Combination genetic signature stratifies lower-grade gliomas better than histological grade.
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ABSTRACT: We studied if combination genetic signature potentially stratifies lower-grade gliomas better than histology by investigating 214 lower-grade gliomas for IDH1/2 and TERTp mutations, 1p/19q codeletion and EGFR amplification as to their impact on prognostication. Prognostic association of grading was independent of other prognostic variables including age, histological type, IDH1/2, 1p/19q and TERTp status. No single marker, including IDH1/2, superseded grading in prognostication, indicating grading was still a very important tool. Prognosis was most favorable in 31.7% of patients with IDH1/2 mutation and either 1p/19q codeletion or TERTp mutation (IDHmut-OT), intermediate in 45.8% of patients with IDH1/2 mutation only (IDHmut) and 16.9% of patients without any of the alterations (IDHwt), and poorest in 5.6% of patients with wild-type IDH1/2 and either TERTp mutation or EGFR amplification (IDHwt-ET). Our results suggested not all IDH1/2 wild-type lower-grade gliomas are aggressive and additional biomarkers are required to identify glioblastoma-equivalent tumors. Multivariate analysis revealed independent prognostic values of grading and genetic signature. Grade II IDHwt-ET gliomas exhibited shorter survival than IDH1/2 mutated grade III gliomas, suggesting combination genetic signature potentially superseded grading in prognostication. In summary, biomarker-based stratification is useful in the diagnosis and prognostication of lower-grade gliomas, and should be used together with grading.
Project description:Unravelling the heterogeneity is the central challenge for glioma precession oncology. In this study, we extracted quantitative image features from T2-weighted MR images and revealed that the isocitrate dehydrogenase (IDH) wild type and mutant lower grade gliomas (LGGs) differed in their expression of 146 radiomic descriptors. The logistic regression model algorithm further reduced these to 86 features. The classification model could discriminate the two types in both the training and validation sets with area under the curve values of 1.0000 and 0.9932, respectively. The transcriptome-radiomic analysis revealed that these features were associated with the immune response, biological adhesion, and several malignant behaviors, all of which are consistent with biological processes that are differentially expressed in IDH wild type and IDH mutant LGGs. Finally, a prognostic signature showed an ability to stratify IDH mutant LGGs into high and low risk groups with distinctive outcomes. By extracting a large number of radiomic features, we identified an IDH mutation-specific radiomic signature with prognostic implications. This radiomic signature may provide a way to non-invasively discriminate lower-grade gliomas as with or without the IDH mutation.
Project description:Cuproptosis is the most recently discovered type of regulated cell death and is mediated by copper ions. Studies show that cuproptosis plays a significant role in cancer development and progression. Lower-grade gliomas (LGGs) are slow-growing brain tumors. The majority of LGGs progress to high-grade glioma, which makes it difficult to predict the prognosis. However, the prognostic value of cuproptosis-related genes (CRGs) in LGG needs to be further explored. mRNA expression profiles and clinical data of LGG patients were collected from public sources for this study. Univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression model were used to build a multigene signature that could divide patients into different risk groups. The differences in clinical pathological characteristics, immune infiltration characteristics, and mutation status were evaluated in risk subgroups. In addition, drug sensitivity and immune checkpoint scores were estimated in risk subgroups to provide LGG patients with precision medication. We found that all CRGs were differentially expressed in LGG and normal tissues. Patients were divided into high- and low-risk groups based on the risk score of the CRG signature. Patients in the high-risk group had a considerably lower overall survival rate than those in the low-risk group. According to functional analysis, pathways related to the immune system were enriched, and the immune state differed across the two risk groups. Immune characteristic analysis showed that the immune cell proportion and immune scores were different in the different groups. High-risk group was characterized by low sensitivity to chemotherapy but high sensitivity to immune checkpoint inhibitors. The current study revealed that the novel CRG signature was related to the prognosis, clinicopathological features, immune characteristics, and treatment perference of LGG.
