fig2

Cancer-associated fibroblasts (CAFs) based model reveals potential for predicting bladder cancer patients' prognoses and immunotherapy responses

Figure 2. (A and B) The ssGSEA algorithm was used to divide the bladder cancer patients into low- and high-CAFs groups; (C) The heatmap demonstrated the different distribution of immune-related cells and fibroblasts in bladder cancer cohort; (D) The different immune-related scores between low- and high-CAFs groups; (E) The different expression levels of HLA-related genes between low- and high-CAFs groups; (F) The different expression level of immune-related cells between low- and high-CAFs groups. *represents a statistical significance level where P ≤ 0.05. **represents a statistical significance level where P ≤ 0.01. ***represents a statistical significance level where P ≤ 0.001. ns represents no statistical significance.

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

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