Research Paper Volume 16, Issue 14 pp 11248—11274
A stemness-based signature with inspiring indications in discriminating the prognosis, immune response, and somatic mutation of endometrial cancer patients revealed by machine learning
Figure 1. The clinical and molecular features associated with the stemness index (mRNAsi) in EC patients. (A) An overview of the association between mRNAsi and clinicopathological features of patients. Columns represented samples ranked by mRNAsi from low to high (top row), and rows represent known clinical and molecular characteristics associated with mRNAsi. (B) Heatmap of the association between TMB and somatic mutation status of the most popular biomarkers of EC. (C) Distribution of mRNAsi in different clinicopathological features including TCGA subtypes, stage, recurrence, peritoneal cytology, LNM, histology, grade, and tumor status displayed by boxplots. (D) Distribution of mRNAsi in different somatic mutation status of the biomarkers including TP53, TMB, TERT, PTEN, IDH1, EGFR, BRAF, ATRX.