Supplementary material: Linking Signaling Pathways to Transcriptional Programs in Breast Cancer



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Figure S9. Correlation of inferred and measured protein activities. Correlation of inferred protein activity and measured protein variation across tumors (left) and breast cancer cell lines (right); for cell line data, we predict protein activity using the TCGA affinity regression model and measure protein expression using the TCPA resource. (Basal-like (red), HER2 (pink), LumA (dark blue), LumB (light blue), for tumors; luminal (black) and basal (coral) for breast cancer cell lines.)




Figure S10. Correlation of inferred protein activities with drug responses in breast cancer cell lines. (A) Heatmap revealing correlations between inferred protein activities of cell lines (rows) and drug responses (columns). We identified two clusters of drugs from unsupervised analysis (corresponding targets given in parentheses): a group consisting mostly of cytotoxic drugs including Carboplatin, Cisplatin, and Docetaxel, but also Erlotinib (EGFR), shown in (B); and a group of targeted therapies including Tamoxifen (ESR1), 17-AAG (HSP90), Temsirolimus (mTOR), Rapamycin (mTOR), Lapatinib (EGFR, ERBB2), and GSK2119563 (PIK3CA), shown in (C). Interaction maps using the STRING resource are constructed for proteins whose inferred activities are highly correlated with drug sensitivity for group (B) and (C).



Figure S11. Transfer learning for drug response models. Prediction performance of elastic net models for each drug (shown in columns) predicting drug response for all drugs (shown in rows); performance reported as Spearman correlations, with values below 0.3 set to 0.



Figure S12. Growth inhibition (GI50) sensitivity profile of the breast cancer cell lines. Paclitaxel and AZD6244 show little variation in drug response (-log10 transformed GI50) compared to drugs with similar modes of action such as docataxel and temsirolimus, respectively.



Figure S13. Growth inhibition (GI50) sensitivity profile of the breast cancer cell lines to oxaliplatin, carboplatin and cisplatin. Cell lines are arranged from resistant to sensitive based on response to (A) oxaliplatin, (B) carboplatin and show lack of strong correlation of responses.


Figure S14. Growth inhibition (GI50) sensitivity profile of the breast cancer cell lines to GSK1120212 and AZD6244. Cell lines are arranged from resistant to sensitive based on response to (A) GSK1120212, (B) AZD6244 and show lack of strong correlation of responses.




Figure S15. Inferred protein activity predicts survival in patients with Luminal A breast cancers (TRANSBIG). Using inferred protein activity, a prognostic signature for overall survival was trained on the METABRIC discovery set. Kaplan–Meier survival curves reveals higher- versus lower-risk patients on the TRANSBIG datasets (Desmedt et al. 2007) using inferred protein activity (top panels) but not the corresponding gene expression (bottom panels) with (A) univariate Cox models for PGR, STAT5A and ERBB2 and (B) multivariate Cox models.


Figure S16. Inferred protein activity predicts survival in patients with Luminal A breast cancers (NKI). Using inferred protein activity, a prognostic signature for overall survival was trained on the METABRIC discovery set. Kaplan–Meier survival curves reveals higher- versus lower-risk patients on the NKI dataset (van de Vijver et al. 2002) using inferred protein activity (top panels) but not the corresponding gene expression (bottom panels) using (A) univariate Cox models for PGR, STAT5A and ERBB2 and (B) multivariate Cox models.



Figure S17. Inferring the impact of RB loss and (phospho) Rb inferred activity on E2F TF activity. (A) Tumors with deletion of RB1 have significatnly higher inferred E2F1 activity than wildtype tumors (Adj p-value < 10e-4, t-test; left), consistent with the role of hypo-phosphorylated Rb in inhibiting E2F transcriptional activators. Mutations of RB1 occur rarely in this cohort (right). (B) Protein expression variation of RB1 and its inferred protein activity are negatively correlated with E2F1 inferred TF activity, whereas phospho-Rb [pS807/S811] protein expression variation and inferred protein activity of phospho-Rb are positively correlated with E2F1 inferred TF activities, again consistent with the known biology. The correlations for inferred protein activity are stronger than for the original measured values.



Figure S18. Inferring the impact of TP53 loss and TP53 inferred activity on TP53 TF activity. (A) Tumors with deletion/mutation of TP53 have significantly lower inferred TP53 activity than wildtype tumors (p-value = 0.031, t-test). Amplification of TP53 occurs rarely in this training cohort. (B) Protein expression variation of TP53 is not correlated with TP53 inferred TF activity, whereas TP53 inferred protein activity is negatively correlated with inferred TF activity, consistent with known biology.


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