Figure 9 — Integrating machine learning and bioinformatics analysis to m6A regulator-mediated methylation modification models for predicting glioblastoma patients’ prognosis and immunotherapy response

Research Paper|Volume 15, Issue 10|pp. 4051–4070

Integrating machine learning and bioinformatics analysis to m6A regulator-mediated methylation modification models for predicting glioblastoma patients’ prognosis and immunotherapy response

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Figure 9.m6Ascore provided predictive outcomes for GBM patients receiving immunotherapies. (A, B) The difference between the IC50 values of Cisplatin and Gemcitabine in the samples of the high-risk group and the low-risk group; (C) The difference of TIDE score between samples of high-risk group and low-risk group; (D) Prediction of immunotherapy response results by using high and low groups of m6Ascore.