Frontiers in Oncology (May 2022)

Calcium-Related Gene Signatures May Predict Prognosis and Level of Immunosuppression in Gliomas

  • Peidong Liu,
  • Peidong Liu,
  • Peidong Liu,
  • Yu Li,
  • Yu Li,
  • Yiming Zhang,
  • Yiming Zhang,
  • John Choi,
  • Jinhao Zhang,
  • Jinhao Zhang,
  • Guanjie Shang,
  • Guanjie Shang,
  • Bailiang Li,
  • Ya-Jui Lin,
  • Ya-Jui Lin,
  • Laura Saleh,
  • Liang Zhang,
  • Liang Zhang,
  • Li Yi,
  • Li Yi,
  • Shengping Yu,
  • Shengping Yu,
  • Michael Lim,
  • Xuejun Yang,
  • Xuejun Yang

DOI
https://doi.org/10.3389/fonc.2022.708272
Journal volume & issue
Vol. 12

Abstract

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Gliomas are the most common primary brain cancer. While it has been known that calcium-related genes correlate with gliomagenesis, the relationship between calcium-related genes and glioma prognosis remains unclear. We assessed TCGA datasets of mRNA expressions with differentially expressed genes (DEGs) and enrichment analysis to specifically screen for genes that regulate or are affected by calcium levels. We then correlated the identified calcium-related genes with unsupervised/supervised learning to classify glioma patients into 2 risk groups. We also correlated our identified genes with immune signatures. As a result, we discovered 460 calcium genes and 35 calcium key genes that were associated with OS. There were 13 DEGs between Clusters 1 and 2 with different OS. At the same time, 10 calcium hub genes (CHGs) signature model were constructed using supervised learning, and the prognostic risk scores of the 3 cohorts of samples were calculated. The risk score was confirmed as an independent predictor of prognosis. Immune enrichment analysis revealed an immunosuppressive tumor microenvironment with upregulation of checkpoint markers in the high-risk group. Finally, a nomogram was generated with risk scores and other clinical prognostic independent indicators to quantify prognosis. Our findings suggest that calcium-related gene expression patterns could be applicable to predict prognosis and predict levels of immunosuppression.

Keywords