Development of an Immune Infiltration-Related Prognostic Scoring System Based on the Genomic Landscape Analysis of Glioblastoma Multiforme

Frontiers in Oncology
Guihua Tang, Wen Yin

Abstract

Introduction: Glioblastoma multiforme (GBM) is the most common deadly brain malignancy and lacks effective therapies. Immunotherapy acts as a promising novel strategy, but not for all GBM patients. Therefore, classifying these patients into different prognostic groups is urgent for better personalized management. Materials and Methods: The Cell type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm was used to estimate the fraction of 22 types of immune-infiltrating cells, and least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed to construct an immune infiltration-related prognostic scoring system (IIRPSS). Additionally, a quantitative predicting survival nomogram was also established based on the immune risk score (IRS) derived from the IIRPSS. Moreover, we also preliminarily explored the differences in the immune microenvironment between different prognostic groups. Results: There was a total of 310 appropriate GBM samples (239 from TCGA and 71 from CGGA) included in further analyses after CIBERSORT filtering and data processing. The IIRPSS consisting of 17 types of immune cell fractions was constructed in TCGA cohort, the patients were successfully...Continue Reading

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Citations

Apr 3, 2020·Journal of Neuro-oncology·Jacky T YeungDanielle F Miyagishima
Dec 19, 2020·Cancer Treatment and Research Communications·Sai Batchu
Sep 21, 2021·Frontiers in Immunology·Saadia Ait SsiAbdallah Badou

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Methods Mentioned

BETA
surgical resection
fluorescence-activated cell sorting
flow cytometry

Software Mentioned

GSEA
R
LASSO
CIBERSORT

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