We aimed to summarize the clinicopathological characteristics and prognostic features of various molecular subtypes of diffuse gliomas (DGs) in the Chinese population.

In total, 1,418 patients diagnosed with DG between 2011 and 2017 were classified into 5 molecular subtypes according to the 2016 WHO classification of central nervous system tumors. The IDH mutation status was determined by immunohistochemistry and/or DNA sequencing, and 1p/19q codeletion was detected with fluorescence in situ hybridization. The median clinical follow-up time was 1,076 days. T-tests and chi-square tests were used to compare clinicopathological characteristics. Kaplan-Meier and Cox regression methods were used to evaluate prognostic factors.

Our cohort included 15.5% lower-grade gliomas, IDH-mutant and 1p/19q-codeleted (LGG-IDHm-1p/19q); 18.1% lower-grade gliomas, IDH-mutant (LGG-IDHm); 13.1% lower-grade gliomas, IDH-wildtype (LGG-IDHwt); 36.1% glioblastoma, IDH-wildtype (GBM-IDHwt); and 17.2% glioblastoma, IDH-mutant (GBM-IDHm). Approximately 63.3% of the enrolled primary gliomas, and the median overall survival times for LGG-IDHm, LGG-IDHwt, GBM-IDHwt, and GBM-IDHm subtypes were 75.97, 34.47, 11.57, and 15.17 months, respectively. The 5-year survival rate of LGG-IDHm-1p/19q was 76.54%. We observed a significant association between high resection rate and favorable survival outcomes across all subtypes of primary tumors. We also observed a significant role of chemotherapy in prolonging overall survival for GBM-IDHwt and GBM-IDHm, and in prolonging post-relapse survival for the 2 recurrent GBM subtypes.

By controlling for molecular subtypes, we found that resection rate and chemotherapy were 2 prognostic factors associated with survival outcomes in a Chinese cohort with DG.

Lower grade gliomas (LGGs), classified as World Health Organization (WHO) grade Ⅱ and grade Ⅲ gliomas, comprise a heterogeneous group with a median survival time ranging from 4–13 years. Accurate prediction of the survival times of LGGs remains a major challenge in clinical practice.

We reviewed the expression data of 865 LGG patients from 5 transcriptomics cohorts. The comparative profile of immune genes was analyzed for signature identification and validation. In-house RNAseq and microarray data from the Chinese Glioma Genome Atlas (CGGA) dataset were used as training and internal validation cohorts, respectively. The samples from The Cancer Genome Atlas (TCGA) and GSE16011 cohorts were used as external validation cohorts, and the real-time PCR of frozen LGG tissue samples (n = 36) were used for clinical validation.

A total of 2,214 immune genes were subjected to pairwise comparison to generate 2,449,791 immune-related gene pairs (IGPs). A total of 402 IGPs were identified with prognostic values for LGGs. The HOXA9-related and CRH-related scores facilitated identification of patients with different prognoses. An immune signature based on 10 IGPs was constructed to stratify patients into low and high risk groups, exhibiting different clinical outcomes. A nomogram, combining immune signature, 1p/19q status, and tumor grade, was able to predict the overall survival (OS) with c-indices of 0.85, 0.80, 0.80, 0.79, and 0.75 in the training, internal validation, external validation, and tissue sample cohorts, respectively.

This study was the first to report a comparative profiling of immune genes in large LGG cohorts. A promising individualized immune signature was developed to estimate the survival time for LGG patients.