The online version of this article (https://doi.org/10.1186/s12885-017-3939-4) contains supplementary material, which is available to authorized users.
Shavira Narrandes and Shujun Huang are co-first authors.
Triple Negative Breast Cancers (TNBCs) lack the appropriate targets for currently used breast cancer therapies, conferring an aggressive phenotype, more frequent relapse and poorer survival rates. The biological heterogeneity of TNBC complicates the clinical treatment further. We have explored and compared the biological pathways in TNBC and other subtypes of breast cancers, using an in silico approach and the hypothesis that two opposing effects (Yin and Yang) pathways in cancer cells determine the fate of cancer cells. Identifying breast subgroup specific components of these opposing pathways may aid in selecting potential therapeutic targets as well as further classifying the heterogeneous TNBC subtype.
Gene expression and patient clinical data from The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) were used for this study. Gene Set Enrichment Analysis (GSEA) was used to identify the more active pathways in cancer (Yin) than in normal and the more active pathways in normal (Yang) than in cancer. The clustering analysis was performed to compare pathways of TNBC with other types of breast cancers. The association of pathway classified TNBC sub-groups to clinical outcomes was tested using Cox regression model.
Among 4729 curated canonical pathways in GSEA database, 133 Yin pathways (FDR < 0.05) and 71 Yang pathways (p-value <0.05) were discovered in TNBC. The FOXM1 is the top Yin pathway while PPARα is the top Yang pathway in TNBC. The TNBC and other types of breast cancers showed different pathways enrichment significance profiles. Using top Yin and Yang pathways as classifier, the TNBC can be further subtyped into six sub-groups each having different clinical outcomes.
We first reported that the FOMX1 pathway is the most upregulated and the PPARα pathway is the most downregulated pathway in TNBC. These two pathways could be simultaneously targeted in further studies. Also the pathway classifier we performed in this study provided insight into the TNBC heterogeneity.
Additional file 1: FDRs of 191 Yin . 133 Yin pathways were selected with PDF < 0.05 (XLS 73 kb)12885_2017_3939_MOESM1_ESM.xls
Additional file 2: P-values of 176 Yang pathways among BC subtypes. 71 Yang pathways were selected with p < 0.05 (XLS 69 kb)12885_2017_3939_MOESM2_ESM.xls
Additional file 3: Other results: Figure S1. Yin pathway significant score profiling among LumA, LumB, Her2, TNBC breast cancer subtype using TCGA data. Figure S2. Yang pathway significant score profiling among LumA, LumB, Her2, TNBC breast cancer subtype using TCGA data. Figure S3. Yin Yang pathway classifier for TNBCs. Figure S4. Pathway classifier comparison. Figure S5. YMR scores of FOXM1 and PPARa pathway among Breast caner cell lines. Figure S6. FOXM1 and PPARa YMR model for GSE58812 data set. Figure S7. FOXM1 and PPARa YMR model for GSE25066 data set. (PDF 1224 kb)12885_2017_3939_MOESM3_ESM.pdf
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