Project description:Purpose of reviewLow-grade gliomas (LGG) are a group of primary brain tumors that arise from supporting glial cells. They are characterized by a mutation in the isocitrate dehydrogenase (IDH) enzyme and include astrocytomas and oligodendrogliomas. They usually affect young adults, and their main treatment consists of surgical resection, followed by radiation and chemotherapy in selected patients. This article reviews recent research on the clinical and molecular aspects of the disease and innovative therapeutic modalities in the process.Recent findingsNewly identified clinical and molecular features are currently used in the classification of LGG and applied in treatment-planning decisions. Advanced studies on the cellular level have an advanced understanding of the metabolic effects induced by IDH mutations, offering opportunities for specific targeted therapies that may improve patient outcomes. Such findings may lead to a paradigm shift in the treatment of these tumors. Although LGG are sensitive to radiation and chemotherapy, these therapies are not curative, and patient survival remains limited, raising the need for more creative and effective interventions.
Project description:BackgroundIsocitrate dehydrogenase (IDH) wildtype (wt) grade II gliomas are a rare and heterogeneous entity. Survival and prognostic factors are poorly defined.MethodsWe searched retrospectively all patients diagnosed with diffuse World Health Organization (WHO) grades II and III gliomas at our center (1989-2020).ResultsOut of 517 grade II gliomas, 47 were "diffuse astrocytomas, IDHwt." Tumors frequently had fronto-temporo-insular location (28/47, 60%) and infiltrative behavior. We found telomerase reverse transcriptase (TERT) promoter mutations (23/45, 51%), whole chromosome 7 gains (10/37, 27%), whole chromosome 10 losses (10/41, 24%), and EGFR amplifications (4/43, 9%), but no TP53 mutations (0/22, 0%). Median overall survival (OS) was 59 months (vs 19 mo for IDHwt grade III gliomas) (P < 0.0001). Twenty-nine patients (29/43, 67%) met the definition of molecular glioblastoma according to cIMPACT-NOW update 3. Median OS in this subset was 42 months, which was shorter compared with patients with IDHwt grade II gliomas not meeting this definition (median OS: 57 mo), but substantially longer compared with IDHwt grade III gliomas meeting the definition for molecular glioblastoma (median OS: 17 mo, P < 0.0001). Most patients with IDHwt grade II gliomas met cIMPACT criteria because of isolated TERT promoter mutations (16/26, 62%), which were not predictive of poor outcome (median OS: 88 mo). Actionable targets, including 5 gene fusions involving FGFR3, were found in 7 patients (24%).ConclusionsOur findings highlight the importance of histological grading and molecular profiling for the prognostic stratification of IDHwt gliomas and suggest some caution when assimilating IDHwt grade II gliomas to molecular glioblastomas, especially those with isolated TERT promoter mutation.
Project description:Metabolism and DNA methylation (DNAm) are closely linked. The value of the metabolism-DNAm interplay in stratifying glioma patients has not been explored. In the present study, we aimed to stratify lower-grade glioma (LGG) patients based on the DNAm associated with metabolic reprogramming. Four data sets of LGGs from three databases (TCGA/CGGA/GEO) were used in this study. By screening the Kendall's correlation of DNAm with 87 metabolic processes from KEGG, we identified 391 CpGs with a strong correlation with metabolism. Based on these metabolism-associated CpGs, we performed consensus clustering and identified three distinct subgroups of LGGs. These three subgroups were characterized by distinct molecular features and clinical outcomes. We also constructed a subgroup-related, quantifiable CpG signature with strong prognostic power to stratify LGGs. It also serves as a potential biomarker to predict the response to immunotherapy. Overall, our findings provide new perspectives for the stratification of LGGs and for understanding the mechanisms driving malignancy.
