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. Author manuscript; available in PMC: 2022 Oct 15.
Published in final edited form as: Cancer Res. 2022 Apr 15;82(8):1518–1533. doi: 10.1158/0008-5472.CAN-21-1807

Figure 2. Wnt signature derived by integrative analysis of VCaP cells and clinical datasets predicts Wnt activities.

Figure 2.

A, Fold change of 47-geneset between Wnt-high versus Wnt-low status in clinical datasets and VCaP with APC knockdown (APCi) and WNT3a/RNF43 knockdown. Patients were stratified into Wnt-high (WH, top 10% Wnt activity score based on 124 gene set) and Wnt-low (WL, bottom 10% of the Wnt activity score) within TCGA (WH, n=55 vs WL, n=105), SU2C (WH, n=14 vs WL, n=14), WCPCDT (WH, n=14 vs WL, n=11) and FHCRC (WH, n=28 vs WL, n=16) datasets. B, C, GO biological processes or Pathway enrichment for 47-geneset with P value <0.01. D, Upstream prediction analysis. E-I, Scatter plots, with lines at median and interquartile ranges, show Wnt activity score distributions in cases with or without APC/CTNNB1 alterations in the following clinical datasets and one PDX dataset: E, TCGA (Rest, n=449; APC, n=10; CTNNB1, n=15); F, SU2C (Rest, n=118; APC, n=9, CTNNB1, n=4); G, WCPCDT (Rest, n=141; APC, n=3; CTNNB1, n=5); H, FHCRC (Rest, n=141; APC, n=3; CTNNB1, n=5); I, LuCaP PDX series (Rest, n=34; APC-deleterious stands for APC loss/truncation mutations, n=10; APC-nonsym is nonsynonymous mutations of unclear functional significance, n=4). Mann-Whitney tests, cutoff p<0.05. **** = p<0.0001, *** = p<0.001, ** = p<0.01, * = p<0.05, ns = no significance.