fig5

Machine learning-based integration of omics and clinical data reveals an N-glycan biosynthesis signature predictive of the outcome in low-grade glioma: an <i>in silico</i> study

Figure 5. Association of Lasso Model-Predicted Risk Score with Treatment Response, Tumor Recurrence, and Immune Infiltration. (A) Boxplot illustrating the distribution of risk scores in differential responses to the first treatment. (B-D) Boxplots presenting the distribution of risk scores in primary and recurrent tumors in TCGA (B), CGGA325 (C), and CGGA693 (D) datasets. (E) Heatmap showing Spearman correlation of risk scores with immune infiltration in TCGA and CGGA datasets. Significance levels: *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

Journal of Cancer Metastasis and Treatment
ISSN 2454-2857 (Online) 2394-4722 (Print)

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Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/