Project description:BackgroundLower-grade gliomas (LGGs) have more favorable outcomes than glioblastomas; however, LGGs often progress to process glioblastomas within a few years. Numerous studies have proven that the tumor microenvironment (TME) is correlated with the prognosis of glioma.MethodsLGG RNA-Sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) were extracted and then divided into training and testing cohorts, respectively. Immune-related differentially expressed genes (DEGs) were screened to establish a prognostic signature by a multivariate Cox proportional hazards regression model. The immune-related risk score and clinical information, such as age, sex, World Health Organization (WHO) grade, and isocitrate dehydrogenase 1 (IDH1) mutation, were used to independently validate and develop a prognostic nomogram. GO and KEGG pathway analyses to DEGs between immune-related high-risk and low-risk groups were performed.ResultsSixteen immune-related genes were screened for establishing a prognostic signature. The risk score had a negative correlation with prognosis, with an area under the receiver operating characteristic (ROC) curve of 0.941. The risk score, age, grade, and IDH1 mutation were identified as independent prognostic factors in patients with LGGs. The hazard ratios (HRs) of the high-risk score were 5.247 [95% confidence interval (CI) = 3.060-8.996] in the multivariate analysis. A prognostic nomogram of 1-, 3-, and 5-year survival was established and validated internally and externally. Go and KEGG pathway analyses implied that immune-related biological function and pathways were involved in the TME.ConclusionThe immune-related prognostic signature and the prognostic nomogram could accurately predict survival.
Project description:IntroductionGlioma is the most common malignant primary brain tumor with survival outcome for patients with lower-grade gliomas (LGGs) being quite variable. Epigenetic modifications in LGGs appear tightly linked to patient clinical outcomes but are not commonly used as clinical tools.AimsWe aimed to derive an epigenetic enzyme gene signature for LGGs that would allow for improved clinical risk stratification.ResultsThe study employed transcriptomic data of 711 lower-grade gliomas from three publically available data sets. Based on least absolute shrinkage and selection operator (LASSO) Cox regression analysis, we discovered a 13-gene epigenetic signature that strongly predicts poor overall survival in LGGs. The robust prediction ability for survival was further verified in two independent validation cohorts. The signature was also significantly associated with malignant molecular signatures including wild-type IDH, unmethylated MGMT promoter, and non-codeletion of 1p19q together with linkage to multiple oncogenic pathways. Interestingly, our results showed that immune infiltration of MDSCs together with mRNA expression of immune inhibition biomarkers was also positively correlated with the epigenetic signature. Lastly, we confirmed the oncogenic role of SMYD2 in glioma tumor cells in functional assays.ConclusionsWe report a novel epigenetic gene signature that harbors robust survival prediction value for LGG patients that is tightly linked to activation of multiple oncogenic pathways.
Project description:BackgroundDiffuse lower-grade gliomas (LGGs) are genetically classified into 3 distinct subtypes based on isocitrate dehydrogenase (IDH) mutation status and codeletion of chromosome 1p and 19q (1p/19q). However, the subtype-specific effects of additional genetic lesions on survival are largely unknown.MethodsUsing Cox proportional hazards regression modeling, we investigated the subtype-specific effects of genetic alterations and clinicopathological factors on survival in each LGG subtype, in a Japanese cohort of LGG cases fully genotyped for driver mutations and copy number variations associated with LGGs (n = 308). The results were validated using a dataset from 414 LGG cases available from The Cancer Genome Atlas (TCGA).ResultsIn Oligodendroglioma, IDH-mutant and 1p/19q codeleted, NOTCH1 mutations (P = 0.0041) and incomplete resection (P = 0.0019) were significantly associated with shorter survival. In Astrocytoma, IDH-mutant, PIK3R1 mutations (P = 0.0014) and altered retinoblastoma pathway genes (RB1, CDKN2A, and CDK4) (P = 0.013) were independent predictors of poor survival. In IDH-wildtype LGGs, co-occurrence of 7p gain, 10q loss, mutation in the TERT promoter (P = 0.024), and grade III histology (P < 0.0001) independently predicted poor survival. IDH-wildtype LGGs without any of these factors were diagnosed at a younger age (P = 0.042), and were less likely to have genetic lesions characteristic of glioblastoma, in comparison with other IDH-wildtype LGGs, suggesting that they likely represented biologically different subtypes. These results were largely confirmed in the cohort of TCGA.ConclusionsSubtype-specific genetic lesions can be used to stratify patients within each LGG subtype. enabling better prognostication and management.
