We demonstrated that macrophage-expressed ARPC1B promoted the migration, invasion, and epithelial-mesenchymal transition of glioma cells. Glioma-intrinsic ARPC1B also maintained the malignant phenotype and promoted macrophage recruitment. Positive feedback signaling between macrophages and glioma cells via ARPC1B was determined to be under control of the IFNγ-IRF2-ARPC1B axis. This study highlights the important role of ARPC1B in GBM malignancy progression and the regulation network between GBM and TAMs, suggesting ARPC1B as a novel biomarker with potential therapeutic implications.

Genome profiling of mismatch repair genes in eight types of tumors.

Mismatch repair (MMR) plays an important role in the occurrence and development of tumors. At present, it is widely believed that MMR is a protective mechanism of tumors that plays a critical role in the progresses of cancer. In this study, 34 genes related to MMR selected from Gene Ontology (GO) database were scored by single sample Gene sets enrichment analysis (ssGSEA), and eight cancers were screened from 23 TCGA solid cancers to investigate the clinical significance of MMR score. MMR had different effects on the prognosis of the eight tumors, with a protective effect in three cancers and functioning as a risk factor in the remaining five cancers. We used unsupervised clustering to divide the patients into four clusters. We found that the immune and metabolic status of the four clusters were extremely different, among which cluster1 had the lowest tumor purity and the most complex microenvironment; this may explain its poor prognosis and immunotherapy effect. In summary, MMR scores can improve the predictive ability and provide effective guidance for immunotherapy in individual type of tumors.

Characterization of an endoplasmic reticulum stress-related signature to evaluate immune features and predict prognosis in glioma.

Endoplasmic reticulum (ER) stress has considerable impact on cell growth, proliferation, metastasis, invasion, angiogenesis and chemoradiotherapy resistance in various cancers. However, the effect of ER stress on the outcomes of glioma patients remains unclear. In this study, we established an ER stress risk model based on The Cancer Genome Atlas (TCGA) glioma data set to reflect immune characteristics and predict the prognosis of glioma patients. Survival analysis indicated that there were significant differences in the overall survival (OS) of glioma patients with different ER stress-related risk scores. Moreover, the ER stress-related risk signature, which was markedly associated with the clinicopathological properties of glioma patients, could serve as an independent prognostic indicator. Functional enrichment analysis revealed that the risk model correlated with immune and inflammation responses, as well as biosynthesis and degradation. In addition, the ER stress-related risk model indicated an immunosuppressive microenvironment. In conclusion, we present an ER stress risk model that is an independent prognostic factor and indicates the general immune characteristics in the glioma microenvironment.

LOXL2 Upregulation in Gliomas Drives Tumorigenicity by Activating Autophagy to Promote TMZ Resistance and Trigger EMT.

Glioma is the most prevalent primary brain tumor in adults and has an extremely unfavorable prognosis. As a member of the lysyl oxidase (LOX) family, lysyl-oxidase-like-2 (LOXL2) is known to play different roles in different tumors. However, the role of LOXL2 in glioma has not yet been fully elucidated. In the present study, we detected that LOXL2 was considerably upregulated in glioma and that LOXL2 upregulation was evidently related to glioma WHO grade, malignant molecular subtypes, and poor prognosis in glioma patients. Additionally, we found that LOXL2 not only promoted glioma cells proliferation, migration, invasion, and induced the epithelial-to-mesenchymal transition (EMT) process, but also reduced the sensitivity of glioma cells to temozolomide (TMZ). Furthermore, we identified that LOXL2 reduced TMZ sensitivity and induced EMT in glioma via the activation of autophagy. Mechanistically, LOXL2 enhanced Atg7 expression by promoting the phosphorylation of Erk1/2, leading to the activation of autophagy and regulation of EMT process and TMZ sensitivity through autophagy. Our study describes an LOXL2-Erk1/2-Atg7 signaling axis that influences glioma EMT and chemosensitivity through autophagy; moreover, LOXL2 may serve as a promising therapeutic target in the treatment of glioma.

Characterization of ROS Metabolic Equilibrium Reclassifies Pan-Cancer Samples and Guides Pathway Targeting Therapy.

