Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Nomogram With a Novel Microenvironment Signature Is Systematically Constructed and Validated to Predict the Survival Rate of Glioma Patients.

Version 1 : Received: 15 December 2020 / Approved: 16 December 2020 / Online: 16 December 2020 (11:01:08 CET)

How to cite: Li, T.; Chen, Y.; Chen, Y.; Liu, G.; Zou, S.; Yang, A.; Liu, Y.; Fan, J. Nomogram With a Novel Microenvironment Signature Is Systematically Constructed and Validated to Predict the Survival Rate of Glioma Patients.. Preprints 2020, 2020120404 (doi: 10.20944/preprints202012.0404.v1). Li, T.; Chen, Y.; Chen, Y.; Liu, G.; Zou, S.; Yang, A.; Liu, Y.; Fan, J. Nomogram With a Novel Microenvironment Signature Is Systematically Constructed and Validated to Predict the Survival Rate of Glioma Patients.. Preprints 2020, 2020120404 (doi: 10.20944/preprints202012.0404.v1).

Abstract

Glioma accounts for the highest proportion of primary intracranial malignant tumors. Microenvironment enormously influences the process of glioma progression. Our study is to establish an individualized prognostic nomogram for glioma patients with microenvironment signature. Glioma samples of Chinese Glioma Genome Atlas (CGGA) were grouped by the immune and stromal score based on ESTIMATE algorithm. Microenvironment-related genes (MRGs) in glioma were analyzed by R. To determine the best prognostic correlation genes, univariate and multivariate Cox regression analysis were used to analyze MRGs. Use the selected genes (CHI3L1, SOCS3, SLC47A2, COL3A1, SRPX2 and SERPINA3), we established the prognostic risk score model (microenvironment signature) and validated it. Gene Set Enrichment Analysis (GSEA) showed that the high-risk group was mainly enriched in immune and stromal function KEGG pathways. Finally, the nomogram was constructed and evaluated. The receiver operating characteristic (ROC) curve, Calibration plots and decision curve analysis (DCA) of training and validation set indicated the excellent predictive performance of nomogram. In conclusion, the 6-gene microenvironment signature can not only provide directions for the basic research of glioma, but also can be included as an independent prognostic index in nomogram for individual prediction to guide clinical treatment.

Subject Areas

microenvironment signature; prognostic model; glioma; CGGA; ESTIMATE algorithm

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