Figure 1.
PTEN re-expression regulates transcription factor expression and activity in PTEN-inducible PtenΔloxp/Δloxp MEFs.
(A) Schematic illustration of rationale and approach used in this study. To identify PTEN-controlled TFs, their activities (TFAs) in PTEN inducible system were first derived from expression of their target genes by NCA. The perturbed TFs were then examined further in mouse models and human cancers. (B) Immunoblot showing PTEN expression levels at 0, 1, and 2 days after treatment with the indicated concentration of Doxycycline in PtenΔloxp/Δloxp MEFs. Isogenic WT cells (PtenL/L) were used as a positive control. (C) Heatmaps showing the changes of expression and activity (TFA) of transcription factors in fold and log10 transformed p-value of the z-test, respectively, caused by PTEN re-expression for 1 day (1/0) or 2 days (2/0).
Figure 2.
PTEN re-expression downregulates activities of c-MYC and LEF1 in PTEN-inducible PC3 cells.
(A) Immunoblot showing PTEN expression levels under Doxycycline induction. (B) Bar graphs showing fold changes of c-MYC and LEF1 mRNA expression by qPCR analysis. (C and D) Bar graphs showing the target gene expression of c-MYC and LEF1 by qPCR analysis, respectively. *p<0.05 and **p<0.01.
Figure 3.
PTEN-regulated TFAs are significantly increased in murine prostate cancer models in vivo.
(A) Heatmap showing changes of PTEN-regulated TFAs in PTEN inducible MEFs (PTEN null compared to PTEN re-expression or PTEN WT) and murine prostate cancer models (compared to WT control mice; Rapa: Rapamycin treatment). TFAs regulated by PTEN/AKT/mTOR pathway are marked in bold. TFAs exhibit discordant regulation between c-Myc and the PTEN/AKT/mTOR pathway are marked by *. The purple and green asterisks indicate Myc-activating and suppressing TFs respectively. (B) Triangle diagram summarizing the TFAs regulated by PTEN, AKT/mTOR and/or c-MYC.
Figure 4.
PTEN-controlled TFAs predict PTEN status in human cancers.
Unsupervised clustering analysis, based on PTEN-controlled TFAs, was used to classify human tumor samples. (A) In prostate cancer, group 1 is largely composed by samples with PTEN copy number changes (CN, red) and lymph node metastases (LN met, pink); Group 2 are primary cancer samples (light blue) with normal PTEN karyotype (blue) that are separated from most of normal prostate tissues (white). TFAs that are significantly altered between group 1 and group 3 are mark by **, p<0.001. The heatmap was plotted based on relative changes to the respective average TFAs of normal samples. (B) In breast cancer, group 1 is mostly comprised of samples with PTEN-negative status (red) identified by immunohistochemistry (IHC). The majority of the samples in group 3 have positive PTEN status (blue), while group 2 includes both positive and negative PTEN samples. (C) In brain tumors, most samples in group 1 are associated with PTEN negative status (red). The PTEN negative subgroup is also correlated with higher tumor grade (green for grade 3 and purple for 4, respectively).
Figure 5.
Enhanced robustness of TFA-based signatures in predicting PTEN status in human cancer.
(A) The Kaplan-Meier survival curves of patients with brain tumors stratified according to PTEN-controlled TFA and IHC analyses. (B) Log10 transformed p-values of the χ2 test evaluating the association of PTEN status with the hierarchical clustering-determined groups of human tumors. Clustering results are based on PTEN-controlled TFAs (red; Figure 3), prostate cancer-related TFAs (blue), TFA-based (gold) and gene expression-based (green) signatures derived from PTEN IHC data in breast tumors. When three major clusters are observed in prostate and breast cancers, the χ2 tests are performed to associate different PTEN status in group 1 and groups 2 plus 3.
Figure 6.
Subsets of PTEN-controlled TFAs preferentially function in specific types of tumors.
(A) t-test p-values comparing TFAs of the subgroups based on PTEN status and clustering results as shown in Figure 5 in three tumor types. In the t-tests performed on of prostate and breast cancers, PTEN positive samples in group 3 were used as the PTEN positive functional status, the PTEN negative samples in group 1 as the PTEN negative functional status. Similarly, in brain tumor PTEN IHC positive samples in group 2 and PTEN IHC negative samples in group 1 were selected for representing PTEN positive and negative functional status respectively. The red line highlighted the 6 TFAs significantly (p<0.05) altered between tumor subgroups in three tumor types. (B) Venn diagram summarizing the overlap of the TFAs that contribute to the discrimination of tumor subgroups with different PTEN status in different tumor types. (C–D) Heatmap of the absolute Pearson correlation coefficients between NCA-inferred TF activity profiles across the tumor samples from prostate (C), breast (D) and brain (E) cancers, indicating groups of co-active transcription factors may function together.