A nuclear transport-related gene signature combined with IDH mutation and 1p/19q codeletion better predicts the prognosis of glioma patients

Abstract

Background: The nuclear transport system has been proposed to be indispensable for cell proliferation and invasion in cancers. Prognostic biomarkers and molecular targets in nuclear transport systems have been developed. However, no systematic analysis of genes related to nuclear transport in gliomas has been performed. An integrated prognostic classification involving mutation and nuclear transport gene signatures has not yet been explored.

Methods: In the present study, we analyzed gliomas from a training cohort (TCGA dataset, n = 660) and validation cohort (CGGA dataset, n = 668) to develop a prognostic nuclear transport gene signature and generate an integrated classification system. Gene set enrichment analysis (GSEA) showed that glioblastoma (GBM) was mainly enriched in nuclear transport progress compared to lower-grade glioma (LGG). Then, we developed a nuclear transport risk score (NTRS) for gliomas with a training cohort. NTRS was significantly correlated with clinical and genetic characteristics, including grade, age, histology, IDH status and 1p/19q codeletion, in the training and validation cohorts.

Results: Survival analysis revealed that patients with a higher NTRS exhibited shorter overall survival. NTRS showed better prognostic value compared to classical molecular markers, including IDH status and 1p/19q codeletion. Furthermore, univariate and multivariate analyses indicated that NTRS was an independent prognostic factor for gliomas. Enrichment map and Gene Ontology analysis demonstrated that signaling pathways related to the cell cycle were enriched in the NTRS^High group. Subgroup survival analysis revealed that NTRS could differentiate the outcomes of low- and high-risk patients with wild-type IDH or mutant IDH and 1p/19q non-codeletion.

Conclusions: NTRS is associated with poor outcomes and could be an independent prognostic marker in diffuse gliomas. Prognostic classification combined with IDH mutation, 1p/19q codeletion and NTRS could better predict the survival of glioma patients.

Keywords: CGGA; Classification; Gene signature; Gliomas; Nuclear transport; Prognosis; TCGA.

Fig. 1

Identification of the 7-gene nuclear transport risk score (NTRS) via LASSO regression analysis in TCGA datasets. a Gene set enrichment analysis (GSEA) of nuclear transport between LGG and GBM in the training and validation datasets. NES: normalized enrichment score. b Development pipeline of NTRS. c Cross-validation with the TCGA dataset. d Coefficient values of the seven genes by LASSO. e Heatmap of Pearson correlation coefficient(r) of seven genes. Correlation between 7 genes was significant (P < 0.001)

Fig. 2

Association of NTRS and clinicopathological characteristics. a The distribution and association of NTRS and clinical or genetic characteristics in the training set (n = 660). b The distribution of NTRS in patients stratified by WHO grade, age, IDH status and 1p/19q status in the validation set. ^*P < 0.05; ^**P < 0.01; ^***P < 0.001

Fig. 3

Prognostic significance of NTRS in glioma patients. a The cut-off value was determined by ROC analysis. Patients with a higher NTRS (> = 0.078) were classified as the NTRS^High group, and those with a lower NTRS (< 0.078) were classified as the NTRS^Low group. b survival analysis of glioma patients with a high NTRS (NTRS^High) versus low NTRS (NTRS^Low) in the training set and validation set. The hazard ratio was determined by the Mantel-Haenszel method, and the P value was determined by the chi-square test between the two groups. c, d Prognostic efficiency of NTRS in patients with different grades and subgroups. e ROC curves of the prediction of 2-year survival with NTRS and other markers in the training set and validation set

Fig. 4

High NTRS gliomas exhibit accelerated cell cycle and enhanced immune responses. a Enrichment map of high NTRS group (n = 269) versus low NTRS group (n = 391). b Representative cell cycle related gene-sets in (a). c GO analysis of differentially expressed genes between low- and high-risk patients. d mRNA expression of cell cycle genes was detected in LN229 cells over-expressing indicated NTRS related genes

Fig. 5

Prediction of prognosis with NTRS in cohorts stratified by WHO grade, IDH mutation and 1p/19q codeletion status. a Distribution of glioma patients with low and high NTRS in the indicated subgroups classified by WHO grade, IDH mutation and 1p/19q codeletion status. b Survival analysis was performed in glioma patients of (a) with a high NTRS versus low NTRS

Fig. 6

NTRS is a prognostic marker for molecular classification combined with IDH mutation and 1p/19q codeletion. a, b Overall survival analysis of glioma patients with the indicated mutations in the training set (TCGA for a) and validation sets (CGGA for b and Grevendeel for c). d Proposed prognostic classification for glioma combining IDH mutation, 1p/19q codeletion and NTRS. The variation in color from green to red represents the patients’ outcome from good to poor