Background: Abnormal redox equilibrium is a major contributor to tumor malignancy and treatment resistance. Understanding reactive oxygen species (ROS) metabolism is a key to clarify the tumor redox status. However, we have limited methods to evaluate ROS in tumor tissues and little knowledge on ROS metabolism across human cancers. Methods: The Cancer Genome Atlas multi-omics data across 22 cancer types and the Genomics of Drug Sensitivity in Cancer data were analyzed in this study. Cell viability testing and xenograft model were used to validate the role of ROS modulation in regulating treatment efficacy. Results: ROS indexes reflecting ROS metabolic balance in five dimensions were developed and verified. Based on the ROS indexes, we conducted ROS metabolic landscape across 22 cancer types and found that ROS metabolism played various roles in different cancer types. Tumor samples were classified into eight ROS clusters with distinct clinical and multi-omics features, which was independent of their histological origin. We established a ROS-based drug efficacy evaluation network and experimentally validated the predicted effects, suggesting that modulating ROS metabolism improves treatment sensitivity and expands drug application scopes. Conclusion: Our study proposes a new method in evaluating ROS status and offers comprehensive understanding on ROS metabolic equilibrium in human cancers, which provide practical implications for clinical management.

Secretory Pathway Kinase FAM20C, a Marker for Glioma Invasion and Malignancy, Predicts Poor Prognosis of Glioma.

PURPOSE: Glioblastoma (GBM) is the most lethal primary cancer in adult central nervous system, and new strategies are desperately needed. The secretory pathway kinase or kinase-like proteins (SPKKPs) have been shown to mediate multiple physiological functions by phosphorylating extracellular proteins and proteoglycans. However, their roles in cancers, especially GBM, remain poorly defined. METHODS: The least absolute shrinkage and selection operator (LASSO) regression was employed for establishing the SPKKPs signature for IDH wild type (wt) GBM prognosis. Integrative analyses with multiple datasets were employed to identify the core member of this gene family in glioma. The receiver operator characteristic (ROC) curves and immunohistochemistry were further used for evaluating its association with progressive malignancy in glioma and GBM patients' survival, respectively. Gene set enrichment analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to interpret its functions in GBM, which were further verified in vitro. RESULTS: A SPKKPs classifier was constructed with 3 genes of this family. This signature could effectively distinguish IDH wt GBM survival. Family with sequence similarity 20 C (FAM20C) was further identified as the core member of this family in glioma. Elevated FAM20C expression was not only closely correlated with glioma malignancy progression and the mesenchymal subtype of GBM but also indicated unfavorable survival of GBM patients. FAM20C was also found to be associated with the disrupted immune response in GBM microenvironment and was required for the migration of glioma and immune cells. CONCLUSION: These data indicate that the potential of FAM20C serving as a predictive molecule and a therapeutic target for GBM.

Profiling pro-neural to mesenchymal transition identifies a lncRNA signature in glioma.

BACKGROUND: Molecular classification has laid the framework for exploring glioma biology and treatment strategies. Pro-neural to mesenchymal transition (PMT) of glioma is known to be associated with aggressive phenotypes, unfavorable prognosis, and treatment resistance. Recent studies have highlighted that long non-coding RNAs (lncRNAs) are key mediators in cancer mesenchymal transition. However, the relationship between lncRNAs and PMT in glioma has not been systematically investigated. METHODS: Gene expression profiles from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), GSE16011, and Rembrandt with available clinical and genomic information were used for analyses. Bioinformatics methods such as weighted gene co-expression network analysis (WGCNA), gene set enrichment analysis (GSEA), Cox analysis, and least absolute shrinkage and selection operator (LASSO) analysis were performed. RESULTS: According to PMT scores, we confirmed that PMT status was positively associated with risky behaviors and poor prognosis in glioma. The 149 PMT-related lncRNAs were identified by WGCNA analysis, among which 10 (LINC01057, TP73-AS1, AP000695.4, LINC01503, CRNDE, OSMR-AS1, SNHG18, AC145343.2, RP11-25K21.6, RP11-38L15.2) with significant prognostic value were further screened to construct a PMT-related lncRNA risk signature, which could divide cases into two groups with distinct prognoses. Multivariate Cox regression analyses indicated that the signature was an independent prognostic factor for high-grade glioma. High-risk cases were more likely to be classified as the mesenchymal subtype, which confers enhanced immunosuppressive status by recruiting macrophages, neutrophils, and regulatory T cells. Moreover, six lncRNAs of the signature could act as competing endogenous RNAs to promote PMT in glioblastoma. CONCLUSIONS: We profiled PMT status in glioma and established a PMT-related 10-lncRNA signature for glioma that could independently predict glioma survival and trigger PMT, which enhanced immunosuppression.

IFI30 Is a Novel Immune-Related Target with Predicting Value of Prognosis and Treatment Response in Glioblastoma.

