Fig. 2: Loss of IRE1α inhibits PCa tumor growth and activates the expression of anti-tumor immunity-related genes in the TME.

A, B Myc-CaP IRE1α KO cell lines were generated by CRISPR-Cas9 genome editing. Cells were subcutaneously injected into two flanks of FVB mice. A Tumor sizes were measured at the indicated time points for WT (n = 4 mice, 7 tumors) and three independent IRE1α KO clones - KO1 (n = 4 mice, 7 tumors), KO2 (n = 5 mice, 10 tumors) and KO3 (n = 5 mice, 10 tumors). B Same as in (A) but tumor weights were measured at the end of the experiment. C IRE1α WT (n = 3 mice, 5 tumors) or KO clones 1–3 (n = 3 mice, 6 tumors per KO clone) of Myc-CaP cells grown as xenografts in nude mice. D, E Tumor samples were collected at the end of the experiment presented in Fig. 2A, RNA was isolated and subjected to RNA-seq analysis. KO clones (n = 3 mice, 3 tumors per KO clone) were compared with WT (n = 4 mice, 4 tumors) samples. GSEA for (D) downregulated or (E) upregulated genes in IRE1α KO tumors is presented. Note that for several processes, the q-value equals 3; this is because the GSEA tool computes 3 as the maximum possible q-value. F, G Enrichment plots for the indicated datasets enriched in GSEA analysis related to (F) innate or (G) adaptive immunity are presented. Mean ± standard error for two-tailed student’s t-test is presented for Figure (A) (IRE1α WT vs KO #1 (p = 0.0008), vs KO #2 (p = 0.0007), vs KO #3 (p = 0.003), for Figure (B) (IRE1α WT vs KO #1 (p = 3.4E-05), KO #2 (p = 0.001), vs KO #3 (p = 0.008), and for Figure C (WT vs KO #3, p = 0.87); **p < 0.01, ***p < 0.001, n.s, non-significant.