Background: A major challenge in interpreting high-throughput multianalyte genomic data sets such as those produced by the ISPY clinical trials is data integration and interpretation within the context of biologically relevant pathways. To address this need, the data analysis tool PARADIGM (PAthway Recognition Algorithm using Data Integration on Genomic Models) was developed to infer the activities of genetic pathways by integrating any number of functional genomic data sets for a given patient sample into a pathway activity profile.
Methods: We used PARADIGM to integrate gene expression (Agilent 44K) and DNA copy number data (AFFY 22K and 330K MIP) from 133 ISPY-1 patients into pathway component activity levels for approximately 1400 curated signal transduction, transcriptional and metabolic pathways superimposed onto a single non-redundant ‘SuperPathway'. These pathway activities then become the substrate for statistical analyses to identify pathways characterizing different breast cancer subtypes, as well as those associated with recurrence and response to neoadjuvant chemotherapy within breast cancer subgroups. To identify subtype-specific pathway activities, we used ANOVA for initial feature filtering followed by Tukey analysis with Benjamini Hochberg multiple testing correction. For other binary outcome comparisons we used Mann-Whitney (2-sample Wilcoxon) analysis. PARADIGM results were corroborated with pathway enrichment analysis and filtered for significance.
Results: In agreement with breast cancer cell line and other prior studies, basal-like and triple negative cancers are dominated by upregulation of the FOXM1 and MYC/Max subnetworks and downregulation of the FOXA1/ER signal transduction pathway, the converse of the activity pattern seen in luminal breast cancers. These and other subtype associations pass stringent multiple testing corrected significance tests. Though an association study of recurrence over the entire patient cohort mostly yields pathways characteristic of basal-like tumors, alternative pathway associations emerge when subtypes are analyzed individually for outcome and significance tests are relaxed to include features that pass un-corrected Wilcoxon significance tests and also generate highly significant pathway enrichment scores. Subtype-specific drivers of recurrence and chemo-resistance supported by this level of evidence include ALK1/2 (TGFB-BMP) and p53 effector signaling for basals and Syndecan-1 and c-MYC for luminals. Chemo-sensitivity pathways, assessed by association with pCR and RCB1, appear to be subtype-specific as well, with HDAC class 1 signaling, LRP6-Wnt, and IRE1alpha chaperones dominating basal-like cancers and c-MYB activity dominating Her2+ cancers, whereas chemo-sensitivity of HR+Her2- cancers though rare appears to be driven by the DNA damage axis (BRCA/BARD1).
Conclusion: These and other similar analyses suggest that patients with TN or basal-like disease might benefit from the addition of ALK1 pathway inhibitors to treatment, whereas high risk HR+ patients might benefit from Syndecan-1 inhibitors. C-MYC/MAX inhibitors might benefit all high risk patients.