PURPOSE: As a crucial part of anti-tumor immunotherapy, interferon-α/ß (IFN-α/ß) treatment has been broadly applied to clinical trials of glioma. However, less is known about implement of interferon-γ (IFN-γ) in glioma. Further investigating the valuable hub molecular of IFN-γ family might provide us a novel guidance for glioma therapy. METHODS: This study carried out an analysis on glioma patients from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) cohorts. The analyses were performed by GraphPad Prism 8 and R language. All the validated experiments were performed three times independently. RESULTS: We identified IFI30 as the most stable independent prognostic gene among 20 classical IFN-γ stimulated genes (ISGs) in glioma patients. Furthermore, we found that IFI30 highly expressed in malignant subtypes of glioma and associated with chemotherapy response. We also found IFI30 could activate IL6-STAT6 signal pathway to decline the glioma cells' chemotherapy sensitivity by performing experiments. Gene ontology (GO) analysis showed IFI30 associated with enhanced leucocyte mediated immune and inflammatory response. Microenvironment analysis referred that high IFI30 expression accompanied with more infiltration of M2 type macrophages. CONCLUSION: IFI30 is involved in the malignant progression and chemotherapy response of glioblastoma, which can be a potential target for treatment in glioblastoma patients.

A risk signature with four autophagy-related genes for predicting survival of glioblastoma multiforme.

Glioblastoma multiforme (GBM) is a devastating brain tumour without effective treatment. Recent studies have shown that autophagy is a promising therapeutic strategy for GBM. Therefore, it is necessary to identify novel biomarkers associated with autophagy in GBM. In this study, we downloaded autophagy-related genes from Human Autophagy Database (HADb) and Gene Set Enrichment Analysis (GSEA) website. Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis were performed to identify genes for constructing a risk signature. A nomogram was developed by integrating the risk signature with clinicopathological factors. Time-dependent receiver operating characteristic (ROC) curve and calibration plot were used to evaluate the efficiency of the prognostic model. Finally, four autophagy-related genes (DIRAS3, LGALS8, MAPK8 and STAM) were identified and were used for constructing a risk signature, which proved to be an independent risk factor for GBM patients. Furthermore, a nomogram was developed based on the risk signature and clinicopathological factors (IDH1 status, age and history of radiotherapy or chemotherapy). ROC curve and calibration plot suggested the nomogram could accurately predict 1-, 3- and 5-year survival rate of GBM patients. For function analysis, the risk signature was associated with apoptosis, necrosis, immunity, inflammation response and MAPK signalling pathway. In conclusion, the risk signature with 4 autophagy-related genes could serve as an independent prognostic factor for GBM patients. Moreover, we developed a nomogram based on the risk signature and clinical traits which was validated to perform better for predicting 1-, 3- and 5-year survival rate of GBM.

Elevated lymphocyte specific protein 1 expression is involved in the regulation of leukocyte migration and immunosuppressive microenvironment in glioblastoma.

Immune cell infiltration mediates therapeutic response to immune therapies. The investigation on the genes regulating leukocyte migration may help us to understand the mechanisms regulating immune cell infiltration in tumor microenvironment. Here, we collected the data from Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) to analyze the expression of leukocyte migration related genes in glioblastoma (GBM). Lymphocyte specific protein 1 (LSP1) was identified as the only gene in this family which not only has an elevated expression, but also serve as an independent predictive factor for progressive malignancy in glioma. We further confirmed these results in clinical glioma samples by quantitative PCR, immunofluorescence, immunohistochemistry, and western blot. Moreover, LSP1 expression was closely related to the response to radio- and chemotherapy in GBM, and positively correlated with immunosuppressive cell populations, including M2 macrophages, neutrophil, and regulatory T cell. Additionally, elevated LSP-1 expression enhanced the expression of immunosuppression related genes like programmed cell death 1 (PD1) and leukocyte associated immunoglobulin like receptor 1 (LAIR1) in macrophages. LSP1 also promoted the migration of macrophages. Together, our study suggests a novel role of LSP1 contributing to immunosuppressive microenvironment in GBM and serving as a potential therapeutic target for it.

Identification of a Five-Pseudogene Signature for Predicting Survival and Its ceRNA Network in Glioma.

Background: Glioma is the most common primary brain tumor with a dismal prognosis. It is urgent to develop novel molecular biomarkers and conform to individualized schemes. Methods: Differentially expressed pseudogenes between low grade glioma (LGG) and glioblastoma multiforme (GBM) were identified in the training cohort. Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox proportional hazards regression analyses were used to select pseudogenes associated with prognosis of glioma. A risk signature was constructed based on the selected pseudogenes for predicting the survival of glioma patients. A pseudogene-miRNA-mRNA regulatory network was established and visualized using Cytoscape 3.5.1. Gene Oncology (GO) and signaling pathway analyses were performed on the targeted genes to investigate functional roles of the risk signature. Results: Five pseudogenes (ANXA2P2, EEF1A1P9, FER1L4, HILS1, and RAET1K) correlating with glioma survival were selected and used to establish a risk signature. Time-dependent receiver operating characteristic (ROC) curves revealed that the risk signature could accurately predict the 1, 3, and 5-year survival of glioma patients. GO and signaling pathway analyses showed that the risk signature was involved in regulation of proliferation, migration, angiogenesis, and apoptosis in glioma. Conclusions: In this study, a risk signature with five pseudogenes was constructed and shown to accurately predict 1-, 3-, and 5-year survival for glioma patient. The risk signature may serve as a potential target against glioma.

