An amino acid metabolism‐related gene expression‐based risk signature can better predict overall survival for glioma

Abstract

Metabolic reprogramming has been proposed to be a hallmark of cancer. Aside from glycolytic pathway, the metabolic changes of cancer cells primarily involve amino acid metabolism. However, the characteristic of amino acid metabolism‐related gene set has not been systematically profiled in glioma. In this study, RNA sequencing expression data from 309 patients in the Chinese Glioma Genome Atlas database were included as training set, while another 550 patients with the Cancer Genome Atlas database were used to validate. Consensus clustering of the 309 samples yielded two robust groups. Compared with Cluster1, Cluster2 correlated with a better clinical outcome. Then, we developed an amino acid metabolism‐related risk signature for glioma. Our results showed that patients in the high‐risk group had dramatically shorter overall survival than low‐risk counterparts in any subgroup, stratified by IDH and 1p/19q status based on the 2016 World Health Organization classification guidelines. The 30‐gene signature showed the better prognostic value than the traditional factors "age" and "grade" by analyzing the receiving operator characteristic curve, with areas under curve of 0.966, 0.692, 0.898 and 0.975, 0.677, 0.885 for 3‐ and 5‐year survival, respectively. Moreover, univariate and multivariable analysis shows that the 30‐gene signature was an independent prognostic factor for glioma. Furthermore, Gene Ontology analysis and Gene Set Enrichment Analysis illustrated that the tumors with high risk score correlated with various aspects of the malignancy of glioma. In summary, we demonstrated a novel amino acid metabolism‐related risk signature for predicting prognosis for glioma.

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