Project description:Background: Mutations in isocitrate dehydrogenase (IDH) affect the development and prognosis of gliomas. We investigated the role of IDH mutations in the regulation of immune phenotype in lower-grade gliomas (LGGs).Method and patients: A total of 1,008 cases with clinical and IDH mutation data from five cohorts were enrolled. Samples with RNA sequencing data from the Chinese Glioma Genome Atlas (CGGA) were used as training set, whereas RNA data from the Cancer Genome Atlas, Repository for Molecular Brain Neoplasia, GSE16011, and CGGA microarray databases were used for validation. R language tools and bioinformatics analysis were used for gene signature construction and biological function annotation.Results: We found that IDH mutations caused down-regulation of local immune response as among 332 immune system-related genes, 196(59.0%) were differentially expressed according to IDH mutation status. Nearly 70% of those differentially expressed genes exhibited prognostic value in LGGs. An immune response-based gene signature was constructed that distinguished cases with high- or low-risk of unfavorable prognosis and remained an independent prognostic factor in multivariate analyses in both training and validation cohorts. Samples from high-risk cases exhibited elevated expression of genes involved in immune response and NF-?B pathway activation. Furthermore, we found a strong correlation between the risk score and T cells, macrophage-related immune response, and expression of several prominent immune checkpoints.Conclusion: Our results indicated that mutant IDH is highly associated with the regulation of the immune microenvironment in LGGs. The observed immune system gene signature, which was sensitive to IDH mutation status, efficiently predicted patient survival.
Project description:Background: Lower-grade glioma (LGG) is the most common histology identified in gliomas, a heterogeneous tumor that may develop into high-grade malignant glioma that seriously shortens patient survival time. Recent studies reported that glutamatergic synapses might play an essential role in the progress of gliomas. However, the role of glutamatergic synapse-related biomarkers in LGG has not been systemically researched yet. Methods: The mRNA expression data of glioma and normal brain tissue were obtained from The Cancer Genome Atlas database and Genotype-Tissue Expression, respectively, and the Chinese Glioma Genome Atlas database was used as a validation set. Difference analysis was performed to evaluate the expression pattern of glutamatergic synapse-related genes (GSRGs) in LGG. The least absolute shrinkage and selection operator (LASSO) Cox regression was applied to construct the glutamatergic synapse-related risk signature (GSRS), and the risk score of each LGG sample was calculated based on the coefficients and expression value of selected GSRGs. Univariate and multivariate Cox regression analyses were used to investigate the prognostic value of risk score. Immunity profile and single-sample gene set enrichment analysis (ssGSEA) were performed to explore the association between risk score and the characters of tumor microenvironment in LGG. Gene set variation analysis (GSVA) was performed to investigate the potential pathways related to GSRS. The HPA database and real-time PCR were used to identify the expression of hub genes identified in GSRS. Results: A total of 22 genes of 39 GSRGs were found differentially expressed among normal and LGG samples. Through the LASSO algorithm, 14-genes GSRS constructed were associated with the prognosis and clinicopathological features of patients with LGG. Furthermore, the risk score level was significantly positively correlated with the infiltrating level of immunosuppressive cells, including M2 macrophages and regulatory T cells. GSVA identified a series of cancer-related pathways related to GSRS, such as P13K-AKT and P53 pathways. Moreover, ATAD1, NLGN2, OXTR, and TNR, hub genes identified in GSRS, were considered as potential prognostic biomarkers in LGG. Conclusion: A 14-genes GSRS was constructed and verified in this study. We provided a novel insight into the role of GSRS in LGG through a series of bioinformatics methods.