Integrin Beta 5 Is a Prognostic Biomarker and Potential Therapeutic Target in Glioblastoma.

Background: Glioblastoma (GBM) is the most lethal cancer of the central nervous system. Integrin beta 5 (ITGB5) is thought to be involved in intercellular signal transduction and regulation of tumor initiation and progression. However, the function of ITGB5 in GBM is not known. Methods: To address this question, we evaluated the expression level of ITGB5 in clinical specimens by immunohistochemistry and western blotting, as well as the association between ITGB5 expression and GBM patient survival using data from Chinese Glioma Genome Atlas and The Cancer Genome Atlas. The biological function of ITGB5 in GBM was investigated by Gene Ontology, gene set enrichment, and in vitro loss-of-function experiments using glioma cells. Results: Among integrin family members, ITGB5 showed the greatest difference in expression between low-grade glioma and GBM. Elevated ITGB5 expression was highly correlated with glioma progression and a mesenchymal subtype and poor survival in GBM patients. ITGB5 was found to be associated with regulation of the immune response and angiogenesis in GBM, and was required for migration and invasion of glioma cells and tube formation by endothelial cells. Conclusions: These data indicate that ITGB5 can serve as a predictive biomarker for GBM patient survival and is a potential therapeutic target in GBM treatment.

Long non-coding RNA, HOTAIRM1, promotes glioma malignancy by forming a ceRNA network.

Long non-coding RNAs play critical roles in tumorigenesis and the immune process. In this study, RNA sequencing data for 946 glioma samples from The Cancer Genome Atlas and the Chinese Glioma Genome Atlas databases were analyzed to evaluate the prognostic value and function of homeobox A transcript antisense RNA myeloid-specific (HOTAIRM)1. HOTAIRM1 expression was associated with clinical and molecular features of glioma: patients with high HOTAIRM1 expression were more likely to be classified as malignant cases, and elevated HOTAIRM1 level was associated with shorter survival time in subgroups stratified by clinical and molecular features. A multivariate Cox regression analysis showed that HOTAIRM1 was an independent prognostic factor for patient outcome. In vitro experiments revealed that HOTAIRM1 knockdown suppressed the malignant behavior of glioma and increased tumor sensitivity to temozolomide. The results of an in silico analysis indicated that HOTAIRM1 promotes the malignancy of glioma by acting as a sponge for microRNA (miR)-129-5p and miR-495-3p. HOTAIRM1 overexpression was also associated with immune activation characterized by enhanced T cell-mediated immune and inflammatory responses. These results suggest that HOTAIRM1 is a prognostic biomarker and potential therapeutic target in glioma.

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

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

Development and validation of an interferon signature predicting prognosis and treatment response for glioblastoma.

Background: Interferon treatment, as an important approach of anti-tumor immunotherapy, has been implemented in multiple clinical trials of glioma. However, only a small number of gliomas benefit from it. Therefore, it is necessary to investigate the clinical role of interferons and to establish robust biomarkers to facilitate its application. Materials and methods: This study reviewed 1,241 glioblastoma (GBM) and 1,068 lower grade glioma (LGG) patients from six glioma cohorts. The transcription matrix and clinical information were analyzed using R software, GraphPad Prism 7 and Medcalc, etc. Immunohistochemical (IHC) staining were performed for validation in protein level. Results: Interferon signaling was significantly enhanced in GBM. An interferon signature was developed based on five interferon genes with prognostic significance, which could reflect various interferon statuses. Survival analysis showed the signature could serve as an unfavorable prognostic factor independently. We also established a nomogram model integrating the risk signature into traditional prognostic factors, which increased the validity of survival prediction. Moreover, high-risk group conferred resistance to chemotherapy and high IFNB1 expression levels. Functional analysis showed that the high-risk group was associated with overloaded immune response. Microenvironment analysis and IHC staining found that high-risk group occupied a disorganized microenvironment which was characterized by an enrichment of M0 macrophages and neutrophils, but less infiltration of activated nature killing (NK) cells and M1 type macrophages. Conclusion: This interferon signature was an independent indicator for unfavorable prognosis and showed great potential for screening out patients who will benefit from chemotherapy and interferon treatment.