COVPRIG robustly predicts the overall survival of IDH wild-type glioblastoma and highlights METTL1+ neural-progenitor-like tumor cell in driving unfavorable outcome

Abstract

Abstract Background Accurately predicting the outcome of isocitrate dehydrogenase (IDH) wild-type glioblastoma (GBM) remains hitherto challenging. This study aims to Construct and Validate a Robust Prognostic Model for IDH wild-type GBM (COVPRIG) for the prediction of overall survival using a novel metric, gene–gene (G × G) interaction, and explore molecular and cellular underpinnings. Methods Univariate and multivariate Cox regression of four independent trans-ethnic cohorts containing a total of 800 samples. Prediction efficacy was comprehensively evaluated and compared with previous models by a systematic literature review. The molecular underpinnings of COVPRIG were elucidated by integrated analysis of bulk-tumor and single-cell based datasets. Results Using a Cox-ph model-based method, six of the 93,961 G × G interactions were screened to form an optimal combination which, together with age, comprised the COVPRIG model. COVPRIG was designed for RNA-seq and microarray, respectively, and effectively identified patients at high risk of mortality. The predictive performance of COVPRIG was satisfactory, with area under the curve (AUC) ranging from 0.56 (CGGA693, RNA-seq, 6-month survival) to 0.79 (TCGA RNAseq, 18-month survival), which can be further validated by decision curves. Nomograms were constructed for individual risk prediction for RNA-seq and microarray-based cohorts, respectively. Besides, the prognostic significance of COVPRIG was also validated in GBM including the IDH mutant samples. Notably, COVPRIG was comprehensively evaluated and externally validated, and a systemic review disclosed that COVPRIG outperformed current validated models with an integrated discrimination improvement (IDI) of 6–16%. Moreover, integrative bioinformatics analysis predicted an essential role of METTL1+ neural-progenitor-like (NPC-like) malignant cell in driving unfavorable outcome. Conclusion This study provided a powerful tool for the outcome prediction for IDH wild-type GBM, and preliminary molecular underpinnings for future research.